Spatially Non-Stationary Relationships between Changing Environment and Water Yield Services in Watersheds of China’s Climate Transition Zones

Abstract

Identifying the spatial and temporal heterogeneity of water-related ecosystem services and the mechanisms influencing them is essential for optimizing ecosystem governance and maintaining watershed sustainable development. However, the complex and undiscovered interplay between human activities and natural factors underpins the solutions to the water scarcity and flooding challenges faced by climate transition zone basins. This study used a multiple spatial-scale analysis to: (i) quantify the spatial and temporal variations of the water yield ecosystem service (WYs) of the Wei River Basin (WRB) from 2000 to 2020 using the InVEST model and remote sensing data; and (ii) look at how human activities, climate, topography, and vegetation affect the WYs at the climate transition zone sub-catchment scale using the geographical detector model and multi-scale geographically weighted regression (MGWR). The conclusive research reveals that there would be a gradual increase in WYs between the years 2000 and 2020, as well as a distinct and very different spatial aggregation along the climatic divide. The average yearly precipitation was shown to be particularly linked to the water yield of the WRB. The interplay of human, climatic, plant, and terrain variables has a substantially higher influence than most single factors on the geographical differentiation of WYs. Bivariate enhancement and non-linear enhancement are the most common types of factor interactions. This shows that there are significant interactions between natural and human variables. Our study shows that precipitation and temperature are the main factors that cause WYs in the semi-arid zone. In the semi-humid zone, precipitation and vegetation are the key controlling factors that cause WYs. We provide new perspectives for understanding and optimizing ecosystem management by comparing the drivers of WYS in sub-basins with different climatic conditions. Based on the findings, we recommend that particular attention should be paid to ecosystem restoration practices in watersheds in climatic transition zones.

Combining APHRODITE Rain Gauges-Based Precipitation with Downscaled-TRMM Data to Translate High-Resolution Precipitation Estimates in the Indus Basin

“…The actual ET, LST, and slope were found to be equally important in the model for predicting precipitation data. Several variables were introduced in the RF and MGWR model to predict the high-resolution precipitation forecast in the Indus Basin, although the geographically weightage regression (GWR) model has a widely applied approach to building non-stationary relationships between the explanatory variables and prediction (TRMM in our case) [45,75,76], and these relationships facilitate the downscaling spatial resolution of gridded satellite products [45,74]. The GWR model considers all input variables' coefficients as non-stationary, which is invalid.…”

Exploring driving factors of soil erosion using a Multiscale GWR model: a case study at Central Citarum Watershed, West Java, Indonesia

“…To obtain an optimal regression model, the initial step involved selecting key variables, removing unnecessary ones, and ensuring that explanatory variables were not multicollinear, as determined by the Variance Inflation Factor (VIF) values. We removed driving factors with a VIF greater than ten, indicating multicollinearity among those variables [12,14].…”

Spatiotemporal Variation and Quantitative Attribution of Carbon Storage Based on Multiple Satellite Data and a Coupled Model for Jinan City, China

“…Second, since most carbon storage processes follow a non-linear storage path, the construction of a non-linear response model of carbon storage rate versus time can be enhanced in the future to improve the accuracy of carbon storage amounts. Finally, forest ecosystem management under climate change and other ecosystem services, such as water conservation, soil and water conservation, and habitat quality, is also worth studying [69][70][71]. At the same time, we only analyzed carbon sequestration by regulating services, so a future research direction includes exploring the synergistic and trade-off characteristics of integrated ecosystem services.…”