road runoff harvesting in the drylands of sub-saharan africa · road runoff harvesting in the...
TRANSCRIPT
I
Road Runoff Harvesting in the
Drylands of Sub-Saharan Africa:
Its Potential for Assisting Smallholder Farmers in
Coping with Water Scarcity and Climate Change,
Based on Case Studies in Eastern Province, Kenya
BEN KUBBINGA
FREE UNIVERSITY / VRIJE UNIVERSITEIT, AMSTERDAM
FACULTY OF EARTH AND LIFE SCIENCES
A THESIS SUBMITTED TO THE INSTITUTE OF ENVIRONMENTAL SCIENCES IN
PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER IN
SCIENCE IN ENVIRONMENT AND RESOURCE MANAGEMENT (SPECIALISATION
BIODVERSITY AND ECOCYSTEM SERVICES)
Supervisors:
Dr Will Critchley, Center for International Cooperation (CIS-VU), Amsterdam
Dr Jetske Bouma, Institute for Environmental Studies (IVM-VU), Amsterdam
Dr Maimbo Malesu, World Agroforestry Centre (ICRAF), Nairobi
Alex Oduor, World Agroforestry Centre (ICRAF), Nairobi
I
Acknowledgements
This thesis is the product of fieldwork carried out in Kenya and a literature study in The Netherlands.
Many people have helped me in making these activities possible.
First of all, I would like to thank my supervisors for their guidance and patience. I am grateful to Dr Will
Critchley for his suggestion to focus my thesis on the topic of road runoff harvesting, as well as for his
continuous positive feedback despite the many delays in preparing this thesis. I would like to thank Dr
Jetske Bouma for her critical and constructive comments when I presented the first results of my
fieldwork and for her further support during the writing. My fieldwork would not have been possible
without the kind hospitality and expertise offered by Dr Maimbo Malesu and Alex Oduor, who have
dedicated much of their time in visiting the different road runoff harvesting sites with me.
I am grateful for the warm welcome and support provided by Ms Hellen Ochieng and Ms Rose
Onyango during my stay at ICRAF. I would also like to thank the staff of the ICRAF library for their kind
help. I further appreciate Dr Stephen Ngigi’s help in acquiring one of his books (Ngigi, 2003a) and his
PhD thesis.
During my field visits I have been accompanied by Ms Rose Mueni. I am very much indebted to her for
her nice company and her willingness to translate from Kiswahili or Kikamba to English, and vice versa
– which was most useful both during interviews and in our free time. I am particularly obliged to all the
farmers who have been so kind to host me from a couple of hours to a few days. These farmer
innovators are: Mr Muindu Musyoka, Mr Mwema Maswili, Mr Samuel Mweu Maingi, a neighbour of Mr
Samuel Maingi, Mr David Kyula and Mr Sammy. Though they are not part of the case studies, I would
also like to give thanks to Mr Daniel Kyalo and Mr Patrick Mwendwa, whose farms I have visited
during my stay at Mr Musyoka’s farm in Mwingi District.
At the Kenya Rainwater Association, I have been welcomed by Ms Katie Allan. I greatly appreciate her
assistance in providing information on the activities of KRA and her help in giving me access to the
KRA library. I would also like to thank Ms Elizabeth Khaka – the ‘grandmother of water harvesting in
Africa’ – for her availability to discuss the activities of UNEP in the field of water harvesting. On the
same ‘family’ note, I was pleased to meet Mr Erik Nissen-Petersen – the ‘grandfather of water
harvesting in Africa’ – who kindly provided me with a hard copy of his book ‘Water from roads’
(Nissen-Petersen, 2006).
Furthermore, I would like to warmly thank my friends Adriaan Tas, Angela Kronenburg and their
children for hosting me during my stay in Nairobi.
Last but not least, I am very thankful to Sanne Jansen, Peter de Lange and Alba Martinez Salas for
proofreading parts of this thesis and for their useful suggestions.
II
Preface
This thesis is the final part of the MSc programme “Environment and Resource Management”, ERM in
short, which I followed during the period 2010-2011. This programme is provided by the Institute for
Environmental Studies (IVM) of the Vrije Universiteit (VU) in Amsterdam. I made the decision to carry
out this short research project during the one-month course on Sustainable Land Management (SLM),
provided by Dr. Will Critchley of the Centre for International Cooperation (CIS). The SLM course has
been one of the most inspiring courses of the ERM programme, in particular because of the many
practical real-life examples of SLM technologies and approaches that were given. I have been given
the chance to go to Kenya for fieldwork, under the local supervision of Dr Maimbo Malesu and Alex
Oduor, two experts in rainwater harvesting at the World Agroforestry Centre based in Nairobi. This
chance I have taken with both hands. My fieldwork in the countryside of Eastern Kenya has allowed
me to get to know some of the most humble, hospitable and kind people I know. Though the outcomes
of this study are limited in scope, I hope they can contribute to the further promotion of the various
forms of road runoff harvesting amongst smallholder farmers in Kenya and the rest of sub-Saharan
Africa.
Summary
Water scarcity is a major challenge for smallholder farmers in the drylands of sub-Saharan Africa,
where agriculture is predominantly rainfed. Collecting runoff from road surfaces and culverts may help
some of these farmers in coping with the unreliable and erratic rainfall. Road runoff harvesting (RRH),
as this technology is called, is already practiced by several farmers for instance in Kenya, Tanzania
and Uganda. The objective of this thesis was twofold: 1) to evaluate the performance of farms that use
RRH, and 2) to assess the potential for up-scaling RRH in the rest of sub-Saharan Africa. Two case
studies in Kenya were selected prior to this study, and four other sites were visited as well during the
fieldwork. The WOCAT Questionnaire on SLM Technologies was used as a basic framework for
collecting data on the performance. The data were further analysed using the TEES-test, which
focuses on the Technical performance, Economic viability, Environmental friendliness and Social
acceptance of a technology. The outcomes suggest that the RRH systems perform well – farmers are
overall positive about the impacts of their RRH system. Small technical improvements could be made
in all cases. The establishment costs are a major economic constraint, yet the benefits seem to
outweigh these and other (social) costs. Negative environmental effects have not been observed. The
RRH systems of the two case studies are based on both local knowledge and expertise from
development agents. Assessment of the potential for up-scaling RRH was done with data on the size
of drylands of each country in sub-Saharan Africa, combined with road density data per country and
informed estimates of the road surface and number of culverts per kilometre of road; population
density levels per dryland area (arid, semi-arid and dry sub-humid) were used as a proxy to calculate
the road density for each area. The results show a large potential for RRH: some 2.2 million
households (including both smallholder farmers and pastoralists) could potentially benefit from an
estimated 0.5 cubic kilometre of road runoff, either through runoff farming or by storing the runoff for
later use (for livestock or supplemental irrigation of crops). The findings are in line with the sporadic
yet promising information about RRH technologies in current (and often grey) literature. This study
highlights the importance of further research on the (technical, economic, environmental and social)
costs and benefits of RRH systems, involving more farms as well as a combination of success stories
and failures. Detailed GIS-mapping of regional and local opportunities for RRH would be very helpful
to estimate the real potential of this technology. Based on the present assessment, it is recommended
that national and local administrations, who deal with infrastructure, agriculture, environment or water,
as well as development agents, consider the incorporation of RRH into their policies, programmes and
activities.
III
Contents
Acknowledgements .............................................................................................................. I
Preface ................................................................................................................................. II
Summary .............................................................................................................................. II
Glossary ............................................................................................................................... 1
List of Figures...................................................................................................................... 2
List of Tables ....................................................................................................................... 3
List of Boxes ........................................................................................................................ 3
Acronyms and Abbreviations ............................................................................................. 4
1. Introduction .................................................................................................................. 5
1.1 Problem analysis ........................................................................................................ 5
1.2 Research questions ................................................................................................... 7
1.3 Thesis structure ......................................................................................................... 7
2. Road runoff harvesting in sub-Saharan Africa ........................................................... 8
2.1 The concept of road runoff harvesting ........................................................................ 8
2.2 Runoff harvesting with roadside drain .......................................................................10
2.3 Runoff harvesting through a culvert ...........................................................................11
2.4 Benefits of road runoff harvesting for smallholder farmers ........................................13
2.5 Upstream-downstream impacts of road runoff harvesting .........................................14
2.6 Adoption by other farmers .........................................................................................15
2.7 Impacts of up-scaling ................................................................................................17
3. Methods .......................................................................................................................18
3.1 Analysis framework for case studies .........................................................................18
3.2 Selection of case studies ..........................................................................................20
3.3 Study area ................................................................................................................21
3.4 Fieldwork and interviews ...........................................................................................21
3.5 Methodology for determining the potential for up-scaling road runoff harvesting .......22
4. Results .........................................................................................................................27
4.1 Case study 1: Muindu Musyoka ................................................................................27
4.2 Case study 2: Mwema Maswili ..................................................................................34
4.3 Four other sites in Machakos District ........................................................................40
4.4 Suitable roads and culverts in sub-Saharan Africa ....................................................44
IV
5. Analysis .......................................................................................................................48
5.1 Technical performance ..............................................................................................48
5.2 Economic viability .....................................................................................................50
5.3 Environmental friendliness ........................................................................................51
5.4 Social acceptance .....................................................................................................52
5.5 Factors that may influence the adoption of road runoff harvesting.............................53
5.6 Sensitivity analysis of the sub-Saharan Africa-wide assessment ...............................55
6. Discussion ...................................................................................................................57
6.1 Addressing the research questions ...........................................................................57
6.2 Performance of road runoff harvesting sites ..............................................................57
6.3 Potential for up-scaling road runoff harvesting in sub-Saharan Africa .......................58
6.4 Experience of using WOCAT and the TEES-test .......................................................59
6.5 Refining the sub-Saharan Africa-wide suitability assessment ....................................60
7. Conclusions .................................................................................................................61
8. Recommendations ......................................................................................................62
8.1 Further research .......................................................................................................62
8.2 Policy-making............................................................................................................62
8.3 Development and extension work .............................................................................63
References ..........................................................................................................................64
Annex I Categorisation of WOCAT data ...........................................................................68
1
Glossary
adoption / uptake the process of copying a technology by other farmer(s)
berkad type sub-surface water tank used in Somalia
caag external catchment system for harvesting water from ephemeral streams (Kenya)
catchment area used for collecting (road) runoff
cultivated lands lands that are used for crop production or agroforestry (both rainfed and irrigated)
cultivation area area where runoff is applied for productive purposes
culvert conduit (pipe or other structure) running underneath a road constructed for drainage
drylands arid, semi-arid and dry sub-humid areas
external catchment catchment that lies outside the farm land (generally longer than 30 m)
fanya chini terraces formed by channels along the contours of a hill that have been created by throwing soil down (chini) hill (Kiswahili)
fanya juu terraces formed by channels along the contours of a hill that have been created by throwing soil down (juu) hill (Kiswahili)
hafir natural depression/water pan in the landscape (Kenya)
hybrid knowledge local/traditional and scientific knowledge combined
majaluba retention basin (Tanzania)
microcatchment catchment that lies within-field (generally less than 30 m long)
rangelands lands used for nomadic and sedentary livestock raising
road runoff harvesting the collection of runoff from roads and road sides for productive purposes
shamba farm field (Kiswahili)
T-basins basins which trap runoff from footpaths and roads; crop are grown on the interconnected (at the base) T-shaped bunds
technique a single measure (e.g. digging a trench)
technology a set of techniques plus the knowledge and skills to use these techniques (e.g. water harvesting)
up-scaling the process of increasing the rate of adoption by farmers
water harvesting the collection of runoff for productive purposes
2
List of Figures
Figure 1. Projected reduction of plant growing periods in sub-Saharan Africa ....................... 5
Figure 2. The principle of rainwater harvesting ...................................................................... 8
Figure 3. Runoff harvesting with roadside drains: three basic forms .....................................10
Figure 4. Runoff harvesting through a culvert: two basic forms .............................................12
Figure 5. Picture of a gully formed at the outlet of a culvert ..................................................13
Figure 6. Map showing the location of the visited farms ........................................................20
Figure 7. Methodology used to determine the suitability of roads for runoff harvesting .........22
Figure 8. Schematic depiction of runoff flows on Muindu Musyoka’s farm ............................27
Figure 9. Pictures of Muindu Musyoka showing how runoff is redirected to his farm .............28
Figure 10. Schematic overview of the terraces of Muindu Musyoka ......................................29
Figure 11. Catchment and cultivation area of Muindu Musyoka highlighted on a
satellite image ....................................................................................................30
Figure 12. Muindu Musyoka showing dried maize in a calabash at his homestead ...............33
Figure 13. Schematic overview of the Mwema Maswili’s farm ..............................................34
Figure 14. Roadside drain and fanya chini channel on the farm of Mwema Maswili ..............35
Figure 15. Pond of Mwema Maswili ......................................................................................36
Figure 16. Schematic overview of three of the four additional farms .....................................41
3
List of Tables
Table 1. Comparison of yields obtained with and without road runoff harvesting ................ 14
Table 2. Approaches and tools used to analyse each of the TEES-test criteria. ................. 18
Table 3. Methodology used to categorise data from the WOCAT Questionnaire on SLM
Technologies ........................................................................................................ 19
Table 4. Timing of field visits and type of interviews ........................................................... 21
Table 5. Characteristics of arid, semi-arid and dry sub-humid areas. ................................. 23
Table 6. Proportion of rangelands, cultivated lands, urban areas and other areas in the
drylands of the world. ........................................................................................... 24
Table 7. Summary of assumptions made to determine the potential for up-scaling road
runoff harvesting ................................................................................................... 26
Table 8. Yields and sales of Muindu Musyoka during the period 1998-2011 ...................... 32
Table 9. Length of total road network in the drylands ......................................................... 45
Table 10. Estimates per country of number of culverts, potential runoff volumes and
number of households that could benefit from road runoff .................................... 46
Table 11. Estimates per country of road surface, potential cultivation area (in cultivated
lands), potential runoff volumes and number of households that could benefit
from road runoff .................................................................................................... 47
Table 12. Overview of rainwater harvesting elements on the six farms ................................ 48
Table 13. Description of the technical performance of each site. .......................................... 49
Table 14. Benefit-costs analysis of the road runoff harvesting systems of Musyoka and
Maswili ................................................................................................................. 50
Table 15. Environmental impacts and related Ecosystems Services of the studied road
runoff harvesting sites .......................................................................................... 52
Table 16. Adoption rates and reasons for successful or unsuccessful adoption ................... 53
Table 17. Overview of potential adoption factors derived from data gathered at the six
farms .................................................................................................................... 54
Table 18. Sensitivity of the outcomes of the sub-Saharan Africa-wide assessment .............. 56
Table 19. Structural adjustments that could make road runoff harvesting structures more
efficient. ................................................................................................................ 57
List of Boxes
Box 1. Ecosystem Services typical of drylands in Africa ........................................................ 6
Box 2. Methods for calculating the potential amount of road runoff and the cultivation area
size based on rainfall depth, runoff efficiency and crop water requirements ................ 9
Box 3. Road runoff harvesting in other parts of the world .....................................................16
4
Acronyms and Abbreviations
AMCOW African Ministerial Conference on Water
C/CA ratio Catchment/Cultivation Area ratio
E efficiency factor
ETc crop water requirements
FAO Food and Agriculture Organization
GHA Greater Horn of Africa
GHARP Greater Horn of Africa Rainwater Partnership
GIS Geographic Information Systems
GOK Government of Kenya
ha hectare (100 by 100 m = 10,000 m2 = 2.47105 acre)
ICRAF World Agroforestry Centre
IPA Issuing Paying Agent
IWRM Integrated Water Resources Management
K runoff coefficient
kc ‘crop’ factor
MEA Millennium Ecosystem Assessment
O&M Operation and Maintenance
Pd design rainfall
PET potential evapotranspiration
PFI Promoting Farmer Innovation
QT WOCAT’s Questionnaire on SLM Technologies
RRH road runoff harvesting
SLM Sustainable Land Management
SSA sub-Saharan Africa
UNDP United Nations Development Programme
UNEP United Nations Environmental Programme
WOCAT World Overview of Conservation Approaches and Technologies
WVI World Vision International
1. Introduction
1.1 Problem analysis
Water scarcity is a major problem for smallholde
predominantly rainfed (e.g. Falkenmark, 1989; Molden,
population depend for more than three
Particularly in Africa’s drylands, where
erratic rainfall is a challenge. Drylands comprise, in the context of this thesis,
sub-humid zones of sub-Saharan Africa
the Green Revolution (IUCN, 2007)
(FAO, 1992). Lack of basic infrastructure is
et al., 2009). As this situation is
with the limited availability of water for crop production.
In addition to the weather-related
uncertainties. As the majority of farmers are subsistence f
food security is directly linked
vulnerability, the economic situation (e.g. high market volatility) and social context (e.g. conflicts)
countries can greatly impinge on
Figure 1. Projected reduction of plant growing periodTwo scenarios (left and right map) showing which areas will see a reduction in plant growing period of over 20% until
2050 (Thornton et al., 2006). The scenarios are based on two different models. The yellow areas (LGA) depict the
rangelands, the green areas (MRA) are used for rainfed mixed systems with crops and livestock. (For a definition of
rangelands and cultivated lands see Chapter 3.5)
5
Water scarcity is a major problem for smallholder farmers in sub-Saharan Africa, where agriculture is
Falkenmark, 1989; Molden, 2007). At the country level, 40 to 70% of the rural
population depend for more than three-quarters on on-farm resources for their income (IFAD, 2011).
drylands, where some 325 people live (Murray et al., 1999)
. Drylands comprise, in the context of this thesis, the
Saharan Africa. Irrigation has not seen the same success as in South Asia under
(IUCN, 2007) and is restricted to less than 5% of the agricultural
infrastructure is one of reasons for the failure of irrigation schemes (
likely to stay the same, solutions are required that help farmers to cope
of water for crop production.
related impacts on agricultural production, smallholder farmers also
of farmers are subsistence farmers with an income below the poverty line
to local crop production (IFAD, 2010). As a result of
, the economic situation (e.g. high market volatility) and social context (e.g. conflicts)
impinge on farm households (Ibid.).
plant growing periods in sub-Saharan Africa Two scenarios (left and right map) showing which areas will see a reduction in plant growing period of over 20% until
, 2006). The scenarios are based on two different models. The yellow areas (LGA) depict the
as (MRA) are used for rainfed mixed systems with crops and livestock. (For a definition of
rangelands and cultivated lands see Chapter 3.5)
Saharan Africa, where agriculture is
At the country level, 40 to 70% of the rural
farm resources for their income (IFAD, 2011).
, 1999), the unreliable and
the arid, semi-arid and dry
has not seen the same success as in South Asia under
agricultural produce in Africa
for the failure of irrigation schemes (Svendsen
that help farmers to cope
impacts on agricultural production, smallholder farmers also face other
an income below the poverty line,
As a result of the farmers’
, the economic situation (e.g. high market volatility) and social context (e.g. conflicts) of some
Two scenarios (left and right map) showing which areas will see a reduction in plant growing period of over 20% until
, 2006). The scenarios are based on two different models. The yellow areas (LGA) depict the
as (MRA) are used for rainfed mixed systems with crops and livestock. (For a definition of
6
Furthermore, agricultural lands are often degrading, i.e. losing their ability to support crop production, or
even degraded (FAO, 1993; Vlek et al., 2008). Ecosystem services that are characteristic for the drylands
(see Box 1) may thus be affected or lost (Millennium Ecosystem Assessment, 2005). Finally, climate
change is expected to worsen the conditions of rainfed agriculture in sub-Saharan Africa (Thornton et al.,
2006). In West Africa, rainfall will decrease and in East Africa it will likely increase, though here showers
will be shorter and more intensive. One of the consequences of the changing rainfall patterns will be
reduced plant growing periods (Ibid.). Figure 1 shows the areas that will see a reduction of over 20% in
plant growing period by the year 2050 based on two scenarios (left and right).
Box 1. Ecosystem Services typical of drylands in Africa
Supporting services
Regulating services
Provisioning services
Cultural Services
including soil formation, soil conservation, and nutrient cycling; including water management, local climate regulation through surface reflectance and evaporation, regulation of global climate through carbon sequestration, and pollination and seed dispersal; including provisions derived from biological production (food and fiber, woodfuel, biochemicals), and freshwater provisioning; including cultural identity, aesthetically pleasing landscapes, heritage values, spiritual services, recreation and tourism.
Source: adapted from Safriel et al. (2002)
Despite these challenges, there is a clear potential for upgrading rainfed agriculture in sub-Saharan Africa
(Molden, 2007). Analysis of water flows has shown that much of the rain is lost to evaporation or as
runoff. Instead, simple technologies could change these ‘blue water’ flows into ‘green’ water flows, i.e.
water that is absorbed by plant roots and subsequently lost through evapotranspiration (Falkenmark,
1995; Rockström, 1999). In fact, a large gap exists between yields obtained in sub-Saharan African
(under rainfed conditions) and yields in Asia under similar conditions. Average yields are currently around
1 metric ton per hectare – with the available water, this could relatively easily be increased to 1.5-2.0
metric ton per hectare (Rockström and Falkenmark, 2000). Barron and Okwach (2004), for instance,
demonstrated that simple rainwater harvesting technologies (combined with soil fertility measures) can
boost agricultural production. Other studies have also highlighted the benefits from rainwater harvesting
in Africa’s drylands (e.g. Boers and Ben-Asher, 1982; Critchley et al., 1992), also in light of upcoming
climate changes (Stockholm Environment Institute, 2009).
A wide variety of rainwater harvesting technologies have been studied and described in detail – from zaï
pits in Nigeria to demi-lunes in Niger, through to negarim catchments in the Negev desert of Israel and
teras systems in Tunisia (for an overview see e.g. African Development Bank, 2007) – yet one form has
received little attention thus far: road runoff harvesting.
7
1.2 Research questions
The overall aim of this thesis is to shed more light on the performance and potential of road runoff
harvesting. This technology is currently practiced by a number of farmers in sub-Saharan Africa (an
overview is provided in the next chapter). From literature case studies, however, it remains unclear what
the precise impacts are of these road runoff harvesting systems. Furthermore, an assessment has never
been made of the potential for up-scaling the use of this technology throughout the drylands of sub-
Saharan Africa, either for use by smallholder farmers (practicing rainfed agriculture in cultivated lands) or
by pastoralists (keeping livestock in the dryer rangelands).
This thesis focuses on the question what the potential is for practicing and up-scaling road runoff
harvesting in sub-Saharan Africa. More in particular, the research carried out for this thesis aimed at
giving an answer to the following two sub-questions:
1) What is the performance of existing road runoff harvesting systems in terms of sustainability?
2) What is the (bio)physical potential for up-scaling the use of road runoff harvesting in the drylands
of sub-Saharan Africa?
The first question addresses the potential of the technology itself, while the second question focuses on
the feasibility of areas where the technology is not practiced as yet. The latter question is limited to the
physical potential, i.e. social, economic and detailed environmental (hydrology, soil types) are not
included. Assessment of the physical potential for increasing the adoption of road runoff harvesting is
done with data on roads from literature and online databases. The performance of existing technologies is
tested by means of case studies in Eastern Province, Kenya. Providing an answer to these questions will
help to understand the desirability of promoting this technology amongst smallholder farmers, policy-
makers and development agents alike.
1.3 Thesis structure
In Chapter 2, the concept of road runoff harvesting is explained in detail and an overview is given of the
existing knowledge on road runoff harvesting systems in sub-Saharan Africa. Chapter 3 presents the
methodology that has been applied to address the two research questions: first the approach for the case
studies is described, followed by the methodology that was used to assess the potential for up-scaling
road runoff harvesting. Subsequently, in Chapter 4 the data are presented that have been gathered from
the case studies (and additional sites that have been visited) as well as the results from the sub-Saharan
Africa-wide assessment. Analysis of these results is provided in Chapter 5: the case studies are
evaluated according to four criteria (Technical performance, Economic viability, Environmental
friendliness and Social acceptance). The results of the assessment are directly discussed in Chapter 6,
together with the outcomes of the performance analysis. The conclusions are presented in Chapter 7.
Lastly, recommendations are given for researchers, policy-makers and development agents in Chapter 8.
8
2. Road runoff harvesting in sub-Saharan Africa
2.1 The concept of road runoff harvesting
The concept of road runoff harvesting is relatively new to researchers and development agents. In recent
years, the first case studies have appeared in literature that describe the way smallholder farmers gather
and use runoff from roads. This chapter gives an overview of the current knowledge on road runoff
harvesting that is available from literature and other sources. As the case studies in following sections will
show, road runoff systems are often the result of farmer innovations.
Road runoff harvesting is a form of rainwater harvesting. The principle of rainwater harvesting is based on
three steps (see also Figure 2):
1. Collecting and concentrating runoff
2. Storing runoff (optional)
3. Using the runoff for agricultural production or other purposes
In other words, a rainwater harvesting system is composed of a catchment, an optional storage facility
and a cultivation area. In the context of this thesis the term “cultivation area” is used to designate the area
where the runoff is applied for agricultural production. This is done to clearly distinguish the cultivation
area of rainwater harvesting systems from “cultivated lands” that are used as a category for assessing the
potential for up-scaling the use of road runoff harvesting in the drylands of sub-Saharan Africa (see
section 3.5).
The purpose of rainwater harvesting is to make more efficient use of rainwater that would otherwise be
lost as runoff or through evaporation. Two general forms of rainwater harvesting can be distinguished1:
water harvesting with microcatchments (within-field) and with external catchments (Critchley and Siegert,
1991). The first is further characterised by the length of the catchment that is usually a few meters long,
while the length of an external catchment is often 30 meters or more.
Figure 2. The principle of rainwater harvesting
This figure shows the principle of rainwater harvesting (after Critchley and Siegert, 1991). In the case of road runoff
harvesting, the catchment is formed by a road and/or by the sides of this road.
1 NB. Rainwater harvesting also includes rooftop harvesting. However, because the focus of this thesis is on
rainwater (runoff) harvesting from land surfaces, roads and road sides in particular, rooftop harvesting is not discussed.
9
Gathering rainwater with the help of roads falls in the category of external catchments as runoff is
collected outside the cultivation area. Following Critchley and Siegert’s definition for water harvesting
(Ibid.), road runoff harvesting can be briefly defined as: “the collection of runoff from roads and roadsides
for productive purposes”.
Roads (and roadsides) refer to all types of transportation ways, from motorways through to rural roads to
footpaths and livestock trails. Smaller roads and footpaths are often connected to house compounds that
can also contribute to the collection of runoff2. Roadsides refer to the area adjacent to the road that
contributes to the amount of runoff that is gathered along the border of the road.
Productive purposes refer to crop production for subsistence, for cash crops (including kitchen
gardening), for fodder production. Runoff stored in a reservoir can also be used for livestock to drink and,
provided it is clean enough, also for domestic use.
Box 2. Methods for calculating the potential amount of road runoff and the cultivation area size based on rainfall
depth, runoff efficiency and crop water requirements
The amount of runoff that can be harvested in a catchment can be calculated as follows:
Where: Pd: Design Rainfall (generally in mm) K: Runoff Coefficient (no unit) E: Efficiency Factor (no unit) The Design Rainfall is the amount of rainfall (in mm or m) during the growing season, which should be enough to meet the ‘Crop Water Requirement’ (ETc) that is expressed in mm/day (or m/day). The Design Rainfall is often calculated for a certain probability level, by looking at the rainfall over a number of years. The Runoff Coefficient is determined by how much runoff (in mm) can be generated with a certain amount of rainfall (in mm). It is defined as the runoff divided by the rainfall in a given catchment area. It depends on how much of the rainwater is absorbed by the soil; it will therefore also change depending on the length of a shower. A tarmac road with a 10% slope has a large runoff coefficient of 0.9 or more, while for a sandy road with a 3-5% slope this will be more or less 0.2-0.3. The Efficiency Factor takes into account factors that negatively affect the amount of runoff that can be generated, like the inefficient distribution of runoff, evaporation and deep percolation. Generally, this factor is set between 0.5 and 0.75. With the same parameters, the catchment/cultivation area (C/CA) ratio can be calculated (Ibid.):
Where: ETc: Crop water requirement Broadly speaking, the C/CA ratio in a microcatchment (within-field) varies between 1/1 and 3/1, while for external catchments the ratio tends to be larger (2/1 – 10/1; Critchley and Siegert, 1991).
2 This thesis does specifically not focus on rainwater harvesting systems that are based on runoff collection from
house compounds and court yards, such as the ‘water borne manuring systems” described by Mutunga and Critchley (2001).
10
The water that can potentially be harvested in a catchment determines the size of the area where crops
can be grown (Boers and Ben-Asher, 1982). Box 2 explains how the potential amount of runoff can be
calculated, and how the ratio between catchment and cultivation area can be determined.
Like other forms of water harvesting, the collection of road runoff is suitable in areas of low rainfall in the
arid, semi-arid and dry sub-humid areas of sub-Saharan African.
Road runoff harvesting itself can be divided into two categories:
A. Runoff harvesting with roadside drain
Rainwater is collected primarily from the surface of the road
B. Runoff harvesting with culvert
Rainwater is collected in the uphill area adjacent to the (rail) road
2.2 Runoff harvesting with roadside drain
Roads have a large surface that can collect large amounts of rainwater. Rainwater that is not directly
‘absorbed’ by the road and runs off the road, can be collected. In the rainy season, smaller roads can
become completely inaccessible and turn into small rivers. The amount of available runoff can be
calculated in a relatively simple way and depends on the runoff coefficient (see Box 2). If the camber of a
road is convex, only half of the road can be used to collect rainwater. Depending on the potentially
available runoff one can determine the proportion of land and the amount and type of crops that can be
cultivated. Figure 3 shows the basic forms of runoff harvesting from roadside drains.
Examples from the field show that a large variety exists in the application of roadside drains. In Uganda
small drains are used that lead to square soak-away pits with banana plants (Kiggundu, 2002; Critchley et
al., 1999). In Kenya similar pits are known as T-basins according to Bittar (2001, cited in: Mati, 2005). The
majaluba system in the semi-arid regions of Tanzania (Mwanza, Shinyanga, Tabora, Singida, Dodoma) is
based on (road) runoff collection into retention basins (FAO, 2001; Hatibu and Mahoo, 2000 and Hatibu et
al., 2000). The bunds of the majaluba, which are used to grow paddy rice, are reinforced with Cynodon
dactylon grass.
Figure 3. Runoff harvesting with roadside drains: three basic forms
This figure shows three basic forms of road runoff harvesting with a roadside drain. Blue arrows indicate the direction
of the runoff water. The first form (a.) applies water directly in small, restricted cultivation areas (planting pits, T-
basins or retention basins) alongside the road. The second (b.) guides the water into retention ditches that are built
along the contour lines. This form also includes flooding of the cultivation area, which can have contours bunds
instead of trenches. The third and last form (c.) consists of an intermediate storage facility (see examples in text) that
is preferably built above the cultivation area (to facilitate irrigation). Many variations are possible based on these three
general forms.
11
Critchley et al. (1992) describe the caag system in Hiraan Region, Central Somalia, that is based on
(road) runoff diversion into a field where the runoff is guided in a zig-zag manner along earthen bunds
that are built at a small angle following the contour lines (similar to Figure 3b.)
Other examples of run-off farming with roadside drains are found in Machakos District, Kenya, where
runoff is first guided into one or more retention ditches that are built along the contour lines; in the
retention ditches pits are dug for banana plants (Ngigi, 2003a: 144). Two farmers have, each of them,
created a system where water flows from the first ditch (uphill) to the next ditch once the first is full. Water
input is regulated either automatically (it spills over in the next ditch) or manually (by blocking the entry of
a ditch with a gunny bag). Retention ditches vary in size (from 50 cm by 50 cm to more than 1 m by 1 m
in cross section) and can be excavated with soil thrown uphill (fanya juu) or downhill (fanya chini). Long
ditches are generally constructed with a small gradient. Banana pits can be dug in or next to the ditch.
Pawpaw, mango, citrus and guava trees are grown on the embankment, while maize and beans are
cultivated on the terrace in between ditches (along furrows that run parallel to the ditches) (ICRAF, 2012).
Instead of storing the runoff directly in the soil profile, water can also first be stored in a reservoir before it
is used for supplemental irrigation. The guide “Water from roads” by Nissen-Petersen (2006) describes a
variety of water reservoirs, such a borrow pits along roads and water pans (natural depressions, called
hafirs in Kenya), but also reservoirs especially constructed for this very purpose, like: earth dams
(murram pits, ponds, charco dams, hill side dams), above and underground water tanks in many forms
and shapes (e.g. berkads in Somalia), and hand-dug wells near Irish bridges (concrete drifts that function
as a bridge for traffic and, concomitantly, as underground and/or aboveground dam). In Lare District,
Kenya, for instance, hundreds of ponds are used to store all kinds of runoff (including from roads)
(Malesu et al. 2006). An example from a borrow site that was turned into a dam comes from Tigray,
Ethiopia, where farmers have started using it for feeding the water to their livestock (Haile et al. 2000,
cited in: Mati, 2005). Hatibu et al. (2000) also report the use of several borrow pits for road runoff
harvesting along several highways in Tanzania.
Many of the examples above indicate that the origin of road runoff harvesting from roadside drains lies
almost exclusively in the innovative minds of smallholder farmers, who recognise and exploit
opportunities for using road runoff for productive purposes.
2.3 Runoff harvesting through a culvert
This form of road runoff harvesting can be practiced where road construction workers have placed one or
more culverts under a (rail) road. Figure 4 shows the basic forms of water harvesting from a culvert outlet.
Culverts are conduits constructed under (rail) roads for drainage purposes: they aim to channel water
from the uphill side to the downhill area on the other side of the road. They can have various shapes,
lengths and diameters, and are generally made of concrete, polyvinyl chloride, steel or stone. The size of
a culvert depends on the amount of runoff that it has to handle – for large quantities bridges have to be
constructed. Jungerius et al. (2002) report an average diameter of 0.9 metre along a 42 kilometres long
stretch of road north of Nairobi, Kenya (more details on this road are presented below). Though culverts
are built to prevent roads from being flooded, they often cause harm to the downhill field due to the power
of the concentrated runoff they discharge. The huge quantities of water that are released from a culvert
when it rains heavily, can lead to gully formation and severe erosion if the water is not slowed down or
controlled in another way (see Figure 5).
12
Figure 4. Runoff harvesting through a culvert: two basic forms
This figure shows two basic forms of road runoff harvesting based on the water that is discharged by a culvert. In the
first form (a.), the water is guided directly into retention ditches for use within-field. In this case, spill-ways are
essential to prevent waterlogging. The other form (b.) makes use of an intermediate water reservoir that can have all
forms and shapes (see examples in the text under harvesting with a roadside drain), while the size depends on the
amount of runoff water that needs to be stored.
A technical handbook of the World Bank (1997) touches upon the cumulative environmental impacts that
could arise from poorly designed culverts or drainage systems along a road located in a watershed. Yet,
the handbook mainly focuses on the impacts on the road itself, in particular the flooding of a road due to
accumulation of sediment at the inlet of a culvert, and on the migration pathways of animals that use
culverts to cross a road. Potential erosion and the formation of gullies on the downstream side of the road
are not discussed in the handbook.
Controlling the potentially devastating power of runoff from a culvert is crucial. Otherwise, when runoff
from culverts is not properly managed, a situation like along the Tanga-Arusha highway can arise where
55 culverts have created deep gullies in the landscape downstream of every culvert (Hatibu et al., 2000).
Moreover, attempts of farmers to divert the water from gullies onto their lands – with the aim to increase
agricultural production – have resulted in destruction of their farm land. Another example of gully
formation is provided by Jungerius et al. (2002), who report that 13 out of 24 culverts have led to
downslope erosion along a 42 km long earth road between Marich Pass and Kerio Valley in Kenya.
Nevertheless, the effects of road construction on erosion remain largely unstudied.
Once gullies have formed, measures can be taken to reclaim them to avoid further land degradation and
to benefit from the concentrated runoff. Gully reclamation through the construction of check dams would
be an option (see e.g. WOCAT, 2007). Further erosion can also be prevented by adding vegetative
measures like grass to the water way (Ibid.). Diversion into a borrow pit, dam or pond would be another
option in order to stop the water and store it for later use.
If gully formation has not yet taken place, then runoff can be used directly for agricultural purposes. The
Lusilile Irrigation Project is a successful initiative in Manyoni District, Tanzania, that exploits water coming
from two railway culverts (Hatibu et al., 2000). For this purpose, a series of canals (almost 20 km
altogether) was constructed to divert the water to a cultivation area of 150 ha where paddy rice is
produced. Despite an initial increase in production, the system of canals was not designed for the El Niño
rains during the same season and some canals were damaged.
13
Figure 5. Picture of a gully formed at the outlet of a culvert
This picture was taken by Erik Nissen-Petersen in Maasai land (source: Nissen-Petersen (2006)). The gully results
from the destructive power of water that is discharged by a culvert into a field located on the valley side of a road.
Another example is that of Mr. Muindu Musyoka (Mutunga and Critchley, 2001). He owns a farm in
Mwingi District, Kenya, and has developed a form of road runoff harvesting using a culvert under a main
connector road. He constructed a diversion ditch (with the fanya chini technique), through a neighbouring
field, that leads the water from the culvert to his own cultivation area. This farm has been revisited for the
purpose of this thesis.
Due to the fact that this form of road runoff harvesting depends on the presence of culverts, runoff
harvesting through culverts most likely originated only recently – up to a few centuries ago at most –
when the first culverts were built. The case of Muindu Musyoka shows that farmer innovation may be an
important if not crucial factor for using road runoff harvesting. From the information provided by Hatibu et
al. (2000) is not clear what the driving factor behind the Lusilile Irrigation Project has been, though the
development agents may play a role in setting road runoff harvesting as well.
The runoff that is collected by means of a culvert can be calculated by determining the average runoff
coefficient and the surface of the area that generates the runoff. The same calculation method as
described in Box 2 can be used to estimate the amount of runoff.
2.4 Benefits of road runoff harvesting for smallholder farmers
Ngigi (2003a: 217) states that “the capacity of road runoff harvesting to provide food security is immense
for some farmers in Kitui and Machakos Districts (Kenya). The farmers, who previously suffered
persistent crop failures even during normal rains, report improved yields.” There thus seems to be a great
potential for this technique to improve the lives of smallholder farmers living in the dry areas of sub-
Saharan Africa.
14
Existing case studies point at the promising impacts of road runoff harvesting on the lives of smallholder
farmers. In Machakos District, for instance, a farmer named Mr Nzove now manages to yield 40 large
bunches of bananas per month, as opposed to the 10 small bunches he would otherwise produce. In
addition, he produces three times as much coffee as before (Ngigi (2003a: 215). With road runoff
harvesting, his monthly income attained US$ 80 (Ibid.: 224).
The same author mentions the improved welfare of Ms Angeline Muthue, who also lives in Machakos
District. A higher income from the sales of banana, vegetables and pawpaw (US$ 40 per month) has
enabled this farmer to create employment for her children with the opening of a butchery and a hardware
store. A rough comparison of the Muthue’s yields with the average yields of farmers in the area shows a
significant impact of road runoff harvesting on her produce (see Table 1). Though this table provides a
very limited picture, it is the most detailed comparison of yields that was found in literature.
Table 1. Comparison of yields obtained with and without road runoff harvesting
Crop
Ms Muthue’s farm production (kg)
Average neighbours’ farm production (kg)
Beans 2,340 90 Maize 450 10 Cowpeas 200 20 Green grams 100 10 Pumpkin 1000 0
This table compares the production of a farmer in Machakos District using road runoff harvesting with the production
of her neighbours (source: Ngigi, 2003: 218). The data correspond to the harvest during the long rainy season in
2002 (April-May).
In the earlier mentioned Lusilile Irrigation Project, significantly higher yields were recorded after the
construction of the channels. By 1997/98, 145 farmers benefited from a yield increase from 1 to 3.5 metric
tonnes per hectare (Hatibu et al., 2000).
Nissen-Petersen (2006) lists other benefits that could arise from road runoff harvesting, besides income
from the cultivation of crops and fruit trees:
- Selling water to neighbours
- Raising ducks, geese, fish and bees in or near open water reservoirs
- Recharge of wells or dams
At the same time, the same author warns for potential health hazards associated with runoff harvested
from tarmac roads that could contain traces of tar, oil and rubber. The process and impacts of pollution
through road runoff harvesting remain largely unstudied.
2.5 Upstream-downstream impacts of road runoff harvesting
The collection of rainwater in upstream catchments (like roads and roadsides) can have both positive and
negative consequences for downstream areas (e.g. SIWI, 2001; Rockström et al., 2003, Bouma et al.,
2011). One impact can be that less runoff reaches the fields downhill, which can cause problems for
water users like smallholder farmers. An example of such a situation comes from Kenya, where banana
growers along the roadsides get into conflicts because too much water is ‘tapped’ from the uphill-side of
the road (Ngigi, 2003a: 213). The same author even argues that “[…] in most cases of road runoff
harvesting there is an offended neighbour who now realizes the crop on his/her own farm could perform
better with extra input in form of road runoff.” He mentions (ibid.) the case of Mrs. Musyoka in Kitui
District, Kenya, who used to divert all runoff from a road, thus leaving no water for her downstream
15
neighbours. The local administration had to intervene to settle the case: they advised the farmers to find
an agreement to equitably share the water. He also reports of a similar case involving three farmers along
an earth road in Laikipia District in Kenya (Ngigi, 2003a: 212). While such conflicts are becoming more
common in Laikipia District, “[t]he water laws in most countries of GHA [Greater Horn of Africa] do not
provide policy guidelines on runoff sharing as anyone is free to harvest as much runoff as possible
without seeking permission from government authorities” (Ngigi, 2003a: 191). Equitable sharing of runoff
from roads may thus represent a challenge in areas where several farmers exploit runoff from the same
road drain – or culvert for that matter.
The opposite consequence may be that a community living downstream receives more water owing to the
fact that more rainwater can infiltrate the soil in the uphill area and – provided that the permeability of the
ground is good enough – reaches the downhill area via the underground streamflow. Rainwater
harvesting may thus influence the ecosystem services like (downstream) water provision provided by a
watershed. Indirectly, by altering the amount of groundwater, runoff and evapotranspiration, it will have an
impact on other ecosystem services (e.g. soil conservation and nutrient cycling) as well.
Up-scaling of rainwater harvesting technologies in a watershed may further change its hydrology. A
modelling study by Mutiga et al. (2011) suggests that in the upper Ewaso Ngiro North basin only
moderate effects can be expected from expanding the use of rainwater harvesting (which in this study
includes in-situ water conservation techniques3
). The study of the upstream and downstream
consequences of rainwater harvesting, and road runoff harvesting in particular, has started to receive
attention only in recent years. Concomitantly, policies are lacking to address conflicts that are the results
of downstream impacts of upstream water harvesting (Rockström, 2000).
2.6 Adoption by other farmers
Farmers around the world have adopted road runoff harvesting (see examples in Box 3). Besides the
above-mentioned examples from East Africa (Kenya, Tanzania, Uganda) it is not known how many other
smallholder farmers in sub-Saharan Africa practice road runoff harvesting, nor is it clear whether there is
trend regarding adoption by other farmers. A video produced by ASAL Consultants (Nissen-Petersen,
2010) tells that road runoff harvesting is a commonly used technique in the African drylands. As far as
Kenya is concerned, this is corroborated by Shaxson and Barber (2003) who write that “the most common
and successful concentrated runoff harvesting practice in Kenya is the harvesting of road runoff in
retention ditches”. Besides the earlier examples from Machakos, Kitui and Mwingi Districts, road runoff
harvesting is widely practiced in Lare Division of Nakuru District, Kenya (Malesu et al., 2006). Here, runoff
is harvested by farmers from hillsides and roads and stored in ponds (and pans) that are used for
supplemental irrigation. Tuitoek et al., 2001 (cited in: Mati, 2005) writes that 1,000 pans have been
installed in Lare Division to trap road runoff. With reference to a publication of the Ministry of Agriculture
from 2001, Ngigi (2003a: 76) writes that 4,000 hectares in Kitui District benefit from road runoff
harvesting.
3 In situ water conservation techniques are within field measures that prevent rainwater and runoff from leaving the
field, like mulching and growing continuous ground cover (e.g. as part of conservation agriculture).
16
Box 3. Road runoff harvesting in other parts of the world
The technology is not only practiced in arid regions of Africa; other parts of the world have developed their own ways to collect rainwater from roads. Already in 1995, FAO organised a workshop where road runoff cases from Argentina, Brazil en Venezuela were discussed (UNEP, 1997). India has a long history when it comes to water harvesting technologies; nevertheless, road runoff harvesting is not mentioned explicitly in the standard work ‘Dying Wisdom’ (Agarwal, 1997). Sachdeva and Sharma (2008) do present a case for road runoff harvesting in India, yet only for urban areas. In Gansu Province, China, road runoff is collected and stored in tanks for supplemental irrigation of crops and trees (Qiang and Yuanhon, 2003).
Also in industrialised countries like the United States of America farmers make effective use of road runoff (see e.g. Zeedyk (2006). The technique is also incorporated in the functioning of modern ‘vinex’ living quarters in The Netherlands, where water from roads is collected and cleaned before it is released back into the environment.
Regarding Tanzania, “tapping road runoff for supplemental irrigation [of] crops is widespread”, as stated
in SIWI (2002, cited in: Mati, 2005). For Uganda, Critchley et al. (1999) refer to earlier observations that
water harvesting from roads and paths for banana plantations has been practiced by “many people” for
decades. For other countries in sub-Saharan Africa indications about the occurrence of road runoff
harvesting have not been found.
Information about the factors influencing adoption of road runoff harvesting is limited and scattered.
Mugerwa (2007) studied the adoption factors of soil and water conservation measures, including runoff
diversion from roadside drains into retention ditches, in banana plantations in Kiboga and Masaka
Districts in Uganda. He identified the following barriers that explain the low adoption rate of (road) runoff
harvesting technologies:
• Use of simple tools (hand hoe) vs. more sophisticated tools required for establishing runoff
harvesting structures
• High labour costs vs. low income from the sales of banana
• Low actual yield increase vs. expected yield increase
• Low market prices of banana
• Lack of government support; extension service receive inadequate funding and consider
rainwater harvesting as ‘soft and inappropriate’
• Lack of donor support due to the low priority (road) runoff harvesting receives
• Lack of financial incentives such as credit
Mugerwa remarks that socio-economic factors like produce sharing, jealousy and witchcraft were not
accounted for in his study, yet could also play a role.
For soil and water conservation measures in general and rainwater harvesting in particular, some factors
discouraging adoption have been summarised by Critchley (2009) based on two earlier reviews and
personal experience. These (broadly defined) barriers include poor project design, lack of technical
knowledge, inadequate institutional and policy support, and economic barriers. Furthermore, Ngigi et al.
(2005a) emphasize the importance of matching technical ‘solutions’ with the actual priorities of farmers,
who are generally risk-averse and consider other options to sustain or improve their livelihood as well.
There is a multitude of factors that influence the decision of a farmer to adopt rainwater harvesting
measures (e.g. Ngigi, 2003), which vary from region to region owing to differences in technical, social,
cultural, economic and environmental conditions. Broadly speaking, the same factors also apply to road
runoff harvesting in particular. Nevertheless, some factors are specific for road runoff harvesting for
obvious reasons (e.g. proximity of and access to a road or culvert). In this thesis, some adoption factors
specifically related to the road runoff harvesting case studies will be presented.
17
2.7 Impacts of up-scaling
Little is yet known about the impacts of scaling up rainwater harvesting. Ngigi (2003b) discusses a case
study in Wajir District, north-eastern Kenya, where water pans have been constructed for communities
that are predominantly pastoral. The reduced need for water from other sources as a result of water
harvesting has led to increased harmony between different clans. Normally, these clans would compete
over the limited water resources – and competition is growing since more farmers are shifting from
livestock to crop production. The author concludes that scaling up water harvesting may act as a conflict
mechanism in water scarce areas.
From a theoretical perspective, Ngigi et al. (2007) propose a framework for modelling the hydrological
impacts of up-scaling rainwater harvesting in a river basin, allowing indirectly also to assess the socio-
economic and environmental consequences. The upper Ewaso Ng’iro river basin in Kenya was chosen as
a case study to design scenarios for river flows. The scenarios are based on the assumptions that
adoption will increase over time and river flows will decrease as a result. An important factor in the model
are the downstream water requirements, that is chosen as an indicator – with the aim to assist decision-
makers – in order to intervene in time in upstream water harvesting activities (i.e. once the downstream
water requirements are no longer met). Practical applications of this model have not yet been reported.
Focusing on the same basin, Mutiga et al. (2011) looked at the hydrological responses to land use
change (rainwater harvesting) using the soil and water assessment tool (SWAT) model and satellite
imagery covering a period of sixteen years. The outcomes show that scaling up rainwater harvesting has
no significant impacts on downstream areas, despite a 5% increase of base flow and 2% decrease in
surface runoff.
These studies highlight the fact that research on the impacts of up-scaling rainwater harvesting
technologies is still in its early stages. In this context, road runoff harvesting in particular was not found in
any study or report.
18
3. Methods
3.1 Analysis framework for case studies
To answer the first sub-question – “What is the performance of existing road runoff harvesting systems in
terms of sustainability? – the criteria for identifying environmentally sustainable technologies (ESTs)
developed by UNEP were chosen as a starting point (UNEP, 2003). According to these criteria, a
technology should be environmentally sound, economically viable and socially acceptable (Ibid.). In other
words, an EST should positively contribute to the economic, natural and social capital of its environment.
Regarding the evaluation of water harvesting technologies, several authors (e.g. Critchley and Siegert,
1991; Oweis et al.,1999; Rockström, 1999 and Hatibu et al., 2000) indeed emphasize the importance of
taking into account the related socio-economic and environmental issues.
Initially, the framework of the World Organisation for Conservation Approaches and Technologies
(WOCAT; WOCAT, 2007) was envisioned as the analysis framework. The WOCAT Questionnaire on
SLM Technologies (WOCAT, 2000) was used for collecting data for the case studies. This questionnaire
is structured in three parts: General Information, Specification of the SLM technology and Analysis of the
SLM technology (see Annex I, first column). To systematically address the technological, economic,
environment and social aspects, this framework was not deemed practical. Instead, during the course of
this study, it was decided to use the TEES-test developed by Critchley (2007; see Table 2, left column),
which incorporates the three sustainability criteria as well as a technical performance criterion – which is
essential for assessing the long-term performance of a technology like road runoff harvesting.
For this reason, the data gathered with the questionnaire have been classified according to the categories
of the TEES-test (see Annex I; NB: general information on the technology was put in a fifth category
called ‘General’). In addition, the elements of the questionnaire were structured according to 3 to 5 sub-
categories under each criterion. The result of this classification – in terms of input for the TEES-test – is
presented in Table 3.
For the Technical feasibility these are (physical) Conditions, Purpose (of the Technology), Measures
(including potential runoff and catchment/cultivation ratio) and Knowledge required. For the Economic,
Environmental and Social data three sub-categories are used: Conditions, Benefits and Disadvantages.
The Conditions describe the characteristics of the area where the technology is applied and do not regard
the impact of the technology. The Benefits and Disadvantages instead cover the consequences of using
road runoff harvesting. In addition, for the Economic data the sub-category Costs was used, and for the
Social data the two sub-categories Origin (of the innovation) and Adoption (by other farmers) were used.
Analysis of these data was done using the approaches and tools described in Table 2.
Table 2. Approaches and tools used to analyse each of the TEES-test criteria
Criteria of TEES-test Analysis approach/tool
Technical performance - Comparison physical conditions - Performance of collection, storage and use measures - Comparison level of knowledge required
Economic viability - Comparison economic conditions - Quantitative benefit-cost analysis, similar to Ngigi et al. (2005a), taking
into account economic disadvantages Environmental friendliness - Comparison environmental / ecological conditions
- Qualitative comparison benefits and disadvantages Social acceptance - Comparison social conditions
- Qualitative comparison benefits and disadvantages
19
Table 3. Methodology used to categorise data from the WOCAT Questionnaire on SLM Technologies
Sub-category Elements of QT
GENERAL • NA • Common name, local name, part of watershed, Approach, area definition, coordinates, definition of Technology, photos
TECHNICAL • Conditions
• Purpose
• Measures
• Knowledge required
• Rainfall, climate, growing seasons, altitude, land form, slope, soil: depth, texture, fertility, organic matter, drainage, water storage capacity; groundwater table, surface water availability, water quality
• Problems, land use type, goals, land degradation type, causes of land degradation
• Conservation measures (agronomic, vegetative, structural and /or management), measures against land degradation; type and layout; establishment and maintenance activities (including potential runoff, catchment / cultivation area ratio)
• Knowledge required
ECONOMIC • Conditions
• Costs • Benefits
• Disadvantages
• Level of wealth, significance of off-farm income, access to services and infrastructure, market orientation, land use tools, type of cropping system, water supply, size of cropland
• Establishment costs, maintenance costs, costs of agricultural input
• Production and socio-economic benefits, benefits vs. establishment and maintenance costs
• Production and socio-economic disadvantages
ENVIRONMENTAL • Conditions • Benefits • Disadvantages
• Biodiversity (and other) • Ecological benefits • Ecological disadvantages
SOCIAL • Conditions • Origin • Benefits • Disadvantages • Adoption
• Type of land users applying Technology, population density, pop. growth, land and water rights
• Origin (of idea/innovation) • Socio-cultural benefits • Socio-cultural disadvantages • Adoption (including acceptance)
In this table the elements of the WOCAT Questionnaire on SLM Technologies (third column) are categorized according to the four categories of the TEES-test (see text) plus a general category (GENERAL) listed in the first column. In addition, the elements are divided into a number of sub-categories (second column) to facilitate comparison. Annex I shows, question per question, how the elements have been categorised.
20
3.2 Selection of case studies
Two case studies were identified to assess the performance of road runoff harvesting. The first is a revisit
of an existing case study in Mwingi District, Kenya, first described by Mutunga and Critchley (2001). This
site was chosen to study 1) runoff harvesting through a culvert, and 2) the long-term impact of road runoff
harvesting on a single farm. The second is a road runoff harvesting system with roadside drains in
Machakos District that has never been described before. It was not possible to identify more case studies
in the same area prior to the field visits. In addition, during the field trip four other sites in Machakos
District were identified as well that provide additional information about the possibilities that exist to use
and adapt road runoff harvesting to local conditions. Figure 6 shows where the six sites are located.
It is important to note that these six sites show examples of road runoff harvesting that have in one way or
the other succeeded. For this reason, they have been identified during fieldwork of researchers. Though it
would be particularly useful to study examples of sites where the adoption of road runoff harvesting has
failed, such failures are seldom reported or described.
Nevertheless, the information from the six sites provides some insight into the performance and potential
impact of road runoff harvesting for smallholder farmers and their environment.
Figure 6. Map showing the location of the visited farms
The map in the upper right corner shows the location of the case studies (#1 and #2) and of the four additional sites
(#3 – #6) that were visited during the fieldwork.
21
3.3 Study area
The semi-arid agro-ecological zones of Mwingi and Machakos Districts (Eastern Province, see Figure 6)
are located at an altitude of 400-1800 m and 1000-1600 m respectively (Pretty et al., 2011). Annual
rainfall depths of 400-700 mm (Ibid.), which are higher in the highlands (Tiffen et al., 1994). Two rainy
seasons are distinguished: a ‘short’ season from October to December and a ‘long’ season from March to
May (Critchley, 1991). The main staple food is maize, which is often mixed with cowpeas and pigeon
peas, and also with beans, green grams, millet, and sorghum (Muhammad et al., 2003). Livestock is
reared by pastoralists on rangelands (e.g. the eastern part of Mwingi District) and by farmers in the
cultivated areas. The people living in these districts belong mostly to the Akamba tribe (Tiffen and
Mortimore, 1994).
Machakos District has become known all over the world because it has managed to increase agricultural
production in the period 1930-1990 despite a more than twofold population increase and problems with
agricultural lands that used to suffer from severe erosion (Ibid.). Over 70% of the land has been turned
into fanya juu terraces (Critchley, 1991). Other soil and water conservation measures, such as grass
strips, contour ploughing and agroforestry have also contributed to the success. The district (which is
divided into Machakos and Makueni Counties) has a total population of 1,983,111. Machakos County has
a population density of 176.96 persons per square kilometre and in Makueni County the density is 110.45
persons per square kilometre (Kenya National Bureau of Statistics, 2012).
Mwingi District has not received as much attention from researchers as Machakos District. In Mwingi
District, Kamba herders are the dominant group, followed by Orma and Somalis (Opiyo et al., 2011). The
district has a population of 303,828 and an average population density of 28 people per square kilometre
(Kenya National Bureau of Statistics, 2012).
3.4 Fieldwork and interviews
Farmers were visited on-site and interviewed with the WOCAT Questionnaire on SLM Technologies.
Translation from English to Kikamba or Kiswahili and back was done by an interpreter (Ms Rose Mueni).
Table 4 shows the order and dates of the six visits.
Table 4. Timing of field visits and type of interviews
# Farmer Date(s) Type of interview 1 Muindi Musyoka 9 - 13 May 2011 QT*
2 Mwema Maswili 18 May 2011 QT* 3 Samuel Mweu Maingi 17 May 2011 Open interview 4 Neighbour of Samuel Mweu Maingi 17 May 2011 Open interview 5 David Kyula 18 May 2011 Open interview 6 Mr. Sammy 18 May 2011 Open interview (QT: WOCAT Questionnaire on SLM Technologies
22
3.5 Methodology for determining the potential for up-scaling road runoff
harvesting
To answer the second sub-question, “What is the (bio)physical potential for up-scaling the use of road
runoff harvesting in the drylands of sub-Saharan Africa?”, a simplified approach was taken to estimate the
length of roads in the drylands of sub-Saharan Africa and their potential for generating runoff for road
runoff harvesting purposes. Though more elaborate approaches for mapping the potential for water
harvesting have been considered, involving GIS-tools for instance (e.g. Gupta et al., 1997, Ziadat et al.,
2006), this was not possible within the scope of this study.
Figure 7. Methodology used to determine the suitability of roads for runoff harvesting
The flowchart describes the methodology that was used to determine the suitability of roads in sub-Saharan Africa for
road runoff harvesting. Besides the first step (determination of the size of the dryland area in each country), all the
data are estimates.
The suitability of roads in sub-Saharan Africa for road runoff harvesting was estimated using the steps
shown in the flowchart of Figure 7. This process was carried out for all individual countries in sub-Sahara
Africa, most of which have drylands on their territory. Railways have not been incorporated in the
assessment, as they represent only a small fraction of the total network of roads (less than 1%, according
to data from the online World Bank database only). Considering the fact that this assessment is meant to
provide a rough estimate of the potential for up-scaling road runoff harvesting, the fraction of agricultural
land under irrigation (less than 5%) was not taken into consideration for the calculations.
The ‘mapping’ of roads and culverts that could be suitable for road runoff harvesting was done as follows.
First, the area of drylands per country in sub-Saharan Africa was calculated. In literature several
definitions of ‘drylands’ are used. For the purpose of this thesis, drylands are defined as arid, semi-arid
and dry sub-humid zones, following the categorisation of FAO (1993). These three areas correspond to
the agro-ecological zones where rainwater harvesting is generally practiced. Table 5 gives an overview of
the main characteristics of drylands.
23
Table 5. Characteristics of arid, semi-arid and dry sub-humid areas
Aridity Index* (precipitation / potential evapotranspiration)
Annual rainfall** (in mm)
Plant growing period**** (in days)
Arid 0.05 - 0.2 Up to 300 Less than 75
Semi-arid 0.2 - 0.5 200-800 75 - 115
Dry sub-humid 0.5 - 0.65 Upper range around 1000*** 115 - 179
Drylands 0.05 - 0.65 Up to 800 (excluding dry sub-humid areas)
Up to 179
Sources: *UNEP (1992), ** adapted from FAO (1989), ***Rockström (1999) and ****FAO (2000)
The starting point for calculating the length of the road network in the drylands was the length of the
national network of which the most recent figures can be found in the database of the World Bank (World
Bank, 2012). Though on its website, the World Bank states that “Total road network includes motorways,
highways, and main or national roads, secondary or regional roads, and all other roads in a country. A
motorway is a road designed and built for motor traffic that separates the traffic flowing in opposite
directions.”, this does not correspond to figures found for Kenya. For this country, figures from the World
Bank database only refer to classified roads. In Kenya, classified roads include International Trunk
Roads, National Trunk Roads, Primary Roads, Secondary Roads, Minor Roads and Special Purpose
Roads (Kenya Roads Board, 2012), though a definition of each road category is not provided. In addition
to classified roads, there are also unclassified roads that in the case of Kenya include Urban Roads,
Rural Roads and Tracks, National Park & Reserve Roads and Forest Roads. Rural Roads and Tracks
cover 110,000 kilometres and classified roads 63,291 kilometres (Ibid.).
For Tanzania, a distinction between classified and unclassified roads is not made (Roads Fund Board,
2012). However, the figure presented by the Roads Fund Board (which is practically the same as the
figure of the World Bank), refers solely to national and district roads – from trunk roads up to roads
leading to villages. This observation, and the fact that the total length is even smaller than the total length
of classified roads in Kenya, suggests that rural roads and tracks have not included in the calculation. For
a third check, the road network of South Africa was taken. According to the World Bank, this country has
a network of over 362,000 kilometres. This is in sharp contrast with a country like Kenya for instance, also
taking into consideration that it is only half the size of South Africa. Though this can partly be explained by
the fact that South Africa has invested more in its road network, such a high figure also suggest that more
roads, including those located in rural areas, have been classified. However, in the absence of data to
corroborate this hypothesis, the ratio (Unclassified) Rural Roads and Track / Classified Roads in Kenya
(110,000 kilometres / 63,291 kilometres or 1.74 / 1) was taken to estimate the length of unclassified roads
for the other countries in sub-Saharan Africa. The sum of classified and (estimated) unclassified rural
roads for each country was the basis for further calculations.
Subsequently, the length of the roads in each of the three types of dryland was calculated by using the
population density in each of these areas as a proxy (assuming a correlation of 100% between population
density and road density), in order to provide a more accurate estimate than using only the road density
of each country as a whole. This was not based on scientific evidence, yet under the assumption that
inhabited zones have a denser road infrastructure than less inhabited zones (e.g. deserts). Data on the
population size in the dryland areas were taken from Murray et al. (1999).
Next, a distinction was made between the rangelands and the cultivated lands that make up drylands for
the most part. Rangelands are characterised by (a combination of) nomadic/transhumant pastoralism,
sedentary livestock raising and/or cattle and sheep ranching (FAO, 1993). Cultivated lands include areas
where rainfed and irrigated agriculture is practiced (Ibid.). In the absence of data
24
Table 6. Proportion of rangelands, cultivated lands, urban areas and other areas in the drylands of the world
Rangelands Cultivated Urban Others Totals
Area (km2) Share Area (km
2) Share Area (km
2) Share Area (km
2) Share Area (km
2) Share
Dry subhumid 4.344.897 34% 6.096.558 47% 457.851 4% 1.971.907 15% 12.871.213 100%
Semiarid 12.170.274 54% 7.992.020 35% 556.515 2% 1.871.146 8% 22.589.955 100%
Arid 13.629.625 87% 1.059.648 7% 152.447 1% 822.075 5% 15.663.795 100%
Total dryland 30.144.796 59% 15.148.226 30% 1.166.813 2% 4.665.128 9% 51.124.963 100%
Source: adapted from MEA (2005: table 22.2)
regarding (sub-Saharan) Africa specifically, the share of the two land use types at the global level was
used: worldwide, rangelands occupy on average 59% of the drylands, while cultivated lands make up
30% (Millenium Ecosystem Assessment, 2005; see Table 6). In rangelands, road runoff harvesting is
suitable for pastoralists, while in cultivated lands the technology can be used for crop production by
farmers. The estimates are likely not very accurate for each individual country; however, this assessment
is primarily intended to provide a picture of the potential of using the road infrastructure for road runoff
harvesting in sub-Saharan Africa as a whole.
The next step consisted in estimating 1) the surface area of the roads that could be used for collecting
road runoff, and 2) the number of culverts that is present and that could be used for road runoff
harvesting (in both rangelands and cultivated lands) . The latter was done based on numbers published
by Jungerius et al. (2003) and Mati (1993), who reported an average of 0.57 and 2.1 culverts per
kilometre on road stretches of 42 and 149 kilometres, respectively. Due to a lack of information regarding
the culvert ‘density’ in other parts of Africa, it was decided to use a range of 0.25 and 2 culverts per
kilometre. Furthermore, only 25% of these culverts were assumed to be suitable for road runoff
harvesting, taking into account that they may not be located in the proximity of a farm, that the topography
does not allow for water harvesting (high slopes), that a gully has already formed making runoff
harvesting impossible, as well as possible other factors. Mati (1993), for instance, reports that 68% of the
culverts were found to discharge on slope steeper than 10% with severe erosion as result.
Regarding the surface area of the roads, a conservative width range of 5 to 10 meters was used based
on a broad approximation, which incorporates the roadside that also contributes to the amount of runoff.
At the same time, it was assumed that the whole road width can be used to collect runoff. Though this is
far from accurate, it does correct for additional runoff that is generally harvested from roadsides.
Moreover, 75% of the roads was assumed not to be suitable for road runoff harvesting, taking into
account areas with slopes of 0% or over 5%, the absence of farmland in the proximity of the road, areas
in the drylands that receive extremely low annual rainfall and possible other factors.
The total runoff volume that could be harvested with roadside drains was estimated using an average
annual rainfall of 300 mm, which according to the FAO classification (see Table 5) corresponds to the
upper range of the arid zones in Africa. A runoff coefficient of 0.2 and an efficiency factor of 0.5 were
applied for conservative estimates of runoff volumes, considering that more than half of the roads are
rural, unpaved roads. (In fact, part of the road network in sub-Saharan Africa is paved, which means that
for these roads runoff coefficients could be around 0.9, the share of paved classified roads varies per
country and is generally far below 50%; see World Bank (2012)).
The total runoff volume that culverts could collect was based on an estimated average catchment area of
1 hectare, more or less in line with the size of the catchment area of Mr Muindu Musyoka (Mutunga and
Critchley, 2001; see also Case study 1 in Chapter 4) but also taking into account the necessarily much
larger catchment area in the Tanzanian example from Hatibu et al. (2000).
25
Based on the assumption that no crop production takes place in rangelands, only the road surface in the
cultivated lands was deemed suitable for runoff harvesting with the intention to use the water for farming
purposes. To determine the potential size of the total cultivation area, a catchment/cultivation area ratio of
2/1 was used.
For both rangelands and cultivated lands the number of households that could potentially benefit from
road runoff harvesting was calculated. This was based on the following assumptions:
- One culvert can benefit one farmer household in the cultivated lands (as in the case of Muindu
Musyoka)
- One culvert can benefit at least one pastoralist household, i.e. one pan or dam can provide water
for their livestock (not based on scientific estimates)
- An average of 500 m of road is used for road runoff harvesting both in rangelands and in
cultivated lands (considering the example of Muindu Musyoka as well as the examples from
banana growers in Uganda, that use smaller stretches of road (Ngigi, 2003a))
Lastly, the average size of a household in sub-Saharan Africa of 5.3 people (Bongaart, 2001) was taken to give an estimate of the total number of people who could benefit from road runoff harvesting.
Table 7 summarises the assumptions that were made to perform the overall assessment.
26
Table 7. Summary of assumptions made to determine the potential for up-scaling road runoff harvesting
Assumption Explanation
1. Total length of rural roads is sum of classified (World Bank figures) and unclassified rural roads, and length of unclassified roads can be estimated by multiplying the length of classified roads by 1.74
The figures by the World Bank (2012) only cover ‘classified’ roads The examples from Kenya and Tanzania indicate that a large part of the road network is ‘unclassified’ and is not represented byt he World Bank figures. The rural road network in Kenya is 1.74 times the length of the classified network.
2. Road density is (fully) correlated with population density
As deserts generally have lower road densities than more densily populated areas, the known population densities in arid, semi-arid and dry sub-humid areas of sub-Saharan African (Murray et al., 1999) were used to estimate the road densities of these areas for each country.
3. Cultivated lands and rangelands make up 30 and 59% of drylands (respectively) and this amount of land cover is spread equally over all countries and regions.
Country specific information on the occurrence of cultivated lands and rangelands in the drylands of sub-Saharan Africa was not available. For this reason, the global figures reported by Millenium Ecosystem Assessment (2005) have been taken as a basis.
4. Cultivated lands are only rainfed (no land is irrigated)
Less than 5% of the agricultural land in Africa is irrigated.
5. Between 0.25 and 2 culverts can be found on a random stretch of 1 kilometre of road
This range is based on the numbers reported by Jungerius et al. (2003) and Mati (1993), who reported an average of 0.47 and 2.1 culverts per kilometre
6. Roads (plus roadsides) have a width of 5 to 10 metre
This is a broad approximation based on the limited data available.
7. 25% of both culverts and road(side) surfaces are suitable for road road runoff harvesting
This is a rough estimate that takes into account unsuitable topography, unsuitable location of farms, unsuitable local climatic conditions and other potential factors limiting the use of road runoff harvesting
8. Average annual rainfall depth is 300 mm across the drylands
Conservative estimate based on lower range of rainfall depth in semi-arid areas
9. Runoff coefficient (K) is 0.2 and efficiency factor (E) is 0.5
For reasons of simplicity, the same runoff efficiency factors were used for estimating the runoff from both culverts and road surfaces
10. Average catchment size for culverts is 1 hectare
Conservative estimate based on the estimated size of the culvert catchment of Muindu Musyoka (first case study, approximately 2 ha)
11. 1 household can benefit from 1 (suitable) culvert
Conservative estimate. Hatibu et al. (2000) show that more households can benefit from large culverts
12. 1 household can benefit from a stretch of 500 m of road (with an estimated average width of 7.5 metre)
Conservative estimate based on the estimated length of the road used by Muindu Musyoka.
13. 1 household consists on average of 5.3 persons
Estimate based on average household size in sub-Saharan Africa calculated by Bongaarts (2001)
27
4. Results
4.1 Case study 1: Muindu Musyoka
General description
Name of farmer: Mr Muindu Musyoka
Location: Kenya, Mwingi District, Kyethani Location, Mbondoni village (10 km west of Mwingi town) Coordinates: (-0.978941, 37.987897)
Annual rainfall: 250 to 500 mm
Visited: 9 - 13 May 2011
WOCAT code: KEN 022 b ; not yet recorded in the WOCAT system
The farm (or shamba) of Muindu Musyoka is located 10 km from Mwingi town. This 83 year old farmer
has been cultivating his land since 1952. Only in 1992 he started tapping runoff from a culvert that runs
under a nearby road – the one-lane motorway that leads eastwards from Nairobi, through Mwingi town to
the city of Garissa. Later, Musyoka also constructed fanya chini and fanya juu terraces: the first were
created by digging channels and throwing the soil downhill, the latter by throwing the soil uphill.
Schematically, his road runoff system looks like Figure 8.
His water harvesting technique was first described in 2000 with the WOCAT Questionnaire for SLM
Technologies (Mutunga and Critchley, 2001; the WOCAT questionnaire code is: KEN 022). Mutunga and
Critchley (2001) also mention that the technology was reported earlier by Mwarasomba and Mutunga as
early as 1995.
Figure 8. Schematic depiction of runoff flows on Muindu Musyoka’s farm Schematic drawing of the farm of Muindu Musyoka. The blue arrows points in the direction of the water flow, that starts left of the main road (a.) and is guided via a fanya chini channel (dotted line) in a neighbouring field (b.) to the fanya chini and fanya juu (striped lines) terraces on his farm land. The schoolyard and a small road leading to his farm further contribute to the amount of runoff that enters the farm land.
28
Technical performance
Conditions: Annual rainfall varies between 250 and 500 mm according to the farmer. There
are two growing seasons: from March to the middle of May, and from October to
December. The farm is located at an altitude of around 1200 m above sea level.
The savannah-like environment is hilly with slopes between 2 and 5%. The soil is
20-80 cm deep with a sandy to loamy texture; the soil is moderately fertile and
contains little organic matter. Drainage is relatively good; the water storage
capacity of the ground is considered moderately good by the farmer. It is not clear
at what level the water table lies – it has likely sunk due to the recent dry years.
The 23 meter deep well on the farm’s courtyard was empty during the visit. There
is no surface water.
Purpose: The reason for using road runoff harvesting is the lack of water for growing crops.
The land is primarily used for crop production. Musyoka also has some goats and
chicken that are fed with fodder from the land. The general purpose of this road
runoff harvesting system in combination with terraces is to enhance soil and
water conservation for improved crop production.
Measures: The first structural measures that were taken are the channel that leads from the
culvert to the field, as well as small bunds across the road that guide the runoff
towards the entry of the culvert. This was done entirely by the farmer himself. In
addition, the farmer also uses the runoff that comes from two small roads that
lead to his farm as well, one of which is connected to a schoolyard (property of
his sister). For this purpose, he has adjusted the drains along the side of these
roads (see Figure 9)
Figure 9. Pictures of Muindu Musyoka showing how runoff is redirected to his farm
The picture on the left shows Muindu Musyoka pointing out the fanya chini channel that diverts the runoff from the
culvert (where the farmer is standing) to his field. The picture on the right shows Mr Musyoka explaining how the
runoff is guided from the schoolyard to his field (in the back).
29
Figure 10. Schematic overview of the terraces of Muindu Musyoka
The figure shows the dimensions of the fanya juu and fanya chini terraces. The space between the channels is
approximately 18 meters (or 60 feet).
The fanya chini and fanya juu terraces – structural measures – have been added
to improve the distribution of the road runoff, and at the same time to prevent
surface soil erosion, soil fertility loss and the loss of runoff. The terrace channels
are 2 feet deep and 3 feet wide with bunds (juu or chini) of 1.5 foot high and 4
feet wide. The distance between the channels is approximately 18 m (see Figure
10). Due to the terraces, water is given the time to infiltrate the soil and as the
slope of the terraces slowly decreases every year, more fertile soil is conserved
in the cultivation area. The terraces are fortified with grass (species unknown4;
vegetative measure). Management measures consist of controlling the inlets to
the terrace channels during showers in order to ensure a good distribution of the
water.
In the channels Musyoka grows maize, bananas, mango, sugar cane and
cassava. On the bunds he cultivates beans and on the terraces he grows maize
and beans.
The catchment area is the sum of area adjacent to the main road that leads to the
culverts and the area represented by the small roads and schoolyard (see Figure
11). The total surface of the catchment area was estimated at 65,000 m2 (6,5
hectares) with an average slope of approximately 3%. The average runoff
coefficient (K) was roughly estimated to be 0.3, taking into account the sandy soil,
slope and vegetation. The design rainfall (Pd) for one season was set at 200 mm
(considering an annual rainfall of 250-500 mm). Taken an efficiency factor (E) of
0.7, the amount of water that could be harvested can be calculated:
4 Probably Napier grass or Makarikari grass (Ngigi, 2003: 216).
30
Water Harvested = 65,000 m2 * 200 mm * 0.2 * 0.7 = 1820 m
3
The size of Musyoka’s cultivation area (see Figure 11) was estimated at 60,000
m2 (6 ha). The actual catchment : cultivation area ratio is thus 65,000/60,000 or
1.1/1. The crop water requirement (ETc) for one growing seasons was estimated
based on the two main crops of Musyoka, i.e. for beans (400 mm) and maize
(650 mm) following the FAO Irrigation Water Management Training Manual No. 3
(FAO, 1986), and thus estimated at an average 475 mm for the long season. The
required minimum catchment/cultivation area ratio would therefore be:
Required C/CA ratio = (475 – 200) / (200 * 0.3 * 0.7) = 275 / 42 ~ 6,5/1
With such a ratio the ideal cultivation area would be 3,800 m2 (0.38 ha). This
estimate is much smaller than the actual size of Musyoka’s farmland.
Knowledge required: For the road runoff harvesting it not necessary to have a strong technical skills.
Just like the farmer did, this can be done on a trial and error basis. For the
terraces, no skilled labour is needed. However, to define the types of terraces
and the distance between the channels, farmers may need the advice from an
extension worker.
Figure 11. Catchment and cultivation area of Muindu Musyoka highlighted on a satellite image
Google Earth image of Musyoka’s farm land (indicated in green), his homestead (yellow pointer) and the estimated
catchment indicated in blue.
31
Economic viability
Conditions: The farmers living in this area are all relatively poor. Off-farm income is important
for Musyoka, who has grandchildren working in the city that send him money. The
wife of one of his sons works in a shop in town and also provides money to the
family. Farming is done for subsistence and for cash crops (maize and beans).
Seasonal cropping is combined with the cultivation of fruit trees (agroforestry).
Access to the market (and possibly also government employees and extension
workers) is relatively easy since Mwingi town is only 10 km away. Ploughing is
done by hand or with help of a zebu oxen. There is no other source of water than
rain; rainwater is also collected on the roofs of his homestead and stored in one
(leaking) concrete tank. This water is used for household purposes only.
Costs: Construction of the road runoff harvesting system was done by Musyoka himself.
The costs of hiring day workers to construct the fanya chini and fanya juu
terraces from August to October 1996 (3 months) – just before the rainy season –
were US$ 4715. Musyoka had to borough some money from his family members
to pay for this. In 2009 he spent approximately US$ 30 on day workers for the
maintenance of the channels. The maintenance costs become higher every year.
The costs of agricultural input (seeds and fertiliser) are not known.
Benefits: According to the farmer, the yields are 20 to 50% higher and the risk of failure is
much smaller. Income increases with 20-50% with the sales of maize and beans.
He needs 5-20% less fertiliser. However, the last year in which he sold bags of
maize or beans was 2007. Table 8 shows the data on yields and sales that
Musyoka recalls. He does not know in detail what he produced before 2007. In
the period 2004-2006 his yields were low; in 2003 they were somewhat better.
2002 was a good year, while yields in 2000-2001 were similar to 2003. It is
interesting to see that from 2007 no yields have been recorded – though it has
not been possible to support this information via another independent source.
During productive rainy seasons, there is less need to produce sisal ropes
(kamba – the reason why the tribe is called the Kamba) for sale on the local
market.
The benefits, both on the short and the long term, outweigh the establishment
and maintenance costs – provided, however, there is enough rain.
Disadvantages: The main disadvantage is that water is the limiting factor. As long as there is (not
enough) rain, production is impossible.
Labour for establishment and maintenance of the structures is the most
expensive factor.
5 For each amount of money, the exchange rate on the 1
st of January of the corresponding year (in this case 1993)
was used to convert KSh. to US$.
32
Table 8. Yields and sales of Muindu Musyoka during the period 1998-2011
Year Season Maize yield Beans yield Sales (and further remarks)
1998-2006 Both seasons Varying
yields
Varying
yields • No data
2007
March - May 1350 kg 540 kg • 450 kg maize sold US$ 39
October- December 1530 kg 180 kg • 630 kg maize sold for US$ 81 • (450 kg of maize destroyed by
Osama weevil )
2008-2011 Both seasons 0 0 • No sales
Timeline showing the yields and sales of maize and bean of Musyoka. Produce that was not sold or lost to weevils
was used for subsistence purposes of the farmer and his family.
Environmental friendliness
Conditions: Musyoka’s farm is surrounded mostly by farmland used by other farmers for
cultivation. It is a savannah like environment with limited biodiversity (wild
mammals, birds and insects like butterflies were very rare during the time of visit).
Benefits: The increase in production during the productive rainy season ensures a wider
ground cover, which results in a higher above and underground biomass and
adds to a higher biodiversity at the surface and in the soil. The farmer also has
the impression that evaporation from the soil surface decreased, as well as its
salinity.
Disadvantages: Musyoka is not aware of any negative (downstream) impacts on the environment.
Nevertheless, due to the fact that the water is collected from a tarmac road, there
is a risk of some oil, rubber or other pollution. This may however partly be filtered
out in the catchment area and in the channel leading to his farm.
Social acceptance
Conditions: The Technique is applied by one man from a single (large) household. Ploughing
is done by hand or with animal traction. The land is the property of Musyoka; he
has all land and water use rights. Population density is between 10-50 people per
square kilometre. There are no data on annual population growth in the region.
Origin: The idea of starting road runoff harvesting comes from Musyoka himself, though
he also received some advice from the Ministry of Agriculture and Rural
Development according to Mutunga and Critchley (2001).
Benefits: The farmer’s large family benefits from the production in times of rain. Other
farmers have benefited from the Musyoka’s knowledge of soil and water
conservation techniques: in the period from 1999 until 2007 he hosted up to 10 (!)
group visits per month. (In total, around 800 farmers have been brought by
Promoting Farmer Innovation (PFI) to his farm according to Mutunga and
Critchley (2001))
33
Disadvantages: Musyoka is not aware of consequences for his downstream neighbour. However,
in the upstream catchment area, he has a small dispute with his sister who owns
the land through which the channel runs that links the culvert to his land (William
Critchley, pers. comm.).
Another negative impact is the fact that some farmers living in the area have
become annoyed with the attention Musyoka has received as a ‘model farmer’
over the years from government employees and researchers alike (Ibid.).
Adoption: Probably thanks to the training courses that the farmer organised on his farm, 8
other farmers in the area have adopted road runoff harvesting according to
Musyoka.
Figure 12. Muindu Musyoka showing dried maize in a calabash at his homestead
34
4.2 Case study 2: Mwema Maswili
General description
Name of farmer: Mr Mwema Maswili
Location (coordinates): Kenya, Mwala District, Jathui County, 1 km northeast of Wamunyu town (-1.413974, 37.625281)
Annual rainfall: 250 to 750 mm
Visited: 18 May 2011
WOCAT code: Not yet recorded in the WOCAT system
It is the first time that this farm has been described with the WOCAT Questionnaire for SLM
Technologies. The road runoff harvesting system has been set up by Mwema Maswili in 1998. The
system is based on a roadside drain along a dust road that runs of which the runoff is guided through a
fanya chini ditch and an old gully to a pond located at the bottom of his field (see schematic drawing in
Figure 13). Just like Muindu Musyoka (Case study 1), he has added fanya juu terraces to his farm later
on. They were built along the contour lines with technical support from peace workers in 2005.
Figure 13. Schematic overview of the Mwema Maswili’s farm
Runoff is collected from the road and guided through a fanya chini ditch across his farm into a pond. Arrows indicate
the direction of the runoff flow.
35
Technical performance
Conditions: Maswili says annual rainfall varies between 250 and 750 mm. There are two
growing seasons: a short season from March until the middle of May, and a
longer season from October to December. The shamba lies between 1260 and
1275 m above sea level. Slopes in the area vary between 2 and 5%.The soil has
limited fertility, is 120 cm deep and its texture is sandy to loamy. Natural drainage
is considered sufficient. It is not clear what the ground water level is, though it is
likely very low, because drinking water comes from the river and is available from
a tap at a neighbouring farm – there is no well in use for this.
Purpose: The technical purpose of the system is first to increase water availability for
supplementary irrigation of crops and fruit trees. Second, the terraces have been
constructed to harness the rainwater that falls in situ.
The reasons for the land degradation were water and wind erosion, loss of
topsoil, gully erosion, and compaction by people walking over the unterraced
field.
Measures: The structural measures consist of a roadside drain running along the side of Mr
Maswili’s farm, which leads via a drain along the path leading to his courtyard to a
fanya chini channel that transects his shamba (see Figure 14); subsequently, the
water runs into an old gully (!) which ends up in a pond. The pond was
constructed with help of day workers and has a concrete wall on the downhill side
(see Figure 15). The pond is 10 m wide, 20 m long and 2.5 m deep which
corresponds to a volume of 500 m3. The pond has a spillway in the corner
opposite of the inlet – this spillway leads into a short fanya chini channel. At first,
water was drawn from the pond with a small diesel pump; later the farmer took
water with a jerry can. Other structural measures are the fanya juu terraces. On
the bunds of the terraces Napier grass has been planted as a vegetative
measure. The only management measure is the fact that people are not allowed
to walk over the field anymore.
Figure 14. Roadside drain and fanya chini channel on the farm of Mwema Maswili
The picture on the left shows Maswili (holding his two children) next to the roadside drain that runs along his field. On
the right Ms Rose Mueni (interpreter) shows the channel that transects Maswili’s farm and directs road runoff to the
pond.
36
Figure 15. Pond of Mwema Maswili
The white arrow shows the direction of the water flow at the inlet of the pond. The farmland is located on the right
side (uphill). The picture clearly shows that only one side (downhill) of the pond is fortified with a concrete wall.
Crops (80%) and fruits trees (20%) on the lower three terraces (0.2 ha) are
provided with water through supplementary irrigation (1 jerry can of water every
second day for each tree). On these terraces he grows maize and beans as well
as mango, lemon, pawpaw and guava tress (approximately 100 in total). On the
other terraces uphill, which are only rainfed, the farmers grows maize, beans and
pigeon peas.
The roadside drain was dug by the farmer and his son. The pond was dug bit by
bit from 1998 onwards by the farmer, his son and additional day workers, for a
period of 3-4 years. The fanya juu terraces were built by day-workers in 2005.
The pond has cracks in the floor and water is lost through the porous stone on
which it is built. It would require lining to prevent it from leaking.
The catchment area is formed by the dust road and a number of paths uphill that
lead onto this road. The surface area is roughly estimated at 10,000 m2 (1 ha).
The runoff coefficient is estimated at 0.4, taking an average slope of around 3%,
a sandy soil and no vegetation. The design rainfall (Pd) for the second, long
season of the year was estimated at 300 mm (considering an annual rainfall of
250-750 mm). Taken an efficiency factor (E) of 0.7, the potential amount of runoff
was calculated as follows:
Water Harvested = 10,000 m2 * 300 mm * 0.4 * 0.7 = 840 m
3
The size of Maswili’s cultivation area was estimated at 6,000 m2 (0.6 ha; only on
the lower part of his land supplemental irrigation is used). The actual catchment :
cultivation area ratio is thus 10,000/6,000 or 1.7/1. The crop water requirement
(ETc) was estimated at 500 mm for one season, based on the average for maize
and beans and the amount that fruit trees use, which varies between 300 and 800
mm. The minimum catchment/cultivation area ratio would therefore be:
37
Required C/CA ratio = (500 – 300) / (300 * 0.4 * 0.7) = ~ 2.4/1
With such a ratio the ideal cultivation area would be approximately 0.4 ha. This
comes close to the 0.6 ha which Maswili uses.
Knowledge required: Little knowledge is required for diverting the road runoff in the field. With
inventiveness, the farmer has constructed a fanya chini channel and incorporated
an existing gully in the system.
More difficult is the creation of a pond that is well-lined and that has proper in-
and outlets and a water pump.
The fanya juu terraces require some knowledge about the right sizes of channel
and distance between the channels. This knowledge is generally available at the
local government post (extension workers).
Economic viability
Conditions: The farmers living in this area are all relatively poor. Off-farm income becomes
more important in times of drought. Maswili sells small animal statues carved out
of wood. Another source of income is the selling of water from his pond to
farmers in the area (the last time was in 2006). The farmer has also started
keeping bees for the production of honey that has a high economic value.
Farming is done for subsistence and for cash crops (maize, beans and fruits).
The market that is closest by is about 1 km away in Wamunyu town. Extension
workers are active in the area. Ploughing is done with cows. Besides rainwater,
the farmer also buys water at a neighbouring farm when needed; this water
comes from a nearby river. Maswili collects rainwater from the roofs of the
building on his compounds, which is stored in tanks for domestic use.
Costs: Establishment of the pond cost US$ 1,260 to pay day workers over a period of
around 300 days. They were paid for digging 114 ‘spaces’ (each 24 feet long, 3
feet wide, 2 feet deep), each worth US$ 11. Costs were entirely born by the
farmer.
Establishment of terraces (approximately 500 m of fanya juu terraces) cost US$
173 in 2005.
The maintenance activities include the re-excavation of the roadside drain in
2011, by two labourers (among whom his assistant), which took 3 full time days
for a total cost of US$ 18. Re-excavation of the fanya juu channels by labourers
cost US$ 35.
The farmer also hires people to water the trees: one man is paid US$ 1.7 per day,
and another man is hired on a continuous basis for US$ 35 per month.
Maswili’s wife spends 2-3 days planting seeds and seedlings: 10 kg beans (US$
12), 6 kg maize (US$ 17) and 1 package of sukuma seedlings (very cheap) and 2
kg cowpeas every two seasons (US$ 1.20).
Benefits: In 1998 the maize yield was 270 kg (3 bags); in 2010 he obtained a yield of 1890
kg (21 bags), of which he sold 10 bags for in total US$ 260 and kept 11 bags for
his family. Due to increase in fodder production he also increased the number of
cows from 2 in 1998 to 6 in 2010. He uses the manure of his livestock to fertilise
38
the land, thereby decreasing the need to buy fertiliser. Because of the recent
drought has had to sell some of his livestock.
The rainwater harvesting system has allowed him to starting growing fruit trees.
Last season (February 2011), he earned US$ 123 from selling mangos from his
mango trees (a normal yield is gives US$ 74). The variety of agricultural products
has increased since he started collecting road runoff.
Labour constraints and workload have decreased slightly. This has allowed him
to invest some time and money in the production of honey (since 2007).
When rainfall is sufficient, the farmer sells the excess water in the pond to his
neighbours: in January and February 2006, he earned $ 111.
The farmer is very positive about the short and long term benefits of his soil and
water conservation measures, taking into account both the investments for
establishment and maintenance of the structures.
Disadvantages: The farm pond has cracks in the floors and water seeps through the porous
stone. It would cost about US$ 980 to line the pond. Adding the costs for the
necessary extra digging, the total expenditure would amount to around US$
1,200. Mr Maswili is nonetheless very interested, especially in setting up a
greenhouse close to his pond (see case study D), which would allow the fast
recuperation of the investment costs.
Environmental friendliness
Conditions: The savannah-like environment showed little sign of a rich fauna. The area
located downhill from Maswili’s land is rangeland.
Benefits: One of the benefits from this system is that the farmer has been able to start
beekeeping, which represents both an increase in fauna as well as in the
provision of an ecosystem service: pollination.
The increase in the varieties of fruit trees has led to a richer agrobiodiversity. The
natural fertiliser from the livestock has likely made the soil more rich in carbon
and in soil biodiversity.
It is not clear whether the increase in runoff downhill has benefited the flora and
fauna on the bare land that is located in the downstream area next to Maswili’s
shamba.
Disadvantages: The farmer is not aware of any negative impacts on the environment.
39
Social acceptance
Conditions: Population density is between 10-50 people per square kilometre. Data on annual
population growth in the region were not found. Land and water use rights belong
to the farmer. Manual labour and animal traction are used to cultivate the land.
Maswili does not know of other farmers in the area using road runoff harvesting.
Origin: Road runoff harvesting is an invention of Maswili. For the construction of the
fanya juu terraces, the farmer followed the example of his neighbour Mr Mulei
Ndolo and asked peace workers for advice on how to construct them.
Benefits: In times of rain, the pond is a source of water also for other people. The
pollination service provided by the honey bees also benefits other farmers in the
area. Because of the prior investment and the subsequently increased
production, the farmer has been able to provide jobs to day workers and a fixed
employee. His increased purchasing power (he bought extra cows for instance)
was also good for the local economy.
Disadvantages: Social disadvantages are not known.
Adoption: The farmer says no other farmers have adopted road runoff harvesting. His
neighbour, he says, is “too lazy” to invest in it.
40
4.3 Four other sites in Machakos District
Farm of Samuel Mweu Maingi (site #3)
Location (coordinates): Kenya, Machakos District, a few kilometres from Masii town (-1.46092, 37.439492)
Visited: 17 May 2011
The owner of the farm is Mr Samuel Maingi (64 years old and an old chief). The road runoff harvesting
system is done with roadside drains from small sandy roads, a pond and a rope-and-washer pump for
irrigation of four fanya juu terraces (see Figure 16). Runoff from the road flanking is led into a parallel
within-field channel through mitre. This channels directs the runoff into a pond. Before entering the pond,
the water passed through a small silt trap which lets the water into the pond6.
The pond was established in 2004, yet there are no data regarding the total establishment and
maintenance costs. The pond is approximately 5 m wide, 10 m long and 4 m deep and has a total
volume of approximately 200 m3. It is lined with 0.8 cm thick, high quality polythene that cost US$ 4.75
per m2 in Nairobi; total costs of lining were approximately US$ 570. The pond was constructed over a
period of one year in 2004. The lining has a ten year guarantee and still hasn’t shown any leakages.
There is a separate overflow pipe on the downhill side.
His harvests fail because of insufficient amounts of rainwater or because of (previous) leakage from the
ponds. According to Samuel Maingi, the payback time is only 3 years.
According to Maingi, one shower is enough to fill the entire pond. He pumps the water with a simple rope-
and-washer pump7 up to four terrace levels or 3 metre higher and irrigates approximately 0.8 ha with the
harvested water.
The farmer grows sukuma, maize, cabbages, onions, tomatoes, papayas, mangos, sweet potatoes,
‘sweet peppers’, eggplants, cowpeas, chickpeas. He uses fertilizer and manure. He hired an extension
worker to make the planning profile for the season that started in October 2011.
This road runoff harvesting approach has been adopted by at least two farmers as far as Maingi is aware.
However, these farmers used local, thinner and less expensive lining of the pond that is less resistant.
6 According to Alex Oduor (ICRAF), who joined the visit, a T or Y junction just before the silt trap would be better, as it
would allow water to leave the pond from the same side, which prevents sedimentation in the pond. 7 It would be beneficial to use a rope-and-washer pump with two pulleys instead of one (see Malesu et al. 2007), this
would allow the farmer to get the water as high as the upper terrace in one effort. The current pump can be made more efficient by adding a larger bowl on top of the pump (where the water comes out and flows into the irrigation pipe), to prevent water loss when it is pumped to fast.
a. Farm of Samuel Maingi (site #3)
b. Farm of a neighbour of Samuel Maingi (site #4)
c. Farm of David Kyula (site #5)
Figure 16. Schematic overview of three of the four additional
The three drawing (a., b. and c.) correspond to the farms of Samuel Maingi, his
(respectively). No schematic overview of Mr. Sammy’s farm (site #6) was made.
runoff.
41
Farm of Samuel Maingi (site #3)
Schematic overview of three of the four additional farms
The three drawing (a., b. and c.) correspond to the farms of Samuel Maingi, his neighbour and David Kyula
). No schematic overview of Mr. Sammy’s farm (site #6) was made. Arrows indicate the direction of the
neighbour and David Kyula
Arrows indicate the direction of the
42
Farm of a neighbour of Samuel Maingi (site #4)
Location (coordinates): Kenya, Machakos District, a few kilometres from Masii town (-1.46092, 37.439492)
Visited: 17 May 2011
The name of this farmer was not mentioned by Mr Samuel Maingi. The farmer uses a lined pond in
combination with a greenhouse that was paid for and is managed by a group of farmers called ‘Mango
Integrated’, to which Maingi also belongs. Structural measures are the roadside drains that are combined
with a silt trap, a lined pond, a treadle pump, an elevated (foldable) tank and a greenhouse with drip
irrigation system. The pond is ´fed´ with runoff from a roadside drain and from channel that probably
collects water from the same road (see Figure 16). Maintenance of the pond is carried out by people who
were trained in 2004 by RELMA-in-ICRAF.
The greenhouse is provided by Amiran Ltd. as a ‘package’ together with treadle pump, tubes for drip
irrigation (for growing tomatoes), and an easily transportable water tank (made of synthetic material that
can be folded)8. A complete greenhouse package (tent, tank, pipes, and training during the first season)
costs US$ 1,800-2,500. Tomatoes are the main crop produced in the greenhouses; yields can amount to
6-8 ton per ha. According to Mr Peter Kamau (the local agricultural extension officer) the payback time is
just one season.
The greenhouse and drip-irrigation system is part of an initiative of World Vision International (WVI), a
Christian development organization from the USA, and two other partners: Amiran Kenya Ltd and Mwala
IPA. According to Mr Frank Meme (pers. comm.), Mwala IPA provides loans to farmers who are
interested in adopting the package. Amiran Kenya Ltd. constructs the greenhouse systems and visits
each site on a monthly basis during the first 12 months to provide technical assistance. WVI further
assists farmers in Operation and Maintenance (O&M) of the system. The objective of this initiative is to
ensure food security and increase farmers’ incomes.
Twenty groups of farmers have thus far adopted this system, indicating a strong interest of farmers to
commonly engage in such a scheme. They grow tomatoes, capsicum, onions and other cash crops.
Nevertheless, there are many ponds in the area that are used for fish farming – which turns out to be little
profitable because of the low (local) demand, as the Kamba people do not have a habit of eating fish.
However, smallholder farmers are afraid of investing in a greenhouse and don’t want to count further than
one year ahead.
Farm of David Kyula (site #5)
Location (coordinates): Kenya, Machakos District, a few kilometres from Mwala town (-1.352017, 37.450258)
Visited: 18 May 2011
The farmer who developed this road runoff harvesting system is Mr David Kyula. The system combines
roadside drains and a small culvert to collect sheet runoff (see Figure 16). Annual rainfall is 400-1000 mm
according to the farmer, with sometimes 96 mm falling in one day.
Runoff is collected from a small dust road that runs uphill for about a kilometre. Part of the water also
passes through a small culvert under the convex road, after which it is led it via a large earthen silt trap
and a small silt trap into a large unlined pond. The large silt trip is a U-shaped dam made out of soil, that
8 See also http://www.amirankenya.com/
43
filters the water as the water can only leave on the same side where it also enters the trap. The pond is
40 m long, 25 m wide and 4 m deep and hence has a capacity of approximately 4000 m3. Because the
pond is unlined, water seeps through the walls and creates the perfect environment for a vegetable
garden on one side (downhill). Because the pond is constructed uphill with respect to the culvitavation
area, it is easy to transport the water for supplementary irrigation: water is poured with a bucket in a
barrel that stand next to the pond, and that is connected to a hose that is used downhill to fill other barrels
or jerry cans that are used for the irrigation of maize. The water is used to irrigate approximately 2.83 ha
of land.
It took 14 men 3 months (full time) in 2004 to construct the pond. The total cost of US$ 2,700 were paid
by David Kyula himself.
Due to the seepage through the side of the pond, there is not only enough water for Kyula’s vegetable
garden, but also for the field with fruit trees that lies next to his land. His neighbor thus literally enjoys the
fruit of Kyula’s labour. The variety of plants and availability of surface water in this vegetable garden also
attracted insects like bees and butterflies.
It is not known whether other farmers in the area have adopted similar techniques.
Farm of Mr Sammy (site #6)
Location (coordinates): Kenya, Machakos District, a few kilometres from Mwala town
Visited: 18 May 2011
This site belongs to a certain Mr Sammy and is managed by another man also known as Mr Sammy. No
schematic drawing was made of his site.
Road runoff is collected in a large underground tank of 95 m3. It is pumped into two plastic tanks at a
height of approximately 2.5 m with a 2.5 hp petrol pump. The stored runoff is used mainly to provide
supplementary irrigation to mango and orange trees; maize and peas are mostly rainfed. The farmer has
also adopted a zero grazing policy.
Construction of the sophisticated water storage installation has cost more or less US$ 6,000. The farmer,
convinced of the benefits of rainwater harvesting, also collects rainwater from all his roofs for domestic
purposes.
(The farm also has a (Dutch) biogas installation in an underground tank covered with metal boards, which
was constructed by a contractor. The costs of US$ 430 were for a large part paid by the government
(US$ 345) and the rest by the farmer himself.)
44
4.4 Suitable roads and culverts in sub-Saharan Africa
Table 9 presents the estimated road network that is present in the drylands of sub-Sarahan Africa. Of the
estimated total 5.55 million kilometres of road, approximately half (2.65 million kilometres) are located in
the drylands. Of these the majority are located in the semi-arid areas (1.65 million kilometres), while only
a small part (ca. 210,000 kilometres) is found in the arid areas. An estimated 89% or 2.36 million
kilometres of the dryland roads are located in rangelands and cultivated lands. The length of the roads in
the drylands of each country was calculated by adjusting the average road density per country, assuming
that road density is positively correlated with population density. Without this adjustment, the estimated
total length in the drylands would be 11% higher.
Looking at all the rangelands and the cultivated lands of sub-Saharan Africa, the road networks have an
estimated length of around 1.57 and 0.80 million kilometres respectively.
At the country level, there are major differences. The countries located in the wet, tropical zones of sub-
Saharan Africa (e.g. Congo, Gabon and Sierra Leone) have no drylands. Countries with (nearly) all roads
located in the drylands are, for instance, Botswana, Namibia and The Gambia. In Kenya (underlined in
Table 9), it is estimated that 36.6% of the roads can be found in the drylands, of which the majority can be
found in dry sub-humid and semi-arid zones (both around 29,000 kilometres) and a small part in the arid
lands (around 3,800 kilometres). Countries with the largest estimated dryland road networks are South
Africa, Zimbabwe, Burkina Faso and Nigeria.
In Table 10 results are shown which are based on estimated numbers of culverts that can be found under
dryland roads. For the rangelands, between 100,000 and 400,000 culverts in sub-Saharan Africa are
expected to be potentially suitable for runoff harvesting, while this number is estimated between 50,000
and 200,000 in the cultivated areas. The volume of runoff that these culverts can produce together is in
the range of 0.15 and 0.59 cubic kilometres. Assuming that only one household can exploit the runoff
from one culvert, a total of 370,000 households could benefit from the additional water. The highest
estimates can, logically, be found in the countries with the largest road networks. For Kenya (underlined
in Table 10), somewhere between 3,000 and 14,000 culverts could be suitable for runoff harvesting,
which could potentially benefit (an average of) 8,000 households.
The results of the assessment for the suitable road surface are presented in Table 11. In total, between
300,000 and 600,000 hectares of road surface may be available for runoff harvesting with roadside
drains. In the cultivated areas, some 75,000 hectares of land (taking the average of the lower and upper
range) could potentially be flooded or irrigated with the generated runoff (assuming a C/CA ratio of 2/1).
The estimated potential runoff volume that could be collected with roadside drains lies between 0.09 and
0.18 cubic kilometres. The (averaged) number of households that could benefit from the runoff collected
through roadside drains is 1.8 million. Looking at the Kenya for instance, around 41,000 households may
be able to collect road runoff. The potential cultivation area in Kenya’s cultivated lands would be around
1,700 ha.
Roughly estimated, a total of 2.2 million households could thus benefit from approximately 0.5 cubic
kilometre of road runoff. Assuming an average size of 5.3 persons per household (Bongaarts, 2001), 11.7
million people would be able to directly benefit from road runoff harvesting.
45
Table 9. Length of total road network in the drylands
Country* Total
roads
rural
Total in
drylands
Share drylands
of total roads
rural
In dry sub-
humid
areas
In semi-
arid
areas
In arid
areas
In
rangelands
(59% of
drylands)
In cultivated
land (30% of
drylands)
km km km km km km km km
Angola 140,813 45,341 32.2% 11,104 33,559 678 26,751 13,602
Benin 52,022 4,822 9.3% 3,417 1,405 0 2,845 1,447
Botswana 70,635 70,635 100.0% 0 68,524 2,111 41,675 21,191
Burkina Faso 253,252 247,787 97.8% 51,458 192,411 3,917 146,194 74,336
Burundi 33,738 1,285 3.8% 1,285 0 0 758 385
Cameroon 79,011 17,706 22.4% 5,357 12,344 6 10,447 5,312
Cape Verde 3,696 3,581 96.9% 0 0 3,581 2,113 1,074
Central African Rep 66,553 1,020 1.5% 755 265 0 602 306
Chad 109,520 94,053 85.9% 32,442 37,898 23,712 55,491 28,216
Comoros** 2,409 0 0.0% 0 0 0 0 0
Congo 46,546 0 0.0% 0 0 0 0 0
Congo Dem Rep 420,275 9,277 2.2% 9,277 0 0 5,473 2,783
Cote d’Ivoire 224,505 0 0.0% 0 0 0 0 0
Djibouti 8,392 8,308 99.0% 0 14 8,294 4,902 2,492
Equatorial Guinea 7,885 0 0.0% 0 0 0 0 0
Eritrea 10,979 10,851 98.8% 0 7,989 2,862 6,402 3,255
Ethiopia 121,455 44,195 36.4% 21,838 16,601 5,756 26,075 13,259
Gabon 25,107 0 0.0% 0 0 0 0 0
Gambia The 10,246 10,246 100.0% 8,676 1,569 0 6,045 3,074
Ghana 299,852 42,371 14.1% 42,371 0 0 24,999 12,711
Guinea 121,425 694 0.6% 694 0 0 410 208
Guinea-Bissau 9,460 0 0.0% 0 0 0 0 0
Kenya 169,606 62,047 36.6% 29,199 29,093 3,756 36,608 18,614
Lesotho 16,264 11,873 73.0% 10,420 1,453 0 7,005 3,562
Liberia 29,023 0 0.0% 0 0 0 0 0
Madagascar 136,427 15,699 11.5% 3,792 11,907 0 9,262 4,710
Malawi 42,305 25,302 59.8% 23,837 1,466 0 14,928 7,591
Mali 61,534 58,925 95.8% 6,880 42,825 9,220 34,766 17,677
Mauritania 30,299 23,146 76.4% 0 2,893 20,253 13,656 6,944
Mauritius 5,657 0 0.0% 0 0 0 0 0
Mozambique 83,046 45,557 54.9% 31,362 14,195 0 26,879 13,667
Namibia 115,270 110,937 96.2% 0 93,008 17,929 65,453 33,281
Niger 51,880 50,949 98.2% 0 23,104 27,844 30,060 15,285
Nigeria 528,982 201,708 38.1% 45,513 152,363 3,831 119,008 60,512
Rwanda 38,354 2,797 7.3% 2,797 0 0 1,650 839
Sao Tome & Principe 876 0 0.0% 0 0 0 0 0
Senegal 40,591 36,702 90.4% 2,110 31,382 3,210 21,654 11,011
Sierra Leone 30,939 0 0.0% 0 0 0 0 0
Somalia 60,510 56,487 93.4% 0 21,232 35,255 33,327 16,946
South Africa 991,428 776,626 78.3% 153,338 599,129 24,160 458,209 232,988
Sudan 32,582 27,127 83.3% 1,858 12,076 13,193 16,005 8,138
Swaziland 9,840 6,614 67.2% 4,926 1,688 0 3,902 1,984
Tanzania 283,947 147,683 52.0% 95,715 51,968 0 87,133 44,305
Togo 31,903 9,979 31.3% 9,979 0 0 5,887 2,994
Uganda 193,703 20,940 10.8% 18,372 2,568 0 12,354 6,282
Zambia 182,847 95,562 52.3% 72,885 22,677 0 56,382 28,669
Zimbabwe 266,317 255,932 96.1% 95,704 159,895 333 151,000 76,780
TOTALS 5,551,908 2,654,766 797,359 1,647,504 209,903 1,566,312 796,430
% total rural roads: 47.8% 14.4% 29.7% 3.8% 28.2% 14.3%
*Not included are Seychelles and South Sudan; ** Comoros includes island of Mayotte. Sources: World Bank (2012), Murray et al. (1999), Millenium Ecoystem Assessment (2005)
This table shows data on the length of the road network (in kilometres) in the drylands of sub-Saharan Africa. The total length in the drylands is based on the estimates for dry sub-humid, semi-arid and arid arids, that are presented in the shaded columns. Also indicated are the estimated lengths of roads located in rangelands and cultivated lands.
46
Table 10. Estimates per country of number of culverts, potential runoff volumes and number of households that could benefit from road runoff
Assumptions:
Culverts in rangelands Culverts in cultivated
lands
Total runoff volumes Households
Number
(0.25/km,
25%
suitable)
Number
(1/km, 25%
suitable)
Number
(0.25/km,
25%
suitable)
Number
(1/km, 25%
suitable)
Low estimates High estimates 1 household per
culvert
Country Units Units Units Units m3 m
3 (number)
Angola 1,672 6,688 850 3,401 2,522,116 10,088,463 6,305
Benin 178 711 90 362 268,225 1,072,901 671
Botswana 2,605 10,419 1,324 5,298 3,929,073 15,716,293 9,823
Burkina Faso 9,137 36,549 4,646 18,584 13,783,134 55,132,534 34,458
Burundi 47 189 24 96 71,453 285,814 179
Cameroon 653 2,612 332 1,328 984,917 3,939,668 2,462
Cape Verde 132 528 67 269 199,215 796,860 498
Central African Rep 38 151 19 77 56,762 227,046 142
Chad 3,468 13,873 1,763 7,054 5,231,674 20,926,698 13,079
Comoros* 0 0 0 0 0 0 0
Congo 0 0 0 0 0 0 0
Congo Dem Rep 342 1,368 174 696 516,028 2,064,112 1,290
Cote d’Ivoire 0 0 0 0 0 0 0
Djibouti 306 1,225 156 623 462,136 1,848,544 1,155
Equatorial Guinea 0 0 0 0 0 0 0
Eritrea 400 1,601 203 814 603,598 2,414,393 1,509
Ethiopia 1,630 6,519 829 3,315 2,458,372 9,833,490 6,146
Gabon 0 0 0 0 0 0 0
Gambia The 378 1,511 192 768 569,912 2,279,648 1,425
Ghana 1,562 6,250 794 3,178 2,356,909 9,427,637 5,892
Guinea 26 102 13 52 38,627 154,509 97
Guinea-Bissau 0 0 0 0 0 0 0
Kenya 2,288 9,152 1,163 4,654 3,451,392 13,805,567 8,628
Lesotho 438 1,751 223 890 660,419 2,641,674 1,651
Liberia 0 0 0 0 0 0 0
Madagascar 579 2,316 294 1,177 873,265 3,493,060 2,183
Malawi 933 3,732 474 1,898 1,407,448 5,629,791 3,519
Mali 2,173 8,691 1,105 4,419 3,277,691 13,110,765 8,194
Mauritania 854 3,414 434 1,736 1,287,496 5,149,984 3,219
Mauritius 0 0 0 0 0 0 0
Mozambique 1,680 6,720 854 3,417 2,534,123 10,136,491 6,335
Namibia 4,091 16,363 2,080 8,320 6,170,874 24,683,497 15,427
Niger 1,879 7,515 955 3,821 2,834,022 11,336,088 7,085
Nigeria 7,438 29,752 3,782 15,128 11,220,001 44,880,002 28,050
Rwanda 103 413 52 210 155,593 622,373 389
Sao Tome & Principe 0 0 0 0 0 0 0
Senegal 1,353 5,414 688 2,753 2,041,566 8,166,264 5,104
Sierra Leone 0 0 0 0 0 0 0
Somalia 2,083 8,332 1,059 4,237 3,142,087 12,568,349 7,855
South Africa 28,638 114,552 14,562 58,247 43,199,829 172,799,315 108,000
Sudan 1,000 4,001 509 2,034 1,508,918 6,035,672 3,772
Swaziland 244 976 124 496 367,895 1,471,580 920
Tanzania 5,446 21,783 2,769 11,076 8,214,884 32,859,537 20,537
Togo 368 1,472 187 748 555,056 2,220,225 1,388
Uganda 772 3,089 393 1,570 1,164,775 4,659,101 2,912
Zambia 3,524 14,095 1,792 7,167 5,315,631 21,262,526 13,289
Zimbabwe 9,438 37,750 4,799 19,195 14,236,242 56,944,969 35,591
TOTALS 97.894 391.578 49.777 199.107 147.671.360 590.685.441 369.178
This table shows data on the estimated number of culverts in rangelands and cultivated lands, as well as the runoff volumes that these could generate assuming a catchment area of 1 ha (see text for more information). The estimated (averaged) number of households that could potentially benefit from road runoff harvesting in each country is shown in the last column.
47
Table 11. Estimates per country of road surface, potential cultivation area (in cultivated lands), potential runoff volumes and number of households that could benefit from road runoff
Assumptions:
Road surface in
rangelands
Road surface in
cultivated lands
Cultivation area
(in cultivated
lands)
Total runoff volumes Households
5 m width 10 m
width
5 m width 10 m
width
C/CA = 2:1 Low
estimates
High
estimates
1 each 500 m
of road
Country ha ha ha ha ha m3 m
3 (number)
Angola 3,344 6,688 1,700 3,401 1,275 1,513,269 3,026,539 30,265
Benin 356 711 181 362 136 160,935 321,870 3,219
Botswana 5,209 10,419 2,649 5,298 1,987 2,357,444 4,714,888 47,149
Burkina Faso 18,274 36,549 9,292 18,584 6,969 8,269,880 16,539,760 165,398
Burundi 95 189 48 96 36 42,872 85,744 857
Cameroon 1,306 2,612 664 1,328 498 590,950 1,181,900 11,819
Cape Verde 264 528 134 269 101 119,529 239,058 2,391
Central African Rep 75 151 38 77 29 34,057 68,114 681
Chad 6,936 13,873 3,527 7,054 2,645 3,139,005 6,278,009 62,780
Comoros* 0 0 0 0 0 0 0 0
Congo 0 0 0 0 0 0 0 0
Congo Dem Rep 684 1,368 348 696 261 309,617 619,234 6,192
Cote d’Ivoire 0 0 0 0 0 0 0 0
Djibouti 613 1,225 312 623 234 277,282 554,563 5,546
Equatorial Guinea 0 0 0 0 0 0 0 0
Eritrea 800 1,601 407 814 305 362,159 724,318 7,243
Ethiopia 3,259 6,519 1,657 3,315 1,243 1,475,023 2,950,047 29,500
Gabon 0 0 0 0 0 0 0 0
Gambia The 756 1,511 384 768 288 341,947 683,894 6,839
Ghana 3,125 6,250 1,589 3,178 1,192 1,414,145 2,828,291 28,283
Guinea 51 102 26 52 20 23,176 46,353 464
Guinea-Bissau 0 0 0 0 0 0 0 0
Kenya 4,576 9,152 2,327 4,654 1,745 2,070,835 4,141,670 41,417
Lesotho 876 1,751 445 890 334 396,251 792,502 7,925
Liberia 0 0 0 0 0 0 0 0
Madagascar 1,158 2,316 589 1,177 442 523,959 1,047,918 10,479
Malawi 1,866 3,732 949 1,898 712 844,469 1,688,937 16,889
Mali 4,346 8,691 2,210 4,419 1,657 1,966,615 3,933,230 39,332
Mauritania 1,707 3,414 868 1,736 651 772,498 1,544,995 15,450
Mauritius 0 0 0 0 0 0 0 0
Mozambique 3,360 6,720 1,708 3,417 1,281 1,520,474 3,040,947 30,409
Namibia 8,182 16,363 4,160 8,320 3,120 3,702,525 7,405,049 74,050
Niger 3,757 7,515 1,911 3,821 1,433 1,700,413 3,400,827 34,008
Nigeria 14,876 29,752 7,564 15,128 5,673 6,732,000 13,464,001 134,640
Rwanda 206 413 105 210 79 93,356 186,712 1,867
Sao Tome & Principe 0 0 0 0 0 0 0 0
Senegal 2,707 5,414 1,376 2,753 1,032 1,224,940 2,449,879 24,499
Sierra Leone 0 0 0 0 0 0 0 0
Somalia 4,166 8,332 2,118 4,237 1,589 1,885,252 3,770,505 37,705
South Africa 57,276 114,552 29,123 58,247 21,843 25,919,897 51,839,794 518,398
Sudan 2,001 4,001 1,017 2,034 763 905,351 1,810,701 18,107
Swaziland 488 976 248 496 186 220,737 441,474 4,415
Tanzania 10,892 21,783 5,538 11,076 4,154 4,928,931 9,857,861 98,579
Togo 736 1,472 374 748 281 333,034 666,068 6,661
Uganda 1,544 3,089 785 1,570 589 698,865 1,397,730 13,977
Zambia 7,048 14,095 3,584 7,167 2,688 3,189,379 6,378,758 63,788
Zimbabwe 18,875 37,750 9,597 19,195 7,198 8,541,745 17,083,491 170,835
TOTALS 195,789 391,578 99,554 199,107 74,665 88,602,816 177,205,632 1,772,056
This table presents estimates of the road surface per country that would be available for road runoff harvesting divided amongst rangelands in cultivated lands. Also listed are estimates of total runoff volumes for rangelands and cultivated lands combined. The cultivation area was calculated based on the average road surface in the cultivated lands. The last column shows the number of households that could benefit from road runoff harvesting, in both rangelands and cultivated lands, assuming that on average a stretch of 500 m road is used per household.
48
5. Analysis
5.1 Technical performance
All six sites are located in arid, semi-arid or dry sub-humid areas at an altitude between 1100 – 1300 m
above sea level. The land is hilly with slopes of 2 to 5%. Soils have limited fertility and are sandy to
loamy, allowing for good infiltration of rainwater as well as drainage. Problems that are encountered are
related to the loss of fertile soil due to water and wind erosion. Agroforestry is common practice,
especially by those farmers who have started implementing soil and water conservation techniques.
Many farms in both Mwingi and Machakos Districts have adopted fanya juu and or fanya chini terraces,
though with varying degrees of efficiency. The farmers that were visited, however, have correctly
introduced the terraces, following the contours lines and choosing the right distance between the
channels (depending on the slope of their land). Only David Kyula (site #5) has not created an elaborate
terrace system.
Road runoff harvesting is practiced by each farmer in a different way. Three phases in the treatment of
runoff can be distinguished: collection, intermediate storage and distribution (see Table 12). Besides
Muindu Musyoka (site #1), all farmers first collect the water in a pond. The latter have the advantage that
they can use the pond water to bridge dry spells during the growing season, while Musyoka’s system
simply increases the water in the soil immediately after a shower, thus without being able to control the
timing of irrigation.
Table 12. Overview of rainwater harvesting elements on the six farms
Site Farmer Collection Storage Distribution Crops
#1 Mr. Muindu Musyoka
Culvert Drains
No storage Flooding of fanya chini and fanya juu terraces
Maize, beans, banana, sugar cane, cassava
#2 Mr. Mwema Maswili
Drains Pond (unlined, downhill) Supplementary irrigation with jerry can
Mango, lemon, pawpaw, guava
#3 Mr. Samuel Mweu Maingi
Drains Pond (lined, with silt trap, downhill)
Rope-and-washer pump and hose
Fruit trees, beans, peas, vegetables
#4 Unknown (a neighbour of Mr Samuel Maingi)
Drains Pond (lined) Tread pump, ‘water tower’, greenhouse with low-head drip irrigation
Tomatoes
#5 Mr. David Kyula Drains Small culvert
Pond (unlined, with large earthen and small silt trap, uphill)
Buckets and hose (+seepage to neighbouring field)
Maize, vegetables
#6 Mr. Sammy Drains Underground tank and two aboveground tanks (plastic, 2,5 m above ground, with diesel pump)
Hose (?) Mango, orange
This table summarises which rainwater harvesting elements are used on each site (collection, storage and
distribution of runoff) and lists the main crops that are grown in each system.
Lined ponds have the clear benefit of not losing water through seepage. Evaporation takes places in all
ponds however, as none of them are covered. The other farmers use simple techniques to irrigate their
crops and trees with the water from the pond: varying from a bucket or jerry can to a treadle or rope-and-
washer pump. The most advanced irrigation system is used on the farm of Samuel Maingi’s neighbour
(site #5) and his colleague farmers: they have invested in a greenhouse with drip irrigation system. This
system allows for the production of high value cash crop like tomatoes, capsicum and onions.
49
Tools that are used for (manual) construction and maintenance of the structures are generally simple and
include hoe, shovel, panga and wheel barrow.
The technical performance of each site is shortly described in Table 13. For the first two case studies the
actual C/CA ratios have also been estimated. Muindu Musyoka’s farm and Mwela Maswili’s farm have
rather small ratios (1.1/1 and 1.7/1, respectively), considering an expected ratio of 2/1 to 10/1 for external
catchments (Critchley and Siegert, 1991). The calculated sizes of the two areas of Musyoka’s farm (6.5
ha/6.0 ha) are also different from the original estimates by Mutunga and Critchley (2001; 10 ha/5 ha). The
rough estimates of the optimal ratios (6.5/1 and 2.4/1, respectively.) indeed fit better with average ratios
for rainwater harvesting with external catchments. Nevertheless, the calculated ratios are rough estimates
and would require detailed sampling and analysis for establishing more accurate actual and optimal
ratios.
Table 13. Description of the technical performance of each site
Site Technical performance of measures for runoff collection, storage and use
#1 Musyoka’s flooding approach works well but is entirely based on water conservation in the soil. Supplementary irrigation during dry spells in the rainy season is not possible with this system. Harvesting of runoff from across the road is also not optimal because of the water lost due to infiltration in the catchment area (resulting in a lower runoff coefficient).
#2 Maswili has constructed a pond that gives him enough water in times of rain. The pond, however, works far from optimal, because a lot of water is lost through cracks in the floor and wall. Evaporation also affects the availability of stored water. Water enters the pond unfiltered. Owing to the fact that the pond is located downhill, irrigation is done by moving the water uphill with a jerry can.
#3 Maingi has a pond lined with polythene which has proven to be a durable material. The pond has a ‘one-way’ silt trap where water can only enter the pond. An outlet at the side prevents water from overflowing the pond, but also makes that dirty water enters the pond through the silt trap. Evaporation is the only factor contributing to water loss from the pond. The pond is located downhill which means the farmer has to use a (leaking) rope-and-washer pump to transport the water four terraces higher. Nevertheless, the road runoff harvesting represents an (important) improvement for this farmer.
#4 Maingi’s neighbour has a lined pond more or less at the same level as the greenhouse. Evaporation is a cause of water loss from the pond. Water distribution is efficient due to the drip irrigation system in combination with the greenhouse-tent that reduces evapotranspiration from the tomato plants.
#5 Kyula uses an innovative silt-trap made of earth in combination with a smaller silt-trap. It is not clear where the outlet is in case of overflow. The large pond could be improved by lining and covering it. However, the advantage of water seeping into the ground is that the neighbouring cultivation area – which belongs to the farmer himself and to his neighbour – directly receives water, allowing for a thriving vegetable garden and fruit trees, respectively. The distribution system is functional yet very simple with a bucket-hose construction. The advantage is that the pond is located uphill in relation to the cultivation area.
#6 Sammy has a sophisticated storage system that is composed of two elevated tanks and a diesel pump. It is not clear whether this height advantage is also used for irrigation purposes.
The use of roadside drains and culverts requires limited knowledge, at least at first. With trial-and-error,
both Muindu Musyoka and Mwela Maswili have started tapping road runoff. The set up of Musyoka’s farm
has changed very little since 2000.
The creation of a pond requires some basic knowledge. The volume and size of the pond should be
optimal for the amount of runoff that is collected.
50
The technical knowledge required for the greenhouse is relatively complicated and requires support from
external agents. To provide the necessary knowledge, trainings were organized and technical support
offered during the first year. If not properly dealt with, the greenhouse could become useless.
The additional measures like fanya juu and fanya chini terraces can best be implemented by seeking
advice from extension officers, peace workers or researchers that are active in the region.
In summary, the technical performance of all sites is in general sufficient but could be improved with small
adaptations (e.g. lining of pond, or a better pump) as well as more with more sophisticated measures
such as drip irrigation kits. The required knowledge is minimal for runoff collection, while runoff storage
and efficient distribution tools may require more advanced knowledge to ensure proper instalment and
use.
5.2 Economic viability
Smallholder farmers living Mwingi and Machakos District are relatively poor. Off-farm income plays a role
and varies in kind. Production is first for subsistence and in a second place for selling cash crops. Water
supply is limited and agriculture is predominantly rainfed. Only one groundwater irrigation system was
observed near Mwingi town (this site was not included in this study); the well was created by peace
workers next to a sand river. The size of the cropland is generally limited to a few hectares. Land is
cultivated using manual labour and animal traction. Agricultural services are limited and depend on the
availability and pro-active approach of extension workers and development agents. Small towns and
cities have markets were agricultural goods are sold.
The costs for establishing and maintaining a road runoff harvesting system depend on how elaborate the
system is. The creation of roadside drains is done by farmers themselves and only requires a time
investment. Establishing a pond already requires a larger investment – which becomes higher if proper
lining is put in place. Adding more sophisticated irrigation tools further increases the size of the
investment. Additional measures like fanya juu and fanya chini terraces represent a relatively low cost.
Table 14. Benefit-costs analysis of the road runoff harvesting systems of Musyoka and Maswili
Cost item RRH system of Muindu Musyoka
RRH system of Mwema Maswili
Construction terraces 471 173 Construction pond N.A. 1260 Total investment costs
471 1433
Overall maintenance 5 5 Average return seasonal return 26 200 Net benefit on investment per season
19 195
Payback time 52 seasons (26 years!) (assuming US$ 10 of net benefit
can be used per season)
8 seasons (4 years)
(assuming US$ 185 of net benefit can be used
per season)
51
A ‘back-of-the-envelope’ benefit-cost analysis was carried out for the two case studies (see Table 14.).
For Musyoka, average seasonal maintenance costs were roughly estimated to be US$ 5 (based on the
most recent repair in 2009 (see Table 8. Average seasonal return was calculated based on the fact that
yields have varied greatly since the establishment of the road runoff harvesting system, and by assuming
that the 2007 yields were ‘high’ yields – the average seasonal return was thus estimated at only US$ 26
(which is half of the average of both 2007 seasons). For Maswili, the seasonal maintenance costs were
also estimated at US$ 5. Economic benefits however were estimated at US$ 200, considering the recent
income generated with the sales of maize, mango and water. To calculate the pay-back time in the
absence of information regarding the benefits and costs of their farming system prior to the introduction of
road runoff harvesting, it was assumed that part of the net seasonal benefit (US$ 10) is spent on activities
that would take place also without the using road runoff. The pay-back time for Musyoka thus becomes a
remarkably long period of 52 seasons, while the pay-back time for Maswili is approximately 8 seasons.
Interestingly, Musyoka evaluated the overall benefits both on the short and long-term as ‘positive’. Maswili
said he is ‘very positive’ about the short and long-term benefits.
The third and fourth site (of Maingi and his neighbour) showed promising results: the pay-back time for
Maingi’s pond was estimated at 6 seasons, while he said the system of his neighbour (with the
greenhouse and drip-irrigation system) only required 3 seasons to pay back the initial investment of
somewhere between US$ 1,700 – 2,700. Lastly, David Kyula and Mr Sammy also seemed very positive
about the returns generated with their water reservoirs, despite the relatively high investment costs.
The marketing infrastructure is in place for traditional crops (maize, beans) and ‘new’ crops (e.g. mango,
tomato). Tomatoes, for instance, are economically competitive in Masii town. Maingi (site #3) notes that
some farmers also practice aquaculture in their ponds – without as much commercial success, however,
because fish does not sell well on local markets as it is not an element of traditional diets.
Extra income can also be generated without crop production as the case of Maswili demonstrates: the
extra time and money he has available allows him to produce and sell honey.
The overall evaluation of costs and benefits by the farmers was deemed positive to very positive. For the
two case studies, the economic effects are positive both in the short and long term (i.e. beyond 10 years).
The farms of Maingi and his neighbour (sites #3 and 4) have a pay-back time of six and three seasons (or
3 and 1.5 years), respectively.
Thus, despite a wide variation in the use of collection, storage and application techniques as well as
largely differing initial investments, all visited sites seem to be economically viable. Farmers do not keep
track of the exact benefits and costs. Road runoff harvesting has enabled farmers to diversify crop
production and successfully develop new sources of income.
5.3 Environmental friendliness
The major benefit of collecting runoff from road on the environment is, looking at the six visited sites,
probably the increase in agricultural production due to improved soil and water conservation. The richer
crop and fodder diversity is likely to have a positive impact on the diversity of organisms in the soil, and
therefore also on the carbon and biomass stored under- and aboveground. A benefit of Musyoka’s farm
may also be that (severe) soil erosion and gully formation at the outlet of the culvert is foregone, thus
sparing the land of his sister.
The availability of flowering plants and (downstream) water in the vegetable garden of Kyula attracts
insects like butterflies and bees and thus contributes to the local biodiversity. The fact that Maswili (site
#2) has been able to start keeping bees also contributes to the diversity of animals and plants (that are
pollinated by the bees).
52
Table 15. Environmental impacts and related Ecosystems Services of the studied road runoff harvesting
sites
Environmental impact
Ecosystem Service (ES) ES type
Increased plant growth and diversity
Biological production, carbon storage, more biodiversity
Provisioning; Regulating
Increased soil biodiversity Improved nutrient cycles, more biodiversity
Supporting; Regulating
Increased insect diversity (bees and other insects)
More pollination, more biodiversity Regulating
Increased soil moisture and streamflows
Water availability Regulating; Provisioning
Increased amount of soil nutrients and reduced soil erosion
Nutrient availability Supporting
Table 15 shows the observed environmental impacts in relation to ecosystem services in the drylands.
Negative impacts on the environment have not been observed. However, aquaculture that is practiced in
ponds on other farms in Machakos may have negative environmental impacts due to use of fish feed
(ecological footprint) and possibly of hormones.
5.4 Social acceptance
The social circumstances are more or less similar for the two case studies and the four additional sites.
The technology is applied in an agricultural area with between 10-50 people per square kilometre. Land
and water rights seem to belong to the farmers (it has not been able to confirm this at the last four sites).
Land is usually cultivated with manual labour and sometimes with help of animal traction.
The first two road runoff harvesting sites, which have been developed independently Musyoka and
Maswili, represent two cases of local innovation. Additional measures (terraces, pond) were added later
with help of external agents. For the other sites it is not clear where the idea of using runoff from drains
originated, yet is not unlikely that this has also been done through trial and error by the farmers
themselves. Further improvements and extensions of the systems (with lined ponds, silt traps, pumps,
irrigation system and greenhouse) have been done with the support of extension workers.
Social impacts can be divided into on-farm and off-farm impacts. On-farm, families of the farmer benefit
from the increased food production. Disadvantages for people living on the farm have not been recorded.
Gender issues were not observed – though all farmers who applied road runoff harvesting were men.
Off-farm, the six sites show that both positive and negative consequences can be associated with road
runoff harvesting. The negative impacts include:
• Upstream neighbours may be affected because water is guided through their field
• The wave of attention that Musyoka (site #1) has received over the past decade, has also led to
negative reactions by farmers in the area, who would like to be treated equally
53
The positive impacts include:
• Neighbours benefit from the collected water that may be sold by a farmer
• Farmers in the area can benefit from the knowledge of a farmer, especially if the farmer
organises on-site trainings
• Other farmers may also benefit from the increased pollination (due to the increased bee
population) and availability of honey
• The creation of additional measures (terraces, ponds) generates temporary labour opportunities
• The increased production may also create more sustainable jobs, e.g. for planting and irrigation
activities
• Greenhouses require a pooled investment of several farmers, which may lead to more social
cohesion and knowledge exchange, and allow for larger projects
Figures related to adoption of similar road runoff harvesting technologies by other farmers are scarce
(see
Table 16). Musyoka (#1) says he knows of 8 farmers who have started collecting road runoff. Maswili (#2)
on the other hand is not aware of any other farmer who has taken over his approach – his neighbour (who
gave him the idea of using fanya juu terraces) is “too lazy” to tap road runoff. The greenhouse kit has
been purchased by 20 other (groups of) farmer(s) in the area of Machakos where site Maingi’s farm is
located (#4).
Table 16. Adoption rates and reasons for successful or unsuccessful adoption
Site District Adoption Reason
#1 Mwingi 8 farmers* - Extension work - On-farm training by Muindu Musyoka
#2 Machakos 0 farmers - Lack of interest #4 Machakos 20 community projects with
greenhouses - Marketing of greenhouses by World
Vision and their partners - Training by World Agroforestry Centre
(ICRAF) - Active involvement local administration
* According to Mutunga and Critchley (2001), even around 40 farmers have adopted road runoff harvesting following the example of
Muindu Musyoka.
No information was available on adoption rates on the other three sites.
5.5 Factors that may influence the adoption of road runoff harvesting
The decision of a farmer to adopt a new technology like road runoff harvesting depends on a wide range
of factors – moreover, poor smallholder farmers in semi-arid environments tend to be risk averse due to
the many uncertainties they face (Ngigi et al., 2005a). Many authors (see e.g. Critchley, 2009) emphasize
the need for taking into account the local socio-economic and cultural conditions that determine whether
farmers will adopt a technology or not. This study did not focus specifically on the adoption factors of
farmers; nevertheless, some potential factors influencing the adoption can be retrieved from the input
farmers at the different sites provided (see Table 17). The table, in a way, represents an extended
benefit-cost analysis incorporating technical, economic and social factors. The factors are given a positive
or a negative balance according to examples in this study.
54
Table 17. Overview of potential adoption factors derived from data gathered at the six farms
Description of adoption factor + - Technical factors
Simple collection techniques (drains / diversion channels)
Risk of erosion
Simple storage techniques (e.g. unlined/lined pond)
More sophisticated storage facility -> Lack of adequate knowledge and tools Possibility of failing structures
Simple runoff application techniques More sophisticated runoff application techniques -> Lack of adequate knowledge and tools
Good technical guidance from external agents
N.A.
Economic factors N.A. High establishment and maintenance costs (labour, materials)
More or less equal agricultural input required
N.A.
Increased production – increased income
N.A.
Quick pay-back time Slow pay-back time Creation of new sources of income (e.g. beekeeping)
N.A.
N.A. Need for credit (family, bank or otherwise) Social factors General interest in new technologies;
Idea (in part) based on personal / local knowledge;
Scepticism towards new technologies
Creation of employment N.A. Need for cooperation with other farmers Need for cooperation with other farmers General interest in change / innovation (leader)
General disinterest in change / innovation (lagger)
N.A. Risk of conflict with upstream or downstream neighbour
Clearly established land and water rights
N.A.
Ngigi et al. (2005a) report that, amongst the technical factors that influence the adoption of water
reservoirs, farmers may refrain from constructing water reservoirs because of the perceived risks of water
loss due to seepage and evaporation. The farm pond of Samuel Mweu Maingi shows that, if proper
support from extension services is available, ponds are adequately lined with durable materials.
Establishment and maintenance of sophisticated drip-irrigation / greenhouse systems require specialist
knowledge (Ngigi, 2008). Such knowledge can be provided if development agents – such as World Vision
International, ICRAF and Amiran Ltd. – cooperate effectively.
High investment costs for labour and/or material are often major constraints for the uptake of rainwater
harvesting technologies (Ngigi, 2003a). As the case studies suggest, the channels and drains for the
collection and diversion of runoff can be built by the farmer for free, provided he has time to do this. A
similar situation can be observed with the banana plantation of in Uganda (Ibid.). The major costs are
associated with the (optional) storage and distribution technologies. Also, complementary soil and water
conservation measures (e.g. terracing) may also be costly. Absence of credit facilities is another potential
economic barrier for adoption (Critchley, 2009).
Openness to innovation is also a factor influencing the uptake of new technologies like road runoff
harvesting. Muindu Musyoka and Mwela Maswili both started diverting road runoff through trial and error.
Only later they learned about soil and water conservation measures like fanya juu and fanya chini
terraces, which they ‘added’ to their water harvesting system years later. In contrast, Ngigi (2003) argues
that farmers using in-situ soil and water conservation measures are more likely to adopt a storage
rainwater harvesting system. Both ways seem thus to be possible for farmers to adopt (road) runoff
55
harvesting. Following Critchley (2007), Musyoka and Maswili can be considered farmer innovators. For
their innovations, they use ´hybrid´ knowledge, i.e. local ideas supported by scientifically proven
techniques. Their willingness to adopt is high compared to other farmers in the area (e.g. Maswili´s
neighbour) – they are early adopters.
With respect to the other farmers it is not clear who initiated the innovation process. The installation of
greenhouses with drip-irrigation kit is actively being promoted by Amiran Ltg and/or World Vision
International in Machakos region, which probably explains the fact that the groups of farmers (including
Maingi’s neighbour) have become acquainted with this technology.
5.6 Sensitivity analysis of the sub-Saharan Africa-wide assessment
The first main outcome of the assessment is that around 0.5 cubic kilometre of runoff could be collected
from roads and road sides. The second main result is that roughly estimated, a total of 2.2 million
households (or 11.7 million people) could benefit from road runoff harvesting. These two figures are
based on a number of assumptions. Table 18 gives an overview of the 13 assumptions and the impact
changes in these assumptions could have on 1) the potential gross runoff volume and 2) the total
estimated number of households that can potentially make use of road runoff harvesting.
This sensitivity analysis demonstrates that the estimated potential runoff volume generated through road
runoff harvesting through road runoff harvesting can drastically change if assumptions are not taken into
account or if upper or lower ranges of the assumptions are taken. In the most pessimistic scenario, less
than 0.026 cubic kilometre of gross runoff could be available, while under the most favourable conditions
1.5 cubic kilometre or more could be use for road runoff harvesting.
The estimated number of households that could be supported by road runoff harvesting measures is
similarly sensitive to changes in the assumptions. In the least favourable situation, less than 114,000 (or
less than 5.2% of 2.2. million) households can potentially benefit from road runoff harvesting. In contrast,
in the most optimistic scenario harvesting road runoff could help over 5.9 million (269% of 2.2 million)
households.
56
Table 18. Sensitivity of the outcomes (potential runoff volume and number of households) of the sub-
Saharan Africa-wide assessment
Assumption
Change to the assumption
Impact on 1) estimated potential runoff volume and 2) total number of households that could benefit from road runoff harvesting
1. Total length of rural roads is sum of classified (World Bank figures) and unclassified rural roads, and length of unclassified roads can be estimated by multiplying the length of classified roads by 1.74 (i.e. total rural roads is 2.74 times World Bank figures)
Countries do not have roads other than those reported by the World Bank
Reduction with 64%
2. Road density is (fully) correlated with population density
Road density is equal across the whole country
Increase with 11%
3. Cultivated lands and rangelands make up 30 and 59% of drylands (respectively) and this amount of land cover is spread equally over all countries and regions
Cultivated lands and rangelands make up less or more of drylands
Increase with max. 11% or reduction that could be larger in theory
4. Cultivated lands are only rainfed (no land is irrigated)
Cultivated lands are rainfed for 95% (NB. rangelands are not included)
Decrease with max. 1.7%
5. Between 0.25 and 2 culverts can be found on a random stretch of 1 kilometre of road (average 1.12 per kilometre)
Average 0.25 or average 2 culverts per kilometre
Decrease or increase with 78%
6. Roads (plus roadsides) have an average width of 7.5 metre
Average 5 or average 10 m Decrease or increase with 33%
7. 25% of both culverts and road(side) surfaces are suitable for road road runoff harvesting
Less or more Decrease or increase
8. Average annual rainfall depth is 300 mm across the drylands
Average annual rainfall depth is lower or higher across the drylands
No impact on number of households (in this assessment) Decrease or increase of runoff volume
9. Runoff coefficient (K) is 0.2 and efficiency factor (E) is 0.5
Runoff coefficient is higher, in particular on paved roads
Increase
10. Average catchment size for culverts is 1 hectare
Average catchment size is smaller or larger
No impact on household (in this assessment) Decrease or increase of runoff volume
11. 1 household can benefit from 1 (suitable) culvert
More than 1 household can benefit from 1 culvert
Increase
12. 1 household can benefit from a stretch of 500 m of road (with an estimated average width of 7.5 metre)
More than 1 household can benefit from a stretch of 500 m (for instance when only a few infiltration pits are used by each farmer)
Increase
13. 1 household consists on average of 5.3 persons
Less persons per household benefit from the road runoff harvesting (e.g. Tiffen et al. (1992) reported an average of approximately 4 persons per household;
No impact on the number of households (decrease of some 20% or more in number of people)
57
6. Discussion
6.1 Addressing the research questions
The research carried out for this thesis focused on the question what the potential is for practicing and up-
scaling road runoff harvesting in sub-Saharan Africa. More specifically, the aim of this thesis is to give an
answer to the following two sub-questions:
1) What is the performance of existing road runoff harvesting systems in terms of sustainability?
2) What is the (bio)physical potential for up-scaling the use of road runoff harvesting in the drylands
of sub-Saharan Africa?
The following two sections address these questions in the same order. Subsequently, the experience of
using the WOCAT Questionnaire for SLM Technologies in combination with the TEES-test is described in
the subsequent section. The last section presents the elements of the sub-Saharan African-wide
assessment that require further refinement.
6.2 Performance of road runoff harvesting sites
The outcomes of the TEES-test suggest that road runoff harvesting – with roadside drain(s) or from
culvert(s) – is a welcome addition to the existing yield-increasing measures that smallholder farmers can
benefit from to better cope with the unreliable and erratic rainfall in the arid and semi-arid regions of sub-
Saharan Africa. While the two case studies were chosen to evaluate road runoff harvesting through
culverts and with roadside drains, the other four sites only shed more light on the different ways roadside
drains can be used to harvest runoff. It should be re-emphasized that this study has focused only on
farms were road runoff harvesting has (successfully) been adopted. Examples of failures have not been
identified either prior or during the fieldwork. The results are in line with the promising prospects of other
case studies that were found in literature.
Table 19. Structural adjustments that could make road runoff harvesting structures more efficient.
Structural measure Benefit Investment required
Improve / introduce terraces Improved water distribution and conservation
Low
Adapt cultivation area to the catchment area (i.e. improving the C/CA ratio)
Improved water use efficiency Low
Add / improve silt traps at the pond inlet (e.g. with Y or T inlet)
Less siltation of pond; creation of fertile “green soup”
Low
Create an (uphill) pond Water available for supplemental irrigation
Medium – High
Line pond / improve lining Prevention of seepage Medium Cover pond Prevention of evaporation Medium Use better hand/foot pump (e.g. rope-and-washer pump or treadle pump)
Efficient water use Low
Introduce low-head drip irrigation Efficient water use Medium - High Use a greenhouse Efficient water use High
This is not to say that the road runoff harvesting systems in this study perform perfectly well. Many are
the small or large technical modifications that could be made to make existing systems more efficient and
effective. For instance, Mutunga and Critchley (2001) point out that making the channels on Musyoka’s
58
farm shallower would allow more runoff to spill over onto his land (in fact, this suggestion was made by
farmers who visited his farm and evaluated his land management measures). Table 19 lists some of the
changes that could be made to the structures. Besides structural modifications, other measures
(agronomic, vegetative and management-related) could also be taken to enhance the efficiency of the
systems (see e.g. WOCAT, 2007).
From an economic investment perspective, the returns from selling more – and more diverse –
agricultural produce seem to justify the farmers’ decision to adopt the road runoff harvesting system. Pay-
back times seem to differ greatly, depending on the type of runoff collection, storage and distribution. For
well-managed greenhouses, pay-back times of 1 season may even be possible (Ngigi, 2009, referring to
a document of the Organic Farmer). Besides the example of Ngigi (2003a: 218), no other studies on the
economic viability of road runoff harvesting were found to complement these results. Few detailed
economic assessments of rainwater harvesting technologies in general – either at the farm level (e.g.
Barron, 2004; Fox et al., 2005; Ngigi et al., 2005; Hatibu and Mahoo, 2000) or at an aggregate
(watershed or community) level – have been carried out up to date (Critchley, 2009). The general
feedback regarding road runoff harvesting is that labour represents the major investment cost for
resource-poor farmers (Ngigi, 2003a; Critchley et al., 1999; ICRAF, 2012). This is supported by the two
case studies. However, more sophisticated road runoff harvesting systems which incorporate lined ponds,
drip irrigation kits and greenhouses, involve relatively high equipment costs. A comprehensive benefit-
cost analysis of the case studies and other sites is needed to confirm these preliminary findings.
Analysis of the environmental impacts shows that road runoff harvesting may contribute to several
ecosystem services that are characteristic for Africa’s drylands (Safriel et al., 2002; see Box 1). Negative
impacts on the environment, biodiversity and ecosystem services’ functioning were not recorded for the
six sites. The lack of direct downstream neighbours may explain why, on the farms of Muindu Musyoka
and Mwema Maswili, changes in downhill water provision have not been perceived. Nevertheless,
downstream impacts on the surface (and sub-surface) flows need to be seriously considered as the case
studies described by Ngigi (2003a) demonstrate.
From a social point of view, the upstream-downstream impacts on the six sites are limited to a minor
conflict on the farm of Muindu Musyoka. As other studies have shown, however, there is a clear potential
for conflict between farmers and even between communities when road runoff harvesting is practiced on
wider scale (Ngigi, 2003a).
6.3 Potential for up-scaling road runoff harvesting in sub-Saharan Africa
Road runoff harvesting can only be practiced by those farmers and pastoralists whose land is located in
the proximity of a road. This sets a limit to the potential for up-scaling road runoff harvesting. Road runoff
harvesting should be seen as an additional (water harvesting) technology that could benefit a selected
group of smallholder farmers and pastoralists. (A large variety of rainwater harvesting technologies exists
that smallholder farmers can use to upgrade their rainfed farming systems. These are all adapted to the
prevailing local conditions and can thus each support a selected number of farmers or pastoralists.) The
preliminary estimates presented in this study exclude the opportunities and barriers that exist at the
social, economic and environmental level and thus do not include, for instance, the potential downstream
impacts that up-scaling could trigger.
Considering the physical suitability of roads, the results of the sub-Saharan Africa-wide assessment
suggest that 2.2 million households or 11.7 million people could benefit from road runoff harvesting. This
figure represents 3.6% of the total population living in the drylands (Murray et al., 1999). This percentage
is higher if only the people who directly depend on agriculture or pastoralism, are taken into account. Due
to the considerable number of assumptions that were necessary for this assessment, it is important to
59
realise that these outcomes present only a rough estimate of the potential for up-scaling road runoff
harvesting. Indeed, the sensitivity analysis shows that these figures merely represent an indication of the
potential for upgrading the collection and use of road runoff. The potential runoff from roads in sub-
Saharan Africa, around 0.5 cubic kilometre, represents approximately 0.01 % of the gross volume of
annual runoff that is generated in Africa as a whole – some 5,195 cubic kilometres (Malesu et al., 2006).
However, it is not known what percentage of this total runoff in Africa is used for agriculture. It was not
possible to quantify the potential impact of up-scaling road runoff harvesting on rainfed agriculture in sub-
Saharan Africa.
As the sensitivity analysis in the previous chapter shows, the outcomes must be regarded with care. A
first, important consideration is that the estimated road lengths in the rangelands and cultivated lands
may significantly differ from the current estimates. First, this is because the total road length is based on
the assumption that ‘unclassified’ rural roads have not been taken into account. Though this may be true
for Kenya, this remains to be verified for all other countries. If this assumption is proven wrong, a more
than 60% lower estimate of the road network length would be the result. Second, the share of rangelands
and cultivated lands is based on world averages. These shares will most likely differ from country to
country. Third, the road lengths have been estimated assuming that road density is fully correlated with
population density. A more accurate estimate of road densities in the drylands could positively or
negatively affect the present results.
Another consideration is that the expected runoff volumes are based on several assumptions. An annual
rainfall of 300 mm was taken to estimated runoff volumes in the drylands as a whole. As this is the upper
limit of rainfall in the arid zones, higher rainfall depths can be expected for the semi-arid and dry sub-
humid zones. In turn, higher runoff volumes could benefit more land and/or more people. Also, the size of
the catchment area of culverts was roughly set at 1 hectare. Depending on the layout of the river basin
and the position of the road, the catchment area of a culvert may be smaller or larger than 1 hectare. This
is also reflected by the size and number of culverts on a given stretch of road. Similarly, the catchment
area represented by the surface of road and roadsides may be very different and depends on the slope,
width and length of the suitable parts of both road and roadside. These factors will in the end determine
what the total amount of runoff is that can be collected from road surfaces and culverts.
Lastly, the estimates of the number of households that could benefit are based on the assumption that
one culvert or an average stretch of 500 metre road can benefit one household (or 5.3 people).
Considering the potentially large difference in catchment area size and hence runoff volumes, the
potential number of households may largely differ from the estimated 2.2 million. In principle, road runoff
harvesting can be practiced using, for instance, only a few banana planting pits. Also, a large culvert may
provide enough runoff for several farmers at a time.
6.4 Experience of using WOCAT and the TEES-test
The WOCAT Questionnaire for SLM Technologies is very long and detailed, which requires a lot of time
and effort from both interviewer and interviewee. This is also pointed out by Schwilch et al. (2011). Filling
in the questionnaire requires experience in asking the right questions, especially when the questions and
answers have to be translated. Furthermore, analysis of benefits and costs is not straightforward (Ibid.).
Incorporating the elements of the WOCAT Questionnaire for SLM Technologies into the four categories of
the TEES-test (plus a ‘general’ category) and a limited number of sub-categories seems to have the
following advantages:
60
1) Comparison of data between different questionnaires is facilitated due to the limited number of
categories; this includes comparison with data from a revisited site (i.e. monitoring and
evaluation) – it is easier to point out the differences
2) More emphasis is given to the social and environmental impacts, which often receive less
attention than technical and economic aspects. These aspects are important to take into account
when the sustainability of a technology is assessed. In addition, these aspects are also directly
related to the potential for (wide-scale) adoption.
3) It is more obvious when new elements have been added (such as the C/CA ratio)
4) Conditions (general context) are clustered and separate from characteristics (measures,
knowledge required, benefits, disadvantages etc) of the Technology
5) Analysis of benefits and costs and/or disadvantages is more straightforward, also because
quantitative and qualitative data from the 2nd
and 3rd
section of the questionnaire are combined.
6) Presentation / communication of the questionnaire data is facilitated, i.e. it is not necessary to
refer to four-digit questions
7) Comparison/combination with other tools is less complicated, for instance with a Social Cost-
Benefit Analysis, an Environmental Impact Assessment, (Valuation of) Ecosystem Services,
sustainability criteria of ESTs
This is the first study that combines WOCAT with the TEES-test. The TEES-test itself is not a fully
developed tool and needs further refinement to turn it into a (strong) scientific tool. Linking it with WOCAT
seems to be a good start to find answers to the questions related to the technical, economic,
environmental and social performance.
6.5 Refining the sub-Saharan Africa-wide suitability assessment
The present assessment gives a first, preliminary indication of the physical potential for up-scaling road
runoff harvesting in sub-Saharan Africa. This potential varies from country to country. For a more
comprehensive assessment, the following information needs to be taken into consideration for each
country:
- The length of classified and unclassified rural roads
- The road density per dryland area
- The share of rangelands and cultivated lands per dryland area
- The topography of the area (exclude slopes where road runoff harvesting cannot be
practiced)
- The number of culverts (from national or regional road administrations)
- Data from ground truthing (to adjust estimates regarding e.g. average road width, number of
suitable culverts, size of culverts, share of suitable road surface, size of catchment for both
culverts and road surface, presence and size of gullies, size of cultivation areas, size of pans
or other reservoirs in rangelands and cultivated areas)
- Length of road that is constructed each year and number of culverts that are place
- Length of road that is maintained each year and number of culverts that are (re)placed
Besides these physical characteristics of roads, other aspects should also be studied to better quantify
the real potential for up-scaling. These aspects include technical capacity of farmers, type(s) of crop
produced, level of wealth, access to credit, access to markets, environmental state of the land and
potential upstream-downstream impacts.
61
7. Conclusions
Two general forms of road runoff harvesting can be distinguished. The first, more common form is
collecting runoff from road surfaces with roadside drains. The second form is road runoff harvesting from
a culvert, which concentrates runoff on the upstream side of a road and releases it on the lower side of
the road. Road runoff harvesting, in most cases, emanates from the tinkering mind of innovative
smallholder farmers.
The case studies (including the four additional sites that were visited) suggest that road runoff harvesting
is performing well and can indeed be considered as a welcome, complementary technology for a selected
number of smallholder farmers to cope with the unreliable and erratic rains in the drylands of sub-
Saharan Africa. It is primarily a simple technology that can easily be adopted by farmers – provided of
course that their farm is located in the vicinity of a road. The case studies show that indigenous
knowledge is often combined with scientific expertise. Runoff is either used directly for flooding the farm
field (runoff farming) or stored for supplemental irrigation. In a second instance, more sophisticated
adaptations to runoff harvesting systems can be made, e.g. by adding water reservoirs and water
distribution tools. The technology is very flexible and can be adapted to the local conditions. These
findings are corroborated by the (sporadic) information on road runoff harvesting found in literature.
Farmers interviewed for this study are overall positive about the impacts of their road runoff systems.
Nevertheless, the technical performance, economic viability, environmental friendliness and social
acceptance differ per case. Negative environmental impacts have not been recorded. Analysis of
adoption factors points at the high establishment and maintenance costs as a critical factor.
Comprehensive (technical, economic, environmental and social) benefit-costs analysis of these and other
case studies is needed to confirm these outcomes.
The estimated potential for up-scaling road runoff harvesting in sub-Saharan Africa is large: around 2.63
million kilometres of roads are located in the drylands (rangelands and cultivated areas only). If only 25%
of these roads would be suitable for collecting runoff, still vast volumes of runoff could be harvested from
the road surface. Together with the estimates of the number of culverts along these roads, these results
suggest that roughly 2.2 million households could benefit from the additional ‘green’ (for crops) or ‘pink’
(for livestock) water flows arising from the approximately 0.5 cubic kilometre of runoff. Studies at the local
level are required to determine the feasibility of applying road runoff harvesting on a case-by-case basis.
As more and more people living in the drylands of other continents are facing water scarcity, farmers in
sub-Saharan Africa may become world leaders in upgrading rainfed agriculture with simple, low-cost
water harvesting technologies like road runoff harvesting.
62
8. Recommendations
8.1 Further research
Based on the research carried out for this thesis, the following recommendations can be made for further
research on road runoff harvesting:
• Document more and different designs of road runoff harvesting systems.
• Monitor runoff flows to estimate actual runoff volumes, monitor pollution of runoff, monitor crop
performance, monitor the impacts on livelihoods, the community and the natural environment.
Include all relevant technical, economic, environmental and social aspects of road runoff
harvesting.
• Focus on long-term research projects: include monitoring and evaluation (M&E) activities over a
period of several years.
• Do a full benefit-cost analysis of road runoff harvesting sites, including social and environmental
factors, based on a large sample size and preferably on data collected over longer periods of
time. Lare Division in Kenya could be a potential target area, because many of the hundreds of
farm ponds are known to collect runoff from roads and have already been mapped (Malesu et al.,
2006). Use GPS and GIS to determine the exact size of catchment and cultivation areas.
• Further analyse the factors that lead to adoption or to non-adoption. Provide further insight into
the adoption process, for instance with regard to early and late adopters. Make an inventory of
both success stories and failures.
• Study the upstream and downstream impacts of road runoff harvesting, at the community level
and at the watershed level.
• Following the preliminary assessment of roads in sub-Saharan Africa presented (the present
study), do a GIS mapping study for sub-Saharan Africa on the potential of roads and culverts for
road runoff harvesting, similar to the study of Mati et al. (2006) that focused on the potential of
rainwater harvesting in Africa.
• Support such a region-wide study with GIS-studies focused on smaller regions (e.g. Machakos
District, Kenya), to map in detail which areas could be used as catchment and cultivation areas.
• Link the data from local case studies and GIS mapping with local data on demographic, climatic,
socio-economic, political and cultural data to determine the local potential for road runoff
harvesting.
• Identify suitable funding mechanisms for up-scaling road runoff harvesting (e.g. through micro-
credit or merry-go-round schemes).
In addition to these research needs related to road runoff harvesting, there also seems to be a need for
standardising the definitions (and thus boundaries) of arid, semi-arid and dry sub-humid areas, as well as
drylands as a whole.
8.2 Policy-making
The outcomes of this study highlight some aspects that are also relevant for policy-makers. It is
recommended that:
63
• Road runoff harvesting is streamlined into the policies and activities of relevant ministries, i.e.
ministries that deal with (railway and road) infrastructure, agriculture, water and the environment.
• Local administrations are made aware of the opportunities of using road runoff harvesting (e.g. as
part of integrated water resources management (IWRM) plans in watersheds).
• Road runoff harvesting is further promoted at supranational level, such as at the African
Ministerial Conference on Water (AMCOW).
• Monitoring and evaluation (M&E) is also done at the level of policy implementation.
• An (agro-) environmental impact assessment is commissioned prior to (rail) road construction or
maintenance activities, and an long-term agreement is reached with neighbouring (farmer)
communities about the management of road runoff (from roadside drains and/or culverts). On one
hand, this could help preventing erosion, gully-formation and pollution; on the other hand it may
provide farmers with extra ‘green’ flows.
• Funding agents (such as the World Bank and the African Development Bank) incorporate an
agro-environmental impact assessment into their guidelines for road construction and
maintenance9, including suggestions for socially accepted management plans that deal with road
runoff harvesting. In addition, road network evaluation and decision making tools that are
available online could be upgraded to also consider the possibilities for road runoff harvesting.
• Credit facilities are put in place to allow farmers to invest in road runoff harvesting technologies
(including reservoirs, drip-irrigation kits and greenhouses).
8.3 Development and extension work
Development agents (such as inter-governmental organisations, non-governmental organisations,
networks, associations and civil society organisations) and extension workers can also be involved in the
further promotion and development of road runoff harvesting schemes. Developments agents include the
United Nations Environment Programme (UNEP), the United Nations Development Programme (UNEP),
the Food and Agriculture Organisation (FAO), World Vision International (WVI), the Southern and Eastern
Africa Rainwater Network (SearNet), and the Greater Horn of Africa Partnership (GHARP) that involves
rainwater associations located in Ethiopia, Kenya, Somalia, Tanzania and Uganda.
It is recommended that these agents:
• Promote the various options of using road runoff harvesting amongst the smallholder farmers in
sub-Saharan Africa, e.g. through FAO’s Farmer Field Schools.
• Incorporate road runoff harvesting as a complementary technology in their programmes, plans
and projects, e.g. in the Promoting Farmer Innovation (PFI) methodology.
• Develop business plans for smallholder farmers to adopt road runoff harvesting, e.g. like the
plans WVI has developed in collaboration with local partners who provide a greenhouse/drip-
irrigation kit and the necessary credit. See for instance:
http://www.amirankenya.com/index.php?option=com_content&view=article&id=305
• Include M&E as a standard element of projects; request the active involvement of farmers in the
M&E activities.
9 See e.g.:
http://web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTTRANSPORT/EXTROADSHIGHWAYS/0,,contentMDK:20483189~menuPK:1097394~pagePK:148956~piPK:216618~theSitePK:338661,00.html
64
References
African Development Bank (AfDB) (2007) Assessment of best practices and experiences in rainwater harvesting. Rainwater harvesting handbook. Tunis, Tunisia: AfDB.
Agarwal A. and Narain, S. (eds) (1997) Dying Wisdom: rise, fall and potential of India’s traditional water harvesting systems. Centre for Science and Environment, New Delhi, India, 404 pages
Barron, J. and Okwach, G. (2005) Run-off water harvesting for dry spell mitigation in maize (Zea mays L.): results from on-farm research in semi-arid Kenya. Agricutlural Water Management 74: 1-21.
Bittar, O.J. (2001) Water conservation and harvesting – Busia experience. Water Conservation, Harvesting and Management (WCHM) in BUsia District, Kenya – A minor field study. Soil and Water Conservation Branch, Ministry of Agriculture.
Boers, D. and Ben-Asher, J. (1982) Review of rainwater harvesting. Agricultural Water Management 5: 145-158.
Bongaarts, J. (2001) Household Size and Composition in the Developing World. Population Council., New York, USA. Available at: http://www.popcouncil.us/pdfs/wp/144.pdf
Bouma, J.A., et al., The downstream externalities of harvesting rainwater in semi-arid watersheds: An Indian case study. Agric. Water Manage. (2011), doi:10.1016/j.agwat.2011.02.010
Critchley, W.R.S. (1991) Looking after our land. Soil and water conservation in Dryland Africa. Ed. Olivia Graham. Oxfam, 1991. Available at http://www.fao.org/docrep/x5301e/x5301e00.htm#Contents.
Critchley, W.R.S. and Siegert, K. (1991) Water Harvesting: A Manual for the Design and Construction of Water Harvesting Schemes for Plant Production. FAO, Rome.
Critchley, W.R.S., Reij, C. and Turner S.D. (1992) Soil and Water Conservation in Sub-Saharan Africa: towards sustainable production by the rural poor. IFAD, Rome and CDCS, Amsterdam.
Critchley, W.R.S., Cooke, R., Jallow, T., Lafleur, S., Laman, M., Njoroge, J., Nyagah, V. and Saint-Firmin, E., (1999) Promoting Farmer Innovation. Nairobi: RELMA WorkShop Report no 2, Nairobi, Kenya.
Critchley, W.R.S. 2007. Working with farmer innovators. A practical guide. Technical Centre for Agricltural and Rural Cooperation (CTA), Wageningen, The Netherlands.
Falkenmark, M. (1989) The Massive Water Scarcity Now Threatening Africa—Why Isn't It Being Addressed? AMBIO 18(2): 112–20.
Falkenmark, M. (1995) Land-water linkages - A synopsis. in Land and`Water integration and river basin management. FAO Land and Water Bulletin No I : 15-16. FAO. Rome, Italy.
FAO (1986) Irrigation Water Management. Training Manual No. 3 (crop water needs). Available online at http://www.fao.org/docrep/S2022E/S2022E00.htm. Accessed on 29-7-2012.
FAO (1989) Arid zone forestry: A guide for field technicians. FAO Conservation Guide. Available at: http://www.fao.org/docrep/T0122E/t0122e00.htm#Contents. Accessed on 5-8-2012.
FAO (1993) Land degradation in arid, semi-arid and dry sub-humid areas: rainfed and irrigated lands, rangelands and woodlands. Inter-governmental negotiating committee for the preparation of a convention to combat desertification and drought (INCD). First Substantive Session, Nairobi 24 May - 4 June 1993. Available at http://www.fao.org/docrep/X5308E/X5308E00.htm. Accessed on 12-8-2012.
FAO (1995) Irrigation in Africa in Figures – L’irrigation en Afrique en Chiffres. FAO, Rome.
FAO (1995) Country Pasture/Forage Resource Profile. Available at: http://www.fao.org/ag/AGP/AGPC/doc/Counprof/kenya/Kenya.htm#3. Consulted on 31-1-2012.
FAO (2001) Smallholder irrigation technology: prospects for sub-Saharan Africa. International Programme for Technology and Research in Irrigation and Drainage Knowledge Synthesis Report No. 3. Roma, Italy, 2001.
Fox, P., Rockström, J. and Barron, J. (2005) Risk analysis and economic viability of water harvesting for supplemental irrigation in semi-arid Burkina Faso and Kenya. Agricultural systems 83: 231-250.
Hatibu, N. and Mahoo, H.F. (2000a). Rainwater Harvesting for Natural Resources Management, A planning guide for Tanzania. Technical Handbook No. 22. RELMA, Nairobi.
65
Hatibu, N., Mahoo, H. F. and Kajiru, G.J. (2000b) The role of RWH in agriculture and natural resources management: from mitigating droughts to preventing floods. In: Rainwater Harvesting for Natural Resources Management. Hatibu, N. and Mahoo, H. F. (eds) A planning guide for Tanzania. Technical Handbook No. 22. RELMA, Nairobi. 58-83.
ICRAF, (2012) Website of World Agroforestry Centre (ICRAF): http://worldagroforestry.org/projects/searnet/index.php?id=67. Accessed on 30-7-2012.
IFAD (2010) Rural Poverty Report. New realities, new challenges: new opportunities for tomorrow’s generation. International Fund for Agricultural Development (IFAD), Roma, Italy, 2010.
IUCN (Behnke, R. ed.) (2007) Kenya’s Drylands – Wastelands or an Undervalued National Economic Resource. The World Conservation Union (IUCN), 2007.
Jungerius, P.D., Matundura, J., van de Ancker, J.A.M. (2002) Road construction and gully erosion in West Pokot, Kenya. Earth Surface Processes and Landforms 27: 1237-1247.
Kenya National Bureau for Statistics (2012) http://www.knbs.or.ke/counties.php. Accessed on 10-8-2012.
Kenya Roads Board (2012) Website of the Kenya Roads Board. http://www.krb.go.ke/road-network/road-network.html Accessed on 10-8-2012.
Kiggundu, N. (2002) Evaluation of rainwater harvesting systems in Rakai and Mbarara Districts, Uganda. GHARP case study report. Greater Horn of Africa Rainwater Partnership (GHARP), Kenya Rainwater Association, Nairobi, Kenya.
Malesu, M., Sang, J.K., Odhiambo, O.J., Oduor, A.R., Nyabenge, M. (2006) Hydrologic impacts of ponds on land cover change: Runoff harvesting in Lare, Kenya. (Rainwater harvesting innovations in response to water scarcity: The Lare experiences.) Technical Report No. 32 Nairobi, Kenya: Regional Land Management Unit (RELMA-in-ICRAF), Netherlands Ministry of Foreign Affairs and Swedish International Development Agency (SIDA), 41 p.
Malesu, M., Oduor, A.R., and Odhiambo, O.J. (2007) Green Water Management Handbook. Rainwater harvesting for agricultural production and ecological sustainability. Technical Manual No. 8 Nairobi, Kenya: World Agroforestry Centre (ICRAF), Netherlands Ministry of Foreign Affairs. 219 p.
Mati, B.M. (1993) Soil erosion and conservation activities on land affected by road drainage: a case study of Nyeri District. In Workshop. Abstracts, 4th Land and Water Management Workshop towards Sustainable Land Use. University of Nairobi.
Mati, B.M. (2005) Overview of water and soil nutrient management under smallholder rainfed agriculture in East Africa. Work Paper 105. Colombo, Sri Lanka: International Water Management Institute (IWMI).
Mati, B., De Bock, T., Malesu, M., Khaka, E., Oduor, A., Nyabenge, M., and Oduor, V. (2006) Mapping the Potential of Rainwater Harvesting technologies in Africa: A GIS overview on development domains for the continent and ten selected countries. Technical Manual No. 6 Nairobi, Kenya: World Agroforestry Centre (ICRAF), Netherlands Ministry of Foreign Affairs. 116 p.
Molden, David. (Ed.) 2007. Water for food, water for life: A Comprehensive Assessment of Water Management in Agriculture. London, UK; Colombo, Sri Lanka: Earthscan; IWMI. 645p.
Mugerwa, N. (2007) Rainwater harvesting and rural livelihood improvement in banana growing areas of Uganda. Master’s Thesis, Department of Water and Environmental Studies, Linköping University.
Muhammad, L., Njoroge, K., Bett, C., Mwangi, W., Verkuijl, H., De Groote, H. (2003) The Seed Industry for Dryland Crops in Eastern Kenya. Mexico, D.F.: CIMMYT and Kenya Agricultural Research Institute (KARI)
Murray, S., Bruke, L., Tunstall, D. and Gilruth, P. (1999). Drylands population assessment II. Draft November, 1999. World Resources Institute and UNDP Office to Combat Drought and Desertification.
Mutiga, J.K., Zhongbo, S, and Woldal, T. (2011) Impacts of agricultural intensification through up-scaling of suitable rainwater harvesting technologies in the upper Ewase Ngiro North basin, Kenya. Hydrol. Earty Syst. Sci. Discuss. 8: 2477-2501.
Mutunga, K., and Critchley ,W. (2001) Farmers' initiatives in Land Husbandry: promising technologies for the drier areas of East Africa. Regional Land Management Unit/Sida. Nairobi. 108 pp.
Ngigi, S.N. (2003a) Rainwater Harvesting for Improved Food Security: promising technologies in the Greater Horn of Africa. Kenya Rainwater Association for the Greater Horn of Africa Rainwater Partnership.
66
Ngigi, S.N. (2003b) What is the limit of up-scaling rainwater harvesting in a river basin? Physics and Chemistry of the Earth. 28: 943-956.
Ngigi, S.N., Savenije, H.H.G., Rockström, J., Gachene, C.K. (2005) Hydro-economic evaluation of rainwater harvesting and management technologies: Farmers investment options and risks in semi-arid Laikipia district of Kenya. Physics and Chemistry of the Earth 30 (2005): 772–782.
Ngigi, S.N., Savenije, H.H.G., Gichuki, F.N. (2007) Land use changes and hydrological impacts related to up-scaling of rainwater harvesting and management in upper Ewaso Ng'iro river basin, Kenya.
Ngigi, S.N. (2008) Technical evaluation and development of low-head drip irrigation systems in Kenya. Irrigation and drainage. 57: 450-462.
Ngigi, S.N. (2009) Climate Change Adaptation Strategies: Water Resources Management Options for Smallholder Farming Systems in Sub-Saharan Africa. The MDG Centre for East and Southern Africa, The Earth Institute at Columbia University, New York. 189p.
Nissen-Petersen, E. (2006) Water from roads. A handbook for engineers and technicians on harvesting rainwater from roads. DANIDA 2006.
Nissen-Petersen, E. (2010) Video on road runoff harvesting. http://www.thewaterchannel.tv/es/videos/categorias/viewvideo/631/water-harvesting/water-from-roads. Accessed on 29-7-2012.
Opiyo, F.E.O., Mureithi, S.M. and Ngugi, R.K. (2011) The Influence of Water Availability on Pastoralist’s Resource Use in Mwingi and Kitui Districts in Kenya. Journal of Human Ecology. 35(1): 43-52.
Oweis, T., Hachum, A., and Kijne, J. (1999) Water harvesting and supplemental irrigation for improved water use efficiency. SWIM Paper No. 7. IWMI, Colombo, Sri Lanka.
Pretty, J., Toulmin, C. and Williams, S. (2011) Sustainable Intensification: Increasing Productivity in African Food and Agricultural Systems. International Journal of Agricultural Sustainability. 9 (1).
Qiang, Z. and Yuanhong, L. (2003) Drought-Proofing villages in Gansu Province. LEISA magazine , Volume 19 no2, ILEIA, The Netherlands
Roads Fund Board (2012). Website Roads Fund Board, http://www.roadsfundtz.org/web/roadnetworks.asp. Accessed on 11-8-2012.
Rockström, J. (1999) On-farm Green Water Estimates as a Tool for Increased Food Production in Water Scarce Regions. Phys. Chem. Earth (B). 24(4): 375-383.
Rockström, J. (2000) Water Resources Management in Smallholder Farms in Eastern and Southern Africa: An Overview. Physics and Chemistry of the Earth, 25 (3): 275-283.
Rockström, J. and Falkenmark, M. (2000) Semiarid crop production from a hydrological perspective: gap between potential and actual yields. Critical Reviews in Plant Sciences, 19: 319–346.
Rockström, J., Barron and Fox, P. (2003) Water Productivity in Rain-fed Agriculture: Challenges and Opportunities for Smallholder Farmers in Drought-prone Tropical Agroecosystems. In: Kijne, J.W. , Barker, R. and Molden, D., , CAB International.
Sachdeva, S.N., Sharma, U. (2008) Potential of Road Rainwater Harvesting in Urban Areas. 3rd IASME / WSEAS Int. Conf. on WATER RESOURCES, HYDRAULICS & HYDROLOGY (WHH '08), University of Cambridge, UK, Feb. 23-25, 2008. Available at http://www.wseas.us/e-library/conferences/2008/uk/WHH/WHH-04.pdf.
Safriel, U., Z. Adeel, D. Neimeijer, J. Puigdefabregas, R. White, M. Lal, M. Winslow, J. Ziedler, S. Prins, E. Archer, en C. Koning. 2002. Dryland Systems (Ch. 22): 625-662. Millennium Ecosystem Assessment. Island Press, New York.
Schwilch, G., Bestelmeyer, B., Bunning, S., Critchley, W., Herrick, J., Kellner, K., Liniger, H.P., Nachtergaele, F., Ritsema, C.J., Schuster, B., Tabo, R., van Lynden, G. and Winslow, M. (2011) Experiences in monitoring and assessment of sustainable land management. Land Degrad. Develop. 22: 214–225.
Shaxson, F. and Barber, R. (2003) Optimizing Soil Moisture for Plant Production. FAO Soils Bulletin 79. Rome, 2003. Available at http://www.fao.org/docrep/006/y4690e/y4690e00.htm#Contents.
SIWI (2001) Water harvesting for upgrading of rainfed agriculture: Problem analysis and research needs. Eds. Falkenmark M, Fox P, Persson G, Rockström J. SIWI report 11, Stockholm, Sweden, (pp41-79).
Stockholm Environment Institute (Barron, J. ed) (2009) Rainwater Harvesting: a Lifeline for Human Well-Being. United Nations Environment Programme.
67
Svendsen, M., Ewing, M., Msangi, S. (2009) Measuring irrigation performance in Africa. International Food Policy Research Institute (IFPRI) Discussion Paper 00894. IFPRI, Environment and Production Technology Division.
Tiffen, M., and Mortimore, M. (1994) Environment, Population growth and Productivity in Kenya: A Case Study of Machakos District. IIED Drylands Networks Programme Issues Paper:27.
Tiffen , M., Mortimore, M. And Gichuki, F. (1994) More People, Less Erosion. Environmental recovery in Kenya. ACTS Press, Nairobi, Kenya, and Overseas Development Institute, London, 1994.
Thornton, P.K., P.G. Jones, T.M. Owiyo, R.L. Kruska, M. Herero, P. Kristjanson, A. Notenbaert, N. Bekele and Co-authors (2006) Mapping Climate Vulnerability and Poverty in Africa. Report to the Department for International Development, ILRI, Nairobi, 200 pp.
Tuitoek, D.K., Owido, S.F.O., China, S.S., Wanjama J.K. (2001) Transfer and adoption of water harvesting technologies for domestic and livestock use in Lare Division, Nakuru District. Unpublished paper.
UNEP (1992) World atlas of desertification. United Nation Environment Programme (UNEP) and Edward Arnold.
UNEP (1997) Source Book of Alternative Technologies for Freshwater Augmentation in Latin America and the Caribbean. IETC Technical Publication Series by UNEP International Environmental Technology Centre, Osaka/Shiga, Japan, 1997.
UNEP (2003) Technology Transfer: The Seven “C”s for the Successful Transfer and Uptake of Environmentally Sound Technologies. International Environmental Technology Centre (IETC), United Nations Environment Programme (UNEP). Osaka, Japan.
Vlek, P.L.G., Bao Le, Q. and Tamene, L. (2008) Land Decline in Land-Rich Africa: A Creeping Disaster in the Making. Consultative Group on International Agricultural Research. Centre for Development Research (ZEF), University of Bonn, Germany.
WOCAT (2005) Online database, available at www.wocat.org.
WOCAT (Liniger H. and Critchley, W. eds) (2007) where the land is greener: case studies and analysis of soil and water conservation initiatives worldwide. CTA, FAO, UNEP, CDE, Bern
WOCAT (2000) WOCAT Questionnaire on SLM Technologies. A framework for Evaluation of Soil and Water Conservation. WOCAT Centre for Development and Environment, University of Bern, Hallerstrasse 12, CH-3012, Berne, Switzerland.
Zeedyk, B. (2006) Water harvesting from low-standard rural roads. Joint publication of The Quivira Coalition, Zeedyk Ecological Consulting, LLC, The Rio Puerco Management Committee – Watershed Initiative, and the New Mexico Environment Department – Surface Water Quality Bureau, April 2006.
Ziadat, F.M., Mazahreh, S.S., Oweis, T.Y., Bruggeman, A. (2006) A GIS-based Approach for Assessing Water Harvesting Suitability in a Badia Benchmark Watershed in Jordan. 14th International Soil Conservation Organization Conference. Water Management and Soil Conservation in Semi-Arid Environments. Marrakech, Morocco, May 14-19, 2006 (ISCO 2006)
68
Annex I Categorisation of WOCAT data
Categorisation of the WOCAT Questionnaire for SLM Technologies according to four elements of the TEES-test
(Technical, Economic, Environmental and Social) as well as General information on a Technology. The sub-
categories of each element are also indicated in the last column.
Input TEES- test Sub-category PART 1: GENERAL INFORMATION 1.1 Specialist* General None 1.2 SLM technology* General None 1.2.1 Common name* General None 1.2.2 Local name* General None 1.2.3 Part of watershed?* General None 1.2.4 Approach* General None 1.3 Area information General None 1.3.1 Area definition* General None 1.3.2 Coordinates* General None PART 2: SPECIFICATION OF SLM TECHNOLOGY 2.1 Description NA NA 2.1.1 Definition* General None 2.1.2 Main characteristics* General None 2.1.3 Photos* General None 2.1 Purpose and classification NA NA 2.2.1 Land use problems* Technical Purpose 2.2.2 Characterisation and purpose Technical Purpose
2.2.2.1 Land use type* Technical Purpose 2.2.2.2 Conservation measures* Technical Measures 2.2.2.3 Goals* Technical Purpose 2.2.2.4 Land degradation type* Technical Purpose 2.2.2.5 Causes of land degradation Technical Purpose 2.2.2.6 Measures against land degradation Technical Measures
2.3 Status NA NA 2.3.1 Origin Social Origin 2.3.2 Technical knowledge required* Technical Knowledge required 2.4 Technical drawing* Technical Measures 2.5 Technical specifications NA NA 2.5.1 Agronomic measures* Technical Measures
2.5.1.1 Type and lay-out* Technical Measures 2.5.1.2 Activities, inputs and costs* Technical / Economic Measures / Input (resp.)
2.5.2 Vegetative measures Technical Measures 2.5.2.1 Type and layout Technical Measures 2.5.2.2 Activities, inputs and costs Technical / Economic Measures / Input (resp.)
2.5.3 Structural measures Technical Measures 2.5.3.1 Type and layout Technical Measures 2.5.3.2 Activities, inputs and costs Technical / Economic Measures / Input (resp.)
2.5.4 Management measures Technical Measures 2.5.4.1 Type and layout Technical Measures 2.5.4.2 Activities, inputs and costs Technical / Economic Measures / Input (resp.)
2.6 Overview of costs NA NA 2.6.1 Establishment Economic Costs 2.6.2 Most determinate factors Economic Costs 2.7 Natural environment NA NA 2.7.1 Average rainfall* Technical Conditions 2.7.2 Agro-climatic zone* Technical Conditions 2.7.3 Thermal climate Technical Conditions 2.7.4 Growing seasons Technical Conditions 2.7.5 Climate tolerance of Technology Technical Conditions 2.7.6 Altitudinal zonation* Technical Conditions 2.7.7 Landforms* Technical Conditions 2.7.8 Slopes* Technical Conditions 2.7.9 Soil depth* Technical Conditions 2.7.10 Soil texture* Technical Conditions 2.7.11 Soil fertility* Technical Conditions 2.7.12 Topsoil organic matter* Technical Conditions
69
2.7.13 Soil drainage / infiltration* Technical Conditions 2.7.14 Soil water storage capacity Technical Conditions 2.7.15 Ground water table Technical Conditions 2.7.16 Availability of surface water Technical Conditions 2.7.17 Water quality (untreated) Technical Conditions 2.7.18 Biodiversity Environmental Biodiversity 2.8 Human environment and land use NA NA 2.8.1 Land users applying Technology* Social Conditions 2.8.2 Population density* Social Conditions 2.8.3 Annual population growth Social Conditions 2.8.4 Land and water ownership and rights* Social Conditions 2.8.5 Level of wealth Economic Conditions 2.8.6 Significance of off-farm income Economic Conditions 2.8.7 Access to services and infrastructure Economic Conditions 2.8.8 Conditions crop land NA NA
2.8.8.1 Market orientation* Economic Conditions 2.8.8.2 Land use tools* Economic / Social Conditions / Conditions 2.8.8.3 Type of cropping system Economic Conditions 2.8.8.4 Water supply Economic Conditions 2.8.8.5 Livestock Economic Conditions 2.8.8.6 Size of cropland* Economic / Technical Conditions / Conditions
2.8.9 Conditions grazing land NA NA 2.8.9.1 Market orientation NA NA 2.8.9.2 Type of grazing system NA NA 2.8.9.3 Water supply NA NA 2.8.9.4 Livestock density NA NA 2.8.9.5 Size of grazing land NA NA
2.8.10 Conditions forest / woodland NA NA 2.8.10.1 Market orientation NA NA 2.8.10.2 Type of forest / woodland NA NA 2.8.10.3 Purpose NA NA 2.8.10.4 Size of forest / woodland NA NA
2.8.11 Conditions other land NA NA 2.8.11.1 Types NA NA
PART 3: ANALYSIS OF THE SLM TECHNOLOGY 3.1 Impacts: benefits and disadvantages NA NA 3.1.1 On-site benefits NA NA
3.1.1.1 Production and socio-economic benefits* Economic Benefits 3.1.1.2 Socio-cultural benefits* Social Benefits 3.1.1.3 Ecological benefits* Environmental Benefits 3.1.1.4 Other benefits* General NA
3.1.2 Off-site benefits* Social / Environmental Benefits 3.1.3 On-site disadvantages NA Disadvantages
3.1.3.1 Production and socio-economic disadvantages
Economic Disadvantages
3.1.3.2 Socio-cultural disadvantages Social Disadvantages 3.1.3.3 Ecological disadvantages Environmental Disadvantages 3.1.3.4 Other disadvantages General NA
3.1.4 Off-site disadvantages Social / Environmental Disadvantages 3.1.5 Contribution to wellbeing Social Benefits 3.2 Economic analysis NA NA 3.2.1 Benefits vs establishment costs* Economic Costs, Benefits 3.2.2 Benefits vs maintenance costs* Economic Costs, Benefits 3.3 Acceptance or adoption NA NA 3.3.1 Acceptance with external material support* Social Adoption
3.3.1.1 Number of land user families* Social Adoption 3.3.2 Spontaneous adoption* Social Adoption
3.3.2.1 Number of land user families* Social Adoption 3.3.2.2 Adoption trend* Social Adoption 3.4 Concluding statements NA NA 3.4.1 Majors strengths of Technology General NA 3.4.2 Major weaknesses of Technology* General NA * Questions that are part of the Summary Questionnaire