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This study aims to enhance maize water demand calculation. We calculate crop evapotranspiration (ETc) through mobile phone photography and meteorological parameters. In terms of crop coefficient (Kc) calculation, we utilize the mobile phone camera image driver to establish a real-time monitoring model of Kc based on plant canopy coverage (PGC) changes. The calculation of PGC is achieved by constructing a PGC classification network and a Convolutional Block Attention Module (CBAM)-U2Net is implemented by the segment network. For the reference crop evapotranspiration (ETo) calculation, we constructed a simplified ETo estimation model based on SVR, LSTM, Optuna LSTM, and GWO-SVM using a public meteorological data-driven program, and evaluated its performance. The results demonstrate that our method achieves high classification accuracy for the PGC 98.9% and segmentation accuracy for the CBAM-U2net-based segmentation network 95.68%. The Kc calculation model exhibits a root mean square error (RMSE) of 0.053. In terms of ETo estimation, the Optuna-LSTM model with four variables demonstrates the best estimation effect, with a correlation coefficient (R2) of 0.953. The final R2 between the estimated ETc value and the true value is 0.918, with an RMSE of 0.014. This method can effectively estimate the water demand of maize.

As water scarcity intensifies due to climate change, improving the efficiency of agricultural water use has become increasingly critical. Current irrigation systems often experience significant water losses, especially in paddy fields in South Korea that largely rely on open-channel water supply networks. However, previous studies have simulated irrigation improvement strategies by aggregating multiple paddy fields into larger unites rather than modeling them individually, which limits the accurate representation of field conditions. To address this limitation, we applied a granular simulation approach, collecting detailed input data through field surveys. Using this granular model, the study evaluated strategies to enhance irrigation efficiency in paddy fields serviced by the Baekma Agricultural Reservoir in South Korea. We assessed four scenarios: the current open-channel system, conversion of open channels to closed conduits, installation of farm ponds, and a combination of closed conduits and farm ponds. These scenarios were simulated using the Strom Water Management Model (SWMM), meticulously configured to represent individual paddy fields and channel networks. The results show that converting open channels to closed conduits increased irrigation efficiency by 5.4% compared to the current open-channel system. Combining closed conduits with farm ponds achieved the highest efficiency, although the independent effect of farm ponds was minimal. These findings suggested that converting open-channels to closed conduits was a highly effective solution for reducing water losses, while farm ponds played a limited role. This study provides valuable insights into the development of precise irrigation strategies, offering a detailed assessment of real-world conditions in paddy fields.

The main aim of this paper was to analyze the sensitivity of the five infiltration equations (Kostiakov, Kostiakov–Lewis, Philip, Horton and SCS) and their coefficients to various ponding depths and initial soil moisture under different irrigation managements. The treatments included three qualities of water (electrical conductivity = 6, 3 and 0.6 dS/m), two managements of irrigation (intermittent irrigation and daily irrigation) and three irrigation periods (100, 45 and 8 days). The HYDRUS-1D model was calibrated to simulate infiltration in various initial soil moistures and ponding depths. Evaluating the performance of infiltration equations showed that the Horton and Kostiakov–Lewis had better accuracy and Kostiakov and SCS had less accuracy than the other equations. The empirical coefficients of SCS and Kostiakov had the most and least sensitivities, respectively. Furthermore, Horton was the most sensitive equation, while SCS was the least sensitive one. The output parameters under daily management were the most sensitive to variations in infiltration coefficients, especially when the salinity and sodium contents of water and soil were higher. The results also showed that the effect of the initial soil moisture on the infiltration coefficient in high permeable soil (arising from daily management) was greater; but in low permeable soil (arising from intermittent management), the ponding depth was more effective. It is concluded that the infiltration equations (specifically the SCS equation) and their coefficients (specifically coefficient c) should be calibrated relative to the initial soil moisture, ponding depth, soil solution and water irrigation quality. Particularly in areas with high permeable soil (in the daily management), the calibration of the infiltration equation should be conducted with the initial soil moisture. In these areas, the irrigation period should be controlled. In areas with low permeable soil (in intermittent management), calibration should be carried out relative to the ponding depth. In these areas, the inflow rate should be controlled.

Water scarcity will increase due to climate change, especially in basins that are currently highly stressed. The Mediterranean area is one of the most vulnerable areas in the world, with a predicted natural water resource reduction of 20% to 35% at the end of the century, due to temperature increases and a 10–20% precipitation reduction. Water scarcity indices, including gross abstraction, net abstraction, and consideration of environmental requirements, can be efficiently used to analyse the effects of climate change in water resource systems and determine the main measures to adapt these systems to climate change. Increasing the reclaimed water use, seawater desalination, irrigation efficiency, and interconnecting water resource systems are the main measures to adapt basins under water stress and reduce their vulnerability to climate change. In the Júcar River Basin District (JRBD), with a 20% reduction in natural water resources, the main measures are: increasing the reclaimed water use in agriculture from 20% to 50% (91 hm3/year to 230 hm3/year), increasing seawater desalination from 30 to 55 hm3/year, increasing irrigation efficiency from 54% to 80%, and finally, fully developing the current water interconnections between water resource systems. In highly stressed basins, moving water from downstream to upstream using energy supplied by photovoltaic systems can help adapt river basins to climate change.

Currently, irrigation consumes approximately 84 per cent of the total available water in India and is predicted to remain the dominant water user. This study assessed the barriers to canal irrigation efficiency in Jharkhand State of India. Through an extensive review of the literature and expert consultation, the study classified the barriers into five primary categories: Resource System, Legal and Institutional, Financial Barriers, Capacity Building, and External Environment. This study applied an integrated approach using the Analytic Hierarchy Process (AHP), fuzzy Analytic Hierarchy Process, and decision-making trial and evaluation laboratory approach to assess the issues prevailing in canal irrigation efficiency. The experts were selected based on their expertise and knowledge, and they provided their preferences on the weighting of the models for applying the three methods. From the study, it can be inferred that more attention is needed to reduce Financial Barriers to improve the overall performance of irrigation projects. This necessitates adequate government funding and collection of water rates. The lack of government support/funding and low collection of water charges make WUAs financially unviable and unable to bear the Operation and Maintenance costs and incurs high maintenance costs, resulting in capital loss.

In rice areas with shallow aquifers, an evaluation of alternative irrigation strategies should include the interactions between irrigation and groundwater recharge and reuse, which influence the overall irrigation efficiency. A modelling system composed of three sub-models within a MATLAB framework (a physically based, semi-distributed agro-hydrological model and two empirical models, the former for the channel network percolation and the latter for the groundwater level) was applied to a 1000 ha rice district in the Padana Plain, Italy. The calibrated framework estimates the daily time series of the water supply needed and of the groundwater level for a given irrigation management, based on the inputs provided (agro-meteorology, crop data, soil data, irrigation practices, groundwater table depth upstream of the study area). Five irrigation management strategies, relevant to the area, were compared: (i) wet seeding and continuous flooding (WFL), (ii) wet seeding and alternate wetting and drying (AWD), (iii) dry seeding and delayed flooding (DFL), (iv) dry seeding and fixed-turn irrigation FTI), (v) early dry seeding and delayed flooding (DFLearly). Due to economic advantages, dry-seeded techniques (DFL, FTI) are replacing the traditional WFL in northern Italy. Simulations show that dry seeding leads to a drastic decrease of the water table in April/May, reducing the overall irrigation efficiency of the area, and that DFL (widely adopted in the area) also causes a spike in rice irrigation needs in June when other crops increase their water demand, exposing the area to water scarcity. All the cited management strategies are assessed in the paper and AWD turned out to couple smaller irrigation needs (from June onwards) compared to continuous flooding techniques with a maintenance of the groundwater recharge, especially in the first part of the irrigation season, thus being a recommendable rice management alternative for the study area.

Water is one of the most determining factors in obtaining high yields in oil palm crops. However, water scarcity is becoming a challenge for agricultural sustainability. Therefore, when the environmental supply of water is low, it is necessary to provide it to crops with the highest degree of efficiency. However, although irrigation technologies are available, for various reasons farmers continue to use inefficient irrigation systems, which causes resource losses. The objective of this study was to analyze the percentage of adoption of irrigation technologies for water management in oil palm crops and to classify the factors influencing their adoption by producers. The method for the classification of influential factors was based on multiple correspondence analysis and perceptron neural networks. The results showed that fewer than 15% of the producers adopt irrigation technologies, and the factors classified as influential in the adoption decision were the age of the palm growers, the size of the plantation, and the access to extension services. These results are the basis for the formulation of effective and focused extension strategies according to the characteristics of the producers and the local and technological specificity.

Nowadays, the leading role of data from sensors to monitor crop irrigation practices is indisputable. The combination of ground and space monitoring data and agrohydrological modeling made it possible to evaluate the effectiveness of crop irrigation. This paper presents some additions to recently published results of field study at the territory of the Privolzhskaya irrigation system located on the left bank of the Volga in the Russian Federation, during the growing season of 2012. Data were obtained for 19 crops of irrigated alfalfa during the second year of their growing period. Irrigation water applications to these crops was carried out by the center pivot sprinklers. The actual crop evapotranspiration and its components being derived with the SEBAL model from MODIS satellite images data. As a result, a time series of daily values of evapotranspiration and transpiration were obtained for the area occupied by each of these crops. To assess the effectiveness of irrigation of alfalfa crops, six indicators were used based on the use of data on yield, irrigation depth, actual evapotranspiration, transpiration and basal evaporation deficit. The series of indicators estimating irrigation effectiveness were analyzed and ranked. The obtained rank values were used to analyze the similarity and non-similarity of indicators of irrigation effectiveness of alfalfa crops. As a result of this analysis, the opportunity to assess irrigation effectiveness with the help of data from ground and space-based sensors was proved.

China is implementing a pilot project to reform the property rights of farmland water facilities to solve the serious problems of chaotic end-of-pipe governance and inefficient irrigation from farmers. Based on microscopic research data of farm households in a typical pilot in Lu Liang County, Yunnan Province, in China, this study uses the Tobit model, and SEM was used to explore the impact of property rights reform on the irrigation efficiency of farmers and the potential mechanism paths. We further analyzed the differences in governance logic and irrigation efficiency between the two property rights models of “multiple cooperative governance” and “private contract governance” formed after the reform. The findings are as follows: (1) Compared with nonreformed areas, reformed areas have a higher promotion of adoption of water-saving technologies and a better quality of facility maintenance, which significantly contributes to irrigation efficiency, but farmers’ perception of water scarcity negatively affects irrigation efficiency; (2) there are differences between the “multiple cooperative governance model” and “private contract governance model” in terms of the mechanism paths to improve irrigation efficiency, resulting in different focuses between the two models, in which the former one has better irrigation efficiency while cutting off some of the farmers’ benefits and the latter benefits more farmers while losing some of the irrigation efficiency. Finally, this study recommends that China should continue to promote the reform of farmland water property rights while focusing on promoting water conservation technologies, improving the quality of facility maintenance and facility water supply capacity, enhancing farmers’ awareness of water scarcity, and implementing a more water-efficient “multiple cooperative governance model”. The results of this study provide a model with Chinese characteristics for developing property rights policies and governance models for farmland water facilities in developing countries.

In the view of increasing water demands in agriculture, efficient water use is a key factor in potato production. The aim of this study was to compare two deficit (80% and 90%) and one abundant (120%) gun sprinkler irrigation levels with the longtime used irrigation level of a farmer (100%). Irrigation was supplied during the 2021 growing season on a loamy sand site in Mecklenburg–Western Pomerania, Germany. Yield and tuber quality of the high-amylopectin potato (HAPP) variety “Waxy/Henriette” were assessed in a three-grade tuber size distribution. Five economic indicators were used to assess the suitability of the investigated irrigation levels to secure economic responses. Yield and starch yield did not significantly differ between the 90% (561.1 dt ha−1 and 102.0 dt ha−1) and the 100% irrigation levels (559.1 dt ha−1 and 102.3 dt ha−1), with total production increasing by 2.0 dt ha−1 and starch production decreasing by 0.4 dt ha−1 at the 90% irrigation level. Tuber lesions decreased the economic responses at all irrigation levels. Potentially, 87,469 m3 of irrigation water (125.8 m3 ha−1) could have been saved on the loamy sand starch potato sites of the local farm (695.3 ha) in 2021.

The global increase in potato production and yield is expected to lead to increased irrigation needs and this has prompted concerns with respect to the sustainability of irrigation water sources, such as groundwater. The magnitude, and inter- and intra-annual variation, of the crop water requirements and irrigation needs for potato production together with their impact on aquifer storage in a temperate humid region (Prince Edward Island, Canada) were estimated by using long-term (i.e., 2010–2019) daily soil water content (SWC). The amount of supplemental irrigation required for the minimal irrigation scenario (SWC = 70% of field capacity; 0.7 FC) was relatively small (i.e., 17.0 mm); however, this increased significantly, to 85.2 and 189.6 mm, for the moderate (SWC = 0.8 FC) and extensive (SWC = 0.9 FC) irrigation scenarios, respectively. The water supply requirement for the growing season (GS) increased to 154.9 and 344.7 mm for a moderately efficient irrigation system (55% efficiency) for the SWC = 0.8 FC and SWC = 0.9 FC irrigation scenarios, respectively. Depending on the efficiency and the areal extent of the irrigation system, the irrigation water supply requirement can approach or exceed both the GS and annual groundwater recharge. The methodology developed in this research has been translated into a free online tool (SWIB—Soil Water Stress, Irrigation Requirement and Water Balance), which can be applied to other areas or crops where an estimation of soil water deficit and irrigation requirement is sought.

The solar greenhouse is a common protected structure for crop production when ambient temperatures are low. In the North China Plain (NCP) winter temperatures are very low and an improved solar greenhouse with a lowered soil surface (0.5–1.5 m deep), referred to as a sunken solar greenhouse (SSG), is used. A four-season experiment was conducted in a commercial SSG with tomato crops to characterize internal microclimate, sap flow (SF) and crop coefficients. Results show that temperature inside the SSG could be more than 20 °C higher than outside in winter, which favors tomato growth and resulted in acceptable yields. Daily total SF was related to solar radiation, vapor pressure deficit (VPD) and temperature, in that order, both in winter and summer. The decoupling coefficient (which is the ratio of radiative to aerodynamic influences on evapotranspiration) in daytime was 0.76 in winter and 0.84 in summer, indicating strong decoupling (i.e., predominance of radiative influences) of the internal environment where wind speed was low. Basal crop coefficients at the mid stage of crop growth averaged 1.15–1.43 in winter and 0.91–0.92 in spring and summer. Thus, in the SSG, for similar climatic conditions sap flow in winter was higher than that in summer, which should be considered in irrigation scheduling.

Urban green spaces can be intensive water and energy consumers in the cities, particularly in water scarce regions. Though a very efficient use of such resources is necessary, tools for assessing both water and energy consumption and efficiency are not available. In this paper, a new methodology based on water and energy balances is developed for assessing the water-use and energy efficiency in urban green spaces. The proposed balances, adapted from those developed for water supply systems, are specifically tailored for accounting for urban green spaces specificities, namely, landscape water requirements, other uses besides irrigation and over irrigation water losses. The methodology is demonstrated in two case studies of different nature and characteristics: a modern garden with a smart irrigation system and an urban park with traditional irrigation system. The results show that the developed water balances allow to estimate and assess the irrigation efficiency over the years and to assess the effectiveness of implemented water saving measures. The application of the water–energy balance demonstrates the impact of water efficiency measures on the energy efficiency of the irrigation systems. The proposed methodology can be used to assess water and water–energy efficiency in urban green spaces and to identify the most adequate improvement measures, contributing for a better management of the two resources in the cities.

Improving irrigation efficiency (IE) is an approach used globally to help meet competing demands for water and facilitate reallocation of water between sectors. In the Murray–Darling Basin in Australia, the Australian government has invested heavily in IE projects to recover water for the environment. However, this approach has been seriously questioned, out of concerns that improved IE would reduce irrigation return flows to rivers and therefore offset water recovery. In this study, we use a water balance model to assess the impact of the IE projects on return flows and highlight sensitivities and uncertainties. The model enables the impact on return flows to be assessed on specific IE projects and regional characteristics. Overall, reductions in return flows are estimated to be less than 20% of the total proposed IE savings. The history of IE in the southern MDB has meant that most of the current reductions are in ground return flows. Our estimate is much lower than two previous studies, mainly due to different assumptions being used on groundwater connectivity between irrigation areas and major streams. While the IE projects significantly reduce seepage to groundwater (with off-farm and on-farm projects reducing seepage by 19% and 53% of total savings respectively), not all seepage reductions will translate to a reduction in ground return flows to rivers. A lower estimate is consistent with existing monitoring and groundwater modeling studies. In this paper, the study results are discussed in a broader context of impacts of IE projects on volumes and salinity of streams and groundwater resources.

Exploring the dynamic mechanisms of coupled sociohydrologic systems is necessary to solve future water sustainability issues. This paper employs system dynamics modeling to determine hydrologic and economic implications of an irrigation efficiency (IE) policy (increased conveyance efficiency and field efficiency) in a coupled sociohydrologic system with three climate scenarios. Simulations are conducted within the lower Rio Grande region (LRG) of New Mexico for the years 1969 to 2099, including water, land, capital, and population modules. Quadrant analysis is utilized to compare the IE policy outcomes with the base case and to categorize results of simulations according to hydrologic and economic sustainability. The four categories are beneficial, unacceptable, unsustainable agricultural development, and unsustainable hydrology. Simulation results for the IE policy analyzed here fall into the categories of unsustainable agricultural development or unacceptable, suggesting there are long-term negative effects to regional economies in all scenarios with mixed results for hydrologic variables. IE policy can yield water for redistribution as increased unit water supply in the field produces more deep percolation; however, IE policy sacrifices regional connectivity. Specifically, simulation results show that the policy increases abundance by 4.7–74.5% and return flow by −3.0–9.9%. These positive results, however, come at the cost of decreased hydrologic connectivity (−31.5 to −25.1%) and negative economic impacts (−32.7 to −5.7%). Long-term net depletions in groundwater are also observed from loss of hydrologic connectivity and increased agricultural water demand from projections of increased consumptive use of crops. Adaptive water management that limits water use in drought years and replenishes groundwater in abundant years as well as economic incentives to offset the costs of infrastructure improvements will be necessary for the IE policy to result in sustainable agriculture and water resources.

Irrigation sustainability is particularly important in the vicinity of Doñana National Park (Huelva, Spain), where Europe’s most important wetland area coexists with a profitable strawberry irrigation activity. In this paper, an innovation and technology transfer project was laid out. The project was promoted by the Institute of Agricultural and Fisheries Research and Training (IFAPA), belonging to the Regional Government of Andalusia. The main objective of the project was to contribute to the sustainability of the complex ecological, productive, and social system of this region. The project was focused on the rational use of water resources. Experimentation, demonstration, technology transfer, and training activities were carried out, involving public administrations, companies, and private farms. The project was carried out in collaboration with strawberry companies covering a total surface area of 1900 hectares. Irrigation application efficiency and irrigation water productivity increased by 66% and there was also a significant increase in water saving (44%), without resulting production losses. The success of the activity was based on the implication of farmers in experimentation assignments. During a five-year time span, irrigation trials took place on several farms. This fact allowed a progressive improvement of irrigation management by farmers based on confidence in the experimental work results.

The primary objective of this study is to estimate and evaluate the technical efficiency of irrigation water use in soybean (Glycine max L.) production in Louisiana, USA. We conducted a farm-level survey to assess information regarding irrigation cost, the volume of water application, and crop yield per acre during the crop year 2016. We use smoothed heterogeneous bootstrapping procedures in conventional data envelopment analysis (DEA) and supplement it with a nonradial measure of efficiency known as the Russell measure. The irrigation efficiency scores obtained from both an input- and an output-based DEA approach indicate that producers are over-applying irrigation water by approximately 37 percent. The results provide evidence that an improvement in water management practices can optimize irrigation efficiency, leading to higher profits for the farmers by lowering the other input prices in the production process. The findings should provide a benchmarking tool to formulate an appropriate irrigation policy that enhances water conservation in crop production in regions with similar environmental conditions and soil characteristics.

Vertical soil moisture profiles based on the principle of maximum entropy (POME) were validated using field and model data and applied to guide an irrigation cycle over a maize field in north central Alabama (USA). The results demonstrate that a simple two-constraint entropy model under the assumption of a uniform initial soil moisture distribution can simulate most soil moisture profiles that occur in the particular soil and climate regime that prevails in the study area. The results of the irrigation simulation demonstrated that the POME model produced a very efficient irrigation strategy with minimal losses (about 1.9% of total applied water). However, the results for finely-textured (silty clay) soils were problematic in that some plant stress did develop due to insufficient applied water. Soil moisture states in these soils fell to around 31% of available moisture content, but only on the last day of the drying side of the irrigation cycle. Overall, the POME approach showed promise as a general strategy to guide irrigation in humid environments, such as the Southeastern United States.

Future agricultural development will be challenged by the impacts of climate change on water, which are expected to be particularly strong in southern European regions. Thus, exploring interrelations between agriculture and water under climate change is essential to frame informed policies that ensure sustainable water management while enhancing food production. Nevertheless, studies that address future agriculture development focus on climate-induced changes in crop productivity and often disregard the water dimension. In this research, we have conducted a sensitivity analysis of agricultural development to drivers of water use in Andalusia in 2050 based on outcomes from the CAPRI-Water model. The results from the analysis show that water cost is the most determinant factor in shaping agricultural land, offsetting the impact of the driver of water availability. In contrast, irrigation water use is driven not only by water cost but also by irrigation efficiency. The magnitude of the sensitivity to these drivers differs significantly across crops. Policies aimed at improving resource use efficiency can contribute to strengthening the resilience and adaptation capacity of future agricultural systems to climate change. To achieve this goal, the policies must consider crop sensitivity to irrigation costs and the potential rebound effect.

Irrigation efficiency is facilitated by matching irrigation rates to crop water demand based on estimates of actual evapotranspiration (ET). In production settings, monitoring of water demand is typically accomplished by measuring reference ET rather than actual ET, which is then adjusted approximately using simplified crop coefficients based on calendars of crop maturation. Methods to determine actual ET are usually limited to use in research experiments for reasons of cost, labor and requisite user skill. To pair monitoring and research methods, we co-located eddy covariance sensors with on-farm weather stations over two different irrigated crops (vegetable beans and hazelnuts). Neural networks were used to train a neural network and utilize on-farm weather sensors to report actual ET as measured by the eddy covariance method. This approach was able to robustly estimate ET from as few as four sensor parameters (temperature, solar radiation, humidity and wind speed) with training time as brief as one week. An important limitation found with this machine learning method is that the trained network is only valid under environmental and crop conditions similar to the training period. The small number of required sensors and short training times demonstrate that this approach can estimate site-specific and crop specific ET. With additional field validation, this approach may offer a new method to monitor actual crop water demand for irrigation management.

The demand for fresh water is on the increase, and the irrigation industry in Australia is looking to a future with less water. Irrigation consumes the bulk of the water extracted from various sources, and hence the efficiency of its use is of outmost importance. This paper reviewed the advancements made towards improving irrigation water use efficiency (WUE), with a focus on irrigation in Australia but with some examples from other countries. The challenges encountered, as well as the opportunities available, are also discussed. The review showed that improvements in irrigation infrastructure through modernisation and automation have led to water savings. The concept of real-time control and optimisation in irrigation is in its developmental stages but has already demonstrated potential for water savings. The future is likely to see increased use of remote sensing techniques as well as wireless communication systems and more versatile sensors to improve WUE. In many cases, water saved as a result of using efficient technologies ends up being reused to expand the area of land under irrigation, sometimes resulting in a net increase in the total water consumption at the basin scale. Hence, to achieve net water savings, water-efficient technologies and practices need to be used in combination with other measures such as incentives for conservation and appropriate regulations that limit water allocation and use. Factors that affect the trends in the irrigation WUE include engineering and technological innovations, advancements in plant and pasture science, environmental factors, and socio-economic considerations. Challenges that might be encountered include lack of public support, especially when the methods used are not cost-effective, and reluctance of irrigations to adopt new technologies.

Climate change and water scarcity are the most important challenges of the agricultural sector, and pressurized irrigation systems (PISs) are one of the most significant ways to improve agricultural water productivity. The main purpose of this research was to identify the factors affecting the use of PISs by farmers. The statistical research population was a total of 2396 Iranian model farmers. The Cochran formula was used to determine the number of statistical samples. Accordingly, this comprised 331 people. The methodology of the study was mixed method research. The structural equation modeling technique, Mann⁻Whitney U, and Kruskal⁻Wallis tests were used to test the hypotheses. The results showed that the personal characteristics, tendency, attitude, self-efficacy, subjective norms, governmental support, environmental tensions, and technological features were the most important factors which influenced the farmers. It was found that all of these variables had a positive and significant relationship with the using of PISs by farmers, and they were able to predict 52% of the behavioral changes (R2) of the farmers. Among these variables, the attitude, with a path coefficient (β) of 0.48, had the highest impact on the using of PISs by the farmers.

Crop irrigation uses more than 70% of the world’s water, and thus, improving irrigation efficiency is decisive to sustain the food demand from a fast-growing world population. This objective may be accomplished by cultivating more water-efficient crop species and/or through the application of efficient irrigation systems, which includes the implementation of a suitable method for precise scheduling. At the farm level, irrigation is generally scheduled based on the grower’s experience or on the determination of soil water balance (weather-based method). An alternative approach entails the measurement of soil water status. Expensive and sophisticated root zone sensors (RZS), such as neutron probes, are available for the use of soil and plant scientists, while cheap and practical devices are needed for irrigation management in commercial crops. The paper illustrates the main features of RZS’ (for both soil moisture and salinity) marketed for the irrigation industry and discusses how such sensors may be integrated in a wireless network for computer-controlled irrigation and used for innovative irrigation strategies, such as deficit or dual-water irrigation. The paper also consider the main results of recent or current research works conducted by the authors in Tuscany (Italy) on the irrigation management of container-grown ornamental plants, which is an important agricultural sector in Italy.

Improved irrigation use efficiency is an important tool for intensifying and diversifying agriculture in Nepal, resulting in higher economic yield from irrigated farmlands with a minimum input of water. Research was conducted to evaluate the effect of irrigation method (furrow vs. drip) on the productivity of nutritious fodder species during off-monsoon dry periods in different elevation zones of central Nepal. A split-block factorial design was used. The factors considered were treatment location, fodder crop, and irrigation method. Commonly used local agronomical practices were followed in all respects except irrigation method. Results revealed that location effect was significant (p < 0.01) with highest fodder productivity seen for the middle elevation site, Syangja. Species effects were also significant, with teosinte (Euchlaena mexicana) having higher yield than cowpea (Vigna unguiculata). Irrigation method impacted green biomass yield (higher with furrow irrigation) but both methods yielded similar dry biomass, while water use was 73% less under drip irrigation. Our findings indicated that the controlled application of water through drip irrigation is able to produce acceptable yields of nutritionally dense fodder species during dry seasons, leading to more effective utilization and resource conservation of available land, fertilizer and water. Higher productivity of these nutritional fodders resulted in higher milk productivity for livestock smallholders. The ability to grow fodder crops year-round in lowland and hill regions of Nepal with limited water storages using low-cost, water-efficient drip irrigation may greatly increase livestock productivity and, hence, the economic security of smallholder farmers.