Water availability and Productivity in the

Andes Region

Mark Mulligan, King’s College London

mark.mulligan@kcl.ac.uk

and the BFPANDES team : Condesan, CIAT, National University, Colombiamark.mulligan@kcl.ac.uk

[50 mins]

Water in the Andes ‘basin’ (all basins above 500 masl) and the 13 key CPWF sub-basins

Context:

1. Not a single basin!

2. All mountains

3. Transnational, globally important

4. Heterogeneous (hyper humid to hyper

arid)

5. Steep slopes, competing demands on

land use

6. Environmentally sensitive

7. Hydropower is important

8. Complex water legislation

9. Climate change

FAO Percentage of

land areas irrigated

Area sum GDP for 1990

(millions USD/yr)

Andes : baseline

1. Much pasture and cropland, especially in the N and W

2. Large urban areas throughout but especially in the N

3. Complex network of large and globally important protected areas

4. Significant irrigated agriculture especially in coastal Peru and the drier

parts of Ecuador and Colombia

5. Highest GDPs concentrated around urban centres, large rural areas

with low GDP

Ramankutty Ramankutty CIESIN WCPA WDPA

CIESIN

WP 2 : Water availability : Methods

1. Whole-Andes analysis of water availability at 1km spatial resolution

using the FIESTA delivery model (http://www.ambiotek.com/fiesta) and

long term climatologies from WORLDCLIM (1950-) and TRMM (1996-).

Per capita supply and demand estimated.

2. Analysis of potential impacts of historic and projected land use

change (results not presented – see www.bfpandes.org).

3. Analysis of potential impacts of multiple-model, multiple scenario

climate change and assessment of hydrologically sensitive areas.

4. Understanding of uncertainty and sensitivity to change.

5. Detailed hydrological modelling for smaller areas using AguAAndes

Policy support system (PSS) (results not presented – see

www.bfpandes.org).

6. Issues of water access discussed elsewhere

Total annual

rainfall

(mm)

<WorldClim

TRMM>

trmm

wclim

Rainfall : falling at the

first hurdle.

Hyper humid in the N and E.

At these scales there is uncertainty even in the fundamentals such as rainfall

inputs (especially because of complex topography/wind driven rain).

See at www.ambiotek.com/fiesta (Google Earth viewer required)

Wind-driven rainfall is very heterogeneous in a

mountainous environment – even at the scale of individual slopes...

CQ

...but even in the Andes rainfall stations are sparsely distributed....

Precipitation stations used by WorldClim in Peru

and Bolivia

WorldClim precipitation stations in central Peru

The points are transparent and an image lies beneath, but what image?

If we cannot understand the distribution of rainfall how are we to understand water resources?

Development agencies please note : there is still a lot of hydrological science we do not know

(including where the rain falls). Sound decisions need sound data.

Per capita water balance

Per capita water availability is high throughout the N and W.

Availability ≠ access

Some low spots at densely populated urban centres.

Lowest in coastal Peru, Chile, Bolivia and Argentina.

CIESIN

Potential Evapo-transpiration (mm/yr) Water balance (mm/yr) [worldclim]

Water balance is

dominated by the

rainfall, which can be

an order of

Magnitude > PET

Makes it Important to

know the rainfall!

Hyper-humid in the N

and E to hyper-arid

in the SW

Annual water demand

(m3)Annual water

surplus/deficit (m3)

Water demand vs. supply

Agricultural demand (green water) is accounted for in the ET/water balance calculation.

Industrial demand highly localised. Domestic demand estimated here from mean p.c. water

use and population density. Deficits in the S.

Annual water supply

(m3)

- =

- =

Water deficits (millions of m3 annually)

Areas of current water deficit (demand>supply)

1. Whole-Andes analysis of plant production based on dry matter

production calculated from SPOT-VGT (1998-2008), masked

to exclude trees.

2. Whole Andes analysis of production per unit rainfall (crop per

drop, not shown).

3. Accurate digitisation of all dams in the Andes using Google

Earth Dams Geowiki (http://www.kcl.ac.uk/geodata)

4. Calculation of dam watersheds using HydroSHEDS and

estimation of their productivity (HEP etc, Leo)

5. Freshwater fisheries productivity and dams discussed in

other presentations

WP 3 : Water productivity : Methods

Water productivity : often defined as the crop per drop or yield

per unit of water use but in BFPANDES defined more broadly as

the contribution of water to human wellbeing through production

of food, energy and other goods and services

Dry matter

production

(Kg/Ha./yr)

[without trees]

Results : water productivity

A coarse scale (1km)

estimate of broad

differences in productivity,

not an estimate of yield.

Dry matter

production

DMP (in kg/ha/yr)

<Averaged in

500m elev. bands

Averaged by

Catchment>

By elevation : lowest elevations have highest productivity.

By catchment : Colombian and Ecuadorian Andean catchments have highest

productivity along with Eastern foothill catchments in the South.

Dry matter productivity

(kg/ha/yr), for cropland

Dry matter productivity

(kg/ha/yr), for irrigated

cropland

Dry matter productivity

(kg/ha/yr), for pasture

DMP (kg/ha/yr) by land use [trees excluded]

Productivity for pasture is highest in Colombia and Ecuador.

Highly productive irrigated cropland in Chile and Argentina.

Cropland also productive in E. Bolivia, lowland Argentina.

The first georeferenced global database of dams (www.kcl.ac.uk/geodata)

There are at least 29,000 large dams between 40N and 40S

23% are in South America

32% of land area between 40S and 40N drains into a dam (capturing some 24%

of rainfall) and this surface provides important environmental and ecosystem

services to specific companies if carefully managed.

Tropical montane cloudforests cover 4% of these watersheds but receive 15% of

rainfall.

Tropics : land areas draining into damsby: Leo Saenz

KCL GLOBAL GEOREFERENCED DAMS DATABASE

Dams turn water into energy, urban, industrial and irrigation water

Water productivity : dams in the Andes

Dams : points in the landscape at

which water=productivity

Andes : 174 large dams

10.5% of land area drains into a dam

Access around 20% of streamflow

At least 100 km3 of water storage

capacity

At least 20,000 MW HEP capacity

Also used for drinking water, irrigation

and industrial purposes (100 million

people)

20% of the Andean population lives

upstream of dams

Catchments of Andean dams

Impacts on water availability I : Land use

Land use conflicts on steep-lands between protected areas supplying ecosystem

services to downstream populations and marginalised poor farmers/pastoralists

or mining companies.

Water quantity services

•Protected ecosystems do not necessarily generate more

rainfall than agricultural land uses.

•Protected ecosystems may have higher evapo-transpiration

and thus lower water yields

Thus quantity benefits difficult to prove

Water regulation services

•Protected ecosystems do not protect against the most

destructive floods

•For ‘normal’ events they do encourage more subsurface flow

and thus more seasonally regular flow regimes

Likely benefits especially in highly seasonal environments

Water quality services (quantity for a purpose)

•Protected ecosystems encourage infiltration leading to lower

soil erosion and sedimentation

•Unprotected land will tend to have higher inputs of pesticides,

herbicides, fertilisers ...

Clear benefits of PA’s: generation of higher quality water than

non-protected areas

The water service benefits of protected areas

see www.kcl.ac.uk/geodata

For all streams sum water falling

as rain on upstream protected

areas as a proportion of water

falling on unprotected land

As you travel downstream

from the protected areas their

contribution to flow diminishes as

rivers are swamped with water

from non-protected areas

Protected areas dilute

Contaminants running off agric

land.

Tracing the impact of protected areas on water

% of water originating in a protected area – WDPA 2009 (Colombia) [gl_pc_wc_fin]

Number of urban people consuming water originating in a protected area – WDPA

2009 (Colombia) [gl_sumurbpc]

see www.kcl.ac.uk/geodata

The beneficiaries can easily

number millions of people.

A strong case for PWS.

Percentage of water arriving at tropical dams that fell as rain on protected areas

see www.kcl.ac.uk/geodata

Method: For all 29,000 dams calculated the percentage of rainfall draining into them

that fell on protected areas upstream.

Result: Indicates the contribution of PA’s to the economic output of those hydro’

companies. Important for the development of PWS schemes.

More conservation to

improve ES at dam Development of

PES schemes to

sustain existing

conservation

% water supply from protected areas

Climate has always changed and will continue to do so. But we do not know what the future holds, how can we understand

the water resource implications?...use our best guess. A general circulation model (GCM)

projection of future climate.

Impacts on water availability II

Climate variability and change

But these are highly uncertain because there is a lot

about the climate we just do not know?

How can we reduce uncertainty?

Use many models and see what they agree and

disagree on and indeed if there is any consensus:

Temperature change AR4-A2a (1961-90) to 2050 – 17 different GCMs

bccr_bcm2_0 cccma_cgcm2 cccma_cgcm3_1cccma_cgcm3_t_t63 cnrm_cm3

csiro_mk3_0 gfdl_cm2_0 giss_aom hccpr_hadcm3gfdl_cm2_1

Climate data source : Ramirez, J.; Jarvis, A. 2008. High Resolution Statistically Downscaled Future Climate Surfaces. International Centre for

Tropical Agriculture, CIAT. Available at: http://gisweb.ciat.cgiar.org/GCMPage/home.html

All GCMS agree

warming.

There is some

consistency in the

pattern of warming for

the Andes but all GCMs

disagree elsewhere....°C

miroc3_2_hires miroc3_2_medres miub_echo_g mpi_echam5

mri_cgcm2_3_2a ncar_pcm1

ipsl_cm4

Precipitation change AR4-A2a (1961-90) to 2050 – 17 different GCMs

bccr_bcm2_0 cccma_cgcm2 cccma_cgcm3_1 cccma_cgcm3_t_t63 cnrm_cm3

csiro_mk3_0 gfdl_cm2_0 giss_aom hccpr_hadcm3gfdl_cm2_1

Climate data source : Ramirez, J.; Jarvis, A. 2008. High Resolution Statistically Downscaled Future Climate Surfaces. International Centre for

Tropical Agriculture, CIAT.

For precipitation there is

disagreement on the

direction of change as

well as the magnitude.

All models indicate

wetting in the Andes...mm/yr

miroc3_2_hires miroc3_2_

medres

miub_echo_g mpi_echam5

mri_cgcm2_3_2a ncar_pcm1

ipsl_cm4

Mean change and uncertainty (s.d.) of 17 GCMs

Warming and wetting for the Andes.

Greatest T uncertainty at high latitudes, coastal and Amazon margins

Rainfall change highly certain

Monthly temperature change to

2050s (°C)

FJ M MA J

J A S O N D

Temperature : seasonality of change : mean of 17 models

Greatest increase in S Andes and in in J,J,A,S

Monthly precipitation change to 2050s (mm)

FJ M MA J

J A S O N D

Rainfall seasonality of change : mean of 17 models

Mostly even seasonal distribution of change.

Likely no major negative changes in seasonal deficits

So what will happen?1. Who knows?

2. It will be warmer and wetter

3. Mean of 17 models warming is highest in the S Andes

4. Mean of 17 models wetting is highest in the W and S

coastal Andes

5. Uncertainty in temperature change is low in the Andes

(the models agree) [but is much greater in the Amazon]

6. Uncertainty in rainfall is greatest in the areas of highest

rainfall

7. Seasonality of change is high for temperature and low for

rainfall

What will be the hydrological impacts? Methods

1. Use monthly anomalies (deltas) (mean of 17 models) to

force FIESTA hydrological model at Andes scale

2. Look into implications for evapo-transpiration and water

balance

Mean annual evapo-

transpiration change to

2050s (mm)

Mean annual temperature

change to 2050s (°C)

Mean annual precipitation

change to 2050s (mm)

Mean annual water balance

change to 2050s (mm)

Regional scale hydrological impact

Temperature and rainfall will increase and this drives up evapo-transpiration.

But, the balance between increased evapo-transpiration and increased

rainfall tends towards more available water (water balance increases)

4 mm/yr loss 100-300 mm/yr gain

So what are the implications for agriculture?

Method:

Examine the current distribution of productivity from 10 years of 10-

daily remote sensing data

Look at relationships between current productivity and current

climate conditions (rainfall and temperature)

Draw implications for impacts of climate change scenaria

Ignore water quality issues (for now)

But then there are also effects of seasonality, CO2 fertilisation,

nutrient limitation, respiration, pests and diseases.... All of which

change with climate.........so we cannot give a definitive answer but

rather start the process of building a system to provide answers

DMP (in Dg/ha/day)

Relationships between productivity and rainfall indicate a linear trend between 0 and

1000 mm/yr but little effect in wetter areas. So productivity may increase in drier areas

that wet.

Rainfall (mm/yr)

DMP (in Dg/ha/day)

Mean annual temperature (°C)Temperature strongly increases productivity in the range 0-20 with a decline from

20-30°. So productivity may decline in the warmest areas.

Impacts on water availability III

Water quality

Some parts of the Andes have a lot of water but not all water is usable because of:

1. Lack of access

2. Lack of storage

3. Water quality is not fit for purpose

Point sources can have a direct influence on downstream users

% of water in streams that fell as rain

on a mine:

1. There are a lot of mines in the Andes

and there will be more

2. Mines can have significant

downstream impacts.

% of water that is human impacted

Human activities (agriculture,

roads, mining, oil and gas and

urban areas influence

downstream water quality.

Likely reflected in higher

sediment loads, organic and

inorganic contaminants,

incl. pesticides and fertiliser

etc.

Influence Decays downstream

by dilution of human

influenced water with runoff

from less influenced areas.

Maps potential quality of

water, usually poor around

people!See: Noviembre 11 de 4:40 a 5:10 pm en el Bloque 4

Manejo del Agua en Zonas Urbanas

Remember the Mona Lisa?We cannot even measure rainfall properly at the Andean

scale and the systems that determine access and productivity of water are much more complex than just

rainfall.How do we deal with this complexity and uncertainty?

1. We change the question from what will the future be like and how will that affect system A? to how much change can system A stand – look at system sensitivity?

2. We run with multiple datasets and multiple parameters to understand the levels of uncertainty.

3. Instead of providing answers, we tie data and knowledge into a system for providing answers (a PSS) that can be applied to geographically and sectorally specific questions.

??Uncertainty??

Runoff sensitivity to

precipitation change (%

change in runoff per %

change in precipitation)

Runoff sensitivity to

temperature change (%

change in runoff per %

change in precipitation)

Runoff sensitivity to tree

cover change (% change

in runoff per % change in

tree cover)

Sensitivity to change

The AGUAANDES POLICY SUPPORT SYSTEM

-Online (web service)

-All data supplied (1km or 1 Ha.)

-Detailed and easy to use IAM

-Bilingual

-Testable climate and land use scenarios

and policy options e.g. dam building

SimTerra : the most detailed global databases, tiled

Detailed grid –based process models

Tools to test scenarios and policy

options

+

+

http://www.policysupport.org/links/aguaandes

Thank you

Concluding:

1. Water productivity is much more than „crop per drop‟ and includes

productivity for energy (HEP), domestic and industrial supply and

sustaining environmental flows. Dams are clearly important.

2. Water quality is currently and will likely continue to be more of a

problem for the Andes than climate change, especially for potable water.

Requires careful legal regulation and benefit sharing mechanisms

3. Climate change will likely have a positive or neutral effect on water

quantity in the Andes but may create regulation or quality issues.

4. There is still an enormous lack of knowledge about the biophysical

components of water resources – do not consider it well known because it

is not.

Much more detail in mid-term and final reports : www.bfpandes.org

Area: 3.8 million km2

Population: of 95 million (Col, Ecu, Peru, Bol, 2005)

Pop growth: 2.5% p.a. (1980-2005)

Highly urbanised: (<15% of population is rural)

46.9 million considered poor (income<essential needs)

People below poverty line (US$1/day) 15-20%: Bolivia, 14%; Colombia, 14%;

Ecuador, 20%; Peru 15.5% (reporting year varies by country; mid- to late 1990s).

Contribution of agriculture to GDP: 10-20% : Bolivia, 20%; Colombia, 13%;

Ecuador, 11%; Peru, 10% (2002 est.)

Climate: varies from humid and tropical to cold and semi-arid

Annual precipitation: 1,835 mm (average) but range from approx. 0 to >10,000mm

Total renewable water resources: 5,100 km3/yr (total)

Annual water use by sector, Andean sub-region (includes Argentina, Chile and

Venezuela): agriculture, 36.5 km3 (73% of total); domestic consumption, 10.5 km3

(21%); industry, 3.1 km3 (6%)

Agricultural area and fertiliser use increasing since the 1960s

Cultivated land: 3.7 % of total

Irrigated land: 30,870 km2

Rainfed land: 108,750 km2 (2000)

Protected areas: 434,058 km2

Statistics : Bolivia, Colombia, Ecuador and Peru

Visualisation by David Tryse based on data from The 2nd UN World Water Development Report: 'Water, a shared

responsibility’ http://www.unesco.org/water/wwap/wwdr/wwdr2/

The “world water crisis”

1. Humans have available less

than 0.08% of all the

Earth's water.

2. Over the next two decades

our use is estimated to

increase by about 40%,

more than half of which to

is needed to grow enough

food.

3. One person in five lacks

safe drinking water now

and the situation is not

likely to get better.

Dry matter productivity

(kg/ha/yr) pastureDry matter productivity

(kg/ha/yr) irrigated cropsDry matter productivity

(kg/ha/yr) crops

If we look at the entire countries, not just the Andes, then the lowlands are clearly more

productive [trees excluded]

But who should pay to manage nature to maintain these

services?

1. Everyone

-through national or international taxation (e.g. The CR fuel tax model)

2. Downstream urban, agricultural and industrial users of water

supplied by water treatment plants and dams

- sustaining protected areas to avoid paying higher treatment costs

- insurance against critical supply problems

3. International users of the virtual water embedded in commodities

-transfers of virtual water are denying downstream users of this water

(assuming transpiration is not locally recycled as rainfall)

- the cost of commodities need to incorporate the costs of sustained and

equitable water provision

4. Voluntary personal contributions

- bundling water offsets with carbon offsets (avoiding multiple

disbenefits)