Presentation at Aguas2009, November 2009, Cali, Colombia. Mark Mulligan.

1. 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, Colombia
mark.mulligan@kcl.ac.uk
[50 mins]

2. 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

3. Andes : baseline
FAO Percentage of Area sum GDP for 1990
land areas irrigated (millions USD/yr)
Ramankutty Ramankutty CIESIN WCPA WDPA
CIESIN
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

4. 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

5. Rainfall : falling at the
first hurdle.
Total annual
rainfall
(mm)
TRMM>
<WorldClim
trmm
wclim
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).

6. 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)

7. ...but even in the Andes rainfall stations are sparsely distributed....
Precipitation stations used by WorldClim in Peru
and Bolivia

8. 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.

9. Per capita water balance
CIESIN
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.

10. 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

11. Water demand vs. supply
- =
Annual water supply
(m3) - 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.

12. Areas of current water deficit (demand>supply)
Water deficits (millions of m3 annually)

13. 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
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

14. Dry matter
Results : water productivity
production
(Kg/Ha./yr)
[without trees]
A coarse scale (1km)
estimate of broad
differences in productivity,
not an estimate of yield.

15. 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.

16. DMP (kg/ha/yr) by land use [trees excluded]
Dry matter productivity Dry matter productivity Dry matter productivity
(kg/ha/yr), for pasture (kg/ha/yr), for irrigated (kg/ha/yr), for cropland
cropland
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.

17. Dams turn water into energy, urban, industrial and irrigation water
KCL GLOBAL GEOREFERENCED DAMS DATABASE
Tropics : land areas draining into dams
by: Leo Saenz
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.

18. 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

19. 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.

20. The water service benefits of protected areas
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

21. Tracing the impact of protected areas on water
% of water originating in a protected area – WDPA 2009 (Colombia) [gl_pc_wc_fin]
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.
see www.kcl.ac.uk/geodata

22. Number of urban people consuming water originating in a protected area – WDPA
2009 (Colombia) [gl_sumurbpc]
The beneficiaries can easily
number millions of people.
A strong case for PWS.
see www.kcl.ac.uk/geodata

23. Percentage of water arriving at tropical dams that fell as rain on protected areas
More conservation to
improve ES at dam Development of
PES schemes to
sustain existing
conservation
see www.kcl.ac.uk/geodata
% water supply from protected areas
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.

24. 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.

25. 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:

26. Temperature 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 gfdl_cm2_1 giss_aom hccpr_hadcm3
All GCMS agree
warming.
There is some
consistency in the ipsl_cm4 miroc3_2_hires miroc3_2_medres miub_echo_g mpi_echam5
pattern of warming for
°C the Andes but all GCMs
disagree elsewhere....
mri_cgcm2_3_2a ncar_pcm1
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

27. 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 gfdl_cm2_1 giss_aom hccpr_hadcm3
For precipitation there is
disagreement on the
direction of change as
well as the magnitude. ipsl_cm4 miroc3_2_hires miroc3_2_ miub_echo_g mpi_echam5
medres
All models indicate
mm/yr
wetting in the Andes...
mri_cgcm2_3_2a ncar_pcm1
Climate data source : Ramirez, J.; Jarvis, A. 2008. High Resolution Statistically Downscaled Future Climate Surfaces. International Centre for
Tropical Agriculture, CIAT.

28. 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

29. Temperature : seasonality of change : mean of 17 models
J F M A M J
J A S O N D
Monthly temperature change to
2050s (°C)
Greatest increase in S Andes and in in J,J,A,S

30. Rainfall seasonality of change : mean of 17 models
J F M A M J
J A S O N D
Monthly precipitation change to 2050s (mm)
Mostly even seasonal distribution of change.
Likely no major negative changes in seasonal deficits

31. 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

32. Regional scale hydrological impact
4 mm/yr loss 100-300 mm/yr gain
Mean annual temperature Mean annual precipitation Mean annual evapo- Mean annual water balance
change to 2050s (°C) change to 2050s (mm) transpiration change to change to 2050s (mm)
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)

33. 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

34. DMP (in Dg/ha/day)
Rainfall (mm/yr)
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.
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.

35. 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

36. 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.

37. % 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
See: Noviembre 11 de 4:40 a 5:10 pm en el Bloque 4
people!
Manejo del Agua en Zonas Urbanas

38. ??Uncertainty??
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.

39. Sensitivity to change
Runoff sensitivity to tree Runoff sensitivity to Runoff sensitivity to
cover change (% change precipitation change (% temperature change (%
in runoff per % change in change in runoff per % change in runoff per %
tree cover) change in precipitation) change in precipitation)

40. The AGUAANDES POLICY SUPPORT SYSTEM
-Online (web service)
-All data supplied (1km or 1 Ha.)
-Detailed and easy to use IAM
SimTerra : the most -Bilingual
detailed global -Testable climate and land use scenarios
databases, tiled and policy options e.g. dam building
+
Detailed grid –based
process models
+
Tools to test
scenarios and policy
options
http://www.policysupport.org/links/aguaandes

41. 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
Thank you

43. Statistics : Bolivia, Colombia, Ecuador and Peru
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

44. 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.
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/

45. If we look at the entire countries, not just the Andes, then the lowlands are clearly more
productive [trees excluded]
Dry matter productivity Dry matter productivity Dry matter productivity
(kg/ha/yr) crops (kg/ha/yr) irrigated crops (kg/ha/yr) pasture

46. 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)