Water availability and Productivity in the Andes Region Mark Mulligan, King’s College London [email protected]and the BFPANDES team : Condesan, CIAT, National University, Colombia [email protected][30 mins] DATA AND MODELS AVAILABLE AT: www.policysupport.org/links/aguaandes and www.kcl.ac.uk/geodata
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Water Availability and Productivity in the Andes Region
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Water availability and Productivity in the Andes Region
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
land use
6. Environmentally sensitive
7. Hydropower is important
8. Complex water legislation
9. Climate change
10. Industrial and extractive impacts on
water quality
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 W2. Large urban areas throughout but especially in the N3. Complex network of large and globally important protected areas4. Significant irrigated agriculture especially in coastal Peru and the drier parts of
Ecuador and Colombia5. 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
...but even in the Andes rainfall stations are sparsely distributed....
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.
points
interpolation
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
Potential Evapo-transpiration (mm/yr) Water balance (mm/yr) [worldclim]
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
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)
Line of water deficit
Water storage and use: dams in the Andes
Dams : points in the landscape at which water=productivity
Andes : 174 large dams10.5% of land area drains into a dam
Accessing around 20% of streamflowAt least 100 km3 of water storage capacityAt 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
Catchments of Andean dams
Impacts on water availability IWater quality
Parts of the Andes have a lot of water but not all water is usable because of:1. Lack of access2. Lack of storage3. 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. 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 anddisagree 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
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.
Therefore, no major negative changes in seasonal deficits likely
So what will happen?1. Who knows?2. It will be warmer and wetter3. Mean of 17 models warming is highest in the S Andes4. Mean of 17 models wetting is highest in the W and S coastal
Andes5. 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 rainfall7. Seasonality of change is high for temperature and low for
rainfall
What will be the hydrological impacts? Methods1. Use monthly anomalies (deltas) (mean of 17 models) to force
FIESTA hydrological model at Andes scale2. 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
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 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 process models
Tools to test scenarios and policy
options
+
+
http://www.policysupport.org/links/aguaandesMore details and Demo BFPANDES workshop Tuesday 10-11
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.
If we look at the entire countries, not just the Andes, then the lowlands are clearly more
productive [trees excluded]
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 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).
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
The first georeferenced global database of dams (www.kcl.ac.uk/geodata)There are at least 29,000 large dams between 40N and 40S23% are in South America32% 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