Land Degradation & Rainfall

Leo Stroosnijder

WAGENINGEN UNIVERSITY

Soil Science Center

Erosion and Soil & Water Conservation Group

CONTENTS

Land degradation (African bias)Rainfall analysis for LD assessment

Rain water balance (at meeting point)Drought mitigation concepts

ConclusionsRecommendations

Less pictures

More ‘Food for Thought’

(based on a large number of PhD’s)

Land Degradation

from a farmers’ perspective

HOW TO DEFINE ?

LAND

Soil + Water + Vegetation + Fauna

LAND DEGRADATIONThe decline in the extent at which land yields productsuseful to local livelihoods

COMPLEX NOTIONS:Too many (bad) definitions

HOW TO DEFINE ?

LAND DEGRADATION

DESERTIFICATION SOIL DEGRADATION

EROSION

LAND DEGRADATION IS SERIOUS !

DOOM PAPERSpapers based on ‘hard’ facts: RS, GIS and computer models

1976 UN Conference on Desertification, Nairobi1984 Lester Brown1986 Parkan1990 Stoorvogel & Smaling1991 Oldeman (ISRIC)1992 Some et al.1995 Pimentel et al. (in Science)1997 UNEP1997 Smaling et al.1999 Scherr (IFPRI)2000 FAO2006 Pimentel

STATE – RATE – IMPACT

2300TOTAL

100Physical degradation

500Chemical degradation

600Wind erosion

1100Water erosion

World soil degradation (millions ha)

STATE – RATE – IMPACT

1Soil formation rate

30-40Africa, Asia, S-America

6-17USA

5-10Europe, Australia

t ha-1 y-1Soil loss

STATE – RATE – IMPACT

David Pimentel (Cornell), 2006 in Environment, Development and Sustainability

8% per yearProductivity loss:

10-40 times faster than renewal

Soil is lost

10 million ha y-1Abandoned land:

1994 Tiffen et al.

(1803 Malthus)

(1965 Boserup)

1995 Biot er al.

1996 Leach & Mearns

1996 Fairhead & Leach

BUT: HOW SERIOUS IS LAND DEGRADATION ?

1997 Crosson1998 Scoones & Toulmin1998 Fairhead & Leach2000 Mazzucato & Niemeijer2000 Lindert2001 Lomborg2001 Mortimer & Adam2001 Scoones2001 Benjaminsen2001 Rasmussen et al. 2001 Warren et al.2001 Mazzucato & Niemeijer2001 Lambin et al.2001 Lal2002 Wolde-Amlak & Stroosnijder2002 Niemeijer and Mazzucato2007 Fleskens and Stroosnijder (olives)

HOW TO EXPLAIN THIS ?

DIFFERENT SCALES

with

DIFFERENT PROXIES FOR LD

FOUR SPATIAL SCALES

Point:proxies: SOM & physical soil qualities

Farmers’ field:proxies: soil fertility

Watershed:proxies: land use changes & gully formation

Regional:proxies: vegetation cover & productivity

Rasmussen et al. (2001)

Studied dunes Burkina (1955-1994)

1970-1985 = 15 yrs degradation, > 1985 reverse

Arid environments highly variable, rather than disturbed equilibrium

Regional proxy: vegetation cover

Regional proxy: vegetation cover

Lomborg (2001)

33 % of world is forest.

World cover has not changed in 50 yrs.

Regional proxy: vegetation cover

Conclusion: vegetation follows rainfall:

no evidence for permanent vegetation cover decline.

Regional proxy: productivity

Burkina Faso, 1960 - 2000

Mazzucato & Niemeijer (2000)

In spite of decrease in rainfall !

No decline but a steady increase of 2.5 % y-1 !

Regional proxy: productivity

Conclusion:

forty years Sahel:

no evidence for productivity decline

Regional proxy: productivity

2.46.814.8Natural forests

8.012.816.3Bare land

10.61.21.8Plantations

11.618.78.5Grazing land

60.656.654.8Cropland

200019841957Land use types

Beressa watershed. Ethiopia (Aklilu Amsalu et al., 2006)

Watershed proxy: land use changes

Conclusion: Land use dynamics:

considerable transitions occurred within the land use types

Watershed proxy: land use changes

The gullied area under cropland declined by 36 %

while those under grassland increased.

(Ginchi watershed)

Conclusion: no strong evidence

Watershed proxy: gully formation

Farmers’ field proxy: fertility

Temporal fertility: IIED paper

No fertility decline over 30 years !

Farmers’ field proxy: fertility

Soil organic matter

Physical soil qualities

Point scale proxies:

Natural reduction

For West Africa: Pieri (1989)

Point proxy: SOM

infiltration capacity

Point proxy:

Point proxy: structural crust

depositional crustPoint proxy

Decrease in soil organic matter

Decrease in physical soil qualities

CONCLUSION:

degrading soil qualities

Point proxies

THE PUZZLE

LD at point scale seems proven

LD at higher scales NOT

WHY?

Delayed effect ?

Compensation effect ?

Aggregation problem ?

This makes up- en downscaling difficult !

HOW TO DEFINE LD ?

Is Land Degradation contextual ???

(Warren, 2002)

What scientists want

At UN headquarters

What farmers’ think

The indifference of many Sahelian farmers to high rates of soil loss may reflect their recognition that erosion does not seriously damage productivity in the short term.

Rainfall Analysis for Land Degradation

Assessment

FIVE TEMPORAL SCALES

Annual

Minute

Daily

Decadal

Monthly

AT EACH SCALE:

Average (does not exist in real world)

Spatial variation (village, social network)

Temporal variation (risk)

Annual rainfall: trend analysis

Burkina: mean over 80 years = 800 mm

Decrease from 1100 (1950) to 700 (1990)

This is 400 mm (50% of mean) over 40 years!

Annual rainfall: probabilities

= wet year

= dry year

Monthly rainfall: Long & short rains

Monthly rainfall for a dry, normal and wet year, Kwalei

Decadal rainfall: Length of growing season

9353Dry10875Normal

Runoff0 %

Runoff50 %

Type of year

Daily rainfall: size classes

Daily rainfall: Probability of non-exceedancedefines return period needed for design

Daily Rainfall: long-term modeling

35 yrs effect of till – no-till on runoff

0

5

10

15

20

25

30

35

40

45

50

1950 1955 1960 1965 1970 1975 1980 1985

Year

Run

off (

% o

f rai

n)

No TillTill

Minute scale: erosivity of rain

0,05

0,10

0,15

0,20

0,25

0,30

0,35

0 20 40 60 80 100

Rain intensity (mm h-1)

Kin

etic

Ene

rgy

(MJ

ha-1

mm

-1)

W&S (1958)

Hudson (1965)

Dijk et al. (2002)

RUSLE-2 (2003)

Threshold erosive showers: 10 – 25 mm h-1

Erosivity INDEX of a shower

Wischmeier & Smith:

KE * I30 correlates best with erosion (splash + overland flow + rill)

I30 is the maximum intensity during 30 minutes

Rain Water Balance

Land Degradation and Rainfall meet

at the soil surface:

the rainfall is divided over several hydrological compartments.

Rain water balance: P = INT + I + R

Infiltration water balance: I = ∆S + D

Soil water balance: ∆S = E + T

Importance Soil Physics knowledge

Soil physical/hydrological processes

at deteriorating physical soil qualities

Runoff ⇑

Evaporation ⇑

Drainage below root zone ⇑

Plant available water ⇓

Transpiration ⇓

Stored and available water:TAW = RD * 0.9(FC - WP)

land degradation = coping with dry spells

For farmers:

Number of days overcoming a dry spell

Good soil: 80 cm * 0.10 = 80 mm/4 = 20 days

Degraded soil: 60 * 0.08 = 48 mm/4 = 12 days

NOT a change in rainfall BUT a change in the soil

GREEN WATER USE EFFICIENCY

mm transpiration

mm of rain

In Africa GWUE =10-20 %, Great Plains USA > 55 %

Combating land degradation =

dry spell mitigation

Reduce Runoff

Improve TAW

Improve GWUE

Three approaches to mitigate dry spells

Basket of Land Management Practices

FANYA JUU TERRACE

Progressive terracing

COMBINATION = AREA + LINE

MULCH

STONE BARRIER

Water Harvesting

Conclusions

Conclusion 1

Be critical on ‘hard evidence’ of LD from RS, models and measurements.

Conclusion 2

Analyse LD at multiple spatial-temporal scales.

Conclusion 3

Analyse rainfall also at multiple scales.

Conclusion 4

Dryland ecosystems are adapted to the magnitude and frequency of dry periods and these are instrumental in controlling the long term functioning of these systems.

Conclusion 5

Africa’s Green Water Use Efficiency is too low.

Conclusion 6

What farmers perceive as drought is the effect of deteriorating physical soil characteristics.

Recommendations

Recommendation 1

Combine model studies with empirical studies at farm and village level.

Recommendation 2

Improve the monitoring of land degradation and rainfall.

Recommendation 3

Make available rainfall data better accessible: present situation is a shame!

Recommendation 4

Invest in GWUE improvement.

Recommendation 5

Research as well as education have become too disciplinary. There are hardly professionals that oversee the complexity of land management.

Recommendation 6

Develop a system of timely transfer of rainfall information to farmers.

Recommendation 7

Learn farmers how to adapt their land management.

Thanks for your attention

Leo.Stroosnijder@wur.nl