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Search Results (1,389)

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Keywords = hydrological sustainability

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24 pages, 2540 KiB  
Article
Classification Framework for Hydrological Resources for Sustainable Hydrogen Production with a Predictive Algorithm for Optimization
by Mónica Álvarez-Manso, Gabriel Búrdalo-Salcedo and María Fernández-Raga
Hydrogen 2025, 6(3), 54; https://doi.org/10.3390/hydrogen6030054 - 6 Aug 2025
Abstract
Given the urgent need to decarbonize the global energy system, green hydrogen has emerged as a key alternative in the transition to renewables. However, its production via electrolysis demands high water quality and raises environmental concerns, particularly regarding reject water discharge. This study [...] Read more.
Given the urgent need to decarbonize the global energy system, green hydrogen has emerged as a key alternative in the transition to renewables. However, its production via electrolysis demands high water quality and raises environmental concerns, particularly regarding reject water discharge. This study employs an experimental and analytical approach to define optimal water characteristics for electrolysis, focusing on conductivity as a key parameter. A pilot water treatment plant with reverse osmosis and electrodeionization (EDI) was designed to simulate industrial-scale pretreatment. Twenty water samples from diverse natural sources (surface and groundwater) were tested, selected for geographical and geological variability. A predictive algorithm was developed and validated to estimate useful versus reject water based on input quality. Three conductivity-based categories were defined: optimal (0–410 µS/cm), moderate (411–900 µS/cm), and restricted (>900 µS/cm). Results show that water quality significantly affects process efficiency, energy use, waste generation, and operating costs. This work offers a technical and regulatory framework for assessing potential sites for green hydrogen plants, recommending avoidance of high-conductivity sources. It also underscores the current regulatory gap regarding reject water treatment, stressing the need for clear environmental guidelines to ensure project sustainability. Full article
(This article belongs to the Special Issue Advances in Hydrogen Production, Storage, and Utilization)
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22 pages, 2029 KiB  
Article
A Deep Reinforcement Learning Framework for Cascade Reservoir Operations Under Runoff Uncertainty
by Jing Xu, Jiabin Qiao, Qianli Sun and Keyan Shen
Water 2025, 17(15), 2324; https://doi.org/10.3390/w17152324 - 5 Aug 2025
Viewed by 37
Abstract
Effective management of cascade reservoir systems is essential for balancing hydropower generation, flood control, and ecological sustainability, especially under increasingly uncertain runoff conditions driven by climate change. Traditional optimization methods, while widely used, often struggle with high dimensionality and fail to adequately address [...] Read more.
Effective management of cascade reservoir systems is essential for balancing hydropower generation, flood control, and ecological sustainability, especially under increasingly uncertain runoff conditions driven by climate change. Traditional optimization methods, while widely used, often struggle with high dimensionality and fail to adequately address inflow variability. This study introduces a novel deep reinforcement learning (DRL) framework that tightly couples probabilistic runoff forecasting with adaptive reservoir scheduling. We integrate a Long Short-Term Memory (LSTM) neural network to model runoff uncertainty and generate probabilistic inflow forecasts, which are then embedded into a Proximal Policy Optimization (PPO) algorithm via Monte Carlo sampling. This unified forecast–optimize architecture allows for dynamic policy adjustment in response to stochastic hydrological conditions. A case study on China’s Xiluodu–Xiangjiaba cascade system demonstrates that the proposed LSTM-PPO framework achieves superior performance compared to traditional baselines, notably improving power output, storage utilization, and spillage reduction. The results highlight the method’s robustness and scalability, suggesting strong potential for supporting resilient water–energy nexus management under complex environmental uncertainty. Full article
(This article belongs to the Section Hydrology)
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14 pages, 2532 KiB  
Article
Machine Learning for Spatiotemporal Prediction of River Siltation in Typical Reach in Jiangxi, China
by Yong Fu, Jin Luo, Die Zhang, Lingjia Liu, Gan Luo and Xiaofang Zu
Appl. Sci. 2025, 15(15), 8628; https://doi.org/10.3390/app15158628 (registering DOI) - 4 Aug 2025
Viewed by 118
Abstract
Accurate forecasting of river siltation is essential for ensuring inland waterway navigability and guiding sustainable sediment management. This study investigates the downstream reach of the Shihutang navigation power hub along the Ganjiang River in Jiangxi Province, China, an area characterized by pronounced seasonal [...] Read more.
Accurate forecasting of river siltation is essential for ensuring inland waterway navigability and guiding sustainable sediment management. This study investigates the downstream reach of the Shihutang navigation power hub along the Ganjiang River in Jiangxi Province, China, an area characterized by pronounced seasonal sedimentation and hydrological variability. To enable fine-scale prediction, we developed a data-driven framework using a random forest regression model that integrates high-resolution bathymetric surveys with hydrological and meteorological observations. Based on the field data from April to July 2024, the model was trained to forecast monthly siltation volumes at a 30 m grid scale over a six-month horizon (July–December 2024). The results revealed a marked increase in siltation from July to September, followed by a decline during the winter months. The accumulation of sediment, combined with falling water levels, was found to significantly reduce the channel depth and width, particularly in the upstream sections, posing a potential risk to navigation safety. This study presents an initial, yet promising attempt to apply machine learning for spatially explicit siltation prediction in data-constrained river systems. The proposed framework provides a practical tool for early warning, targeted dredging, and adaptive channel management. Full article
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18 pages, 3354 KiB  
Article
Hydrological Modeling of the Chikugo River Basin Using SWAT: Insights into Water Balance and Seasonal Variability
by Francis Jhun Macalam, Kunyang Wang, Shin-ichi Onodera, Mitsuyo Saito, Yuko Nagano, Masatoshi Yamazaki and Yu War Nang
Sustainability 2025, 17(15), 7027; https://doi.org/10.3390/su17157027 - 2 Aug 2025
Viewed by 293
Abstract
Integrated hydrological modeling plays a crucial role in advancing sustainable water resource management, particularly in regions facing seasonal and extreme precipitation events. However, comprehensive studies that assess hydrological variability in temperate river basins remain limited. This study addresses this gap by evaluating the [...] Read more.
Integrated hydrological modeling plays a crucial role in advancing sustainable water resource management, particularly in regions facing seasonal and extreme precipitation events. However, comprehensive studies that assess hydrological variability in temperate river basins remain limited. This study addresses this gap by evaluating the performance of the Soil and Water Assessment Tool (SWAT) in simulating streamflow, water balance, and seasonal hydrological dynamics in the Chikugo River Basin, Kyushu Island, Japan. The basin, originating from Mount Aso and draining into the Ariake Sea, is subject to frequent typhoons and intense rainfall, making it a critical case for sustainable water governance. Using the Sequential Uncertainty Fitting Version 2 (SUFI-2) approach, we calibrated the SWAT model over the period 2007–2021. Water balance analysis revealed that baseflow plays dominant roles in basin hydrology which is essential for agricultural and domestic water needs by providing a stable groundwater contribution despite increasing precipitation and varying water demand. These findings contribute to a deeper understanding of hydrological behavior in temperate catchments and offer a scientific foundation for sustainable water allocation, planning, and climate resilience strategies. Full article
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14 pages, 5954 KiB  
Article
Mapping Wet Areas and Drainage Networks of Data-Scarce Catchments Using Topographic Attributes
by Henrique Marinho Leite Chaves, Maria Tereza Leite Montalvão and Maria Rita Souza Fonseca
Water 2025, 17(15), 2298; https://doi.org/10.3390/w17152298 - 2 Aug 2025
Viewed by 198
Abstract
Wet areas, which are locations in the landscape that consistently retain moisture, and channel networks are important landscape compartments, with key hydrological and ecological functions. Hence, defining their spatial boundaries is an important step towards sustainable watershed management. In catchments of developing countries, [...] Read more.
Wet areas, which are locations in the landscape that consistently retain moisture, and channel networks are important landscape compartments, with key hydrological and ecological functions. Hence, defining their spatial boundaries is an important step towards sustainable watershed management. In catchments of developing countries, wet areas and small order channels of river networks are rarely mapped, although they represent a crucial component of local livelihoods and ecosystems. In this study, topographic attributes generated with a 30 m SRTM DEM were used to map wet areas and stream networks of two tropical catchments in Central Brazil. The topographic attributes for wet areas were the local slope and the slope curvature, and the Topographic Wetness Index (TWI) was used to delineate the stream networks. Threshold values of the selected topographic attributes were calibrated in the Santa Maria catchment, comparing the synthetically generated wet areas and drainage networks with corresponding reference (map) features, and validated in the nearby Santa Maria basin. Drainage network and wet area delineation accuracies were estimated using random basin transects and multi-criteria and confusion matrix methods. The drainage network accuracies were 67.2% and 70.7%, and wet area accuracies were 72.7% and 73.8%, for the Santa Maria and Gama catchments, respectively, being equivalent or higher than previous studies. The mapping errors resulted from model incompleteness, DEM vertical inaccuracy, and cartographic misrepresentation of the reference topographic maps. The study’s novelty is the use of readily available information to map, with simplicity and robustness, wet areas and channel initiation in data-scarce, tropical environments. Full article
(This article belongs to the Section Hydrogeology)
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17 pages, 2032 KiB  
Article
The Impact of Hydrological Streamflow Drought on Pollutant Concentration and Its Implications for Sustainability in a Small River in Poland
by Leszek Hejduk, Ewa Kaznowska, Michał Wasilewicz and Agnieszka Hejduk
Sustainability 2025, 17(15), 6995; https://doi.org/10.3390/su17156995 - 1 Aug 2025
Viewed by 182
Abstract
The paper presents the results of investigations into the relationship between selected water quality parameters and hydrological streamflow drought in a small river situated in the Mazovian Lowlands in Poland. As hydrological streamflow drought periods become more frequent in Poland, investigations about the [...] Read more.
The paper presents the results of investigations into the relationship between selected water quality parameters and hydrological streamflow drought in a small river situated in the Mazovian Lowlands in Poland. As hydrological streamflow drought periods become more frequent in Poland, investigations about the relationship between flow and water quality parameters can be an essential contribution to a better understanding of the impact of low flow on the status of water rivers. Data from a three-year study of a small lowland river along with significant agricultural land management was used to analyze the connection between low flows and specific water quality indicators. The separation of low-flow data from water discharge records was achieved using two criteria: Q90% (the discharge value from a flow duration curve) and a minimum low-flow duration of 10 days. During these periods, the concentration of water quality indicators was determined based on collected water samples. In total, 30 samples were gathered and examined for pH, suspended sediments, dissolved substances, hardness, ammonium, nitrates, nitrites, phosphates, total phosphorus, chloride, sulfate, calcium, magnesium, and water temperature during sampling. The study’s main aim was to describe the relation between hydrological streamflow droughts and chosen water quality parameters. The analysis results demonstrate an inverse statistically significant relationship between concentration and low-flow values for total hardness and sulfate. In contrast, there was a direct relationship between nutrient indicators, suspended sediment concentration, and river hydrological streamflow drought. Statistical tests were applied to compare the datasets between years, revealing statistical differences only for nutrient indicators. Full article
(This article belongs to the Topic Water Management in the Age of Climate Change)
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20 pages, 4874 KiB  
Article
Influence of Vegetation Cover and Soil Properties on Water Infiltration: A Study in High-Andean Ecosystems of Peru
by Azucena Chávez-Collantes, Danny Jarlis Vásquez Lozano, Leslie Diana Velarde-Apaza, Juan-Pablo Cuevas, Richard Solórzano and Ricardo Flores-Marquez
Water 2025, 17(15), 2280; https://doi.org/10.3390/w17152280 - 31 Jul 2025
Viewed by 173
Abstract
Water infiltration into soil is a key process in regulating the hydrological cycle and sustaining ecosystem services in high-Andean environments. However, limited information is available regarding its dynamics in these ecosystems. This study evaluated the influence of three types of vegetation cover and [...] Read more.
Water infiltration into soil is a key process in regulating the hydrological cycle and sustaining ecosystem services in high-Andean environments. However, limited information is available regarding its dynamics in these ecosystems. This study evaluated the influence of three types of vegetation cover and soil properties on water infiltration in a high-Andean environment. A double-ring infiltrometer, the Water Drop Penetration Time (WDPT, s) method, and laboratory physicochemical characterization were employed. Soils under forest cover exhibited significantly higher quasi-steady infiltration rates (is, 0.248 ± 0.028 cm·min−1) compared to grazing areas (0.051 ± 0.016 cm·min−1) and agricultural lands (0.032 ± 0.013 cm·min−1). Soil organic matter content was positively correlated with is. The modified Kostiakov infiltration model provided the best overall fit, while the Horton model better described infiltration rates approaching is. Sand and clay fractions, along with K+, Ca2+, and Mg2+, were particularly significant during the soil’s wet stages. In drier stages, increased Na+ concentrations and decreased silt content were associated with higher water repellency. Based on WDPT, agricultural soils exhibited persistent hydrophilic behavior even after drying (median [IQR] from 0.61 [0.38] s to 1.24 [0.46] s), whereas forest (from 2.84 [3.73] s to 3.53 [24.17] s) and grazing soils (from 4.37 [1.95] s to 19.83 [109.33] s) transitioned to weakly or moderately hydrophobic patterns. These findings demonstrate that native Andean forest soils exhibit a higher infiltration capacity than soils under anthropogenic management (agriculture and grazing), highlighting the need to conserve and restore native vegetation cover to strengthen water resilience and mitigate the impacts of land-use change. Full article
(This article belongs to the Special Issue Soil–Water Interaction and Management)
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25 pages, 10240 KiB  
Article
Present and Future Energy Potential of Run-of-River Hydropower in Mainland Southeast Asia: Balancing Climate Change and Environmental Sustainability
by Saman Maroufpoor and Xiaosheng Qin
Water 2025, 17(15), 2256; https://doi.org/10.3390/w17152256 - 29 Jul 2025
Viewed by 343
Abstract
Southeast Asia relies heavily on hydropower from dams and reservoir projects, but this dependence comes at the cost of ecological damage and increased vulnerability to extreme events. This dilemma necessitates a choice between continued dam development and adopting alternative renewable options. Concerns over [...] Read more.
Southeast Asia relies heavily on hydropower from dams and reservoir projects, but this dependence comes at the cost of ecological damage and increased vulnerability to extreme events. This dilemma necessitates a choice between continued dam development and adopting alternative renewable options. Concerns over these environmental impacts have already led to halts in dam construction across the region. This study assesses the potential of run-of-river hydropower plants (RHPs) across 199 hydrometric stations in Mainland Southeast Asia (MSEA). The assessment utilizes power duration curves for the historical period and projections from the HBV hydrological model, which is driven by an ensemble of 31 climate models for future scenarios. Energy production was analyzed at four levels (minimum, maximum, balanced, and optimal) for both historical and future periods under varying Shared Socioeconomic Pathways (SSPs). To promote sustainable development, environmental flow constraints and carbon dioxide (CO2) emissions were evaluated for both historical and projected periods. The results indicate that the aggregate energy production potential during the historical period ranges from 111.15 to 229.62 MW (Malaysia), 582.78 to 3615.36 MW (Myanmar), 555.47 to 3142.46 MW (Thailand), 1067.05 to 6401.25 MW (Laos), 28.07 to 189.77 MW (Vietnam), and 566.13 to 2803.75 MW (Cambodia). The impact of climate change on power production varies significantly across countries, depending on the level and scenarios. At the optimal level, an average production change of −9.2–5.9% is projected for the near future, increasing to 15.3–19% in the far future. Additionally, RHP development in MSEA is estimated to avoid 32.5 Mt of CO2 emissions at the optimal level. The analysis further shows avoidance change of 8.3–25.3% and −8.6–25.3% under SSP245 and SSP585, respectively. Full article
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22 pages, 3231 KiB  
Article
Evapotranspiration in a Small Well-Vegetated Basin in Southwestern China
by Zitong Zhou, Ying Li, Lingjun Liang, Chunlin Li, Yuanmei Jiao and Qian Ma
Sustainability 2025, 17(15), 6816; https://doi.org/10.3390/su17156816 - 27 Jul 2025
Viewed by 304
Abstract
Evapotranspiration (ET) crucially regulates water storage dynamics and is an essential component of the terrestrial water cycle. Understanding ET dynamics is fundamental for sustainable water resource management, particularly in regions facing increasing drought risks under climate change. In regions like southwestern China, where [...] Read more.
Evapotranspiration (ET) crucially regulates water storage dynamics and is an essential component of the terrestrial water cycle. Understanding ET dynamics is fundamental for sustainable water resource management, particularly in regions facing increasing drought risks under climate change. In regions like southwestern China, where extreme drought events are prevalent due to complex terrain and climate warming, ET becomes a key factor in understanding water availability and drought dynamics. Using the SWAT model, this study investigates ET dynamics and influencing factors in the Jizi Basin, Yunnan Province, a small basin with over 71% forest coverage. The model calibration and validation results demonstrated a high degree of consistency with observed discharge data and ERA5, confirming its reliability. The results show that the annual average ET in the Jizi Basin is 573.96 mm, with significant seasonal variations. ET in summer typically ranges from 70 to 100 mm/month, while in winter, it drops to around 20 mm/month. Spring ET exhibits the highest variability, coinciding with the occurrence of extreme hydrological events such as droughts. The monthly anomalies of ET effectively reproduce the spring and early summer 2019 drought event. Notably, ET variation exhibits significant uncertainty under scenarios of +1 °C temperature and −20% precipitation. Furthermore, although land use changes had relatively small effects on overall ET, they played crucial roles in promoting groundwater recharge through enhanced percolation, especially forest cover. The study highlights that, in addition to climate and land use, soil moisture and groundwater conditions are vital in modulating ET and drought occurrence. The findings offer insights into the hydrological processes of small forested basins in southwestern China and provide important support for sustainable water resource management and effective climate adaptation strategies, particularly in the context of increasing drought vulnerability. Full article
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17 pages, 1976 KiB  
Article
Soil Hydrological Properties and Organic Matter Content in Douglas-Fir and Spruce Stands: Implications for Forest Resilience to Climate Change
by Anna Klamerus-Iwan, Piotr Behan, Ewa Słowik-Opoka, María Isabel Delgado-Moreira and Lizardo Reyna-Bowen
Forests 2025, 16(8), 1217; https://doi.org/10.3390/f16081217 - 24 Jul 2025
Viewed by 311
Abstract
Climate change has intensified over recent decades, prompting shifts in forest management strategies, particularly in the Sudetes region of Poland, where native species like Norway spruce (Picea abies), European beech (Fagus sylvatica), and silver fir (Abies alba) [...] Read more.
Climate change has intensified over recent decades, prompting shifts in forest management strategies, particularly in the Sudetes region of Poland, where native species like Norway spruce (Picea abies), European beech (Fagus sylvatica), and silver fir (Abies alba) have historically dominated. To address these changes, non-native species such as Douglas fir (Pseudotsuga menziesii) have been introduced as potential alternatives. This study, conducted in the Jugów and Świerki forest districts, compared the soil properties and water retention capacities of Douglas fir (Dg) and Norway spruce (Sw) stands (age classes from 8–127 years) in the Fresh Mountain Mixed Forest Site habitat. Field measurements included temperature, humidity, organic matter content, water capacity, and granulometric composition. Results indicate that, in comparison to Sw stands, Dg stands were consistently linked to soils that were naturally finer textured. The observed hydrological changes were mostly supported by these textural differences: In all investigated circumstances, Dg soils demonstrated greater water retention, displaying a water capacity that was around 5% higher. In addition to texture, Dg stands showed reduced soil water repellency and a substantially greater organic matter content (59.74% compared to 27.91% in Sw), which further enhanced soil structure and moisture retention. Conversely, with increasing climatic stress, Sw soils, with coarser textures and less organic matter, showed decreased water retention. The study highlights the importance of species selection in sustainable forest management, especially under climate change. Future research should explore long-term ecological impacts, including effects on microbial communities, nutrient cycling, and biodiversity, to optimize forest resilience and sustainability. Full article
(This article belongs to the Section Forest Ecology and Management)
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27 pages, 21494 KiB  
Article
Deep Learning and Transformer Models for Groundwater Level Prediction in the Marvdasht Plain: Protecting UNESCO Heritage Sites—Persepolis and Naqsh-e Rustam
by Peyman Heidarian, Franz Pablo Antezana Lopez, Yumin Tan, Somayeh Fathtabar Firozjaee, Tahmouras Yousefi, Habib Salehi, Ava Osman Pour, Maria Elena Oscori Marca, Guanhua Zhou, Ali Azhdari and Reza Shahbazi
Remote Sens. 2025, 17(14), 2532; https://doi.org/10.3390/rs17142532 - 21 Jul 2025
Viewed by 669
Abstract
Groundwater level monitoring is crucial for assessing hydrological responses to climate change and human activities, which pose significant threats to the sustainability of semi-arid aquifers and the cultural heritage they sustain. This study presents an integrated remote sensing and transformer-based deep learning framework [...] Read more.
Groundwater level monitoring is crucial for assessing hydrological responses to climate change and human activities, which pose significant threats to the sustainability of semi-arid aquifers and the cultural heritage they sustain. This study presents an integrated remote sensing and transformer-based deep learning framework that combines diverse geospatial datasets to predict spatiotemporal variations across the plain near the Persepolis and Naqsh-e Rustam archaeological complexes—UNESCO World Heritage Sites situated at the plain’s edge. We assemble 432 synthetic aperture radar (SAR) scenes (2015–2022) and derive vertical ground motion rates greater than −180 mm yr−1, which are co-localized with multisource geoinformation, including hydrometeorological indices, biophysical parameters, and terrain attributes, to train transformer models with traditional deep learning methods. A sparse probabilistic transformer (ConvTransformer) trained on 95 gridded variables achieves an out-of-sample R2 = 0.83 and RMSE = 6.15 m, outperforming bidirectional deep learning models by >40%. Scenario analysis indicates that, in the absence of intervention, subsidence may exceed 200 mm per year within a decade, threatening irreplaceable Achaemenid stone reliefs. Our results indicate that attention-based networks, when coupled to synergistic geodetic constraints, enable early-warning quantification of groundwater stress over heritage sites and provide a scalable template for sustainable aquifer governance worldwide. Full article
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24 pages, 5725 KiB  
Article
Modeling of Hydrological Processes in a Coal Mining Subsidence Area with High Groundwater Levels Based on Scenario Simulations
by Shiyuan Zhou, Hao Chen, Qinghe Hou, Haodong Liu and Pingjia Luo
Hydrology 2025, 12(7), 193; https://doi.org/10.3390/hydrology12070193 - 19 Jul 2025
Viewed by 375
Abstract
The Eastern Huang–Huai region of China is a representative mining area with a high groundwater level. High-intensity underground mining activities have not only induced land cover and land use changes (LUCC) but also significantly changed the watershed hydrological behavior. This study integrated the [...] Read more.
The Eastern Huang–Huai region of China is a representative mining area with a high groundwater level. High-intensity underground mining activities have not only induced land cover and land use changes (LUCC) but also significantly changed the watershed hydrological behavior. This study integrated the land use prediction model PLUS and the hydrological simulation model MIKE 21. Taking the Bahe River Watershed in Huaibei City, China, as an example, it simulated the hydrological response trends of the watershed in 2037 under different land use scenarios. The results demonstrate the following: (1) The land use predictions for each scenario exhibit significant variation. In the maximum subsidence scenario, the expansion of water areas is most pronounced. In the planning scenario, the increase in construction land is notable. Across all scenarios, the area of cultivated land decreases. (2) In the maximum subsidence scenario, the area of high-intensity waterlogging is the greatest, accounting for 31.35% of the total area of the watershed; in the planning scenario, the proportion of high-intensity waterlogged is the least, at 19.10%. (3) In the maximum subsidence scenario, owing to the water storage effect of the subsidence depression, the flood peak is conspicuously delayed and attains the maximum value of 192.3 m3/s. In the planning scenario, the land reclamation rate and ecological restoration rate of subsidence area are the highest, while the regional water storage capacity is the lowest. As a result, the total cumulative runoff is the greatest, and the peak flood value is reduced. The influence of different degrees of subsidence on the watershed hydrological behavior varies, and the coal mining subsidence area has the potential to regulate and store runoff and perform hydrological regulation. The results reveal the mechanism through which different land use scenarios influence hydrological processes, which provides a scientific basis for the territorial space planning and sustainable development of coal mining subsidence areas. Full article
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21 pages, 13177 KiB  
Article
Links Between the Coastal Climate, Landscape Hydrology, and Beach Dynamics near Cape Vidal, South Africa
by Mark R. Jury
Coasts 2025, 5(3), 25; https://doi.org/10.3390/coasts5030025 - 18 Jul 2025
Viewed by 285
Abstract
Coastal climate processes that affect landscape hydrology and beach dynamics are studied using local and remote data sets near Cape Vidal (28.12° S, 32.55° E). The sporadic intra-seasonal pulsing of coastal runoff, vegetation, and winds is analyzed to understand sediment inputs and transport [...] Read more.
Coastal climate processes that affect landscape hydrology and beach dynamics are studied using local and remote data sets near Cape Vidal (28.12° S, 32.55° E). The sporadic intra-seasonal pulsing of coastal runoff, vegetation, and winds is analyzed to understand sediment inputs and transport by near-shore wind-waves and currents. River-borne sediments, eroded coral substrates, and reworked beach sand are mobilized by frequent storms. Surf-zone currents ~0.4 m/s instill the northward transport of ~6 105 kg/yr/m. An analysis of the mean annual cycle over the period of 1997–2024 indicates a crest of rainfall over the Umfolozi catchment during summer (Oct–Mar), whereas coastal suspended sediment, based on satellite red-band reflectivity, rises in winter (Apr–Sep) due to a deeper mixed layer and larger northward wave heights. Sediment input to the beaches near Cape Vidal exhibit a 3–6-year cycle of southeasterly waves and rainy weather associated with cool La Nina tropical sea temperatures. Beachfront sand dunes are wind-swept and release sediment at ~103 m3/yr/m, which builds tall back-dunes and helps replenish the shoreline, especially during anticyclonic dry spells. A wind event in Nov 2018 is analyzed to quantify aeolian transport, and a flood in Jan–Feb 2025 is studied for river plumes that meet with stormy seas. Management efforts to limit development and recreational access have contributed to a sustainable coastal environment despite rising tides and inland temperatures. Full article
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25 pages, 7522 KiB  
Article
Quantitative Estimation of Vegetation Carbon Source/Sink and Its Response to Climate Variability and Anthropogenic Activities in Dongting Lake Wetland, China
by Mengshen Guo, Nianqing Zhou, Yi Cai, Xihua Wang, Xun Zhang, Shuaishuai Lu, Kehao Liu and Wengang Zhao
Remote Sens. 2025, 17(14), 2475; https://doi.org/10.3390/rs17142475 - 16 Jul 2025
Viewed by 308
Abstract
Wetlands are critical components of the global carbon cycle, yet their carbon sink dynamics under hydrological fluctuations remain insufficiently understood. This study employed the Carnegie-Ames-Stanford Approach (CASA) model to estimate the net ecosystem productivity (NEP) of the Dongting Lake wetland and explored the [...] Read more.
Wetlands are critical components of the global carbon cycle, yet their carbon sink dynamics under hydrological fluctuations remain insufficiently understood. This study employed the Carnegie-Ames-Stanford Approach (CASA) model to estimate the net ecosystem productivity (NEP) of the Dongting Lake wetland and explored the spatiotemporal dynamics and driving mechanisms of carbon sinks from 2000 to 2022, utilizing the Theil-Sen median trend, Mann-Kendall test, and attribution based on the differentiating equation (ADE). Results showed that (1) the annual mean spatial NEP was 50.24 g C/m2/a, which first increased and then decreased, with an overall trend of −1.5 g C/m2/a. The carbon sink was strongest in spring, declined in summer, and shifted to a carbon source in autumn and winter. (2) Climate variability and human activities contributed +2.17 and −3.73 g C/m2/a to NEP, respectively. Human activities were the primary driver of carbon sink degradation (74.30%), whereas climate change mainly promoted carbon sequestration (25.70%). However, from 2000–2011 to 2011–2022, climate change shifted from enhancing to limiting carbon sequestration, mainly due to the transition from water storage and lake reclamation to ecological restoration policies and intensified climate anomalies. (3) NEP was negatively correlated with precipitation and water level. Land use adjustments, such as forest expansion and conversion of cropland and reed to sedge, alongside maintaining growing season water levels between 24.06~26.44 m, are recommended to sustain and enhance wetland carbon sinks. Despite inherent uncertainties in model parameterization and the lack of sufficient in situ flux validation, these findings could provide valuable scientific insights for wetland carbon management and policy-making. Full article
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15 pages, 3200 KiB  
Review
Research Hotspots and Trends in Soil Infiltration at the Watershed Scale Using the SWAT Model: A Bibliometric Analysis
by Yuxin Ouyang, S. M. Asik Ullah and Chika Takatori
Water 2025, 17(14), 2119; https://doi.org/10.3390/w17142119 - 16 Jul 2025
Viewed by 325
Abstract
Understanding soil infiltration at the watershed level is crucial to hydrological studies, as it significantly influences surface runoff, groundwater replenishment, and ecosystem sustainability. Research in this area—particularly employing the Soil and Water Assessment Tool (SWAT)—has seen sustained scholarly interest, with an upward trend [...] Read more.
Understanding soil infiltration at the watershed level is crucial to hydrological studies, as it significantly influences surface runoff, groundwater replenishment, and ecosystem sustainability. Research in this area—particularly employing the Soil and Water Assessment Tool (SWAT)—has seen sustained scholarly interest, with an upward trend in related publications. This study analyzed 141 peer-reviewed articles from the Web of Science (WOS) Core Collection. By applying bibliometric techniques through CiteSpace visualization software, it explored the key themes and emerging directions in the use of the SWAT model for soil infiltration studies across watersheds. Findings revealed that this field integrates multiple disciplines. Notably, the Journal of Hydrology and Hydrological Processes emerged as two of the most impactful publication venues. Researchers and institutions from the United States, China, and Ethiopia were the core contributors to this area. “Land use” and “climate change” are currently the hotspots of interest in this field. There are three development trends: (1) The scale of research is continuously expanding. (2) The research subjects are diversified, ranging from initially focusing on agricultural watersheds to surrounding areas such as hillsides, grasslands, and forests. (3) The research content becomes more systematic, emphasizing regional coordination and ecological sustainability. Overall, the research on soil infiltration at the watershed scale using the SWAT model presents a promising and thriving field. This study provides researchers with a framework that objectively presents the research hotspots and trends in this area, serving as a valuable resource for advancing academic inquiry in this domain. Full article
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