Coupling water cycle processes with water demand routes of vegetation using a cascade causal modeling approach in arid inland basins

Hu, Ruiyuan; Wang, Yimin; Chang, Jianxia; Istanbulluoglu, Erkan; Guo, Aijun; Meng, Xuejiao; Li, Zhehao; He, Bing; Zhao, Yuexin

doi:10.1016/j.scitotenv.2022.156492

Cited by 13 publications

(4 citation statements)

References 45 publications

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“…Therefore, a clear understanding of terrestrial water and vegetation is needed. Similarly, a clear understanding of the interactions between terrestrial water and vegetation greenness is particularly crucial for predicting future water cycles, especially in arid and semi-arid regions [11]. In this regard, the Normalized Difference Vegetation Index (NDVI) is considered to be a good indicator for identifying vegetation areas and long-term changes in their condition [12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Characteristics of NDVI in the Weihe River Basin and Its Correlation with Terrestrial Water Storage

Wei

Wan

2022

Remote Sensing

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The Weihe River Basin (WRB) of China is located in an arid and water-scarce semi-arid region with a fragile ecological environment, and it is meaningful to study the spatial and temporal changes in vegetation and terrestrial water storage changes in a small-scale inland basin. This study uses normalized difference vegetation index (NDVI) data and Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) time-variable gravity field models to derive changes in vegetation cover and water storage in the WRB from 2002 to 2020. Firstly, taking NDVI as the breakthrough point, the temporal and spatial characteristics of vegetation were analyzed by trend analysis method and F-test. Then, GRACE and GRACE-FO were used to derive water storage variations. Finally, the correlation between NDVI and water storage variations is discussed using the Pearson correlation analysis. The results show that the overall trend of NDVI is increasing, and the increasing trend is more evident before 2014, and after that, there is a significant fluctuation. The spatial distribution shows a large spatial variability, but the growing area still accounts for the majority, and the change varies by vegetation type, among which the cultivated vegetation is more influential. The overall change in terrestrial water storage showed a decreasing trend of −0.09 cm/yr, and also reflected a solid intra-annual regular cycle, i.e., reaching a trough from October to November and a peak from May to June each year. The correlation is 0.6 on the time scale, and there was a 3-month lag between NDVI and TWS. On the spatial scale, the percentage of areas with a negative correlation was about 95.4%, probably due to increased water consumption and evapotranspiration. The study’s results can help to understand the relationship between vegetation and water storage in the WRB and provide scientific support for local environmental management.

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Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Characteristics of NDVI in the Weihe River Basin and Its Correlation with Terrestrial Water Storage

Wei

Wan

2022

Remote Sensing

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“…In contrast to traditional SEM, the most evident characteristic of PLS-SEM (Partial least squares structural equation model) is that it does not strictly follow the standardized normal distribution assumptions for the observed variables [22]. There are two sub-models (measurement and structural) involved in PLS-SEM.…”

Section: Methods For Attributing Inter-annual Trends In Lake Areamentioning

confidence: 99%

Impacts of Climate Change and Human Activity on Lakes around the Depression of Great Lakes in Mongolia

Yang,

Zhou,

Liu

et al. 2024

Land

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The western region of Mongolia is characterized by an arid climate and a fragile ecological environment. It is a sensitive zone in response to global climate change and one of the major sources of dust globally. This region is home to numerous lakes, and their dynamic changes not only reflect global climate variations but also have implications for the global ecological environment quality. In this study, Landsat images were used as the data source, and Google Earth Engine (GEE) was employed to extract lakes with an area larger than 1 km2 from 1992 to 2021. The spatiotemporal characteristics of lake water area (LWA) changes were analyzed, and a structural equation model was applied to attribute the lake changes. The results indicate an overall trend of increasing lake area followed by a decrease in the study area. Specifically, lakes in the provinces of Khovd and Gobi-Altai exhibited a decreasing trend followed by an increasing trend, while lakes in the provinces of Uvs and Zavkhan showed an increasing trend followed by a decreasing trend. Three typical types of lakes, namely, alpine lakes, throughflow lakes, and terminal lakes, all exhibited a trend of increasing area followed by a decrease. The analysis of driving forces behind lake area changes reveals that climate change and human activities primarily exert indirect influences on the lake area changes in each province. Specifically, climate change and human activities lead to changes in soil moisture, which have a significant explanatory power for lake area changes. Regarding the typical types of lakes, climate change serves as the primary driving force for alpine lakes, while human activities are the main driving forces for throughflow lakes and terminal lakes.

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“…The measurement model joins the observed variable (x jh ) to its corresponding latent variable, also known as the external model. The specific algorithm is as follows [37]:…”

Section: Pls-semmentioning

confidence: 99%

Comparative Assessment of the Spatiotemporal Dynamics and Driving Forces of Natural and Constructed Wetlands in Arid and Semiarid Areas of Northern China

Zhang,

Qin,

Zhang

et al. 2023

Land

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Arid and semiarid wetlands, the core geographical unit of desert oases, significantly benefit and improve the ecological environment. In this study, we systematically compared the spatiotemporal dynamics and driving forces of natural and constructed wetlands in arid and semiarid regions of northern China from 1995 to 2019. For these comparisons, we utilized a land-use transition matrix, partial least-squares–structural equation model (PLS-SEM), and geographically weighted regression (GWR) model. The results showed that (1) the area of wetlands as a whole showed an upward trend, with natural and constructed wetlands increasing by 4.16% and 11.86%, respectively. The increases mainly resulted from conversions of grassland and other lands (shrub, sparse vegetation, and bare land). (2) The direct dominant factors that drove natural wetland changes were soil and terrain, while those that drove constructed wetlands were human disturbances. Human disturbance, by affecting soil, had a higher significant indirect effect on natural wetlands. Heat, by affecting moisture, had the greatest indirect effect on constructed wetlands. (3) The sensitivity of natural and constructed wetlands to the responses of different drivers showed significant spatial heterogeneity. This study explores the interaction and driving mechanisms of human and natural attributes on natural and constructed wetlands and provides a scientific foundation for the restoration and sustainable development of wetlands in arid and semiarid areas.

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Coupling water cycle processes with water demand routes of vegetation using a cascade causal modeling approach in arid inland basins

Cited by 13 publications

References 45 publications

Spatial and Temporal Characteristics of NDVI in the Weihe River Basin and Its Correlation with Terrestrial Water Storage

Spatial and Temporal Characteristics of NDVI in the Weihe River Basin and Its Correlation with Terrestrial Water Storage

Impacts of Climate Change and Human Activity on Lakes around the Depression of Great Lakes in Mongolia

Comparative Assessment of the Spatiotemporal Dynamics and Driving Forces of Natural and Constructed Wetlands in Arid and Semiarid Areas of Northern China

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