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A Distributed Hydrological Model Driven by Multi-Source Spatial Data and Its Application in the Ili River Basin of Central Asia

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  • Mingyong Cai
  • Shengtian Yang
  • Hongjuan Zeng
  • Changsen Zhao
  • Shudong Wang

Abstract

Hydrological simulation in ungauged regions is a popular topic in water resource and environmental research, and is also an important part of the international research initiative Predictions in Ungauged Basins (PUB). In this study, a multi-spatial data-based DTVGM (MS-DTVGM), combining multi-source spatial data (MS-spatial data) with the Distributed Time-Variant Gain Model (DTVGM), was built in order to reduce dependence on conventional observation, and was applied to the Ili River basin where traditional data sets are scarce. Because it utilizes MS-spatial data to measure precipitation, potential evapotranspiration, air temperature, vegetation parameters, and soil parameters, the model is driven purely by data from common platforms, thus overcoming the disadvantage of the large amounts of data typically required for distributed hydrological models. The inputs and simulation results were calibrated and validated using station or field observations. The results indicate that: 1) the MS-DTVGM is feasible in the Ili River basin; all model inputs can be acquired from multi-source spatial data and the key parameters are accurate; 2) the MS-DTVGM has good performance on a monthly time scale, and its simulation results can be used for a longer time-scale water resource analysis; and (3) daily runoff generation correlated strongly with snowmelt, the R 2 is about 0.69 indicating that the latter is an important contributor to water resources and suggesting that a snowmelt module is indispensable this area. The potential of distributed models for hydrological simulation in data-scarce regions using MS-spatial data was clearly demonstrated. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Mingyong Cai & Shengtian Yang & Hongjuan Zeng & Changsen Zhao & Shudong Wang, 2014. "A Distributed Hydrological Model Driven by Multi-Source Spatial Data and Its Application in the Ili River Basin of Central Asia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 2851-2866, August.
  • Handle: RePEc:spr:waterr:v:28:y:2014:i:10:p:2851-2866
    DOI: 10.1007/s11269-014-0641-z
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    References listed on IDEAS

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    1. Unknown, 2005. "Forward," 2005 Conference: Slovenia in the EU - Challenges for Agriculture, Food Science and Rural Affairs, November 10-11, 2005, Moravske Toplice, Slovenia 183804, Slovenian Association of Agricultural Economists (DAES).
    2. M. Albuquerque & G. Sanz & S. Oliveira & R. Martínez-Alegría & I. Antunes, 2013. "Spatio-Temporal Groundwater Vulnerability Assessment - A Coupled Remote Sensing and GIS Approach for Historical Land Cover Reconstruction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(13), pages 4509-4526, October.
    3. Giorgos Papadavid & Diofantos Hadjimitsis & Leonidas Toulios & Silas Michaelides, 2013. "A Modified SEBAL Modeling Approach for Estimating Crop Evapotranspiration in Semi-arid Conditions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(9), pages 3493-3506, July.
    4. Pasquale Cutore & Gabriella Cristaudo & Alberto Campisano & Carlo Modica & Antonino Cancelliere & Giuseppe Rossi, 2007. "Regional Models for the Estimation of Streamflow Series in Ungauged Basins," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(5), pages 789-800, May.
    5. Sanjay Jain & Ajanta Goswami & Arun Saraf, 2010. "Assessment of Snowmelt Runoff Using Remote Sensing and Effect of Climate Change on Runoff," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(9), pages 1763-1777, July.
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    1. Rui Xia & Hao Sun & Yan Chen & Qiang Wang & Xiaofei Chen & Qiang Hu & Jing Wang, 2023. "Ecological Flow Response Analysis to a Typical Strong Hydrological Alteration River in China," IJERPH, MDPI, vol. 20(3), pages 1-14, January.

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