Water Resources Management Research Articles

Impact of climate change on permanent lakes in a semiarid region: Southwestern Mediterranean basin (S Spain).

In recent decades, many wetlands in the Mediterranean watershed have dried up. We forecast the impact of climate change on the hydrology of three permanent lakes in a semiarid areo of the southwestern Mediterranean region. To achieve this, we applied daily water balance models to calculate variations in water levels and validated our approach using actual lake level measurements spanning over 20years. To delve into groundwater/lake interactions, we calculated several hydrological indices and compared evaporation with the water level drop during extremely dry periods. After validating the three hydrological models, we applied the RCP 4.5 and RCP 8.5 climate change scenarios. We found Zóñar Lake highly resilient to climate changes because of groundwater contributions, resulting in minimal lake level oscillations even during periods of low rainfall. However, spring management and/or groundwater extractions may affect the lake hydroperiod. The Amarga and Grande lakes have weaker lake/groundwater interactions and show significant water lake level fluctuations, making them more sensitive to climate change. Indeed, our model predict that these lakes will transition into semipermanent or seasonal playa-lakes by mid-21th century. We found that deep and spring and/or groundwater-fed lakes are less vulnerable to climate changes. These results highlight the importance of developing robust hydrogeological models in such water bodies, focusing on the climate changes vulnerability of wetlands in semiarid regions, in order to formulate an integrated strategy for water resources management.

Impacts of anthropogenic activities on land use land cover change dynamics in the Ogun River Basin, Nigeria

ABSTRACT In this research, the impacts of past (1984–2020) and future (2040–2060) changes in Ogun River Basin's land use land cover (LULC) dynamics were studied. LULC changes were classified using the Random Forest algorithm in Google Earth Engine on Landsat imagery from 1984, 2000, and 2020 epochs. The multi-layer perceptron-neural network and Markov Chain in the Land Change Modeler were used to predict the LULC maps under various future scenarios. The results revealed significant alterations in the LULC pattern. Forests, wetlands, and water bodies decreased between the epochs 1984 and 2020 by −29.0%, −58.3%, and −84.5%, respectively, whereas farmland and built-up areas expanded by 104 and 20%, respectively. The Business-as-Usual scenario is anticipated to result in an increase in farmland of 3.73% in 2040 and 3.89% in 2060, respectively, at the detriment of forest cover and wetland areas, which are projected to decrease. Under the afforestation scenario, the forest is predicted to expand at the expense of farmland and built-up areas, which are anticipated to expand by 6% (2040) and 8% (2060), respectively. These results, in combination with those derived from the Markov model, provide the necessary evidence base to support land use planning and the future-proofing of sustainable water resources management strategies in the basin.

Comparative study on lake ice phenology changes and driving factors in large lakes of mid-latitude Xinjiang, China.

The changes in lake ice phenology (LIP) can intuitively reflect the climate evolution in the regions where lakes are located, serving as an important indicator of climate change. The Tianshan Mountains, situated at the southern edge of freezing lakes in the Northern Hemisphere, are a crucial water resource base in Xinjiang and support significant ecosystems closely related to human activities. In the context of intensified climate change, this study focuses on the geographical location, altitude, and water quality differences among large lake groups in the mid-latitude region of Xinjiang, aiming to explore the characteristics of LIP changes in these lakes and their responses to driving factors, thereby providing a basis for effective environmental management and protection. This research conducts a comparative analysis of the LIP changes and driving factors of three large lakes-Sayram Lake (SL), Bosten Lake (BL), and Ebnur Lake (EL)-using multi-source remote sensing data to reveal the response and adaptation mechanisms of lakes under global warming. It effectively captures the time series variations of ice formation and melting, as well as the common responses to environmental and climatic factors. The results indicate that SL has experienced significant climate change effects, with earlier freezing times and accelerated melting speeds; In contrast, EL and BL have shown relatively minor changes, suggesting that geographical and hydrological factors may buffer the impacts of climate. The study finds that all three lakes are jointly influenced by environmental factors such as temperature, wind speed, and precipitation; however, due to differences in altitude, lake surface area, and water transparency, their responses to these climatic factors vary significantly. For instance, SL's high altitude gives water transparency a dominant role in LIP, while BL's larger surface area enhances the impact of precipitation and thermal capacity on the melting process. This indicates that, despite facing similar climate pressures, local environmental conditions can lead to different trends in ice phenology changes. This study offers a novel and efficient monitoring method for LIP, providing valuable insights for future LIP research and water resource management.

Multi-Objective Water Allocation for Wu’an City

To solve the prominent problem of water supply and demand contradictions, enhance water resource security capabilities, and improve economic, social, and ecological benefits, this paper comprehensively analyzes the water resource situation in Wu’an City and proposes a method for calculating the rigid water demand and total water demand threshold for the whole city and a method for calculating the water supply capacity of multiple water sources. At the same time, taking economic, social, and ecological benefits as the objective function and water resource allocation rules, water supply balance, water supply capacity, total water consumption, water consumption per Chinese Yuan(CNY) 10,000 of Gross Domestic Product (GDP), water consumption per CNY 10,000 of industrial added value, and non-negative as constraints, the water resource optimization allocation model for Wu’an City was constructed, and the Non-dominated Sorting Genetic Algorithm III (NSGA-III) combined with the Technique for Order Preference by Similarity to an Ideal Solution (TOSPIS) was used to solve it. The results show that the rigid water demand of Wu’an City is met, the Gini coefficient of water supply satisfaction and ecological water shortage in the flat water scenario are both 0, the overall difference in water supply satisfaction of each township is very small, and the ecological water demand is met. Under the current situation, Wu’an City basically achieves a regional supply and demand balance, which can increase water supply by 5.841 million m3 and increase the net economic benefit of water supply by CNY 136.5515 million. The optimized water resource allocation plan has higher economic, social, and ecological benefits. The research can provide technical support for water resource management in Wu’an City.

Modeling and Optimization of Detention Basins For Cost Minimization and Flood Mitigation in Urban Areas

Objective: The objective of this study was to develop and apply an optimization model for the sizing of detention reservoirs in an urban watershed, aiming to minimize implementation costs and mitigate flood risks in critical areas. Theoretical Framework: The study is based on flood control models and urban drainage infrastructure, focusing on optimization techniques applied to water resource management. References include the SCS Curve Number method for surface runoff, the PCSWMM hydrological model for precipitation simulations, and the HEC-RAS hydraulic model for flood area delineation. Method: The research was divided into three main stages: (i) physical and hydrological characterization of the watershed using PCSWMM; (ii) delineation of flood-prone areas with HEC-RAS 2D; and (iii) development of a nonlinear optimization model in GAMS for the sizing of detention reservoirs. The decision variables included the height, surface area, and outlet diameter of the reservoirs, with implementation cost as the main objective function. Results and Discussion: The optimization modeling determined the ideal characteristics of six reservoirs distributed throughout the watershed to maximize retention and flow control. The total flooded area was estimated at 270,989 m², with maximum depths reaching 1.914 meters. The total cost of the reservoir system was calculated at approximately R$ 1,164,845.91, providing an optimized solution for flood control in the watershed’s vulnerable areas. Research Implications: The results suggest a practical and feasible solution for flood control in urban watersheds, offering a replicable model that can aid in planning drainage infrastructure in other regions facing similar challenges. Originality/Value: This study is original in its integrated application of PCSWMM and HEC-RAS models with a nonlinear optimization approach in GAMS, resulting in an efficient and economical solution for flood mitigation in urbanized areas.

Spatiotemporal Variation Assessment and Improved Prediction Of Cyanobacteria Blooms in Lakes Using Improved Machine Learning Model Based on Multivariate Data.

Cyanobacterial blooms in shallow lakes pose a significant threat to aquatic ecosystems and public health worldwide, highlighting the urgent need for advanced predictive methodologies. As impounded lakes along the Eastern Route of the South-to-North Water Diversion Project, Lakes Hongze and Luoma play a key role in water resource management, making the prediction of cyanobacterial blooms in these lakes particularly important. To address this, satellite remote sensing data were utilized to analyze the spatiotemporal dynamics of cyanobacterial blooms in these lakes. Subsequently, a precise machine learning model, integrating the Projection Pursuit Model and Random Forest (PP-RF) algorithms, was developed to predict the extent of cyanobacterial blooms, considering a range of influencing factors, including physical, chemical, climatic, and hydrologic variables. The findings indicated pronounced seasonal fluctuations in cyanobacterial blooms, with higher levels in summer than in other seasons. Key determinants for cyanobacterial blooms prediction included solar radiation, temperature and total nitrogen for Lake Hongze, while for Lake Luoma, significant predictors were identified as temperature, water temperature, and solar radiation. Compared with traditional data preprocessing methods, PP-RF model has advantages in addressing multicollinearity. This study provides a feasible method for predicting cyanobacterial blooms in impounded lakes within inter-basin water transfer projects. By inputting region-specific data, this model could be applied broadly, contributing to against the adverse effects of cyanobacterial blooms and provide scientific guidance for the protection and management of aquatic ecosystems.

Lake Iriqui’s Remarkable Revival: Field Observations and a Google Earth Engine Analysis of Its Recovery After over Half a Century of Desiccation

In September 2024, following two rare storms, Lake Iriqui in southern Morocco experienced a remarkable revival after five decades of desiccation. Historically, the lake played an important role as one of the largest water bodies before the Sahara Desert, serving as a critical stopover in migratory routes for various bird species. Two field missions documented this event: the first confirmed the lake’s reappearance, while the second recorded the resurgence of the ecosystem and the return of migratory birds, last observed in the lake in 1968. The lake’s surface water extent, which had been completely dry, expanded dramatically, reaching over 80 km2 after the first storm and subsequently increasing to approximately 146 km2 following the second. This event has drawn considerable attention from international and national media. The revival was monitored using satellite imagery from Landsat 8 and 9 and Sentinel-2A, processed through Google Earth Engine (GEE), with the Normalized Difference Water Index (NDWI) applied to detect water presence. A time-series analysis revealed significant changes in the lake’s surface water extent following the rainfall. This study emphasizes the need for proactive support to preserve Lake Iriqui, aligning with sustainable development goals: SDG 15 (Life on Land) and SDG 8 (Decent Work and Economic Growth). These goals highlight the importance of sustainable water resource management, biodiversity conservation, and eco-tourism initiatives to benefit local communities.

Socio-hydrological analysis: a new approach in water resources management in western Iran.

Human consumption patterns have a significant impact on the amount of available water. However, the human effect on water resources is perceived to have been poorly studied. For the effective management of water resources, social and hydrological components should be studied. To fill this gap, the aim of this study was to investigate the socio-hydrological system of the Gavshan Dam in western Iran. Therefore, the qualitative method and root cause analysis (RCA) were used to investigate the causes of the imbalance between water consumption and water resources. Root cause analysis was used to investigate the perceptions of 87 farmers and extension experts from Kermanshah province in Iran. Participants were chosen using the snowball technique and interviewed using a semistructured questionnaire. The results showed that the ineffective administrative structure was the most important and fundamental cause of water management inefficiency, accounting for 48.49% of the total inefficiency. Furthermore, the community sensitivity component (1.34%) indicated that the socio-hydrological system in the studied basin is not fully understood and that network users are not concerned about water crisis and environmental degradation. Poor yield, low income of farmers, reduction of cultivated area, social instability, and lack of secondary agricultural jobs are the main reasons for mismanagement of water resources. Conceptualizing water challenges based on the socio-hydrology revealed by this study can help designers focus on the fundamental causes, discover opportunities for policy, and implement sustainable water management strategies.

Improving groundwater quality predictions in semi-arid regions using ensemble learning models.

Groundwater resources constitute one of the primary sources of freshwater in semi-arid and arid climates. Monitoring the groundwater quality is an essential component of environmental management. In this study, a comprehensive comparison was conducted to analyze the performance of nine ensembles and regular machine learning (ML) methods in predicting two water quality parameters including total dissolved solids (TDS) and pH, in an area with semi-arid climate conditions. The study area under consideration is an aquifer located in the Sirjan plain, Kerman, Iran. The developed models include standard multilayer perceptron neural network (MLPNN), classification and regression trees (CART), Chi-square automatic interaction detection (CHAID), and their ensemble versions in bagging (BG) and boosting (BT) ensemble structures. The analysis revealed that standard MLs yield comparable results in predicting TDS. The MLPNN, exhibiting a standard root mean square error (SRMSE) of 0.085, demonstrated superior accuracy in predicting TDS when contrasted with CART and CHAID models. Predicting pH poses a greater challenge for the models. Ensemble techniques significantly enhanced the accuracy of regular models. On average, the bagging and boosting techniques resulted in a 22.68% improvement in the accuracy of regular models, which represents a statistically significant enhancement. The boosting method, with an average SRMSE of 0.0602, is more accurate than bagging. Based on the results, the CHAID-BT with SRMSE of 0.0790 and CHAID-BG with SRMSE of 0.0330 are ranked the most accurate models for predicting TDS and pH, respectively. The performance of ensemble techniques in predicting TDS is more remarkable. In practical implementation, ensemble techniques can be considered an alternative method with high accuracy for sustainable water resources management in semi-arid regions, helping to address water shortages, climate change, water pollution, etc.

Assessment of environmental degradation and conservation in the Maracanã River Basin, eastern amazon

Coastal basins stand out for their continent-estuary interface and connection as corridors of mangrove forests. The Maracanã River Basin (MRB) represents this environment, holding various ecosystem services for the component municipalities, protected areas with highly sensitive environments and water demand, and potential for multiple water uses. The proposed aim was to identify areas of degradation and environmental conservation in the MRB using the Blueprint model as support for water resource management. The methodology involved the application of the Blueprint model in the MRB, based on land use and cover information, rainfall, and characterization of the ecological units. The results showed that the MRB basin predominantly exhibits the degradation and restoration/connectivity classes in the Annual Blueprint (ABP) and Dry Blueprint (DBP), respectively. On the other hand, the Rainy Blueprint (RBP) predominantly exhibits Environmental Integrity. Statistical tests showed significant differences between ABP-RBP and DBP-RBP, which can be explained by the fact that on an annual scale of analysis, Blueprint classes are more heterogeneous, with a tendency toward environmental integrity, and intermediate classes in the rainy period; in the dry period, restoration and connectivity and degradation classes predominate. The correlation analysis indicates that natural vegetation cover shows a significant correlation with annual precipitation, rainy and dry quarters. These results provide significant insight into understanding the dynamics of degradation and conservation areas, assisting decision-makers in the environmental planning of the basin. In addition, the climatic component showed a differential response on annual and seasonal scales, acting as a modulating agent of the indicators.

SUSTAINABLE WATER RESOURCE MANAGEMENT IN NIGERIA: CHALLENGES, INTEGRATED WATER RESOURCE MANAGEMENT IMPLEMENTATION, AND NATIONAL DEVELOPMENT

Water resource management is essential for societal advancement, as water supports various human activities, including domestic, agricultural, industrial, and recreational uses. In Nigeria, the challenges of managing water resources are exacerbated by uneven distribution, population growth, and inadequate infrastructure. Despite Nigeria's significant renewable freshwater resources, only 69% of the population has access to basic water services, highlighting the nation's inefficiencies in water governance. The Integrated Water Resources Management (IWRM) approach offers a framework to address these challenges by promoting sustainable water use, stakeholder involvement, and the protection of ecosystems. However, Nigeria's implementation of IWRM faces hurdles, such as weak governance, conflicting institutional interests, and insufficient stakeholder engagement. This study examines the historical and current state of water resource management in Nigeria, its impact on national development, and the potential benefits of adopting IWRM. It explores lessons learned from global IWRM practices and provides recommendations for improving water governance to achieve the SDGs, particularly SDG 6 (clean water and sanitation) and SDG 11 (sustainable cities and communities). Addressing these challenges will require stronger institutional frameworks, cost recovery mechanisms, and the integration of local insights with international best practices.

Study of Drinking Water Supply System (SPAM) regulations after the enactment of Law Number 6 Year 2023 About Job Creation

Abstract This study will outline the impacts of policy direction changes on the legal structure management of the Drinking Water Supply System (SPAM) and propose the regulatory concepts for the Drinking Water Supply System (SPAM) that should be implemented following the enforcement of Law Number 6 of 2023 concerning Job Creation. This research is a doctrinal legal study that focuses on examining the legal aspects of Water Supply and Sanitation for Rural and Urban Areas (SPAM) within the Job Creation Law, using a statutory approach and a conceptual approach. The legal materials required for this study include legal instruments and factual data regarding the regulation of SPAM management in the Job Creation Law, employing a triangulation method for the validity of the research materials. Research findings indicate that the policy of resentralisation of licensing in water resource management will lead to disharmony and inconsistency with the management of Drinking Water Supply Systems (SPAM) based on the concept of regional autonomy, which embodies the principle of State Control in the welfare state doctrine. When the direction of water resource management policy is not aligned with the spirit of decentralisation, it hinders the development of SPAM within the legal framework and management culture from a business entity perspective. Post the enactment of Law Number 6 of 2023, the management of water resources should be followed up with efforts to harmonise it with regulations concerning regional autonomy and technical rules related to the management of drinking water supply systems (SPAM). Considering that the concept of decentralisation embodies the fundamental principle of state control within the framework of a welfare state, the regulation of water resource management and SPAM following the implementation of the Job Creation Law must be designed in accordance with the decentralisation concept to meet the basic water needs relevant to regional characteristics.

The Sustainable Strategy of Desalination in Morocco Versus Water Export and Intergenerational Equity. Case Study: Virtual Water Balance of the Desalination Plant in Agadir

A transition in water resource management has been taking place in Morocco for some years. Whereas long before, the needs of all user sectors were met without difficulty. Certainly, without water no life is possible. In this vision, water sovereignty always takes precedence within Moroccan strategies. In the context of structural water stress, actions are multiplying across conventional water boundaries to meet the demands of the sectors that use this vital commodity, moving towards the blue economy. Desalination of seawater is a sustainable opportunity to be seized, despite the energy-intensive and costly process. Among other things, the phenomenon of exporting virtual water through agricultural goods watered from these desalinated marine waters, deserves a judicious reflection and patriotic decisions on the part of decision-makers, in a vision of equality between present and future generations.

Strategies for Increasing Rice Productivity in Lowland Rainfed Fields Environment-Friendly Systems

Abstract Indonesia’s efforts to increase rice production are driven by the goal of becoming the world’s food granary by 2045. Rainfed lowlands currently occupy 46% of all rice cultivation and hold the potential for expanding national rice production but encounter biophysical constraints and low rice productivity. Land management neglecting environmental sustainability threatens sustainable rice production. This study examines alternative technologies that can be applied to lowland rainfed paddy fields to increase productivity and environmental sustainability. This systematic literature review uses 40 references, 81% of which are primary journals related to rainfed agroecosystems, rice cultivation, and environmentally friendly systems. Research showed that efforts to advance rice productivity in rainfed fields were pursued through environmentally friendly technologies and optimization of land management, including using superior varieties, planting technology, timing of planting, water resource management, balanced fertilization, pest/disease control, and appropriate harvesting practices. Drought-adaptive varieties were the solution to increasing plant populations and shortening harvest time. Balanced organic and inorganic fertilization was also essential in managing rainfed lowland rice fields. Furthermore, the farmers’ active role, infrastructure, social, economic, and environmental support have encouraged environmentally friendly technological innovations to attain food self-sufficiency.

Ácido salicílico mitiga os danos causados pelo déficit hídrico em sorgo forrageiro

ABSTRACT The sorghum crop is considered one of the most important worldwide due to its versatility. However, water stress can be considered a significant threat to its yield. The search for products that mitigate water stress is a crucial area of research in agriculture and water resources management. Thus, the objective in this study was to evaluate the feasibility of using salicylic acid as a water stress attenuator in sorghum. The experiment was conducted in a screened environment in a randomized block design with a 4 × 2 factorial scheme, with four replicates. Four levels of water (40, 60, 80, and 100% of evapotranspiration) and two concentrations of salicylic acid (0 and 2.76 g L-1) were evaluated. Plant height, stem diameter, number of leaves, gas exchange, photosynthetic pigments, and chlorophyll a fluorescence were analyzed. Application of deficit irrigation depths reduced plant height, stem diameter, number of leaves, and total chlorophyll in sorghum. However, when these depths were associated with salicylic acid, it was observed that the damage was attenuated, especially in chlorophyll a and b. Furthermore, salicylic acid reduced leaf temperature and increased water use efficiency when applied alone. Thus, salicylic acid can be used to mitigate the effects of salt stress on sorghum plants.

Blue and Green Water Scarcity in the McKenzie Creek Watershed of the Great Lakes Basin

ABSTRACTClimate change and extreme weather events affect hydrology and water resources in catchments worldwide. This study analysed Blue Water (BW) and Green Water (GW) scarcity in the McKenzie Creek watershed in Ontario, Canada, and explored how changes in temperature and precipitation may impact water scarcity dynamics. The McKenzie Creek is the main water source for agricultural activities for the Six Nations of the Grand River reserve (the largest Indigenous community in Canada) and other non‐Indigenous communities in the watershed. Data from the water use surveys and streamflow simulations performed using the Coupled Groundwater and Surface‐Water Flow Model (GSFLOW) under the Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCP) scenarios 4.5 and 8.5, representing moderate and high greenhouse gas emissions and climate warming, respectively, were used to calculate BW and GW scarcity. Study results showed that BW scarcity may increase to ‘moderate’ levels if water users extract the maximum permitted water withdrawal allocation. This level of scarcity has the potential to cause ecological degradation and water quality issues in the watershed. GW scarcity will steadily increase throughout the 21st century due to climate warming with the western portion of the McKenzie Creek watershed projected to experience slightly higher levels of GW scarcity. This may cause users to withdraw more water resources, thereby decreasing BW available for downstream communities, including the Six Nations of the Grand River. This study provides water resource managers and regional planners with important information about potential challenges facing the watershed due to increased water use and changing climate conditions.

Application of High-Performance Building Technologies in Green Building Practices

This paper comprehensively discusses the application of high-performance building technologies in green buildings and their economic implications. The study reveals that by adopting high-performance building technologies such as energy efficiency technologies, water resource management, sustainable material selection, waste management, and indoor environmental quality control, the environmental and economic benefits of buildings can be significantly enhanced. Although the initial investment cost is high, the long-term energy savings and environmental benefits prove the cost-effectiveness of these technologies. Policy incentives, market education, and professional training are crucial for promoting the application of high-performance building technologies. The paper also identifies challenges in implementation and proposes targeted policy recommendations and practical guidance. Finally, the study points out research limitations and suggests future research directions, aiming to promote the widespread adoption and implementation of green buildings to achieve sustainable development in the construction industry.

Revisiting water resources management in the Mandara Mountains.

This article evaluates the prospects for rainwater harvesting (RWH) as a means of optimizing water management in the Mandara Mountains. RWH is a small-scale water conservation approach for locally intercepting and storing rainfall before it enters the usual hydrologic cycle. This ancient practice has recently sustained lives in semiarid areas of the world (e.g. Brazil, China), but is not yet really used in the Mandara Mountains of Cameroon where people are still lacking safe drinking water. Recently, RWH was also demonstrated as the missing puzzle in integrated water resources management (IWRM) not only in areas facing water scarcity. The present article aims to prepare large scale RWH in the Mandara Mountains. Water harvesting yields are estimated for residential roofs, administrative and confessional buildings, and agricultural areas (e.g. farm scale). The results show that RWH is an affordable, applicable, and attractive tool for both rural and urban communities to sustainably solve the long-lasting problem of lack of safe drinking water in the Mandara Mountains. Moreover, despite the short rainy season, RWH may provide enough irrigation water to mitigate dry spells and increase agricultural and livestock productivity. This study is regarded as a blueprint for planning sustainable water management in the Mandara Mountains.

Satellite-Driven Hydrological Modelling in Ungauged Moroccan bassins: Case study Ouzoud river

Predicting streamflow is vital for flash-flood early warning systems and managing water resources under climate change. However, limited streamflow observations restrict advanced prediction techniques to gauged basins, leaving most of the world's ungauged basins at a disadvantage. Developing reliable prediction methods for ungauged basins (PUB) is therefore essential. Over the past two decades, satellite-driven products, such as ERA5, have become crucial for enhancing precipitation and meteorological measurements, especially in complex terrains and changing climatic conditions. This study focuses on Morocco's arid and semi-arid regions, where water resource management is critical for agriculture, urbanization, and economic stability. Using the ERA5 dataset, which provides high-resolution atmospheric information, the study evaluates satellite-derived precipitation against ground measurements from the Sgatt station at Bernat River on daily timescales. Various statistical metrics assess ERA5's performance in representing daily precipitation and its integration into the GR4J-CemaNeige model for flow simulation. Results highlight the potential of ERA5 in improving rainfall representation and hydrological modelling in ungauged basins, verifying its effectiveness in simulating rainfall events compared to ground-based observations. This work underscores the importance of satellite-driven products for enhancing hydrological predictions and supporting water management in data-scarce regions.

Coupling SAR and optical remote sensing data for soil moisture retrieval over dense vegetation covered areas.

Soil moisture is a key parameter for the exchange of substance and energy at the land-air interface, timely and accurate acquisition of soil moisture is of great significance for drought monitoring, water resource management, and crop yield estimation. Synthetic aperture radar (SAR) is sensitive to soil moisture, but the effects of vegetation on SAR signals poses challenges for soil moisture retrieval in areas covered with vegetation. In this study, based on Sentinel-1 SAR and Sentinel-2 optical remote sensing data, a coupling approach was employed to retrieval surface soil moisture over dense vegetated areas. Different vegetation indices were extracted from Sentinel-2 data to establish the vegetation water content (VWC) estimation model, which was integrated with the Water Cloud Model (WCM) to distinguish the contribution of vegetation layer and soil layer to SAR backscattering signals. Subsequently, the Oh model and the Look-Up Table (LUT) algorithm were used for soil moisture retrieval, and the accuracy of the result was compared with the traditional direct retrieval method. The results indicate that, for densely vegetated surfaces, VWC can be better reflected by multiple vegetation indices including NDVI, NDWI2, NDGI and FVI, the R2 and RMSE of VWC estimation result is 0.709 and 0.30 kg·m-2. After vegetation correction, the correlation coefficient increased from 0.659 to 0.802 for the VV polarization, and from 0.398 to 0.509 for the VH polarization. Satisfactory accuracy of soil moisture retrieval result was obtained with the Oh model and the LUT algorithm, VV polarization is found to be more suitable for soil moisture retrieval compared to VH polarization, with an R2 of 0.672 and an RMSE of 0.048m3·m-3, the accuracy is higher than that of the direct retrieval method. The results of the study preliminarily verified the feasibility of the coupling method in soil moisture retrieval over densely veg etated surfaces.