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Surface and ground waters can be considered the main sources of water supply for agricultural, municipal, and industrial consumers. Over the centuries, the combination of both naturally occurring conditions and humanity's actions has placed increasing pressure on these water resources. As an example, climate change and natural variability in the distribution and occurrence of water are among the natural driving forces that complicate the sustainable development of water resources. Recent advances in computer techniques have allowed scientists to develop complex models at different scales to support water-resource planning and management. The Special Issue "Advances in Flow Modeling for Water Resources and Hydrological Engineering" presents a collection of scientific contributions providing a sample of the state-of-the-art research in this field. [ABSTRACT FROM AUTHOR]

This document is an editorial that discusses the importance of water in agriculture, particularly in arid and semiarid regions, and the impact of irrigation on hydrological processes. It covers various research fields within agricultural hydrology, such as water-heat-salt-nutrients transport and evapotranspiration modeling, as well as remote sensing applications. The document provides an overview of published papers on this topic, highlighting research gaps and challenges in integrated agro-hydrological modeling, water resource management, non-point source pollution control, soil salinization, data-driven algorithms, and the use of remote sensing technology. It also lists research topics related to hydrology, including remote sensing, sustainability, ecohydrology, crop water requirement, drought assessment, and groundwater, with studies conducted in different regions such as China, South Africa, Pakistan, Sri Lanka, Brazil, and the USA. The document includes a list of research articles covering various subjects, such as the impacts of climate change on streamflow, water footprint of the animal breeding industry, reference evapotranspiration estimation methods, and the effects of controlled tile drainage on crop growth. The articles are authored by researchers from different countries, including China, Spain, the USA, and Sri Lanka. The document also provides information on the authors' contributions, data availability, and conflicts of interest. [Extracted from the article]

Benzene, toluene, ethylbenzene and xylenes, collectively known as BTEX compounds, are significant emerging contaminants in municipal wastewater. Stricter effluent quality regulations necessitate their removal, especially with concerns about organic micropollutant concentrations. Water scarcity further underscores the need for wastewater treatment to ensure safe agricultural or drinking water supplies. Although biological treatment partially reduces BTEX levels through processes like biodegradation and sorption, additional purification using physico-chemical methods is crucial for substantial reduction. This paper aims to outline plant-wide simulation methods for treating BTEX-contaminated sewage and facilitating reuse, adhering to IWA Good Modelling Practice Guidelines. The model, built upon the MiniSumo process model, incorporates equations detailing BTEX metabolism and removal kinetics, informed by an extensive literature review. Using a variant of the Benchmark Simulation Model with granular activated carbon for water reuse, the study examines strategies for improving effluent quality and minimizing operational costs. These strategies include adjusting the sludge retention time and airflow to enhance BTEX degradation and stripping, respectively, and comparing maintenance approaches for the GAC tower. [ABSTRACT FROM AUTHOR]

The rational management of water, which is determined by the Framework Directive 2000/60/EC of the EU, is a contractual obligation of the Agricultural Sector of Cyprus, both towards the European Union and the next generations of Cypriot citizens. To make decisions about sustainable water use and improve water use, it is necessary to understand the water use of crops in different water-use areas. Especially in large water projects in Cyprus, there must be a good way to determine the water use of crops so that the correct use of crops can be ensured, thus eliminating problems such as a lack of new information about the crop area and agricultural evaporation, Demand, and water. In most projects, water is managed and supplied based on historical data, and current information is available to determine water demand and availability for large areas. This paper also adds, apart from the clear positive effect of remote sensing and new technologies in crop irrigation, to the emerging need for advisory services for the diffusion of innovation to Cypriot farmers since the estimation of crop water requirements is part of estimating the carbon footprint under the project CARBONICA (EU Funded) for carbon farming. [ABSTRACT FROM AUTHOR]

Soil moisture plays a crucial role in various hydrological processes and energy partitioning of the global surface. The Soil Moisture Active Passive-Sentinel (SMAP-Sentinel) remote-sensing technology has demonstrated great potential for monitoring soil moisture with a maximum spatial resolution of 1 km. This capability can be applied to improve the weather forecast accuracy, enhance water management for agriculture, and managing climate-related disasters. Despite the techniques being increasingly used worldwide, their accuracy still requires field validation in specific regions like Thailand. In this paper, we report on the extensive in situ monitoring of soil moisture (from surface up to 1 m depth) at 10 stations across Thailand, spanning the years 2021 to 2023. The aim was to validate the SMAP surface-soil moisture (SSM) Level 2 product over a period of two years. Using a one-month averaging approach, the study revealed linear relationships between the two measurement types, with the coefficient of determination (R-squared) varying from 0.13 to 0.58. Notably, areas with more uniform land use and topography such as croplands tended to have a better coefficient of determination. We also conducted detailed soil core characterization, including soil–water retention curves, permeability, porosity, and other physical properties. The basic soil properties were used for estimating the correlation constants between SMAP and in situ soil moistures using multiple linear regression. The results produced R-squared values between 0.933 and 0.847. An upscaling approach to SMAP was proposed that showed promising results when a 3-month average of all measurements in cropland was used together. The finding also suggests that the SMAP-Sentinel remote-sensing technology exhibits significant potential for soil-moisture monitoring in certain applications. Further validation efforts and research, particularly in terms of root-zone depths and area-based assessments, especially in the agricultural sector, can greatly improve the technology's effectiveness and usefulness in the region. [ABSTRACT FROM AUTHOR]

Protein-based biostimulants (PBBs) are derived from the hydrolysis of protein-rich raw materials of plant and/or animal origins, usually by-products or wastes from agro-industries. The active ingredients (AIs) produced by hydrolysis have the capacity to influence physiological and metabolic processes in plants, leading to enhanced growth, nutrient and water-use efficiency, tolerance to abiotic and biotic stresses, and improved crop yield and quality. This paper reviews the state-of-the-art and future opportunities for use of PBBs, based on potential effects on the soil, crops, and sustainability (social, economic, environmental). In this case, two examples of PBBs (hydrolyzed wheat gluten and potato protein) and their effects on the early growth of three sugar beet varieties are described and discussed. Both PBBs have a significant stimulating effect on early sugar beet growth and development. The opportunity to develop PBBs into superabsorbent polymers (SAPs) is discussed. To conclude, PBBs/SAPs developed from agro-industrial wastes have the potential for sustainably supplying water and nutrients in agricultural systems and for enhancing plant growth and development over a substantial period. [ABSTRACT FROM AUTHOR]

Water quality and quantity are critical issues as the Florida's population grows. This paper analyzed water use regionally (central, north, and south Florida) as well as in rural and urban areas in Florida from 2005 to 2015 using three indicators (total water use, agriculture water use, and per capita water use). Eight (8) water-consuming categories, such as aquaculture, livestock, irrigation, public supply, thermoelectric power, mining, industrial self-supply, and domestic self-supply, were considered for total water use. Per capita water use used public supply category and agricultural water use used aquaculture, livestock, and irrigation categories. Linear regression analysis was used to observe the relationship between population and water use. The highest water use was recorded in south Florida, while the lowest was in north Florida. Water use per capita was higher in urban areas. Irrigation water use was higher among the eight water use categories. Many drivers influencing Florida water use were identified through literature review and causal loop diagram was developed. Some (e.g., household size, land use/land cover change, urbanization, agriculture, population, income, climate change, tourism, and industry) may cause an increase in water use, while others (e.g., pricing systems, conservation methods, education, and technology) may cause a decrease in water use. Overall, this research addresses the need of understanding water use trends and the drivers affecting those trends, which are important to determine whether a water conservation plan is needed. [ABSTRACT FROM AUTHOR]

Proper agricultural water management in arid regions is the key to tackling climatic risks. However, an effective assessment of the current response to climate change in agricultural water use is the precondition for a group adaptation strategy. The paper, taking the Tarim River basin (TRB) as an example, aims to examine the agricultural water use sustainability of water resource increase caused by climatic variability. In order to describe the response result, groundwater change has been estimated based on the Gravity Recovery and Climate Experiment (GRACE) and the Global Land Data Assimilation System (GLDAS)-Noah land surface model (NOAH) data. In order to better understand the relationship between water resource increase and agricultural water consumption, an agricultural water stress index has been established. Agricultural water stress has been in a severe state during the whole period, although it alleviated somewhat in the mid-late period. This paper illustrates that an increase in water supply could not satisfy agricultural production expansion. Thus, seasonal groundwater loss and a regional water shortage occurred. Particularly in 2008 and 2009, the sharp shortage of water supply in the Tarim River basin directly led to a serious groundwater drop by nearly 20 mm from the end of 2009 to early 2010. At the same time, a regional water shortage led to water scarcity for the whole basin, because the water consumption, which was mainly distributed around Source Rivers, resulted in break-off discharge in the mainstream. Therefore, current agricultural development in the Tarim River basin is unsustainable in the context of water supply under climatic risks. Under the control of irrigation, spatial and temporal water allocation optimization is the key to the sustainable management of the basin. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is a major component of the water cycle and agricultural water balance. Estimation of water consumption over agricultural areas is important for agricultural water resources planning, management, and regulation. It leads to the establishment of a sustainable water balance, mitigates the impacts of water scarcity, as well as prevents the overusing and wasting of precious water resources. As evapotranspiration is a major consumptive use of irrigation water and rainwater on agricultural lands, improvements of water use efficiency and sustainable water management in agriculture must be based on the accurate estimation of ET. Applications of precision and digital agricultural technologies, the integration of advanced techniques including remote sensing and satellite technology, and usage of machine learning algorithms will be an advantage to enhance the accuracy of the ET estimation in agricultural water management. This paper reviews and summarizes the technical development of the available methodologies and explores the advanced techniques in the estimation of ET in agricultural water management and highlights the potential improvements to enhance the accuracy of the ET estimation to achieve precise agricultural water management. [ABSTRACT FROM AUTHOR]

Affected by the temporal and spatial changes of natural resources, human activities, and social economic system policies, there are many uncertainties in the development, utilization, and management process of irrigation district agricultural water resources, which will increase the complexity of the use of irrigation district agricultural water resources. Decision makers find it challenging to cope with the complexity of fluctuating water supplies and demands that are critical for water resources' allocation. In response to these issues, this paper presents an optimization modeling approach for agricultural water allocation at an irrigation district scale, considering the uncertainties of water supply and demand. The minimum cross-entropy method was used to estimate the parameters of hydrologic frequency distribution functions of water supply and demand, which are the basis for agricultural water resources' optimal allocation and the evaluation of water resources' carrying capacity in the Hetao Irrigation District. Interval Linear Fractional Programming was used to find water availability, shortage, and use efficiency in different irrigation areas of the Hetao Irrigation District (HID) under different scenarios. The denominator of fractional planning is the environmental goal, and the numerator is the economic goal; so, the objective function of fractional programming is the utility rate required in the post-optimization analysis. Future water availability and shortage scenarios are adopted consistent with the Representative Concentration Pathways' (RCPs') framework, and future water use scenarios are developed using the Shared Socioeconomic Pathways' (SSPs') framework. Results revealed that under SSP1, the annual water consumption increased from 30 billion m3 to 60 billion m3, almost doubling in Urad. The annual water consumption under SSP2 and SSP3 increased slightly, from 30 billion m3 to about 50 billion m3. The amount of water available for well irrigation in Urad decreased from 300 to 250 billion m3, while the amount of water available for canal irrigation in Urad remained at 270 billion m3 from 2010 s to 2030 s, only dropping to 240 billion m3 in 2040 s. The entropy-weight-based Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method was applied to evaluate agricultural water resources' allocation schemes because it can avoid the subjectivity of weight determination and can reflect the dynamic changing trend of irrigation district agricultural water resources' carrying capacity. The approach is applicable to most regions, such as the Hetao Irrigation District in the Upper Yellow River Basi with limited precipitation, to determine water strategies under the changing environment. [ABSTRACT FROM AUTHOR]

The Xiaolangdi Dam is a key project for the control and development of the Yellow River. It bears the functions of flood control, controlling water and sediment in the lower reaches, ice prevention, industrial and agricultural water supply, power generation, and so on. Its safety is related to people's life and property safety and local economic and social development. It is of great significance to carry out comprehensive and regular deformation monitoring for dams since the deformation is an important evaluation index for dam safety. Interferometric Synthetic Aperture Radar (InSAR) technology has been a rapidly evolving technology in the field of space geodesy in recent years. It offers advantages such as high monitoring precision, extensive coverage, and high monitoring point density, making it a powerful tool for monitoring deformations in hydraulic engineering projects. Based on Sentinel-1 data covering the Xiaolangdi Dam from September 2020 to November 2022, the PS-InSAR technique was used to obtain the surface deformation of the Xiaolangdi Dam, and reservoir water level data on image acquisition dates were obtained for joint analysis. The results show that there is a large deformation in the center of the dam crest of the Xiaolangdi Dam, while both sides of the slope and downstream dam foot are relatively stable. The time series deformation of the dam body is closely related to the reservoir water level change. When the water level increases, the dam body tends to deform downstream; when the water level decreases, the dam body tends to deform upstream. The deformation and water level of the Xiaolangdi Dam exhibit a clear negative correlation. There is no significant cumulative deformation on the dam slopes or at the base of the dam. However, cumulative deformation occurs over time in the central area of the dam's crest. The deformation process at the central area of the dam's crest follows a continuous and non-disruptive pattern, which is consistent with the typical deformation behavior of the Xiaolangdi earth–rock dam structure. Therefore, it is judged that the current deformation of the Xiaolangdi Dam does not impact the safe operation of the dam. InSAR technology enables the rapid acquisition of high-precision, high-density deformation information on the surfaces of reservoir dams. With an increasing number of radar satellites in various frequency bands, such as Sentinel-1 and TerraSAR-X, there is now an ample supply of available data sources for InSAR applications. Consequently, InSAR technology can be extended to routine monitoring applications for reservoir dam deformations, especially for small and medium-sized reservoirs that may not be equipped with ground measurement tools like GNSS. This holds significant importance and potential for enhancing the safety monitoring of such reservoirs. [ABSTRACT FROM AUTHOR]

This paper presents an informal process inspired by a public practice of conflict mediation used until a few decades ago in Gallura (NE Sardinia, Italy), named La Rasgioni (The Reason). The aim is twofold: (i) to introduce an innovative method that translates the complexity of water-related conflicts into a "dialogical tool", aimed at enhancing social learning by adopting theatrical techniques; and (ii) to report the outcomes that emerged from the application of this method in Arborea, the main dairy cattle district and the only nitrate-vulnerable zone in Sardinia, to mediate contrasting positions between local entrepreneurs and representatives of the relevant institutions. We discuss our results in the light of four pillars, adopted as research lenses in the International research Project CADWAGO (Climate Change Adaptation and Water Governance), which consider the specific "social-ecological" components of the Arborea system, climate change adaptability in water governance institutions and organizations, systemic governance (relational) practices, and governance learning. The combination of the four CADWAGO pillars and La Rasgioni created an innovative dialogical space that enabled stakeholders and researchers to collectively identify barriers and opportunities for effective governance practices. Potential wider implications and applications of La Rasgioni process are also discussed in the paper. [ABSTRACT FROM AUTHOR]

This paper analyses the agricultural irrigation water use in a closed basin and the impacts on water productivity, and examines how they have affected the 'closure' process of the Guadalquivir river basin observed in recent decades. Following a period of expansion in irrigation, an administrative moratorium was declared on new irrigated areas in 2005. Since then, the main policy measure has been aimed at the modernisation of irrigated agriculture and the implementation of water conservation technologies. The analysis carried out in this paper shows a significant increase in mean irrigation water productivity in the pre-moratorium period (1989-2005), driven by the creation of new irrigated areas devoted to high value crops and with a dominant use of deficit irrigation strategies, while a second phase (2005-2012) is characterised by slower growth in terms of the mean productivity of irrigation water, primarily as a result of a significant reduction in water use per area. Findings show that productivity gains seem to have reached a ceiling in this river basin, since technological innovations (such as new crops, deficit irrigation, and water-saving and conservation technologies) have reached the limits of their capacity to create new value. [ABSTRACT FROM AUTHOR]

This study focuses on the promising use of biospeckle technology to detect water stress in plants, a complex physiological mechanism. This involves monitoring the temporal activity of biospeckle pattern to study the occurrence of stress within the leaf. The effects of water stress in plants can involve physical and biochemical changes. Some of these changes may alter the optical scattering properties of leaves. The present study therefore proposes to test the potential of a biospeckle measurement to observe the temporal evolution in different varieties of sunflower plants under water stress. An experiment applying controlled water stress with osmotic shock using polyethylene glycol 6000 (PEG) was conducted on two sunflower varieties: one sensitive, and the other more tolerant to water stress. Temporal monitoring of biospeckle activity in these plants was performed using the average value of difference (AVD) indicator. Results indicate that AVD highlights the difference in biospeckle activity between day and night, with lower activity at night for both varieties. The addition of PEG entailed a gradual decrease in values throughout the experiment, particularly for the sensitive variety. The results obtained are consistent with the behaviour of the varieties submitted to water stress. Indeed, a few days after the introduction of PEG, a stronger decrease in AVD indicator values was observed for the sensitive variety than for the resistant variety. This study highlights the dynamics of biospeckle activity for different sunflower varieties undergoing water stress and can be considered as a promising phenotyping tool. [ABSTRACT FROM AUTHOR]

The Czech Republic has diverse soil conditions, which cause notable differences in crop water balance (WB). To assess the long-term crop WB and crop water stress (CWS) intensity in rainfed conditions, four conventional eight- and ten-year crop rotations (CRs) with perennial forage (alfalfa), cereals, oilseeds, root crops and legumes were proposed for a heterogeneous lowland soil region (six texture classes) in eastern Bohemia. Two of the CRs were selected irrespective of the WB (eight-year, C-8; ten-year, C-10), and the other two were designated according to soil water resources and crop water requirements (CWRs) as water-saving (W-S) and water-demanding (W-D) for this region. All CRs had a negative WB on average (i.e., CWRs exceeded the available water resources), with varying degrees of CWS (categories 1 (low) to 4 (high)). The W-S CR reduced the WB deficit relative to the other CRs by omitting maize, sunflower and sugar beet and including sorghum, and expanded the proportion of the area not affected by CWS (categories 1–2) to 33% for predominantly loamy soils. In contrast, categories 1–2 in the C-8, C-10 and W-D CRs represented only 15%, 14% and 7% of the area, respectively. Other areas were significantly affected by CWS (categories 3–4) and showed a high risk of yield reduction. These results may help in implementing sustainable farming systems that consider environmental perspectives related to agricultural water use in Central Europe. [ABSTRACT FROM AUTHOR]

Two types of farmer-level mechanisms have been traditionally adopted to increase agricultural water use efficiency in northern China: pricing mechanisms and tradable water rights systems. However, the reluctance of policymakers to exacerbate farmers' burdens has rendered pricing mechanisms politically infeasible, while tradable water rights systems involve prohibitively high transaction costs in rural China. An experiment conducted in 2005 in the Taocheng District of Hebei Province created a new kind of water-saving mechanism that involves a number of institutional innovations, including "flexible total management", "collect then refund" and "collect and subsidize, then refund". This paper evaluates the district's water-saving mechanisms based on efficiency, equity and operability criteria. The results of the analysis demonstrate that the "collect then refund" mechanism can more effectively enhance water use efficiency and reduce farmers' burdens than water pricing instruments, tradable water rights systems and flexible total management. Adequate infrastructure and trusted institutions are identified as necessary prerequisites for the successful implementation of the new water-saving mechanism. We believe the new mechanism has great potential to be scaled up. [ABSTRACT FROM AUTHOR]

The paper explores how agricultural water pricing could contribute to lowering water demand when uses are unobserved (asymmetric information). The topic of the paper is justified by the fact that most water authorities worldwide do not control water uses at the farm scale. The study draws inspiration from the pricing policies of a Reclamation and Irrigation Board in Northern Italy. It analyses the optimal design of current tariff strategies with respect both to the actual regulator's goals and the cost recovery objective of an ideal regulator driven by European Water Framework Directive principles and having full information. The analysis is based on the logic of a Principal-Agent model implemented as a mathematical non-linear programming model. Given the current pricing structure and assuming zero transaction costs, the results show a relevant increase in net benefits for the ideal scenario with respect to the actual one as water use costs increase. Benefits differences between the two scenarios mark a limit in value below which mechanisms able to solve the existing asymmetries between the principal and the agents are economically desirable. The study concludes by showing that the current regulator's discriminatory strategy (pricing structure) would be better justified with higher levels of cost for water use. However, the existence of non-zero transaction costs related to the control of water uses points to the need for further research in order to analyze incentive mechanisms in the absence of water metering. [ABSTRACT FROM AUTHOR]

The present study explores the value generated by the use of information to rationalize the use of water resources in agriculture. The study introduces the value of information concept in the field of irrigation developing a theoretical assessment framework to evaluate whether the introduction of "Precision Irrigation" (PI) practices can improve expectations on income. This is supported by a Stakeholders consultation and by a numerical example, using secondary data and crop growth models. The study reveals that the value generated with the transition to PI varies with pedo-climate, economic, technological and other conditions, and it depends on the initial status of the farmer's information environment. These factors affect the prerequisite needed to make viable PI. To foster the adoption of PI, stakeholders envisaged the need to set up free meteorological information and advisory service that supports farmers in using PI, as well as other type of instruments. The paper concludes that the profitability of adoption and the relevant impact on the environment cannot be considered as generally given, but must be evaluated case by case justifying (or not) the activation of specific agricultural policy measures supporting PI practices to target regions. [ABSTRACT FROM AUTHOR]

In California, alfalfa is grown on a large area ranging between 325,000 and 410,000 hectares and ranks among the thirstiest crops. While the hay production industry is often scrutinized for the large usage of the state's agricultural water, alfalfa is a crucial feed-supplier for the livestock and dairy sectors, which rank among the most profitable commodity groups in the state. Sub-surface drip irrigation (SDI), although only practiced on approximately 2% of the alfalfa production area in California, is claimed to have the potential to significantly increase hay yield (HY) and water productivity (WP) compared with surface irrigation (SI). In 2014-2016 we interviewed a number of growers pioneering SDI for alfalfa production in Central and Southern California who reported that yield improvements in the order of 10-30% and water saving of about 20-30% are achievable in SDI-irrigated fields compared with SI, according to their records and perceptions collected over few years of experience. Results from our research on SDI at the University of California, Davis, revealed significantly smaller yield gain (~5%) and a slight increase of water use (~2-3%) that are similar to findings from earlier research studies. We found that most of the interviewed alfalfa producers are generally satisfied with their SDI systems, yet face some challenges that call for additional research and educational efforts. Key limitations of SDI include high investment costs, use of energy to pressurize water, the need for more advanced irrigation management skills, and better understanding of soil-water dynamics by farm personnel. SDI-irrigated fields also need accurate water monitoring and control, attentive prevention and repair of rodent damages, and careful salinity management in the root zone. In this paper we attempt to evaluate the viability of the SDI technology for alfalfa production on the basis of preliminary results of our research and extension activities, with focus on its water and energy footprints within the context of resource efficiency. [ABSTRACT FROM AUTHOR]

The purpose of the study is to assess whether Corporate Social Responsibility regarding water is considered relevant for sustainability in companies related to agriculture in South Africa, considering that their impact directly influences public access to water. To accomplish this purpose, a qualitative approach was developed through the study of the 22 existing companies from the agriculture sector, food and beverages, forest and paper production, and Tobacco, which published their last integrated report within the Global Reporting Initiative framework. A thematic content analysis was carried out, involving the analysis of the written sustainability reports. For data analyses, ATLAS.ti 7.1 software was used to match the main aspects related to water management. Pragmatic advice for practitioners derives from the research results, considering that Corporate Social Responsibility in general--and sustainable water management in particular--represents an opportunity for companies to get competitive advantages in the market. The study also determines the best practices in the field in South Africa with benchmarking purposes. [ABSTRACT FROM AUTHOR]

Modern agriculture faces the dual challenge of ensuring sustainability while meeting the growing global demand for food. Smart agriculture, which uses data from the environment and plants to deliver water exactly when and how it is needed, has attracted significant attention. This approach requires precise water management and highly accurate real-time monitoring of crop water stress. Existing monitoring methods pose challenges such as the risk of plant damage, costly sensors, and the need for expert adjustments. Therefore, a low-cost, highly accurate water stress estimation model was developed that uses deep learning and commercially available sensors. The model uses the relative stem diameter as a water stress index and incorporates data from environmental sensors and an RGB camera, which are processed by the proposed daily normalization. In addition, domain adaptation in our Transformer model was implemented to enable robust learning in different areas. The accuracy of the model was evaluated using real cultivation data from tomato crops, achieving a coefficient of determination (R2) of 0.79 in water stress estimation. Furthermore, the model maintained a high level of accuracy when applied to different areas, with an R2 of 0.76, demonstrating its high adaptability under different conditions. [ABSTRACT FROM AUTHOR]

Prolonged drought exacerbated by climate change in the Mesilla Valley, one of the major agricultural areas of New Mexico, USA, is causing a shortage of surface water from the Rio Grande for irrigation. Farmers in the Valley are using groundwater for irrigation and complementing it with limited surface water from the river (Rio Grande). Managing irrigation water better is vital to sustaining agriculture in the Valley. Remote sensing (RS)-based crop evapotranspiration (ETa) models offer significant advantages over traditional methods. The ET maps generated by these RS models provide valuable information that can be used to manage irrigation water and crops in water-scarce areas. This study used METRIC and SSEBop RS models to map the ET of alfalfa on a private farm that is managed as commonly practiced in the Valley. The integrated ET values of the two models are compared to those of the ETa measured using the eddy covariance method. The comparison showed that 91.55% of the variability in SSEBop ETa estimates can be explained by the variability in the METRIC ETa estimates, and the variability in eddy covariance ETa can explain 93.07% of the variability in METRIC ETa and 86.01% in the SSEBop Eta estimates. Both METRIC and SSEBop reflected the ETa of alfalfa during full growth and harvesting periods. However, the absolute percent mean relative difference (MRD) of ET was higher for two out of three cuttings by SSEBop (>32%) compared to those for METRIC and eddy covariance. The spatiotemporal variabilities in crop ET estimates using METRIC and SSEBop showed a need to improve on-farm irrigation conveyance and on-the-field irrigation efficiency. Overall, RS models can provide spatiotemporal maps of ET that can be used for decision-making to manage irrigation water better and improve crop yield on a field, farm, and regional scale. [ABSTRACT FROM AUTHOR]

In the Yinchuan Plain, the main source of water supply for agricultural crops is irrigation infiltration. Therefore, the irrigation process, method, and time are crucial for the rational planning and utilization of water resources in the region. In this study, the effects of different irrigation methods on groundwater recharge were investigated through irrigation quadrat tests combined with numerical simulations. The water content at depths of 10–50 cm had a more significant response to irrigation than that at 80 and 100 cm in the intelligent irrigation quadrat. The water content change at depths of 10–50 cm was smaller than that at 80 and 100 cm in the flood irrigation quadrat. The flood irrigation method had a greater impact on the water content in the deep vadose zone. The water content of intelligent irrigation was concentrated at depths of 30–50 cm, with weak groundwater recharge. The water content of the flood irrigation quadrat was concentrated at depths of 50–80 cm, with a significant impact in the vertical direction. The simulation results indicated that flood irrigation had the best effect on groundwater recharge, with an infiltration recharge coefficient of 0.73, compared to intelligent irrigation, which had an infiltration recharge coefficient of 0.41. When the groundwater depth range was 0.65–3.8 m, the infiltration recharge efficiencies of intelligent and flood irrigation were the highest at groundwater depths of 1.3 and 1.8 m. Our findings provide a scientific basis for methods of rational irrigation, which could help save water resources in the study area. [ABSTRACT FROM AUTHOR]

Accurate crop classification is of vital importance for agricultural water management. Most researchers have achieved crop classification by model optimization in the same temporal and regional domain by adjusting the value of input features. This study aims to improve the accuracy of crop classification across temporal and spatial domains. Sentinel-2 satellite imagery is employed for crop classification training and prediction in selected farming areas of Heilongjiang Province by calculating vegetation indices and constructing sequential input feature datasets. The HUNTS filtering method was used to mitigate the influence of cloud cover, which increased the stability and completeness of the input feature data across different years. To address the issue of shifts in the input feature values during cross-scale classification, this study proposes the hypothesis testing distribution method (HTDM). This method balances the distribution of input feature values in the test set even without knowing the crop distribution, thereby enhancing the accuracy of the classification test set. The results indicate that the HTDM significantly improves prediction accuracy in cases of substantial image quality variance. In 2022, the recognition accuracy for crop types at all farms processed by the HTDM was above 87%, showcasing the strong robustness of the HTDM. [ABSTRACT FROM AUTHOR]

The Heihe River is the second largest river in arid areas of China, and the irrigation water of oasis agriculture in its middle reaches accounts for almost 80% of the water resources in the whole watershed. Corn is the most important crop in the middle reaches of the Heihe River, and its water consumption is about 50% of the total agriculture water consumption of the middle reaches. Therefore, in order to effectively use the water resources in the watershed, it is crucial to improve the efficiency of corn irrigation. In this paper, using the Ganzhou District in the middle reaches of the Heihe River as the study region, we carried out a field survey to obtain characteristics of seed and field corn. Based on our results, we conducted parameter calibration using the CROPWAT model and calculated the irrigation water requirements (IWR) of these two corn types. The irrigation water requirements of seed and field corn in the growing seasons were 470.1 and 488.5 mm, respectively. However, we observed big differences in the water consumption sequences of these two corn types. Prior to mid-July, evapotranspiration and IWR of seed corn were 14.3% and 20.1% higher, respectively, than those of field corn. In September, IWR of the two corn types started to decrease, with a value of 82.3 mm for seed corn, which was 32.1% lower than the IWR of field corn (108.7 mm) during the same period. However, there were no significant differences in the irrigation time and single irrigation amount for seed and field corn in the study area. Since corn is widely cultivated in the Zhangye Region, there is a considerable water-saving potential in agriculture if the irrigation water consumption can be adjusted according to the IWR of the two corn types. [ABSTRACT FROM AUTHOR]

As water trading has become increasingly used to optimize the allocation of water resources, it has become necessary to transfer agricultural water allocations for economic development and ecological environmental uses by way of water rights trading. In this paper, we constructed an example water rights trading model in the arid oasis area of Shihezi Irrigation District (located in Northwest China), using the field investigation method and governmental water management decisions based on the systems theory of the agricultural water savings–economy–ecological environment. Furthermore, focusing on the added industrial value produced by trading water, the value of the ecological services provided by fresh water, the negative value of the reduction in greenhouse gas emissions, and the negative ecological value of reduced fertilizer application, a quantitative analysis was carried out using the Shihezi Irrigation District as an example. The results showed that under the most stringent water resource management plan and with the objective of returning land and reducing water, the irrigation area can save 52,504,500 m3 of surplus water from the agricultural sector, of which 49,879,300 m3 can be reallocated to the industrial sector and 2,625,200 m3 can be reallocated to the ecological sector. Using the water rights transaction method, this regional agricultural water saving could generate an industrial benefit equal to 35,024,300 yuan, an ecosystem service equal to 19,482,200 yuan, and an overall benefit equal to 54,420,500 yuan. The water rights trading model proposed in this paper for an arid oasis areas can provide a reference for other arid areas, helping to achieve the sustainable economic development of the economic and ecological environments in arid oasis areas through water rights trading. [ABSTRACT FROM AUTHOR]

Irrigation districts are a pivotal infrastructure of agricultural water conservancy engineering. Implementing modernization will be the main task of large-scale irrigation districts for a considerable amount of time in the future. In this study, four typical large-scale irrigation districts in North China were investigated: the Renmin Shengliqu, Weishan, Shijin, and Zuncun irrigation districts. The concept of a modern irrigation district was deconstructed to establish an evaluation index system which includes four second-level indicators, twelve third-level indicators, and thirty fourth-level indicators. A hybrid approach based on AHP and OWA was used to quantify indicator weights used in group decision making. TOPSIS was introduced to measure the modernization level of the four irrigation districts. An obstacle factor diagnosis model was applied to search for key obstacle factors that will affect the modernization and improvement of the irrigation districts. The results showed that (1) the modernization levels of the Renmin Shengliqu, Weishan, Shijin, and Zuncun irrigation districts in 2020 and 2025 were 0.3916 and 0.5755, 0.3748 and 0.5396, 0.4493 and 0.6012, and 0.2343 and 0.6166, respectively. The evaluation results indicate that the four irrigation districts are still in the beginning phase (or even preparation phase) of the modernization process. (2) Eight indicators were identified as the main common obstacle factors for the four evaluated irrigation districts, including the irrigation water-use efficiency factor, the coverage proportion of information technology, the proportion of efficient water conservation irrigation areas, and so on. (3) There are two effective methods to enhance the modernization level of the four irrigation districts: improving water resource utilization efficiency and strengthening the management system with an emphasis on informatization. The present study can enrich the theoretical evaluation of irrigation districts and provide a scientific basis for the modernized construction and management of irrigation districts in China. [ABSTRACT FROM AUTHOR]

The sustainable management of water scarcity is a globally crucial issue. Germany has established efficient water management systems, but the agricultural sector still struggles with water scarcity as the demand surpasses the available water supply. In this work, the primary aim was to establish a framework for making water accessible for irrigation and additional use in households through the effective utilization of recycled water from wastewater treatment facilities. The research inquiries were focused on evaluating the changes in the CROPWAT agricultural irrigation model, determining the spatial distribution of zonal severity, estimating the capacity of urban roof catchments, and evaluating the economic value addition of retreated water 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, the demand for irrigation water increases during the development, active growth, and mature stages of maize, winter wheat, and wine grapes, reaching around 189 mm, 223 mm, and 63 mm, respectively. According to our observations, the annual water supply in Weinstadt is around 4 million m3. On the other hand, the compensated volume of water to the current water supply calculated from the urban roof rainfall is estimated to be 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, which indicates an opportunity for enhanced agricultural irrigation. [ABSTRACT FROM AUTHOR]

As part of its nationally determined contributions as well as national forest policy goals, India plans to boost tree cover to 33% of its land area. Land currently under other uses will require tree-plantations or reforestation to achieve this goal. This paper examines the effects of converting cropland to tree or forest cover in the Central India Highlands (CIH). The paper examines the impact of increased forest cover on groundwater infiltration and recharge, which are essential for sustainable Rabi (winter, non-monsoon) season irrigation and agricultural production. Field measurements of saturated hydraulic conductivity (Kfs) linked to hydrological modeling estimate increased forest cover impact on the CIH hydrology. Kfs tests in 118 sites demonstrate a significant land cover effect, with forest cover having a higher Kfs of 20.2 mm h−1 than croplands (6.7 mm h−1). The spatial processes in hydrology (SPHY) model simulated forest cover from 2% to 75% and showed that each basin reacts differently, depending on the amount of agriculture under paddy. Paddy agriculture can compensate for low infiltration through increased depression storage, allowing for continuous infiltration and groundwater recharge. Expanding forest cover to 33% in the CIH would reduce groundwater recharge by 7.94 mm (−1%) when converting the average cropland and increase it by 15.38 mm (3%) if reforestation is conducted on non-paddy agriculture. Intermediate forest cover shows however shows potential for increase in net benefits. [ABSTRACT FROM AUTHOR]

As an important agricultural production area in China, the Yangtze River Economic Belt has a large amount of water resources and rich types of energy. Water and energy resources are the supporting basis of food production, and the production and use of energy also need to consume a large amount of water resources. The three affect each other and are interdependent. Paying attention to the synergistic security of water-energy-food system in the Yangtze River Economic Belt is important for regional economic development. This paper uses the pressure-state-response (PSR) model and selects 27 indicators to build an evaluation index system of the regional water-energy-food system. We use the random forest model to evaluate the security level of the Yangtze River Economic Belt from 2008 to 2017, and the Haken model is employed to identify the driving factors that dominate the synergistic evolution of the system. Then we take the identified factors as the key control variables under each scenario and launch a scenario simulation of some provinces in the Yangtze River Economic Belt in 2025. The results show that due to the improvement of water and energy utilization efficiency and the advancement of agricultural production technology, the level of water-energy-food security in the Yangtze River Economic Belt improved significantly from 2008 to 2017. Each province performs differently in different subsystems, with water resources security being better in the upper reaches and Zhejiang and Shanghai in the lower reaches, and food security being better in the middle and lower reaches. The level of energy security is high in Sichuan, Yunnan, and Guizhou in the upper reaches and Shanghai and Anhui in the lower reaches. According to the results of scenario prediction for Jiangsu Province and Hubei Province in 2025, implementing moderate management in accordance with current management objectives can increase the overall security of the system to level 4. The two provinces should focus on controlling water resources and energy consumption and improving the utilization efficiency of water and energy in agricultural production. [ABSTRACT FROM AUTHOR]

To better understand farmers' refusal to pay agricultural water fees under the current policy in rural China and their corresponding negative emotions, this paper applies mental accounting, a behavioral economics framework, to explore how the governmental policies of reform of rural taxes and fees, direct agricultural subsidy programs, and agricultural water fees individually influence farmers' decisions in paying the agricultural water fees. Using fieldwork data from 577 farmers and 20 water managers in Sichuan, we explore farmers' information processing regarding paying agricultural water fees via three sequential mental accounting processes, with the associated underlying principles and measures behind each process. We find that the information processing in three mental accounting scenarios related to the agricultural water fee elucidates farmers' observed behaviors in rural China. Generally, in the three mental accounting scenarios, two conditional intuitive expectations and nine conditional intuitive preferences are formed; however, the conditions of those expectations or preferences cannot be matched with the facts due to the reform of rural taxes and fees, the direct agricultural subsidy programs, and the internal attributes of agricultural water fee, which interpret those negative behaviors in rural China. Additionally, this paper offers a view into how previous policies create negative psychological externalities (such as farmers' psychological dependence on the government) through mental accounting to negatively influence agents' subsequent decision-making; it highlights the significance of underlying mental factors and information processing of negative behaviors in policymaking for managing or conserving common pool resources. [ABSTRACT FROM AUTHOR]

The estimation of site water budget is important in Mediterranean areas, where it represents a crucial factor affecting the quantity and quality of traditional crop production. This is particularly the case for spatially fragmented, multi-layer agricultural ecosystems such as olive groves, which are traditional cultivations of the Mediterranean basin. The current paper aims at demonstrating the effectiveness of spatialized meteorological data and remote sensing techniques to estimate the actual evapotranspiration (ETA) and the soil water content (SWC) of an olive orchard in Central Italy. The relatively small size of this orchard (about 0.1 ha) and its two-layer structure (i.e., olive trees and grasses) require the integration of remotely sensed data with different spatial and temporal resolutions (Terra-MODIS, Landsat 8-OLI and Ikonos). These data are used to drive a recently proposed water balance method (NDVI-Cws) and predict ETA and then site SWC, which are assessed through comparison with sap flow and soil wetness measurements taken in 2013. The results obtained indicate the importance of integrating satellite imageries having different spatio-temporal properties in order to properly characterize the examined olive orchard. More generally, the experimental evidences support the possibility of using widely available remotely sensed and ancillary datasets for the operational estimation of ETA and SWC in olive tree cultivation systems. [ABSTRACT FROM AUTHOR]

A wide variety of pollutants are discharged into water bodies like lakes, rivers, canal, etc. due to the growing world population, industrial development, depletion of water resources, improper disposal of agricultural and native wastes. Water pollution is becoming a severe problem for the whole world from small villages to big cities. The toxic metals and organic dyes pollutants are considered as significant contaminants that cause severe hazards to human beings and aquatic life. The microbial fuel cell (MFC) is the most promising, eco-friendly, and emerging technique. In this technique, microorganisms play an important role in bioremediation of water pollutants simultaneously generating an electric current. In this review, a new approach based on microbial fuel cells for bioremediation of organic dyes and toxic metals has been summarized. This technique offers an alternative with great potential in the field of wastewater treatment. Finally, their applications are discussed to explore the research gaps for future research direction. From a literature survey of more than 170 recent papers, it is evident that MFCs have demonstrated outstanding removal capabilities for various pollutants. [ABSTRACT FROM AUTHOR]

The hot summer of 2018 posed many challenges with regard to water shortages and yield losses, especially for agricultural production. These agricultural impacts might further pose consequent threats for the environment. In this paper, we deduce the impact of droughts on agricultural land management and on water quality owing to nitrate pollution. Using national statistics, we calculate a Germany-wide soil surface nitrogen budget for 2018 and deduce the additional N surplus owing to the dry weather conditions. Using a model farm approach, we compare fertilization practices and legal restrictions for arable and pig breeding farms. The results show that, nationwide, at least 464 kt of nitrogen were not transferred to plant biomass in 2018, which equals an additional average nitrogen surplus of 30 kg/ha. The surplus would even have amounted to 43 kg/ha, if farmers had continued their fertilization practice from preceding years, but German farmers applied 161 kt less nitrogen in 2018 than in the year before, presumably as a result of the new implications of the Nitrates Directive, and, especially on grassland, owing to the drought. As nitrogen surplus is regarded as an "agri-drinking water indicator" (ADWI), an increase of the surplus entails water pollution with nitrates. The examples of the model farms show that fertilization regimes with high shares of organic fertilizers produce higher nitrogen surpluses. Owing to the elevated concentrations on residual nitrogen in soils, the fertilization needs of crops in spring 2019 were less pronounced than in preceding years. Thus, the quantity of the continuously produced manure in livestock farms puts additional pressure on existing storage capacities. This may particularly be the case in the hot-spot regions of animal breeding in the north-west of Germany, where manure production, biogas plants, and manure imports are accumulating. The paper concludes that water shortages under climate change not only impact agricultural production and yields, but also place further challenges and threats to nutrient management and the environment. The paper discusses preventive and emergency management options for agriculture to support farmers in extremely dry and hot conditions. [ABSTRACT FROM AUTHOR]

Agriculture is the most important sector with regard to water resources management due to its social, economic, hydrological, and environmental aspects, and many scholars and researchers have been driven to investigate the dynamic interrelationships among hydrological, environmental, and socioeconomic factors affecting agriculture. The system dynamics (SD) approach has become widely used because of its merits and benefits as a tool to deal with complex, dynamic problems and systems with many aspects and components that are involved and must be understood to ensure sound decisions regarding water and hydrological systems. Although agricultural water management needs to be studied as a main part of water management, socioeconomic management, and environmental management requiring the use of SD, this review shows that SD is currently used to a limited extent in terms of agricultural water management. This paper sheds light on the studies and investigations on the use of SD in the water sector and highlights the strengths of SD in order to encourage researchers to use this promising method to manage such a vital resource. Accordingly, this review seeks to include a comprehensive and up-to-date survey of existing publications and scholarly papers on the use of SD modeling as an effective technique for dealing with different problems associated with planning, management, and analysis of hydrology and water resources systems. Recent trends in the integration of SD with other modeling systems, such as artificial intelligence systems, are discussed along with the limitations and challenges facing application. This article makes a new contribution by giving a foundation of references and studies for scholars, researchers, and academics which encourages future investigation in employing the SD approach to hydrology and water resources management and planning, especially with agricultural water. [ABSTRACT FROM AUTHOR]

To reduce crop-related water consumption and enhance agricultural water resource efficiency in the Beijing–Tianjin–Hebei region, this study employed the AquaCrop model to simulate crop yield and irrigation water requirements and calculated the water scarcity footprint (WSF). The results were as follows: (1) The AquaCrop model exhibited strong applicability, with R2, RMSE (Root Mean Square Error), EF (Nash–Sutcliffe model efficiency coefficient) and d values of 0.9611, 6.6%, 0.91, and 0.98 (winter wheat), and 0.9571, 5.5%, 0.95, and 0.99 (summer maize) for canopy cover simulation. Similarly, aboveground biomass simulation yielded values of 0.9661, 0.8 t/ha, 0.93, and 0.98 (winter wheat), and 0.9087, 1.3 t/ha, 0.90, and 0.98 (summer maize). Winter wheat soil moisture content simulation showed an R2 of 0.9706, RMSE of 3.7 mm, EF of 0.93, and d of 0.98. (2) The AquaCrop model simulated the winter wheat and summer maize yields and irrigation water requirements for the years 2009, 2014, and 2019, validating the scalability and spatial visualization capabilities of GeoSim in extending AquaCrop simulations. (3) Integrating the water footprint and the water resources system, this study assessed the WSFs of winter wheat and summer maize. From 2009 to 2019, winter wheat production in the region increased by 25.08%, and summer maize production increased by 37.39%. The WSF of winter wheat decreased, whereas the WSF of summer maize increased. It is recommended to reduce crop cultivation areas in regions such as Daming County, Ningjin County, and Dingzhou City while further improving irrigation water efficiency, which would facilitate the sustainable utilization of water resources in the area. [ABSTRACT FROM AUTHOR]

Hydrographic connectivity stands as a crucial indicator for analyzing the structural dynamics within river and lake systems. Nevertheless, the impact of changes in hydrographic connectivity, including structural and functional connectivity within extensive river basins, on the progression of agriculture, industry, and habitation remain scarcely explored. To bridge this gap, Henan province in China, traversed by the Yellow River, was selected as a case study. The extraction of water information was facilitated by employing a remote sensing-based Modified Normalized Difference Water Index (MNDWI), while Set Pair Analysis was utilized to construct a hydrographic connectivity evaluation system for the study area spanning the preceding two decades (2000–2020). The results revealed that for structural connectivity, agricultural land covers over 50% and prevails as the primary land-use type; reservoir and lake areas initially increased before subsequently decreasing. Human activities have exerted a profound influence on these changes. Meanwhile, the structural form of the water system has gradually improved, exhibiting an increasing complexity of river networks and a stabilizing connectivity configuration. As for functional connectivity, the natural function remains well-preserved, while the social function demonstrates a positive correlation with the expansion of industrial activities, eventually achieving an excellent level from a moderate level. Overall, agriculture dominated the water usage structure, with residential water consumption steadily increasing, thereby positively impacting hydrographic connectivity in the studied area. [ABSTRACT FROM AUTHOR]

It is crucial to investigate the characteristics of meteorological drought in the Beijing–Tianjin–Hebei (BTH) region to improve the accuracy of agriculture and water resource monitoring and management. In this study, using instrumental observation data from 85 meteorological stations in the BTH region during 1961–2023 derived from the National Meteorological Information Center, we first calculated the meteorological drought comprehensive index (MCI) and analyzed the spatiotemporal characteristics of the MCI. In the BTH region, the MCI intensity from May to June was the most severe in the intraseasonal variation. The trend of the decreasing drought intensity in May–June has occurred for the past 60 years. The southern region in the BTH region was more likely to experience droughts. Next, the spatial patterns of the top two EOF modes of the May–June MCI were depicted. The primary spatial pattern of the BTH, which was characterized by consistent changes in the MCI throughout the entire BTH region, could be represented by the first mode's R2 of 69.01%. Then, we compared the spatial pattern of the MCI intensity under different return periods. Using the May–June MCI of 1961–2023, the drought intensity gradually increased from northwest to southeast for the 10-, 20-, and 50-year return periods. However, the drought intensity decreased and then increased from northwest to southeast based on the 1991–2023 MCI. Notably, a 20-year return period of severe drought affected Beijing and northern Hebei in 2023. Finally, we discussed the linkages of drought in the BTH region and atmospheric circulation/sea surface temperature (SST) anomalies, which were calculated using the Pearson correlation coefficient and wavelet coherence. We suggest that the MCI variations in the BTH region may be related to the SST anomalies of the Indian Ocean in 1961–1990 and the Pacific Ocean in 1991–2023, respectively. The abovementioned studies have enlightened us to focus on predicting the Pacific SST for drought, which will facilitate agricultural production and water resource management in the BTH region. [ABSTRACT FROM AUTHOR]

Climate change is affecting water resources in south-eastern Spain, and this mainly affects irrigated agriculture. In this context, seawater desalination is an adaptive strategy that has provided increasing water allotments to agriculture for the last decade, to replace decreasing conventional resources. Farmers are concerned about the agronomic effects of this substitution and its economic consequences. This study focuses on the potential agronomic impacts of the progressive replacement of the irrigation water from the Tagus–Segura transfer (TST) with desalinated seawater (DSW) on the main crops of south-eastern Spain. To that end, five main agronomic concerns were selected and analyzed under three water supply scenarios using increasing rates of DSW (0, 50, and 100%). The results indicated that, in addition to other economic or environmental considerations, sufficiently relevant agronomic aspects exist that need to be considered when replacing the TST supply with DSW. This study evidences the risks of phytotoxicity and soil alkalinization, due to the increase in boron concentration and the imbalance between monovalent and divalent cations in the DSW, respectively, and also a slight increase in the cost of fertilizers. In addition, the irrigation water salinity effect on production and total irrigation requirements was negligible, as both water sources present sufficiently low salinity. The detrimental effects were mitigated under a partial replacement scenario, so the blended use of DSW with conventional resources seems the most recommendable option for its agricultural management, rather than irrigating with DSW alone. [ABSTRACT FROM AUTHOR]

This study considers critical aspects of water management and crop productivity in wheat cultivation, specifically examining the daily cumulative actual evapotranspiration (ETa). Traditionally, ETa surface energy balance models have provided estimates at discrete time points, lacking a holistic integrated approach. Field trials were conducted with 22 distinct wheat varieties, grown under both irrigated and rainfed conditions over a two-year span. Leaf area index prediction was enhanced through a robust multiple regression model, incorporating data acquired from an unmanned aerial vehicle using an RGB sensor, and resulting in a predictive model with an R2 value of 0.85. For estimation of the daily cumulative ETa integral, an integrated approach involving remote sensing and energy balance models was adopted. An examination of the relationships between crop yield and evapotranspiration (ETa), while considering factors like year, irrigation methods, and wheat cultivars, unveiled a pronounced positive asymptotic pattern. This suggests the presence of a threshold beyond which additional water application does not significantly enhance crop yield. However, a genetic analysis of the 22 wheat varieties showed no correlation between ETa and yield. This implies opportunities for selecting resource-efficient wheat varieties while minimizing water use. Significantly, substantial disparities in water productivity among the tested wheat varieties indicate the possibility of intentionally choosing lines that can optimize grain production while minimizing water usage within breeding programs. The results of this research lay the foundation for the development of resource-efficient agricultural practices and the cultivation of crop varieties finely attuned to water-scarce regions. [ABSTRACT FROM AUTHOR]

The reference crop evapotranspiration (ET0) statistic is useful for estimating agricultural system water requirements and managing irrigation. In dry areas, the accurate calculation of ET0 is crucial for optimal agricultural water resource utilization. By investigating the relationship between meteorological information and ET0 in Shihezi City, four prediction models were developed: a BP neural network prediction model, a BP neural network prediction model improved by genetic algorithm (GA-BP), a BP neural network prediction model improved by particle swarm algorithm (PSO-BP), as well as an improved hybrid BP neural network prediction model (GA-PSO-BP). The Pearson correlation analysis found that the key parameters influencing ET0 were temperature (Tmax, Tave, Tmin), hours of sunshine (N), relative humidity (RH), wind speed (U), as well as average pressure (AP). Based on the analysis results, different combinations of meteorological input factors were established for modeling, and the results showed that when the input factors were temperature (Tmax, Tave, Tmin), hours of sunshine (N), as well as relative humidity (RH), the overall effect of the ET0 prediction model was better than the other input combinations, and the GA-PSO-BP prediction model was the best, which could provide some guidance for the deployment and use of water resources. This may assist in the allocation and utilization of agricultural water resources in Shihezi. [ABSTRACT FROM AUTHOR]

Water is one of the most important limiting resources for food production. How much water is needed for food depends on the size of the population, average food consumption patterns and food production per unit of water. These factors show large differences around the world. This paper analyzes sub-continental dynamics of the water footprint of consumption (WFcons) for the prevailing diets from 1961 to 2009 using data from the Food and Agriculture Organization (FAO). The findings show that, in most regions, the water needed to feed one person decreased even if diets became richer, because of the increase in water use efficiency in food production during the past half-century. The logarithmic mean Divisia index (LMDI) decomposition approach is used to analyze the contributions of the major drivers of WFcons for food: population, diet and agricultural practices (output per unit of water). We compare the contributions of these drivers through different subcontinents, and find that population growth still was the major driver behind increasing WFcons for food until now and that potential water savings through agricultural practice improvements were offset by population growth and diet change. The changes of the factors mentioned above were the largest in most developing areas with rapid economic development. With the development of globalization, the international food trade has brought more and more water savings in global water use over time. The results indicate that, in the near future and in many regions, diet change is likely to override population growth as the major driver behind WFcons for food. [ABSTRACT FROM AUTHOR]

Water is vital and an essential entity directly and indirectly for all living creatures from their birth, whereas electrical energy has a dominant role in the growth of society in general and for human beings in particular. Optimal use of water and production of electrical energy at minimum cost are potential research challenges. Hydraulic energy is one of the cheapest and the most exploited renewable energy resource for power generation worldwide, and is in line with the seventh United Nations Sustainable Development Goal (SDG 7). The Indus basin is a trans-boundary basin, and its modeling has been a source of interest for scientists and policymakers. Indus Basin Model Revised (IBMR) has many variants, all focusing on optimal use of water for irrigation purposes. In this paper, the modified IBMR model is proposed addressing both agriculture and power generation aspects simultaneously. This model optimizes the Consumer Producer Surplus (CPS) by considering different water inflow probabilities. A parameter has been introduced in the modified objective function to manipulate the supply of water to agriculture and hydropower generation. The proposed model has been implemented in Generic Algebraic Modeling System (GAMS) and case studies have been investigated in presence and absence of power generation. The results obtained show that, with incorporation of hydropower, basin wide income is increased up to 11.83% using 50% exceedance probability, and results are in agreement with reference power generation estimated by National Transmission and Dispatch Company (NTDC). The SDG 7 targets ensure the reasonable, dependable, sustainable and contemporary energy access to all. The current research is focusing on how Pakistan would achieve the SDG 7 targets. By 2040, it is anticipated that Pakistan's energy mix will have around 40% of hydropower and 16% of renewable energy. [ABSTRACT FROM AUTHOR]

This paper introduces a modified version of the DisPATCh (Disaggregation based on Physical And Theoretical scale Change) algorithm to disaggregate an SMAP surface soil moisture (SSM) product at a 20 m spatial resolution, through the use of sharpened Sentinel-3 land surface temperature (LST) data. Using sharpened LST as a high resolution proxy of SSM is a novel approach that needs to be validated and can be employed in a variety of applications that currently lack in a product with a similar high spatio-temporal resolution. The proposed high resolution SSM product was validated against available in situ data for two different fields, and it was also compared with two coarser DisPATCh products produced, disaggregating SMAP through the use of an LST at 1 km from Sentinel-3 and MODIS. From the correlation between in situ data and disaggregated SSM products, a general improvement was found in terms of Pearson's correlation coefficient (R) for the proposed high resolution product with respect to the two products at 1 km. For the first field analyzed, R was equal to 0.47 when considering the 20 m product, an improvement compared to the 0.28 and 0.39 for the 1 km products. The improvement was especially noticeable during the summer season, in which it was only possible to successfully capture field-specific irrigation practices at the 20 m resolution. For the second field, R was 0.31 for the 20 m product, also an improvement compared to the 0.21 and 0.23 for the 1 km product. Additionally, the new product was able to depict SSM spatial variability at a sub-field scale and a validation analysis is also proposed at this scale. The main advantage of the proposed product is its very high spatio-temporal resolution, which opens up new opportunities to apply remotely sensed SSM data in disciplines that require fine spatial scales, such as agriculture and water management. [ABSTRACT FROM AUTHOR]

Surface waters are very important for society, as they are a source of potable water, as well a water supply for agricultural, industrial and recreational purposes. This paper presents changes in the quality of the water in the Utrata River, along its entire length, as a function of the catchment area's land use. Water-quality measurements were carried out once a month for a total period of one year (April 2019–March 2020) at 24 measurement points. The concentrations of the following compounds were measured: total phosphorus, ammonia nitrogen and nitrate nitrogen, dissolved oxygen, and chemical oxygen demand. The results were compared with the limit values specified in the Regulation of the Minister of Maritime Economy and Inland Navigation. In order to determine the impact of land use on water quality in the Utrata River, principal component analyses (PCA) were conducted. The research demonstrated a considerably negative impact of agricultural land use and the presence of urban areas on the water quality of the Utrata River, with elevated concentrations of total phosphorus, ammonia nitrogen, nitrate nitrogen and COD, and decreasing concentrations of dissolved oxygen. The presented results point to the need for effective strategies to mitigate the adverse impact of agriculture and urbanisation on the environment and surface waters. [ABSTRACT FROM AUTHOR]

We enhanced the agro-hydrologic VegET model to include snow accumulation and melt processes and the separation of runoff into surface runoff and deep drainage. Driven by global weather datasets and parameterized by land surface phenology (LSP), the enhanced VegET model was implemented in the cloud to simulate daily soil moisture (SM), actual evapotranspiration (ETa), and runoff (R) for the conterminous United States (CONUS) and the Greater Horn of Africa (GHA). Evaluation of the VegET model with independent data showed satisfactory performance, capturing the temporal variability of SM (Pearson correlation r: 0.22–0.97), snowpack (r: 0.86–0.88), ETa (r: 0.41–0.97), and spatial variability of R (r: 0.81–0.90). Absolute magnitudes showed some biases, indicating the need of calibrating the model for water budget analysis. The seasonal Landscape Water Requirement Satisfaction Index (L-WRSI) for CONUS and GHA showed realistic depictions of drought hazard extent and severity, indicating the usefulness of the L-WRSI for the convergence of an evidence toolkit used by the Famine Early Warning System Network to monitor potential food insecurity conditions in different parts of the world. Using projected weather datasets and landcover-based LSP, the VegET model can be used not only for global monitoring of drought conditions, but also for evaluating scenarios on the effect of a changing climate and land cover on agriculture and water resources. [ABSTRACT FROM AUTHOR]

Time series data of multiple water quality parameters are obtained from the water sensor networks deployed in the agricultural water supply network. The accurate and efficient detection and warning of contamination events to prevent pollution from spreading is one of the most important issues when pollution occurs. In order to comprehensively reduce the event detection deviation, a spatial-temporal-based event detection approach with multivariate time-series data for water quality monitoring (M-STED) was proposed. The M-STED approach includes three parts. The first part is that M-STED adopts a Rule K algorithm to select backbone nodes as the nodes in the CDS, and forward the sensed data of multiple water parameters. The second part is to determine the state of each backbone node with back propagation neural network models and the sequential Bayesian analysis in the current timestamp. The third part is to establish a spatial model with Bayesian networks to estimate the state of the backbones in the next timestamp and trace the "outlier" node to its neighborhoods to detect a contamination event. The experimental results indicate that the average detection rate is more than 80% with M-STED and the false detection rate is lower than 9%, respectively. The M-STED approach can improve the rate of detection by about 40% and reduce the false alarm rate by about 45%, compared with the event detection with a single water parameter algorithm, S-STED. Moreover, the proposed M-STED can exhibit better performance in terms of detection delay and scalability. [ABSTRACT FROM AUTHOR]

Located in the southeastern region of Morocco, the Zagora area mainly relies on groundwater as a source of water supply. However, this groundwater is often of concern, due to the limited recharge and unfavorable geological conditions for the development of the aquifer. Despite this, private wells in the Zagora ditch reveal relatively rich water resources. Geochemical and isotopic studies were conducted in the area to understand the origin of the groundwater and its salinity, aiding in informed water management strategies to assist in better planning and regulation of well construction, as well as in mitigating the impacts of high salinity on local water supply and agricultural systems. The results show that the water quality varies, with some wells having conductivity values in excess of 5 mS/cm. Most groundwater samples have high salinity and low pH due to the CO2 dissolved in groundwater. Geochemical analysis indicated two chemical facies: chloride–sulfate calcic/magnesic and bicarbonate calcic/magnesic. The presence of Na+ and Cl− indicated that the origin of these two elements in these waters was the dissolution of halite, with some samples showing an enrichment of Na+ compared to Cl−. This could be attributed to cation exchange. The concentration of Ca2+ and HCO3− suggested that their origin is the dissolution of calcite and the weathering of calcium silicate minerals such as plagioclase. The isotopic analysis showed that the δ18O values ranged from −10.98‰ to −8.54‰, and δ2H values ranged from −75.9‰ to −62.3‰. This indicated that the groundwater originated from the High Atlas with a recharge altitude between 2600 m and 2800 m. The groundwater flows into the graben through fissures and regional fault networks. [ABSTRACT FROM AUTHOR]

Efficient water management is crucial for sustainable agriculture and water resource conservation, particularly in water-scarce regions. This study investigated the effect of different irrigation depths on onion (Allium cepa L.) yield and water use patterns in a semi-arid tropical region of Colombia, using a completely randomized design with five treatments. The treatments ranged from 0–100% of total available water (TAW), T1 (100% of TAW), T2 (80% of TAW), T3 (60% of TAW), T4 (40% of TAW), and T5 (20% of TAW). The experiment was conducted in a greenhouse during one growing season (2022–2023). The normalized water productivity (WP *), irrigation water productivity (IWP), consumptive water productivity, blue water footprint (WFblue), marginal water use efficiency (MWUE), and elasticity of water productivity (EWP), as well as some parameters of quality onion, were determined. The soil in the experimental field was classified as sandy loam; the results show that the WP * of onion is 17.42 g m−2, the water production function shows the maximum production will be achieved at a water application depth of approximately 943 mm, and beyond that, the biomass yield will decrease with additional water application, IWP values for onion ranged from 2.18 to 3.42 kg m−3, the highest Wfblue was in T5 (34.10 m3 t−1), and low Wfblue was T1 (20.95 m3 t−1). In terms of quality, treatment T1 had the most favorable effects on bulb weight, polar diameter, and equatorial diameter, while treatment T5 had the least favorable effects. The study highlights the importance of efficient irrigation on sandy loam soils to maximize yield and water use efficiency. It provides valuable data for evaluating the potential yield benefits of precision irrigation in the study area. Optimizing irrigation depth can significantly improve onion yield and water use efficiency in semi-arid regions. [ABSTRACT FROM AUTHOR]

Agriculture contributes extensively to the economic development of countries; however, it is one of the main water-consuming industries. Revealing the characteristics and network structure of agricultural water use efficiency (AWUE) is conducive to green and coordinated development of agriculture. Considering that analyzing the variation of AWUE is helpful to calculating the AWUE, this study aims to calculate the total water consumption coefficient of the agricultural sector in the Yangtze River Economic Belt (YEB) by using the China interregional input-output tables in 2012 and 2017. The gravity model was modified to deduce the spatial correlation network of agricultural total water consumption coefficient (ATWCC), and the social network analysis method was used to analyze the network structural characteristics. The results show that: (1) compared to 2012, the AWUE of YEB in 2017 improved, with a decrease of ATWCC from 532.5 to 387.5 m3/10,000-yuan, account for 27.2%; (2) The network relevance of ATWCC of YEB's 11 provinces (cities) enhanced, the rank relationship within the network and the network structure was relatively stable; (3) The spatial correlation network formed several network centers, Zhejiang and Jiangsu in the eastern coastal area were the main destinations of the spatial spillover of the spatial correlation network. [ABSTRACT FROM AUTHOR]