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Land degradation significantly impacts regional economic development and food security, particularly in arid river basins where soil and water conservation is crucial. Understanding the extent and causes of land degradation is pivotal for effectively prevention and management. This study employs the soil adjusted vegetation index (SAVI), the temperature vegetation dryness index (TVDI), and the salinization detection index (SDI), combined with the analytic hierarchy process and the entropy weight method, to construct a comprehensive land degradation index (LDI). Sen’s slope trend analysis and the Mann-Kendall significance test were used to analyze land degradation trends in the Ebinur Lake watershed from 2002 to 2022. Additionally, the optimal parameters-based geographical detector was used to examine the underlying mechanisms of land degradation. The results indicate the following: (1) From 2002 to 2012, the degree of land degradation in the Ebinur Lake watershed worsened, particularly in the eastern and southeastern parts, as well as in the southern region of Toli County. From 2012 to 2022, land degradation significantly improved, with a notable reduction in degraded land area. (2) Over the period of 2002-2022, of the land in the research region exhibited a declining LDI trend, showed no change, and only showed an increasing LDI trend. (3) Moderate, severe, and very severe degradation mainly occurred on grassland and unused land, while light degradation and non-degradation primarily occurred on forest land and cultivated land. (4) Unreasonable land use and overgrazing were identified as the primary factors influencing land degradation, with elevation being a secondary factor. The interaction between land use and other factors was found to be most significant, followed by the synergistic effects of grazing quantity with elevation, annual average temperature, gross domestic product, soil moisture, and elevation with annual average precipitation, and temperature. The results of this study offer an empirical basis and taking decisions assistance for land degradation control in the Ebinur Lake Basin, as well as examples and references for assessing land degradation in other places.
Land degradation significantly impacts regional economic development and food security, particularly in arid river basins where soil and water conservation is crucial. Understanding the extent and causes of land degradation is pivotal for effectively prevention and management. This study employs the soil adjusted vegetation index (SAVI), the temperature vegetation dryness index (TVDI), and the salinization detection index (SDI), combined with the analytic hierarchy process and the entropy weight method, to construct a comprehensive land degradation index (LDI). Sen’s slope trend analysis and the Mann-Kendall significance test were used to analyze land degradation trends in the Ebinur Lake watershed from 2002 to 2022. Additionally, the optimal parameters-based geographical detector was used to examine the underlying mechanisms of land degradation. The results indicate the following: (1) From 2002 to 2012, the degree of land degradation in the Ebinur Lake watershed worsened, particularly in the eastern and southeastern parts, as well as in the southern region of Toli County. From 2012 to 2022, land degradation significantly improved, with a notable reduction in degraded land area. (2) Over the period of 2002-2022, of the land in the research region exhibited a declining LDI trend, showed no change, and only showed an increasing LDI trend. (3) Moderate, severe, and very severe degradation mainly occurred on grassland and unused land, while light degradation and non-degradation primarily occurred on forest land and cultivated land. (4) Unreasonable land use and overgrazing were identified as the primary factors influencing land degradation, with elevation being a secondary factor. The interaction between land use and other factors was found to be most significant, followed by the synergistic effects of grazing quantity with elevation, annual average temperature, gross domestic product, soil moisture, and elevation with annual average precipitation, and temperature. The results of this study offer an empirical basis and taking decisions assistance for land degradation control in the Ebinur Lake Basin, as well as examples and references for assessing land degradation in other places.
Constructing a precise and effective evaluation index system is crucial to flood disaster prevention and management in coastal areas. This study takes Lucheng District, Wenzhou City, Zhejiang Province, southeastern China, as a case study and constructs an evaluation index system comprising three criterion levels: disaster-causing factors, disaster-gestation environments, and disaster-bearing bodies. The weights of each evaluation index are determined by combining the Analytic Hierarchy Process (AHP) and the entropy method. The fuzzy matter-element model is utilized to assess the flood disaster risk in Lucheng District quantitatively. By calculating the correlation degree of each evaluation index, the comprehensive index of flood disaster risk for each street area is obtained, and the flood disaster risk of each street area is classified according to the risk level classification criteria. Furthermore, the distribution of flood disaster risks in Lucheng District under different daily precipitation conditions is analyzed. The results indicate that: (1) the study area falls into the medium-risk category, with relatively low flood risks; (2) varying precipitation conditions will affect the flood resilience of each street in Lucheng District, Wenzhou City. The flood disaster evaluation index system and calculation framework constructed in this study provide significant guidance for flood risk assessment in coastal plain cities.
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