Smart Agricultural Technology 4 (2023) 100186 Available online 18 January 2023 2772-3755/© 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/). Assessment of crop water requirement of maize using remote sensing and GIS Sanjay H. Parmar a , G.R. Patel b , M.K. Tiwari c, * a Research Associate, Centre of Excellence on Soil and Water Management, Research Training and Testing Centre, Junagadh Agriculture University, Junagadh, Gujarat, India b Associate Professor & I/c Registrar, Department of Agricultural Engineering, College of Agriculture, Anand Agricultural University, Vaso, Gujarat, India c Assistant Professor & Head, Department of Irrigation and Drainage Engineering & Soil and Water conservation Engineering, College of Agricultural Engineering and Technology, Anand Agricultural University, Godhra, Gujarat, India A R T I C L E INFO Editor by: Spyros Fountas Keywords: Sentinel-2 Crop acreage Crop water requirement NDVI Crop coeffcient ABSTRACT 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 km 2 . 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 (ET C ) 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 avail- ability 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 fve-day sensing interval, with a total of 68 images were downloaded and applied. The coeffcient 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 coeffcient K C (FAO) showed a higher correlation with R 2 = 0.8. As a result, the correlations of crop coeffcient (K C ) with the NDVI were used to create the K C map. Crop water demand based on actual crop evapotranspiration is a product of the average ET C value and the corresponding area. The total crop water demand for maize crop seasons was found to be 171.50 MCM. ET C maps helped to explain the variability of crop water use during the growing season. According to the fndings, ET C maps created using remotely sensed multispectral vegetation indices are a helpful tool for assessing crop water usage at regional and feld scales. The fndings 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 ET C maps at the feld scale, leading to water conservation, and better irrigation water management. 1. Introduction Irrigated agriculture is the largest consumer of water in arid and semi-arid areas. Most of the large irrigation schemes have extremely high water losses, with crop evapotranspiration accounting for only 20%–35% of the water supplied, with the remainder being wasted [1]. Limited water resources and water scarcity in India are obstructing ag- riculture’s horizontal expansion. At the same time, the world’s popu- lation is growing and agricultural land is decreasing. As a result, the amount of food available will be reduced. FAO-Penman-Monteith method is the most accurate for ET 0 estimation in both humid and arid climatic conditions. It provides ET 0 estimates for planning and effcient use of agricultural water resources [2]. At the farm level, determining ET C generally depends on a two-step process. The frst one is ET 0 , and the second is a semi-empirical coeffcient (crop coeffcient) that is applied to represent crop and environmental factors [3]. Evapotranspiration is a key hydro meteorological process and its estimation is important in many felds of hydrological and agricultural sciences. The importance of accurate evapotranspiration prediction in hydrological modelling, irrigation planning, and water resource * Corresponding author. E-mail addresses: grpatel@aau.in (G.R. Patel), mukesh.tiwari@aau.in (M.K. Tiwari). Contents lists available at ScienceDirect Smart Agricultural Technology journal homepage: www.journals.elsevier.com/smart-agricultural-technology https://doi.org/10.1016/j.atech.2023.100186 Received 14 November 2022; Received in revised form 11 January 2023; Accepted 12 January 2023