Search Results (155)

Vegetation dynamics are complexly influenced by multiple factors such as climate, human activities, and topography. In recent years, the frequency, intensity, and diversity of human activities have increased, placing substantial pressure on the growth of vegetation. Arid and semi-arid regions are particularly sensitive to climate change, and climate change and large-scale ecological restoration have led to significant changes in the dynamic of dryland vegetation. However, few studies have explored the nonlinear relationships between these factors and vegetation dynamic. In this study, we integrated trend analysis (using the Mann–Kendall test and Theil–Sen estimation) and machine learning algorithms (XGBoost-SHAP model) based on long time-series remote sensing data from 2001 to 2020 to quantify the nonlinear response patterns and threshold effects of bioclimatic variables, topographic features, soil attributes, and anthropogenic factors on vegetation dynamic. The results revealed the following key findings: (1) The kNDVI in the study area showed an overall significant increasing trend (p < 0.01) during the observation period, of which 26.7% of the area showed a significant increase. (2) The water content index (Bio 23, 19.6%), the change in land use (15.2%), multi-year average precipitation (pre, 15.0%), population density (13.2%), and rainfall seasonality (Bio 15, 10.9%) were the key factors driving the dynamic change of vegetation, with the combined contribution of natural factors amounting to 64.3%. (3) Among the topographic factors, altitude had a more significant effect on vegetation dynamics, with higher altitude regions less likely to experience vegetation greening. Both natural and anthropogenic factors exhibited nonlinear responses and interactive effects, contributing to the observed dynamic trends. This study provides valuable insights into the driving mechanisms behind the condition of vegetation in arid and semi-arid regions of China and, by extension, in other arid regions globally. Full article

The main soil type in the Sanjiang Plain of Northeast China, dryland albic soil is of great significance for studying nutrient distribution characteristics. This study focuses on 852 Farm in the typical dryland albic soil area of the Sanjiang Plain, using a combination of paired t-test, geostatistics, correlation analysis, and principal component analysis to systematically reveal the spatial differentiation of soil nutrients in the black soil layer and white clay layer of dryland albic soil, and to clarify the impact mechanism of plow layer nutrient characteristics on crop productivity. The results show that the nutrient content order in both the black and white clay layers is consistent: total potassium (TK) > organic matter (OM) > total nitrogen (TN) > total phosphorus (TP) > alkali-hydrolyzable nitrogen (HN) > available potassium (AK) > available phosphorus (AP). Both layers exhibit a spatial pattern of overall consistency and local differentiation, with spatial heterogeneity dominated by altitude gradients—nutrient content increases with decreasing altitude. Significant differences exist in nutrient content and distribution between the black and white clay layers, with the comprehensive fertility of the black layer being significantly higher than that of the white clay layer, particularly for TN, TP, TK, HN, and OM contents (effect size > 8). NDVI during the full maize growth period is significantly positively correlated with TP, TN, AK, AP, and HN, and the NDVI dynamics (first increasing. then decreasing) closely align with the peak periods of available nitrogen/phosphorus and crop growth cycles, indicating a strong coupling relationship between vegetation biomass accumulation and nutrient availability. These findings provide important references for guiding rational fertilization, agricultural production layout, and ecological environmental protection, contributing to the sustainable utilization of dryland albic soil resources and sustainable agricultural development. Full article

Leaf phenology is key to ecosystem functioning by regulating carbon, water, and energy fluxes and influencing vegetation productivity. Yet, detecting land surface phenology (LSP) in drylands using remote sensing remains particularly challenging due to sparse and heterogeneous vegetation cover, high spatiotemporal variability, and complex spectral signals. Unlike the Northern Hemisphere, these challenges are further compounded in the Southern Hemisphere (SH), where several regions experience year-round moderate temperatures. When combined with irregular rainfall, this leads to highly variable vegetation activity throughout the year. However, LSP dynamics in the SH remain poorly understood. This study presents a review of remote sensing-based phenology research in drylands, integrating (i) a synthesis of global methodological advances and (ii) a systematic analysis of peer-reviewed studies published from 2015 through April 2025 focused on SH drylands. This review reveals a research landscape still dominated by conventional vegetation indices (e.g., NDVI) and moderate-spatial-resolution sensors (e.g., MODIS), though a gradual shift toward higher-resolution sensors such as PlanetScope and Sentinel-2 has emerged since 2020. Despite the widespread use of start- and end-of-season metrics, their accuracy varies greatly, especially in heterogeneous landscapes. Yet, advanced products such as solar-induced chlorophyll fluorescence or the fraction of absorbed photosynthetically active radiation were rarely employed. Gaps remain in the representation of hyperarid zones, grass- and shrub-dominated landscapes, and large regions of Africa and South America. Our findings highlight the need for multi-sensor approaches and expanded field validation to improve phenological assessments in dryland environments. The accurate differentiation of vegetation responses in LSP is essential not only for refining phenological metrics but also for enabling more realistic assessments of ecosystem functioning in the context of climate change and its impact on vegetation dynamics. Full article

Afforestation with Pinus sylvestris var. mongolica in northern China is hindered by soil degradation. This study evaluated a ternary amendment combining sewage sludge (SS), cattle manure (CM), and maize straw (MS) to rehabilitate degraded sandy soils in the Horqin Sandy Land. Five treatments were tested: control (CK), SS (T1), SS + CM (T2), SS+MS (T3), and SS + CM + MS (T4). The ternary amendment (T4) achieved optimal outcomes: soil pH decreased from 8.02 to 7.79, organic carbon increased 2.5–fold, and total nitrogen (127%) and phosphorus (87.5%) were enhanced compared to CK. Pinus sylvestris exhibited a 65.6% greater basal diameter and 29.5% height increase under T4, while heavy metal concentrations (Cd: −54.6%, Cu: −35.1%, Pb: −12.2% and Zn: −27.6%) were reduced. These findings highlight a synergistic waste valorization strategy for dryland afforestation, balancing soil fertility improvement with ecological safety. Future studies should prioritize long-term microbial community dynamics and field-scale validation. Full article

Efficient water management is critical for sustainable dryland agriculture, especially under increasing water scarcity and climate variability. Shanxi Province, a typical dryland region in northern China characterized by pronounced climatic variability and limited soil water availability, faces severe challenges due to uneven precipitation and restricted water resources. This study aimed to evaluate the spatiotemporal dynamics of soil water resources and their coupling with crop water demand under different hydrological year types. Using daily meteorological data from 27 stations (1963–2023), we identified dry, normal, and wet years through frequency analysis. Soil water resources were assessed under rainfed conditions, and water deficits of major crops—including millet, soybean, sorghum, winter wheat, maize, and potato—were quantified during key reproductive stages. Results showed a statistically significant declining trend in seasonal precipitation during both summer and winter cropping periods (p < 0.05), which corresponds with the observed intensification of crop water stress over recent decades. Notably, more than 86% of daily rainfall events were less than 5 mm, indicating low effective rainfall. Soil water availability closely followed precipitation distribution, with higher values in the south and west. Crop-specific analysis revealed that winter wheat and sorghum had the largest water deficits in dry years, necessitating timely supplemental irrigation. Even in wet years, water regulation strategies were required to improve water use efficiency and mitigate future drought risks. This study provides a practical framework for soil water–crop demand assessment and supports precision irrigation planning in dryland farming. The findings contribute to improving agricultural water use efficiency in semi-arid regions and offer valuable insights for adapting to climate-induced water challenges. Full article

Arid and semi-arid regions serve as crucial ecological barriers in China, making the spatiotemporal evolution of their ecological environmental quality (EEQ) scientifically significant. This study developed a Modified Remote Sensing Ecological Index (MRSEI) by innovatively integrating the Comprehensive Salinity Indicator (CSI) into the Remote Sensing Ecological Index (RSEI) and applied it to systematically evaluate the spatiotemporal evolution of EEQ (2014–2023) in Yinchuan City, a typical arid region of northwest China along the upper Yellow River. The study revealed the spatiotemporal evolution patterns through the Theil–Sen (T-S) estimator and Mann–Kendall (M-K) test, and adopted the Light Gradient Boosting Machine (LightGBM) combined with the Shapley Additive Explanation (SHAP) to quantify the contributions of ten natural and anthropogenic driving factors. The results suggest that (1) the MRSEI outperformed the RSEI, showing 0.41% higher entropy and 5.63% greater contrast, better characterizing the arid region’s heterogeneity. (2) The EEQ showed marked spatial heterogeneity. High-quality areas are concentrated in the Helan Mountains and the integrated urban/rural development demonstration zone, while the core functional zone of the provincial capital, the Helan Mountains ecological corridor, and the eastern eco-economic pilot zone showed lower EEQ. (3) A total of 87.92% of the area (7609.23 km²) remained stable with no significant changes. Notably, degraded areas (934.52 km², 10.80%) exceeded improved zones (111.04 km², 1.28%), demonstrating an overall ecological deterioration trend. (4) This study applied LightGBM with SHAP to analyze the driving factors of EEQ. The results demonstrated that Land Use/Land Cover (LULC) was the predominant driver, contributing 41.52%, followed by the Digital Elevation Model (DEM, 18.26%) and Net Primary Productivity (NPP, 12.63%). This study offers a novel framework for arid ecological monitoring, supporting evidence-based conservation and sustainable development in the Yellow River Basin. Full article

Returning straw and green manure to the field is a vital agronomic practice for improving crop yields and ensuring food security. However, the existing research primarily focuses on drylands and low-fertility paddy fields. A systematic discussion of the yield-increasing mechanisms and soil response patterns of medium- and long-term organic fertilization in subtropical, high-organic-matter paddy fields is lacking. This study conducted a six-year field experiment (2019–2024) in a typical high-fertility rice production area, where the initial organic matter content of the 0–20 cm topsoil layer was 44.56 g kg⁻¹. Four treatments were established: PK (no nitrogen, only phosphorus and potassium fertilizer), NPK (conventional nitrogen, phosphorus, and potassium fertilizer), NPKM (NPK + full-amount winter milk vetch return), and NPKS (NPK + full-amount rice straw return). We collected 0–20 cm topsoil samples during key rice growth stages to monitor the dynamic changes in nitrate and ammonium nitrogen. The rice SPAD, LAI, plant height, and tiller number were also measured during the growth period. After the six-year rice harvest, we determined the properties of the topsoil, including its organic matter, pH, total nitrogen, phosphorus, potassium, available phosphorus and potassium, and alkali hydrolyzable nitrogen. The results showed that, compared to NPK, the organic matter content of the topsoil (0–20 cm) increased by 6.36% and 5.16% (annual average increase of 1.06% and 0.86%, lower than in low-fertility areas) in the NPKS and NPKM treatments, respectively; the total nitrogen, phosphorus, and potassium content increased by 16.59%, 8.81%, and 10.37% (NPKS) and 6.70%, 5.12%, and 11.62% (NPKM), respectively; the available phosphorus content increased by 21.87% and 8.42%, respectively; the available potassium content increased by 47.38% and 11.56%, respectively; and the alkali hydrolyzable nitrogen content increased by 3.24% and 2.34%, respectively. However, the pH decreased by 0.07 in the NPKS treatment while it increased by 0.17 in the NPKM treatment, respectively, compared to the PK treatment. NPKS and NPKM improved key rice growth indicators such as the SPAD, LAI, plant height, and tillering. In particular, the tillering of the NPKS treatment showed a sustained advantage at maturity, increasing by up to 13.64% compared to NPK, which also led to an increase in the effective panicle number. Compared to NPK, NPKS and NPKM increased the average yield by 9.52% and 8.83% over the six years, respectively, with NPKM having the highest yield in the first three years (2019–2021) and NPKS having the highest yield from the fourth year (2022–2024) onwards. These results confirm that inputting organic materials such as straw and green manure can improve soil fertility and rice productivity, even in rice systems with high organic matter levels. Future research should prioritize the long-term monitoring of carbon and nitrogen cycle dynamics and greenhouse gas emissions to comprehensively assess these practices’ sustainability. Full article

The Honghe Hani Rice Terraces, a UNESCO World Heritage agroecosystem, embody a millennia-old synergy of cultural heritage and ecological resilience, yet face declining water yields amid land-use intensification and climate variability. This study employs the InVEST model and geographic detector analysis to quantify water-yield dynamics from 2010 to 2020 and identify their spatial and mechanistic drivers. Annual water yield averaged 558 mm, with cultivated lands contributing 33% of total volume, while built-up areas reached 980 mm per unit in 2018. A 31% decline by 2020, driven by cropland fragmentation and tourism growth, revealed persistent-yield hotspots in forested central-eastern terraces and cold spots in southwestern dryland margins. Land-use pattern accounted for 80–95% of yield variability, exacerbated by temperature interactions. Forests, delivering 68.7 million m³ over the decade, highlight the hydrological significance of traditional landscape mosaics. These findings advocate reforestation in critical recharge zones, terrace restoration to preserve agroecological integrity, and regulated tourism integrating rainwater harvesting to sustain water security and cultural heritage. By blending hydrological modeling with socio-cultural insights, this study provides a scalable framework for safeguarding terraced agroecosystems worldwide, aligning heritage conservation with sustainable development. Full article

Selenium (Se) is essential for various metabolic and physiological functions in the human body. However, the mechanisms of Se cycling in soils, particularly under different parent materials and land uses, remain understudied. This study investigates the spatial distribution and influencing factors of total Se in surface soils derived from limestone and sandstone in paddy and dryland systems in a Se-rich karst region of Southwest China. The mean Se content was 0.5 mg/kg, with 100% of samples exceeding national and global background levels, confirming Zheng’an County as a newly recognized Se-rich area. Soil Se concentrations, along with environmental variables such as soil organic matter (SOM), pH, elevation, slope, and trace elements (V, Cr, and Zn), were analyzed. One-way ANOVA revealed significant differences in Se content between parent materials and land-use types. Stepwise multiple regression identified SOM as the strongest predictor of Se, while Spearman correlation showed significant associations with topographic and chemical factors. These findings highlight the complex interactions between geology, land use, and topography in Se dynamics. Given the global distribution of karst landscapes, this research provides valuable insights into Se behavior in similar environments worldwide, with implications for land management and nutritional security. Full article

Petroleum pollution has become a substantial challenge in soil ecology. The soil bacterial consortia play a major role in the biodegradation of petroleum hydrocarbons. The main objective of this study was to assess changes in bacterial composition and diversity in oil-contaminated dryland soils. The Illumina MiSeq high-throughput sequencing technique was used to study the bacterial diversity and structural change in hyper-arid oil-contaminated soil in the Arava Valley of Israel. The diversity and abundance of soil bacteria declined significantly following oil pollution. The dominant phyla in the petroleum-contaminated soils were Proteobacteria (~33% higher vs. control soil) and Patescibacteria (~2.5% higher vs. control soil), which are oil-associated and hydrocarbon-degrading bacteria. An opposite trend was found for the Actinobacteria (~8%), Chloroflexi (12%), Gemmatimonadetes (3%), and Planctomycetes (2%) phyla, with the lower abundances in contaminated soil vs. control soil. Investigation of long-term contaminated sites revealed significant genus-level taxonomic restructuring in soil bacterial communities. The most evident changes were observed in Mycobacterium, Alkanindiges, and uncultured bacterium-145, which showed marked abundance shifts between spill and control soils across decades. Particularly, hydrocarbon-degrading genera such as Pseudoxanthomonas demonstrated persistent dominance in contaminated sites. While some genera (e.g., Frigoribacterium, Leifsonia) declined over time, others—particularly Nocardioides and Streptomyces—exhibited substantial increases by 2014, suggesting potential ecological succession or adaptive selection. Minor but consistent changes were also detected in stress-tolerant genera like Blastococcus and Quadrisphaera. The effect of oil contamination on species diversity was greater at the 1975 site compared to the 2014 site. These patterns highlight the dynamic response of bacterial communities to chronic contamination, with implications for bioremediation and ecosystem recovery. The study results provide new insights into oil contamination-induced changes in soil bacterial community and may assist in designing appropriate biodegradation strategies to alleviate the impacts of oil contamination in drylands. Full article

Land use and land cover change (LULCC) is a key driver of carbon storage changes, especially in complex coastal ecosystems such as the Yellow River Delta (YRD), which is jointly influenced by climate change and resource development. The compounded effects of sea-level rise (SLR) and land subsidence (LS) are particularly prominent. This study is the first to integrate the dual impacts of SLR and LS into a unified framework, using three climate scenarios (SSP1–26, SSP2–45, SSP5–85) provided in the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6), along with LS monitoring data, to comprehensively assess future inundation risks. Building on this, and taking into account land use and ecological protection policies in the YRD, three strategic scenarios—Ecological Protection Scenario (EPS), Natural Development Scenario (NDS), and Economic Growth Scenario (EGS)—are established. The PLUS and InVEST models are used to jointly simulate LULCC and carbon storage changes across these scenarios. Unlike previous studies focusing on single driving factors, this research innovatively develops a dynamic simulation system for LULCC and carbon storage driven by the SLR-LS compound effects, providing scientific guidance for land space development and coastal zone planning in vulnerable coastal areas, while enhancing carbon sink potential. The results of the study show the following: (1) Over the past 30 years, the land use pattern of the YRD has generally extended toward the sea, with land use transitions mainly from grasslands (the largest reduction: 1096.20 km²), wetlands, reservoirs and ponds, and paddy fields to drylands, culture areas, construction lands, salt pans, and tidal flats. (2) Carbon storage in the YRD exhibits significant spatial heterogeneity. Low-carbon storage areas are primarily concentrated in the coastal regions, while high-carbon storage areas are mainly found in grasslands, paddy fields, and woodlands. LULCC, especially the conversion of high carbon storage ecosystems to low carbon storage uses, has resulted in an overall net regional carbon loss of 2.22 × 10⁶ t since 1990. (3) The risk of seawater inundation in the YRD is closely related to LS, particularly under low sea-level scenarios, with LS playing a dominant role in exacerbating this risk. Under the EGS, the region is projected to face severe seawater inundation and carbon storage losses by 2030 and 2060. Full article

Accurate, real-time, and dynamic monitoring of crop planting distributions in hilly areas with complex terrain and frequent meteorological changes is highly important for agricultural production. Dual-polarization SAR has high application value in the fields of feature classification and crop distribution extraction because of its all-day all-weather operation, large mapping bandwidth, and easy data acquisition. To explore the feasibility and applicability of dual-polarization synthetic-aperture radar (SAR) data in crop monitoring, this study draws on two basic methods of dual-polarization decomposition (eigenvalue decomposition and three-component polarization decomposition) to construct time series of crop dual-polarization radar vegetation indices (RVIs), and it performs a full coverage analysis of crop distribution extraction in dryland mountainous areas of southeastern China. On the basis of the Sentinel-1 dual-polarization RVIs, the time-series classification and rapeseed distribution extraction impacts were compared using southern Hunan Province’s principal rapeseed (Brassica napus L.) production area as the study area. From the comparison results, $RV{I}_{3-c}$ performed better in terms of single-point recognition capability and area extraction accuracy than the other indices did, as verified by sampling points and samples, and the OA and F-1 score of rapeseed extraction based on $RV{I}_{3-c}$ were 74.13% and 81.02%, respectively. Therefore, three-component polarization decomposition is more suitable than other methods for crop information extraction and remote sensing classification applications involving dual-polarized SAR data. Full article

The interplay between terrestrial water storage and vegetation dynamics in arid regions is critical for understanding ecohydrological responses to climate change and human activities. This study examines the coupling between total water storage anomaly (TWSA) and vegetation greenness changes in the Hexi Corridor, an arid region in northwestern China consisting of three inland river basins—Shule, Heihe, and Shiyang—from 2002 to 2022. Utilizing TWSA data from GRACE/GRACE-FO satellites and MODIS Enhanced Vegetation Index (EVI) data, we applied a trend analysis and partial correlation statistical techniques to assess spatiotemporal patterns and their drivers across varying aridity gradients and land cover types. The results reveal a significant decline in TWSA across the Hexi Corridor (−0.10 cm/year, p < 0.01), despite a modest increase in precipitation (1.69 mm/year, p = 0.114). The spatial analysis shows that TWSA deficits are most pronounced in the northern Shiyang Basin (−600 to −300 cm cumulative TWSA), while the southern Qilian Mountain regions exhibit accumulation (0 to 800 cm). Vegetation greening is strongest in irrigated croplands, particularly in arid and hyper-arid regions of the study area. The partial correlation analysis highlights distinct drivers: in the wetter semi-humid and semi-arid regions, precipitation plays a dominant role in driving TWSA trends. Such a rainfall dominance gives way to temperature- and human-dominated vegetation greening in the arid and hyper-arid regions. The decoupling of TWSA and precipitation highlights the importance of human irrigation activities and the warming-induced atmospheric water demand in co-driving the TWSA dynamics in arid regions. These findings suggest that while irrigation expansion cause satellite-observed greening, it exacerbates water stress through increased evapotranspiration and groundwater depletion, particularly in most water-limited arid zones. This study reveals the complex ecohydrological dynamics in drylands, emphasizing the need for a holistic view of dryland greening in the context of global warming, the escalating human demand of freshwater resources, and the efforts in achieving sustainable development. Full article

This study investigated and compared the spatiotemporal evolution and driving factors of groundwater storage anomalies (GWSAs) under the dual pressures of climate change and urban expansion in two contrasting river basins of China. Integrating GRACE and GLDAS data with multi-source remote sensing data and using attribution analysis, we reveal divergent urban GWSA dynamics between the humid Yangtze River Basin (YZB) and semi-arid Yellow River Basin (YRB). The GWSAs in YZB urban grids showed a marked increasing trend at 3.47 mm/yr (p < 0.05) during 2002–2020, aligning with the upward patterns observed in agricultural land types including dryland and paddy fields, rather than exhibiting the anticipated decline. Conversely, GWSAs in YRB urban grids experienced a pronounced decline (−5.59 mm/yr, p < 0.05), exceeding those observed in adjacent dryland regions (−5.00 mm/yr). The contrasting climatic regimes form the fundamental drivers. YZB’s humid climate (1074 mm/yr mean precipitation) with balanced seasonality amplified groundwater recharge through enhanced surface runoff (+6.1%) driven by precipitation increases (+7.4 mm/yr). In contrast, semi-arid YRB’s water deficit intensified, despite marginal precipitation gains (+3.5 mm/yr), as amplified evapotranspiration (+4.1 mm/yr) exacerbated moisture scarcity. Human interventions further differentiated trajectories: YZB’s urban clusters demonstrated GWSA growth across all city types, highlighting the synergistic effects of urban expansion under humid climates through optimized drainage infrastructure and reduced evapotranspiration from impervious surfaces. Conversely, YRB’s over-exploitation due to rapid urbanization coupled with irrigation intensification drove cross-sector GWSA depletion. Quantitative attribution revealed climate change dominated YZB’s GWSA dynamics (86% contribution), while anthropogenic pressures accounted for 72% of YRB’s depletion. These findings provide critical insights for developing basin-specific management strategies, emphasizing climate-adaptive urban planning in water-rich regions versus demand-side controls in water-stressed basins. Full article

Eurasian drylands are vital for the global climate and ecological balance. Quantifying spatiotemporal variations in surface soil moisture (SSM) is essential for monitoring water, energy, and carbon cycles. The suitability of recent global-scale surface soil moisture datasets for Eurasian arid and semi-arid regions has not been comprehensively evaluated. This study investigates spatiotemporal trends of five SSM products—MERRA-2, ESACCI, GLEAM, GLDAS, and ERA5—from 1980 to 2023. The performance of these products was evaluated using in situ station data and the three-cornered hat (TCH) method, followed by partial correlation analysis to assess the influence of environmental factors, including mean annual temperature (MAT), mean annual precipitation (MAP), potential evapotranspiration (PET), vapor pressure deficit (VPD), and leaf area index (LAI), on SSM from 1981 to 2018. The results showed consistent SSM patterns: higher values in India, the North China Plain, and Russia, and lower values in the Arabian Peninsula, the Iranian Plateau, and Central Asia. Regionally, MAT, PET, VPD, and LAI increased significantly (0.04 °C yr⁻¹, 1.66 mm yr⁻¹, 0.004 kPa yr⁻¹, and 0.003 m² m⁻² yr⁻¹, respectively; p < 0.05), while MAP rose non-significantly (0.29 mm yr⁻¹). ERA5 exhibited the strongest correlation with in situ station data (R² = 0.42), followed by GLEAM (0.37), ESACCI (0.28), MERRA2 (0.19), and GLDAS (0.17). Additionally, ERA5 showed the highest correlation (correlation = 0.72), while GLEAM had the lowest bias (0.03 m³ m⁻³) and ESACCI exhibited the lowest ubRMSE (0.03 m³ m⁻³). The three-cornered hat method identified ERA5 and GLDAS as having the lowest uncertainties (<0.03 m³ m⁻³), with ESACCI exceeding 0.05 m³ m⁻³ in northern regions. Across land cover types, cropland had the lowest uncertainty among the five SSM products, while forest had the highest. Partial correlation and dominant factor analysis identified MAP as the primary driver of SSM. This study comprehensively evaluated SSM products, highlighting their strengths and limitations. It underscored MAP’s crucial role in SSM dynamics and provided insights for improving SSM datasets and water resource management in drylands, with broader implications for understanding the hydrological impacts of climate change. Full article