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

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.

An improved gridded water resource distribution for China based on second-order basin data

“…The statistical water resources in China are mostly organized and shared based on the polygon statistical units (administrative region or basin), which cannot reveal the spatial distribution patterns and disparity of water resources within the polygon statistical units (Wang and You 2008;Xia et al 2011;Geng et al 2014;Do et al 2015;Tu et al 2016). However, detailed information about water resources in the pixel scale is urgently needed for the investigation of the relationship between economic growth and water resource scarcity (Bao et al 2007;Jiang and Liu 2010;Zhou et al 2015).…”

“…Many studies have been applied to explore the methods of distributing the water resources of polygon statistical units into grid cells (Duarte et al 2002;Chen et al 2005;Lei et al 2007;Cai 2008;Tian et al 2012;Li and Ma 2014;Bao and Chen 2015;Wang et al 2017). Tu et al (2016) utilized the Moran's I index to analyse the spatial patterns of water resources of the third-order basins and then constructed an autocorrelation model between statistical basin water resources and its relative factors. However, the proposed model only takes the factors of precipitation and slope into account, and ignores the influences of water catchment area.…”

Zoning and Analysis of Control Units for Water Pollution Control in the Yangtze River Basin, China

“…Watershed management is a key issue for regional water resource retention, ecosystem conservation and pollution reduction [1][2][3][4]. In the watershed management domain, the control unit is defined as a spatial management unit integrating administrative area, water body and control section.…”

“…The control section is a water quality monitoring section on the downstream of the water body to control and reflect the pollution of upstream water body, and the control unit is the main pollutant control area to ensure water quality standards of the control area [5][6][7][8]. The main purpose of management units zoning is to decompose the complex water environment problems into various governance units [2,5], so that the specific measures and policies can be implemented effectively to achieve environmental water quality improvement [9]. Hydrological units usually represent surface and sub-surface runoff aggregated above a certain measurement point, where the runoff conditions determine basin characteristics and are therefore suitable as the subjects of watershed water pollution control researches (Examples include: point-source and non-point source pollution) [5].…”

Development of an Evapotranspiration Data Assimilation Technique for Streamflow Estimates: A Case Study in a Semi-Arid Region

“…As an important component of the water budget, it is also critical for sustainable crop production, food security and social sustainability [2][3][4]. With the data assimilation method and remotely sensed data, streamflow estimates can be improved a lot [5][6][7][8][9].…”