Water system characteristics of Karst river basins in South China and their driving mechanisms of hydrological drought

Zhonghua He (), Hong Liang, Zhaohui Yang, Fasu Huang and Xinbo Zeng
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Zhonghua He: Guizhou Normal University
Hong Liang: Guizhou Normal University
Zhaohui Yang: Department of Water Resources of Guizhou Province
Fasu Huang: Guizhou of Hydrology and Water Resource Bureau
Xinbo Zeng: Department of Water Resources of Guizhou Province

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2018, vol. 92, issue 2, No 28, 1155-1178

Abstract: Abstract It is common knowledge that drought is considered one of the most damaging natural disasters in terms of economic costs, societal problems, and ecological impacts. In this study, we selected 53 Karst drainage basins in South China as research areas and automatically extracted the characteristics of water system based on 30 m DEM data using GIS technology. The surface confluence and runoff process of atmospheric precipitation were simulated by BP neural network, and we analyzed space coupling of drainage characteristics and studied their driving mechanisms for hydrological drought. Results show that (1) basin shape index, river network density, and main channel’s longitudinal slope respond positively to atmospheric precipitation, while other drainage characteristics respond negatively. This shows that drainage characteristics’ response to atmospheric precipitation gradually decreases from input layer to output layer, which means that watershed confluence capability gradually weakens. (2) Driving of drainage characteristics to runoff process is positive in the first hidden layer with its driving effect order arranged from small to big as follows: river network density 0.9), with excellent model significance (Sig. = 0.0).

Keywords: Hydrological drought; Driving mechanism; BP neural network; Karst drainage basin; South China (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s11069-018-3275-2

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