Accuracy assessment of gridded precipitation Datasets in ... · University of Cambridge...

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Asif Khan

Post Doctorate (IIASA, Austria)

Ph.D (Cambridge, UK)

Accuracy assessment of gridded precipitation

Datasets in the HKH region

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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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Current/Past Affiliations:

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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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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: variability in modelled flows

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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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Potential Causes: use of different precipitation datasets

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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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Precipitation datasets accuracy assessment

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Precipitation datasets accuracy assessment

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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

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Snowmelt runoff modelling

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Uncertainty in existing studies

Constraints: variability in flow components

Hunza basin (Karakoram)

Astore basin (Himalayas)

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ISI-MIP precipitation and modelled flow

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ISI-MIP precipitation and modelled flow

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Modelled monthly flows (ISI-MIP)

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ISI-MIP water scarcity

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FAO water scarcity

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engrasif_civil@yahoo.comFig: variability in modelled flows

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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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