Estimation Of Crop Water Requirements Research Articles

Crop Water Requirement and Irrigation Scheduling under Climate Change Scenario, and Optimal Cropland Allocation in Lower Kulfo Catchment

Crop water requirement and irrigation scheduling in Lower Kulfo Catchment of southern Ethiopia have not assessed under climate change scenarios, and the allocation of crop land also not optimal that signifcantly challenges to crop productivity.Therefore, this study was conducted to evaluate the effects of climate change on future crop water requirements, and irrigation scheduling, and to allocate cropland optimally. Bias of projected precipitation and temperature were corrected by utilizing Climate Model data with the hydrologic modeling tool (CMhyd). Alongside, crop water requirements and irrigation scheduling were assessed using Crop Water Assessment Tool. After estimating crop water requirement, crop land were allocated optimally using General Algebraic Modeling System programming with non-negativity constraints (scenario 1), and non-negativity constraints based on farmers adaptation (scenario 2). Average reference evapotranspiration from 2030 to 2050 and 2060 to 2080 was increased by 11.9%, and 16.2%, respectively compared with the reference period (2010-2022). The total seasonal crop water requirements were 4,529mm, 4866.7mm, and 5272.2mm under 2010 to 2022, 2030 to 2050, and 2060 to 2080 climate change scenarios, respectively. The meean irrigation interval in 2010-2022, 2030 to 2050, and 2060 to 2080 climate change scenarios were 8 days, 7 days, and 5 days, respectively. This irrigation interval was decreased by 14% (2030-2050), and 34% (2060-2080) compared with the reference period. In 2030 to 2050 and 2026 to 2080 climate change scenarios, the required irrigation water at the inlet of main canal increased by 6.8%, and 18%, respectively. The optimal allocated area for tomato (60.4%), maize (20.8%), and watermelon (18.8%) in scenario 1 with net benefit of 1.47*108 Ethiopian Birr. The allocated areas in scenario 2 were (48%) for maize, (31.6%) for tomato, and (20.4%) for watermelon with 1.34*108 Ethiopian Birr net benefit it was reduced by 19.1% compared with the net benefit in scenario 1. Fruit crops alone may not suffice for local food needs and to address this, small farmers should grow maize, tomato, and watermelon. This research aids policymakers in encouraging climate-resilient agriculture and improving small-scale farmers' awareness through conducting workshops and training.

Estimation of Crop Water Requirement and Determination of Irrigation Schedule for Tomato Crop by using CROPWAT 8.0 Model

A study was conducted to estimate the crop water requirement and also to determine the irrigation schedule of tomato crop using CROPWAT 8.0 model at College of Agricultural Engineering Madakasira, Andhra Pradesh. The experiment was carried out under two methods of irrigation scheduling (Traditional furrow irrigation method and CROPWAT irrigation scheduling method). The total volume of water applied to the crop under traditional furrow irrigation method and CROPWAT irrigation scheduling method was 73.188 m3 and 47.0611 m3 respectively. Hence 35.69% of water saved in CROPWAT irrigation scheduling method. It was observed that the yield of the tomato crop in CROPWAT irrigation scheduling method was 36.8% more than the traditional furrow irrigation method. The crop water use efficiency in CROPWAT irrigation method was 58.36% more than the traditional furrow irrigation method. Thus, the study concluded that it is capable for strategic planning on irrigation management and scheduling in the view of water saving technology.

Assessment of crop water requirement and irrigation scheduling for selected crops in the Kohima district, Nagaland, India

Abstract This study was done to examine agricultural water and irrigation schedules for key crops grown in Kohima area of Nagaland, India, which has a humid subtropical climate. Climatic data over 16 years (2006–2021) were used to estimate crop water requirements using CROPWAT 8.0 model. Rice, maize, soybean, potato, cabbage, dry bean, ginger, and naga chili are the most common crops. ET0 was calculated using the FAO Penman–Monteith method and ranged from 1.41 to 3.65 mm/day. The USDA SCS approach calculated effective rainfall. The average annual ETC for rice, maize, ginger, soybean, bean (dry), potato, cabbage, and naga chili were 537.1, 305.7, 342.7, 292.2, 288.1, 364.3, 190.6, and 141 mm, respectively. Rice, maize, ginger, soybean, bean (dry), potato, cabbage, and naga chili require an average of 251.7, 54.9, 26, 73.1, 21.3, 21.9, 121.9, and 14.5 mm of irrigation each year, respectively. The crop irrigation schedules were created with 70% efficiency. The study emphasizes that irrigation must be adjusted to each crop's individual needs, whether through strategic scheduling or modifying net and gross irrigation volumes, to enhance water management and maximize crop production in the region.

Spatio-temporal Variability of Reference Evapotranspiration and Trend Analyze of Crop Water Requirement

The study was aimed to analyse the trend of Reference Evapotranspiration (ETo) for estimation of Crop Water Requirement (CWR) for Rice (Oryza sativum) cultivation in Manipur from 2011-2021 in 16 districts (Bisnupur, Churachandpur, Jiribam, Imphal East, Kamjong, Senapati, Imphal West, Tengnoupal, Ukhrul, Thoubal, Noney, Pherzwal, Chandel, Kakching, Tamenglong and Kangpokpi) ETo and CWR was estimated using CROPWAT. Spatial trends of climate variables were analysed using Mann– Kendall test and Sen’s slope estimator.

Estimating crop water requirement in Madhya Pradesh's agro-climatic regions: A CROPWAT and CLIMWAT software case study

Estimating actual crop evapotranspiration is vital in water-scarce environment affected by climate change, particularly for optimizing irrigation and enhancing crop yield. This research focuses on assessing crop water and irrigation requirement for major crops across six districts of Madhya Pradesh, India, spanning diverse agro-climatic regions. Employing CLIMWAT 2.0 and CROPWAT 8.0 software, calculated crop evapotranspiration and devised irrigation strategies tailored to local climatic conditions. The FAO-Penman-Montieth (FAO-PM) equation for reference evapotranspiration (ET0), aiding in crop water requirement computation and irrigation planning. Our findings reveal substantial variations in crop water requirements across crops and districts. For instance, soybean in Indore requires the highest water input at 380 mm, while in Guna, was least at 303 mm. Wheat, on the other hand, register the highest water needs in Khandwa at 510.6 mm and the lowest in the Neemuch district at 370.8 mm, particularly during the rabi season. Besides that, this study underscores the need for district-specific considerations, taking into account climate and soil characteristics when formulating water management strategies. Employing efficient irrigation practices and techniques to manage water stress becomes imperative for optimizing crop yield and achieving economic returns. Implementing customized approaches to enhance water use efficiency and promote sustainability in agricultural production is crucial. These research outcomes provide valuable insights for policymakers, agricultural practitioners, and water resource managers to develop context-specific water management strategies.

Satellite and Model-based Estimation of Crop Water Requirement of Major Irrigated Crops in the Koga Irrigation Scheme, Ethiopia

Satellite and Model-based Estimation of Crop Water Requirement of Major Irrigated Crops in the Koga Irrigation Scheme, Ethiopia

Implementing Management Practices for Enhancing Water-Food Nexus Under Climate Change

The current investigation aims to develop a management strategy to enhance the relationship between water and food in the Euphrates River Basin, Iraq. The research methodology utilized the LARS-WG model to generate weather data for the future period (2020–2050) for the CanESM2 model. The weather data was subsequently employed in the CROPWAT model to estimate crop water requirements. Finally, the Water Evaluating and Planning (WEAP) model analyzed the great-inhabitant growth rate scenario (5%), climate change scenarios (i.e., RCP2.6, RCP4.5, and RCP8.5), and management scenarios. The WEAP model was initially calibrated and validated utilizing several statistical metrics, viz., the root mean square (RMS), Nash-Sutcliffe coefficient efficiency (NSE), and the coefficient of determination (R2). Results revealed a superior performance of the WEAP model in terms of the statistical metrics utilized. The findings illustrate that the projected water demand under RCP 2.6, RCP4.5, and RCP8.5 scenarios and the inhabitants growth scenario increased by 49%, 54%, and 56%, respectively, in the year 2050 compared to the reference scenario. In addition, the findings indicate that the water demand would decrease by 59% under the considered management scenario. Accordingly, the investigation recommends implementing water management practices, especially adaptation measures for climate change. Doi: 10.28991/CEJ-2023-09-12-010 Full Text: PDF

Estimation of crop water requirement of tomato in Algeria using CROPWAT model

Estimation of crop water requirement of tomato in Algeria using CROPWAT model

Crop Water Requirement Estimation by Using Cropwat Model: A Case Study of Abrajit Earthen Dam Command Area, East Gojjam, Ethiopia

Crop Water Requirement Estimation by Using Cropwat Model: A Case Study of Abrajit Earthen Dam Command Area, East Gojjam, Ethiopia

Effect of foliar application of different concentrations of salicylic acid on Washington navel orange trees under water stress

BackgroundA field experiment was performed from 2021 to 2022 on 10-year-old Washington navel orange trees (Citrus sinensis) budded on sour orange rootstock (Citrus aurantium) under sandy loam soil conditions in the region of Belbeis—El Sharkia Governorate, Egypt. This study was carried out to increase water use efficiency, maximize water utilization and determine the most effective treatment of Washington navel orange trees by using different concentrations of salicylic acid (control, 250, 500, and 750 ppm) under some levels of water stress (100, 75 and 50% of estimated crop water requirement).ResultsIn this scenario, the water use efficiency increased with 750 ppm of salicylic acid under 75% of the estimated crop water requirement, which produced 2.27 and 3.09 kg of fruit for each cubic meter of irrigation water in the first and second seasons, respectively. In addition, using salicylic acid treatment with 750 ppm under 75% of the estimated crop water requirement had a high economic return through increasing water unit return, while using less water irrigation amount by 25% at the same time, which reached 9.06 and 12.38 EGP per every cubic meter of irrigation water in the first and the second seasons, respectively.ConclusionIn summary, the data cleared that the irrigation water quantity could reduce by 25% while maintaining the production and the possibility of increasing it by using salicylic acid with the highest concentration. Thus, we recommend applying the treatment of the estimated crop water requirement with 75% combined with salicylic acid 750 ppm to Washington navel orange trees budded on sour orange rootstock to gain a high economic return.

Determination of Crop Water Requirement and Crop Coefficient at Different Growth Stages of Tomato by Using Weighing Type Lysimeter in Raichur Region

The water requirement for any cropping system is important consideration for designing and managing irrigation systems. Water requirement of crops varies substantially over the growing season mainly due to variation in crop cover and climatic conditions. For estimating crop water requirement of tomato crop, we have taken field experiment in weighing lysimeter for three seasons rabi - (7th September 2021 to 5th January 2022); Summer - (15th January 2022 to 15th May 2022) and Kharif - (6th June 2022 to 4th October 2022). The crop water requirement helps us to develop the crop coefficients for various growth stages (initial, development, mid and late season) for particular climatic conditions. Further, with exact crop coefficients derived from weighing type lysimeter will be helpful for determining water requirement. The results showed that the crop evapotranspiration (ETc) for initial, development, mid-season and late-season being 22.76, 110.71, 173.47 and 68.71 mm, respectively. With respect to crop coefficient (Kc), it is estimated to be 0.38, 0.64, 1.12 and 0.66 for initial, development, mid-season and late season stages, respectively during rabi season. The crop evapotranspiration (ETc) for initial, development, mid-season and late-season being 26.53, 164.76, 235.56 and 121.51 mm, respectively. With respect to crop coefficient (Kc), it is estimated to be 0.56, 0.87, 1.22 and 0.78 for initial, development, mid-season and late season stages, respectively during summer season. The crop evapotranspiration (ETc) for initial, development, mid-season and late-season being 32.31, 131.38, 173.51 and 60.13 mm, respectively. With respect to Kc, it is estimated to be 0.36, 0.77, 1.13 and 0.74 for initial, development, mid-season and late season stages respectively during kharif season. The measured Kc values were significantly different from the FAO-56 reported values. Therefore, local calibration of crop coefficients is an essential for efficient irrigation water management and precise water applications.

Evaluation of evapotranspiration models for cucumbers grown under CO2 enriched and HVAC driven greenhouses: A step towards precision irrigation in hyper-arid regions

Evapotranspiration is considered as one of the most crucial surface fluxes describing the water movement from the land to the atmosphere in the form of evaporation from the soil and transpiration from plants. Several evapotranspiration models exist, but their accuracy is subject to change because of the differences between the underlying assumptions used in their formulation and the conditions of the application at hand. The appropriate selection of an evapotranspiration model is necessary to ensure the accurate estimation of crop water requirements. This work compares between 20 different evapotranspiration models for the estimation of transpiration of cucumber crops grown in a cooling-based greenhouse with CO2 enrichment located in a high solar radiation region. The models are classified into temperature-based, radiation-based, mass transfer-based, and combination models. These models are assessed against direct gas exchange measurements in a greenhouse with cucumber crops. The performance of the models is evaluated using nine statistical indicators to determine the most suitable models for the application under study. Results demonstrate that among the temperature-based models, Schendel and Blaney and Criddle models resulted in the best transpiration prediction, contrary to Hargreaves and Samani which presented the worst performance. Transpiration estimates from Rohwer were the closest and that of Trabert were the furthest to the measured data amongst the other mass-transfer based models. The Abtew model was the best transpiration predicting model, while Priestley and Taylor exhibited the worst performance in the radiation-based model category. The combination-based FAO56 Penman Monteith entailed the best performance among all models and can be considered the best suitable method to estimate transpiration for cucumber crops grown in CO2 enriched and HVAC based greenhouses located in high solar radiation regions. Nonetheless, the parametrization of this model is still crucial and should be considered to achieve better estimates and accurately evaluate the effect of high solar radiation, CO2 enrichment and HVAC cooling for this agricultural greenhouse application.

Assessment of Virtual Water Flows in Morocco’s Foreign Trade of Crop Products

As a semi-arid/arid country located in the northwest of Africa, Morocco is facing serious water scarcity driven by the dual stresses of decreasing availability of water resources and increasing water demands. Virtual water trade could be an effective tool to alleviate water scarcity. The paper presents an analysis of the relationships between agrarian productions, foreign trade, and the water sector in Morocco by deriving a comprehensive estimate of virtual water export and import in Morocco’s foreign trade of 40 crop products during the period from 2000 to 2017. Our objectives include determining the intensity of water consumption of exported and imported crop products and quantifying the water consumed and saved, respectively, by locally producing and importing these products. To this end, FAO’s Penman-Monteith climate model was used to estimate crop water requirements based on data on meteorological factors. The results show that Morocco was a net virtual water importer during the study period. The deficit was 595.74 Gm3. The tendency of total virtual water export was on a rising trend, while the total virtual water import was on a downward trend. The main exported virtual water was from vegetables (68.87 Gm3, 72.47%) and the main imported virtual water was from cereals (679.68 Gm3, 98.4%). Regarding crop product’s water intensity, we found that the exported crop products were excessively concentrated on water-intensive products such as mandarins and clementines, figs, oranges, apricots, plums, citrus fruits, olives, tomatoes, asparagus, peas, and artichokes. On the other hand, the agricultural policy of 2009–2020 increased the production of water-intensive products. This finding seems to be going against the virtual water trade theory, which states that water-poor countries should import water-intensive products and produce local products with lower water requirements.

Predictive Modelling of Reference Evapotranspiration Using Machine Learning Models Coupled with Grey Wolf Optimizer

Mismanagement of fresh water is a primary concern that negatively impacts agricultural productivity. Judicious use of water in agriculture is possible by estimating the optimal requirement. The present practice of estimating crop water requirements is using reference evapotranspiration (ET0) values, which is considered a standard method. Hence, predicting ET0 is vital in allocating and managing available resources. In this study, different machine learning (ML) algorithms, namely random forests (RF), extreme gradient boosting (XGB), and light gradient boosting (LGB), were optimized using the naturally inspired grey wolf optimizer (GWO) viz. GWORF, GWOXGB, and GWOLGB. The daily meteorological data of 10 locations falling under humid and sub-humid regions of India for different cross-validation stages were employed, using eighteen input scenarios. Besides, different empirical models were also compared with the ML models. The hybrid ML models were found superior in accurately predicting at all the stations than the conventional and empirical models. The reduction in the root mean square error (RMSE) from 0.919 to 0.812 mm/day in the humid region and 1.253 mm/day to 1.154 mm/day in the sub-humid region was seen in the least accurate model using the hyperparameter tuning. The RF models have improved their accuracies substantially using the GWO optimizer than LGB and XGB models.

Estimation of Crop Water Requirement in different Agro-Climatic regions of Madhya Pradesh Employing CROPWAT and CLIMWAT Software

Estimation of Crop Water Requirement in different Agro-Climatic regions of Madhya Pradesh Employing CROPWAT and CLIMWAT Software

Assessment of crop water requirement of maize using remote sensing and GIS

Irrigation water is limited and scarce in many areas of the world, including the Panchmahal region, Gujarat, India. Panchmahal is located in between 22° 30′ N to 23° 30′ N latitudes and 73° 15′ E to 74° 30′ E covering an area of 3314.56 km². Thus, better estimations of irrigation water requirements are essential to conserve water. The overall objective of the present study was to estimate crop acreage and crop water requirement (ETC) of dominant maize crop at various scales using a satellite remote sensing-based vegetation index. The resulted acreage estimation will helpful in understanding the cropping patterns and their interaction with spatial and temporal variability for present and future estimation of crop water requirements and proper resource availability in this selected region. Twelve clear sky Sentinel-2 satellite images from November 2020 to April 2021 were acquired for the study area for the analysis. For the Rabi season chosen for the current study, 34 images, each with two scenes and a five-day sensing interval, with a total of 68 images were downloaded and applied. The coefficient of maize crop for the entire growing season was generated using average NDVI based values, which were evaluated using remote sensing and GIS techniques. For maize crop, the NDVI and crop coefficient KC (FAO) showed a higher correlation with R2 = 0.8. As a result, the correlations of crop coefficient (KC) with the NDVI were used to create the KC map. Crop water demand based on actual crop evapotranspiration is a product of the average ETC value and the corresponding area. The total crop water demand for maize crop seasons was found to be 171.50 MCM. ETC maps helped to explain the variability of crop water use during the growing season. According to the findings, ETC maps created using remotely sensed multispectral vegetation indices are a helpful tool for assessing crop water usage at regional and field scales. The findings in this study will be helpful to the irrigation planners and farmers for applying appropriate amounts of irrigation water corresponding to each growth stage using ETC maps at the field scale, leading to water conservation, and better irrigation water management.

Models Comparative Study for Estimating Crop Water Requirement and Irrigation Scheduling of Maize in Metekel Zone, Benishangul Gumuz Regional State, Ethiopia

This study was aimed to compare estimation methods of crop water requirement and irrigation scheduling for major crops using different models and compare the significance of models for adoption at different situations in Metekel zone. Crop water requirement and irrigation scheduling of maize in selected districts of Metekel zone were estimated using CropWat model based on soil, crop and meteorological data and AquaCrop based on soil, crop and meteorological data including Co 2 , groundwater, field management, and fertility status. Model performance was evaluated using Normalized Root mean square errors (NRMSE), model by Nash-Sutcliffe efficiency (NSE), Prediction error (Pe), and Model efficiency (MF). It is observed that the maximum reference evapotranspiration in the study area was found to be 7.1 mm/day in Guba and minimum reference evapotranspiration was 2.9 mm/day in Bullen district. In all cases, the maximum ETo in all districts was fund to in March and the lowest in August. The maximum ETc of maize was found to be 702.4mm in Guba district and minimum ETc was found to be 572.6mm in Bullen district using CropWat but the effective rainfall (Pe) for maize were determined as 185mm respectively in Wembera district. However, using AquaCrop model the maximum ETc of 565 mm was recorded in Guba but 425 mm was recorded as minimum in Wembera district for irrigated maize in the study area. The study revealed that the irrigation scheduling with a fixed interval criterion for maize 10 days with 12 irrigation events has been determined. Moreover, furrow irrigation with 60 % irrigation application efficiency was adjusted during irrigation water applications for all districts. The performance of the irrigation schedule and crop response was evaluated by the analysis results in the simulation using different models. It has been observed that there was a strong relationship and a significant relation between the simulated and observed values for validation. Hence, Normalized Root mean square errors (NRMSE), model by Nash-Sutcliffe efficiency (NSE), Prediction error (Pe), and Model efficiency (MF) showed that AquaCrop model well simulated in all parameters considered. AquaCrop model is the most suitable soil-water-crop-environment management model, so future studies should suggest a focus on addressing deficit irrigation strategy with different field management conditions to improve agricultural water productivity under irrigated agriculture for the study area for major crops. Keywords: Depilation, Irrigation events, AquaCrop, Fixed interval and Deficit Irrigation. DOI: 10.7176/JEES/13-1-01 Publication date: January 31 st 2023

Estimation of Crop Water Requirements and Irrigation Scheduling for Major Crops Grown in India's North-Eastern Region

The water demand of some agricultural crops grown in Assam was assessed in this research. To estimate the crop water requirements of potato, chili, and brinjal, the FAO-CROPWAT model was used. The climatic parameters like rainfall, solar radiation, wind speed, sun hours, relative humidity, minimum and maximum temperature were collected for 30 years from the Indian Meteorological Department (IMD) to estimate the crop water requirement (CWR). The reference evapotranspiration (ETo) was computed by using the Food and Agriculture Organization (FAO)-recommended Penman-Monteith method and was found to vary from 1.84 mm/day to 4.49 mm/day. The calculated ETo was further used to compute the CWR, the net irrigation requirement (NIR), and the gross irrigation requirement (GIR) to plan for irrigation application during the growing stages of the selected crops. The total CWR of potato, chili, and brinjal was estimated to be 260.6 mm, 262.1 mm, and 274.2 mm, respectively, and the total NIR of potato, chili, and brinjal sowed on the 1st of October was found to be 162.8 mm, 149.0 mm, and 167.2 mm, respectively, with an irrigation efficiency of 70%. In December, the CWR and NIR of potato and brinjal were found to be the highest. The month with the least effective rainfall (8.5 mm) was December. The findings of the study showed that efficient irrigation water management and irrigation scheduling can be achieved by using the CROPWAT model to maximize crop yield and minimize crop water stress.

Irrigation of protected pepper crops according to growth stage using dynamic evapotranspiration estimates increases the water use efficiency

Current knowledge on crop irrigation in greenhouses is limited, and most irrigation measures are based on evapotranspiration (ET) estimated using external climatic conditions. Moreover, crop water requirement estimation by the Penman-Monteith (PM) model assumes complete coverage of the soil by the plants and usually does not account for partial cover, which changes during the growth of annual crops. The main goals of the present research were: (i) to develop and apply irrigation demand estimates for greenhouse pepper crops during their growth, based on internal meteorological conditions and real-time plant characteristics; and (ii) to examine the effect of that irrigation on yield. Experiments were conducted during two consecutive seasons in greenhouse pepper crops in the Jordan Valley region of eastern Israel. Four irrigation treatments were applied based on four different ET models: (i) PM model for outside reference evapotranspiration based on the FAO56 methodology, also denoted as the commercial treatment; (ii) PMrb model for pepper plants, which is a standard PM model in which a boundary layer resistance replaces the aerodynamic resistance; (iii) Shuttleworth-Wallace Layer (SWL) model which considers the soil and plants as separate interactive layers; (iv) Shuttleworth-Wallace Patch (SWP) model which considers the soil and plants as independent patches. The commercial treatment used external climatic conditions from a nearby meteorological station, whereas the other three treatments used internal meteorological conditions measured inside the greenhouse. Results showed a high correlation (R2 > 0.88) between leaf area index, vegetation cover fraction, and plant height during plant growth. Using the same meteorological conditions inside the greenhouse, the seasonal ET estimated by the PMrb model, which considers full vegetation cover, was larger by 21-28% than the SWL and SWP models, which consider the partial plant cover. Irrigation doses were deduced from ET multiplied by crop coefficients derived in a previous study for the same crop and structures. Using average data of the two seasons, we found that seasonal irrigation based on the two SW models was lower by 5-15% than that based on PMrb, and by 35-42% than the commercial irrigation. The water use efficiency of the commercial treatment was the lowest, while for the other treatments it was about 0.02 ton m-3 and higher by about 40% than the commercial. We conclude that irrigation of annual crops based on partitioning ET into evaporation and transpiration based on crop coverage and using internal climatic conditions allows water-savings without significant yield loss.

Estimation of Crop Water Requirement of Kharif Maize Crop using CROPWAT 8.0 Model in Bilaspur District

Water is one of the most important elements in this world. No life will exist without water. The main consumer of water is agriculture but due to mismanagement, overpopulation, and climatic changes this valuable natural resource is getting scarce position throughout the world. It has become very important to define appropriate strategies for planning, development, and management of water resources. The main objective of this paper is to the estimation of crop water requirement of Kharif maize crop for effective irrigation management. For proper irrigation management, CROPWAT is the best model suggested by FAO. 16-year climatic data were analyzed with the CROPWAT model, which is based on the United Nations Food and Agriculture Organization (FAO) paper number 56 (FAO 56). The Penman-Monteith method was used to estimate reference evapotranspiration (ET0). The model predicted the daily, decadal as well as monthly crop water requirement at different growing stages of maize crop. The average reference crop evapotranspiration (ETc­) during the 16 years was found to be 313.21 mm. It varies from 222.8 mm to 515.9 mm. The average irrigation requirement for maize crops during the period from 25th June to 17th September was 42.01 mm.