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Water 2014, 6(11), 3270-3299; doi:10.3390/w6113270

Simulating Water Resource Availability under Data Scarcity—A Case Study for the Ferghana Valley (Central Asia)

1
Landscape, Water and Biogeochemical Cycles, Research Center for BioSystems, Land Use and Nutrition, Justus Liebig University Giessen, Heinrich-Buff-Ring 26-32, Giessen 35392, Germany
2
Center for International Development and Environmental Research (ZEU), Justus-Liebig-University Giessen, Senckenbergstr. 3, Giessen 35390, Germany
*
Author to whom correspondence should be addressed.
Received: 17 June 2014 / Revised: 29 September 2014 / Accepted: 14 October 2014 / Published: 30 October 2014
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Abstract

Glaciers and snowmelt supply the Naryn and Karadarya rivers, and about 70% of the water available for the irrigated agriculture in the Ferghana Valley. Nineteen smaller catchments contribute the remaining water mainly from annual precipitation. The latter will gain importance if glaciers retreat as predicted. Hydrological models can visualize such climate change impacts on water resources. However, poor data availability often hampers simulating the contributions of smaller catchments. We tested several data pre-processing methods (gap filling, MODAWEC (MOnthly to DAily WEather Converter), lapse rate) and their effect on the performance of the HBV (Hydrologiska Byråns Vattenavdelning)-light model. Monte Carlo simulations were used to define parameter uncertainties and ensembles of behavioral model runs. Model performances were evaluated by constrained measures of goodness-of-fit criteria (cumulative bias, coefficient of determination, model efficiency coefficients (NSE) for high flow and log-transformed flow). The developed data pre-processing arrangement can utilize data of relatively poor quality (only monthly means or daily data with gaps) but still provide model results with NSE between 0.50 and 0.88. Some of these may not be accurate enough to directly guide water management applications. However, the pre-processing supports producing key information that may initiate rigging of monitoring facilities, and enable water management to respond to fundamentally changing water availability. View Full-Text
Keywords: hydrological modeling; Monte Carlo simulation; MODAWEC; HBV-light model; lapse rate; multiple linear regression hydrological modeling; Monte Carlo simulation; MODAWEC; HBV-light model; lapse rate; multiple linear regression
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Radchenko, I.; Breuer, L.; Forkutsa, I.; Frede, H.-G. Simulating Water Resource Availability under Data Scarcity—A Case Study for the Ferghana Valley (Central Asia). Water 2014, 6, 3270-3299.

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