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This document is an editorial from the International Journal of Water Resources Development, discussing the importance of water resource management in agriculture for achieving food and water security in Asia. It highlights the role of agriculture in water usage and the challenges posed by climate change and increased demand. The editorial presents research papers on topics such as the impact of climate change on food security, the effects of weather variables on crop yields, the benefits of irrigation mechanization, and groundwater governance. It concludes by emphasizing the need for integrated measures, technological development, provision of irrigation facilities, and improved water governance for sustainable water management in agriculture. Additionally, the document includes a list of contact information for individuals affiliated with institutions such as the Asian Development Bank Institute and the University of Glasgow's School of Social & Environmental Sustainability. [Extracted from the article]

The document titled "Resilient and sustainable water management in agriculture" emphasizes the importance of water resources and agricultural systems for sustainable development. It discusses the use of computer-based technologies like remote sensing, GIS, and machine learning in understanding and managing water resources. The document introduces a special issue on water management in agriculture, which includes research papers covering topics such as optimal reservoir operation, crop water demand assessment, groundwater contamination, rainfall data estimation, agricultural drought vulnerability, irrigation water quality, groundwater potential zones, groundwater quality assessment, and the toxic effects of copper oxide nanoparticles on aquatic organisms. These papers offer valuable insights for decision-making and planning in water resource management and sustainable agriculture. The collection of research papers also covers various topics related to environmental science and geospatial analysis, utilizing remote sensing data, GIS technology, and analytical methods to assess aspects like land use, water quality, and morphometric parameters. The findings highlight the effectiveness of these approaches in decision-making for sustainable development and resource management. Additionally, one paper explores the impact of the COVID-19 pandemic on environmental pollution and emphasizes the need for short-term and long-term solutions. Overall, these papers provide valuable insights for researchers and policymakers in the field of environmental science. [Extracted from the article]

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]

The agriculture sector on the whole planet has been subjected to abrupt climate changes, sudden floods and continuous drought. The nutrition of the planet is indangered taking into account the rate of population growth combating with water resources scarcity on some places. There is a need of developing water efficient technologies and improving their management. The MOHID-Land model has been developed in 2018 and simulates the full soil-water-plant-atmosphere transfer system and can help the improvement of agricultural water management. The current paper discussed the simulation of the soil water dynamics of drip-irrigated tomatoes cultivated in the Experimental field of the Agricultural University – Plovdiv, Bulgaria. The data by the simulations has been compared with experimental data obtained at three soil depths. [ABSTRACT FROM AUTHOR]

This paper speaks to the uneven scholarly attention gone into tracing dominant forms of water governance as opposed to practices crafting alternative human-water relations on the ground. Through the case of an Indian-based network mobilising to transform how we understand rainfed regions as rain-dependent socio-ecologies, I theorise their action 'with care', a commitment to think-with grassroots movements as actors capable of bringing new worlds into being. Describing their activities as worlding-practices, I explore how the network confronts the invisibilities inscribed by the current paradigm reducing water to irrigation by defining alternative metrological tools that recentre the governance of water from the perspective of the rainfall. Tinkering with the variables of the constituted metrology, the network utilises an atlas, a formula, and an acronym to enact a different rainfed sociality into being, creating visibilities and cares for neglected things. Through the story of a grassroots group and their strategies of mobilisation, this account contributes to debates on how to pluralise water governance, suggesting that reimagining its practices requires taking seriously the performativity of grassroots knowledges. Building alliances between research and activism as e/affective world-building partners becomes key to co-theorise liveable human-water relations and caring socio-ecologies at large. [ABSTRACT FROM AUTHOR]

The development of the Internet of Things (IoT) and machine learning (ML) technologies has triggered smart agricultural systems. In smart agriculture, irrigation management plays a major role to reduce water waste. The monitoring settings, hardware modules, communication technology, and storage systems used in smart irrigation systems were analyzed to determine the optimal nature of water flow. This assessment aims to give an overview of the current state of the irrigation system by taking into account weather and soil moisture. This paper provides a comprehensive review of the utilization of various hardware modules in smart irrigation systems. Moreover, various communication technologies that aid in data transfer for efficient smart irrigation are reviewed. The ML method used for prediction is also evaluated, as well as based storage technologies like the cloud and databases used to store data for predictive irrigation systems. As a result, the paper provides an overview of all the factors that contribute to irrigation systems' smart operation as well as potential future paths for improving agricultural systems through IoT. Core Ideas: Irrigation management is crucial in smart agriculture for minimizing water waste.This apper presents the ideal type of water flow that was determined by smart irrigation systems.Monitoring configurations, hardware modules, communication technology, and storage systems were analyzed in the smart irrigation system. [ABSTRACT FROM AUTHOR]

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]

Ground water is the main source of water for domestic and agricultural purposes in rural areas in Malawi. Continued exploitation of the ground water for domestic, agricultural, mining and other industrial purposes results in continued temporal changes in its levels. Understanding changes in the Groundwater Storage Capacity is crucial in development and in improving the livelihoods of people. Attempts to study groundwater storage have been made in Malawi. However, the lack of groundwater data, triggered by scarcity of ground observation facilities, hampers water resource management efforts. In this paper, the Gravity Recovery and Climate Experiment (GRACE-FO), supported by Global Land Data Assimilation System (GLDAS), has been used to determine variations in Terrestrial Water storage capacity levels, which combine the surface moisture, groundwater, snow and canopy water conditions in Balaka district, in Malawi, over a period of ten years (2012-2022). Owing to the fact that Balaka does not register any snowfall, only the surface moisture anomaly was considered in reducing the terrestrial water storage anomaly to determine the groundwater storage level changes from 2012 to 2022. Since an increasing trend, declining to levels as low as 0.002mm/year, was determined, the GRACE-based groundwater storage anomalies revealed no significant changes in groundwater levels. Influencing factors for the increasing trend were not addressed in this paper. Nonetheless, the results of this paper can contribute positively to the effective management of groundwater resources and promote the use of geodetic gravity data in water resource management. [ABSTRACT FROM AUTHOR]

The implementation of conventional supply-based mechanisms, in which the allocation of irrigation water entitlement for individual farmers is determined by their specific water requirements, has resulted in the inefficiency of economic processes and the squandering of water resources. This paper introduces a new dynamic bi-objective equity framework within an irrigation system. The framework aims to minimize the disparity of water supply per net benefit at the upper level and optimize the disparity of water shortage at the lower level. In order to obtain a feasible and satisfactory outcome, the study considers the use of fuzzy goal programming and Improved Particle Swarm Optimization (IBPSO) to analyze the initial data gathered from Sistan Basin, a real arid area in Iran. The uncertainty surrounding inflow, planting area, and irrigation coefficient has presented potential challenges for the irrigation process. As a result, new adaptation measures are being explored to mitigate the effects of these challenges. The following study examines the equity of the irrigation system under various scenarios in light of the anticipated deterioration of climatic patterns in the coming years, and offers constructive insights. The final results indicate that watermelon has the highest water consumption, whereas grapes exhibit lower sensitivity to water availability. The adoption of adaptation strategies, such as transitioning from water-intensive and low-value watermelon cultivation to alternative crops like wheat, could significantly enhance water conservation efforts in arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

Jingdian Irrigation Area is a high-lift cross-basin irrigation area with agricultural economy as the main, drought and water shortage have become the main factors restricting the high and stable yield of crops, water-saving irrigation technology has been popularized in Jingdian Irrigation Area reasonable water-saving irrigation can save water improve unilateral water efficiency it is beneficial to promote the intensive and economical utilization of water resources and the construction of water-saving irrigation area. This paper is based on the entropy method, the evaluation system of water-saving irrigation benefit is constructed from the aspects of social economic benefit and ecological environmental benefit, the benefits of different water-saving irrigation modes for the main crops in irrigated areas are analyzed. The results show that the efficiency of efficient water-saving irrigation is generally higher than other irrigation methods drip irrigation is the best water-saving irrigation mode in this area. The evaluation results are basically consistent with the reality, it shows that this method is feasible to evaluate the benefit in irrigated areas, so it has a guiding significance to the comprehensive evaluation of irrigated areas. [ABSTRACT FROM AUTHOR]

Water Conservation and Saving Technologies (WCSTs) can contribute to reduce the pressure on water resources from agricultural activities. A significant strand of literature on agricultural and innovation economics has explored the main drivers behind the adoption of WCSTs in agriculture, but due to the shortage of data most studies are based on survey analyses focusing on a specific case study. Therefore, results cannot be easily generalised. In this paper, we used a structured literature review (SRL) approach to systematise the original studies already published on the WCSTs adoption. Focusing on the econometric analysis used to estimate the main drivers of WCSTs adoption, our analysis started from an initial selection of 1027 studies, then after excluding book chapters, book, conference chapters and after checking abstracts and key-words we arrived to a final selection of 36 papers which have been deeply scrutinized with a structured analysis of their contents. Several findings have emerged from the analysis. The drivers of WCSTs adoption are various and heterogenous. We synthetized the main determinants into different categories: a) farm characteristics (land size, the presence of extension services, capital assets and internal organization within the farm; b) farmer characteristics (age, level of education, income); c) institutional environment (social networks, previous information on the technology, membership to farmer organizations, public fundings, access to credit, cost of water, access to groundwater, water constraint); d) geographic and climate characteristics (soil quality, drought, aridity). • The literature on WCSTs explored the main drivers of adoption but without generalisable results. • A structured literature review (SRL) has been used to systematise the studies already published on the WCSTs adoption. • This paper focuses on the econometric analysis used to estimate the main drivers or barriers of WCSTs adoption. • This analysis started from a base of 113 studies, the relevant studies have been reduced to 36 papers. • Various factors influence WCSTs adoption as farm, farmer, institutional, geographical and climatic characteristics. [ABSTRACT FROM AUTHOR]

In January 2021, the new Horizon 2020 project “Promoting SMART agricultural WATER management in Bosnia and Herzegovina” (SMARTWATER) was launched. It was the first time that an academic institution from Bosnia and Herzegovina implemented a Horizon 2020 project as Coordinator. The main objective of SMARTWATER is to reinforce networking, research and S&T cooperation capacities of the University of Banja Luka (UNI-BL), the University of Sarajevo (UNSA) and other connected national institutions, in the field of sustainable agricultural water management and to increase their competency and fund-raising skills for a successful participation in the European Union Research Programs. Main project topics include: 1) cloud-based smart technologies, 2) new generation of satellite remote sensing data, 3) water-energy-food nexus and 4) climate change impact on agriculture. At two locations in BiH (Aleksandrovac and Butmir) 3-year field experiments on maize (Zea mays L.), hybrid BL 43 (from FAO 400 group) were completed. The Randomized Complete Block design included two factors, irrigation (3 irrigation regimes) and fertilization (2 nitrogen levels). During the project implementation, our scientific teams published several academic papers in peer-reviewed international Journals and Proceedings and these documents are available in open access on Zenodo platform [1]. The project consortium is preparing additional scientific papers. The project outputs are: 3 advanced training courses, 3 summer schools, joint research activities (experiments) at 2 locations in BiH, 3 stakeholders’ meetings (roundtables), 3 post-graduate MSc courses, 13 mutual staff exchanges, 3 hands-on workshops on R&I, the development of 2 smart water management tools and the organization of an international conference in BiH at the end of the project. So far (period 2021-2023) most of these activities were finished. All project reports were prepared and sent to the EC. All info about the project is being disseminated, on a regular basis, and for this purpose social media profiles were used: Facebook, Twitter/X, LinkedIn and YouTube as well as the SMARTWATER website [2]. The dissemination of SMARTWATER achievements is an ongoing process. SMARTWATER project officially ends in June 2024. The remaining activities in 2024 include the organization of academic exchanges in Portugal and Italy, the 3rd stakeholders' meeting, the completion of the scientific publishing and the organization of an international conference in Trebinje (BiH) in May. We ask all interested stakeholders to visit our sites, to attend our events and to join the SMARTWATER network. [ABSTRACT FROM AUTHOR]

Using Economic Irrigation Water Productivity (EIWP) as an indicator for on-farm irrigation decision-making is of utmost importance in addressing the challenges posed by poor policies in managing agricultural water use, particularly in water-scarce basins. Various modeling systems are available for quantifying crop actual evapotranspiration (ET a) and biomass needed for measuring the economic output obtained from each unit of irrigation water utilized. The difference in ET a and biomass estimates between the modeling systems could translate into a difference in EIWP outcomes, which influences the basin-wide irrigation water management. In this paper we examine the influence of selecting different ET a and biomass models, particularly the hybrid single-source energy balance HSEB, the Global Field-Scale Crop Yield and ET Mapper in Google Earth Engine GYMEE, and FAO's WaPOR V2, on evaluating EIWP on a basin-wide level. The method includes combining remote sensing and economic data to compare variability in ET a , biomass, and EIWP values derived from HSEB, GYMEE, and WaPOR. The approach is demonstrated with field survey data from the upper hydrologic unit of Lebanon's largest catchment, the Litani River Basin, in its three productive districts Baalbak, Zahleh, and West Bekaa for the year 2021. Field-scale mean monthly ET a and biomass estimates for all crops, obtained from both models, are very comparable. On a district level, the results reveal a reasonable model agreement for the four crops in the estimation of ET a with moderate to strong correlation (0.75 < r < 0.95). WaPOR consistently produces slightly higher mean ET a values for potato, wheat, and table grapes when compared to HSEB. Both models reasonably agree when estimating biomass for the four crops with high correlation (r > 0.9). Contrary to the ET a results, the GYMEE model consistently estimates slightly higher mean biomass values for all crops compared to WaPOR. The EIWP values produced by both models consistently indicate that potato holds the highest EIWP across all districts, followed by onion, table grapes, and wheat. The mean district HSEB-GYMEE model derived EIWPs are slightly higher than those derived from the WaPOR model for most crops. For EIWP obtained from HSEB-GYMEE, mean EIWP for potato is 12 times higher than that of wheat. As for that obtained from WaPOR, mean EIWP for potato is 10 times higher than that of wheat. The paper establishes a basis for future research on the application of remote sensing models in addressing water-stressed and socioeconomically challenged basins, with the potential to inform strategic irrigation management decisions based on model selection. ● WAPOR and HSEB models compared for ET and Economic Water Productivity. ● Model choice significantly impacts EIWP outcomes, affecting water management. ● Comparative analysis of ET and biomass enhances policy precision. ● Potato leads in EIWP across districts, optimizing water resource use. [ABSTRACT FROM AUTHOR]

Many parts of the world face severe and prolonged drought conditions, stressing the sustainability of water resources and agriculture. Transitioning to water-efficient crops is one strategy that can help adapt to water scarcity. An emerging drought-tolerant crop of interest is chia (Salvia hispanica). Yet, no study has compared its large-scale water use dynamics to those of widely established crops across the globe. Here, we use satellite data over multiple years to assess the water use efficiency of chia, alfalfa, corn, and soybean globally. Results show that chia consumed 13-38% less water than alfalfa, corn, and soy and assimilated 14-20% more carbon per amount of water used. Substituting 10% of Southwest United States alfalfa cultivation with chia would save 184 million liters of water per growing season, equivalent to the annual water consumption of 1,300 households. Future research shall explore the economic, societal, and environmental ramifications of substituting alfalfa with chia in dry areas worldwide. These insights can guide decision-makers in promoting sustainable agriculture and water resource management. A large-scale remote sensing study on water use by chia suggests that chia could be a sustainable choice for agriculture, consuming 13-38% less water than alfalfa, corn, and soybean, while assimilating 14-20% more carbon per unit of water. [ABSTRACT FROM AUTHOR]

Artificial recharge of groundwater has been recognized as a promising option for sustaining groundwater supplies and ensure water security for the ever rising population. With the aid of geospatial and multi-criteria decision analysis methodologies, the current study's scope aids in evaluating groundwater potential zones and locating suitable zones and sites for groundwater recharge for the revival of the Kanari River. A pragmatic methodology was suggested in this study for implementing water harvesting structures for river revival and estimation of water demand, pumping, and recharge. The geometric mean and the normalized weight for individual features were specified using the AHP in a GIS environment. All the different features/datasets were overlaid, and possible groundwater zones were revealed using AHP. Integrated maps were used to identify the groundwater recharge zone and locations for establishing artificial recharge structures within the Kanari River system. Ultimately, the domestic water demand, agriculture water use, pumping, and livestock water demand were estimated for water budgeting, and based on this data, the water availability was calculated. Based on the study results, the water demand of the Kanari River watershed was estimated to be 732 MCM. Taking into consideration the supply and demand scenarios, the pumping overdraft of the Kanari River watershed was found to be 423 MCM, and the proposed additional recharge through the planned conservation structures was estimated to be 859 MCM. So, even if pumping overdraft is considered, this additional groundwater recharge can fulfill the local demand, help maintain the river flow, and ensure water availability and security in the region. [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]

Precipitation can induce a surface sensible heat flux since the raindrops are generally cooler than the surface. This precipitation‐induced sensible heat flux (QP) is typically ignored in models. However, during heavy rainfall, QP can be large and may not be negligible such as over India during the summer monsoon season. We provide the first results of incorporating QP in a simulation that shows ∼2% (∼5%) reduction in precipitation over India compared to the simulation without QP during a monsoonal active phase in 2017 (2018). This reduction was primarily due to a reduction in vertical advection of moisture. Additionally, QP modified the spatial distribution of precipitation with 40% of the geographical area encountering alterations of at least 20% in precipitation. This change in precipitation distribution across the region can have important implications for regional agriculture and irrigation practices. Changes in the partitioning of surface heat flux components due to QP is also discussed. Plain Language Summary: Rainfall during the monsoon season in India has widespread influences on agriculture and water supply. Therefore, understanding and predicting monsoon rainfall is of utmost importance. Among many parameters, surface energy budget influences precipitation. One of the components of the surface energy budget is the sensible heat flux due to precipitation (QP), which arises because the temperature of raindrops is typically different (cooler) than the temperature of the surface. The QP is thought to be small and is neglected in climate models. By incorporating QP in a regional climate model, we show its influence on monsoon precipitation and surface energy budget. We found that QP reduces precipitation by ∼2% and affects the spatial distribution of precipitation, which may have implications for regional agriculture and irrigation strategies. We also show that QP leads to significant changes in the magnitude and spatial distribution of surface energy budget terms. Key Points: Precipitation‐induced surface sensible heat flux is typically neglected in numerical weather and climate modelsModel simulations show that rain‐induced sensible heat flux reduces monsoonal precipitation and changes its spatial distributionChanges in the spatial distribution of monsoonal rain can have important implications for regional agriculture and irrigation practices [ABSTRACT FROM AUTHOR]

Agriculture water use accounts for 70% of the total water withdrawal worldwide. The evapotranspiration during crop growth is one of the important hydrological processes in the agricultural water cycle. This study proposed the concept of artificial irrigation evapotranspiration of irrigated crops to describe that the evapotranspiration caused by irrigation water use. Irrigated crops rely on two kinds of water sources: precipitation and irrigation water. With the construction of irrigation schemes, the artificial irrigation evapotranspiration plays an increasingly important role in the dualistic water cycle system of irrigated cropland. To reveal the amount of artificial irrigation evapotranspiration of 17 categories of irrigated crops in China, this study proposed a new quantitative model system which was established based on traditional evapotranspiration models and soil water balance models. Based on the new model system, we calculated the annual artificial irrigation evapotranspiration of irrigated crops for the period 2013 to 2017 in China. The results showed that the proportion of artificial irrigation evapotranspiration to the total evapotranspiration of irrigated crops was 41.3%, whose value was 228.1 km3 a−1. The artificial irrigation evapotranspiration in different agricultural water management regions were 90.0 km3 a−1 in the northeast region, 86.0 km3 a−1 in the southeast region, and relatively low 52.2 km3a−1 in the west region. The results of this study can provide methods for water management and policy–making in agricultural irrigated areas, and it can also provide a preliminary understanding of the influence of human activities on the dualistic water cycle in cropland. [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 line with the evaluation and monitoring of the actions of the Lake Urmia Restoration Headquarters, this research was conducted with the aim of evaluating the socio-economic effectiveness of the actions of the Lake Urmia Restoration Headquarters and measuring the participation of local communities on the shores of Lake Urmia. In the current research, according to the nature of the subject and research objectives, qualitative survey research method was used. In order to carry out this research, three types of restoration actions were selected, including planting with Atriplex species in Azarshahr city, planting and with Tamarix, Nitraria and Atriplex species in Shabestar city, and constructing a non-living windbreak using Tamarix species in Ajabshir city. local communities are most willing to participate in the implementation of new irrigation systems in order to save water consumption, agriculture with less water demand, and participation in planning and formulation of revitalization plans with average scores of 3.41, 3.19 and 2.93 respectively. According to the results, from the point of view of the local communities, the actions of the restoration headquarters have a significant difference in terms of economic effectiveness, and the economic effects of constructing a non-living windbreak have been greater than the other two methods. It seems that we can hope for positive results of the actions of the restoration headquarters if the appropriateness of restoration measures is observed with the ecological conditions of the region and the participation of local communities. [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]

Spatial and temporal patterns of water supply and consumptive water use were analyzed from 475 Detailed Analysis Units by County (DAUCOs) spatial units across California during 2002 through 2016 to evaluate spatial and temporal variability and how it might associate with precipitation variability and other factors. Many, but not all, DAUCOs have relatively low total water supply variability compared to that of state-wide precipitation. Such low variability, in DAUCOs having sufficient diversity of water supply sources, is the result of switching between sources as needed to maintain a reliable total water supply. We used multiple approaches to explore these variations which involved four categories of water supply (local, groundwater, imported, and other) and two categories of water use (agricultural and urban). First, a cluster analysis of the volumetric water balance data identified a small set of clusters having similar magnitudes and proportions of water supply sources and water use—some of them composed of only a few DAUCOs but accounting for a disproportionate amount of the state’s water use. Second, a principal components analysis identified leading modes of anomalous water supply and water use among the 475 DAUCOs, capturing most of the time variation during 2002 to 2016. The most prominent mode exhibits a multi-year trend, most strongly involving increasing groundwater supply and agricultural water use, and decreasing urban water use and imported water supply. Over the study period, trends in both supply and use were pronounced, but differed considerably across California DAUCOs. One predominant subset of DAUCOs grew their agricultural water use with increased groundwater supply; in contrast to a widespread group of DAUCOs which reduced their urban water use. An important result for planners is our finding that variation in precipitation—itself important—is amplified by the human response to water supply availability and regulatory policy. [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]

Water scarcity presents a formidable challenge to agriculture, particularly in arid, semiarid, and rainfed settings. In agricultural contexts, hydrogels serve as granular agents for water retention, undergoing considerable expansion upon water exposure. They assume versatile roles encompassing soil‐water retention, the dispensation of nutrients and pesticides, seed encapsulation, erosion mitigation, and even food supplementation. This study's objective involves the examination of biochar‐infused hydrogels, fashioned by incorporating vine pruning waste‐derived biochars, and the assessment of swelling behaviors in various aqueous environments encompassing deionized, tap, and saline water at concentrations of 0.5–1%. Characterizations of the vine‐biochars‐VB and biochar‐incorporated hydrogels‐VBHG are executed, with particular attention to their swelling properties across diverse media. As an initial step toward appraising their agricultural relevance, these hydrogels are introduced to a germination medium featuring wheat seeds to discern potential influences on germination dynamics. The maximum swelling capacity of VBHG is recorded in deionized water, tap water at pH 7.0, tap water at pH 9.0, saline water at 0.5%, and saline water at 1%, reaching 352%, 207%, 230%, 522%, and 549%, respectively. Remarkably, the 0.5% VBHG treatment exhibits the most pronounced root elongation. The application of hydrogels in agriculture exhibits promise, particularly within drought‐related contexts and potential soilless applications. [ABSTRACT FROM AUTHOR]

Synthetic fertilizers have been revolutionary in the way that the increased production of food crops has increased as a result of the application of synthetic fertilizers. Despite the fact that global N, P, and K consumption have increased from 64.9, 25.9, and 18.2 kg/ha in the year 2000 to 85.5, 33.2, and 20.4 kg/ha, respectively, they are still relatively low. Additionally, excessive use of inorganic fertilizers has also resulted in a deterioration of environmental systems, especially that of water resources. The presence of this toxic substance inside the human body is therefore due to the fact that it enters the body through the food chain and causes serious illnesses, such as cancer. For instance, in most countries, the maximum nitrate concentration for drinking water is restricted to between 45 and 50 mg/L. Besides promoting the use of chemicals and the application of fertilizers in farming, there should be a push to encourage the sustainable use of biofertilizers to protect the environment and human health. Composts that have been developed from various waste materials, such as poultry farms, dairy farms, and other sources, have proven to be very rich in N, P, and K. For example, compost generated from dairy farm wastes can provide a value of 45,100, 7300, and 9100 mg/kg of N, P, and K, respectively. In order to make the use of these biofertilizers in agriculture possible, it will be necessary to spread awareness among the farmers so that they can adopt the concepts of sustainable management in agriculture. [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]

Considerable research has been conducted on the estimation of Gross Primary Productivity (GPP) and Net Primary Productivity (NPP) from different viewpoints. Each vision has proposed special applied materials and methodologies and has provided specific insight into the results and overall conclusions. As NPP generally declines once crops start to begin competing intensively for water resources, the identification of precise NPP estimation approaches can be of importance in water and agricultural studies. Due to the lack of a comprehensive overview of the subject that investigates GPP and NPP studies from both environmental and agricultural perspectives, we reviewed the existing approaches in estimating these two parameters with a special focus on estimating NPP for agricultural studies. Categorization of the diverse proposed models and approaches, with special attention to the role of newly introduced materials, such as chlorophyll proxies, is provided on GPP and NPP estimations. After introducing the different categories, from the environmental perspective, we addressed the most recent improvements in GPP estimations in the biosphere by applying a chlorophyll-based fraction of Absorbed Photosynthetically Active Radiation (fPAR) into the light use efficiency (LUE) model. Then, by considering the agricultural perspectives, the application of both chlorophyll-based fPAR and a new chlorophyll-based predictor was discussed to estimate NPP and yield. It is expected that the outlined vision on estimating NPP in agricultural studies helps to identify the current boundary of knowledge in these types of studies. [ABSTRACT FROM AUTHOR]

From the perspective of sustainable development in irrigation areas, imperfect constraints, which have negatively impacted previous agricultural planting structure optimization models, tend to produce unreasonable optimization results. Thus, in this paper, attempts are made to incorporate the resilience of water resource systems into the constraint set and explore the optimal layout of agricultural planting structures in irrigation areas. We selected 12 sample irrigation areas in Heilongjiang Province, China, including Chahayang, Fuyu, and Tailai, as the research areas and considered their actual situations. Then, we established a multiobjective optimization model for an agricultural planting structure with rice, soybean, and corn planting areas as decision variables; socioeconomic benefits, agricultural production benefits, ecological benefits, and water resource benefits as objective functions; and water resource system resilience and net crop output value and other factors as constraints. Fifteen scenarios were assessed through the combination of objective functions, and the nondominated sorting genetic algorithm III (NSGA-III) was used to optimize and analyze the agricultural planting structure of typical irrigation areas in Heilongjiang Province and to determine the optimal planting plan. The research results found that the function values adjusted by planting area have significantly improved compared to those before optimization. The adjustment trend of agricultural planting area is to increase the planting area of rice and soybean and reduce the planting area of corn. The introduction of constraints on water resource system resilience ensures that other benefits remain basically unchanged; thus, the water resource objective function is significantly better with resilience constraints than without them. Therefore, water resource system resilience can act as an effective constraint; this finding enriches and expands the theoretical and methodological system for optimizing the management of agricultural planting structures in irrigation areas and thus provides important technological support for ensuring regional food security, ecological security, and water security, which has substantial practical significance. • Exploring the feasibility and implementation path of embedding the resilience of water resource systems. • Seeking the optimal adjustment plan for agricultural planting structure in irrigation areas based on the NSGA-III algorithm. • Analyzing the constraint effect of water resource system resilience on the optimization of agricultural planting structure. [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]

Water resources are indispensable for human existence and agricultural irrigation, particularly in countries where the agricultural sector occupies a substantial proportion of the gross domestic product (GDP). Consequently, improving agricultural water-use efficiency has become a critical strategic choice. Egypt is one of the countries in the world that falls below the water poverty line, and the water scarcity in Egypt has been exacerbated over the last several years. Sustainable growth and food security in Egypt necessitate more efficient use of the country's water resources, particularly in the irrigation of crops and livestock. Therefore, this study analyzed the potential economic and social impacts of irrigation infrastructure development on Egypt's economic growth. Furthermore, it sought to ascertain whether investments directed toward irrigation modernization projects are sufficient to alleviate Egypt's water crisis, an essential question for Egyptian policymakers. The computable general equilibrium model was employed on the basis of a social accounting matrix for the Egyptian economy in its latest edition for the base year 2015. This study employed the latest version of the Agriculture Investment for Development Analyzer, developed by the International Food Policy Research Institute, which provided a more holistic account of the agricultural sector and a high diversity of population details. The results show that the effects of investments in irrigation are favorable for the economy but are relatively modest. Furthermore, the increase in investments in irrigation improves production in most sectors. Moreover, the GDP is anticipated to increase by 0.05% by 2030. In conclusion, adopting the modernization process for irrigation will enable Egypt to observe the success of the modernization program under various scenarios. Indeed, efforts to achieve irrigation modernization are insufficient heretofore. Finally, this study recommends that Egyptian policymakers invest more in developing irrigation infrastructure. [ABSTRACT FROM AUTHOR]

Climate change is a global phenomenon affecting the entire planet, including Sri Lanka. The Northern Province of Sri Lanka is particularly vulnerable to the impacts of climate change, especially regarding water resources. Public awareness of climate change and its impact on water resources is crucial for sustainable water management practices in the study area. In this context, this study attempted to analyze public perception of the climate change impact on the water resources of Northern Sri Lanka. There are different groups of water users in the study area. They were stratified as agriculture water users, industrial water users, fishing water users and domestic and drinking water users. Accordingly, a questionnaire survey was conducted using a stratified sampling method to identify consumer perceptions, and the collected data were analyzed using the SPSS tool. 87% of the consumers believe that climate change has a significant impact on water resources, and 50% of the people expressed vulnerability of the agriculture sector to the climate change impact on water resources. Water scarcity during the yala season became a crucial threat to paddy cultivation in the study area. Other kind of water users such as industrial water users, fishing water users and drinking and domestic water users face difficulties in obtaining water resources for their needs during the SWMS and FIMS. Furthermore, drinking and domestic water users mentioned that they face water quality issues especially during July, August and September. During the southwest monsoon season, water users face difficulties in obtaining water for their domestic needs due to water scarcity. Majority of the water users know about climate change, but many of them don't know how climate change affects their water sources. Water suppliers should implement special projects regarding climate change impacts on water resources in the study area. This will lead the water users to use water efficiently and protect the water sources sustainably. [ABSTRACT FROM AUTHOR]

The article discusses the risks that water scarcity and excess pose to agriculture, particularly in California. The authors, experts in civil and environmental engineering from UC Merced, highlight the impact of climate change, human interventions, and misaligned governance on water-related agricultural costs. They emphasize the challenges faced by California due to its diverse agricultural landscape and varying climate and water needs. The article also mentions the economic consequences of drought and the need for policies, programs, and tools to support agricultural resilience and mitigate water-related risks. [Extracted from the article]