Water Resources Management Strategies Research Articles

‘Water resource’ framing for the value and governance of glacier water availability in the semi-arid Chilean Andes

Water scarcity associated with glacier retreat in mountainous regions is of growing concern worldwide, especially in arid regions, where precipitation is scarce or seasonal. Scientists and decision makers aim to respond to glacier driven water scarcity by improving glacier protection and developing water resource management strategies. Despite the increasingly prominent ‘water resource’ lens for understanding the changing mountain cryosphere, little research has investigated what this framing means for how different actors value, study, manage, and protect cryospheric water stores. This paper therefore presents a critical analysis of how we conceptualise the importance of glaciers. Specifically, this paper examines how environmental campaigns, scientific research, and policy interact to make glaciers into a water resource, and how this impacts glacier protection. Focusing on a case study of glacier management and protection in the Chilean Andes, the motivations and processes that made glaciers into a water resource in Chile are examined, and the impacts of this for glacier protection in a country where glaciers are exposed to threats from climate change and the mining industry are explored. This paper presents qualitative analysis of interviews conducted with experts in glacier science, policy, and environmental campaigning, and documents associated with managing glaciers as a water resource in Chile. The research shows how, in response to mining threats, glaciers were strategically framed as water resources by environmental campaigners to improve Chilean state protection. This framing was institutionalised within Chile’s water resource management system through science and policy, resulting in some successful protection legislation. However, this resource framing has also integrated glaciers into a system which inherently limits their protection, because their protection is conditional on the shifting ways glaciers are valued for storing and releasing water to downstream communities and ecosystems. Here, we highlight processes that make glaciers into a resource, demonstrate that glaciological knowledge is not directly translated into policy, and importantly, show how managing glaciers as a resource may limit, or even undermine glacier protection efforts. As concern globally grows about water scarcity driven by glacial retreat, these findings are vital for the development of glacier protections and effective management of glacial water.

A sustainable environment requires sustainable water—a review of some water issues to learn from

Water sustainability has become one of the most severe issues in the 21st century due to urban population growth and climate change. This paper reviews some of the critical key water issues that need to be considered in the quest for water sustainability for the upcoming decades. The purpose is to recognize the critical circumstances for maintaining water sustainability and send warning signals for regions that have passed the “tipping point” of balancing their water sustainability, while failing to realize restoring sustainability will be extremely difficult. Examples are used to demonstrate situations which, in hindsight, have been initially shown to be effective but highly problematic in the long term. This review considers, amongst others, the example of 1960s India, which shows that an agricultural “success” that started in the 1960s has subsequently become an environmental disaster. Additional issues, including the impacts of dietary adjustments, upstream diversions raising downstream shortfalls, and water transfers from agriculture to urban areas, are used as examples. They demonstrate that lessons must be learned from the past to achieve water sustainability, and adaptive measures must be adopted to help humanity avoid irreversible environmental tragedies. This paper highlights the urgent need for policymakers and stakeholders to proactively promote better water resource management strategies, domestic/international collaborations, and strict water use practice regulations, all of which will contribute to water sustainability and management plans.

Hydrochemical and Isotopic Characterization of Groundwater in the Nakivale Sub-Catchment of the Transboundary Lake Victoria Basin, Uganda

This study characterized groundwater resources for the Nakivale sub-catchment of the transboundary Victoria Basin in Uganda using classical hydrochemical and stable isotopic approaches. Groundwater in the study area is essential for domestic, agricultural, and industrial uses. As a sub-domain of the larger Victoria Basin, it also plays a crucial role in shaping the hydrological characteristics of this vital transboundary basin, both in terms of quality and quantity fronts. This makes its sustainable management and development vital. The predominant groundwater type is Ca-SO4, with other types including Ca-HCO3, Na-Cl, Na-HCO3, and Ca-Mg-SO4-Cl. Hydrochemical facies analysis highlights the importance of rock–water interactions in controlling groundwater chemistry, mainly through incongruent chemical weathering of Ca-rich plagioclase feldspars and the oxidation of sulfide minerals, such as pyrite, which are prevalent in the study area. Groundwater recharge is primarily influenced by the area’s topography, with recharge zones characterized by lineament networks, located in elevated areas. Stable isotope analyses indicate that groundwater mainly originates from local precipitation, while tritium data suggest the presence of both recent and older groundwater (likely over 20 years old). The study’s comprehensive approach and findings contribute significantly to the understanding of groundwater systems in the region, thus providing valuable insights for policymakers and stakeholders involved in water resource management and development strategies.

Spatiotemporal Variations and Driving Factors of Water Availability in the Arid and Semiarid Regions of Northern China

It is anticipated that global warming will modify precipitation and evapotranspiration patterns, consequently affecting water availability. Changes in water availability pose challenges to freshwater supply, food security, and ecosystem sustainability. However, the variations and driving mechanisms of water availability in the arid and semiarid regions of Northern China remain unclear. This study evaluates the accuracy of three evapotranspiration products and analyzes the changes in water availability in the arid and semiarid regions of Northern China over the past 39 years (1982–2020) along with their driving factors. The results indicate that during this period, precipitation increased at a rate of 7.5 mm/decade, while evapotranspiration rose at a higher rate of 13 mm/decade, resulting in a decline in water availability of 5.5 mm/decade. Spatially, approximately 30.17% of the area exhibited a significant downward trend in water availability, while 65.65% remained relatively stable. Evapotranspiration is the dominant factor leading to the decrease in water availability, with a contribution rate of 63.41%. The increase in evapotranspiration was primarily driven by temperature (32.53% contribution) and the saturation vapor pressure deficit (24.72% contribution). The decline in water availability may further exacerbate drought risks in arid and semiarid regions. The research results can provide a scientific basis for developing water resource management strategies and ecological restoration strategies under environmental change.

Public complaints of water pollution: A long-term spatiotemporal analysis in Japan

Public complaints about water pollution are important indicators of public environmental risk perception and provide crucial feedback for evaluating the effectiveness of water resource management strategies. This study conducts a comprehensive analysis of water pollution complaints in Japan from 1989 to 2021, utilizing integrated datasets that include river networks, water quality monitoring stations, regional industrial demographics, and socioeconomic indicators. Our findings reveal a significant decline in complaints—over 45% from the peak in 2006—following the implementation of various environmental policies aimed at reducing industrial discharge and restoring natural ecosystem function. The shift in complaint targets from industries to individuals suggests that these policies have been effective in mitigating industrial pollution, while also highlighting the need to address individual behaviors that impact water quality. Despite long-term improvement in water quality indicators such as Suspended Solids (SS) and Dissolved Oxygen (DO), no significant correlation was observed between these indicators and the temporal or spatial patterns of water pollution complaints. Instead, a strong positive correlation was observed between complaints and reported water quality incidents, reflecting heightened public sensitivity to acute pollution events. Spatial analysis further identified a significant association between complaints and the manufacturing workforce, indicating that industrial activity continues to shape public perception of water pollution risks. Our findings underscore the complex interaction between public perception, environmental policies, and industrial activities, and suggest that effective water management requires a multifaceted approach. Policymakers should continue to enforce stringent industrial regulations, while also enhancing public education and communication strategies to improve awareness of individual responsibilities in water protection. This research provides a theoretical basis for developing more responsive and effective environmental policies and public education strategies.

Analysis of future water demands in Al-Madinah (1990–2030) based on the modified IPAT model and sheared socio-economic pathways scenarios

Arid regions such as Saudi Arabia are facing water scarcity and availability issues and experiencing growing pressure by rapid water consumption. Determining the main driving forces contributing to rising water demands and future water demand prediction are considered the cornerstone for developing a good sustainable management plan. Al-Madinah city was chosen as a case study. In this study, the population, affluence, and technology (IPAT) model has been modified to apply in the water sector to analyse water needs in Al-Madinah from 1990 to 2020 and examines factors including population, GDP-per capita, agricultural lands/GDP and built-up area/agricultural lands. In addition, Sheared Socio-economic Scenarios (SSPs) have been developed to predict water demands in Al-Madinah from 2020 to 2030. The results confirm that population was the most important in explaining water consumption trends. Moreover, water demand under all IPCC_ SSP scenarios is expected to increase by between 17 to 28%. The scenarios of SSP3 and SSP4 are projected to experience an increase in water demands by an average of 25% and 26%, respectively. In contrast, the water demand is forecasted to lower under the SSP1 and SSP5 by around 20% and 17%, respectively. This evaluation could highly reinforce and improve sustainable water resource management strategies, which have recently become increasingly essential to face growing water challenges and demands.

General Features of the Libyan Strategy for Water Resource Management

General Features of the Libyan Strategy for Water Resource Management

Assessment of catchment water resources allocation under climate change in Luwombwa sub-catchment, Zambia

The uncertainty in climate change and high water demand pose pressure on the natural water resources supply. Not only does this require better understanding but also a call for immediate interventions, mitigation and adaptive measures. This study evaluates catchment water resources in the Luwombwa sub-catchment in Zambia through statistical analysis in the downscaling of past, present and future climatic variables from the CMIP6 climatic model. These variables are then integrated into WEAP - a semi-distributed hydrological and water evaluation model - to perform water demand and allocation scenario modelling. Mult-site calibration and validation were conducted on five selected micro-catchments within Luwombwa sub-catchment. The model performance was assessed usng the R2, NSE and PBIAS as the objective functions. Satisfactory values of 92 % for R2, 82 % for NSE and 6.9 % for PBIAS were achieved. This allowed for scenario modelling on water demand and allocation among competing users. Three future scenarios (2022–2050) were developed from the historical to baseline (1988–2022) and included state of water resources availability under climate change, expansion of irrigation area and impact of dam construction in the sub-catchment. The study reveals a decrease of 20 % in sub-catchment's water availability resulting from 9.3 % (equivalent to 4oC) rise in maximum temperature and 4.5 % reduction in rainfall within the entire sub-catchment. This is especially under the persistence of SSP370 climate variability scenario projections downscaled from four GCM models by the year 2050. The study further revealed that the change point for anticipated future climate extremes is likely to occur between 2027 and 2030. The results are indicative of downward trends in streamflow under climate change and socioeconomic development leading to increase in water value and water scarcity. The insights from the study are critical to inform formulation of effective catchment water resources management strategies such as the development of management plans and adapation measures in the face of climate change and the needs for different stakeholders involvement.

Spatial and temporal variations of dug well water quality in Korba basin, Chhattisgarh, India: Insights into hydrogeological characteristics

Comprehensive assessment of groundwater quality in mining-affected regions is crucial to sustainably manage water resources and protect public health and ecosystems. This study investigated the hydrogeochemical characteristics and water quality of 18 dug wells in the Korba basin, Chhattisgarh, India, an area heavily impacted by coal mining activities. Water samples were collected over three seasons (pre-monsoon, monsoon, and post-monsoon) and analyzed to determine physicochemical parameters, major ions, trace elements, and carbon content. Results revealed very high total dissolved solids concentrations ranging from 315 to 19,738 mg L−1. Nitrate levels surpassed the Bureau of Indian Standard (BIS) limit of 45 mg L−1 in over 50% of samples, reaching a maximum of 200 mg L−1. Fluoride concentrations in all samples exceeded the BIS limit (1.5 mg L−1), ranging from 1.5 to 15.2 mg L−1. The predominant water type was Ca-Mg-HCO₃, primarily influenced by rock-water interactions. Factor analysis indicated that both geogenic and anthropogenic processes influence pollution levels. Pollutant concentrations exhibited seasonal variations, generally peaking during the monsoon period. Temporal analysis from over six years revealed increasing trends for most parameters, indicating deteriorating water quality. Based on Water Quality Index values, all samples were classified as unsuitable for drinking, while assessments of irrigation water quality using various indices indicated that 61.11% of samples were suitable for agricultural use. The findings provide data to inform decision-making and public health protection in this heavily industrialized region and emphasize the urgent need for sustainable water resource management and pollution prevention strategies in the Korba basin to align with UN Sustainable Development Goals 3 (good health and well-being) and 6 (clean water and sanitation).

Advanced streamflow forecasting for Central European Rivers: The Cutting-Edge Kolmogorov-Arnold networks compared to Transformers

Accurate streamflow forecasting is crucial for effective water resource management, flood mitigation, and maintaining ecological balance, especially in Central Europe’s major rivers. This study investigates the performance of two advanced deep learning algorithms—Kolmogorov-Arnold Network (KAN) and Transformers—using long-term hydrological data from four key rivers: the Rhine, Danube, Elbe, and Oder. These rivers, characterized by varying flow regimes and significant human and climatic impacts, serve as vital arteries for both commerce and ecosystems.The dataset comprises historical daily streamflow data, alongside derived input parameters such as moving averages and flow rate changes, used to predict short-term (1 to 7 days) river discharges. The KAN model, leveraging learnable spline-based activation functions, was developed to enhance accuracy and interpretability in capturing complex hydrological patterns. In contrast, the Transformer model uses advanced attention mechanisms, which excel in handling sequential data with long-range dependencies.Results show that the KAN model significantly outperforms the Transformer in short-term forecasts (up to 3 days). For 1-day forecasts, the KAN achieved R2 values of 0.975 for the Rhine, 0.956 for the Danube, 0.992 for the Elbe, and 0.969 for the Oder, with MAPE values ranging from 3.20 % to 8.09 %. At the 3-day horizon, the KAN’s R2 values remained high, demonstrating its robustness. However, as the forecasting horizon extends to 7 days, the performance of both models converges.These findings underscore the methodological novelty of KAN, which provides enhanced short-term predictive capabilities compared to existing methods, offering valuable insights for improving water resource management strategies in complex hydrological settings.

Development of a water resources utilization model and optimization of the patterns of rice genotypes with system dynamics approach

The system dynamics approach was conducted to optimize genotype patterns in various climatic and water availability scenarios, to address the water productivity improvement of the Sefidrood irrigation network. The studied cropping pattern scenarios were SD1 (the continuation of current trends), SD2 (the reduction in the cultivated area), SD3 (replacing modified crops on an annual basis), and SD4 (increasing the annual cultivated area of Hashemi type rice). Moreover, the impacts of irrigation efficiency improvements and water resources management strategies on the physical and economic water productivity indices were studied. The results indicated that the SD3 scenario has the most positive impact on water productivity with 0.45 kg/m3 increases. However, a questionnaire survey revealed that this scenario that belongs to the increase in the modified genotype area cannot be recommended due to cooking quality and low prices. The Hashemi genotype was the favorite rice among farmers and experts. Also, analyzing the irrigation efficiency improvement scenario showed that this strategy has a limited impact on the physical and economic water productivity. Increasing the capacity of local rainwater storage pools, Ab-bandans, and increasing the drainage water reuse had the highest water productivity in the condition of river water reduction and uncertain water availability.

Reassessing water resource challenges in a changing climate in the Kagera transboundary river basin, Tanzania

The dynamic shifts in climatic patterns, particularly alterations in precipitation, have significantly impacted water resource availability and accessibility. These climate-induced changes affect hydrological processes, encompassing runoff, groundwater replenishment, water demand, and biophysical patterns within river basins. This study seeks to unravel the multifaceted implications encountered and challenges in water resource management within the river basin. It employed a survey-based approach for data collection, including Key informant interviews (KI), consultation methods and documentary reviews. The study utilized Statistical Package for the Social Sciences (SPSS) and Microsoft Excel for quantitative analysis and thematic synthesis for qualitative insights, including local community perspectives. The findings reveal substantial fluctuations in precipitation, protracted droughts, severe flooding, and other climatic extremes. The observed annual mean rainfall of 832 mm, with a standard deviation of 248, a standard error of 361, and a skewness of −945, accentuates the pronounced variability in mean precipitation, exhibiting a declining trend indicative of climatic shifts (R2 = 0.1797 and P = 0.002). The challenges are limited access to hydrological and meteorological data, undermining prediction accuracy, infrastructure planning, and response strategies for water resource allocation and management. The absence of unified approaches, influenced by the politics of riparian states, feeble coordination, conflicting sectoral policies, and ambiguous priorities, hinders effective transboundary water resource management. The study addresses these complexities and advocates for institutionalizing robust water management strategies that capitalize on existing resources and foster innovative capacities among critical stakeholders. Central to these efforts is harmonizing and enforcing policies, regulations, and laws governing water use, coupled with a concerted focus on inclusive governance to ensure the sustainability of water resource management. Such effort entails synchronized strategies, programs, plans, and livelihood practices underpinned by active stakeholder involvement in pivotal facets of water resources management.

Rainwater Harvest with Desert-Sand Bricks: An Adaptive Water Resources Management Strategy for Climate Change

Rainwater Harvest with Desert-Sand Bricks: An Adaptive Water Resources Management Strategy for Climate Change

Assessment and Modeling of Water Quality in the Niger River: A Comprehensive Study Using Water Quality Indices and Intelligent Techniques

The Niger River is essential to the livelihoods of those in Bamako and its neighboring areas, providing vital resources for drinking water, agriculture, livestock, industry, and fishing. Given its significance across these sectors, there is a pressing need to establish an effective water resource management strategy that incorporates a thorough qualitative assessment of the river's water quality. This research seeks to characterize the water quality of the Niger River by employing Water Quality Indices (WQI) and intelligent modeling techniques. To fulfil this objective, various physicochemical parameters, including pH, electrical conductivity (EC), nitrate (NO3-), nitrite (NO2-), and iron (Fe), were collected from 40 sampling points along the river during three distinct periods: December 2017, March 2018, and July 2018. The study utilized a weighted arithmetic approach to compute the WQIs, while the predictive models were developed using two of the most famous and effective modeling techniques namely Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN). In order to evaluate the predictive performance of the models, the dataset was partitioned into three distinct segments, allocating 60% for training purposes, 20% for validation, and the remaining 20% for testing, with the segments organized in a sequence from upstream to downstream. The performance of both models was evaluated using metrics such as the correlation coefficient (r²), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The computed Water Quality Indices (WQIs) vary from 0.44 to 1887.40, indicating a diverse range of water quality across the samples analyzed. The classification of these samples reveals that 62.5% are considered excellent, while 15% are categorized as good, another 15% as poor, 2.5% as very poor, and 5% as unsuitable for consumption. Furthermore, the results derived from ANN with five inputs, one hidden layer (13 neurons) and one output (WQI) demonstrates superior efficiency in assessing water quality.

The Impact of Digital Technology on Water Resources Management: Evidence from China

Digital technology is gradually emerging as a new driving force in the field of water resources management. In this paper, we conduct a thorough analysis of panel data from 30 provinces in China spanning from 2013 to 2022. Utilizing the fixed-effects model, the mediation effect model, a panel threshold model, and a coupling coordination degree model, this study empirically examines the impact of digital technology on water resources management. The findings are as follows: (1) The direct impact of digital technology on water resources management is significantly positive at the 1% level, with notable regional variations. (2) Digital technology improves water management through green innovation. (3) In the process of digital technology promoting water resources management, green innovation exhibits a threshold effect, with an estimated threshold value of 1.840. (4) During the sample period, the national coupling coordination degree of digital technology and water resources management was barely coordinated, showing the following characteristics: Eastern China > Western China > Central China. These research conclusions will offer valuable insights and directions for advancing sustainable water resources management strategies and fostering the deep integration of digital technology and water resources management.

Spatial data modelling of atmospheric water availability and stress in Jharkhand, India

Due to climate and human activity, water supply in Jharkhand, India, fluctuates. This study measured AWS and AWA in Jharkhand, India. MODIS NDVI and Terra Climate data processed by Google Earth Engine (GEE) are used in the analysis. Based on mean annual values for NDWI, run-off, precipitation, and ET, AWS and AWA are categorised. Results show significant regional differences in ET, precipitation, runoff, AWS, and AWA in Jharkhand. Purbi Singhbhum has far higher ET rates than Garhwa, Palamu, and Chatra. High AWS levels in Sahibganj, Godda, Pakur, Garhwa, and Kodarma indicate serious water scarcity. Therefore, these locations need focused water management approaches. Different districts including Giridih, Chatra, Jamtara, Latehar, Simdega, and Hazaribagh have different levels of AWS, highlighting the need for individualised treatments. The AWA index helps resource managers make educated decisions by detecting water-scarce places. Climate variability affects temperatures and precipitation, worsening AWS in high-AWS areas. Water scarcity mitigation requires local infrastructure development and water management measures. To verify remote sensing data accuracy, future study should improve data resolution and include in-situ measurements. These findings can help policymakers and stakeholders in Jharkhand create efficient water resource management strategies to reduce water stress and assure water supply.

Monitoring of Vegetation Drought Index in Laibin City Based on Landsat Multispectral Remote Sensing Data

Due to the impact of global warming, drought has caused serious damage to China’s ecological environment and social status. This article selects Laibin City in the Guangxi Zhuang Autonomous Region as the research area, utilizing multispectral remote sensing data as the data source and Landsat series image data for relevant preprocessing. It calculates the monthly normalized vegetation index (NDVI) and surface temperature (LST) data for Laibin City. Based on the ecological environment and surface coverage conditions of the research area, the ratio vegetation index (RVI), normalized vegetation moisture index (NDWI), temperature vegetation drought index (TVDI), and conditional vegetation temperature drought index (VTCI) were selected to calculate and invert the drought monitoring results of Laibin City. The drought monitoring results were obtained and overlaid with the vegetation area map to generate the vegetation drought monitoring results of Laibin City. Based on the climate, geography, and ecological characteristics of the monitored area in Laibin City, a specific analysis will be conducted to develop an appropriate TVDI index drought level, and generate vegetation drought level result maps for Laibin City in 2021, 2022, and 2023. Then, a detailed analysis of the vegetation drought situation in Laibin City is conducted according to time and space. Among them, in the past three years, the vegetation areas in Laibin City have experienced drought seasons mostly in summer and autumn. The interannual drought is mainly mild drought, and the proportion of areas with mild drought shows a relatively stable trend. In conclusion, TVDI proves to be a valuable tool for monitoring vegetation drought in Laibin City, offering insights for efficient water resource management strategies.

Water resource management and policy evaluation in Middle Eastern countries: Achieving sustainable development goal 6

This study explores the challenges and management strategies of water resources in 15 Middle Eastern countries, framed within the context of Sustainable Development Goal 6 (SDG6). This study used 123 water resource policies in Middle Eastern countries as data and employed a pre-trained large language model based on RoBERTa, trained on the SNLI and MNLI datasets, to perform text classification tasks. In combination with the TF-IDF algorithm for keyword extraction, this approach is used to systematically evaluate and compare the water resource policies of these countries. The results reveal that the region faces significant water stress, exacerbated by high population growth, climate variability, and political instability. While countries like Kuwait and the UAE utilize advanced desalination technologies to mitigate water scarcity, policy gaps in sanitation and transboundary cooperation persist. Jordan's innovative partnerships for water resource management highlight the potential of collaborative frameworks to enhance regional water security. The findings suggest that comprehensive water management strategies, including technological innovation and public-private partnerships, are essential for addressing the region's pressing water challenges. This research contributes to understanding the complexities of water governance in arid regions and offers practical implications for policymakers aiming to achieve sustainable water resource management.

Variability of bio-optical properties of Sundarbans mangrove estuarine ecosystem using elemental analysis, Sentinel 3 OLCI imageries and neural network models

Coastal water bodies face significant contamination risks stemming from various factors, such as growing populations, rapid urban development, dam construction, heightened industrial operations (notably in ports), and increasing tourism activities. The release of untreated sewage from municipalities, industrial discharges, and various recreational and commercial activities along the coast significantly deteriorates water quality and presents a serious risk to marine ecosystems, food chains, and human health. Hence, continual monitoring of coastal water quality is essential for the ecological sustainability of marine and aquatic ecosystems. This study examines the spatiotemporal variability of optical characteristics within the Sundarbans estuary system, a transboundary ecosystem shared by India and Bangladesh. The study employs Sentinel-3 OLCI satellite data alongside in-situ measurements of critical water quality parameters, including chlorophyll-a (Chl-a), total suspended matter (TSM), and chromophoric dissolved organic matter (CDOM), collected from 100 sampling sites across the Sundarbans estuarine system during the pre-monsoon, monsoon, and post-monsoon periods of 2021 and 2022.This study employs the sophisticated C2RCC model, a machine learning-based neural network-driven approach recognized for its robustness and precision. It examines the various bio-optical properties in tropical estuarine environments. The C2RCC model addresses this challenge directly. This advanced processor, powered by neural network technology, effectively interprets the complex optical signals found in Case-2 waters, offering essential insights into their quality. The findings indicate the highest TSM levels during the pre-monsoon seasons of both years. Additionally, the estimated Chl-a concentrations indicated a rise during the monsoon season (0.03–4 mg m3), whereas the intensified pre-monsoon CDOM levels showed consistency across both years. The strong positive correlation observed between in-situ and satellite data, with an average R2 value ranging from 0.90 to 0.99, underscores the reliability of the high-resolution remote sensing approach. The study illustrates the efficacy of OLCI data in observing near-shore and coastal ecosystems, clearly exceeding conventional methods for evaluating Chl-a, TSM, and CDOM. This study underscores the potential of high spatial and spectral resolution of Sentinel-3 Ocean color data for effective monitoring and management of the complex estuarine ecosystem of the Sundarbans. The findings of this study provide important insights to inform the development of sustainable coastal water resource management strategies. Furthermore, the findings will be crucial in achieving Sustainable Development Goal 14, which focuses on life below water, particularly in the conservation and management of marine and coastal biodiversity.

Geo-spatial assessment of geomorphic characteristics of Swat Valley, Pakistan

Morphometric analysis is essential for understanding drainage networks and landform evolution, particularly in complex mountainous regions like the Swat Valley. Accurate characterization of these features aids in water resource management and mitigating climate-induced challenges. The study employed GIS and remote sensing technologies, utilizing SRTM-30m DEM data to perform a comprehensive morphometric and hypsometric analysis. Key morphometric parameters such as basin size, stream order, bifurcation ratio, drainage density, circularity ratio, and elongation ratio were calculated by using Whitebox tool. Additionally, three-dimensional parameters including basin relief, roughness number, ruggedness index, and slope were analyzed. Hypsometric analysis was conducted to examine area-elevation relationships, using empirical formulas and contour data. The basin was found to be irregularly shaped, with an elongation ratio of 6.97 and a circulatory ratio of 0.3091, indicating an elongated form. Flow accumulation data highlighted areas of rapid and moderate water flow. Hypsometric analysis showed that 14 sub-basins were in an erosional stage, 8 were mature, and the remainder were older and more resistant to erosion. The overall hypsometric integral (HI) of 0.406 reflects moderate elevation variation across the basin. The study provides critical insights into the geomorphometric controls of the Swat Valley's drainage system, contributing to improved water resource management strategies. Understanding morphometric and hypsometric characteristics is vital for adapting to climate-induced risks and safeguarding water resources in mountainous landscapes.