Search Results (647)

Building on the success of its predecessors, the 9th International Electronic Conference on Water Sciences (ECWS-9) has been hosted entirely online. The conference aims to explore pivotal advancements in water sciences amidst environmental change. Researchers and practitioners are invited to contribute across a spectrum of critical topics, from hydrological processes, water resources management, and ecohydrology to urban water systems, agricultural water use, wastewater reuse, and the application of remote sensing and artificial intelligence. Special attention will be given to extreme hydro-meteorological events, water policy, and the impacts of climate change. Full article

Net primary productivity (NPP) and its response to global climate change are one of the hot topics in global change research. Based on Net primary productivity remote sensing data and meteorological data, this study analyzed the spatiotemporal variation in vegetation NPP in Maowusu sandy land by using Sen trend analysis, Mann–Kendall significance test, coefficient of variation stability analysis, partial correlation and complex correlation analysis, and quantitatively analyzed the response of vegetation NPP to climate factors. The results showed that from 2001 to 2023, the overall vegetation NPP showed a significant upward trend, and the annual average increased from 124.28 g·(m⁻²·a)⁻¹ to 221.41 g·(m⁻²·a)⁻¹. The Theil–Sen median slope of NPP was +3.87 g·(m⁻²·a)⁻¹ with a coefficient of variation (CV) of 0.19, suggesting a robust but spatially variable greening trend. In total, 98.53% of the area showed an upward trend, with a very significant and significant increase area. The overall stability of vegetation NPP was strong, with an average coefficient of variation (CV) of 0.19 and a CV< of 0.30 in 97.96% of the regions, but the local area from southwest to east was highly volatile and there was a risk of secondary desertification. The influence of climate factors on vegetation NPP had significant spatial heterogeneity: precipitation was the key driving factor, and most areas were positively correlated. Potential evapotranspiration was positively correlated in the central and northern regions, and negatively correlated in some southern areas. The overall temperature has a negative effect, and only the local area has a weak promoting effect. Multi-correlation analysis shows that vegetation NPP is the result of the synergy of multiple climatic factors, and the hydrothermal coupling mechanism plays a decisive role in its spatial pattern. This study can provide a scientific basis for the restoration of vegetation ecosystems, environmental protection policy formulation, ecological protection and high-quality development of the Yellow River Basin in Maowusu Sandy Land. Full article

This study systematically evaluates the regulatory effects of multi-reservoir water diversion on ecological risk thresholds in the upper Yangtze River. Taking multiple reservoirs in the upper basin as the research object, a system dynamics model was developed to simulate reservoir operation, water level regulation, ecological water diversion, and diversion capacity enhancement. Key indicators included upstream ecological risk thresholds, ecohydrological risk levels, habitat ecological risk levels, and water environment ecological risk levels. Five scenarios were designed: S0 (baseline), S1 (enhanced ecological compensation), S2 (industrial coordination and optimization), S3 (economic synergy promotion), and S4 (comprehensive regulation and optimization). These scenarios were used to assess the combined effects of different diversion strategies on ecological risk control. Results indicate the following: (1) All scenarios reduce ecological risks to some extent, but the degree of effectiveness differs. (2) The overall ranking is S4 > S1 > S3 > S2 > S0, demonstrating that comprehensive regulation optimization is most effective in mitigating ecohydrological risks, improving habitat quality, and enhancing water environment security. (3) S1 is particularly effective in reducing ecohydrological risks and is suitable as an emergency safeguard during dry seasons, though less effective than S4 in habitat and water quality improvements. (4) S3 supports economic–ecological synergy but remains less effective than S1 and S4. (5) S2 primarily enhances industrial–ecological coordination with limited contribution to overall risk control. (6) S0 yields minimal improvement under existing operational conditions, failing to meet ecosystem safety thresholds. Overall, the findings highlight that in multi-reservoir joint diversion contexts, a composite strategy centered on comprehensive regulation optimization, supplemented by ecological compensation and economic synergy, should be prioritized to achieve systematic ecological risk reduction and ensure long-term watershed ecological security. Full article

Soil CO₂ emissions are critical for predicting terrestrial ecosystem feedbacks to climate change, yet significant knowledge gaps persist regarding carbon flux dynamics within the deep vadose zone and during freeze–thaw processes. In this study, the Mu Us Sandy Land, a representative seasonally frozen and semi-arid region in Northwestern China, was selected as the research site. Based on in situ observation data and the XGBoost algorithm, the spatiotemporal variations of soil carbon flux and its environmental drivers were investigated. Results revealed distinct depth-dependent patterns, where carbon release reached its maximum flux in the 100–200 cm layer and carbon sequestration dominated the soil layers below 200 cm. Soil temperature and moisture were the primary controlling factors, but their impacts exhibited significant depth and seasonal heterogeneity. Notably, in the 20–50 cm soil layer, soil water content provided the highest explanatory power, reaching 55.3% and 47.8% in winter and summer, respectively. Furthermore, carbon fluxes exhibited distinct response thresholds to environmental factors, and their spatiotemporal variations were fundamentally regulated by an atmosphere-driven coupled water–vapor–heat–carbon process. These findings elucidate the complex relationship between soil carbon fluxes and the environment at different depths, providing theoretical support for deepening the understanding of regional carbon cycling. Full article

Urbanization alters the hydrological and structural functioning of tropical urban streams, influencing organic matter transport and retention processes. This study investigated leaf litter retention dynamics in the Bindá Stream in central Amazonia. A six-month leaf release experiment (100 leaves per 12 trial; 1200 leaves total) was conducted alongside hydrological monitoring and floristic surveys of riparian vegetation (adult and regeneration strata). Leaf retention remained consistently low (<33%) across sampling periods. Generalized linear models indicated that flow velocity and discharge were the primary predictors of retention probability, with higher hydrodynamic intensity significantly reducing in-stream storage. Riparian vegetation exhibited moderate structural complexity (Shannon H′ = 1.80; Structural Complexity Index = 3.80), yet limited channel roughness and physical obstructions constrained retention efficiency. Anthropogenic debris locally increased retention, but represents a structurally altered retention mechanism. Hydrodynamic forcing, rather than precipitation totals alone, governed organic matter transport dynamics. Reduced retention capacity suggests limited buffering of downstream material export under high-flow conditions. Although direct water-quality or epidemiological indicators were not measured, findings align with ecohydrological frameworks linking structural simplification and flow flashiness to diminished ecosystem regulation. These results inform riparian restoration and urban stormwater management strategies aimed at enhancing ecosystem regulation and water-quality buffering in tropical cities. Full article

The 2022 Chongqing wildfires, occurring during an unprecedented heatwave, severely degraded subtropical forest ecosystems and disrupted hydrological cycling. We developed an integrated artificial intelligence framework combining Long Short-Term Memory and Transformer architectures to simulate post-fire evapotranspiration (ET) dynamics using 37 months of field observations (2022–2025) across 24 plots with four burn severities. The Penman–Monteith–Leuning model provided physically based benchmarks. Results revealed three distinct recovery phases: destruction/stagnation (0–7 months, ET at 6%–10% of pre-fire levels), rapid recovery (8–19 months), and stabilization (20–37 months, reaching 100% ET recovery). The coupled LSTM–Transformer ensemble achieved superior performance (RMSE = 0.10 mm·day⁻¹, NSE = 0.98), outperforming single models by 31% in uncertainty reduction. SHAP analysis identified phase-dependent factor shifts: soil water content dominated Stage I (42.5%), while leaf area index (LAI) controlled Stages II–III (>48%). A bimodal LAI time-lag effect emerged: 4–7 days (leaf water potential equilibrium, 27.7% contribution) and 8–14 days (root uptake compensation, 21.7%). Burn severity significantly extended time-lags (severe burns: 12/21 days vs. unburned: 5/12 days), indicating hydraulic system reconstruction requirements. Despite equivalent LAI recovery, severe burns maintained 12%–15% ET reduction, suggesting lasting hydraulic limitations. This study demonstrates that physics-constrained AI models effectively capture complex post-fire ecohydrological dynamics while providing mechanistic interpretability, advancing understanding of vegetation–water coupling reconstruction under increasing fire frequency. Full article

In arid and semi-arid agroecosystems, soil water availability is a critical regulator of coupled carbon–water (C–W) cycling, vegetation dynamics, and ecosystem resilience under environmental change. This research investigated the temporal evolution and spatial patterns of soil moisture across sand dune slopes within the Mu Us Sandy Land. Data were collected via a combination of continuous high-frequency in situ monitoring spanning 20 months and manual sampling campaigns. We analyzed moisture levels at various depths and slope positions (windward vs. leeward) to understand their distribution and reaction to precipitation. Statistical analysis of all rainfall events that triggered measurable soil moisture responses showed that precipitation was the primary determinant of soil moisture fluctuations. Specifically, shallow soil (10 cm) reacts rapidly to rainfall events > 4.6 mm, whereas intermediate layers (20–50 cm) require > 8.6 mm. Conversely, deep soil moisture (>100 cm) remains stable, responding only to substantial storm events (>50 mm). Topography exerts a strong control over spatial variance; notably, slope toes consistently exhibit higher moisture than upper sections, particularly during wet seasons, indicating strong topographic control on moisture redistribution and possibly reflecting lateral subsurface transfer. Additionally, a nonlinear correlation was observed between mean moisture content and its variability, peaking under intermediate moisture conditions. The results provide a mechanistic basis for understanding agroecosystem responses to climate variability and offer valuable insights for adaptive land management, vegetation restoration, and hydrological modeling in water-limited regions. Full article

The Soil and Water Assessment Tool (SWAT) model has been widely used to simulate ecohydrological processes in watersheds. However, the SWAT model uses a simplified Environmental Policy Impact Climate (EPIC) model to simulate the leaf area index (LAI), creating a critical gap in accurately simulating evapotranspiration (ET) and runoff in semi-arid regions. This work aims to fill this gap by modifying the SWAT source code to integrate high-resolution Global Land Surface Satellite (GLASS) leaf area index (LAI) data. The modified version was applied to the semi-arid Wuding River Basin and calibrated using a Fortran-based dynamic dimension search (DDS) algorithm. The results show a relatively significant improvement in the accuracy of the daily-scale runoff simulation (R² from 0.52 to 0.71 and NSE from 0.52 to 0.7 for the calibration period, and R² from 0.21 to 0.58 and NSE from 0.2 to 0.51 for the validation period). The improved version also corrects the unrealistic default LAI peak (from >5.0 to 1.5–3.0), correcting the multi-year average ET from 251.7 mm to 341.8 mm. The improved vegetation growth module of the SWAT model effectively improved the accuracy of hydrologic simulation in the semi-arid region and enhanced the structural robustness of SWAT for water management. Full article

Accurate quantification of groundwater evapotranspiration (ET_g) is essential for reliable water resource assessment. Existing methods for estimating ET_g from water table fluctuation largely rely on one-dimensional simplifications that neglect transient groundwater flow. However, in areas with shallow water table and topographic relief, where transient groundwater flow often occurs, the validity and accuracy of this simplification remain inadequately evaluated. In this study, we used HYDRUS-2D to construct a 50 m-long sandy hillslope with a 0.05 gradient to investigate ET_g based on the water table fluctuation (WTF) method under transient groundwater flow conditions. The results indicate that periodic evapotranspiration generates water table fluctuations along the hillslope that exhibit amplitude attenuation and temporal phase lag, features not captured by 1D models. Ignoring transient groundwater flow leads to a systematic underestimation of ET_g by up to 85% in sandy soil near the topographic lows. Furthermore, we found that both the decoupling depth and the extinction depth are significantly amplified by lateral groundwater flow, by up to 66% and 51%, respectively, compared with 1D estimates derived from the Shah method. These findings highlight the importance of incorporating transient flow processes into ET_g estimation to improve the accuracy of water balance assessments and ecohydrological predictions, particularly in areas with shallow water tables and topographic relief. Full article

Soil texture exerts fundamental control over nutrient retention in arid ecosystems; however, its mechanistic coupling with nutrient stoichiometry in wind-eroded desert steppes remains poorly resolved. We investigated soil particle-size distribution and nutrient characteristics across contrasting vegetation types in a desert steppe on the northern slope of the Yinshan Mountains. The interactions between soil texture and nutrient distribution were quantified through field sampling and laboratory analyses. The Caragana grassland was dominated by fine-textured soils, with a silt-to-sand ratio of 21.58% and a fractal dimension ranging from 2.1 to 3.95, indicating a complex soil structure with strong nutrient-retention capacity. In contrast, the Leymus grassland and desert sites were characterized by higher sand content, with a median particle size of 1.67 mm and sorting coefficients ranging from 0.06 to 4.2, reflecting a simpler structure and comparatively lower nutrient levels. Overall, soils in the region were nutrient-deficient, with widespread phosphorus and potassium limitations, whereas nitrogen was relatively more abundant. Total nitrogen (<0.75 mg kg⁻¹), total phosphorus (0.2–0.4 mg kg⁻¹), total potassium and available nutrients were predominantly classified as ‘deficient’ to ‘extremely deficient’, exhibiting a clear surface accumulation pattern. The Poaceae meadow surface layer showed the highest total nitrogen and phosphorus contents. The sorting coefficient and fractal dimension were identified as key particle-size parameters regulating soil nutrient stoichiometric ratios. The silt-to-sand ratio exerted negative path effects (−0.11 to −0.18) on SOC/TN and AK/AN, whereas fractal dimension showed positive path effects (0.17–0.23) on AK/AN. These findings provide a scientific basis for ecological restoration and soil management in the region. Full article

Under recurring droughts, the southwestern U.S. loses a significant proportion of precipitation as evapotranspiration (ET), suggesting an opportunity to reduce ET via forest thinning. To better understand the potential impacts of thinning on the forest hydrologic cycle, we used sap flow sensors and Bowen ratio stations to measure ET in thinned and non-thinned ponderosa pine (Pinus ponderosa Douglas ex C. Lawson) stands in northern Arizona during the wet year of 2023, where thinning removed 42% of overstory basal area. Although our study site had experienced prolonged drought in previous years, heavy winter snowfall made 2023 a wet year. We correlated sap flow with environmental variables and used principal component analysis to identify the primary drivers of ponderosa pine water use in thinned and non-thinned stands. Results showed that after accounting for tree size, thinned stands had ~20% (~5 L day⁻¹) higher individual-tree water use at daily and weekly temporal scales than non-thinned stands. At the stand level, thinning decreased overstory ET (OET) but increased understory ET (UET), indicating a reallocation of outgoing water fluxes in the water balance. As a result, total ET (sum of OET and UET) decreased from 584 to 516 mm year⁻¹. In the semi-arid forest, this decrease in total ET of 68 mm year⁻¹ (~12% reduction) indicates an ecohydrologically meaningful outcome of forest thinning. In both stands, tree water use was strongly regulated by environmental variables, primarily atmospheric variables such as air temperature and vapor pressure deficit. Overall, our results suggest that thinning can still promote an improved stand-level forest water balance during a wet year and thus may enhance forest resilience under projected increases in heat and aridity in the southwestern U.S. Full article

As Guangdong is a pivotal province in China’s national forest city initiative, examining the spatiotemporal evolution and key drivers of eco-environmental quality (EEQ) in Guangdong is essential for advancing regional sustainable development. To address the complexity of EEQ assessments in areas that are characterized by dense hydrological networks, extensive vegetation cover, and rapid urban expansion, the Google Earth Engine platform was utilized in this study, and remote sensing indices with heightened sensitivity to vegetation and moisture dynamics—namely, the kernel normalized difference vegetation index and the kernel normalized difference moisture index—were introduced to develop an improved water benefit-based ecological index (ImWBEI). Through an integrated analytical framework incorporating Theil–Sen trend analysis, Mann–Kendall significance testing, Hurst exponent analysis, an optimal parameter-based geographical detector, and a coupled coordination degree model, this research systematically evaluated the spatiotemporal patterns, future trends, driving mechanisms, and coordination with urbanization of the EEQ in Guangdong from 2000 to 2021. The results demonstrated that the ImWBEI enhanced the detailed characterization of complex underlying surfaces, such as urban built-up areas and land–water transition zones. Throughout the study period, the EEQ in Guangdong displayed a stable spatial distribution characterized by higher values in the north and lower values in the south. Concurrently, the EEQ significantly improved at a rate of 0.0092 per year. Hurst index analysis indicated that this trajectory would likely persist, with the future trend dominated by a pattern of weak persistent improvement. The comprehensive urbanization index was identified as the most critical factor influencing the spatial differentiation of the EEQ in Guangdong. Although notable north–south disparities were observed in the coordination between the EEQ and comprehensive urbanization, the provincial-level coupled coordination consistently improved. Consequently, this work yielded actionable insights and a replicable framework for ecological monitoring and coordinated development in similar water–forest integrated urban regions. It was particularly relevant for informing ecological restoration prioritization and development restriction decisions in critical land–water transition zones—areas where the ImWBEI demonstrated enhanced sensitivity. Full article

Soil moisture is a critical variable in the eco-hydrological processes of arid regions; however, the vertical stratified mechanisms of soil moisture response to meteorological factors in artificial grassland remain inadequately quantified. Based on 10-min interval monitoring data from 2015 to 2024 in the middle reaches of the Heihe River, this study investigated the dynamics of soil moisture within a 0–160 cm depth profile in an arid artificial grassland. By integrating the Mann–Kendall trend test, Pearson correlation, time-lagged cross-correlation, multiple regression analysis and redundancy analysis, we systematically investigated the changing relationships between meteorological factors and soil moisture. The results revealed the following: (1) main meteorological factors driving surface processes (e.g., net radiation, air temperature, vapor pressure deficit) showed significant increasing trends with strong variability, while relative humidity decreased significantly, and these findings collectively point to a general trend of warming and drying in the region; (2) WS, Ta, rainfall, and RH are the principal factors explaining soil moisture variations, wherein temperature and humidity exhibit positive correlations with soil moisture; (3) RDA results showed that shallow soil moisture (0–20 cm) was primarily governed by air temperature and rainfall, whereas deep soil moisture was increasingly regulated by vapor pressure deficit; (4) time-lagged cross-correlation analysis showed that the response time of soil moisture to rainfall almost increased with soil depth, while the correlation coefficient gradually weakened from 0.43 to 0.06. This study quantitatively elucidates the stratified control mechanism of meteorological factors on the vertical pattern of soil moisture, contributing to a deeper understanding of the response of eco-hydrological processes under climate change and providing a scientific basis for water resource management, agricultural planning, and climate prediction. Full article

Amid a deepening global socio-ecological crisis, Indigenous eco-spiritual practices are gaining renewed relevance for environmental governance. This article examines the water-caring practices of the Papallaqta, an Indigenous community in the Colombian Macizo—one of South America’s most vital hydrological systems. Drawing on relational methodologies, as well as extensive fieldwork conducted between 2024 and 2025, the study shows how Papallaqta spiritual relationships with water constitute a sophisticated form of governance grounded in reciprocity, reverence, and more-than-human relationality. The article situates these practices within global debates on environmental governance, where recent COP16 (Cali) and COP30 (Belém) summits have revealed the limits of technocratic, market-driven approaches to biodiversity loss, energy transition, and climate justice. Against these constraints, Papallaqta eco-spiritual governance offers an alternative paradigm based on spiritual animacy, legal cosmologies, and embodied ecological stewardship. Empirically, the article documents four interrelated dimensions of Papallaqta water-care: offerings to the water, ecological stewardship, territorial governance, and memory and cultural revitalization. Conceptually, it proposes eco-spiritual governance as an analytic for understanding how spiritual world-making informs environmental ethics, justice, and peacebuilding. The study concludes that Papallaqta practices illuminate viable pathways toward relational and regenerative environmental governance urgently needed in the current planetary crisis. Full article