A spatiotemporal optimization method for nutrient control in lake watersheds. Journal of environmental management Developing an efficient strategy for managing nutrients in less-developed lake watersheds that can balance the need for socioeconomic progress with the protection of aquatic ecosystems has become an urgent research subject for achieving sustainable development. This paper improves the optimization method for environmental and economic management of lake watersheds proposed in our previous research. A spatiotemporal optimization method based on a coupling model consisting of the Soil and Water Assessment Tool, system dynamics model, and objective programming model was applied to an agricultural non-point source (ANPS) pollution control program and a rural sewage treatment program at the Yilong Lake watershed as a case study. A simulation evaluation showed that the efficiency of the previous scheme was significantly improved after conducting spatiotemporal optimization. This scheme was dynamic and distributed, demonstrating an annual and high-resolution control program that can provide a basis for the precise management of ANPS. Although it still requires improvement, a framework for coupling simulation and two-step optimization was achieved in this study. 10.1016/j.jenvman.2023.119608

New modeling framework for describing the effects of landscape pattern changes on nutrient pollution transport. The Science of the total environment Landscape pattern plays a crucial role in regulating hydrological and pollutant migration processes. However, there is a lack of quantitative tools to describe the nutrient pollution transport process under the influence of different landscape patterns. To fill this gap, this study presents a new modeling framework, namely the Landscape Pattern-Source Flow Sink model (LP-SFS). The model consists of three modules: nutrient pollution emission, land transport, and river transport. Each module is implemented using a separate calculation program. It characterizes the transport path of pollutants on landscape units conceptually and operationally and focuses on quantifying the blocking effect of grid-scale landscape units on nutrients. The framework takes the Luanhe River Basin in the North China Plain as an exemplary case. The simulation results of the new framework indicated that in regions predominantly occupied by forest and urban (FU), the intensity of terrestrial pollutant migration attained the highest level. In the slope zone ranging from 25 to 35°, owing to the relatively strong responsiveness of water flow and gravity to the slope, soil erosion is inclined to occur, thereby causing the intensity of terrestrial nutrient pollution transport in this slope zone to reach the maximum value of 4.55 kg/km. Furthermore, in the elevation zone <700 m, urban and cultivated land was concentratedly distributed, which leads to more pollutants entering surface water bodies and increases the intensity of terrestrial migration of pollutants. The complex boundary shape of forestland and grassland in the watershed weakened the transport capacity of nutrients, resulting in pollutants remaining in the soil and being difficult to be transported to surface water bodies. This new method is applicable to large-scale watersheds with strong spatial heterogeneity and severe landscape fragmentation and can provide technical support for nutrient pollution control and optimization of land resource allocation in large-scale watersheds. 10.1016/j.scitotenv.2024.178090

Optimization of landscape pattern in the main river basin of Liao River in China based on ecological network. Environmental science and pollution research international As a main stream method of landscape pattern optimization, the ecological network plays an important role in maintaining ecosystem stability, improving landscape connectivity, and promoting landscape sustainable development. Based on landscape connectivity index and morphological spatial pattern analysis (MSPA), a comprehensive evaluation system of ecological patches was constructed in the main river basin of Liao River, and ecological sources were extracted. According to the habitat characteristics of the study area, the ecological cumulative resistance surface was constructed, and the ecological corridors and nodes were extracted by the minimum cumulative resistance (MCR) model. The ecological network of the study area was comprehensively evaluated by using the network analysis method, and the importance level of the ecological corridor was divided by the gravity model, so as to put forward the optimization suggestions of the landscape pattern based on the ecological network. The results showed that the ecological network in the main river basin of Liao River is composed of 20 ecological sources, 108 ecological corridors, and 72 ecological nodes, with the distribution characteristics of dense east and sparse west. The main landscape components are cropland and woodland. The closure degree, line point rate, and connectivity index of the ecological network are 0.27, 1.50, and 0.51, respectively, and the cost ratio is 0.23. In the optimization of landscape pattern, priority should be given to the restoration of primary ecological sources and ecological corridors, followed by the ecological construction of secondary and tertiary ecological sources and ecological corridors, the rational use of engineering technology for habitat remodeling, and the adoption of the "patch-corridor-substrate" model to improve the stability and landscape connectivity of the regional ecosystem. The construction of ecological network in the main river basin of Liao River is of great significance to regional ecological security and biodiversity conservation, and provides data support for optimizing the landscape pattern of the basin and promoting regional sustainable development. 10.1007/s11356-023-26963-w

Influence of climate and landscape structure on soil erosion in China's Loess Plateau: Key factor identification and spatiotemporal variability. The Science of the total environment Climate and landscape structure are widely recognized as the primary drivers of soil erosion; however, the spatiotemporal variability of their effects remains insufficiently understood, limiting our comprehension of the dynamic processes of soil erosion. To address this gap, this study analyzed soil erosion trends on the Loess Plateau from 2000 to 2018. extreme Gradient Boosting was used to identify key climatic and landscape structural factors, while a geographically and temporally weighted regression model was applied to assess the spatiotemporal variability of these influences. The results indicate a decreasing trend in soil erosion from 2000 to 2008, followed by a sharp increase from 2008 to 2018. Grassland edge density emerged as the most important factor, followed closely by grassland percentage and annual precipitation. Temporally, the positive effect of annual precipitation has been intensifying since 2010, contributing to increased erosion, while landscape structural factors progressively enhanced their hydrological regulatory roles, reflecting dynamic interactions with climate. Spatially, the direction of climatic influences remained generally stable, consistently promoting erosion, although by 2018, the effects of average annual temperature and annual sunshine duration reversed to suppress erosion in specific areas. In contrast, landscape structural influences exhibited greater spatial variability, often fluctuating or reversing depending on topography, human activity, and land use. This variability applied specifically and differentially to each metric of fragmentation and diversity, highlighting the critical importance of trade-offs in landscape management. The findings emphasize the complexity and dynamics of soil erosion in response to climate and landscape structure, suggesting implications for the development of spatially targeted soil erosion control strategies that accommodate the phases of temporal variation. 10.1016/j.scitotenv.2024.177471

Modelling of soil erosion susceptibility incorporating sediment connectivity and export at landscape scale using integrated machine learning, InVEST-SDR and Fragstats. Journal of environmental management Evaluating the linkage between soil erosion and sediment connectivity for export assessment in different landscape patterns at catchment scale is valuable for optimization of soil and water conservation (SWC) practices. Present research attempts to identify the soil erosion susceptible (SES) sites in Kangsabati River Basin (KRB) using machine learning algorithm (decision trees, decision trees cross validation, CV, Extreme Gradient Boosting, XGB CV and bagging CV) taken thirty five variables, for investigating the linkage between erosion rates and sediment connectivity to assess the sediment export at sub-basin level employing connectivity index (IC) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) sediment delivery ratio (SDR) model. Based on AUC of receiving operating curve in validation test, excellent capacity of extreme Gradient Boosting, XGB CV and bagging CV (0.95, 0.90) than decision tree and decision tree CV (0.78, 0.82), exhibits about 18.58 % of basin areas facing susceptible to very high erosion. Conversely, considering universal soil loss equation (RUSLE) parameters, InVEST-SDR model estimated about 64.24 % of soil loss rate occurred from high SES in where sediment export rate become very high (136.995 t/ha/y). The IC result show that high sediment connectivity (<-4.4) measured in high SES of laterite and bare land in upper catchment, and double crop agricultural areas in lower catchment, while least connectivity (>-7.1) observed in low SES of dense forest, vegetation cover and settlement built-up areas. Pearson correlation matrix revealed that four landscape indices category i.e. edge metrics (p < 0.01), aggregation metrics (p < 0.001), shape metrics (p < 0.01-0.001) and diversity metrics (p < 0.01) signified the influence of landscape patterns on IC and SES. Accordingly, RUSLE, SDR and landscape matrices reveals that maximum sediment export rate associated with high connective delivery outlet and high SES in laterite, double crop and bare land due to simple landscape and greater homogeneity, whilst minimum export rate related with low connectivity and low SES in dense forest, vegetation cover and settlement built up area causes of fragmented landscape and spatial heterogeneity. Finally, findings could immense useful for formulating the optimizing measures of SWC in the watershed. 10.1016/j.jenvman.2024.120164