Cotton is an important plant since it provides raw materials for various in-dustry bracnhes. Even though cotton is generally tolerant of drought, it is af-fected negatively by long-term drought stress. This experiment was conduct-ed according to a completed randomized plots trial design with 3 replications to determine the upland cotton genotype’s reactions against drought under controlled conditions in the 2022 year. All genotypes were watered with 80 mL-1 of water (100% irrigation, Field capacity) until three true leaves ap-peared. After this period water stress was applied at limited irrigation of 75% (60 mL-1), 50% (40 mL-1), and 25% (20 mL-1) of field capacity. After the trial terminated at 52. Days, the cv. G56, elit line G44, G5, and commercial variety G86 genotype, respectively resulted in the highest Root Length (RL), and the G76 genotype resulted in the lowest RL followed by G41 and G35 elite lines. G1 cultivar showed the highest Root Fresh Weight (RFW), followed by G56, G44, G86, G51, and G88, respectively. The lowest RFW was also obtained in elite lines G76 and G41. The third drought morphological marker, the Num-ber of Lateral Roots (NLRs), was the highest in G44, followed by G86, Cv. G56, elite lines G13 and G5 genotype. The lowest NLRs value was obtained in genotype G47 and G76. The highest RDW means was obtained in elite line G5, followed by Cv. G56, elite line G44, G75 and cv. G90, while the lowes RDW mean obtained in elite line G76, G35, and local varieties G20 and G61. In the SL marker, the highest averages were recorded for genotypes G35, G15, G26, G67, and G56, respectively. In the SFW marker, the highest averages were observed in genotypes G15, G52, G60, G31, and G68, respectively. The lowest SL values were observed in genotypes G91, G72, G32, and G22. Simi-larly, the lowest SFW values were found in genotypes G83, G2, G75, and G91. In another shoot drought marker, Shoot Dry Weight (SDW), the highest val-ues were obtained in genotypes G35, G52, G57, G41, and G60, respectively. Conversely, the lowest SDW values were observed in genotypes G65, G91, G4, G20, and G22. In conclusion, the commercial varieties with high averages in roots, namely G86, G56, G88, and G90, and the genotypes G67, G20, G60, and G57 showing tolerance in shoots, are suggested to be potential parent plants for developing cotton varieties resistant to drought. Using the culti-vars found tolerant in the current study as parents in a drought-tolerant vari-ety development Marker-assisted selection (MAS) plant breeding program will increase the chance of success in reaching the target after genetic diversi-ty analyses are performed. It is highly recommended to continue the plant breeding program with the G44, G30, G19, G1, G5, G75, G35, G15, G52, G29, and G76 genotypes which show high tolerance in both root and shoot sys-tems.

The gradual decline of the Aral Sea’s water level over the past five decades poses a huge environmental problem in the heart of Central Asia. Uzbekistan, once blessed with abundant water resources, now struggles with water scarcity in certain regions. While global environmental issues contribute to some degree to this dilemma, irrigation mismanagement plays a central role. This study focuses on the widespread problem of irrigation mismanagement in Uzbekistan and specifically addresses the rural district of Oltinsoy in the southern province of Surkhandarya. The main objective of this research project is to propose effective measures that can alleviate the pressing problem of water scarcity in the region while emphasizing the urgent need for well-executed projects and careful maintenance to ensure long-term sustainability at the local level. It is important to note that this study does not include an examination of the impact of global warming on the decline of water resources in Uzbekistan.

The sustainable management of water scarcity is a global crucial issue. Germany has es- tablished efficient water management systems, but the agricultural sector still struggles with water scarcity as the demand surpasses the available water supply. The primary aim is to establish a framework for making water accessible for irrigation and additional use on households through the effective utilization of recycled water from wastewater treatment facilities. The research inquiries are focused on evaluating the changes in the agricultural irrigation model in CROPWAT, determining the spatial distribution of zonal severity, estimating the capacity of urban roof catchments, and evaluating the reduction volume of efficient water required from the existing wastewater treatment plant supply. According to the findings, the annual amount of water required for agriculture in the designated study location is approximately 2.9 million m3. Although there is no initial need for irrigation water, yet the demand for irrigation water increases during the development, active growth, and mature stages of maize, winter wheat, and wine grapes, reaching around 189mm, 225mm, and 62mm, respectively. According to our observation, the annual water supply in Weinstadt is around 4 million m3. On the other hand, the amount of water calculated from urban roof rainfall is estimated 0.8 million m3, which is considered valuable from an economic standpoint. This economically efficient volume of water would reduce the current treated water supply passes an opportunity for enhanced agricultural irrigation

The Brazilian water legislation advocates that some uses have priority over others, but this aspect has never been clearly addressed, generating conflicts. Water authorities usually refer to hydrological models to justify their decisions on water allocation. However, a significant group of stakeholders does not feel qualified to discuss these models and is, therefore, excluded from the decision process. We hereby propose a hydrologically robust method to correlate water uses with their respective reservoir alert volumes, which should empower the less formally educated stakeholders. The method consists of: (i) generating the water discharge versus reliability curve, using a stochastic approach; (ii) generating the withdrawal discharge versus alert volume family of curves, using a water-balance approach; (iii) calibrating the key parameter T using field data; and (iv) associating each water use with its alert volume. We have applied the method to four of the largest reservoirs (2.10³ - 2.10² hm³) in the semi-arid Ceará State. The results indicate that low-priority water uses should be rationalized when the reservoir volume is below 20%; whereas uses with very high priority should start rationalization when it is below 11%. These hydrological guidelines should help enhance water governance among non-specialist stakeholders in water-scarce and reservoir-dependent regions.

The world will experience an estimated 40% freshwater supply shortage by 2030, converting water scarcity into one of the principal global challenges that modern society face. Urban water-reuse is recognized as a promising and necessary measure to alleviate the growing water stress in many regions. The transformation to widespread application of water-reuse systems requires major changes in the way water is governed, and countries such as Spain already find themselves involved in this process. Through the systematic assessment of the city of Sabadell (Spain), we aim to identify the main barriers, opportunities and transferable lessons that can enhance governance capacity to implement systems for non-potable reuse of treated wastewater in cities. It was found that continuous learning, the availability and quality of information and level of knowledge and strong agents of change are the main capacity-building priorities. On the other hand, awareness, multilevel network potential and implementing capacity are already well-established. It is concluded that in order to undertake a widespread application of water-reuse practices, criteria examining water quality according to its use need to be developed, independently of the water’s origin. The development and implementation of such a legislative frame should be based on the experience of local water-reuse practices and continuous evaluation. Finally, the need for public engagement and adequate pricing mechanisms are emphasized.

Currently, a large part of the wells for agricultural use located in the state of Sonora are overexploited, which generates a high degree of saline intrusion and abandonment by nearby communities. In this paper the temperature effect on the final concentration of permeate water was evaluated through voltage and intel concentration variations in a batch electrodialysis reversal process (EDR), in order to identify optimal operating conditions with emphasis on the reduction of energy consumption and cost of desalinated water. Thirty-six samples were prepared: eighteen 2,000 mg/L total dissolved solids (TDS) samples and eighteen 5,000 mg/L TDS samples; brackish well water of 639 mg/L TDS and synthetic salt were mixed to obtain those concentrations. 3 different temperatures (25, 30, 35 °C) and 2 different voltages (10 and 20 V) were tested for each sample. The best salt removal occurred in the 20 V arrays, with 18.34% higher removal for 2,000 mg/L TDS experiments and 25.05% for 5,000 mg/L experiments (average between the 25 to 35 °C tests). Temperature positively affected EDR, especially in the experiments at 10 V voltage, where increasing 10 °C increased its efficiency by 10.83% and 24.69% for 2,000 and 5,000 mg/L TDS, respectively. Energy consumption was lower with increasing temperature (35 °C), as it decreased by 1.405% and 1.613% for 2,000 and 5,000 mg/L TDS concentrations, respectively (average between 10 and 20 V tests), decreasing the cost per m3 of water.

Over the coming decades, global freshwater withdrawals are expected to grow, especially in low and middle-income countries. Unless there are significant improvements in the efficiency of water use by economies, freshwater stress, crises and scarcity will worsen. This paper explores further the economic relationship between water use efficiency and scarcity. Because growing scarcity of freshwater in many regions and countries is not adequately reflected in markets, there is often insufficient incentives for investment and innovation to improve the efficiency of water use. To explore further changes in water use efficiency across countries, we conduct a panel analysis of water productivity changes for 130 countries over 1995 to 2020. Countries with lower initial levels of water use efficiency tended to have higher water productivity growth, whereas more agriculturally dependent economies displayed lower improvements in water use efficiency. Better institutional quality and capacity for innovation may also increase water use efficiency. We discuss the implications of these results for improving water use productivity in economies, and in particular, the opportunities and challenges for improving water markets and trades to alleviate water scarcity. We conclude by identifying further areas of research.

The increasing demand for water resources in urban areas, such as Bangladesh, due to population growth is a significant concern. One potential solution under consideration is the use of air conditioning (AC) condensate water. A study conducted at the European University of Bangladesh (EUB) focused on assessing the quality and quantity of AC condensate water from various systems. The results indicate that the collected water generally adhered to the quality standards established for drinking and household use in Bangladesh. Parameters such as pH (averaging 6.8), turbidity (1.08 NTU), total dissolved solids (TDS) (averaging 219 mg/L), iron content (0 mg/L), alkalinity (averaging 41.67 mg/L), arsenic (0 mg/L), chemical oxygen demand (COD) (averaging 3.67 mg/L), biochemical oxygen demand (BOD) (averaging 1.33 mg/L), chloride content (averaging 30.77 mg/L), and other factors were evaluated. Moreover, the AC units at EUB, varying in cooling capacity (1 ton, 2 tons, and 4 tons), produced substantial monthly volumes of 96, 177, and 354 liters of condensate water, respectively. This underscores the potential of AC condensate water as a valuable resource for addressing urban water scarcity. As a result, there is a pressing need for local decision-makers and policymakers to establish well-defined guidelines for the effective utilization of AC condensate water to mitigate water scarcity issues in urban areas.

Water scarcity is a key challenge to global development. In Brazil, the Sao Francisco River Basin (SFB) has experienced water scarcity problems because of decreasing streamflow and increasing demands from multiple sectors. However, the drivers of decreased streamflow, particularly the potential role of surface-groundwater interaction, have not been yet investigated. Here, we assess long-term trends in baseflow, quickflow, and streamflow of the SFB during 1980–2015 and constrain the most likely drivers of observed decreases through trend analysis of precipitation (P), evapotranspiration (ET), and terrestrial water storage change (TWS). We found that over 82% of the observed decrease in streamflow can be attributed to a significant decreasing baseflow trend (< -20 m3 s-1 y-1) along the SFR with spatial agreement between decreased baseflow, increased ET, and irrigated agricultural land. We also noted a decrease in TWS across the SFB with trends exceeding -20 mm y-1. Overall, our findings indicate that decreasing groundwater contributions (i.e., baseflow) is providing the observed reduction in total SFR flow. A lack of significant P trends indicates that only P variability likely has not caused the observed baseflow reduction, mainly in the Middle and Sub-middle SFB. Therefore, groundwater and surface withdrawals may be likely a driver of water scarcity over the SFB.

Water scarcity is significantly increasing water stress in Africa and some parts of the world. This is due to human induced factors such as climate change, increase of human population that raises demand which outstrips food availability, and put great changes of land use which results in changes of hydrological mechanics and water availability as whole. The investigation was through literature review and it tries to examine the criticality of water scarcity in Africa regions, and the major factors that mastermind this menace. Also possible strategies that can be promptly used to manage water scarcity at domestic level and in agriculture are described in this paper, not with standing the fact that agriculture sectors in Africa and the rest of the world remain the utmost vulnerable enterprise to water scarcity and withdrawal on the planet earth.

Achieving water security and availability for all is the main agenda of the UN-Sustainable Development Goals by the year 2030. To achieve the goal of water secure future in rapidly urbanizing cities, the sustainable water supplies are necessary. In the western part of India, the city of Surat is continuously growing and rapidly urbanized, which exerting massive pressure on groundwater water supply to meet increasing water demands. The study adopted the investigative approach, in which a total 33 groundwater samples were collected in and around the city from open, bore and dug wells and hand pumps. The selection of sampling sites was based on the land use signature, areas with a different depth of aquifers and different geological formations. After the hydrogeochemical analysis, the study evaluated the present state of the groundwater quality and determined the spatial distribution of groundwater quality parameters such as hardness, electrical conductivity, Cl −, pH, SO42-, and NO3 −  concentrations. An interpolation technique, known as ordinary kriging, was used to acquire the spatial distribution of parameters of groundwater quality parameters. The result showed that the groundwater quality falls under class I (>25%) and class II (25 to75%) category. The study recommends that the groundwater in the study area is not suitable for potable purposes, especially without any improved onsite water treatment facilities but it is appropriate for the irrigation purposes in City.

The Kabul River basin (KRB) of Afghanistan, a lifeline of around 10 million people, has multiplicity of governance, management and development related challenges leading to inequity, inadequacy and unreliability of irrigation water distribution. Prior to any uplifting intervention, there is a need to evaluate the performance of irrigation system on long term basis to identify the existing bottlenecks. Although there are several indicators used for the performance evaluation of the irrigation schemes, but we used the coefficient of variation (CV) of actual evapotranspiration (ETa) in space (basin, sub-basin, and provincial level), relative evapotranspiration (RET) and temporal CV of RET to assess the equity, adequacy and reliability of water distribution respectively, from 2003 to 2013. The ETa was estimated through surface energy balance system (SEBS) algorithm and the ETa estimates were validated using advection aridity (AA) method with R2 value of 0.81 and 0.77 at Nawabad and Sultanpur stations respectively. The global land data assimilation system (GLDAS) and moderate-resolution imaging spectroradiometer (MODIS) products were used as main inputs to the SEBS. Results show that mean seasonal sub-based RET values during summer (May – September) (0.37 ± 0.06) and winter (October – April) (0.40 ± 0.08) are below the target values (RET ≥0.75) during 2003-2013. The CV of mean ETa within sub-basins and provinces for the entire study period has equitable distribution of water from October-January (0.09±0.04) whereas the highest inequity (0.24±0.08) in water distribution is during early summer. The range of the CV of mean ETa (0.04-0.06) on monthly and seasonal basis shows the unreliability of water supplies in several provinces or sub-basins. The analysis of temporal CV of mean RET highlights unreliable water supplies across the entire basin. The maximum ETa during the study period was estimated for Shamal sub-basin (552±43mm) while among provinces Kunar experienced the highest ETa (544±39mm). This study highlights the dire need for interventions to improve the irrigation performance in time and space. The proposed methodology can be used as a framework for monitoring and implementing the water distribution plans in future.

Recent increases in the demand for automotive lithium-ion batteries (LIBs) have led to higher needs for critical materials like lithium, cobalt, nickel, and graphite. Consequently, recovering materials from spent batteries has gained importance. This study aimed to (1) develop a mechanical pre-treatment method for separating and concentrating materials from spent NCM622 cells, and (2) evaluate the economic, environmental, and scarcity potentials of these fractions. The pre-treatment involved grinding and granulometric separation, producing six particle-size fractions. Analysis showed that the finest fraction (n < 0.5 mm) had 85% of lithium, 77.4% of cobalt, 75.1% of manganese, and 68.5% of nickel. This fraction represented 40.4% of the processed mass and had the highest economic value (USD 3,669/ton NCM cell). This fraction was also prioritized for recycling due to its superior environmental and scarcity considerations.

Fresh water is an increasingly scarce resource in both urban and rural developments. As a response to this challenge, non-potable water reuse is on the rise. This research explored a potential off-grid system for water purification, consisting of a staircase wetland with terracotta pot plants working as a filter for greywater. The study further investigated the physicochemical properties of the greywater and the soil before and after the wetland purification. Results showed that the filtered water satisfied all requirements for water reuse, e.g., pH, turbidity, and total coliforms. The research then uniquely investigated the effect of greywater on the soil biodiversity and soil biomass using soil DNA extraction and the tea bag index testing method. The filtered greywater absorbed by soil decomposed the soil faster and stabilized it better compared to tap water-absorbed soil or unfiltered greywater. The DNA generation sequencing revealed no significant differences in alpha diversity between control and treatment samples. The beta diversity differences were significant. This nature-based solution can lead to reduced load on the sewage system, resulting in less wastewater generation.

The monitoring of surface-water quality followed by water-quality modeling and analysis is essential for generating effective strategies in water-resource management. However, worldwide, particularly in developing countries, water-quality studies are limited due to the lack of a complete and reliable dataset of surface-water-quality variables. In this context, several statistical and machine-learning models were assessed for imputing water-quality data at six monitoring stations located in the Santa Lucía Chico river (Uruguay), a mixed lotic and lentic river system. The challenge of this study is represented by the high percentage of missing data (between 50% and 70%) and the high temporal and spatial variability that characterizes the water-quality variables. The competing algorithms implemented belonged to both univariate and multivariate imputation methods (inverse distance weighting (IDW), Random Forest Regressor (RFR), Ridge (R), Bayesian Ridge (BR), AdaBoost (AB), Hubber Regressor (HR), Support Vector Regressor (SVR), and K-nearest neighbors Regressor (KNNR)). According to the results, more than 76% of the imputation outcomes are considered satisfactory (NSE > 0.45). The imputation performance shows better results at the monitoring stations located inside the reservoir than the ones positioned along the mainstream. IDW was the most chosen model for data imputation.

Cooperative and self-enforceable water allocation is a key instrument to manage geopolitical conflict induced by water scarcity, which necessitates concerning the cooperative willingness of the agents and considering their heterogeneity in geography, climate, hydrology, environment and social economy. Based on a multi-indicator system that contains asymmetric information on water volume contribution, current water consumption, water economic efficiency and efforts for eco-environmental protection, this study proposed a water allocation framework by combining the asymmetric power index approach with bankruptcy theory for solving the transboundary water allocation problem under scarcity. The proposed method was applied to the Yellow River Basin in northern China, which is mainly shared by nine provincial districts and frequently suffers from severe water shortage, and its results were compared with six alternative methods. The results highlight the necessity of quantifying agent’s willingness to cooperate under the background of asymmetric negotiation power when making decisions on transboundary water allocations. The proposed method allows to perform transboundary water allocations through simultaneous consideration of the agent’s cooperation willingness, asymmetric negotiation power as well as disagreement allocation points, which ensure the stability, fairness and self-enforceability of allocation results. Therefore, it can offer practical and valuable decision-making insights for transboundary water management under water scarcity.

This study investigates the sociological dimensions informing public perceptions of water scarcity during the El Niño drought period in Colombia. We conducted this study in Santa Marta, Colombia, and surveyed 405 urban and rural residents to understand their perceptions of water scarcity, management, and the impacts of the El Niño phenomenon. The survey used a Likert scale to measure responses and employed a multivariate analysis of variance to analyze the data while considering factors such as location (urban versus rural) and gender. The study results indicated that urban residents often experience an irregular water supply all year, whereas most rural respondents noted a more consistent availability of water. The perception of water scarcity also differed notably between urban and rural areas due to their different historical and cultural experiences (habitus). Urban respondents mostly recognized the presence of water, while rural perspectives were less conclusive, likely influenced by their direct access to natural water sources. Participants across various demographics consistently reported that poor management by local, regional, and national governments contributes to the water scarcity crisis, highlighting the widespread call for urgent reforms in water management policies and practices. Our research suggests that better understanding the social foundations of such perceptions using Bourdieu's concepts of social fields, habitus, and capital forms can significantly enhance water management strategies.

The global rising demand for exploiting limited shared groundwater resources, coupled with significant water deficit, especially in arid and semi-arid regions, has led to escalating conflicts among stakeholders. As such, using Bankruptcy Theory methods can be an appropriate response to the reallocation of resources. This study introduces a novel approach to weighted Bankruptcy, where the relative importance of stakeholders is determined by their contributions to sustainable development, and the impact of their claims on the shared groundwater resources is considered. The framework is implemented in a two-level bankruptcy process including the plains and their beneficiaries (agriculture, drinking and industry). The proposed two-level weighted bankruptcy process applies to the Neyshabour-Ataiyeh-Sabzevar plains in Iran. The process is implemented for two scenarios including the Baseline scenario related to the present status of demands and the Future scenario associated with the estimated demands for the year 2041. To compare the weighted proposed method with the other weighted methods such as Proportional (WPRO), Constrained Equal Awards (WCEA), Pinile (WPIN), Talmud (WTAL), Constrained Equal Losses (WCEL), Modified Constrained Equal Losses (MWCEL), two categories including the deficit-based and resource-based approaches are considered. According to the stability analysis using the Bankruptcy Allocation Stability Index (BASI) method, among the deficit-based methods, the novel approach is chosen as the preferred method for the beneficiaries’ reallocation like the Sabzevar’s beneficiaries. Accordingly, it allocates 86.95%, 10.86% and 2.17% of the shared resource to the agricultural, drinking, and industrial demands, respectively. Among the resource-based methods, the WPIN method is selected for reallocation between the stakeholders and their beneficiaries in each level and scenario of reallocation. The novel approach offers a promising solution to the water resource reallocation problem, ensuring a more equitable and sustainable management of shared groundwater resources.

CGT is composed of fiber residues, leaves, dust particles, soil and others derived during the ginning and yarn spinning process at processing industries,. In the cotton spinning industrial clusters, farmers are using CGT) as one of the alternative roughage feed for their sheep, mainly during forage shortages in the summer months. To have baseline information on farmers using gin and factors driving them to choose CGT as a roughage source, which need to be identified for future planning on the usage of CGT in sheep feeding. Considering the above facts, the present study was undertaken to assess socio-personal characteristics, managemental practices associated with farmers using cotton gin in the feeding of sheep and also identify the factors driving the choice of the CGT as the primary source of roughage in the cotton spinning industry cluster of Tamil Nadu. For this, a survey among 80 sheep farmers was carried out using a pre-tested in-terview schedule. The collected data was analysed using descriptive statistics and logit regres-sion. The results indicated that the majority of male, aged, and large-land farmers were involved in practicing CGT feeding during the summer and also indicated the non-availability of green fodder during the summer season. The coarse type of CGT preferred more than the fine type of CGT trash in that area due to quality perception and price. The replacement level of CGT as roughage ranged from 33 to 75% of the total roughage requirement per day. About 88 percent-age of farmers were highly satisfied with the results of using CGT and they also expressed that the presence of foreign particles and dust were the major problems with using CGT. The choice of CGT as primary roughage among sheep farmers was primarily influenced by selective farming contexts, namely landholding, access to labour, and feeding practices of other livestock with cotton gin. Further, research has to be focused on to improve the quality of CGT in the future, as it is being utilised largely by sheep farmers.

In the context of developing machine learning models, until and unless we have the required data engineering and machine learning development competencies as well as the time to train and test different machine learning models and tune their hyperparameters, it is worth trying out the automatic machine learning features provided by several cloud-based and cloud-agnostic platforms. This paper explores the possibility of generating automatic machine learning models with low-code experience. We have developed criteria to compare different machine learning platforms for generating automatic machine learning models and presenting their results. Thereafter, lessons learned by developing automatic machine learning models from a sample dataset across four different machine learning platforms were elucidated. We have also interviewed machine learning experts to conceptualize their domain-specific problems that automatic machine learning platforms could address. Results showed that automatic machine learning platforms could provide a fast track for organizations seeking digitalization of their businesses. Automatic machine learning platforms help produce results, especially for time-constrained projects where resources are lacking. The contribution of this paper is in the form of a lab experiment in which we demonstrate how low-code platforms could provide a viable option to many business cases and henceforth provide a lane that is faster than the usual hiring and training of already scarce data scientists and to analytics projects that suffer from overruns.

A framework for the review of existing water management systems and their transformation into robust water sharing systems is offered. The framework focuses on the need to develop efficient and equitable ways to manage water scarcity and plan to deal with the tensions scarcity imposes on any community. The framework identifies a way to bring together traditional community-managed systems with those typically used to allocate water to large water users and more commonly found in developed countries. So that use can be kept within sustainable limits while optimizing use, the framework includes mechanisms that enable the reallocation of water as demand and supply conditions change. Non-consumptive uses are recognized and environmental objectives can be delivered efficiently. Compliance with well-established accounting and hydro-logical concepts. Ways to increase the value of existing entitlements, encourage innovation and protect investments are included as options. It is recognized that the governance and legal arrangements necessary to underpin successful implantation are context specific.

This paper reviews the design and component of two types of RWHS, namely roof harvesting system (RHS) and pond harvesting system (PHS). The performance in terms of quantity and quality of collected rainwater and energy consumption for RWHS with different capacities were evaluated, as well as the benefits and challenges particularly in environmental, economic and social aspects. Presently, RHS is more commonly applied but its effectiveness is limited by its small scale. The PHS is of larger scale and has greater potentials and effectiveness as an alternative water supply system. Results also indicate the many advantages of PHS especially in terms of economics, environmental aspects and volume of water harvested. While RHS may be suited to individual or existing buildings, PHS has greater potentials and should be applied in newly developed urban areas with wet equatorial climate.

The heavy demand of water resources from the Zarqa River Basin (ZRB) has resulted in a base-flow reduction of the River from 5m³/s to less than 1m³/s. This paper aims at predicting Curve Numbers (CN) as a baseline scenario and proposing restoration scenarios for ZRB. The method includes classifying the soil type and land use, predicting CNs, and proposing CN restoration scenarios. Prediction of existing CNs will be in parallel with the runoff prediction using the US Army Corps of Engineers HEC-1 Model, and Rainfall-Runoff Model (RRM). The models have been set up at the land use distribution of 0.3% water body, 9.3% forest and orchard, 71% mixture of grass, weeds, and desert shrubs, 7.0% crops, 4.0% urban areas, and 8.4% bare soil. The results show that CN under dry condition are 59, 78 under a normal condition and 89 under a wet condition. During vegetation period, CN are 52, 72 and 86 for the dry, normal and wet condition respectively. The restoration scenarios; CN decreases runoff, and increases soil moisture when using the contours, terraces and crop residues. Analyzing results of CN scenarios will be a fundamental tool to support end-users related to their targets to achieve watershed restoration.

In water scarcity regions, using data-driven approaches to predict groundwater level is challenging due to limited data availability. However, these regions have substantial water needs and require cost-effective groundwater utilization strategies. In this study, we use artificial intelligence to predict groundwater levels to provide guidance for drilling shallow boreholes for subsistence irrigation. The Bilate watershed, which is located in southern Ethiopia, was selected as the study area. This is typical of areas in Africa with high demand for water and limited availability of well data. Using a non-time-series database of 75 boreholes, machine learning models including multiple linear regression, multivariate adaptive regression spline, artificial neural networks, random forest regression, and gradient boosting regression (GBR) were constructed to predict the depth to the water table. 20 independent variables were considered in the models. GBR performed the best of the approaches with an average 0.77 R-squared value on testing data. Finally, a map of predicted water levels in the Bilate watershed was created based on the best model with water levels ranging from 1.6 to 245.9 meters. With the limited set of borehole data, the results show a clear signal that can provide guidance for borehole drilling decisions for sustainable irrigation with additional implications for drinking water.

In times of water scarcity, water conservation measures from authorities are primarily directed to the residential sector—homeowners and renters who engage in individual activities to reduce water consumption. Business owners, manufacturers, and institutional workers—the ICI sector, generally, do not receive targeted information and education on water savings measures, and when they do, the information, typically, refers to indoor technologies, and behavior choice. In answer to this shortfall, this research illustrates how the ICI sector might engage in outdoor water conservation and, thus, realize water savings using the well-established Pittenger’s Simplified Landscape Irrigation Design Estimation (SLIDE) formula that estimates outdoor water conservation/savings for the lesser studied industrial, commercial, and institutional (ICI) sector. We applied the SLIDE formula five diverse climate areas in Texas to demonstrate the potential water savings in each, as well as identifying the type of water technology measures that yielded the greatest water savings for outdoor ICI landscapes. Overall, the greatest water savings for outdoor ICI landscapes was realized through smartscape design with soil moisture sensors-SMS technology, second best. Our findings will provide ICI facility owners/managers with knowledge and examples of a simplified system for quantitative decision making when considering choices among technologies and/or practices toward outdoor water conservation for their own facilities.

Fundamental science and applied research and technology development (RTD) are facing significant challenges that particularly compound to the notorious credibility, reproducibility, funding and sustainability crises. The underlying, serious shortcomings are substantially amplified by a metrics-obsessed publication culture, and a growing cohort of academics fishing for fairly stagnant (public) funding budgets. This work presents, for the first time, a groundbreaking strategy to successfully address these severe issues; the novel strategy proposed here leverages the distributed ledger technology (DLT) “blockchain” to capitalize on cryptoeconomic mechanisms, such as tokenization, consensus, crowdsourcing, smart contracts, reputation systems as well as staking, reward and slashing mechanisms. This powerful toolbox, which is so far widely unfamiliar to traditional scientific and RTD communities (“TradSci”), is synergistically combined with the exponentially growing computing capabilities for virtualizing experiments through digital twin methods in a future scientific “metaverse”. Project contributions, such as hypotheses, methods, experimental data, modelling, simulation, assessment, predictions and directions are crowdsourced using blockchain, and captured by so-called non-fungible tokens (“NFTs”). The so enabled, highly integrative approach, termed decentralized science (“DeSci”), is destined to move research out of its present silos, and to markedly enhance quality, credibility, efficiency, transparency, inclusiveness, sustainability, impact, and sustainability of a wide spectrum of academic and commercial research initiatives.