الفهرس 
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Abstract
This study focused on measuring and comparing actual evapotranspiration from four methods CROPWAT model using FAO (P-M) equation, Eddy covariance, ETWatch-Egypt model, FAO WaPOR tool and then comparing with Lysimeter. Also irrigation scheduling was computed, which is an important step to save water and crop coefficient (Kc). The area of interest is Zankalon Water Requirements Experimental Station, which is located in the eastern part of the Nile Delta, Sharkia Governorate, Egypt. The site is located at 30o 35’ N and 31o 30’ E with an elevation of about 7 meters above sea level. Two seasons were selected (summer season, cotton crop from 01/05/2014 to 16/10/2014 and winter season, wheat crop from 01/12/2014 to 10/05/2015). Cotton and wheat crops used Surface Irrigation method with efficiency of 50 %. The soil type belongs to heavy clay class. The weather data were collected from the automatic weather station in Zankalon weather station, Sharkia Governorate, Egypt. Eddy covariance (EC) data are from Zankalon tower station. It has an elevation of about 15 meters. ETWatch model data are from National Authority for Remote Sensing & Space Sciences (NARSS). FAO WaPOR (1.1version) data from (https://wapor.apps.fao.org/home/WAPOR/1). Lysimeter is classified as weighing Lysimeter from Zankalon station. It has (2 m × 4 m) surface area and 2 m depth. 1. Data needed. Data required for each method is significantly different. CROPWAT model needed meteorological, soil, and crop data. Eddy covariance required input was latent hat flux. ETWatch model required both meteorological and remote sensing data. Also FAO WaPOR tool input data were remote sensing data. Rainfall, irrigation amount, and soil weigh data were used for Lysimeter method. 2. Output data. Tested methods output parameter were daily and dekadal actual evapotranspiration (ETa), daily and dekadal irrigation scheduling and Kc values. 2.1 Actual evapotranspiration (ETa) ETa demonstrates the exchange of water and energy between soil, land, and atmosphere. It is essentially for modeling and management water resources and important for agricultural or hydrological studies. 2.2 Irrigation scheduling. Irrigation scheduling is the process used to decide when and how much water to apply to a field that is maximize irrigation efficiency by applying the exact amount of soil moisture. It is based on soil water balance calculations and important for gaining optimal crop yields. 2.3 Crop coefficient (Kc) Kc is a factor indicating the ratio of actual with reference evapotranspiration. Each crop has its Kc value. Conclusions that explain our study results; or summer season crop (cotton) daily ETa values for CROPWAT and Lysimeter showed the most significant linear relationship than, FAO WaPOR, Eddy covariance, and ETWatch model, respectively. Regression of determination (R²) for CROPWAT was 0.67 and 0.60 for WaPOR. While for EC and ETWatch were 0.47 and 0.44, respectively. Dekadal values indicated that CROPWAT showed the most significant linear relationship. Also R² values were 0.86, 0.81, 0.77, and 0.69 for CROPWAT, WaPOR, EC, and ETWatch, respectively. Daily and dekadal ETa values for winter season crop (wheat) for CROPWAT tool with Lysimeter indicated the most significant linear relationship then FAO WaPOR, ETWatch model and Eddy covariance. R² for daily ETa were 0.58, 0.47, 0.34, and 0.32 for CROPWAT, WaPOR, ETWatch model, and Eddy covariance, respectively. And for dekadal ETa were 0.80, 0.62, 0.60, and 0.55 similarly. One can observed that the values of (R2) for dekadal ETa were becoming higher than daily ETa. Also the values of R2 were becoming closer for CROPWAT and WaPOR as well as for Eddy covariance and ETWatch for cotton crop. On the other hand the values of R2 were becoming closer for Eddy covariance and WaPOR tool, CROPWAT indicated highest value, and ETWatch indicated the lowest for wheat crop. The arrangement of performance as measured through RMSE and MBE was CROPWAT, WaPOR tool, ETWatch model, and Eddy covariance, respectively for (daily - dekadal) ETa for both cotton and wheat seasons. Lysimeter and CROPWAT ETa values were similar with some minor differences. Eddy covariance ETa values were always lower than ETa values from CROPWAT model. FAO WaPOR tool values were highly near to ETWatch values throughout both the cotton and wheat seasons. For cotton crop ETa values were 978.62, 959.40, 561.52, 670.04, and 662.07 mm/season for Lysimeter, CROPWAT, EC, ETWatch model, and FAO WaPOR tool, respectively. For wheat crop ETa values were 506.55, 460.40, 301.16, 366.39, and 375.15 mm/season for Lysimeter, CROPWAT, EC, ETWatch model, and FAO WaPOR tool, respectively. Net Irrigation Water Requirement (NIWR) values for cotton crop were 1007.08, 584.62, 699.59, 691.15, and 1026.60 mm/season for CROPWAT, EC, ETWatch model, FAO WaPOR tool, and Lysimeter, respectively. On the other hand Gross Irrigation Water requirement (GIR) values were 2014.15, 1169.24, 1399.19, 1382.30, and 2053.19 mm/season for CROPWAT, EC, ETWatch model, FAO WaPOR tool, and Lysimeter, respectively. NIWR values for wheat crop were 462.42, 293.82, 365.11, 371.45 and 510.64 mm/season for CROPWAT, EC, ETWatch model, FAO WaPOR tool, and Lysimeter, respectively. And values were 924.85, 587.65, 730.22, 742.90 and 1021.29 mm/season for CROPWAT, EC, ETWatch model, FAO WaPOR tool, and Lysimeter, respectively. For cotton crop number of irrigations were 7 irrigations for CROPWAT and Eddy covariance, 8 irrigations for ETWatch model and WaPOR tool and 12 irrigations for Lysimeter. For winter crop (wheat) the number of irrigations were 4 irrigations for CROPWAT and Eddy covariance, 5 irrigations for ETWatch model and WaPOR tool and 8 irrigations for Lysimeter. For cotton crop Kc values for initial, mid, and end stages according to FAO (56) were 0.35, 0.65, and 1.20, respectively. from Eddy covariance were 0.34, 0.56, and 0.61, respectively. But from ETWatch model were 0.47, 0.72, and 0.66, respectively. And from FAO WaPOR tool were 0.28, 0.85, and 0.59, respectively. from Lysimeter were 0.44, 0.21, and 1.05, respectively. For wheat crop Kc values were 0.70, 1.15, and 0.25, respectively for FAO (56). from Eddy covariance were 0.73, 0.67, and 0.42, respectively. But Kc values obtained from ETWatch model were 0.69, 0.84, and 0.61, respectively. from FAO WaPOR tool were 0.90, 0.81, and 0.66, respectively. And from Lysimeter were 1.17, 1.23 and 0.81, respectively. CROPWAT model is the only method from the tested method that allow computing irrigation scheduling easily. Irrigation scheduling for other methods were manually computed. FAO WaPOR tool is a promising tool for calculating actual evapotranspiration. As it is a publicly accessible near real time database using satellite data and allows monitoring of agricultural water productivity. Recommendations : Eventually, if meteorological data available, it is recommend to use CROPWAT model for calculating crop water requirements and irrigation scheduling. This is because of its availability, simplicity and easiness to use. It also allows the simulation of crop water use under various climate, crop, and soil conditions. The Eddy covariance is a powerful method to estimate the surface-atmosphere exchange at the ecosystem scale especially for evapotranspiration. Unfortunately it is not widely available in Egypt. It is an expensive method. The measurements are sometimes difficult to explain when atmospheric turbulence is weak, this occurs commonly at night. Generally, it gives lower vales than measured with FA-PM equation. As ETWatch model and FAO WaPOR tool values were very near as mentioned before. It is recommend to use FAO WaPOR tool because it is Open-access (availability to download data), easy to use, and have various versions. ETWatch model isn’t an open-source model, somewhat complicated and need high experience and time to preparing input data. It is highly recommended to use CROPWAT when predicting daily ETa, while in predicting dekadal ETa FAO WaPOR tool could be used. To accurately calculate Kc, needs huge data set so, it is important to use data for different growing season. Because of the necessity of calculating actual ET and the scarcity of freshwater resources, it is highly recommended to develop another inexpensive and efficient technique of measuring actual ET directly.