Net Irrigation Water Requirements Research Articles

Agricultural Water Management for Rice Production: A Comprehensive Analysis

The identified problem revolves around establishing the water requirements for rice seeding, growth, and maturity in hot climatic conditions. This study reviews the net water requirement for rice growth or production under various climatic conditions in the Cross River Basin. It was observed that the water requirement from seeding to harvest varies from location to location, maintaining a FAO range, as postulated by Brouwer et al., 1986, ultimately falling between 450mm to 700mm for hot weather.The methodology used for investigating the Net Irrigation Water Requirements for rice growth to maturity involves the application of New_Clim Location and CropWater software. These tools were utilized to compute Reference Evapotranspiration (ETo) and Crop Water Requirements (CWR) for the net irrigation water requirements of rice, respectively. The data were obtained from meteorological stations within the Cross River Basin. In rainfed conditions, no water stress is practically observed throughout the entire crop cycle, affirming that no irrigation system is needed in such a specific climate. This study uses data generated through New_LocClim as input into CropWat, which, among other factors, determines the net water requirement for rice growth and production. Consequently, the results obtained from the use of the CropWat model in determining rice water requirements for Obudu, Nkari, Ikom, and Ijegu-Yala were 633.7 mm, 397.9 mm, 303.0 mm, and 548.4 mm, respectively. The water requirement of only two locations, Obudu and Ijegu-Yala, fell within the FAO-suggested range of 450 mm to 700 mm (Brouwer et al., 1986) for hot climates, while Nkari and Ikom LGAs did not comply with Brower et al., 1986 postulation due to their location in a relatively less hot climate.

Irrigation Water Management in a Water-Scarce Environment in the Context of Climate Change

Climate change has a considerable impact on irrigated agriculture, which is vital for food and fiber production. In this study, in the context of climate change, simulation model CROPWAT 8 was employed to compute the reference evapotranspiration, and net irrigation water requirement for wheat, barley, maize, sugar beet, potato, tomato, and date palm. In addition, the WaterGEMS model was utilized to design a new sprinkler irrigation system to run long-term simulations of hydraulic behavior within pressurized pipe networks to irrigate 43 acres for two arid sites (Siwa Oasis and West Elminya fields) inside the 1.5-million-acre groundwater irrigation project in the Egyptian western desert. Five scenarios for climate change were employed in the current (1991–2023), representative concentration path (RCP) 8.5 greenhouse gas emission scenarios for the 2040s, 2060s, 2080s, and 2100s. Mean ETo values for the current scenario show 4.56 and 5.7 mm for the Siwa Oasis and West Elminya fields, respectively. The climate changes cause an increase of the reference evapotranspiration by 4.6, 5.9, 9.4, and 12.7% for RCP: 8.5 greenhouse gas emissions for the 2040s, 2060s, 2080s, and 2100s scenarios, respectively, for the Siwa Oasis field. On the other hand, an increased ratio for the reference evapotranspiration by 4.2, 5.4, 8.6, and 11.6% was observed for the scenarios in the West Elminya field, respectively. The designed sprinkler system indicated a capacity of 111.4 m3 h−1 and 167 m3 h−1 for Siwa and West Elminya fields, respectively. The study suggests using crop patterns for wheat, barley, potato, and sugar beet to save irrigation water.Graphical abstract

Simulation of Irrigation Strategy Based on Stochastic Rainfall and Evapotranspiration

The North China Plain plays a pivotal role in China’s crop production, contributing to 30% of the maize yield. Nevertheless, summer maize in this region faces challenges due to climatic constraints characterized by concurrent high temperatures and rainfall during the growing season, resulting in a relatively high evapotranspiration rate. In this study, we explored eight soil moisture-based threshold irrigation strategies, consisting of two upper limits and four lower limits, along with a rainfed mode (E). The upper and lower irrigation limits are expressed as a percentage of the field’s water-holding capacity (sfc). For the four full irrigation modes (A1, A2, A3, A4), the lower limits were set at 0.6 sfc, 0.6 sfc, 0.5 sfc, and 0.5 sfc, respectively. The upper limits were defined at two levels: 0.8 sfc for A1 and A2 and sfc for A3 and A4. Similarly, for the four deficit irrigation modes (B1, B2, B3, B4), the lower limits were established at 0.4 sfc, 0.4 sfc, 0.3 sfc, and 0.3 sfc, respectively, with the upper limits set at two levels: 0.8 sfc for B1 and B2 and the full sfc for B3 and B4. To investigate the impact of rainfall and potential evapotranspiration on these irrigation modes under long-term fluctuations, we employed a stochastic framework that probabilistically linked rainfall events and irrigation applications. The Monte Carlo method was employed to simulate a long-term series (4000a) of rainfall parameters and evapotranspiration using 62 years of meteorological data from the Xinxiang region, situated in the southern part of the North China Plain. Results showed that the relative yield and net irrigation water requirement of summer maize decreased with decreasing irrigation lower limits. Additionally, the interannual variation of rainfall parameters and evapotranspiration during the growing season were remarkable, which led to the lowest relative yield of the rainfed mode (E) aligned with a larger interannual difference. According to the simulation results, mode A4 (irrigation lower limit equals 0.5 sfc, irrigation upper limit equals 0.8 sfc) could be adopted for adequate water resources. Conversely, mode B2 is more suitable for a lack of water resources.

CROP WATER REQUIREMENT IN A SUB-WATERSHED OF MAHABUBNAGAR DISTRICT OF TELANGANA FOR KHARIF RICE CULTIVATION USING GEOSPATIAL TECHNIQUES

In a sub-watershed of the Mahabubnagar district of Telangana state, India, the paper focuses on estimating the irrigation water requirements of paddy crops for the kharif season from 2019 to 2021. The Random Forest Classifier in Google Earth Engine has used Sentinel-2 to determine the area that is being used for paddy cultivation. Using the Hargreaves model, potential evapotranspiration (ETο) has been calculated. The crop coefficient (Kc) for paddy and potential evapotranspiration (ETο) were used to calculate the crop's water requirements (Etc). Utilizing gridded rainfall data from the CHRS (Center for Hydrometeorology and Remote Sensing) - PERSIANN-Cloud Classification System (PERSIANN-CCS 4km x 4km), effective rainfall was calculated. To calculate the amount of irrigation water needed, effective rainfall and crop water needs were taken into consideration. Net irrigation water need was calculated by assuming 30% losses. The amount of water needed for paddy is calculated by multiplying the paddy cropped area by the net irrigation water requirement.

Impact of climatic changes on future irrigation water requirement in the Middle East and North Africa's region: a case study of upper Egypt

Freshwater shortages in the Middle East and North Africa's region (MENA) cause serious issues, while climate change causes even more issues. The current study examines how climate change may impact future irrigation requirements in Egypt's Upper Region using the medium greenhouse emission RCP 4.5 and high emission RCP 8.5 scenarios. Based on the Intergovernmental Panel on Climate Change (IPCC) and the Fifth Assessment Report, the climatic projections for RCPs 4.5 and 8.5 for the years 2023–2080 and 2081–2100 were used to determine the patterns of temperature and rainfall in the upper Egypt territory. The CROPWAT model was employed to estimate reference evapotranspiration (ETo) and net irrigation water requirement (NIWR) for the upper Egypt territory key crops sugar cane, potatoes, berseem clover (alfalfa), dry bean, wheat, cotton, maize, and tomato based on the predicted meteorological conditions. Five different scenarios for the key crops' future irrigation needs were calculated. The results reveal that under RCP 4.5 greenhouse emission for the periods 2023–2080 and 2081–2100, respectively, the overall NIWR for all examined crops increases by 5.1 and 5.9% in comparison to the current (2022) total NIWR for all crops. The total NIWR for all crops analyzed increases by 7.7 and 9.7% under the RCP 8.5 greenhouse emission scenario for the periods 2023–2080 and 2081–2100, respectively, in contrast to the current total NIWR for all crops. It is important to consider changes in water resource management in the MENA region, such as applying modern irrigation systems, using crop pattern rotation strategies with minimal water demands, and changing crop calendars or the times and locations of cropping activities.

Creation of Geospatial Database and Estimation of Irrigation Water Requirement of a Canal Command in Gayathri Irrigation Project, Kerala

The water requirement of crops in the canal command of distributaries of Gayathri Irrigation Project in Palakkad district, Kerala was estimated using GIS and CROPWAT 8 model. The geospatial data base for canal network, land use, soil and climate were prepared using Geographic Information System (GIS) tools. This data base was used as input to CROPWAT model to estimate irrigation water requirement of different distributaries of the canal command. The gross irrigation requirement was estimated for the historical climate data (2004-2018) as well as the predicted climate data for the years 2026 and 2031. The net irrigation water requirement of different crops in the distributary command was found to vary spatially depending on soil, crop and climate. The net irrigation water requirement of paddy (mundakan) in distributaries located at head to tail reaches varied from 1004.5 to 1573.6 mm. The high value of net irrigation requirement in tail reach was due to the influence of soil series with high infiltration rate compared to head reach soil. The net irrigation requirement also varied for the same crop in same soil series in different distributaries depending upon the climatic conditions. The net irrigation water requirement of paddy (mundakan) in distributaries located at head to middle reaches for the same soil series varied from 1056.5 to 1004.5 mm due to the influence of variations in rainfall. The gross estimated irrigation water requirement showed that distributaries at the middle and tail reaches required more water than the distributaries at the head end. The maximum gross irrigation water requirement of 25369.7 m3/ha was observed for Peringhotukavu distributary in tail reach and lowest of 4390.9 m3/ha for Parakkalchalla distributary in head reach. The estimation of irrigation requirement for projected climate data also showed the same trend as that of historical data.

Future Water Requirements and Crop Productivity at Al-Najaf Governorate Under Different Climate Change Scenarios (2020–2080)

This study aims to predict the effect of climate change on net irrigation water requirements (NIWR) and agricultural productivity from five common crops (wheat, barley, summer maize, and sorghum) in the Al-Najaf Governorate in Iraq. GFDL-ESM2M mode was used to predict the lower and upper temp and precipitation for two time periods (2020-2080) with 30 years for two periods (P1 and P2) under representative concentrations paths (RCP 2.5, RCP6, and RCP8.5). The CROPWAT model is used to determine NIWR, and the extreme learning model was used to estimate agricultural yields using previous crop yield production and weather data, supported vectors machine (SVM) is executed as a Machines Learns algorithm. Results showed NIWR increment to consider cropping owing to climate change. Barley is the crop most affected by climate change under the (RCP2.5, RCP6, and RCP8.5) scenarios, with increasing crop water requirements (NIWR) of (22%, 23%, and 24% ) for P1 and (23%, 24%, and 29%) for P2, respectively. Summer maize is the crop least affected by climate change under all climate change scenarios, with increasing crop water requirements of (1%, 2%, and 4%) for P1 and (1%, 2%, and 5% for P2. Climate change negatively affects the crop yield of all crops under the different climate change scenarios. The findings of this study could be used as a guide to developing adaptation strategies for dealing with potential changes in water availability and agricultural water productivity due to climate change.

Climate Change Impacts on Water Resources in Arid and Semi-Arid Regions: A Case Study in Saudi Arabia

In the coming years, climate change is predicted to impact irrigation water demand considerably, particularly in semi-arid regions. The aim of this research is to investigate the expected adverse impacts of climate change on water irrigation management in Saudi Arabia. We focus on the influence of climate change on irrigation water requirements in the Al Quassim (97,408 ha) region. Different climate models were used for the intermediate emission SSP2-4.5 and the high emission SSP5-8.5 Coupled Model Intercomparison Project Phase 6 (CMIP6) scenarios. The FAO-CROPWAT 8.0 model was used to calculate reference evapotranspiration (ETo) using weather data from 13 stations from 1991 to 2020 and for both the SSP2-4.5 and SSP5-8.5 scenarios for the 2040s, 2060s, 2080s, and 2100s. The findings indicated that, for the 2100s, the SSP2-4.5 and SSP5-8.5 scenarios forecast annual average ETo increases of 0.35 mm/d (6%) and 0.7 mm/d (12.0%), respectively. Net irrigation water requirement (NIWR) and growth of irrigation water requirement (GIWR) for the main crops in the Al Quassim region were assessed for the current, SSP2-4.5, and SSP5-8.5 scenarios. For SSP5-8.5, the GIWR for the 2040s, 2060s, 2080s, and 2100s are expected to increase by 2.7, 6.5, 8.5, and 12.4%, respectively, compared to the current scenario (1584.7 million m3). As a result, there will be higher deficits in 2100 under SSP5-8.5 for major crops, with deficits of 15.1%, 10.7%, 8.3%, 13.9%, and 10.7% in the crop areas of wheat, clover, maize, other vegetables, and dates, respectively. Optimal irrigation planning, crop pattern selection, and modern irrigation technologies, combined with the proposed NIWR values, can support water resources management. The findings can assist managers and policymakers in better identifying adaptation strategies for areas with similar climates.

An Artificial Intelligence Approach to Manage Crop Water Requirements in South Africa

Estimation of crop water requirements is of paramount importance towards the management of agricultural water resources, which is a major mitigating strategy against the effects of climate change on food security. South Africa water shortage poses a threat on agricultural efficiency. Since irrigation uses about 60% of the fresh water available, it therefore becomes important to optimise the use of irrigation water in order to maximize crop yield at the farm level in order to avoid wastage. In this study, combined application of an artificial neural network (ANN) and a crop – growth simulation model for the estimation of crop irrigation water requirements and the irrigation scheduling of potatoes at Winterton irrigation scheme, South Africa was investigated. The crop-water demand from planting to harvest date, when to irrigate, the optimum stage in the drying cycle when to apply water and the amount of irrigation water to be applied per time, were estimated in this study. Five feed –forward backward propagation artificial neural network predictive models were developed with varied number of neurons and hidden layers and evaluated. The optimal ANN model, which has 5 inputs, 5 neurons, 1 hidden layer and 1 output was used to predict monthly reference evapotranspiration (ETo) in the Winterton area. The optimal ANN model produced a root-mean-square error (RMSE) of 0.67, Pearson correlation coefficient (r) of 0.97 and coefficient of determination (R2) of 0.94. The validation of the model between the measured and predicted ETo shows a r value of 0.9048. The predicted ETo was one of the input variables into a crop growth simulation model, called CROPWAT. The results indicated that the total crop water requirement was 1259.2 mm/decade and net irrigation water requirement was 1276.9 mm/decade, spread over a 5-day irrigation time during the entire 140 days of cropping season for potatoes. A combination of the artificial neural networks and the crop growth simulation models have proved to be a robust technique for estimating crop irrigation water requirements in the face of limited or no daily meteorological datasets.

Effects on Net Irrigation Water Requirement of Joint Distribution of Precipitation and Reference Evapotranspiration

To establish the uncertain influence that the joint distribution of precipitation and reference evapotranspiration has on net irrigation water requirement, a Copula function–Monte Carlo method (CFMC) was proposed to calculate the probability of irrigation water requirement. Taking the Jingdian Irrigation District in Northwest China as an example, the distribution laws of precipitation and reference evapotranspiration were studied. Furthermore, five typical years under different crop planting structure conditions were selected, and the variation characteristics of net irrigation water requirement in each typical year under the conditions of climate uncertainty were analyzed. The results revealed the optimal distribution functions of precipitation and reference evapotranspiration to be gamma distribution and lognormal distribution. The probability density map of the joint distribution of precipitation and reference evapotranspiration has a “saddle” shape; that is, irrigation water requirement and reference evapotranspiration are usually inversely related. As the probability of the irrigation water requirement increases, the net irrigation water requirement in the irrigation area also increases. The CFMC method can determine the design value of the net irrigation water requirement under a specific probability for typical years under different crop planting structure conditions, which can provide a reference for agricultural water resource allocation in irrigation areas.

Estimation of regional farmland irrigation water requirements and water balance in Northeast 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.

Minimization of deep percolation by a parabolic simulation model in a blocked end furrow irrigation method

AbstractSurface irrigation methods enable a lower cost of investment and energy requirements than pressurized systems if they are designed and managed properly. The aim of this investigation was to devise a new simulation model that would enable the determination of the optimum water application time and furrow length in a blocked end furrow system. The infiltration properties of the soil, net irrigation water requirement of the crop and inflow to the furrow constitute the main variables of this process. Deep percolation and the cross‐sectional area of the wetting pattern where the net irrigation water requirement of the crop is met along the furrow are the main components that were simulated interactively in the model. They were described as a function of time. The proposed model devised in this investigation was run for two different sample applications. While values of 93 and 94% water application efficiencies were obtained by running the USDA SCS method for the first and second sample applications, respectively, values of 92 and 94% were obtained, respectively, from the proposed model. These results indicate that the proposed model can be used in the design of a blocked end furrow system.

Sensitivity of Irrigation Water Requirement to Climate Change in Arid and Semi-Arid Regions towards Sustainable Management of Water Resources

This study aimed to assess the spatiotemporal sensitivity of the net irrigation water requirement (NIWR) to changes in climate, for sixteen crops widely cultivated in four irrigation projects located in arid and semi-arid regions of Iraq. Using LARS-WG and five GCMs, the minimum and maximum temperature and precipitation were projected for three periods from 2021–2080 with 20-year steps (P1, P2, and P3) under representative concentration pathways (RCPs) 2.6, 4.5, and 8.5. Weather data available for a reference period from 1990–2019 in four representatives’ meteorological stations were used. The climate variables and other required data were inserted into the CROPWAT 8 NIWR tool. Findings revealed that the increase in the NIWR for the considered crops due to climate change falls in the range 0.1–42.4%, 1.8–44.5%, 1.2–25.1%, and 0.7–14.7% for the North Jazeera Irrigation Project (NJIP), Kirkuk Irrigation Project (KRIP), Upper Khalis Irrigation Project (UKIP), and Dalmaj Irri-gation Project (DLIP), respectively. Barley is more susceptible to changes in climate, whereas maize, potato, soybean, and millet are found to withstand changes in climate better than others. The novel outcomes of this study support optimal spatiotemporal allocation of irrigation water requirement and the sustainable management of water resources in a changing climate in arid and semi-arid regions.

Climate-Induced Perspective Variations in Irrigation Schedules and Design Water Requirements for the Rice–Wheat System

Conceptualizing the implications of climate change for crop evapotranspiration (ETc) and subsequent net irrigation water requirement (NIWR) is critical to sustaining Pakistan’s agriculture and food security. In this article, future ETc, NIWR, and design water requirements (DWR) were projected for the rice–wheat system of Punjab, Pakistan. Consistently increasing temperatures signify an impending hotter transition in the future thermal regime, accompanied by a substantial increase in monsoon rainfall. Future climate warming accelerated ETc and NIWR, which were compensated by 2–5 and 1–2 additional irrigations during the rice and wheat seasons, respectively. Future rice and wheat required 13–18 and 2–5 irrigations per season, respectively. Effective rainfall increments did not compensate for the warming-driven higher ETc and NIWR because of uneven and erratic rainfall distribution. Rainfall occurrence and the duration of peak irrigation demand were mismatched, resulting in surplus rainwater availability during the future rice season. The results suggest that DWR for 5- and 10-year return period droughts during the baseline period (965 and 1000 mm, respectively) should be revised to accommodate the additional 100–200 mm of irrigation water per season; otherwise, the study area will face an acute water shortage in the future.

Systems Analysis of Coupled Natural and Human Processes in the Mekong River Basin

The Mekong River Basin is one of the world’s major transboundary basins. The hydrology, agriculture, ecology, and other watershed functions are constantly changing as a result of a variety of human activities carried out inside and by neighboring countries including China, Myanmar, Thailand, Laos, Cambodia, and Vietnam in order to meet increased food and water demands for an increasing population. The Mekong River, which provides irrigation and fishing for a population of over 60 million people, also has an estimated 88,000 MW of untapped hydropower potential. The construction of dams for energy supply has a wide-ranging impact on downstream reservoir regions, resulting in unprecedented changes in hydrologic functions, the environment, and people’s livelihoods. We present a holistic view of how external stressors such as climate change and variability, land cover, and land-use change affect supply and demand. We present an integrated modeling framework for analyzing the supply–demand scenarios and tradeoffs between different sectors. Specifically, we evaluated the impacts of future climate on irrigation, hydropower, and other needs in the basin through a feedback loop. We focused on hydrologic extremes to evaluate their impacts on the reservoir operations during flood and low flow events. The inflow is projected to change by +13% to −50% in the future, while a 0.25% (15.24 billion m3) reduction is projected for the net irrigation water requirement (NIWR). A unit percentage increase in irrigation demand will reduce energy generation by 0.15%, but climate change has a beneficial impact on dam performance with a predicted increase in energy generation and supply to all sectors. Flood events will cause excessive stress on reservoir operation to handle up to six times more flow volumes; however, the low-flow events will marginally affect the system. While the flow and storage rule curves consider both supply and demand, changing human water use comes second to changing climate or other biophysical considerations. This paper emphasizes the importance of considering feedback between climate–water–human society in the systems modeling framework in order to meet societal and ecological challenges. The findings will provide information on the risks and tradeoffs that exist in the water, energy, and food sectors of the basin.

Climate Change Effect on Irrigation Water Requirement of Wheat and Maize in Northern Part of Bangladesh

Bangladesh is one of the most vulnerable countries for climate change in agricultural water management. A research had been done to assess climate change effects on irrigation water use of wheat and maize in the northern part of Bangladesh. The twenty nine years of data (1990-2018) were analyzed with Mann-Kendall test as well as Sen’s slope for climate change impact and the responsible weather parameters due to climate change were identified with correlation coefficients. The crop water requirement of wheat in Bogura and Rangpur was declining at the rate of 3.3mm and 2.3mm per decade respectively. Net irrigation water requirement of wheat at both Bogura and Rangpur was inclining at the rate of 1mm and 10mm per decade respectively because the effective rainfall of these regions was decreasing at 5mm and 11mm per decade respectively. The crop water requirement of maize for similar districts was increasing at the rate of 3.2mm and 2.5mm per decade respectively although net irrigation water requirement had statistically non-significance for climate change effect. The weather parameter, which was mainly responsible for climatic change in irrigation water requirement, was increasing temperature. Therefore, wheat cultivation might be coped with climate change in the northern part of Bangladesh rather than maize on the basis of irrigation and water management.

Irrigation scheduling and requirements of processing tomato (Lycopersicon esculentum L.) in Eastern Canada

A 3-year study was conducted to determine the irrigation requirements for field tomato production in southwestern Ontario, Canada. Irrigation requirements were ascertained using both a weather-based crop water model, and data from soil moisture sensors. The equivalent irrigation depth applied based on real-time soil moisture measurements among four soil moisture treatments ranged from 102 to 168 mm, 85 to 190 mm, and 58 to 196 mm for 2008, 2009, and 2010, respectively. Using the crop simulation model—AquaCrop, the net irrigation water requirement (NIWR) was estimated as 163–236 mm over the 3-year period. The model overestimated the NIWR compared to the real-time sensor-based measurements. A comparison between these two approaches indicated that a soil moisture depletion of ≤ 45% available water content (AWC) resulted in adequate moisture to meet crop water requirements, and correspondingly produce higher crop yields. From this study, we conclude that real-time soil moisture sensors proved to be very effective for scheduling irrigation of processing tomatoes in Eastern Canada and leads to higher water savings.

Determination of crop coefficient for chufa crop (Cyperus esculentus L. var. sativus Boeck.) for sustainable irrigation scheduling

Chufa is a traditional crop in L'Horta de València (Spain), a historical agricultural system that has been recognised in the register of Globally Important Agricultural Heritage Systems, managed by the Food and Agriculture Organization of the United Nations (FAO), and is one of the six protected Mediterranean and metropolitan horticultural fields as per the European Environment Agency. Chufa is a horticultural crop cultivated for its tubers. Our team has carried out different studies to improve the sustainability of chufa crop, particularly the efficiency of irrigation water use; however, the complete irrigation water requirements remain unknown. Therefore, the main aim of this study was to determine the crop coefficient values for chufa crop along its crop cycle using a smart field weighing lysimeter for three consecutive seasons and to determine its irrigation water requirements. The single crop coefficient values are 0.32, 1.40, and 0.80 for the initial stage, mid-season stage, and end of the late season stage, respectively for local conditions and 1.24 and 0.73 for mid- and late season stages, respectively for standard conditions. FAO segmented and second-order polynomial functions are presented to describe the crop coefficient evolution throughout the cycle, and could be used for irrigation scheduling and may lead to important water savings. The average seasonal net irrigation water requirement for chufa crop was approximately 640 mm, representing around 57% of the irrigation depth usually applied by chufa growers. The water savings that may be achieved by the adjustment of irrigation water with irrigation water requirements, using the crop coefficient, would improve, to a great extent, the sustainability of the L'Horta de València historical agricultural system, in view of the water scarcity resulting from climate change. This sustainable irrigation scheduling will improve the ecosystem indices, which have been altered by the application of over-irrigation, in the area.

Assessment of irrigation management practices using FAO-CROPWAT 8, case studies: Tina Plain and East South El-Kantara, Sinai, Egypt

The present study aims to assess current irrigation management practices in two totally different soil types and climatic conditions case studies at Tina Plain (AER1) and East South El-Kantara (AER2), Egypt. Net irrigation water requirements (NIWR) for eight crops were computed using the FAO-CROPWAT8 model. The results showed increasing in NIWR of about 25% for cultivating crops in AER2 compared to AER1. The current free crop pattern indicated 22.5% potential water savings compared to available water resources under surface irrigation efficiency of 40% in AER1 (clay soil) and 60% for surface, drip, and sprinkler irrigation in AER2 (sandy soil). Different crop pattern scenarios were tested and their income optimization was computed. Suggested scenarios showed Greenbeans and Sugarbeet crops had the maximum income (44% water saving). Whereas, Berseem clover and Cotton had minimum income and can cause 24% water shortage. Improving irrigation efficiency and cultivating Greenbeans and Sugarbeet are recommended.

Assessing HC27 Soil Database for Modeling Plant Production

Soil information is a vital input for crop models applications in various large area studies including climate change impact and food security. One of the global soil databases that provide full information for crop models is HC27 of IFPRI. The quality of the database has not been assessed for crop modeling so far. A tested crop simulation model (SSM-iCrop2) was used for this purpose that needs soil water related properties (i.e., depth, albedo, curve number for runoff, drainage coefficient, and soil water limits at saturation, drained upper limit and lower limit) for the simulation of crop properties. Actual data of two soil profiles from three different climate zones (locations) were used as model inputs to simulate potential yield, evapotranspiration (under rainfed conditions) or net irrigation water requirement (under irrigated conditions) of some important plant species (alfalfa, sugar beet, sugar cane, wheat, olive, soybean, apricot and chickpea) under rainfed and irrigated conditions of Iran. Results showed that the application of HC27 soil information in the SSM-iCrop2 model resulted in model output that was not different from the model output with actual soil information with respect to mean, variance, and distribution. No statistically significant difference was found in the simulation of various combinations of soil profiles-plant species-locations. It was concluded that HC27 information can be used in simulation studies with SSM-iCrop2 or other similar simple models for the simulation of potential yield, net irrigation water, or evapotranspiration that are commonly required for food security and climate change studies.