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Water 2016, 8(10), 441; doi:10.3390/w8100441

Investigating Alternative Climate Data Sources for Hydrological Simulations in the Upstream of the Amu Darya River

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1,2,* , 1,2
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1,2,3
and
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1
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi 830011, China
2
University of Chinese Academy of Sciences, No. 19A, Yuquan Road, Shijingshan District, Beijing 100049, China
3
Ministry of Agriculture and Water Resources of the Republic of Uzbekistan, Scientific Research Institute of Irrigation and Water Problems under the Tashkent Institute of Irrigation and Melioration, Tashkent 100187, Uzbekistan
*
Author to whom correspondence should be addressed.
Academic Editor: Karl-Erich Lindenschmidt
Received: 13 August 2016 / Revised: 17 September 2016 / Accepted: 27 September 2016 / Published: 11 October 2016
View Full-Text   |   Download PDF [5343 KB, uploaded 11 October 2016]   |  

Abstract

The main objective of this study is to investigate alternative climate data sources for long-term hydrological modeling. To accomplish this goal, one weather station data set (WSD) and three grid-based data sets including three types of precipitation data and two types of temperature data were selected according to their spatial and temporal details. An accuracy assessment of the grid-based data sets was performed using WSD. Then, the performances of corrected data combination and non-corrected grid-based precipitation and temperature data combinations from multiple sources on simulating river flow in the upstream portion of the Amu Darya River Basin (ADRB) were analyzed using a Soil and Water Assessment Tool (SWAT) model. The results of the accuracy assessments indicated that all the grid-based data sets underestimated precipitation. The Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources (APHRODITE) precipitation data provided the highest accuracy (correlation coefficients (CF) > 0.89, root mean square error (RMSE) < 41.6 mm), followed by the CRUNCEP reanalysis data (a combination of the CRU TS.3.2 data and the National Centers for Environmental Prediction (NCEP) reanalysis data) (CF > 0.5, RMSE < 58.1 mm) and Princeton’s Global Meteorological Forcing Dataset (PGMFD) precipitation data (CF > 0.46, RMSE < 62.8 mm). The PGMFD temperature data exhibited a higher accuracy (CF > 0.98, RMSE < 7.1 °C) than the CRUNCEP temperature data (CF > 0.97, RMSE < 4.9 °C). In terms of the simulation performance, the corrected APHRODITE precipitation and PGMFD temperature data provided the best performance. The CF and Nash-Sutcliffe (NSE) coefficients in the calibration and validation periods were 0.96 and 0.92 and 0.93 and 0.83, respectively. In addition, the combinations of PGMFD temperature data and APHRODITE, PGMFD and CRUNCEP precipitation data produced good results, with NSE ≥ 0.70 and CF ≥ 0.89. The combination of CRUNCEP temperature data and APHRODITE precipitation produced a satisfactory result, with NSE = 0.58 and CF = 0.82. The combinations of CRUNCEP temperature data and PGMFD and CRUNCEP precipitation data produced poor results. View Full-Text
Keywords: climate data sources; different combinations of multisource data; river flow simulation; SWAT model climate data sources; different combinations of multisource data; river flow simulation; SWAT model
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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

Sidike, A.; Chen, X.; Liu, T.; Durdiev, K.; Huang, Y. Investigating Alternative Climate Data Sources for Hydrological Simulations in the Upstream of the Amu Darya River. Water 2016, 8, 441.

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