Remote Sensing (Aug 2022)

Quantifying the Effects of Climate Variability, Land-Use Changes, and Human Activities on Drought Based on the SWAT–PDSI Model

  • Yanbing Zhu,
  • Baofu Li,
  • Lishu Lian,
  • Tianxiao Wu,
  • Junshan Wang,
  • Fangshu Dong,
  • Yunqian Wang

DOI
https://doi.org/10.3390/rs14163895
Journal volume & issue
Vol. 14, no. 16
p. 3895

Abstract

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Much attention has recently been devoted to the qualitative relationship between climate factors and drought; however, the influences of climate variability, land-use/cover changes (LUCC), and other human activities on drought have rarely been quantitatively assessed. Based on the Soil and Water Assessment Tool (SWAT) model and the Palmer drought severity index (PDSI), this study presents a framework to quantify drought changes in an attribution study, and quantifies the effects of climate factors, LUCC, and other human activities on drought in a typical basin (Yihe River) in eastern China from 1980 to 2019. (1) The SWAT–PDSI results revealed a slight decreasing trend from 1980 to 2019, indicating that the degree of drought increased—especially in the middle of the basin. (2) The precipitation in the basin exhibited a downward trend (−2.7 mm/10 a), while the temperature exhibited a significant increasing trend (0.13 °C/10 a, p 2) and an increase in the built-up area (135 km2), which changed by −1.77% and 18.96%, respectively. (3) Climate fluctuation was the main driving factor of drought change, with a contribution rate ranging from 68 to 84%, and the contribution to drought gradually increased. Among the various factors, the contribution of temperature exceeded that of precipitation from 2010 to 2019, suggesting that temperature has become the most important climate factor affecting drought. The contribution rates of LUCC to drought changes over the periods 1990–1999, 2000–2009, and 2010–2019 were 7.8%, 18%, and 12.6%, respectively. This indicates that the relative contributions of other human activities to drought changes gradually decreased. This study refines the drought attribution framework, which could provide scientific support for the quantitative attribution of drought and the formulation of disaster prevention and reduction strategies.

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