Gridded Water Resource Distribution Simulation for China Based on Third-Order Basin Data from 2002

Mingguang Tu, Futao Wang, Yi Zhou and Shixin Wang
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Mingguang Tu: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
Futao Wang: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
Yi Zhou: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
Shixin Wang: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

Sustainability, 2016, vol. 8, issue 12, 1-14

Abstract: Water resources are a key factor for regional sustainable development. However, the published water resource data in China is based on a large geographical scale, such as watershed units, and the data cannot reflect subtle differences in water resource distribution. The paper aimed to distribute water resources of the third-order basin of China into grid-cells of 1 km × 1 km. First, we used Moran’s I index to analyze the spatial pattern of water resources of the third-order basin. Second, we constructed a spatial autocorrelation model between water resources of third-order basins and the associated factors. Third, we applied the model to simulate the gridded water resource distribution and evaluated the simulation accuracy. The results indicated that significant spatial autocorrelation existed among the water resources of third-order basins. Northern China was the low-value clustering area of water resources and Southeast China was the high-value clustering area of water resources. Slope and precipitation were the main factors that influenced the amount of water resources. The simulating accuracy of water resource distribution was very high, apart from some extremely arid regions (Gurbantunggut Desert, Kumtag Desert, and Hexi Desert). On the whole, the gridded water resource distribution map was valid and was helpful for regional water resource management.

Keywords: water resources; data gridding; distribution simulation; Moran’s I index; spatial autocorrelation model; precipitation; evapotranspiration; land cover; slope (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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