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The UnCommons Project, as the name implies, introduces an alternative building model to traditional inefficient and environmentally destructive building stock, making it a beacon of sustainability. This state-of-the-art structure is a localized, bio-based structure reflecting concentric rings of impact from the site level, to regional, and to liberating materials from global supply chain constraints. This project’s approach integrates restorative renewable resources, water harvesting, recycling, and conservation measures to minimize its footprints. This 1,000 square foot structure, serving as a student common area at UCI, showcases high-tech, low-impact sustainable solutions through the seamless integration of AI for temperature regulation, structural wall-adjustments, and predictive maintenance systems. Given its proximity to the UCI Ecological Preserve, this structure aims to augment local biodiversity, cultivate ecological resilience, and enable students to blend with and foster an enhanced coexistence with nature. The UnCommons Project envisions buildings as living structures that harmonize with their environment.Industry Advisors: James Bucknam, Brett Kaufmann

Water scarcity and climate change led to changes in water management, especially in urban areas. RainWater Harvesting (RWH) is a promising technique that allows the collection and reuse of rainwater, as well as protecting sewage systems from overload. This article reviews the current state of RWH in Europe, including advantages, implementation, potential efficiency, usage requirements, quality, and treatment processes. The main findings include the importance of RWH as a sustainable water management technique, the historical background and renewed interest in RWH systems in recent years, the positive impact of RWH on reducing energy consumption and greenhouse gas emissions, the versatility of rainwater usage, and the potential cost savings and benefits in various regions. RWH systems are gaining popularity in Europe, particularly in Germany, Austria, and Switzerland. Climate change and precipitation patterns affect rainwater availability and quality. RWH can be used for various purposes, including drinking, but requires proper purification for health safety. It is also being implemented in new locations like airports and large buildings. RWH systems have a high potential to overcome undesired results of climate change. Among that, numerous aspects still need to be considered in the future that allow the application of RWH systems on a larger scale. [ABSTRACT FROM AUTHOR]

The use of reclaimed water is expected to increase in the coming years, mainly in water-scarce areas. In the European Union (EU), an increase in the use of reclaimed water is expected to play a significant role within the European circular economy strategy and climate change adaptation policies with the aim to enhance overall sustainability of water resource management. While several institutions have offered estimations of the potential of reclaimed water reuse in the EU context, these estimations tend to overestimate potential reuse volumes since they fail to fully consider the following important issues: (a) the role of return flows in basins where cascade reuse is crucial in maintaining downstream uses (including ecological flows); (b) the availability of abundant (and cheaper) conventional resources; and (c) the economic productivity of water as an indicator of users' willingness to pay for reclaimed water. This study focuses on the Spanish case since this is currently the EU member state with the highest potential for reclaimed water reuse. Findings show that previous estimations of reusable water volumes in Spain may have overestimated potential volumes. The proposed analysis can be extrapolated to other EU regions, where realistic estimations of the potential of reclaimed water might be much needed. [ABSTRACT FROM AUTHOR]

Climate change imposes significant pressure on existing urban water systems. Prolonged low-flow periods, attributed to shifting climatic conditions, swiftly reduce the available water storage in reservoirs and threaten the quality of river water. This paper introduces a framework for assessing the environmental dynamic resilience (EDR) of urban water systems. The EDR framework stands as a state-of-the-art risk assessment tool that incorporates the dynamic nature and recovery time of water systems. The framework employs outputs from a series of models, including climate, hydrological, and urban water system models, as input data. To validate the findings from the proposed framework, environmental reliability (ER) is utilized as a conventional risk metric in the realm of water resource management. London, UK, serves as a case area to showcase the effectiveness of the proposed climate-related risk metric. The findings suggest a projected 10.5% decrease in the overall EDR during the near-future period (2020–2049) when compared to the baseline period (1975–2004). The sharpest declines in EDR are anticipated for the water quality (15.4%) and reservoir parts (13.6%) of the urban water system. Conversely, ER aligns with the insights from the introduced framework, suggesting a reliability reduction of approximately 6.8%. Nevertheless, ER neglects the recovery time essential for attaining full system functionality, leading to a potential underestimation of the climate-related risks to the urban water system. [ABSTRACT FROM AUTHOR]

Optimizing both performance and stability under varying relative humidity (RH) conditions is crucial for proton exchange membrane fuel cells (PEMFCs). Therefore, effective management of mass transfer and water is an essential key factor. To further improve performance and stability, this paper reports a novel PEMFC design strategy that introduces carbon nanotube (CNT) sheets with titanium (Ti) deposited onto them as an additional functional layer using the sputtering method. The Ti‐CNT (as Ti‐deposited CNT is abbreviated to Ti‐CNT) sheets are inserted between the catalyst layer (CL) and the gas diffusion layer (GDL). This exhibit enhances performance across all testing conditions (25‐100% RH), which is attributed to their optimal pore structure and hydrophilic properties. It shows up to ≈94% higher power density and ≈60% improvement in charge transfer resistance compared to conventional. Moreover, stability tests conducted under a constant voltage demonstrated that this innovative design strategy significantly reduced degradation, thereby proving its superior stability. This novel design strategy of inserting Ti‐CNTs as a functional layer improves electrochemical performance and stability. [ABSTRACT FROM AUTHOR]

Soil volumetric water content (VWC) is one of the key factors in hydrological cycles and responsible for inducing droughts and floods. Therefore, the precise prediction of VWC is crucial for the effective management of water resources. However, the complexity in structural characteristics and interaction with several other external meteorological factors cause difficulty in establishing a mathematical model which can predict soil VWC accurately. This study demonstrates the applicability of Convolution Neural Network-Long short-term memory (CNN-LSTM) hybrid model to predict soil VWC (%), concentrating specifically on optimizing the predictors combination using recursive feature elimination (RFE) which results in a more interpretable model with less complexity. The model was developed using the data collected from Benton County of Washington, USA, and generalization capacity of the model was tested in other counties of Washington. To verify the improved prediction ability of the proposed model, the results were compared with the established CNN, LSTM and MLR models. The results reflected that the proposed CNN-LSTM model predicted better than the individual CNN, LSTM and MLR models for the training site as well as for the five testing sites, proving its good generalization capacity. [ABSTRACT FROM AUTHOR]

The prediction of tap water quality serves as a pivotal component in enhancing water resource management. The intricate nonlinearity and inherent instability in water quality data make this task challenging. In this paper, we present a Tap-Water Quality Temporal Prediction Network (TWQ-TPN) to accurately predict tap-water quality by focusing on the impact of temporal nonlinear patterns and long-term seasonal fluctuations. To achieve this, we design two modules, namely the Temporal Feature Extraction Module (TFEM) and the Feature Transformation and Prediction Module (FTPM). The TFEM learns complex dynamic nonlinear features in the temporal domain. The FTPM is to realize feature transformation in the high-dimensional features for long-term seasonal fluctuations. Thus, our TWQ-TPN can accurately predict tap water quality trends to help improve water management. We validate TWQ-TPN’s superiority using 5 years’ data from 33 major water facilities in South Korea, demonstrating excellence in pH, turbidity, and residual chlorine. Ablation experiments support TWQ-TPN’s rationale. [ABSTRACT FROM AUTHOR]

The impacts of environmental change on Lake Biwa have been explored for decades, with water monitoring and palaeolimnological studies revealing how environmental forcing, including climate warming, eutrophication, water level manipulation and human manipulation of fish populations, has influenced the food web of Lake Biwa. However, these studies have rarely accounted for microbial food‐web components. This knowledge gap is mostly due to the lack of time series spanning more than a couple of decades, coupled with the high taxonomical expertise required to identify organisms belonging to very diverse groups. The use of a sedimentary DNA approach allows for the reconstruction of past changes in the diversity, composition and structure of the microbial eukaryotic community of aquatic systems. The application of 18S metabarcoding has been proven successful to describe the response of unicellular eukaryotes (protists) and aquatic fungi in lake ecosystems, encompassing a large taxonomic and functional diversity such as phototrophs, heterotrophs and mixotrophs. We applied 18S metabarcoding to 31 sediment core samples from Lake Biwa, spanning the past 100 years and explored the response of microbial eukaryotic communities to changes in multiple environmental stressors, including nutrient levels, lake water level, climate, as well as fish and zooplankton biomass for the period 1973–2010. We found that the manipulation of the water level and changes in fish community composition were the primary factors impacting (indirectly) the structure of the lake microbial eukaryotic community with minor, but significant, effects of climate warming and phosphorus levels. Co‐occurrence network analysis highlighted the potential food web impacts on the microbial eukaryotic community, suggesting that organisms from this compartment were impacted by both bottom‐up and top‐down processes. [ABSTRACT FROM AUTHOR]

This opinion article presents arguments to sustain the inclusion of local actors in the governance and management of water resource restoration projects. There is a lack of knowledge regarding this issue, and we propose that governance and management must be adaptive because of the complexity and constant modification of the local systems. Our proposal has theoretical, methodological, and management impacts on the network governance of local projects. We present a matrix of variables to facilitate research and management plans. [ABSTRACT FROM AUTHOR]

Summary Emulsions are combinations of two‐phases of immiscible liquids, where one liquid is dispersed throughout the other liquid with the help of emulsifiers such as surfactants. Surfactants, which are emulsifiers composed of small amphiphilic molecules, have several drawbacks. These include being non‐biodegradable and releasing various chemical compounds into the environment. Consequently, they are not ideal for prolonged use. Solid particles can be an alternative candidate to stabilise emulsions, forming what are known as Pickering emulsions (PEs). It has shown that PEs exhibited greater encapsulation efficiency (EE) of other substances up to 98%, which is more than twice compared with that of surfactant‐stabilised emulsions. Due to its irreversible adsorption, PEs has been recognised in various industries such as cosmetics, food, biomedical and aquaculture which have potential in targeted drug and nutrient delivery to the fish, water management, feed enhancement and stress reduction in aquaculture species. Thus, this review will be discussing on (i) emulsion stability and performance, (ii) solid particles in stabilising Pickering emulsions, (iii) use of PEs in various industries, (iv) nanotechnology in PEs to optimise aquaculture, (v) potential of PEs as drug delivery in fish culture, (vi) PEs as agents in water quality management, and (vii) PEs as encapsulation of stress‐relieving compounds, (viii) PEs as fish and fish feed enhancer, (ix) innovations of chitosan‐based PEs from aquaculture by‐product, and (x) innovations of PEs from fisheries by‐product. This review would provide insight into future research on enhancing the sustainability and functionality of Pickering emulsions by exploring novel, environmentally friendly solid particles and incorporating advanced nanotechnology techniques to further improve Pickering emulsions stability. [ABSTRACT FROM AUTHOR]

Communities around the world rely on snowmelt to meet water demands, and periods of lower than normal snow accumulation, snow droughts, can decrease water supplies. Leveraging 172 minimally disturbed and seasonally snow-covered watersheds, we developed an approach to examine the effects of cool & dry, warm & dry, and warm & wet snow droughts on streamflow timing and magnitude by hydrologic region. Our results showed all types of snow droughts in all regions correlate with lower annual streamflow, lower maximum and minimum flows, and lower runoff ratios, with more numerous low flow days and earlier streamflow timing. However, departures from non-snow drought conditions differed substantially between drought types and regions. Consecutive snow droughts further reduced runoff ratios and increased low flow days, likely due to additional subsurface storage depletion. With warm snow drought occurrence expected to increase, we discuss impacts for water management systems whose design specifications may not reflect the changing hydroclimate. [ABSTRACT FROM AUTHOR]

The adoption of agricultural water interventions for climate change adaptation has been slow and limited despite their established efficacy and benefits. While several studies have identified socio-economic, biophysical, technological and institutional factors that influence adoption, psychological factors have often been overlooked. This study examines the socio-economic and psychological factors, using RANAS behavioral model, that influence the adoption of agricultural water interventions in the semi-arid region of Saurashtra in India. Two contrasting and dominating agricultural water interventions in the area: drip irrigation and borewells are evaluated. Despite subsidies being available for drip irrigation systems, the adoption rate remains low (-16% adopting rate) compared to borewells (-24.5% adoption) with no subsidies reflecting farmer's preference for supply augmentation measures over demand management. Incorporating psychological factors in the analysis improved the explanatory power of the logistic model by almost threefold, underscoring the significance of psychological factors in explaining farmers' adoption decisions. Based on the logistic model, major factors determining farmers adoption behaviour identified are farmer's perceived ability, risk preference and positive beliefs about the technologies along with socio-economic (e.g., land size) and biophysical factors (e.g., proximity to water). The study recommends a multi-pronged approach to increase the adoption of interventions, including augmenting subsidies with efforts on extension services, post-adoption services, training, and awareness campaigns to build farmers' capacity and raise awareness. [ABSTRACT FROM AUTHOR]

The Climate Suitability Index (CSI) can increase agricultural efficiency by identifying the high-potential areas for cultivation from the climate perspective. The present study develops a probabilistic framework to calculate CSI for rainfed cultivation of 12 medicinal plants from the climate perspective of precipitation and temperature. Unlike the ongoing frameworks based on expert judgments, this formulation decreases the inherent subjectivity by using two components: frequency analysis and Particle Swarm Optimization (PSO). In the first component, the precipitation and temperature layers were prepared by calculating the occurrence probability for each plant, and the obtained probabilities were spatially interpolated using geographical information system processes. In the second component, PSO quantifies CSI by classifying a study area into clusters using an unsupervised clustering technique. The formulation was implemented in the Lake Urmia basin, which was distressed by unsustainable water resources management. By identifying clusters with higher CSI values for each plant, the results provide deeper insights to optimize cultivation patterns in the basin. These insights can help managers and farmers increase yields, reduce costs, and improve profitability. [ABSTRACT FROM AUTHOR]

Outcrops play an important role in groundwater recharge. Understanding groundwater origins, dynamics and its correlation with different water sources is essential for effective water resources management and planning in terms of quantity and quality. In the case of the Guarani Aquifer System (GAS) outcrop areas are particularly vulnerable to groundwater pollution due to direct recharge processes. This study focuses on the Alto Jacaré-Pepira sub-basin, a watershed near Brotas, a city in the central region of the state of São Paulo, Brazil, where groundwater is vital for supporting tourism, agriculture, urban water supply, creeks, river and wetlands. The area has a humid tropical climate with periods of both intense rainfall and drought, and the rivers remain perennial throughout the year. Therefore, the aim of this study is to investigate the interconnections between a spring and its potential sources of contribution, namely rain and groundwater, in order to elucidate the relationships between the different water sources. To achieve this, on-site monitoring of groundwater depth, rainfall amount, and stable isotope ratios (deuterium (2H) and oxygen-18 (18O)) from rain, spring discharge, and a monitoring well was carried out from 2013 to 2021. The results indicate that the mean and standard deviations for δ18O in rainwater exhibit higher variability, resulting in −4.49 ± 3.18 ‰ VSMOW, while δ18O values from the well show minor variations, similar to those of the spring, recording −7.25 ± 0.32 ‰ and −6.94 ± 0.28 ‰ VSMOW, respectively. The mixing model’s outcomes reveal seasonal variations in water sources contribution and indicate that groundwater accounts for approximately 80 % of spring discharge throughout the year. Incorporating stable isotopes into hydrological monitoring provides valuable data for complementing watershed analysis. The values obtained support the significance of the aquifer as a primary source, thereby offering critical insights into stream dynamics of the region. [ABSTRACT FROM AUTHOR]

Population models can be a useful tool for ecological risk assessment to increase ecological realism. In the present study, population models were used to extrapolate toxicity test results of four metals (Ag, Cu, Ni, Zn) to the population level. In total, three primary producers, five invertebrate species, and five fish species were covered. The ecological modeling–based laboratory to population effect extrapolation factor (ECOPEX factor), defined as the ratio of the predicted 10% effect concentration (EC10) at the population level and the observed EC10 for the laboratory toxicity test, ranged from 0.7 to 78.6, with a median of 2.8 (n = 27). Population modeling indicated clearly higher effect concentrations in most of the cases (ECOPEX factor >2 in 14 out of 27 cases), but in some cases the opposite was observed (in three out of 27 cases). We identified five main contributors to the variability in ECOPEX factors: (1) uncertainty about the toxicity model, (2) uncertainty about the toxicity mechanism of the metal, (3) uncertainty caused by test design, (4) impact of environmental factors, and (5) impact of population endpoint chosen. Part of the uncertainty results from a lack of proper calibration data. Nonetheless, extrapolation with population models typically reduced the variability in EC10 values between tests. To explore the applicability of population models in a regulatory context, we included population extrapolations in a species sensitivity distribution for Cu, which increased the hazardous concentration for 5% of species by a factor 1.5 to 2. Furthermore, we applied a fish population model in a hypothetical Water Framework Directive case using monitored Zn concentrations. This article includes recommendations for further use of population models in (metal) risk assessment. Environ Toxicol Chem 2024;00:1–21. © 2024 SETAC [ABSTRACT FROM AUTHOR]

Pacific Islands present unique challenges for water resource management due to their environmental vulnerability, dynamic climates, and heavy reliance on groundwater. Quantifying connections between meteoric, ground, and surface waters is critical for effective water resource management. Analyses of the stable isotopes of oxygen and hydrogen in the hydrosphere can help illuminate such connections. This study investigates the stable isotope composition of rainfall on O'ahu in the Hawaiian Islands, with a particular focus on how altitude impacts stable isotope composition. Rainfall was sampled at 20 locations from March 2018 to August 2021. The new precipitation stable isotope data were integrated with previously published data to create the most spatially and topographically diverse precipitation collector network on O'ahu to date. Results show that δ18O and δ2H values in precipitation displayed distinct isotopic signatures influenced by geographical location, season, and precipitation source. Altitude and isotopic compositions were strongly correlated along certain elevation transects, but these relationships could not be extrapolated to larger regions due to microclimate influences. Altitude and deuterium excess were strongly correlated across the study region, suggesting that deuterium excess may be a reliable proxy for precipitation elevation in local water tracer studies. Analysis of spring, rainfall, and fog stable isotope composition from Mount Ka'ala suggests that fog may contribute up to 45% of total groundwater recharge at the summit. These findings highlight the strong influence of microclimates on the stable isotope composition of rainfall, underscore the need for further investigation into fog's role in the water budget, and demonstrate the importance of stable isotope analysis for comprehending hydrologic dynamics in environmentally sensitive regions. [ABSTRACT FROM AUTHOR]

Environmental flows (e-flows) aim to mitigate the threat of altered hydrological regimes in river systems and connected waterbodies and are an important component of integrated strategies to address multiple threats to freshwater biodiversity. Expanding and accelerating implementation of e-flows can support river conservation and help to restore the biodiversity and resilience of hydrologically altered and water-stressed rivers and connected freshwater ecosystems. While there have been significant developments in e-flow science, assessment, and societal acceptance, implementation of e-flows within water resource management has been slower than required and geographically uneven. This review explores critical factors that enable successful e-flow implementation and biodiversity outcomes in particular, drawing on 13 case studies and the literature. It presents e-flow implementation as an adaptive management cycle enabled by 10 factors: legislation and governance, financial and human resourcing, stakeholder engagement and co-production of knowledge, collaborative monitoring of ecological and social-economic outcomes, capacity training and research, exploration of trade-offs among water users, removing or retrofitting water infrastructure to facilitate e-flows and connectivity, and adaptation to climate change. Recognising that there may be barriers and limitations to the full and effective enablement of each factor, the authors have identified corresponding options and generalizable recommendations for actions to overcome prominent constraints, drawing on the case studies and wider literature. The urgency of addressing flow-related freshwater biodiversity loss demands collaborative networks to train and empower a new generation of e-flow practitioners equipped with the latest tools and insights to lead adaptive environmental water management globally. Mainstreaming e-flows within conservation planning, integrated water resource management, river restoration strategies, and adaptations to climate change is imperative. The policy drivers and associated funding commitments of the Kunming–Montreal Global Biodiversity Framework offer crucial opportunities to achieve the human benefits contributed by e-flows as nature-based solutions, such as flood risk management, floodplain fisheries restoration, and increased river resilience to climate change. [ABSTRACT FROM AUTHOR]

Adequate monitoring of river discharge is crucial for effective water resource management. However, this objective remains difficult to achieve in the context of large and ungauged river basins. This study assesses the performance of remote sensing applications for discharge monitoring in the lower reach of the Congo River, where daily discharge information is required to support many water resource operations. The approach is based on the use of Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing imagery to produce a daily time series of a ratio of reflectance values (C/M) for discharge monitoring. The validation of the approach is performed based on three-year water level data collected at the outlet gauging site and limited in situ Acoustic Doppler Current Profiler (ADCP) cross-section measurements for high and low flow seasons. The simulated discharge closely matches the observed values and falls within acceptable ranges, with errors below 10% and Nash-Sutcliffe coefficients ranging from 0.65 to 0.76 for ADCP and gauging station, respectively. [ABSTRACT FROM AUTHOR]

This paper delves into the intersection of women's empowerment and water management throughout Africa, examining the diverse roles women undertake in water governance through the lens of case studies and initiatives showcasing their contributions to sustainable development. Utilising interdisciplinary perspectives, the paper scrutinises policy frameworks, institutional mechanisms, and challenges confronting women in water management, emphasising the necessity of gender-responsive approaches and collaborative efforts to foster equitable and resilient water systems. Through empowerment, innovation, and partnership, women emerge as pivotal catalysts for change in navigating the intricate landscape of water governance across the continent. [ABSTRACT FROM AUTHOR]

Waterbody extraction from satellite imagery plays a crucial role in various environmental monitoring and management applications. Accurate identification and delineation of water bodies are essential for assessing water resources, monitoring changes in aquatic ecosystems, and supporting decision-making processes. This review presents a comprehensive analysis of different methods used for waterbody extraction from satellite images, highlighting their strengths, limitations, and recent advancements. This review begins by discussing traditional methods, such as thresholding-based methods, machine learning methods, and object-based image analysis, which have been widely employed in the past. Consequently, the focus shifts towards, how deep learning models, such as convolutional neural networks (CNNs) have been applied to improve waterbody extraction accuracy and address challenges posed by spectral variations, cloud cover, and sensor limitations. Overall, this review serves as a valuable resource for researchers, practitioners, and decision-makers involved in water resource management and environmental monitoring. [ABSTRACT FROM AUTHOR]

In the Biosphere Reserve of the Maya Lowlands, the large‐scale characterisation of the current wetlands ecology and the exploitation and management of their natural resources by the ancient Maya is severely constrained by the forest. This paper presents an integrated geomatic, geoarchaeological and ecological approach, developed to overcome this obstacle in the microregion of the Naachtun Maya city. It is based on the analysis of LiDAR, and field and laboratory data. This approach has revealed the mosaic of current ecological conditions of the wetlands, thanks to the characterisation and spatial modelling of the landforms, hydrology, vegetation and soil cover. It has enabled the characterisation of numerous hydraulic and agricultural structures: 70 large reservoirs, raised fields (the largest over 1.5 km²), canals and ditches (with a cumulative length of over 300 km) and dikes. Eight morphological types of hybrid structures—hydraulic and agricultural—are described. These constructions have enabled the intensive exploitation of water and soil resources, their management and the resulting environmental risks. This study has shown that the agroecosystems of lowland areas were created as early as ~1500 B.C.E. and evolved in a polyphasic way, until a phase of radical decline around 1000 C.E. This study has made it possible to characterise the legacy of the Maya Early Anthropocene on current wetlands, as well as their important natural and cultural heritage. [ABSTRACT FROM AUTHOR]

Non-stationary sediment load analysis is critical for river engineering design and water resource management. Traditional sediment load frequency analysis methods usually assume stationarity, which can lead to inconsistent results in a changing environment because they cannot account for factors such as time variations. Here, we use generalized additive models for location, scale and shape (GAMLSS) to establish non-stationary models with time, precipitation and streamflow as covariates (named Model 1 and Model 2, respectively), and compare their fitting effects with stationary models (parameters unchanged: Model 0). In this study, the sediment load of the Jinsha River Basin in southwest China was analyzed. Outcomes indicate that: (1) the research area's sediment load decreased significantly, with a significant change point in 2002 (p < 0.1); (2) the goodness of fit indices (global fitting deviation: GD, AIC criterion and SBC criterion) based on Model 2 are smaller than the values of the other two models. The other two models' sediment load quantile design values are within Model 2's range. (3) Compared with Model1, precipitation and streamflow as covariates in Model 2 are more able to capture the non-stationary features of sediment load frequency. Furthermore, Model 2 can more accurately forecast future changes in sediment load when external physical factors are considered. The findings of this research can serve as a scientific foundation for decision makers to carry out water conservancy planning and design and river management and development. [ABSTRACT FROM AUTHOR]

Streamflow forecasting holds a pivotal role in the effective management of water resources, flood control, hydropower generation, agricultural planning, and environmental conservation. This study assessed the effectiveness of a stacked Multilayer Perceptron-Random Forest (MLP-RF) ensemble model for short- to medium-term (7 to 15 days ahead) daily streamflow forecasts in the UK. The stacked model combines MLP and RF, enhancing generalization by capturing complex nonlinear relationships and robustness to noisy data. Stacking reduces bias and variance by aggregating predictions and addressing differing sources of bias and variance in MLP and RF. Furthermore, this ensemble model is computationally inexpensive. The study also examined the impact of different meta-learner algorithms, Elastic Net (EN), Isotonic Regression (IR), Pace Regression (PR), and Radial Basis Function (RBF) Neural Networks, on model performance. For 1-day ahead forecasts, all models performed well (Kling Gupta efficiency, KGE, from 0.921 to 0.985, mean absolute percentage error, MAPE, from 3.59 to 13.02%), with minimal impact from the choice of meta-learner. At 7-day ahead forecasts, satisfactory results were obtained (KGE from 0.876 to 0.963, MAPE from 11.53 to 24.55%), while at the 15-day horizon, accuracy remained reasonable (KGE from 0.82 to 0.961, MAPE from 18.31 to 34.38%). The RBF meta-learner generally led to more accurate predictions, particularly affecting low and peak flow rates. RBF consistently outperformed in predicting low flow rates, while EN excelled in predicting flood flow rates in many cases. For estimating total discharged water volume, all models exhibited low relative error (< 0.08). [ABSTRACT FROM AUTHOR]

Hydrological models are critical for water resources planning and management. The precision and reliability of the simulations hinge greatly on the accessibility and quality of available input data. Particularly in developing nations, the major challenge in modeling is the scarcity of fine-scale spatiotemporal input data, specifically precipitation. Remotely sensed weather data has been increasingly used in recent years. However, they possess bias compared to ground observations due to the nature of indirect measurement and may affect the simulated water balance. To address these limitations, we explored data assimilation techniques to improve the Global Precipitation Measurement product (IMERG) precipitation using limited ground observations. Multiple assimilation methods are applied by incorporating Linear scaling Correction Factor (CF) and Power Transformation Function methods (PF). The assimilated IMERG precipitation from the most effective method identified, is utilized in an eco-hydrological model, and the resulting stream flow simulations are validated against observed flow data. The findings indicate that assimilated precipitation enhances the monthly flow statistics in both CF and PF methods and also in conditional merged precipitation. An ensemble of hydrological simulations, outperformed those based on raw IMERG precipitation. Additionally, the hydrological simulations are compared with observed gauge precipitation data and the widely used Climate Forecast System Reanalysis (CFSR) dataset in data-limited watersheds. The simulations utilizing the assimilated IMERG dataset (NSE = 0.52) are comparable to gauge precipitation-based simulations (NSE = 0.61) and significantly superior to CFSR-based simulations (NSE=-0.2). These results highlight the potential of utilizing assimilated remote sensing data for hydrological modeling in data-limited watersheds, leading to improved simulation accuracy and reliability. [ABSTRACT FROM AUTHOR]

Poor water resource management is a major cause of water loss and exacerbates water shortages. In order to avoid some misconceptions and misunderstandings associated with irrigation efficiency, the term real water savings (RWS) has been introduced in contrast to apparent water savings (AWS). In this study, irrigation technology interventions were evaluated in terms of return flow and water saving in the Qazvin Plain irrigation network in Iran. This was accomplished using the REWAS tool developed by FAO to evaluate the effects of technological and management interventions on the RWS at the macro level (network, basin, etc.). According to the results, switching the irrigation system from furrow to center pivot with height-regulated sprinklers (Scenario A), center pivot with height-fixed sprinklers (Scenario B), linear-move irrigation system (Scenario C), and solid-set sprinkler irrigation (Scenario D), results in RWS of 390, 383, 326, and 331 mm, respectively. In turn, as a result of applying scenarios A, B, C, and D, the AWSs at the field scale were determined to be 90%, 88%, 75%, and 76%, respectively, while the RWS at the irrigation network scale was determined to be 19%, 19%, 17%, and 18%, respectively. Due to the influence of nonrecoverable return flows, the RWS is much lower than expected. In conclusion, the RWS can only be increased by preventing nonrecoverable return flows. The assessment of RWS can assist decision-makers in choosing sustainable interventions to improve agricultural water productivity by providing insight into field flows, irrigation networks, and basin scales. [ABSTRACT FROM AUTHOR]

The cooperative operation of cascade reservoir systems is an efficient way to regulate water resources. However, noncooperation among various reservoir stakeholders is often observed in practice; this produces an interesting dilemma in the game of water resource management. Considering the upper Yellow River cascade reservoir system as a case study, in this paper we model and analyze the cooperation dilemma in a cascade reservoir system. In our game theoretical analysis, we find that, except for the most upstream reservoir, all reservoirs have free-ride strategies. The free-ride strategy indicates that a reservoir obtains free gain from the cooperation of other reservoirs due to spatial connections, and this fact changes the cooperative game in terms of equilibrium and benefit allocation. The results show that the regulation capacity of the free rider directly affects the equilibrium and benefit allocation of the game. A midstream reservoir with a small or medium regulation capacity tends to employ a free-ride strategy. A midstream reservoir with a large regulation capacity can entirely interrupt the cooperation between upstream and downstream reservoirs, interestingly, which can lead to the disappearance of the free-ride strategy for the midstream reservoir. However, the downstream reservoir may employ a free-ride strategy when the midstream reservoir chooses to cooperate. This implies that grand cooperation is not stable when considering free-ride, whereas partial coalitions are more likely to form. In this paper, we derive equilibrium in the cooperative game of cascade reservoirs, providing theoretical interpretation of the noncooperation phenomenon in the operation of cascade reservoirs. [ABSTRACT FROM AUTHOR]

Water distribution networks, like other large infrastructure systems, must consider reliability and resilience efforts to resist and recover from failure with limited resources. Management of these assets requires a plan to prioritize the maintenance of system components, which are key to its reliability. Many current asset management practices for water distribution networks include only reactive strategies, such as fixing components after breaking, or on predetermined maintenance schedules, which might not correlate with a component's condition or need. Asset management and graph theory principles are utilized in this study to evaluate a water distribution network and its vulnerabilities at Tyndall Air Force Base (AFB). We begin by estimating pipe condition indices and establishing the importance of each pipe through a set of graph-theoretic measures (e.g., pipe betweenness centrality and network efficiency). We next simulate two pipe failure scenarios: (1) a single pipe failure scenario, and (2) a cascading failure scenario. The outcomes of the second scenario reveal that a larger betweenness centrality equates to being a critical pipe in relation to overall system performance. Further, we estimate the risk associated with each pipe by combining pipe condition and network properties. We find that ∼7 km (or ∼6%) of pipes are at high risk, while the majority of the network's pipes (∼79 km or ∼62%) are low risk. This study demonstrates how integrating condition indices with graph theory metrics could be employed to promote best practices in pipe maintenance and create a risk-informed framework for asset management. [ABSTRACT FROM AUTHOR]

Agricultural land, water, and fertilizer utilization significantly impact the nutrient and water balances and greenhouse gas (GHG) emissions. This study explores the impacts of agricultural water, land, and fertilizer management on the trade-offs between economic benefit, GHG emissions, and water, salinity, nitrate, and phosphate balances by employing crop growth, flow, and solute simulation models, linked with an optimization algorithm. The coupled models can simulate flow, crop growth, and nutrient transport, and capture the water and solutes interaction between the farmland soil zone and saturated groundwater zone, while considering spatial heterogeneity of soil, crop, fertilizer, and irrigation. The optimization model was used to find the trade-offs between the conflicting objectives of maximizing the net economic benefit and minimizing GHG emissions. The optimal water and land allocation schemes, fertilizer application, and crop type were obtained under wet, normal, and dry hydrological years. Then a simple rule was introduced based on the optimum results of the wet, normal and dry years. The proposed methodology was applied to the Dashteabbas irrigation network in southwest Iran. The results showed that the mass loading of salt, nitrate and phosphate decreases to water bodies by 7%, 37%, and 37%, respectively, and less land (−19%), water (−16%), and fertilizer (−35%) are exploited. Also, despite the lower net benefit of the optimum solution (12% lower than the current situation), the GHG emissions (28% lower than the current situation) would decrease, indicating that the introduced rule can help decision-makers to promote coordinated economic and environmental development in the agricultural irrigation systems. [ABSTRACT FROM AUTHOR]

Valuing water is receiving increasing attention within the global water policy agenda as a new water management paradigm. However, it is not yet clear how it can be operationalized in local water management contexts. We apply the Value Landscapes Approach as a conceptual framework to show how water-related preferences are informed by underlying assigned/water values and governance-related values and how these values may explain three different visions for water management among professional respondents in a Northern Kenyan case study. Through making shared and conflicting values explicit, these insights may serve as a foundation for addressing water conflicts in practice. [ABSTRACT FROM AUTHOR]

This study examines hotel water management in Madeira, Portugal and Tenerife, Spain, which differ in water stress and tourism pressure, both much higher in Tenerife. Determinants of hotel water use and water-saving measures are evaluated using correlations and cluster analyses. In Tenerife, more decisive implementation of water-saving measures results in much lower consumption. Conversely, in Madeira, hotel size and category appear to overshadow the effect of water-saving measures. The novelty of this study lies in applying the same methodology to two different destinations, highlighting the role of external factors in shaping hotel water management, while exploring water-saving measures in depth. [ABSTRACT FROM AUTHOR]

Understanding the rainfall variability is crucial for managing water resources and mitigating agricultural hazards, particularly in poorly gauged regions like the Abaya–Chamo basin. This study compares various satellite-derived rainfall products, including Climate Hazards Group Infrared Precipitation with Stations (CHIRPS), Tropical Applications of Meteorology using Satellite data and ground-based observations (TAMSAT), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and Climate Hazards Group Infrared Precipitation (CHIRP), with observed rainfall data from 1990 to 2019. Accordingly, this study evaluates the performance of these satellite rainfall products using multiple metrics at daily and monthly scales. The correlation coefficient (CC), mean square error (MSE), Nash-Sutcliffe efficiency (NSE), percent of bias (PBIAS), mean absolute error (MAE), and categorical analysis metrics such as probability of detection (POD), false alarm ratio (FAR) and critical success index (CSI) indicators were applied to evaluate the accuracy of these products. Among them, the CHIRPS satellite product demonstrates superior agreement with observed data, with CC = 0.871 and NSE = 0.925, warranting its selection for further analysis of seasonal and annual rainfall variability. The coefficient of variation (CV) and precipitation concentration index (PCI) were applied to investigate rainfall variability. The study indicates that precipitation patterns in the Abaya–Chamo basin exhibit moderate to high variability throughout the year, with a CV ranging from 20–30%. This suggests substantial variability in annual rainfall within the region, in some instances where the variability exceeds 30%. Moreover, the southern and northern regions of the basin experience a consistent moderate to high variation in precipitation throughout the entire season, while the lowest variability was observed in the central part of the basin. These findings underscore the importance of satellite-derived rainfall data, particularly the CHIRPS product, in understanding spatiotemporal rainfall patterns and making informed decisions in water resource management. This research contributes in advancing our knowledge of rainfall variability in the Abaya–Chamo basin and underscores the utility of satellite data in regions lacking adequate ground-based monitoring. [ABSTRACT FROM AUTHOR]

Water is the most important basic need for sustaining life, and groundwater remains the primary source of this need in the coastal area of Semarang City. This indicates that the recharge of the source must be monitored as an important part of water resource management. Therefore, this study aimed to determine the origin of groundwater through the analysis of stable isotopes 18O and ²H, as well as the calculation of the sodium adsorption ratio (SAR) in Semarang City. The purpose is to determine the origin of deep wells and the quality of water for irrigation. The methods used in this study included hydrogeological mapping, testing groundwater samples, and the analysis of stable isotopes 18O and ²H. Semarang City was located in an area with geological components, including the Alluvium and Damar Formation, as well as geological structures such as rectification. Chemical parameter testing was carried out by comparing the SAR aspect of 30 samples with their electrical conductivity (EC). From the analysis of stable isotopes 18O and ²H, most of the samples were obtained from deep groundwater, while 1 was found in shallow aquifers. Furthermore, the stable isotope composition of 29 samples still followed the Global Meteoric Water Line (GMWL), indicating that they were obtained from global rainwater and had experienced mixing. [ABSTRACT FROM AUTHOR]

Inland waters have an important role in increasing fishermen's income, satisfying community nutritional needs, providing food security for the community, functioning as habitats for aquatic organisms, and maintaining environmental balance. The gap in fish resource management in Inland Water is that many problems in Inland Water have not been revealed and are not well documented. For this reason, it is necessary to collect references to review the problems and challenges of fish resource management in Inland Waters, as well as provide solutions so that Inland Water Fisheries can be sustainable. Inland water fisheries' problems in Indonesia are sedimentation, pollution, habitat destruction, lack of fishways, and overfishing. To reduce sedimentation, deforested land on the hillsides must be replanted. Green belts on the banks of reservoirs should not be used for agriculture and settlements, and must have a good master plan for land use, and sediment dredging should be carried out regularly. To tackle pollution from fish farming activities in inland waters, fish farming in reservoirs/ lakes must not pollute the waters, and the amount must match the carrying capacity. To deal with pollution from industry, waste must be treated first before being discharged into water. Dams in rivers must be equipped with fishways so that fish can migrate. To overcome overexploitation, the number and types of large fishing gear, such as liftnets, filtering device, active seine, and active barrier, along with fishing using poisons, chemicals, or electricity, must be monitored and punished. Based on the findings in the review that explain the problem and how to overcome it, fish resource management has a chance of success if it is good in its management. [ABSTRACT FROM AUTHOR]

Accurate quantification of snow cover facilitates the prediction of snowmelt runoff, the assessment of freshwater availability, and the analysis of Earth's energy balance. Existing fractional snow cover (FSC) data, however, often suffer from limitations such as spatial and temporal gaps, compromised accuracy, and coarse spatial resolution. These limitations significantly hinder the ability to monitor snow cover dynamics effectively. To address these formidable challenges, this study introduces a novel data fusion framework specifically designed to generate high-resolution (1 km) daily FSC estimation across vast regions like North America, regardless of weather conditions. It achieved this by effectively integrating the complementary spatiotemporal characteristics of both coarse- and fine-resolution FSC data through a multi-stage processing pipeline. This pipeline incorporates innovative strategies for bias correction, gap filling, and consideration of dynamic characteristics of snow cover, ultimately leading to high accuracy and high spatiotemporal completeness in the fused FSC data. The accuracy of the fused FSC data was thoroughly evaluated over the study period (September 2015 to May 2016), demonstrating excellent consistency with independent datasets, including Landsat-derived FSC (total 24 scenes; RMSE=6.8–18.9 %) and ground-based snow observations (14,350 stations). Notably, the fused data outperforms the widely used Interactive Multi-sensor Snow and Ice Mapping System (IMS) daily snow cover extent data in overall accuracy (0.92 vs. 0.91), F1_score (0.86 vs. 0.83), and Kappa coefficient (0.80 vs. 0.77). Furthermore, the fused FSC data exhibits superior performance in accurately capturing the intricate daily snow cover dynamics compared to IMS data, as confirmed by superior agreement with ground-based observations in four snow-cover phenology metrics. In conclusion, the proposed data fusion framework offers a significant advancement in snow cover monitoring by generating high-accuracy, spatiotemporally complete daily FSC maps that effectively capture the spatial and temporal variability of snow cover. These FSC datasets hold substantial value for climate projections, hydrological studies, and water management at both global and regional scales. [ABSTRACT FROM AUTHOR]

In this research, a sophisticated integration of Deep Learning (DL), Wireless Sensor Networks (WSN), and Fuzzy Logic (FL) is presented, aimed at enhancing agricultural water management in response to global food security challenges. The developed model, named TowaNet, integrates advanced architectures such as Long-Short Term Memory with Attention Mechanism (LSTM-ATT), Convolutional Neural Networks with Squeeze and Excitation block (CNN-SE), and Graph Convolutional Neural Networks (GCN). TowaNet was trained on data from a WSN comprising four nodes, each capturing essential agricultural parameters like air temperature, air humidity, light intensity, and soil moisture using specialized sensors. After three optimization steps were applied to each architecture, the model achieved impressive predictive performance, with Root Mean Square Error (RMSE) of 1.8010 and Mean Absolute Error (MAE) of 0.9005. When compared with other state-of-the-art models like LSTM-ATT, Convolutional Neural Networks combined Long-Short Term Memory with Attention Mechanism (CNN-LSTM-ATT), Random Forest (RF), and Extreme Gradient Boosting (XGBoost), TowaNet demonstrated superior prediction capabilities across several different datasets. The prediction data from TowaNet, processed using the MAMDANI fuzzification method, enabled precise calculation of required irrigation volumes based on environmental parameters. An experimental deployment of the TowaNet technique over a 7-day period resulted in up to a 27% reduction in water consumption compared to traditional irrigation techniques. This research highlights the effectiveness of precision irrigation in promoting sustainable water management and emphasizes the importance of tailoring irrigation to specific crop requirements. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is a vital process involving the transfer of water from the Earth's surface to the atmosphere through soil evaporation and plant transpiration. Accurate estimation of ET is important for a variety of applications, including irrigation management and water resource planning. The two-source energy balance (TSEB) model is a commonly used method for estimating ET using remotely sensed data. This study used the TSEB model and high-resolution unmanned aerial vehicle (UAV) imagery to estimate sorghum ET under four different irrigation regimes over two growing seasons in 2020 and 2021. The study also validated net radiation (Rn) flux through hand-held radiometer measurements and compared the estimated ET with a soil water balance model. The study outcomes revealed that that the TSEB model capably estimated Rn values, aligning well with ground-based Rn measurements for all irrigation treatments (RMSE = 32.9–39.8 W m−2 and MAE = 28.1–35.2 W m−2). However, the TSEB model demonstrated robust performance in estimating ET for fully irrigated conditions (S1), while its performance diminished with increasing water stress (S2, S3, and S4). The R2, RMSE, and MAE values range from 0.64 to 0.06, 10.94 to 17.04 mm, and 7.09 to 11.43 mm, respectively, across the four irrigation treatments over a 10-day span. These findings not only suggest the potential of UAVs for ET mapping at high-resolution over large areas under various water stress conditions, but also highlight the need for further research on ET estimation under water stress conditions. [ABSTRACT FROM AUTHOR]

There is increased call to demonstrate the benefits of EU Member States' river basin management plans, whose implementation has been delayed largely due to insufficient funding. This paper applies a contingent valuation study to investigate the benefit value of improved ecological status in river basins and the discrepancy between the quality of waters as perceived by river basin residents and as monitored under the Water Framework Directive. Respondents often reported worse quality for their focal water body than the monitored status indicated, a tendency established in a GIS analysis. The likelihood of such divergence increased most with degree of perceived deterioration of surface waters. Observed deterioration in waters, official status of one's focal water body and divergence between two quality measures had implications for welfare estimates. Describing water quality according to ecological criteria and as uniformly as possible would facilitate the use of valuation results in future benefit transfers. [ABSTRACT FROM AUTHOR]

• Identified the severity and frequency of drought in Singbhum Protocontinent, India. • Meteorological and remote sensing indices are used to identify drought dynamics. • 1.67 to 1.05 percent extreme drought frequency shows in the western part. • Poor aquifer properties and extreme climate are the main reason for droughts. • Sustainable watershed management is highly required. Drought is an extremely hazardous situation that predominantly affects ecosystems, hydrological systems, and agricultural mechanisms in different pockets of the world. Management of water resources in dry and semi-arid environments has become a critical challenge in the last few decades. The principal objectives of this study are (i) to categorize the severity and frequency of drought events using the Reconnaissance Drought Index and Rainfall Deviation Index and ii) to evaluate the spatial extension of drought in particular drought times of severe and extreme droughts through Remote Sensing Drought Indices (RSDIs). This drought monitoring index is commonly used index for its high degree of resilience and sensitivity to droughts. The result shows that severe to extreme drought occurred in Bero, Tulin, Sirkabad, Manbazar and Bundwan which are 22, 28, 23, 14 and 25 months correspondingly based on RDI3 whereas RDI12 values indicated 26, 47, 42, 22 and 38 months in the study period (1981 to 2021). Bundwan area faced the most extreme drought occurrence in May month of 1996 with −3.58 values followed by Sirkabad, Bero, Manbazar and Tulin. Manbazar is going through severe to extreme drought months (for short time) whereas 'extreme drought' frequency (1.67 % to 1.05 %) is higher in the western part mainly in Jhalda I, Jhalda II, Bagmundi, and Arsha blocks of Purulia district (part of Manbhum Singhbhum Plateau). Additionally, the recurrence of 'moderate drought' is much greater in Balarampur along with some portions of Purulia I block. The whole study can be summarized as the northeastern portion being challenged with moderate or severe drought conditions while mild or severe drought is a considerable recurrence in the northern section. The outcome of this study will be helpful for local planners and management officials during implementation strategies related to water resource management. [ABSTRACT FROM AUTHOR]

Traditional approaches devoted to upgrading the sewerage system functionality are highly costly and time demanding. Thus, the implementation of comprehensive modelling approaches can be intended as an effective and economically viable strategy to detect and outdo the critical issues of the networks. This paper presents an integrated procedure to monitor and simulate the network's performance, based on the coupling of Supervisory Control and Data Acquisition (SCADA) networks for data collecting and monitoring, with hydraulic simulations by the Storm Water Management Model 5.1 (EPA-SWMM) solver. The drawbacks of the network are then assessed by proposing several upgrades to improve the system. The proposed strategy was applied to the Nora-Noreña sewerage system, located in North Spain. Results show the potentiality of the methodology in reducing sewer network maximum filling degree requirements and overflows into the receiving water bodies. [ABSTRACT FROM AUTHOR]

Key Takeaways: US Southwest cities can benefit from innovative conservation approaches to further reduce water demand amid rising population growth and drought driven by climate change. To ensure a resilient water supply, Albuquerque Bernalillo County Water Utility Authority has successfully used adaptive strategies for 30 years to improve consumptive‐use efficiency. The Water Authority's partnership with the city's Parks Department takes a holistic water management approach to meet water supply needs while promoting responsible usage. [ABSTRACT FROM AUTHOR]

Water loss control tools have become more precise and robust while their importance for measuring and controlling nonrevenue water has increased. [ABSTRACT FROM AUTHOR]

Understanding how the laboratory is integral with the success of plant operations is key for operators to improve treatment processes and expand their knowledge. [ABSTRACT FROM AUTHOR]

A wide range of endeavors has been made to propose various approaches to reduce Greenhouse gas emissions in the agricultural sector. The present study investigates the impacts of Surface Water Distribution Systems (SWDS) modernization in reducing groundwater overexploitation, energy consumption, and carbon emission in the agriculture sector. Four modernization alternatives, including an improved manual-based system (A1, A2), off-line, and real-time automatic control systems (A3, A4), are developed and tested on a real test case in Central Iran, which is confronted with severe water shortages. The results reveal that SWDS's operating system modernization improves 4 ~ 21% surface water distribution through the alternatives A1 ~ A4. This surface water distribution enhancement led to groundwater over-extraction reduction. Spatial analysis reveals that 0.075, 0.100, 0.281, and 0.470 of the irrigation district's cultivated area was thoroughly fulfilled by the delivered surface water and no need for groundwater extraction due to alternatives A1 ~ A4, respectively. Closure of several active tubewells up to 1,668 semi-deep and 497 deep tube-well were verified. SWDS' modernization led to 5, 7, 20, and 30% of energy consumption and consequently 1,864.90, 2,714.33, 8,427.19, and 12,674.32 tC ha-1 carbon emission reduction in alternatives A1 ~ A4, respectively. This study's results show that modernization of off-farm operating systems - responsible for surface water conveyance and distribution from a dam reservoir to farms - resulted in significant environmental benefits through improving the reliability of systems supplied by surface water and reducing the tendency of the farmers to groundwater resources. [ABSTRACT FROM AUTHOR]