Optimize Water Use Research Articles

Impact of alternative water policies for drought adaptation in the Guadalquivir Mediterranean river basin, southern Spain

Study regionThe Guadalquivir Basin in Spain as a representative Mediterranean basin. Study focusThe aim of this study is to assess the adaptive capacity of Mediterranean basins to long periods of severe drought. To do so, a hydro-economic model has been developed that includes a spatial representation of the major economic uses of water and enables an analysis of the economic and environmental effects of alternative water management policies under a single event of water scarcity. New hydrological insights for the regionResults highlight the trade-offs among economic uses of water and environmental flow requirements since water resources in the Guadalquivir are fully allocated. Moreover, the increase of irrigated perennial crops area will aggravate vulnerability to drought by limiting the adaptive capacity of the basin. Survival irrigation is the first option for farmers to adapt to the simulated extreme drought. 148,000 ha are shifted from normal irrigation to survival irrigation in the Drought Management Protocol scenario. These findings call for policy interventions to ensure greater management flexibility toward optimising water use while meeting environmental goals. For instance, enabling water trading among farmers would reallocate 22 % more water to the upper basin, reducing drought losses by 22 M EUR. The hydro-economic model developed here can be adapted to basins elsewhere and the results show that it can be a useful tool to guide the design of efficient water management policies to address severe droughts in water-stressed basins.

Farm Pond Technology for Crop Productivity Enhancement in Rainfed ecosystem of Marathwada Region of Maharashtra

Marathwada region is traditionally a drought-prone region. The region receives annual rainfall in the range of 500 to 1100 mm and major area comes under assured rainfall zone (60%). Rainfall in uncertain and erratic in this region and sometimes suffers from severe droughts. The productivity of all crops decreases with either deficiency of rainfall and its distribution or due to moisture stress in critical growth period due to dryspells occurred in July and August. Thus, protective irrigation to rain fed crops particularly during dryspells from harvested water in farm pond is important concept of dryland agriculture for assured crop production. Major crops of the region are soybean, cotton, pigeon pea, sorghum, green gram and black gram during kharif season. Similarly, gram, rabisorghum and safflower are grown in rabi season. Based on the farmers need, technical interventions were taken up under NICRA (National Innovations in Climate Resilient Agriculture) action research project through preparedness. Farmers had constructed farm ponds through Government schemes on their field for harvesting runoff water. Similarly farmers procured sprinkler set from the Government government schemes. Farmers were advocated to apply farm pond water using sprinkler set during critical dryspells period in kharif and during critical growth period in rabi season. Optimum use of farm pond water to soybean and pigeonpea during kharif season resulted in increase in crop yield up to 50 per cent. Similarly, application of farm pond water to gram in rabiseason resulted in productivity enhancement in gram.

Study and Development of IOT based Smart Irrigation System using Soil Moisture and Weather Prediction

Abstract: The smart irrigation system was developed to optimize water use of crops. The system has a distributed wireless network of soil-moisture temperature sensors placed in the root zone of the plants. Also, a gateway unit handles sensor information, triggers, actuators, and transmits data to the web application. The intelligence of The proposed system is based on a smart algorithm, which considers sensed data along with the weather forecast parameters like precipitation, air temperature, humidity, and UV for the near future. The complete system has been developed and deployed on a pilot scale, where the sensor node data is wirelessly collected over the cloud using web- services and a web-based information visualization and decision support system provides real-time information insights based on the analysis of sensor dataand weather forecast data. The paper describes the system and discusses in detail the information processing results of three weeks data based on the proposed algorithm. The system is fully functional and the prediction results are very encouraging

How Important for Society Is Recreation Provided by Multi-Purpose Water Reservoirs? Welfare Analysis of the Vltava River Reservoir System

Contrary to the other functions of multi-purpose reservoirs, recreational use is not associated with a tangible social value, which hinders the search for new balances among optimal uses of water that will likely be needed under climate change. The objective of this study is to analyze visitation behavior and its patterns at a large-scale reservoir system on the Vltava River to quantify the total social benefits associated with recreation in monetary terms and to suggest how the magnitude of estimated recreation welfare relates to hydro-energy benefits, which are in usual practice taken much more into account than recreation in the strategic management of water dams. The elicited average consumer surplus per person and trip is EUR 55.7, which yields a total yearly recreation value of EUR 34 billion (ranging between 22 and 57). When compared to, e.g., the social value of hydro-energy generation, the actual yearly recreation welfare represents 1/3 of this nowadays more prioritized use. The results of the study bring new information for water management bodies that has been missing up to now, and they bring new arguments for reaching socially optimal water use in the strategic and operational management of the cascade of dams. From this perspective, the actual strategic relative prioritization of these two reservoir functions at the pilot site may be viewed as rational.

Optimizing Water Use Efficiency in Arid Tunisia: An Economic Evaluation of Public Irrigated Schemes for Agricultural Development

Optimizing Water Use Efficiency in Arid Tunisia: An Economic Evaluation of Public Irrigated Schemes for Agricultural Development

A framework for the assessment of alternative uses in international water law

AbstractIn establishing an equitable and reasonable use of a transboundary watercourse, States are to take into consideration a variety of factors, including the availability of alternative uses. This article seeks to provide a framework for assessing such alternative uses by first exploring treaty practice and relevant cases across the fields of international environmental law and international water law. Three key components are identified: comparable feasibility, practicality and cost‐effectiveness of alternatives. These components are then explored through a case study of Central Asian transboundary waters. The results demonstrate that the use of alternatives after analysing key components would help reduce the hidden cost of low efficiency and assist in finding optimal water use solutions in transboundary water cooperation.

Impacts of Irrigation Technology, Irrigation Rate, and Drought-Tolerant Genetics on Silage Corn Production

Many studies have examined individual water-saving management practices for corn (Zea mays L.), but few studies have looked at how combinations of practices might further enhance water optimization. The research objectives of this paper were to evaluate the impact of irrigation technology, irrigation rate, and crop genetics, as well as their interactions, on silage corn yield and forage quality. Trials were conducted in three Utah locations from 2019 through 2021. The results from five site-years indicated that the best water optimization practices varied by site-year. Low-elevation sprinklers commonly applied water more efficiently, with four of the five site-years having improved or equivalent yield compared to mid-elevation sprinklers. Irrigation rate reductions and yield losses were not proportional, as a 25% irrigation reduction resulted in better silage quality and a 7% average yield loss across site-years. Further, targeted deficit irrigation (less water during vegetation and more during maturation) was inferior to a uniform deficit during all growth stages. Drought-tolerant genetics often maintained but did not improve yield in extreme water stress environments compared to non-DT genetics. No cumulative benefits were observed when combining irrigation technology, rate, and DT genetics. Irrigation technology had the greatest potential of the three factors to optimize water use in silage corn production in the Western U.S. region.

Toward Sustainable Farming: Implementing Artificial Intelligence to Predict Optimum Water and Energy Requirements for Sensor-Based Micro Irrigation Systems Powered by Solar PV

Future trends in climate change, water scarcity, and energy costs will motivate agriculturists to develop innovative agricultural systems. In order to achieve sustainable farming in arid regions, there is an urgent need to use artificial intelligence (AI) to predict and estimate the optimum water and energy requirements for the irrigation of date palms. Therefore, this study aimed to predict the optimum water and energy requirements for date palm irrigation depending on the optimum water use efficiency (WUE) and yield in arid conditions. To achieve this aim, four solar-powered micro irrigation systems were developed and evaluated under six irrigation levels for date palm irrigation. Soil moisture sensor-based controllers were used to automate irrigation scheduling for the micro irrigation systems. The water pumping in these systems was powered using a solar photovoltaic (PV) system. In addition, four machine-learning (ML) algorithms, including linear regression (LR), support vector regression (SVR), long short-term memory (LSTM) neural network, and extreme gradient boosting (XGBoost), were developed and validated for prediction purposes. These models were developed in Python programing language using the Keras library. The results indicated that the optimum WUS was achieved when the maximum setpoints of irrigation control were adjusted at the field capacity and by adjusting the minimum setpoints at 40, 50, 70, and 80% of the available water (AW). The optimum yield was achieved by adjusting the minimum setpoints at 60, 70, 80, and 90% of AW for subsurface irrigation, subsurface drip irrigation, drip irrigation, and bubbler irrigation, respectively. Therefore, the dataset was prepared at these levels for four years to train and test the models, and a fifth year was used to validate the performance of the best model. The evaluation of the models showed that the LSTM followed by XGBoost models were more accurate than the SVR and LR models for predicting the optimum irrigation water and energy requirements. The validation result showed that the LSTM was able to predict the water and energy requirements for all irrigation systems with R2 ranging from 0.90 to 0.92 based on limited meteorological variables and date palm age. The findings of the current study demonstrated that the developed LSTM model can be a powerful tool in irrigation water and energy management as a fast and easy-to-use approach.

Water Availability in China's Oases Decreased Between 1987 and 2017

AbstractThe significant expansion of China's oases during recent decades has inevitably increased water demand, profoundly affecting the regional water budget. While streamflow and precipitation have increased in China's oases under climate change, it remains uncertain whether this augmented water supply will suffice to meet the increasing water demand of oases, presenting a great challenge to guarantee regional water security. Here we used a process‐based crop water model, oasis land use datasets, vegetation maps, and observational data on streamflow and grain production to estimate the impacts of China's oasis dynamics on regional water resources from 1987 to 2017. We found that the water demand in oases significantly increased during 1987–2017, and oasis areas that have existed since 1987 accounted for a greater proportion of the increased water demand than newly expanded oasis areas. Although increases in precipitation and streamflow largely offset the additional water demand, 60.3% of counties in oasis regions experienced a decrease in water availability after 1987 because of a spatiotemporal mismatch between water supply and demand, and some counties suffered water deficits. Our findings provide a quantified basis for identifying and optimizing water use structures for water security in oases.

Relationship between Indigenous Knowledge Development in Agriculture and the Sustainability of Water Resources

The relationship between agricultural knowledge and water management is very important. Indigenous knowledge in agriculture can improve the water crisis situation and alleviate water stress from dry and semi-arid areas. Therefore, the combination of these two impacts can improve the agricultural sector and reduce the effects of drought. The purpose of this study was to investigate the factors affecting indigenous knowledge and the sustainable management of water resources for optimal water use in agriculture in the Sistan region of Iran. Alongside field research and interviews with 40 indigenous experts and experts from the Jihad-e-Agriculture sector of the Sistan region, the required information was collected by means of a questionnaire. Using the fuzzy hierarchy process (FAHP), the factors affecting indigenous knowledge and the sustainable management of water resources for optimal water use in the Sistan region were ranked. The final rankings of the factors influencing indigenous knowledge for optimal agricultural use of water resources indicate that the educational-extensional factor, with a final weight of 0.37, is the first priority, while social factors, government support, economics, farmers’ knowledge, and information, with weights of 0.24, 0.21, 0.13, and 0.03, respectively, are the next priorities. It is recommended that the indigenous knowledge of local authorities be augmented, and that farmers be encouraged to use modern irrigation techniques to optimize the agricultural irrigation of water.

Organic mulches as an alternative for under-vine weed management in Mediterranean irrigated vineyards: Impact on agronomic performance

One of the main challenges for organic vineyards is weed management. Weeds tend to compete for water and nutrients, and can cause large yield reductions. Traditional under-vine weed management in organic vineyards consists on mechanical cultivation along the season, which is associated to soil and young vine root damages, and to high fuel consumption. Thus, sustainable alternatives need to be found. Cover crops are becoming common in the last decades due to their multiple benefits in agroecosystems. Nevertheless, under-vine cover crop implementation in Mediterranean vineyards is limited as this competes for resources (water and nutrients), reducing the yield, vegetative development, and grape size of vines. The use of organic mulches could overcome all these problems, while benefitting vine performance. In the present work, the response of vines, soil and weeds to mulching was evaluated. An experiment was carried out in Raimat, Lleida (Catalonia, NE Spain) in a commercial vineyard from 2019 to 2021, and the following treatments applied: 1) mechanical cultivation with an in-row tiller; 2) mowing a permanent spontaneous cover with an in-row mower; 3) almond shell mulch; and 4) chopped pine wood mulch. Results showed lower weed cover along the three seasons in mulched treatments, as well as higher yield, better vine water status, and greater vegetative development from traditional measurement. The latter was confirmed by and analised with further detail with measurements acquired with a mobile terrestrial laser scanner (MTLS) based on light detection and ranging (LiDAR) sensors. Besides, petiole nutrient status was better in vines without a spontaneous living cover. Organic mulches improved vine performance and weed control, so these results allow to optimize water use efficiency in the Mediterranean basin with scarce water resources. Mulching can be considered as a useful strategy that enhances a more sustainable viticulture.

Optimal Tape Spacing and Water Use Efficiency for Wheat Crop on Silty Clay Loam Soil Texture

Optimal Tape Spacing and Water Use Efficiency for Wheat Crop on Silty Clay Loam Soil Texture

BRIEF HYDROGEOLOGICAL STUDIES OF WATERSHED MR-21 IN CONTEXT OF GROUNDWATER ESTIMATION AND GROUNDWATER RECHARGE PLAN, OSMANABAD, MAHARASHTRA, INDIA

The global population is increasing rapidly and expected to touch the 9.5 billion mark by 2050 from the current 7.2 billion. The management of the groundwater resources is a challenging task worldwide against the backdrop of the growing water demand for industrial, agricultural, and domestic uses and shrinking resources. Moreover, this task has been hampered significantly due to declining/rising groundwater levels and associated contamination. A broad range of solutions could be considered to address the aforementioned problems of groundwater management strategy. This paper presents a comprehensive review on the Water level, Rainfall, Groundwater estimation and cropping pattern of the studied area which can be useful for applications of the management of groundwater resources and recharge techniques.It would also be necessary to plan, recharge and control the use of groundwater under the prevailing conditions. Publication and distribution of annual reports and related programmes for creating awareness amongst the community and for educating them will have to be undertaken regularly. This will enable avoiding scarcity in the studies area, as well as the hectic activity and excessive expenditure that has become characteristic of summer months in the marathwada and adjacent area. The present study discussed about the optimum planning of GW recharge and need to control the irrigation draft less than the recharge for future use. Application of Regulatory measures for not drilling bore wells. Optimum use of water saving practices. There should be annual GW budgeting on regular basis, need to plan cropping as per GW availability.

Effects of shade and deficit irrigation on maize growth and development in fixed and dynamic AgriVoltaic systems

Maize production is essential for global food security and represents a major supply in several value chains. However, the projected effects of climate change are likely to decrease drastically water availability for crops in many regions, affecting yield. AgriVoltaics (AV) systems are an innovative solution that may improve maize resilience in water-scarce regions mainly by protecting plants from excessive radiation and by reducing irrigation needs. However, shade from panels may also affect crop development and production. This study addresses the interplay between radiation transmission, crop development and irrigation needs of maize cropping in field conditions, by the description of crop development dynamics, distinguishing between fixed and dynamic panels. We showed that maize crop responded to both independent and combined stresses (shade and water deficit), with a significant decrease in leaf area index, total dry matter and grain yield. Concerning water use, we showed the potential of AV to reduce irrigation inputs (by up to 19–47% compared to unshaded plots) via reduced soil water depletion and reference evapotranspiration. The crop development was impacted by shade by increasing phyllochron and causing a generalized delay in phenology. At a finer temporal scale, we concluded that maize leaves react to shade by reducing stomatal conductance, net assimilation of CO2 and leaf temperature in a correlated way to radiation, opening the possibility to use this behavior to optimize water use and shading strategies. The spatial heterogeneities of radiation in fixed AV systems, compared to dynamic AV systems, were identified as a second-order effect at the plot level on leaf area index and phyllochron, compared to the effect of radiation reduction. Moreover, dynamic AV showed their ability to reduce the spatial heterogeneities in soil water depletion, showing the importance of controlled shade strategies in AV systems concerning water use.

The Interactive Effects of Deficit Irrigation and Bacillus pumilus Inoculation on Growth and Physiology of Tomato Plant.

The effects of inoculating plant growth promoting rhizobacteria (PGPR) and soil water deficits on crop growth and physiology remain largely unknown. Here, the responses of leaf gas exchange, growth, and water use efficiency (WUE) of tomato plants to Bacillus pumilus (B.p.) inoculation under four irrigation strategies (I1-I4) were investigated in a greenhouse. Results showed that soil water deficits, especially at I4 (20%, v/v), significantly decreased leaf stomatal conductance (gs), transpiration rate (Tr), and photosynthetic rate (An), and the decrease of gs and Tr were more pronounced than An. Reduced irrigation regimes significantly lowered dry matter and plant water use both in the non-B.p. control and the B.p. plants, while reduced irrigation significantly increased plant WUE, and B.p. inoculation had little effect on this parameter. Synergistic effects of PGPR and deficit irrigation on leaf gas exchange, leaf abscisic acid content, and stomatal density were found in this study, and specifically, B.p. treated plants at I4 possessed the highest WUE at stomatal and leaf scales, suggesting that B.p. inoculation could optimize water use and partly alleviate the negative effects of soil water deficit. These findings provide useful information for effective irrigation management and the application of PGPR in agriculture in the future.

Smart IoT lysimetry system by weighing with automatic cloud data storage

Water is an essential resource for human life and for agricultural food production, climate change and the increased demand for water resources, has already impacted the availability of this resource in the world, in view of future forecasts of scarcity its rational use will be increasingly demanded. Thus, more efficient irrigation systems that optimize water use and reduce water loss will be important tools to help agriculture in the future. This work aims to develop and calibrate an intelligent and autonomous system for determining reference evapotranspiration (ETo), and precise irrigation control optimized for IoT operation, with data storage in a cloud database. Intelligent system integrates: mechanical weighing lysimeter; sensors and actuators commanded by a digital controller based on a microcontroller platform, connected to the internet through a Wi-Fi communication interface to cloud computing services models: platform as a service (PaaS) and software as a service (SaaS). The operation test results reveal that the system is capable of accurately measuring ET O values, consistent with the values estimated by the FAO-56 standard method, with high sensitivity and precision for determining mass variations, with an R² Correlation coefficient = 0.999321, and coefficient of determination of adjusted R² of 0.999321. Being a viable option for application in precision agriculture.

Potential of the hazelnut tree search–ELM hybrid approach in estimating yield and water productivity

Wheat plays a vital role in the food security of society, and early estimation of its yield will be a great help to macro-decisions. For this purpose, wheat yield and water productivity (WP) by considering soil data, irrigation, fertilizer, climate, and crop characteristics and using a novel hybrid approach called hazelnut tree search algorithm (HTS) and extreme machine learning method (ELM) was examined under the drip (tape) irrigation. A dataset including 125 wheat yield data, irrigation and meteorological data of Mahabad plain located southeast of Lake Urmia, Iran, was used as input parameters for crop year 2020–2021. Eighty percentage of the data were used for training, and the remaining 20% for model testing. Nine different input scenarios were presented to estimate yield and WP. The efficiency of the proposed model was calculated with the statistical indices coefficient of determination (R2), root-mean-square error (RMSE), normalized root-mean-square error, and efficiency criterion. Sensitivity analysis result showed that the parameters of irrigation, rainfall, soil moisture, and crop variety provide better results for modeling. There was good agreement between the practical values (field management data) and the estimated values with the HTS–ELM model. The results also showed that the HTS–ELM method is very efficient in selecting the best input combination with R2 = 0.985 and RMSE = 0.005. In general, intelligent hybrid methods can enable optimal and economical use of water and soil resources.

Optimization of irrigation management and environmental assessment using the water cycle algorithm

AbstractObtaining high crop yields with limited water consumption requires optimal irrigation strategies based on comprehensive studies of the parameters of plant–environment interactions. Here, we used a structural equation modelling (SEM) to assess the relationships among input irrigation factors and moderate factors to find an optimum water use efficiency (WUE) response factor, for outdoor and greenhouse cultivation of eggplant (Solanum melongena). The input irrigation factors (including irrigation interval, water salinity and environment) and the moderate factors (evapotranspiration, soil salinity, plant parameters, fruit parameters and crop yield) were used in water cycle algorithm (WCA) and genetic algorithm (GA) methods to optimize the water use efficiency. The optimization process included finding the best combination of irrigation factors and optimized eggplant cultivation. The structural equation modelling results indicate that irrigation interval negatively affected water use efficiency with a more dominant effect on plant parameters. Water salinity negatively affected the water use efficiency with a more dominant effect on soil salinity, crop yield and fruit parameters. Low salinity water was more effective than full irrigation to optimize the water use efficiency. The water cycle algorithm revealed that for outdoor cultivation, the optimal range of irrigation interval was 2–5 days and water salinity in the range of 0.8–2.2 ds/m. These factors optimized evapotranspiration (346.23–738.19 mm), soil salinity (4.16–9.45 ds/m), fruit parameters (33.81–35.12 cm) and crop yield (1715.7–2190.8 g/plant), as well as increasing the water use efficiency (3.08–4.89 g/(plant‐mm)). Both the water cycle algorithm and genetic algorithm yielded very close to optimal values. Two years of repeated experiments and the closeness of the optimal values using the algorithms confirmed that the optimal amounts are reliable.

Irrigation management of common bean cultivars with contrasting growth habits

A study was undertaken comparing the water requirements of two common bean ( Phaseolus vulgaris L.) cultivars to generate specific recommendations aimed at optimizing water use. To accomplish this work, the agronomic performance, responsiveness to water and water productivity of these two common bean cultivars of determinate and indeterminate growth habits were identified. The 2-year experiment was carried out during the winter growing season in the southeast of Brazil. Cultivars IAC Imperador, with an early season of determinate growth habit, and IPR Campos Gerais, having a mid-season of indeterminate growth habit, were subjected to five irrigation levels (54, 70, 77, 100, and 132 % of the crop evapotranspiration). Water deficit affected agronomic performance, reducing plant height (by up to 29 %), leaf area index (by up to 40 %), soil cover fraction (by up to 28 %), and grain yield (GY - by up to 31 %), in both cultivars. In contrast, excess water was more detrimental to cultivar IAC Imperador. Cultivar IPR Campos Gerais produced 18 % more than GY, showing superior water productivity and response to irrigation depth than IAC Imperador. Out of all the variables evaluated, the soil cover fraction correlated the most with grain yield in both common bean cultivars during the 2-year study. In other words, cover fraction evaluation in common bean allows for estimating crop production potential, which helps producers and technicians in their decision making regarding management practices. Thus, a cultivar directly affects water use in common bean production, thereby suggesting the need for a or water conservation strategy and sustainability of irrigated common bean production.

ORBITAL REMOTE SENSING FOR THE MANAGEMENT OF AREAS IRRIGATED WITH A CENTRAL PIVOT SYSTEM

Irrigated agriculture is considered one of the most important techniques for agricultural production in the world, despite being the sector that uses water resources the most. Thus, technological advances have been constantly developed and applied in the sector as a way to improve water management and reduce its consumption, considering that some cultures are affected by economic costs and feasibilities of production, because the water cost has increased significantly in recent years. Remote sensing is a technology that has provided good results for estimating evapotranspiration (ETr) in producing areas, enabling more efficient irrigation management for low costs. This study aimed to answer the question about how the generation of irrigation management zones (IMZs) can be used to optimize water use and improve irrigation systems and which ETr models are better for it. Three ETr estimation models (Surface Energy Balance Algorithm for Land [SEBAL], Mapping Evapotranspiration at High Resolution and with Internalized Calibration [METRIC] and Simple Algorithm for Evapotranspiration Retrieving [SAFER]) were used to design IMZs in center pivot cultivated with cotton. The design of IMZs with ETr data proved to be a viable alternative, making it possible to improve water management in irrigated systems, reducing costs with viability irrigation for cotton and others cultures. The METRIC method displayed the greatest ease in obtaining the data used in the ETr estimation for generating the IMZs.