Remote Sensing (Feb 2022)

Identifying Reservoirs and Estimating Evaporation Losses in a Large Arid Inland Basin in Northwestern China

  • Qian-Qian Xia,
  • Ya-Ning Chen,
  • Xue-Qi Zhang,
  • Jian-Li Ding,
  • Guang-Hui Lv

DOI
https://doi.org/10.3390/rs14051105
Journal volume & issue
Vol. 14, no. 5
p. 1105

Abstract

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Reservoirs play a vital role in agricultural irrigation, food security, and ecological protection in arid and semi–arid areas where water resources are scarce. In the Tarim Basin (TB) in northwestern China, a large number of reservoirs have been built or are being built, resulting in significant evaporation losses. However, information about the distribution, area and evaporation rate of the reservoirs in TB is limited. To contribute, we present an inventory of reservoirs and calculate their monthly surface area and evaporation rate during the study period of 1990–2019, using the TerraClimate dataset, Google Earth Engine (GEE) platform, Landtrendr algorithm, Penman method, and Landsat images. The results suggest: (1) The inventory of 167 reservoirs in TB consists of 142 existing reservoirs (built before 1990), 5 new reservoirs (mountain reservoirs, built during 1990–2019), and 20 dried–up reservoirs (plain reservoirs that went extinct during 1990–2019). (2) The reservoir types in TB are mainly plain reservoirs with an altitude of less than 1500 m and an area of less than 10 km2, accounting for about 88% of the total number of reservoirs. (3) The surface area of the reservoirs increased at a significant rate (p 2/y from 401 km2 in 1990 to 766 km2 in 2019. (4) The evaporation rate of the reservoirs increased at a slight trend of 0.004 mm/d/a and varied from 2.57 mm/d in 1990 to 2.39 mm/d in 2019. Lastly, (5) The evaporation losses of reservoirs in TB significantly increased (p 8 m3 to 4.92 × 108 m3 due to the significant increase in reservoir surface area (p < 0.05) and the slight increase in evaporation rate from 1990 to 2019. This study provides essentials of the reservoir inventory, surface area, and evaporation rate with considerable baseline inferences for TB that may be beneficial for long–term investigations and assist in local water resources decision support and sustainable management in arid regions.

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