Regional Water Resources Research Articles

Effect of Vegetation Growth, Agricultural Irrigation and Climatic Variability on Streamflow in Wujiang, China

Vegetation restoration and farmland irrigation are important environmental factors affecting the water cycle process in basins. Analyzing the impact of vegetation restoration and farmland irrigation on runoff is an international frontier and hot topic in current research, which is crucial for the management and protection of water resources, especially for the ecological protection and high-quality development of basins. Based on the normalized difference vegetation index (NDVI), effective irrigated area (EIA), and meteorology and hydrology data for Wujiang River (WJR), this research aims to quantitatively calculate the influence degree of vegetation recovery, agricultural irrigation, and climatic variability on discharge alteration in WJR. First, Mann–Kendall and Pettitt approaches were used for recognizing the mutation year of streamflow data at Wulong station from 1982 to 2015. Then, a corrective Budyko model was built by constructing multiple linear regression equations for the NDVI, climate factors, EIA, and Budyko parameters. Finally, the corrective Budyko model was adopted to reveal how vegetation restoration, agri-cultural irrigation, and climate variation influence discharge alteration in WJR. The results showed the following: (1) Both runoff depth (R) and rainfall (Pr) exhibited a non-significant de-clining tendency, while potential evapotranspiration (ET0) demonstrated a non-significant in-creasing tendency. The NDVI and EIA both demonstrated a notable upward tendency (p<0.01). (2) The mutation year of discharge in WJR was 2004. (3) The underlying surface parameters ω have a strong correlation with vegetation, agricultural irrigation, and climate factors. (4) The contribution of rainfall (Pr), potential evapotranspiration (ET0), NDVI, EIA, and human activities to runoff depth in WJR were 57.34%, 24.67%, -11.75%, 11.71%, and 18.02%, respectively. This re-search is helpful for elucidating the effects of ecological construction measures and agricultural irrigation on streamflow in WJR, and offers great scientific significance and practical value for understanding the evolution mechanism of water circulation and for managing regional water resources.

Using Commercial Satellite Imagery to Reconstruct 3 m and Daily Spring Snow Water Equivalent

AbstractSnow water equivalent (SWE) distribution at fine spatial scales (≤10 m) is difficult to estimate due to modeling and observational constraints. However, the distribution of SWE throughout the spring snowmelt season is often correlated to the timing of snow disappearance. Here, we show that snow cover maps generated from PlanetScope's constellation of Dove Satellites can resolve the 3 m date of snow disappearance across seven alpine domains in California and Colorado. Across a 5‐year period (2019–2023), the average uncertainty in the date of snow disappearance, or the period of time between the last date of observed snow cover and the first date of observed snow absence, was 3 days. Using a simple shortwave‐based snowmelt model calibrated at nearby snow pillows, the PlanetScope date of snow disappearance could be used to reconstruct spring SWE. Relative to lidar SWE estimates, the SWE reconstruction had a spatial coefficient of correlation of 0.75, and SWE spatial variability that was biased by 9%, on average. SWE reconstruction biases were then improved to within 0.04 m, on average, by calibrating snowmelt rates to track the spring temporal evolution of fractional snow cover observed by PlanetScope, including fractional snow cover over the full modeling domain, and across domain subsections where snowmelt rates may differ. This study demonstrates the utility of fine‐scale and high‐frequency optical observations of snow cover, and the simple and annually repeatable connections between snow cover and spring snow water resources in regions with seasonal snowpack.

Long-term analysis of reference evapotranspiration variations in the lower Bhavani basin

Evapotranspiration is a crucial component of the hydrological cycle and is profoundly influenced by climate change. Assessing regional evapotranspiration changes is essential for effective water resource management. The study investigated the dynamics of reference evapotranspiration in the Lower Bhavani Basin, a region with diverse landscapes increasingly vulnerable to climatic variability. Reference evapotranspiration data from the Food and Agriculture Organization using the AgERA5 dataset was analyzed to assess annual and seasonal trends from 2000 to 2022. The result showed that the mean yearly reference evapotranspiration in the basin is 1672.87 mm, with a significant decline of 3.53 mm per year. Seasonal analysis revealed a consistent decreasing trend across all seasons, with the southwest monsoon season showing the most significant reduction in evapotranspiration rates. The notable shift in the annual evapotranspiration rate was observed in 2016, highlighting the impact of climate change. Further, temperature, solar radiation and relative humidity were identified as the dominant factors influencing evapotranspiration rates in the basin. The relative moisture index indicated prevalent dry conditions, making the region susceptible to water stress. The findings provide critical insights for regional water resources management and accentuate the need for sustainable water management strategies to mitigate the impacts of climate change.

Variation Characteristics of Actual Evapotranspiration and Uncertainty Analysis of Its Response to Local Climate Change in Arid Inland Region of China

Exploring the variation characteristics of actual evapotranspiration (ETa) and its response to climate change in the arid inland region of China is of great significance for strengthening regional water resources management and maintaining ecological environment security and stability. Taking the Dulan River Basin as the research area, based on the meteorological data from the Wulan Station and hydrological data from the Shanggaba Station from 1981 to 2020, the variation characteristics of ETa at the annual scale were analyzed. The ETa estimation model and joint distribution model of P and potential evapotranspiration (ET0) was constructed based on climate factors, and the uncertainty of ETa response to climate change was explored with the water balance method, multiple linear regression, marginal distribution function, Copula function, and Monte Carlo algorithm. The results showed that the multi-year mean value of ETa in the study area was 261.6 mm, and the interannual process showed an insignificant upward trend, and had no abrupt change during the period. There were two obvious main cycles, which were 19-year periodic changes on the 30-year time scale and 6-year periodic changes on the 9-year time scale. The ETa estimation model based on precipitation (P) and ET0 had good simulation accuracy. The optimal marginal distributions of P and ET0 were Pearson-III (P-III) distribution and Generalized Extreme Value (GEV) distribution, respectively. The Copula joint distribution probability density of P and ET0 was a symmetric saddle-shaped distribution. ETa showed an inverted ‘S’ distribution with the change in joint guarantee rate of P and ET0, ranging from 116.9 mm to 498.6 mm. ETa was an interval range under a certain joint guarantee rate. The research results can provide support for the assessment of ETa, and help to further understand the driving mechanism of climate change on ETa in the arid inland region of China.

Combining WetSpass and MODFLOW to assess the groundwater recharge in the agricultural highlands of Ethiopia

Estimating the temporal and spatial patterns of recharge is crucial in Jedeb Watershed, which has shallow aquifers, a proliferation of wells, and limited observations. This paper uses the WetSpass-MODFLOW coupling to evaluate the groundwater recharge in the Jedeb watershed. The ArcGIS tool is used to build grid maps that contain the input data for the WetSpass-M model. These findings are then used to simulate the hydraulic head distribution in the groundwater flow simulation program MODFLOW. WetSpass-M calculated that long-term spatial and temporal average annual precipitation of 1394 mm is distributed as 99 mm (7.1%) groundwater recharge and 722 mm (51.79%) surface runoff, while 574 mm (41.11%) is lost through evapotranspiration. In such seasonal variations, the groundwater level due to the annual stress period varied from 2164.2 to 2213.1 m. The findings contribution could serve as a benchmark for future research by researchers, policymakers, and specialists in regional water resources.

The Spatiotemporal Dynamics of Temperature Variability Across Mts. Qinling: A Comparative Study from 1971 to 2022

Analyzing the spatiotemporal patterns of atmospheric temperature in sensitive areas is critically important for understanding the broader implications of global climate change, which remains a prominent topic in geosciences. It also plays a crucial role in advancing sustainable development. This study utilized daily minimum, maximum, and mean temperature data from twelve meteorological stations across the South and North Mts. Qinling (Qinling Mountains). Employing trend analysis, the Mann–Kendall mutation test, and Morlet wavelet analysis, we explored the predominant temperature trends and characteristics from 1971 to 2022. Our findings revealed consistent inter-annual warming trends in both regions, with more rapid temperature increases in the North compared to the South. Notably, significant shifts occurred in 2003 for both mean and minimum temperatures in the North, while the maximum and minimum temperature values were recorded in the 2010s and 1980s, respectively. Both regions exhibited a primary temperature fluctuation cycle of 28 years. Seasonally, the strongest warming effects appeared in spring, with the weakest in autumn, and moderate effects in winter and summer, indicating that spring contributes most significantly to regional warming. Monthly analysis showed positive temperature trends across all months, with higher rates in the North. The weakening temperature boundary effect of the Mts. Qinling suggested a weakening North–South division, particularly highlighted by the northward shift of the 1 °C isotherm curve for the coldest month, moving away from the previously observed 0 °C isotherm. This northward shift highlights the differential warming rates between the northern and southern regions. Overall, the analysis confirms a robust warming trend, with notable fluctuations in January’s temperatures since 1998, suggesting the Mts. Qinling’s emerging role as a climatic divider in the Chinese Mainland. This introduces new challenges for regional ecosystems, agricultural production, and water resource management, highlighting the pressing need to advance regional sustainable development in the face of climate change.

Integrated geophysical and geospatial techniques for surface and groundwater modeling

An integrated approach using geophysical and geospatial techniques was employed to model the surface and subsurface water-bearing strata and assess aquifer vulnerability in the Sehnsa town, Kotli district, State of Azad Kashmir, Pakistan. The inadequate scientific studies in the hilly terrain with such complex geological conditions has led to the failure of the boreholes for groundwater extraction. For the evaluation of groundwater potential and subsurface lithology, 30 vertical electrical soundings (VES) stations utilizing the Schlumberger electrode configuration were completed, modeled and analyzed spatially. Numerous geoelectrical parameters like true resistivity, thickness of subsurface layers and Dar-Zarrouk parameters were evaluated. The subsurface lithology delineated comprised topsoil, clayey sand, sandstone, and boulder clays which closely resemble to the borehole lithologs available in the study area. The inversion model confirms the presence of patches of high-resistivity sandstone in the southwestern part of the study area with the maximum thickness of the aquifer up to 140 m. Most aquifers were classified as unconfined with Q–type resistivity curves. The protective overburden capacity of the aquifers is rated as poor at VES 1, 3–5, 8, 10–16, 18, 19, 22–25, 27 and 30 whereas the moderate category was found at VES 2, 9 and 20 and excellent at VES 7 and 28, respectively. Therefore, the VES stations with poor and moderate ratings of overburden protective capacity are vulnerable for surface contaminants. The aquifer recharge was associated with rainfall and partly from the Poonch River. The effective integration of geophysical and geospatial techniques in this study provides sufficient information about the regional water resources and gives a preliminary model that can facilitate efficient water resource management in the area. These approaches can be successfully applied to diverse geographical and hydrogeological sites due to their versatility and reliability.

The Contribution of Moisture Sources of Precipitation to Water Resources Recharge in Semi-Arid Regions

This study investigates the isotopic composition of precipitation in Iran and its moisture sources, offering insights crucial for addressing water recharge and management in semi-arid regions. This study analyzes 150 precipitation events collected from 11 stations across Iran over multiple years. The HYSPLIT model was used to trace air mass trajectories contributing to these events. The isotopic composition of precipitation from each moisture source was examined to identify their distinct characteristics. Furthermore, the contribution of each air mass to groundwater and surface water recharge was quantified using the Simmr mixing model in R programming language, combining stable isotope data from precipitation and surface/groundwater samples. Precipitation in northern Iran is associated with low d-excess values, indicating moisture from high-latitude sources, particularly the Caspian Sea, while higher d-excess values in the west and south point to moisture mainly from the Persian Gulf and the Mediterranean Sea. Air mass trajectory analysis via the HYSPLIT model identified the dominant pathways of Continental Tropical (CT), Continental Polar (CP), and Mediterranean (MedT) air masses across Iran. Quantitative analysis using the Simmr mixing model revealed that the CT air mass contributes up to 33.6% to groundwater recharge in southern Iran’s karstic regions, while the CP air mass dominates in the north, with up to 46.8% contribution. The MedT air mass, although significant in the west, decreases in influence towards the east. Isotope data from groundwater and surface water sites showed more depleted values than local precipitation, likely due to larger catchment areas. These findings contribute to water management strategies by identifying the variations in moisture sources that influence groundwater and surface water recharge in Iran. Understanding these variations enables the development of targeted strategies for managing water resources in semi-arid regions facing increasing water scarcity. The methodologies applied in this study can be adapted to other regions, providing a valuable framework for sustainable water management in areas where identifying moisture sources is critical.

The Effect of a Parcel-Aggregated Cropping Structure Mapping Method in Irrigation-Water Estimation in Arid Regions—A Case Study of the Weigan River Basin in Xinjiang Province

Effective management of agricultural water resources in arid regions relies on precise estimation of irrigation-water demand. Most previous studies have adopted pixel-level mapping methods to estimate irrigation-water demand, often leading to inaccuracies when applied in arid areas where land salinization is severe and where poorly growing crops cause the growing area to be smaller than the sown area. To address this issue and improve the accuracy of irrigation-water demand estimation, this study utilizes parcel-aggregated cropping structure mapping. We conducted a case study in the Weigan River Basin, Xinjiang Province, China. Deep learning techniques, the Richer Convolutional Features model, and the bilayer Long Short-Term Memory model were applied to extract parcel-aggregated cropping structures. By analyzing the cropping patterns, we estimated the irrigation-water demand and calculated the supply using statistical data and the water balance approach. The results indicated that in 2020, the cultivated area in the Weigan River Basin was 5.29 × 105 hectares, distributed over 853,404 parcels with an average size of 6202 m2. Based on the parcel-aggregated cropping structure, the estimated irrigation-water demand ranges from 25.1 × 108 m3 to 30.0 × 108 m3, representing a 5.57% increase compared to the pixel-level estimates. This increase highlights the effectiveness of the parcel-aggregated cropping structure in capturing the actual irrigation-water requirements, particularly in areas with severe soil salinization and patchy crop growth. The supply was calculated at 24.4 × 108 m3 according to the water balance approach, resulting in a minimal water deficit of 0.64 × 108 m3, underscoring the challenges in managing agricultural water resources in arid regions. Overall, the use of parcel-aggregated cropping structure mapping addresses the issue of irrigation-water demand underestimation associated with pixel-level mapping in arid regions. This study provides a methodological framework for efficient agricultural water resource management and sustainable development in arid regions.

Irrigation Water Salinity Affects Solute Transport and Its Potential Factors Influencing Salt Distribution in Unsaturated Homogenous Red Soil

As a promising alternative water source to alleviate irrigation water scarcity in red soil regions in southern China, low-quality water could enhance regional water resource utilization and promote sustainable agriculture. However, its soluble salt and ions could affect soil solute distribution and transport, potentially hindering crop growth. Undoubtedly, it is necessary to understand the mechanism of solute transport in red soil under low-quality water irrigation with different water salinity levels. Therefore, a one-dimensional vertical water infiltration experiment and a solute breakthrough experiment were conducted to evaluate the solute transport (soluble salt, Na+, and Cl−) in unsaturated and saturated homogenous red soil at different salinity levels [1 (S1), 2 (S2), 3 (S3), 5 (S5), and 10 (S10) g/L] when irrigated with simulated low-quality water using analytical-grade NaCl. Moreover, the potential factors affecting salt distribution in unsaturated red soil were determined. The findings indicate positive linear relationships between accumulations of three solutes and irrigation water salinity. Generally, the depth of maximum solute concentration increased with the increase in irrigation water salinity. Soluble salt, Na+, and Cl− exhibited early breakthrough and trailing in red soil, but higher irrigation water salinity could reduce PV and retardation. A mobile and immobile water model (MIM) showed that convection was dominant in solute transport in red soil under low-quality water irrigation. D decreased as a power function with increasing irrigation water salinity, while v and R decreased linearly. Furthermore, the red soil can adsorb Cl− resulting from its special charge characteristics under low-quality water irrigation, which may be the main source of salt adsorption. Additionally, v > soil pH > βsalt primarily influenced salt distribution in the 0–40 cm soil profile. This study can provide insights into solute transport in red soil under low-quality water irrigation, facilitating soil fertility and structure, as well as low-quality water irrigation strategy optimization.

Construction of a quantitative model for ski resort water demand and preliminary exploration of drainage irrigation pathways

In China, natural snowfall is insufficient, and ski resorts often require artificial snowmaking in winter and turf management in summer, which results in high overall water consumption and considered as one of the high water-consuming service industries, with an urgent need for theoretical foundations related to water management. Based on life cycle theory, we examined the characteristics of the water systems of ski resorts in winter and summer. A Monte Carlo simulation was used to construct a stochastic model to quantify the theoretical water consumption for snowmaking at ski resorts and to investigate the mechanisms by which various factors influence this consumption. We summarize the necessity of summer turf management and irrigation requirements at ski resorts, explore the interaction between ski resorts and agricultural irrigation. The results show that the theoretical water demand of ski resorts is basically consistent with the actual water consumption of ski resorts, that the constructed model is feasible, and that snowmaking water is the most important water use of ski resorts. Exploring the collection and reuse of meltwater or rainwater from ski resorts for agricultural irrigation in the spring and summer could provide more possibilities for the sustainable management of regional water resources. The research findings can provide a theoretical basis for scientifically and reasonably setting the norm of water intake for ski resorts and for developing comprehensive water resource management plans for ski resorts and agricultural irrigation.

Assessing long-term water storage dynamics in Afghanistan: An integrated approach using machine learning, hydrological models, and remote sensing

Assessment of Terrestrial Water Storage (TWS) components is crucial for understanding regional climate and water resources, particularly in arid and semi-arid regions like Afghanistan. Given the scarcity of ground-based data, this study leverages remote sensing datasets to quantify water storage changes. We integrated Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-on (GRACE-FO) data with WaterGap, Global Land Water Storage (GWLS), Catchment Land Surface Model (CLSM), and climate variables (precipitation, temperature, potential evapotranspiration) using artificial neural networks (ANN) and random forests (RF). Additionally, Ice, Cloud, and Land Elevation Satellite (ICESat-1,2) data were utilized to estimate glacier mass changes. Seasonal trend decomposition using Loess (STL) was applied to assess TWS changes from 2003 to 2022. Our methodology reveals a high correlation (R = 0.90–0.97) between reconstructed and observed TWS anomalies across Afghanistan's major basins. Glacier mass decreased by −0.59 and −1.17 Gt/year during 2003–2009 and 2018–2022, respectively, while overall TWS declined by −2.46 Gt/year. The HRB experienced the largest TWS loss (−1.47 Gt/year), primarily due to groundwater depletion (−1.18 Gt/year). These findings underscore the importance of our approach for assessing water resources, providing vital insights for sustainable management under a changing climate in a data-scarce country.

Dynamic Changes and Driving Factors in the Surface Area of Ebinur Lake over the Past Three Decades

Dryland lakes are indispensable to regional water resource systems. Ebinur Lake, the largest saline lake in Xinjiang Uygur Autonomous Region, is vital for regional biodiversity and environmental stability but has been facing the predicament of gradual shrinkage in recent decades. In this study, we proposed a new dual-index method for Landsat (-5, -7, -8, and -9) data to extract water with the combinations of the normalized difference water index (NDWI) and the modified NDWI for turbid waters (NDWIturbid). The dual-index method showed a high overall accuracy of 96.36% for Ebinur Lake. Landsat series images from 1992 to 2023 were employed to acquire the water areas of Ebinur Lake. The results showed that, over the past three decades, the area of Ebinur Lake exhibited a fluctuating decreasing trend, with an average lake area of 568.74 ± 152.43 km². The northwest intermittent water areas showed significant changes, and there was a close connection between the northwest and core water areas. Seasonally, the lake area decreased from spring to autumn. River inflow, driven by rainfall and human activities, was the primary factor affecting the inter/inner annual changes in Ebinur Lake. Furthermore, due to the valley effects, wind was found to be a critical factor in the diurnal changes in the water areas. This study should deepen the understanding of the variations of Ebinur Lake and benefit local water resource management.

Groundwater renewal time by environmental tritium isotopes as a tracer for sustainable water resource management

Studying groundwater renewal time is a valuable tool to deepen the comprehension of sustainable groundwater resources specific to arid regions. Tritium is a radioactive isotope of hydrogen often used as an environmental tracer to study groundwater renewal time. The present work reports groundwater renewal times by the environmental tracer tritium to understand sustainable water resources in arid regions. First, groundwater samples were collected from wells in northeastern arid regions of Saudi Arabia. Then, an electrolysis process was employed to significantly increase the tritium level from twenty-five to thirty times the original concentration. Subsequently, the enriched water was analyzed using a liquid scintillation counter under optimized measurement conditions to determine the tritium concentration precisely. Two internationally recognized tritium laboratories conducted independent assessments to validate the estimated tritium levels. The verified tritium concentration was then used to estimate the groundwater renewal time using the Morgenstern and Pimenta curves. The results suggest that most of the monitored wells in the surveyed areas are more than a century old. Conversely, a few monitoring wells exhibit renewal times of several hundred years and may be considered nonrenewable water sources. These studies help to understand the geochemical characteristics of arid regions to ensure the sustainable management and protection of groundwater resources.

Research on a cloud model intelligent computing platform for water resource management

ABSTRACT As the demand for water management information systems continues to increase, addressing issues such as poor generalizability, low reusability, and difficulties in updating and maintaining water resource planning cloud model service platforms becomes crucial. To achieve goals like business-oriented functionality, high availability, and reliability, this study proposes constructing a cloud model service platform for basin water resource planning based on cloud computing technology and business workflows. This study couples water cycle models with multi-objective optimization models for water resource allocation, using digital topological water networks to achieve dynamic regional water resource allocation. The cloud service platform adopts a business-oriented modeling method based on B/S development architecture. This paper takes the Weihe River Basin as an example to simulate and analyze the evolution of the water cycle pattern and optimize the annual water resources allocation plan. Results show that: (1) the water cycle model of the cloud model service platform can better describe the runoff change process in the verification period; (2) through the cloud platform service model, the water shortage rate of the Weihe River Basin in 2025 is 7.95%. The research findings provide technical references and insights for intelligent water management and refined allocation of water resources in the Weihe River Basin.

Unrevealing the water-use strategies for typical ecological restoration plants and cash crops in the Eastern Chinese Loess Plateau region

Study regionFour geomorphic types in the eastern Loess Plateau (ECLP). Study focusquantitatively study the water-use strategies of typical plants (ecological restoration plants, food crops) based on stable isotope technology. New hydrological insights for the regionSignificant spatial-temporal heterogeneity appeared in regional soil water content and stable isotopes, with more significant fluctuations in soil water isotope values appearing in the rocky mountain region. Regional tree growth (including natural and plantation forests) was mainly influenced by precipitation (35±14 %) and surface layer (0–40 cm depth) soil water (25±11 %) during April and June, whereas deep soil water gradually became the main water source (> 20 %) in autumn and winter. A. Lavandulifolia mainly uses surface soil water (> 23 %), and the proportion of deep soil water utilization has increased after September. Surface soil water (0–40 cm) was the primary water source for T. aestivum during the overwintering (> 16 %) and reviving periods (> 26 %), and Z. mays utilized the largest proportion of soil water from 0 to 20 cm depth layer during the seeding (> 60 %) and maturation stages (> 35 %). Collectively, the results of this study have important implications for sustainable vegetation protection and the optimal allocation of water resources in the arid region.

Quantitative Analysis about the Spatial Heterogeneity of Water Conservation Services Function Using a Space–Time Cube Constructed Based on Ecosystem and Soil Types

Precisely delineating the spatiotemporal heterogeneity of water conservation services function (WCF) holds paramount importance for watershed management. However, the existing assessment techniques exhibit common limitations, such as utilizing only multi-year average values for spatial changes and relying solely on the spatial average values for temporal changes. Moreover, traditional research does not encompass all WCF values at each time step and spatial grid, hindering quantitative analysis of spatial heterogeneity in WCF. This study addresses these limitations by utilizing an improved water balance model based on ecosystem type and soil type (ESM-WBM) and employing the EFAST and Sobol’ method for parameter sensitivity analysis. Furthermore, a space–time cube of WCF, constructed using remote-sensing data, is further explored by Emerging Hot Spot Analysis for the expression of WCF spatial heterogeneity. Additionally, this study investigates the impact of two core parameters: neighborhood distance and spatial relationship conceptualization type. The results reveal that (1) the ESM-WBM model demonstrates high sensitivity toward ecosystem types and soil data, facilitating the accurate assessment of the impacts of ecosystem and soil pattern alterations on WCF; (2) the EHSA categorizes WCF into 17 patterns, which in turn allows for adjustments to ecological compensation policies in related areas based on each pattern; and (3) neighborhood distance and the type of spatial relationships conceptualization significantly impacts the results of EHSA. In conclusion, this study offers references for analyzing the spatial heterogeneity of WCF, providing a theoretical foundation for regional water resource management and ecological restoration policies with tailored strategies.

The Impact of Major Ecological Projects on the Water Yield of Mountain Basins, Northern China

Water yield, one of the most valuable and important ecological indicators, reflects the renewable capacity of regional water resources. The Taihang Mountains are a natural ecological barrier and an important source of water production for the North China Plain. Two large-scale projects involving returning farmland to forest and grassland have significantly changed the distribution of land use in the Taihang Mountains, and also affect the water production characteristics of the Taihang Mountains. Taking the Hutuo River Basin, a typical river in the Taihang Mountainous region, as the study area, the InVEST model is utilized to calculate the spatial and temporal changes in water yield capacity in the Hutuo River basin, and four scenarios were set to judge the impact of different ecological projects on the water yield of the mountainous watershed of the Hutuo River. The results showed that the water yield in the five study periods was 218.58–376.44 mm. The interannual variations in both precipitation and water yield of the study area in the last decade were large. The water yield is mainly concentrated in the northeast region of the upper reaches of the basin, and the smallest is the northwest and central regions of the upper reaches. The water yield in each year in the study area is mainly less than 400 mm, accounting for more than 60% of the study area, and the water yield has shown a large regional expansion in the past 10 years. Grassland has the largest water yield capacity of all land use types, and climate change has basically no effect on the water yield capacity of different land use types. The ecological project of returning farmland to forestland has a negative impact on the water yield capacity, whereas the water yield capacity increases after returning farmland to grassland. The water conservancy project of river training has a negative impact on the water yield capacity of the Hutuo River mountainous basin. The research results provide theoretical data for judging the relationship between vegetation restoration and water yield in mountainous watersheds, a scientific basis for evaluating the implementation effect of major projects, and strong data support for water resource management in the North China Plain.

Evaluation of atmospheric moisture transport to the Tibetan Plateau from 33 CMIP6 models

Atmospheric moisture transport is pivotal in regulating water resources over the Tibetan Plateau (TP). With the growing concerns about climate change, understanding the evolution of atmospheric moisture transport over the TP has become increasingly critical. however, the spatiotemporal distinctions of this transport remain poorly understood in the CMIP6 models. Here, we conducted a comprehensive evaluation of simulated historical atmospheric moisture transport from 33 CMIP6 models, utilizing a novel methodology that assesses the accuracy of model simulations in replicating regional atmospheric moisture transport over the TP. Our results indicate that the CMIP6 models generally succeed in reproducing the broad spatial patterns of atmospheric moisture transport. Nonetheless, substantial errors occur during the monsoon period, primarily attributable to inaccuracies in the location, movement, and intensity of the simulated Indian summer monsoon. The coarser resolution and poor representation of physical processes are potential reasons for errors in atmospheric moisture transport simulation over the TP. The Failure to simulate the terrain blocking on atmospheric moisture transport exacerbates these deficiencies, leading to significant discrepancies. Of the 33 CMIP6 models we investigated, over one-third displayed serious deficiencies in this regard. While coarser resolution and orographic gravity waves are plausible factors, they do not fully account for all the results obtained in this study. Insufficiently detailed or inaccurate topographic data used in the models may also contribute to this deficiency. This study highlights the necessity of using rigorously evaluated models to develop effective regional adaptation strategies over the Tibetan Plateau.

Evaluation of water environment quality in a typical wetland on the Qinghai-Tibet Plateau using positive matrix factorization and self-organizing map

The Qinghai-Tibet Plateau (QTP), the world's largest plateau, harbors rich lake resources but is ecologically fragile. Vulnerable river ecosystems in these areas face significant threats from environmental and anthropogenic pressures. Thus, comprehensive water quality monitoring is essential prior to conservation efforts. This study focuses on the Selin Co International Wetland in Tibet, a model of natural wetland ecosystems. We employed methods including water quality assessment, source apportionment, and clustering analysis to evaluate the water environment. Results from the Water Quality Index (WQI) indicate overall good water quality; however, parameters such as COD, DO, TN, TP, and As require monitoring for potential exceedance. Positive Matrix Factorization (PMF) analysis reveals that the primary sources of substances are identified as natural sources (37.17%), animal disturbance sources (32.93%), and anthropogenic activities (22.31%). The results of the water source analysis using the PMF and the cluster analysis based on the self-organizing map (SOM) indicate that natural and geographical environmental factors are the primary determinants of water quality, with minimal influence from human activities. This research emphasizes the importance of these natural influences, providing a scientific foundation for the protection and management of wetlands in the QTP, which is critical for ensuring regional water resource security.