Precipitation is scarce in semi-arid areas, which results in serious drought. Occurrence of flash drought is quite often in these areas, and flash drought may also cause significant disasters. However, monitoring flash drought is still weak and remains a challenge. This study aims to identify, evaluate, and monitor flash drought events that occurred from 1961 to 2020 in reservoirs of the Ceará State, Brazil. The Christian's method, standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), and evaporative demand drought index (EDDI) were used to assess the severity and persistence of flash drought. Moreover, analyses conducted in 2001, 2008, 2011, 2012, 2016, and 2020 revealed the complexity and interaction of flash drought with environmental and meteorological factors. The results indicated that in dry years such as 2001, 2012, and 2016, drought indices pointed to the intensification of drought conditions, with impacts on major reservoirs in the area, such as Banabuiú, Castanhão, and Orós. Low precipitation, associated with high evaporative demand, intensified water stress, reducing water availability for the population and local ecosystems. In wet years such as 2008, 2011, and 2020, SPEI and EDDI indicated higher moisture levels and drought relief, favoring the recovery of reservoirs. It was also observed that most flash drought episodes evolved into conventional droughts, highlighting their persistence and potential long-term impact. Moreover, the months of May and November presented a higher frequency of flash drought during the wet and dry periods, respectively, negatively impacting most of the studied reservoirs. These findings underscore the need for effective drought monitoring and mitigation strategies to reduce its impacts on agriculture and water resources in the semi-arid area. Early detection and analysis of flash drought are important for improving water resource management and for continuous adaptation to changing drought conditions.

Understanding the impact of meteorological and topographical factors on snow cover fraction (SCF) is crucial for water resource management in the Qilian Mountains (QLM), China. However, there is still a lack of adequate quantitative analysis of the impact of these factors. This study investigated the spatiotemporal characteristics and trends of SCF in the QLM based on the cloud-removed Moderate Resolution Imaging Spectroradiometer (MODIS) SCF dataset during 2000-2021 and conducted a quantitative analysis of the drivers using a histogram-based gradient boosting regression tree (HGBRT) model. The results indicated that the monthly distribution of SCF exhibited a bimodal pattern. The SCF showed a pattern of higher values in the western regions and lower values in the eastern regions. Overall, the SCF showed a decreasing trend during 2000-2021. The decrease in SCF occurred at higher elevations, while an increase was observed at lower elevations. At the annual scale, the SCF showed a downward trend in the western regions affected by westerly (52.84% of the QLM). However, the opposite trend was observed in the eastern regions affected by monsoon (45.73% of the QLM). The SCF displayed broadly similar spatial patterns in autumn and winter, with a significant decrease in the western regions and a slight increase in the central and eastern regions. The effect of spring SCF on spring surface runoff was more pronounced than that of winter SCF. Furthermore, compared with meteorological factors, a variation of 46.53% in spring surface runoff can be attributed to changes in spring SCF. At the annual scale, temperature and relative humidity were the most important drivers of SCF change. An increase in temperature exceeding 0.04°C/a was observed to result in a decline in SCF, with a maximum decrease of 0.22%/a. An increase in relative humidity of more than 0.02%/a stabilized the rise in SCF (about 0.06%/a). The impacts of slope and aspect were found to be minimal. At the seasonal scale, the primary factors impacting SCF change varied. In spring, precipitation and wind speed emerged as the primary drivers. In autumn, precipitation and temperature were identified as the primary drivers. In winter, relative humidity and precipitation were the most important drivers. In contrast to the other seasons, slope exerted the strongest influence on SCF change in summer. This study facilitates a detailed quantitative description of SCF change in the QLM, enhancing the effectiveness of watershed water resource management and ecological conservation efforts in this region.

Intense evaporation in areas with loess-like sulfate saline soils has resulted in significant ecological challenges that include water shortages and soil salinization. Investigating evaporation rate in loess-like sulfate saline soils under varying salt contents carries crucial implications for understanding regional water loss processes, predicting soil salinization advancement, and formulating effective ecological management strategies. Therefore, this study sampled the loess-like sulfate saline soil that is widely distributed in western China as experimental materials and investigated the impact of different initial salt contents (0.00%, 0.50%, 1.50%, 3.00%, and 5.00%) on the evaporation rate, water content, and temperature of soil. The results showed that the evaporation rate decreased with increasing initial salt content. After a salt accumulation layer formed on the soil surface, the water content of the surface soil fluctuated. An increase in the initial salt content resulted in a corresponding increase in the surface temperature. Considering the evaporation characteristics of loess-like sulfate saline soil and the impact of an anomalous increase in surface soil water content on soil surface resistance, this study proposed a modified evaporation model on the basis of Fujimaki's evaporation model of saline soil by introducing a correction coefficient β to modify the soil surface resistance. A comparison of the calculated evaporation rates before and after the modification with the measured evaporation rates revealed a significant improvement in the calculation accuracy of the modified model, indicating that the modified model is capable of more accurately simulating the evaporation rate of sulfate saline soil with different initial salt contents. This paper proposes an effective method for calculating the evaporation rate of loess-like sulfate saline soils, providing a theoretical basis for evaporation research in saline soil.

Coal mining predisposes soils to heavy metal (HM) accumulation, which adversely affects the ecological environment and human health, particularly in extremely arid and vulnerable areas. In this study, soil samples were gathered from the Black Mountain Open Pit Coal Mine in Turpan City, Northwest China to determine the health risk of heavy metals (HMs). Results showed that positive matrix factorization model divided the sources of soil HMs into four categories, i.e., natural and animal husbandry (43.46%), industrial transportation (22.87%), fossil fuel combustion (10.64%), and atmospheric deposition and domestic pollution (23.03%). All kinds of pollution evaluation indices showed that Cd (cadmium) and Pb (plumbum) pollution was evident. The Monte Carlo simulated health risk assessment results showed that 4.00% non-carcinogenic risk and 12.00% carcinogenic risk were posed to children, and the positive matrix factorization-based health risk assessment showed that fossil fuel combustion had the highest contribution to the health risks to adults and children, while industrial transportation was the lowest. In this study, the risks of HMs in the soil of mining area were analyzed using source analysis, which not only provides reliable data support for the prevention and control of HM pollution in the soil of this arid mining area, but also provides a theoretical basis for subsequent regional research.

The Loess Plateau (LP), one of the most ecologically fragile regions in China, is affected by severe soil erosion and environmental degradation. Despite large-scale ecological restoration efforts made by Chinese government in recent years, the region continues to face significant ecological challenges due to the combined impact of climate change and human activities. In this context, we developed a kernal Remote Sensing Ecological Index (kRSEI) using Moderate Resolution Imaging Spectroradiometer (MODIS) products on the Google Earth Engine (GEE) platform to analyze the spatiotemporal patterns and trends in ecological environmental quality (EEQ) across the LP from 2000 to 2022 and project future trajectories. Then, we applied partial correlation analysis and multivariate regression residual analysis to further quantify the relative contributions of climate change and human activities to EEQ. During the study period, the kRSEI values exhibited significant spatial heterogeneity, with a stepwise degradation pattern in the southeast to northwest across the LP. The maximum (0.51) and minimum (0.46) values of the kRSEI were observed in 2007 and 2021, respectively. Trend analyses revealed a decline in EEQ across the LP. Hurst exponent analysis predicted a trend of weak anti-persistent development in most of the plateau areas in the future. A positive correlation was identified between kRSEI and precipitation, particularly in the central and western regions; although, improvements were limited by a precipitation threshold of 837.66 mm/a. A moderate increase in temperature was shown to potentially benefit the ecological environment within a certain range; however, temperature of -1.00°C-7.95°C often had a negative impact on the ecosystem. Climate change and human activities jointly influenced 65.78% of LP area on EEQ, primarily having a negative impact. In terms of contribution, human activities played a dominant role in driving changes in EEQ across the plateau. These findings provide crucial insights for accurately assessing the ecological state of the LP and suggest the design of future restoration strategies.

Understanding plant community assembly is crucial for effective ecosystem conservation and restoration. The ecological filter framework describes community assembly as a process shaped by dispersal, environmental, and biotic filters. Additionally, functional traits and phylogenetic relationships are increasingly recognized as important factors influencing species coexistence and community structure. However, both the ecological filter framework and the roles of functional traits and phylogeny in community assembly remain underexplored in the Algerian steppes—particularly in the El Bayadh region, where ongoing vegetation degradation threatens ecosystem stability. This study applied Hierarchical Modeling of Species Communities (HMSC) as an integrative approach to assess how ecological filters influence plant community assembly in the El Bayadh steppe and to evaluate the roles of functional traits and phylogenetic relationships in this process. Environmental data—including soil properties, topography, precipitation, and land use types (grazing and exclosure)—were collected across 50 plots in April and October, 2023, along with functional traits from 24 species. These traits include root length, leaf area, specific leaf area, clonality, life history, and seed mass. HMSC results revealed that soil properties and precipitation were the primary drivers of community structure, while sand height and elevation had a moderate influence. In contrast, competition and grazing played relatively minor roles. Species responses to environmental covariates were heterogeneous: soil fertility and texture had mixed effects, benefiting some species while limiting others; sand encroachment and precipitation variability generally had negative impacts, whereas grazing exclusion favored many species. A weak phylogenetic signal was recorded, indicating that community assembly was driven more by environmental filtering than by shared evolutionary history. Functional trait responses to environmental variation reflected plant strategies that balanced resource acquisition and conservation. Specifically, seed mass, leaf area, and root length increased under higher soil moisture and nutrient availability but declined in response to salinity, precipitation variability, and sand height. Clonality and perennial life history traits enhanced the survival of plant species under harsh conditions. Overall, this study provides a holistic understanding of community assembly processes in the El Bayadh steppe and offers valuable insights for ecosystem management and restoration in arid and degraded ecosystem environments.

Grassland is a key component of the ecosystem in the Qinghai Lake Basin, China. Understanding the effects of climate change and human activities on grassland productivity significantly improves ecological conservation and promotes sustainable vegetation growth in this area. Based on the net primary productivity (NPP) products of MOD17A3HGF (a moderate-resolution imaging spectroradiometer (MODIS) product that provides annual NPP at 500 m resolution) and meteorological data, we analyzed the spatial and temporal evolution of grassland NPP and its interaction with climate factors in the Qinghai Lake Basin from 2001 to 2022 via partial correlation and trend analysis methods. We also used the deflecting trend residual method and scenario analysis method to quantitatively assess the relative contributions of climatic factors and human activities to grassland NPP. The results revealed that: (1) during the past 22 a, grassland NPP increased considerably, with a gradient change from the northwest to the southeast of the study area; (2) sunshine duration, precipitation, and temperature positively influenced grassland NPP, with sunshine duration exerting a stronger effect on grassland NPP than precipitation and temperature; and (3) 98.47% of the grassland in the study area was restored, with an average contribution of 65.00% from human activities and 35.00% from climatic alterations. Compared with climate change, human-induced factors had a greater effect on grassland NPP in this area. The results of the study not only provide important scientific support for ecological restoration and sustainable development of the basin but also offer new ideas for research on similar ecologically fragile areas.

Biochar and animal manure application can improve crop yields in salt-affected soil. Previous studies have primarily applied biochar and animal manure either alone or at fixed ratios, while their combined effects with varying combination proportions are still unclear. To address this knowledge gap, we performed a 2-a experiment (2023-2024) in a salinized cotton field in Wensu County of Xinjiang Uygur Autonomous Region of China with the following 6 treatments: control; application of biochar (10 t/hm²) alone (BC100%); application of cow manure (10 t/hm²) alone (CM100%); application of 70% biochar (7 t/hm²) combined with 30% cow manure (3 t/hm²) (BC70%+CM30%); application of 50% biochar (5 t/hm²) combined with 50% cow manure (5 t/hm²) (BC50%+CM50%); and application of 30% biochar (3 t/hm²) combined with 70% cow manure (7 t/hm²) (BC30%+CM70%). By measuring soil pH, electrical conductivity, soil organic matter, available phosphorus, available potassium, and available nitrogen at 0-20 and 20-40 cm depths, as well as yield components and cotton yield in 2023 and 2024, this study revealed that soil nutrients in the 0-20 cm depth were more sensitive to the treatment. Among all the treatments, BC50%+CM50% treatment had the highest value of soil pH (9.63±0.07) but the lowest values of electrical conductivity (161.9±31.8 μS/cm), soil organic matter (1.88±0.27 g/kg), and available potassium (42.72±8.25 mg/kg) in 2024. Moreover, the highest cotton yield (5336.63±467.72 kg/hm²) was also observed under BC50%+CM50% treatment in 2024, which was 1.9 times greater than that under the control treatment. In addition, cotton yield in 2023 was jointly determined by yield components (density and number of cotton bolls) and soil nutrients (available phosphorus and available potassium), but in 2024, cotton yield was only positively related to yield components (density, number of cotton bolls, and single boll weight). Overall, this study highlighted that in salt-affected soil, the combination of biochar and cow manure at a 1:1 ratio is recommended for increasing cotton yield and reducing soil salinity stress.