Evaluating Water Withdrawals for Regional Water Management Under a Data-driven Framework

With an increase in population and economic development, water withdrawals are close to or even exceed the amount of water available in many regions of the world. Modelling water withdrawals could help water planners improve the efficiency of water use, water resources allocation, and management in order to alleviate water crises. However, minimal information has been obtained on how water withdrawals have changed over space and time, especially on a regional or local scale. This research proposes a data-driven framework to help estimate county-level distribution of water withdrawals. Using this framework, spatial statistical methods are used to estimate water withdrawals for agricultural, industrial, and domestic purposes in the Huaihe River watershed in China for the period 1978–2018. Total water withdrawals were found to have more than doubled, from 292.55 × 10⁸ m³ in 1978 to 642.93 × 10⁸ m³ in 2009, and decreased to 602.63 × 10⁸ m³ in 2018. Agricultural water increased from 208.17 × 10⁸ m³ in 1978 to 435.80 × 10⁸ m³ in 2009 and decreased to 360.84 × 10⁸ m³ in 2018. Industrial and domestic water usage constantly increased throughout the 1978–2018 period. In 1978, industrial and domestic demands were 20.35 × 10⁸ m³ and 60.04 × 10⁸ m³, respectively, and up until 2018, the figures were 105.58 × 10⁸ m³ and 136.20 × 10⁸ m³. From a spatial distribution perspective, Moran’s I statistical results show that the total water withdrawal has significant spatial autocorrelation during 1978–2018. The overall trend was a gradual increase in 1978–2010 with withdrawal beginning to decline in 2010–2018. The results of Getis-Ord Gᵢ* statistical calculations showed spatially contiguous clusters of total water withdrawal in the Huaihe River watershed during 1978–2010, and the spatial agglomeration weakened from 2010 to 2018. This study provides a data-driven framework for assessing water withdrawals to enable a deeper understanding of competing water use among economic sectors as well as water withdrawal modelled with proper data resource and method.