Water availability and Productivity in the Andes Region

Water availability and Productivity in the

Andes Region

Mark Mulligan, King’s College London

[email protected]

and the BFPANDES team : Condesan, CIAT, National University, [email protected]

[30 mins]

DATA AND MODELS AVAILABLE AT:

www.policysupport.org/links/aguaandes and www.kcl.ac.uk/geodata

Water in the Andes ‘basin’ (all basins above 500 masl) and the 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 5. Steep slopes, competing demands on

land use

6. Environmentally sensitive

7. Hydropower is important

8. Complex water legislation

9. Climate change

10. Industrial and extractive impacts on

water quality

Andes : baseline

FAO Percentage of

land areas irrigated

Area sum GDP for 1990

(millions USD/yr)

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 in other presentations

Total annual rainfall

(mm)

<WorldClim

TRMM>

Rainfall : falling at the

first hurdle.

trmm

wclim

1. Hyper humid in the N and E.

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

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

Wind-driven rainfall is very heterogeneous in a

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

CQ

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

...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

points

interpolation

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.

Water balance is

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

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

Water demand vs. supply

- =

Annual water demand

(m3)

Annual water surplus/deficit

(m3)

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)- =

Areas of current water deficit (demand>supply)

Water deficits (millions of m3 annually)

Line of water deficit

Water storage and use: 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

Accessing around 20% of streamflow

At least 100 km3 of water storage capacity

At least 20,000 MW HEP capacity

Catchments of

Andean dams

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 – importance of careful

land management

See presentation of Leo Saenz for detail

Impacts on water availability I

Water quality

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 so need careful

management and planning.

% 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. 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: Wednesday 11th 4:40 - 5:10 pm en el Bloque 4 session:

Manejo del Agua en Zonas Urbanas

Impacts on water availability II

Climate variability and change

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.

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:

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

FJ M MA J

J A S O N D

Temperature : seasonality of change : mean of 17 models

Monthly temperature change to 2050s (°C)

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

FJ M MA J

J A S O N D

Rainfall seasonality of change : mean of 17 models

Monthly precipitation change to 2050s (mm)

Mostly even seasonal distribution of change.

Therefore, no major negative changes in seasonal deficits likely

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 rainfall6. 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

Regional scale hydrological impact

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

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)

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)

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

??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.

Sensitivity to change

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)

The AGUAANDES POLICY SUPPORT SYSTEM

-Online (web service)

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

-Detailed and easy to use PSS

-Bilingual

-Testable climate and land use scenarios

and policy options e.g. dam building

SimTerra : the most

detailed global

databases, tiled

Detailed grid –based

+

Detailed grid –based

process models

Tools to test

scenarios and policy

options

+

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

More details and Demo BFPANDES workshop Tuesday 10-11

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

Thank you

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

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

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/

3. One person in five lacks

safe drinking water now

and the situation is not

likely to get better.

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.

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

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

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.

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

productive [trees excluded]

Dry matter productivity

(kg/ha/yr) pastureDry matter productivity

(kg/ha/yr) irrigated crops

Dry matter productivity

(kg/ha/yr) crops

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.

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

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

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

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 (dams discussed in presentation by Leo Saenz)

5. Freshwater fisheries productivity (discussed in presentation by

UNAL).

KCL GLOBAL GEOREFERENCED DAMS DATABASE

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

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