Impact of Land Use Change on Water Conservation: A Case Study of Zhangjiakou in Yongding River

Evaluation and prediction of water conservation of the Yellow river basin in Sichuan Province, China, based on Google Earth Engine and CA-Markov

The Yellow River Basin in China has the world's most serious soil erosion problem. The Yellow River Basin in Sichuan Province (YRS), as the upper reaches of the Yellow River, and its water conservation (WC) capacity greatly affects the ecological environment of the downstream basin. In recent years, YRS has received more and more attention, and numerous policies have been developed to improve local WC. However, there is a vacancy in the long-term research of WC in the YRS due to the lack of in-situ data. This study quantitatively evaluated the WC of YRS from 2001 to 2020 through Google Earth Engine (GEE) and analyzed the spatio-temporal variations of WC and land cover (LC). CA-Markov predicted the LC and WC in 2025 under three scenarios to assess the contribution of different scenarios to WC. The WC in YRS fluctuated from 1.93 to 6.77 billion m3. The climate is the dominant factor of WC change, but the effect of LC on WC is also evident. The WC capacity increases with vegetation coverage and height. The WC capacity of forests per km2 exceeds 600 mm, while that of grasslands is about 250 mm, and barren can cause around 300 mm of WC loss. In 2025, the WC in YRS may exceed 7.5 billion m3, but the past ecological management mode should be transformed. Improving the quality of land use and converting grasslands to forests is better than reducing cropland to improve WC.

Spatial-Temporal Variations in of Soil Conservation Service and Its Influencing Factors under the Background of Ecological Engineering in the Taihang Mountain Area, China

Soil conservation (SC) plays an important role in maintaining regional land productivity and sustainable development. Ecological engineering (EE) is being implemented in different countries to effectively alleviate the damage to the ecological environment and effectively protect soil and food security. It is important to determine whether or not the SC capacity becomes stronger after the implementation of EE and whether or not EE has a notable impact on SC in different altitude zones. The exploration of the influencing mechanism and identification of the dominate influencing factors in different geographical regions needs to be improved. In this study, the soil conservation services (SCSs) from 1980 to 2020 in the Taihang Mountain area was assessed using the integrated valuation of ecosystem services and trade-offs (InVEST) model, and the spatial and temporal distributions and influencing factors were explored. The results showed the following: (1) the average SCSs exhibited an increasing trend from 1980 to 2020 on the whole, and the rate of increase reached 50.53% during the 41-year period. The rate of increase of the SCSs varied in the different EE implementation regions, and it was significantly higher than that of the entire study area. (2) The spatial distribution of the SCSs was highly heterogeneous, and the high SCS value areas were coincident with the high-altitude areas where forest and grassland occupied a large proportion. The low value areas were mainly located in the hilly zone or some of the basin regions where the proportion of construction land was relatively high. (3) The distribution pattern of the SCSs was the result of multiple factors. The EE intensity had the strongest explanatory power for the SCSs in the hilly zone, explaining 34.63%. The slope was the most critical factor affecting the SCSs in the mid-mountain and sub-alpine zones. The slope and normalized difference vegetation index (NDVI) had the greatest interactions with the other factors in the three altitude zones, especially in the high-altitude regions. The quantitative analysis of the SCSs and the influences of EE and natural factors on the SCSs revealed the heterogeneity in the mountainous areas. These results also provide a scientific basis for the reasonable implementation of EE and sustainable management of SCSs in the Taihang Mountain area.

Driving factors of ecosystem services and their spatiotemporal change assessment based on land use types in the Loess Plateau

A clear understanding of the driving factors for different ecosystem services (ESs) is quite essential for sustainable ecosystem management. It is important to strengthen research in ESs and social sustainable development to identify the main driving factors of different ESs. This study assessed carbon sequestration (CS), water yield (WY) and soil conservation (SC) from 2000 to 2018 in the Loess Plateau using CASA (The Carnegie-AmesStanford Approach), InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) and RUSLE (Revised Universal Soil Loss Equation) models. The spatial heterogeneity, trade-offs and synergies and driving factors were explored in the whole Loess Plateau. The results showed that the WY, CS and SC had increased from 2000 to 2018. The spatial relationships between WY and SC, SC and CS, and WY and CS were mainly synergistic. Annual mean precipitation (MAP) was the dominant driving factor of WY, while normalized difference vegetation index (NDVI) and slope (SL) had the strongest explanatory power for CS and SC. The LU was the most critical factor affecting the ESs in the different climatic zones. These results could act as a reference for decision-makers on how to control various influencing factors of ESs to improve the local ecology under local conditions.

Study on the Relationship between Snowmelt Runoff for Different Latitudes and Vegetation Growth Based on an Improved SWAT Model in Xinjiang, China

Rivers located in high altitude mountainous areas provide a large number of water resources and are also high-risk areas for seasonal snow melt floods. The accurate calculation and simulation of snow melting processes can provide reliable data for flood disaster prediction. In order to make the Soil and Water Assessment Tool (SWAT) model more suitable for high altitude mountainous areas, the effect of the daily accumulated temperature on the precipitation pattern and snow melting is fully considered. Applying the modified model to three mountain systems with different latitudes in Xinjiang can not only improve our understanding of the characteristics of snowmelt flooding but can also be used to test the applicability of the modified model. Through comparison, it was found that the simulation accuracy of the modified model of the flood peak value was improved by 56.19%. The correlation coefficient between the Normalized Difference Vegetation Index (NDVI) and snowmelt increased from 0.27 to 0.68. This study provides a new method for accurately understanding the process of snowmelt runoff in the mountainous area and provides new insights into the effects of snowmelt runoff on vegetation growth at different latitudes.