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Appropriate irrigation schedules could minimize the existing imbalance between agricultural water supply and crop water requirements (ETc), which is severely impacted by climate change. In this study, different hydrological years (a wet year, normal year, dry year, and an extremely dry year) in Heilongjiang Province were calculated by hydrological frequency methods. Then, the single crop coefficient method was used to calculate the maize ETc, based on the daily meteorological data of 26 meteorological stations in Heilongjiang Province from 1960 to 2020. Afterward, the CROPWAT model was used to calculate the effective precipitation (Pe) and irrigation water requirement (Ir), and formulate the irrigation schedules of maize in Heilongjiang Province under different hydrological years. The results showed that ETc and Ir decreased first and then increased from west to east. The Pe and crop water surplus deficit index increased first and then decreased from west to east in Heilongjiang Province. Meanwhile, the average values of the Ir in were 171.14 mm, 232.79 mm, 279.08 mm, and 334.47 mm in the wet year, normal year, dry year, and extremely dry year, respectively. Heilongjiang Province was divided into four irrigation zones according to the Ir of different hydrological years. Last, the irrigation quotas for the wet year, normal year, dry year, and extremely dry year were 0~180 mm, 20~240 mm, 60~300 mm, and 80~430 mm, respectively. This study provides reliable support for maize irrigation practices in Heilongjiang Province, China.

Agricultural water use has long accounted for more than 70% of water consumption in Northeast China. Estimating farmland irrigation water requirements and water balance is essential to ensure safe agricultural water and promote rational development and utilization of regional water resources. In this study, based on the modified Penman–Monteith equation recommended by the Food and Agriculture Organization (FAO) and Geographic Information System (GIS) technology, the net crop irrigation water requirements for four main crops in Northeast China were calculated, and the spatiotemporal distribution characteristics were also analyzed. Additionally, regional farmland irrigation water requirements were estimated, water balance in a typical year was determined, and the dominant factors affecting farmland irrigation water requirements in different regions were analyzed. From 1986 to 2020, the net irrigation water requirements for four main crops all showed the temporal trend of no significant increase and the spatial distribution characteristic of being high in the west and low in the east. The farmland irrigation water requirement decreased, and the monthly average farmland irrigation water requirement peaked in July during 2010–2019. Compared with 2010, in 2019, the irrigation water requirement per cultivated land grid cell in 20 cities increased and that in 16 cities decreased. Most cities were facing varying degrees of water shortage. Precipitation had the greatest direct effect on the farmland irrigation water requirement in different regions. These results quantify the farmland irrigation water requirement and water balance in Northeast China, and provide a reference for water resources and related environmental governance.

The climate of Iraq is of the subtropical semi-dry type; however, the country was rich in water resources until a few decades ago. Climate change and the construction of many dams on the Tigris and Euphrates rivers in the neighboring countries have caused water shortages and poor water quality. Now, there is a need to decrease consumption, improve management of water resources, and determine the water requirements of the major crops because agriculture is the first consumer of water in Iraq. The Food and Agriculture Organization (FAO) CROPWAT 8.0 simulation software and the CLIMWAT 2.0 tool attached to it have been used in this research for Dhi-Qar Province in southern Iraq to find the crop water requirements (CWRs) and irrigation schedules for some major crops. The CROPWAT Penman–Monteith method was used to calculate the reference crop evapotranspiration (ET0) and the United States Department of Agriculture (USDA) soil conservation (S.C.) method was used to estimate the effective rainfall. The study results showed that ET0 varied from 2.18 to 10.5 mm/day and the effective rainfall varied from 0.0 to 23.1 mm. The irrigation requirements were 1142, 203.2, 844.8, and 1180 mm/dec for wheat, barley, white corn, and tomatoes, respectively. There is a higher water demand for crops during the dry seasons (summer and autumn) and a lower demand during the wet seasons (winter and spring). The total gross irrigation and the total net irrigation were 343.8 mm and 240.7 mm for wheat, 175.2 mm and 122.6 mm for barley, 343.8 mm and 240.7 mm for white corn, and 203.3 mm and 142.3 mm for tomatoes. This study proved that the CROPWAT model is useful for calculating the crop irrigation needs for the proper management of water resources.

Elucidating the variation of allocation pattern of ecosystem net primary productivity (NPP) and its underlying mechanisms is critically important for understanding the changes of aboveground and belowground ecosystem functions. Under optimal partitioning theory, plants should allocate more NPP to the organ that acquires the most limiting resource, and this expectation has been widely used to explain and predict NPP allocation under changing precipitation. However, confirmatory evidence for this theory has mostly come from observed spatial variation in the relationship between precipitation and NPP allocation across ecosystems, rather than directly from the influences of changing precipitation on NPP allocation within systems. We performed a 6-yr five-level precipitation manipulation experiment in a semiarid steppe to test whether changes in NPP allocation can be explained by the optimal partitioning theory, and how water requirement of plant community is maintained if NPP allocation is unaltered. The 30 precipitation levels (5 levels × 6 yr) were divided into dry, nominal, and wet precipitation ranges, relative to historical precipitation variation over the past six decades. We found that NPP in both aboveground (ANPP) and belowground (BNPP) increased nonlinearly as precipitation increased, while the allocation of NPP to BNPP (f BNPP) showed a concave quadratic relationship with precipitation. The declined f BNPP as precipitation increased in the dry range supported the optimal partitioning theory. However, in the nominal range, NPP allocation was not influenced by the changed precipitation; instead, BNPP was distributed more in the surface soil horizon (0–10 cm) as precipitation increased, and conversely more in the deeper soil layers (10–30 cm) as precipitation decreased. This response in root foraging appears to be a strategy to satisfy plant water requirements and partially explains the stable NPP allocation patterns. Overall, our results suggest that plants can adjust their vertical BNPP distribution in response to drought stress, and that only under extreme drought does the optimal partitioning theory strictly apply, highlighting the context dependency of the adaption and growth of plants under changing precipitation.

The nations that comprise the Gulf Cooperation Council (GCC) are located in one of the most water-stressed regions in the world. This region has faced serious socioeconomic and environmental development issues as a result of its increasing water demand over time. The extreme aridity, high rates of evaporation, and scarcity of nonrenewable groundwater resources in the GCC countries pose a significant threat to food security. This study aims to explore the impact of climate change on the potential availability of irrigation water in the State of Kuwait, which serves as an example of all GCC nations. A modeling scheme using CropWat8 was developed to study the impact of four climate change scenarios (encompassing the past, present, and future) on the net and gross irrigation water requirements (NIWR and GIWR) for selected agricultural crops, while also determining optimum irrigation schedules. Scenario 1 represented past climate conditions (1996–2006), while Scenario 2 represented the current situation (2007–2021). Projected scenarios (3 and 4) were analyzed using Representative Concentration Pathways (RCP) 4.5 and RCP 8.5, which were adopted by the IPCC to project the concentrations of greenhouse gases (GHG) emissions for 2060. The simulation results showed that compared with the current GHG levels, the increase in GHG emissions also increased the demand for NIWR by a minimum of 8.2% and a maximum of 15% for the same agricultural areas and cropping patterns. The measured GIWR in the field was 1915 m3, while the simulated NIWR was 1724 m3. With a drip irrigation efficiency of 90%, the model adequately demonstrated the validity of the CropWat8 package for simulating the climate impact on crop water requirements with a precision of approximately 92.2%. These findings suggest that the GCC countries should develop strategies to minimize GHG emissions and adopt innovative solutions for better management of water resources.

Climate and land use change modify surface water availability in African savannas. Surface water is a key resource for both wildlife and livestock and its spatial and temporal distribution is important for understanding the composition of large herbivore assemblages in savannas. Yet, the extent to which ungulate species differ in their water requirements remains poorly quantified. Here, we infer the water requirements of 48 African ungulates by combining six different functional traits related to physiological adaptations to reduce water loss, namely minimum dung moisture, relative dung pellet size, relative surface area of the distal colon, urine osmolality, relative medullary thickness, and evaporation rate. In addition, we investigated how these differences in water requirements relate to differences in dietary water intake. We observed strong correlations between traits related to water loss through dung, urine and evaporation, suggesting that ungulates minimize water loss through multiple pathways simultaneously, which suggests that each trait can thus be used independently to predict water requirements. Furthermore, we found that browsers and grazers had similar water requirements, but browsers are expected to be less dependent on surface water because they acquire more water through their diet. We conclude that these key functional traits are a useful way to determine differences in water requirements and an important tool for predicting changes in herbivore community assembly resulting from changes in surface water availability.

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e., professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies (Geographic Information Systems based on web technologies). This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools, which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools.

Understanding future changes in water supply and requirement under climate change is of great significance for long-term water resource management and agricultural planning. In this study, daily minimum temperature (Tmin), maximum temperature (Tmax), solar radiation (Rad), and precipitation for 26 meteorological stations under RCP4.5 and RCP8.5 of MIRCO5 for the future period 2021–2080 were downscaled by the LARS-WG model, daily average relative humidity (RH) was estimated using the method recommended by FAO-56, and reference crop evapotranspiration (ET0), crop water requirement (ETc), irrigation water requirement (Ir), effective precipitation (Pe), and coupling degree of ETc and Pe (CD) for soybean during the growth period were calculated by the CROPWAT model in Heilongjiang Province, China. The spatial and temporal distribution of these variables and meteorological factors were analyzed, and the response of soybean water supply and requirement to climate change was explored. The result showed that the average Tmin, Tmax, and Rad under RCP4.5 and RCP8.5 increased by 0.2656 and 0.5368 °C, 0.3509 and 0.5897 °C, and 0.0830 and 0.0465 MJ/m², respectively, while the average RH decreased by 0.0920% and 0.0870% per decade from 2021 to 2080. The annual average ET0, ETc, Pe, and Ir under RCP4.5 for 2021–2080 were 542.89, 414.35, 354.10, and 102.44 mm, respectively, and they increased by 1.92%, 1.64%, 2.33%, and −2.12% under the RCP8.5, respectively. The ranges of CD under RCP4.5 and RCP8.5 were 0.66–0.95 and 0.66–0.96, respectively, with an average value of 0.84 for 2021–2080. Spatially, the CD showed a general trend of increasing first and then decreasing from west to east. In addition, ET0, ETc, and Pe increased by 9.55, 7.16, and 8.77 mm per decade, respectively, under RCP8.5, while Ir decreased by 0.65 mm per decade. Under RCP4.5 and RCP8.5, ETc, Pe, and Ir showed an overall increasing trend from 2021 to 2080. This study provides a basis for water resources management policy in Heilongjiang Province, China.

Groundwater is a critical resource in remote and isolated islands where rainfall hardly provides a continuous and even water supply. In this paper, in a very rare and uncommonly found artificial aquifer on Miyako Island, far away from the main continent of Japan, with limited experimental results of evaluations of crop water requirement, MODIS ET together with crop ETc estimated from Kc coefficient from the nearest island were compared to determine the reliability of the MODIS ET and FAO-56-based ETc value. The testified Kc approach for sugarcane ET was used to assess the risk of irrigation water shortages using historical metrological data and to predict the future risk of irrigation agriculture under different scenarios of GCM models. It was shown that FAO-56-based ETc and MOD16A2 were both applicable for crop evapotranspiration on the island. Then, the response of groundwater storage to gross irrigation water requirement was analyzed to clarify the effect of irrigation on groundwater storage and the risk of groundwater depletion under current and future climatic conditions. Results showed that the construction of the dam efficiently secured the irrigation of sugarcane. Using historical climatic data (1951–2021), the influence of estimated irrigation water requirements on groundwater showed that in 296 out of 852 months, irrigation was heavily required. Over a 71 year period, there was absolutely no water for irrigation four times, or nearly once every 18 years. Under the future projected climate from four bias-corrected GCM models with two emission scenarios (2022–2100), the risk of groundwater depletion both in terms of frequency and duration will increase. Therefore, there is a need for either improvement of irrigation water management or additional construction of artificial aquifers on the island. The study proved the value of ET derived from remote sensing in areas lacking the support of experimental results. The methodology developed in the study can be potentially used to evaluate long-term irrigation demand and groundwater management over dry periods for engineering design or dam construction globally.

According to the importance of water conservation in water scarcity regions, estimating the exact amount of required water for crops under different stress conditions in irrigation networks is vital. One of the challenges in water management is estimating these stresses with crop models. AquaCrop is a robust model that can simulate the actual evapotranspiration and the water needs under different biophysical and management conditions. In this study, the actual evapotranspiration (Eta) and the irrigation requirement of wheat, barley, and maize are estimated by the AquaCrop model in the Qazvin province, and then compared with the results of the CropWat model. According to the results, the irrigation requirement for all three crops was significantly less than the CropWat estimation that were 184, 55.9, and 38.6 mm less water volume is needed for wheat, barley, and maize, respectively, showing using this model, the water efficiency will increase and the less amount of water can bring us the same amount of production. After that, for better comparison and assessment of the AquaCrop model, results were compared to the amount estimated by the Moghan plain and represented a higher amount of the actual evapotranspiration and the irrigation requirement because of different climate situations. These differences are mostly due to the AquaCrop model that is able to adjust itself under different stress conditions.