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University of Cambridge
Asif Khan
Post Doctorate (IIASA, Austria)
Ph.D (Cambridge, UK)
Accuracy assessment of gridded precipitation
Datasets in the HKH region
University of Cambridge
Academics:
Post Doctorate (Water-Energy-Food-Climate)
PGS in GIS and RS
EMBA Project Management
B.Sc Civil Engineering
PhD in Water and Climate
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OutlineImportance of hydrological modelling in various regions of the
world
Why accurate hydrological modelling is vital in the Indus
Basin?
Gridded precipitation products, their variability and constraints
Accuracy assessment of various gridded precipitation
products
Conclusions and Recommendations
Questions and Answers Session
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Global challengeso Population growth
o Global warming and climate change
Increased population will need more: i) water supply, ii) food production, iii) energy
production/supply, iv) flood and drought mitigation, v) urbanization, and
v) industrial development
Source: UN: facts and trends (2006)
Importance of Hydrological Modelling
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Global challengeso Population growth
o Global warming and climate change
Global mean surface temperature increased by 0.74 +/- 0.18 °C during 1906-2005, while
projected expected increase is 1.4 to 5.8 °C during 1990 to 2100 (IPCC 2007, 2013)
Source: (Inman 2010)
Global warming is causing glacier retreat,
Severity in floods and droughts,
Increasing water scarcity,
Increasing slope instability and landslides,
Increasing Glacier Lake Outburst Floods (GLOFs)
Reservoir sedimentation,
Forest fires, and
Increasing water losses/evapotranspiration
1/5th of the global population lives in basins of the Himalayas (Asia)
Importance of Hydrological Modelling
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Potential Adaptation/Mitigation measures
Decline in Green House Gas (GHG) emissions,
Construction of new irrigation, hydro-power groundwater recharge dams,
Renewable energy exploitation (hydropower, Bio fuel, solar and wind energy)
Adaptation of improved irrigation practices,
Adaptation of sustainable agricultural practices,
Precise and accurate policy making against floods and droughts,
Afforestation, and
Preparation of climate change adaptation strategies and policies
Importance of Hydrological Modelling
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Hydrological Modelling Constraints
in the Upper Indus Basin
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Constraints: potential causes
Use of different hydrological models
Use of different time period data
Use of different input datasets
Basin Boundaries
Precipitation Datasets
Snow-cover Datasets
Glacier-cover Datasets
Snow and ice-melt parameters
Calibration Parameters
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Thus, improved hydro-climatic modelling is needed
Most important factor is accuracy of input precipitation datasets and glacier data
What is needed?
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Data sets and Analysis:
Measured flow of six sub-basins
Average actual evapotranspiration based on 04 data sets
Average groundwater recharge based on 03 data sets
Average groundwater abstraction based on 02 data sets
Average glacier net-mass balance contributions to flows based on 05 datasets
Average potential evapotranspiration based on 05 data sets
𝑄 = 𝑃 − 𝐸𝑇𝑎𝑐𝑡 ± 𝐺𝑀 − 𝑛𝐺𝑊𝑅 ± ∆𝑆
Accuracy of 12 Gridded precipitation data sets (1999-2010) and 05
GCMs precipitation data (1986-1998) have been evaluated based on
mass balance relationship:
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Results and Discussion: Precipitation Accuracy Assessment
Precipitation data sets
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Results and Discussion: Precipitation Accuracy Assessment
Climatic stations density in
APHRODITE data based on
number of stations in 0.05o grid
Climatic stations density in
CRU TS 3.1 data based on
number of stations in 0.5o grid
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Uncertainty in existing studies
Constraints: variability in flow components
Hunza basin (Karakoram)
Astore basin (Himalayas)
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Conclusions and Recommendations
Climatic models precipitation (e.g., JRA 55) provide better precipitation in the
UIB compared to precipitation data based on climatic stations (e.g.,
APHRODITE)
Accuracy of available gridded precipitation datasets can be improved by using
additional available climatic stations data, together with installation of new
stations in the UIB (at least)
Modelled flows of ISI-MIP models are far less than measured flows in all sub-
basins of the UIB, except the Kharmong basin, and are mainly due to use of
underestimated precipitation
FAO water scarcity overestimation in the UIB is an artefact produced by CRU
underestimated precipitation, which lead to low modelled surface water
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Conclusions and Recommendations
Extreme caution is deemed necessary to interpret global hydro-climatic
studies results without prior validation at regional scale, particularly in complex
mountain regions such as the HKH basins
In the HKH region hydro-climatic studies can be improved by using
appropriate hydrological models together with best available precipitation data
sets, JRA 55 and ERA interim for the UIB, although some precipitation bias
correction is inevitable at sub-basin level
Precipitation is one of the vital source of biased results, therefore other
sources of biases in the discussed and other hydro-climatic studies need to be
investigated
Model better today……Live better in future
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