Evaluating net primary productivity dynamics and their response to land-use change in the loess plateau after the 'Grain for Green' program.

Assessing net primary productivity (NPP) dynamics and the contribution of land-use change (LUC) to NPP can help guide scientific policy to better restore and control the ecological environment. Since 1999, the "Green for Grain" Program (GGP) has strongly affected the spatial and temporal pattern of NPP on the Loess Plateau (LP); however, the multifaceted impact of phased vegetation engineering measures on NPP dynamics remains unclear. In this study, the Carnegie-Ames-Stanford Approach (CASA) model was used to simulate NPP dynamics and quantify the relative contributions of LUC and climate change (CC) to NPP under two different scenarios. The results showed that the average NPP on the LP increased from 240.7 gC·m-2 to 422.5 gC·m-2 from 2001 to 2020, with 67.43% of the areas showing a significant increasing trend. LUC was the main contributor to NPP increases during the study period, and precipitation was the most important climatic factor affecting NPP dynamics. The cumulative amount of NPP change caused by LUC (ΔNPPLUC) showed a fluctuating growth trend (from 46.23 gC·m-2 to 127.25 gC·m-2), with a higher growth rate in period ΙΙ (2010-2020) than in period Ι (2001-2010), which may be related to the accumulation of vegetation biomass and the delayed effect of the GGP on NPP. The contribution rate of LUC to increased NPP in periods Ι and ΙΙ was 101.2% and 51.2%, respectively. Regarding the transformation mode, the transformation of grassland to forest had the greatest influence on ΔNPPLUC. Regarding land-use type, the increased efficiency of NPP was improved in cropland, grassland, and forest. This study provides a scientific basis for the scientific management and development of vegetation engineering measures and regional sustainable development.

Evaluating multifaceted effects of watershed properties and human activities on drought propagation in the Wei River Basin with an integrated framework.

Understanding the factors driving propagation from meteorological to hydrological drought is crucial for drought mitigation. In this study, an integrated framework based on the Soil and Water Assessment Tool model, standardised drought indices and Geographical Detector were used to investigate how and to what extent watershed properties and human activities affect the spatial heterogeneity of drought propagation in the Wei River Basin, a typical arid and semi-arid region in China. Results indicated that (1) spatially, the propagation times increased from southwest to northeast. Seasonally, the propagation was shorter and stronger in summer and autumn. (2) The aridity index significantly affected the spatial distribution of drought propagation time for the entire basin, especially in summer, while human activities primarily drove spatial distribution in the sub-basins. The explanatory power of any two independent factors was non-linearly enhanced after the interaction. (3) Watershed properties potentially impacted the anthropogenic driving factor of drought propagation. Strong anthropogenic effects on drought propagation often occurred in watersheds with moderate drought levels, steep slopes, low elevations, and small areas, and the key factors varied seasonally. These findings help elucidate the multifaceted effects of watershed properties and human activities on drought propagation. The proposed framework and the results of this study provide valuable guidance for formulating precise drought control strategies in the Wei River Basin and worldwide.

Analysis and simulation of the driving mechanism and ecological effects of land cover change in the Weihe River basin, China.

Land cover change (LCC) is both a consequence and a cause of global environmental change. This paper attempts to construct a framework to reveal the driving mechanism and ecological effects of different ecological factors under LCC and to explore the ecological characteristics of future LCC. A rule-mining framework based on a land expansion analysis strategy (LEAS) in the patch-generating land use simulation (PLUS) model was used to analyze the drivers of LCC. Neighborhood analysis and ecological effect index were used to investigate multiple ecological effects of LCC. Remote sensing-based ecological indices (RSEI) and the PLUS and stepwise regression model were introduced to explore and predict the integrated ecological effect of LCC. Focusing on the Weihe River basin, study's main drivers of LCC were precipitation, temperature, elevation, population, water table depth, proximity to governments and motorways, GDP, and topsoil organic carbon were the main drivers of LCC. Change directionality were similar for the effects of greenness and biomass formation but opposite for summertime and wintertime temperature. In addition, the conversion of land cover types to cropland had the most significant integrated ecological effect, followed by forest, grassland-shrubland, and other types. The RSEI is predicted to rise to 0.77 in 2030, and the areas where the ecological quality grade will improve and decrease are concentrated on the east and west sides of Ziwuling Mountain, respectively. The findings of this study have practical significance for land management and ecological protection.

Assessing the Variability of Heavy Metal Concentrations in Liquid-Solid Two-Phase and Related Environmental Risks in the Weihe River of Shaanxi Province, China.

Accurate estimation of the variability of heavy metals in river water and the hyporheic zone is crucial for pollution control and environmental management. The biotoxicities and potential ecological risks of heavy metals (Cu, Zn, Pb, Cd) in a solid-liquid two-phase system were estimated using the Geo-accumulation Index, Potential Ecological Risk Assessment and Quality Standard Index methods in the Weihe River of Shaanxi Province, China. Water and sediment samples were collected from five study sites during spring, summer and winter, 2013. The dominant species in the streambed sediments were chironomids and flutter earthworm, whose bioturbation mainly ranged from 0 to 20 cm. The concentrations of heavy metals in surface water and pore water varied obviously in spring and summer. The degrees of concentration of Cu and Cd in spring and summer were higher than the U.S. water quality Criteria Maximum Concentrations. Furthermore, the biotoxicities of Pb and Zn demonstrated season-spatial variations. The concentrations of Cu, Zn, Pb and Cd in spring and winter were significantly higher than those in summer, and the pollution levels also varied obviously in different layers of the sediments. Moreover, the pollution level of Cd was the most serious, as estimated by all three assessment methods.