Management Of Freshwater Resources Research Articles

Clarity tubes as effective citizen science tools for monitoring wastewater treatment works and rivers.

Improved freshwater resource management requires the implementation of widespread, effective, and timely water quality monitoring. Conventional monitoring methods are often inhibited by financial, infrastructural, and human capacity limitations, especially in developing regions. This study aimed to validate the citizen-scientist-operated transparency or clarity tube (hereafter "clarity tube") for measuring water clarity as a proxy for total suspended solids (TSS) concentration, a critical quality metric in river systems and wastewater treatment works (WWTW) effluent in Southern Africa. Clarity tubes provided a relatively accurate and precise proxy for TSS in riverine lotic systems and WWTW effluent, revealing significant inverse log-linear relationships between clarity and TSS with r2 = 0.715 and 0.503, respectively. We demonstrate that clarity-derived estimates of TSS concentration (TSScde) can be used to estimate WWTW compliance with WWTW effluent TSS concentration regulations. The measurements can then be used to engage with WWTW management, potentially affecting WWTW performance. Overall, these findings demonstrate the usefulness of clarity tubes as low-cost, accessible, and easy-to-use citizen science tools for high spatial and temporal resolution water quality monitoring, not only in rivers in Southern Africa but also in WWTW effluent for estimating compliance, with strong global relevance to the sustainable development goals (SDGs). Integr Environ Assess Manag 2024;00:1-10. © 2024 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Sustainable management of freshwater resources in Ghana: an analysis of the perspectives of local residents

Sustainable management of freshwater resources in Ghana: an analysis of the perspectives of local residents

Monitoring the Industrial waste polluted stream - Integrated analytics and machine learning for water quality index assessment

The Water Quality Index (WQI) is a primary metric used to evaluate and categorize surface water quality which plays a crucial role in the management of fresh water resources. Machine Learning (ML) modeling offers potential insights into water quality index prediction. This study employed advanced ML models to get potential insights into the prediction of water quality index for the Aik-Stream, an industrially polluted natural water resource in Pakistan with 19 input water quality variables aligning them with surrounding land use and anthropogenic activities. Six machine learning algorithms, i.e. Adaptive Boosting (AdaBoost), K-Nearest Neighbors (K-NN), Gradient Boosting (GB), Random Forests (RF), Support Vector Regression (SVR), and Bayesian Regression (BR) were employed as benchmark models to predict the Water Quality Index (WQI) values of the polluted stream to achieve our objectives. For model calibration, 80% of the dataset was reserved for training, while 20% was set aside for testing. In our comparative analyses of predictive models for water quality index, the Gradient Boost (GB) model stood out the fittest for its precision, utilizing a combination of just seven parameters (chemical oxygen demand, total organic carbon, oil & grease, Ammonia- nitrogen, arsenic, nickel and zinc), surpassing other models by achieving better results in both training (R2 = 0.88, RMSE = 7.24) and testing (R2 = 0.85, RMSE = 8.67). Analyzing feature importance showed that all the selected variables, except for NO3 N, TDS and temperature had an impact on the accuracy of the models predictions. It is concluded that the application of machine learning to assess water quality in polluted environments enhances accuracy and facilitates real-time tracking, enabling proactive risk mitigations.

Recent advances in heavy metal/metalloid ion treatment from wastewater using nanocomposites and bionanocomposites

Wastewater remediation is of paramount importance for the water-stressed modern civilization from the perspective of sustainable development and the management of limited freshwater resources. Contaminants such as heavy metal and metalloid ions, toxic dyes, and pathogenic microbes present in the aquatic ecosystem have adverse effects not only on the environment but also on human health. Traditional wastewater remediation processes are costly, energy-consuming, and have less efficiency in removing pollutants from wastewater. Multi-phasic nanomaterials or nanocomposites have enormous potential for removing contaminants from water bodies. These materials have an enormous tunable surface area for interacting with the target toxicants and are extremely stable in the aquatic system, but they readily agglomerate. Many research groups have exploited biosorption, bioleaching, and bioprecipitation capacities of fungal hyphae for wastewater remediation. Recently, researchers have attempted to explore the synergistic effect of the bionanocomposite of fungal hyphae and nanomaterials for removing pollutants from wastewater. This bionanocomposite has already shown promise as a superior material for wastewater treatment and can easily be separated from the polluted water for reuse over several cycles. The bionanocomposite-mediated decontamination of water can lead to a total paradigm shift in wastewater management strategies.

Dominant nitrogen metabolisms of a warm, seasonally anoxic freshwater ecosystem revealed using genome resolved metatranscriptomics.

Nitrogen (N) availability is one of the principal drivers of primary productivity across aquatic ecosystems. However, the microbial communities and emergent metabolisms that govern N cycling in tropical lakes are both distinct from and poorly understood relative to those found in temperate lakes. This latitudinal difference is largely due to the warm (>20°C) temperatures of tropical lake anoxic hypolimnions (deepest portion of a stratified water column), which result in unique anaerobic metabolisms operating without the temperature constraints found in lakes at temperate latitudes. As such, tropical hypolimnions provide a platform for exploring microbial membership and functional diversity. To better understand N metabolism in warm anoxic waters, we combined measurements of geochemistry and water column thermophysical structure with genome-resolved metatranscriptomic analyses of the water column microbiome in Lake Yojoa, Honduras. We sampled above and below the oxycline in June 2021, when the water column was stratified, and again at the same depths and locations in January 2022, when the water column was mixed. We identified 335 different lineages and significantly different microbiome membership between seasons and, when stratified, between depths. Notably, nrfA (indicative of dissimilatory nitrate reduction to ammonium) was upregulated relative to other N metabolism genes in the June hypolimnion. This work highlights the taxonomic and functional diversity of microbial communities in warm and anoxic inland waters, providing insight into the contemporary microbial ecology of tropical ecosystems as well as inland waters at higher latitudes as water columns continue to warm in the face of global change.IMPORTANCEIn aquatic ecosystems where primary productivity is limited by nitrogen (N), whether continuously, seasonally, or in concert with additional nutrient limitations, increased inorganic N availability can reshape ecosystem structure and function, potentially resulting in eutrophication and even harmful algal blooms. Whereas microbial metabolic processes such as mineralization and dissimilatory nitrate reduction to ammonium increase inorganic N availability, denitrification removes bioavailable N from the ecosystem. Therefore, understanding these key microbial mechanisms is critical to the sustainable management and environmental stewardship of inland freshwater resources. This study identifies and characterizes these crucial metabolisms in a warm, seasonally anoxic ecosystem. Results are contextualized by an ecological understanding of the study system derived from a multi-year continuous monitoring effort. This unique data set is the first of its kind in this largely understudied ecosystem (tropical lakes) and also provides insight into microbiome function and associated taxa in warm, anoxic freshwaters.

Effects of urbanization and accessibility to sanitation services on water quality in urban streams in Uruguay.

The world's urban population is growing rapidly, and threatening natural ecosystems, especially streams. Urbanization leads to stream alterations, increased peak flow frequencies, and reduced water quality due to pollutants, morphological changes, and biodiversity loss, known as the urban stream syndrome. However, a shift towards recognizing urban streams as valuable natural systems is occurring, emphasizing green infrastructure and nature-based solutions. This study in Uruguay examined water quality in various watersheds with different urbanization levels and socio-environmental characteristics along a precipitation gradient. Using Geographic Information Systems (GIS) and in situ data, we assessed physicochemical parameters, generated territorial variables, and identified key predictors of water quality. We found that urbanization, particularly urban areas, paved areas, and populations without sanitation, significantly influenced water quality parameters. These factors explained over 50% of the variation in water quality indicators. However, the relationship between urbanization and water quality was non-linear, with abrupt declines after specific urban intensity thresholds. Our results illustrate that ensuring sanitation networks and managing green areas effectively are essential for preserving urban stream water quality. This research underscores the importance of interdisciplinary teams and localized data for informed freshwater resource management.

Standardized Precipitation Index for Metrological Drought Analysis In Kashmir Valley Of Jammu And Kashmir

Abstract: The term "drought" is multifaceted, with varying interpretations based on personal experiences. It is a natural disaster that is distinguished by a severe and ongoing precipitation deficit. The planning and management of freshwater resources as well as the forecasting of the arrival and intensity of droughts depend heavily on drought monitoring. A number of indices have been put forth over time to track and measure data related to droughts. The Standardized Precipitation index (SPI), which is based on the idea of probability, is the most commonly used index. The current study examines the possibility of analysing the temporal pattern and severity of drought in the Kashmir Valley (Jammu and Kashmir) using precipitation-based SPI. Utilizing the "DrinC" software application, the Indices were calculated. SPI values were calculated using monthly precipitation data for the IMD Srinagar 2003 to 2022. SPI series computations were carried out for short, moderate, and long time scales. Based on the data, the Kashmir region experienced four periods of moderate drought in the years 2007, 2009, 2012, and 2016. Additionally, there was no significant drought from 2003 to 2022. 2007 had the maximum intensity with an SPI value of -1.37 for a moderate drought.

A random forest approach to improve estimates of tributary nutrient loading

Estimating constituent loads from discrete water quality samples coupled with stream discharge measurements is critical for management of freshwater resources. Nutrient loads calculated based on discharge-concentration relationships form the basis of government nutrient load targets and scientific studies of the response of receiving waters to external loads. In this study, a new model is developed using random forests and applied to estimate concentrations and loads of total phosphorus, dissolved phosphorus, total nitrogen, and chloride, using data from 17 tributaries to Lake Champlain monitored from 1992 to 2021. I benchmark this model against one of the most widespread models currently used to estimate nutrient loads, Weighted Regressions on Time, Discharge, and Season (WRTDS). The random forest model outperformed both the base WRTDS model and an extension of the WRTDS model using Kalman filtering in the great majority of cases, likely due to the inclusion of rate-of-change in discharge and antecedent discharge over different leading windows as predictors, and to the flexibility of the random forest to model predictor-response relationships. The random forest also had useful visualization capabilities which provided important process insights. WRTDS remains a useful model for many applications, but this study represents a promising new approach for load estimation which can be applied easily to existing datasets, and which is easy to customize for different applications.

Impact of Reduced Fluvial Sediment Supply on Saltwater Intrusion in the Yangtze Estuary

AbstractA decline of the fluvial sediment supply leads to coastal erosion and land loss. However, the fluvial sediment load may influence not only coastal morphodynamics but also estuarine hydrodynamics and associated saltwater intrusion. Previous studies revealed that suspended sediments influence estuarine hydrodynamics through various flow–sediment interactions. In this contribution, we systematically investigate how changes in fluvial sediment load and other climate‐change‐induced environmental change influence estuarine hydrodynamics and sediment dynamics. For this purpose, we utilize a well‐calibrated fully coupled model in which hydrodynamics, saltwater intrusion, and sediment transport interact with each other, to explore saltwater intrusion in the Yangtze Estuary in response to a decline in the sediment load, modified discharge, and sea‐level rise. Model results suggest that a 70% decline in the suspended sediment load weakens the impact of sediments on salinity‐induced stratification and thereby reducing saltwater intrusion. Sea‐level rise or discharge peak reduction increases saltwater intrusion. However, a fully coupled model accounting for sediment effects predicts a much larger increase in saltwater intrusion compared to noncoupled models. Whether this effect is important depends on estuarine sediment concentrations and therefore the potential role of sediments should be carefully investigated before applying a noncoupled model. This work highlights not only the relevance of a suspended sediment decline but also the use of fully coupled models for predicting saltwater intrusion in turbid estuaries and has broad implications for freshwater resource management in turbid estuarine systems influenced by human interventions and climate change.

Changes in energy balance and total evaporation with age, and between two commercial forestry species in South Africa

Expansion of the area planted to eucalypts has been observed in the last two decades due to an improvement in markets for products from this tree species. This has raised concerns over the management of freshwater resources as other species are replaced by Eucalyptus, which has been shown to use more water than other commercial forestry species. The energy balance (EB) and total evaporation (ET) over Acacia mearnsii was previously monitored at the Two Streams research catchment, and the site harvested in 2018 with subsequent re-planting of E. dunnii. This presented an opportunity to measure the two-year-old E. dunnii (Edun2) EB and ET for comparison on the same site with the previously planted A. mearnsii with results from two-year-old A. mearnsii (Amear2) and six-year-old A. mearnsii (Amear6) crops. ET and EB measurements on Amear2 were obtained using a large aperture scintillometer, while eddy covariance was used for Amear6 and Edun2. Measurements were conducted in October 2007 to September 2008, October 2012 to September 2013 and October 2019 to September 2020 for Amear2, Amear6 and Edun2. The leaf area index (LAI) was measured using a LAI 2200 plant canopy analyser for all crops. The annual plantation water productivity (PWPWOOD) was calculated as a ratio of productive stand volume to ET for Amear2, Amear6 and Edun2. Results showed that latent energy fluxes dominated the EB in all crops for both summer and winter seasons, indicating a possibility that trees were not limited by plant available water in winter (dry season). The Edun2 and Amear2 annual ET was statistically (p > 0.05) similar, while ET of the younger crops (Amear2 and Edun2) was 12% greater than Amear6. High ET in Edun2 was caused by high LAI while Amear2 was caused by high transpiration per unit leaf area in young trees than in mature trees. Monthly crop factors were derived from FAO ETo and ET for all three crops, providing a convenient and transferable method of estimating ET from meteorological data over a large scale. The Edun2 PWPWOOD was greater than Amear2, while Amear6 was greater than both the young crops. This study provides insight into the total water-use by different species at different stages of growth at the same site. It is recommended that catchment water balance measurements be continued on the current E. dunnii crop for the full crop rotation to assess the long-term impact of E. dunnii on streamflow.

Water Management Education in the East African Region: A Review of the Challenges to Be Addressed

Increased urbanisation coupled with inadequate awareness of the public on the issue of freshwater resource management has affected the use and the availability of freshwater resources in urban areas of Uganda, Kenya, and Tanzania. Lake Victoria has been the clearest example, with the water level decreasing 0.005 m/year from 1993 to 2016 causing an overall drop of 0.115 m. In order to develop sustainable methods for addressing these issues, this paper critically reviews the different legal frameworks used in each country (Uganda, Kenya, and Tanzania) adopted to manage the water resources and identifies the challenges faced by each legal framework applied. It also analyses the education systems implemented within these three nations to educate students at various levels about water resources and identifies the challenges involved in each system. Finally, suggestions are made for future research to be conducted to obtain specific benefits for better management of water resources in East Africa.

Exploring machine learning algorithms for accurate water level forecasting in Muda river, Malaysia

Accurate water level prediction for both lake and river is essential for flood warning and freshwater resource management. In this study, three machine learning algorithms: multi-layer perceptron neural network (MLP-NN), long short-term memory neural network (LSTM) and extreme gradient boosting XGBoost were applied to develop water level forecasting models in Muda River, Malaysia. The models were developed using limited amount of daily water level and meteorological data from 2016 to 2018. Different input scenarios were tested to investigate the performance of the models. The results of the evaluation showed that the MLP model outperformed both the LSTM and the XGBoost models in predicting water levels, with an overall accuracy score of 0.871 compared to 0.865 for LSTM and 0.831 for XGBoost. No noticeable improvement has been achieved after incorporating meteorological data into the models. Even though the lowest reported performance was reported by the XGBoost, it is the faster of the three algorithms due to its advanced parallel processing capabilities and distributed computing architecture. In terms of different time horizons, the LSTM model was found to be more accurate than the MLP and XGBoost model when predicting 7 days ahead, demonstrating its superiority in capturing long-term dependencies. Therefore, it can be concluded that each ML model has its own merits and weaknesses, and the performance of different ML models differs on each case because these models depends largely on the quantity and quality of data available for the model training.

How best to incorporate conjunctive water management into international water law: legal amendment, instrument coupling, or new protocol adoption?

International water conventions—e.g., the 1997 United Nations Convention on the Non-Navigational Uses of International Watercourses—include positive but insufficient focus on groundwater and its interaction with surface water. As such, a growing body of literature has proposed modifications to existing frameworks to enable consideration to surface and groundwater and their interactions. While this literature places considerable focus on coupling and amending existing legal frameworks, elaboration and evaluation of a new protocol on conjunctive water management comprises a key gap. To fill this gap, this paper seeks to answer the following question: does formulation and adoption of a new “conjunctive” protocol provide more value than existing proposals centered around modifications to existing law? This paper seeks to compare benefits associated with current proposals to strengthen the international legal framework for management of surface–groundwater interaction, vis-a-vis adoption of a new protocol on conjunctive management of transboundary freshwaters. To do so, the authors use doctrinal legal methods to analyze the existing main instruments globally assessing the degree to which they consider key interlinkages between surface water and groundwater. Then, the paper examines the concept of conjunctive water management and deduces tenets that should be pursued in shared waters to achieve this objective. To identify the preferred option to support conjunctive water management in international water law, the paper explores the degree to which existing proposals vs a new protocol enable an embrace of these tenets of conjunctive water management. The paper finds that while a new protocol may add greater value in advancing conjunctive water management, multiple options can and should be concurrently pursued. In particular, the authors argue that new protocols to the existing treaties must be adopted in combination with the amendment of the Draft Articles on the Law of Transboundary Aquifers. Benefits of doing so include more effective management of transboundary freshwater resources that are interconnected hydrologically, a less fragmented and more consistent international water regime, and ultimately more benefits accruing to the populations and environmental goods dependent on shared water resources.

A Review on Challenges, Opportunities and Outlook of Water Sector Privatization for Sustainability and Water Scarcity Management

The sustainable use and management of freshwater resources is on the center of developmental debate and becoming a global challenge. The overall aim of this study is to document published literature in the field of water privatization, critically review them and to draw a conclusion about how private sector participation can contribute in the initiative of sustainability for freshwater. To accomplish the specific goal of this paper, review articles, research papers, mini-articles, book and reports of authorized organizations published from last 25 years were reviewed. Comparative advantages, problems, challenges and opportunities of private and public sector management in water resources were thoroughly analyzed. Based on those reviews, this study found that there is a mixed legacy in water privatization throughout the world which needs to be strongly regulated to fulfill the basic requirements of consumers in one side and for sustainable management of scarce freshwater resources in another side. Meanwhile, after careful analysis of various water delivery systems and case-studies managed by different agencies around the world, this paper postulates the pubic-private-partnership as an appropriate form of privatization in water which not only helps to increase the project efficiency but also improves the service delivery to end-users.

Changes of terrestrial water storage during 1981–2020 over China based on dynamic-machine learning model

A reliable estimation of long-term change in terrestrial water storage (TWS) is critical for a sustainable management of freshwater resources and infrastructures. Although the Gravity Recovery and Climate Experiment (GRACE) satellites provide unprecedented accurate TWS anomaly (TWSA) observation since 2002, the limited time span and the gaps between the GRACE and GRACE-Follow On datasets hinder their climatological applications. Here we apply LightGBM, a more accurate and efficient machine learning model, to merge the land surface model simulation, human activities, land properties, and establish a dynamic-machine learning model that can reasonably depict the impacts of climate variation and human interventions on TWSA. We apply the hybrid model to reconstruct the historical TWSA during 1981–2020 over China, which shows reliable results and is consistent with other independent datasets including drought index, TWS change based on water balance, and water withdrawal dataset. The reconstructed TWSA shows significant drier (wetter) trend in North (South) China during the past 40 years, while the TWS variability has increased over 60% regions. We find the change of TWSA is mainly attributed to the climate variation in humid regions, but the human interventions dominate the decline of TWSA in arid and semiarid areas, such as the Yellow and Hai river basins (contributing about 70%). Our findings imply the potential of using artificial intelligence to represent human interventions, which is still uncertain in physical models. Our physical-machine learning model can be applied in long-term prediction and projection of TWSA and its components as well.

Local Knowledge and Innovation: An Ethnographic Study of Fishing Technology in Banjar Regency's Freshwater Environment

The goal of this anthropological investigation is to examine how fishing technology innovation in Banjar Regency relates to local knowledge. Using ethnographic techniques, such as participant observation and semi-structured interviews, this study was carried out over the course of six months, from January 2022 to June 2022. Interviews were conducted with 30 people, including 20 fisherman, 5 fish traders, and 5 representatives of the local administration. Following that, the concepts were put into categories. The study's conclusions shed light on the nuanced interplay between conventional wisdom and cutting-edge fishing techniques and showed that local communities ought to be included in the management of freshwater resources. The study also emphasizes the value of striking a balance between profitability and sustainability in fishing methods and emphasizes the necessity for ongoing research and cooperation between government organizations, academics, and local people to overcome the difficulties of sustainable fishing methods. Overall, the results point to the necessity of integrating traditional knowledge into contemporary fishing methods for sustainable fisheries management, and show that excessive reliance on fishing equipment has led to the loss of fish populations and the degradation of the freshwater ecosystem.

Global scale analysis on the extent of river channel belts

Rivers form channel belts that encompass the area of the river channel and its associated levees, bars, splays and overbank landforms. The channel belt is critical for understanding the physical river evolution through time, predicting river behavior and management of freshwater resources. To date, there is no global-scale, quantitative study of the extent of river channel belts. Here we show, based on a pattern recognition algorithm, the global surface area of channel belts at an approximate 1 km resolution is 30.5 × 105 km2, seven times larger than the extent of river channels. We find 52% of river channels associated with the channel belts have a multi-threaded planform with the remaining 48% being single-threaded by surface area. The global channel belt (GCB) datasets provide new methods for high-resolution global scale landform classifications and for incorporating the channel belt into flood mitigation, freshwater budgets, ecosystem accounting and biogeochemical analyses.

Thirsty Islands and Water Inequality: The Impact of Colonial Practices on Freshwater Challenges in the Dutch Caribbean

Small Island Developing States (SIDS) and Territories in the Dutch Caribbean face unique water challenges related to climate change. With fragile ecosystems and surrounded by rising sea levels and limited natural resources, island communities are increasingly faced with the reality of life withextreme drought and floods. While Caribbean SIDS in general have limited freshwater resources and limited water-retaining capacity due to natural characteristics, it is undeniable that unsustainable actions, practices and attitudes under colonial rule, such as deforestation and “property-thinking,” have contributed to present-day environmental degradation, freshwater resource management problems and water inequality. In the Netherlands, there are ongoing discussions about reparative justice compensation for the impact of Dutch colonial imperialism. In this light, it is worth considering whether reparative justice for the former colonial territories could take the form of eco- and heritage- system reparations and substantial investments in nature- and heritage-based solutions.

Risk evaluation and prioritization of contaminants of emerging concern and other organic micropollutants in two river basins of central Argentina

A research gap exists in baseline concentrations of organic micropollutants in South American rivers. Identification of areas with different degrees of contamination and risk to the inhabitant biota is needed to improve management of freshwater resources. Here we inform the incidence and ecological risk assessment (ERA) of current used pesticides (CUPs), pharmaceutical and personal care products (PPCPs) and cyanotoxins (CTX) measured in two river basins from central Argentina (South America). Risk Quotients approach was used for ERA differentiating wet and dry seasons. High risk was associated to CUPs in both basins (45 % and 30 % of sites from Suquía and Ctalamochita rivers, respectively), mostly in the basins extremes. Main contributors to risk in water were insecticides and herbicides in Suquía river and insecticides and fungicides in Ctalamochita river. In Suquía river sediments, a very high risk was observed in the lower basin, mainly from AMPA contribution. Additionally, 36 % of the sites showed very high risk of PCPPs in Suquía river water, with the highest risk downstream the wastewater treatment plant of Córdoba city. Main contribution was from a psychiatric drug and analgesics. In sediments medium risk was observed at the same places with antibiotics and psychiatrics as main contributors. Few data of PPCPs are available in the Ctalamochita river. The risk in water was low, with one site (downstream Santa Rosa de Calamuchita town) presenting moderated risk caused by an antibiotic. CTX represented in general medium risk in San Roque reservoir, with San Antonio river mouth and the dam exit showing high risk during the wet season. The main contributor was microcystin-LR. Priority chemicals for monitoring or further management include two CUPs, two PPCPs, and one CTX, demonstrating a significant input of pollutants to water ecosystems from different sources and the need to include organic micropollutants in current and future monitoring.

Future water security under climate change: a perspective of the Grand River Watershed

Abstract Climate change poses a threat to the water security of the Grand River Watershed (GRW) by altering the precipitation patterns and other weather variables, which affect streamflow and freshwater availability. Therefore, in this study, a Soil and Water Assessment Tool (SWAT) model for the GRW, Ontario, Canada, was used to assess the blue and green water scarcity for future periods for future sustainable management of freshwater resources in the region. The ensemble results predicted a warmer and wetter future for the GRW. The ensemble model result, when considering both emission scenarios and future periods, showed that blue water (BW) is projected to increase by 23–40% while green water storage (GWS) is projected to experience an overall decrease (2–8%). The results suggested that BW may become more scarce compared to green water in the future. The scarcity of BW is primarily due to the projected increase in population growth and water demand in the watershed. Green water scarcity in some regions indicated that changes in irrigation might be needed in the future in some parts of the watershed. The results indicate that the careful planning is essential for future water management in GRW.