Assessing Water Consumption of Major Crops in the Command Area of Malwah Distributary, Shaheed Benazirabad, Sindh.
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Abstract
Soil and water are vital natural resources on which agriculture sector growth and village livelihood depend and having the proper knowledge of the Soil, Plant, and water relationship are extremely important to achieve sustainable agricultural productivity. Pakistan has entered the 21st century with the rising challenge to meet food and fiber requirements for its population for domestic consumption and export. Without having appropriate knowledge about the intense water need of plants, most of the agricultural land in Pakistan is still being irrigated by conventional methods, which in turn produces so many problems and reduces the agricultural productivity putting extra stress on the country’s economy, so to avoid these issues, it is extremely necessary to provide the required quantity of water to plant, which will only be possible by consideration and accurate estimation of Evapotranspiration of plant so to enhance awareness and practice of water-saving agriculture in Pakistan to increase the agricultural commodities. In this study, estimation of Actual Evapotranspiration ( ETa ) of Malwah Distributary located in Shaheed Benazirbad, Sindh was selected from Command area of Rohri Canal, ET of four different crops; Cotton, Fallow, Rice and Sugarcane for the period of Rabi 2019-2020 and Kharif 2020 was estimated by using satellite-based evapotranspiration mapping tool namely METRIC REFLUX. The actual ET for each season was obtained using the Reference ET fraction (ETrf) of satellite data and reference ET(ETr) obtained from the literature. The classified crop mask was obtained using maximum likelihood classification on bands 8,4, and 3 of sentinel-2 images of the year 2020. The overall accuracy obtained is 93% with a kappa coefficient 0.921841. The average Actual Evapotranspiration of different crops namely, banana, cotton, rice, and sugarcane were found to be 1527.2 mm, 536.6 mm, 386.80 mm, and 814.02 mm
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References
[2] S. A. Kadam, C. O. Stöckle, M. Liu, Z. Gao, and E. S. Russell, "Suitability of Earth Engine Evaporation Flux (EEFlux) Estimation of Evapotranspiration in Rainfed Crops," Remote Sensing, vol. 13, no. 19, p. 3884, 2021.
[3] L. Zhichkina, V. Nosov, K. Zhichkin, H. Aydinov, V. Zhenzhebir, and V. Kudryavtsev, "Satellite monitoring systems in forestry," in Journal of Physics: Conference Series, 2020, vol. 1515, no. 3, p. 032043: IOP Publishing.
[4] J. A. Benediktsson, P. H. Swain, and O. K. Ersoy, "Neural network approaches versus statistical methods in classification of multisource remote sensing data," 1990.
[5] M. Elhag and S. Boteva, "Mediterranean land use and land cover classification assessment using high spatial resolution data," in IOP Conference Series: Earth and Environmental Science, 2016, vol. 44, no. 4, p. 042032: IOP Publishing.