{"title":"Sustainability of water resources with precise modelling of crop coefficients","authors":"K. Reddy","doi":"10.1109/IEEECONF53624.2021.9668184","DOIUrl":null,"url":null,"abstract":"The sustainability of water resources depends on various factors, out of which one is a precise assessment of crop water requirements, in turn, the crop coefficients. Therefore, in this research, efforts are being made to generate a precise crop coefficient model to determine crop coefficients. The sugarcane is one among several vital crops cultivated in the Anakapalle research area. This study focused primarily on the evolution of crop coefficient (K<inf>c</inf>) models for sugarcane. The crop evapotranspiration (ET<inf>c</inf>) observed using a lysimeter, and reference evapotranspiration (ET<inf>0</inf>) assessed with the Penman-Monteith technique (proposed by FAO-56) was adopted in the study. The ET<inf>c</inf>and ET<inf>0</inf>values are substituted in K<inf>c</inf>= ET<inf>c</inf>/ ET<inf>0</inf>to obtain K<inf>c</inf>values. Graphs were plotted using the K<inf>c</inf>values on the y-axis and the days, weeks, or months after sowing the crop on the x-axis. The best curve fitting for these values in the graph is observed as a third-order polynomial curve, and the equation of the curve is considered as the K<inf>c</inf>model. The various statistical indicators are used to assess the capabilities of the K<inf>c</inf>models. It has been inveterate that the K<inf>c</inf>model functions effectively in both the phases of training and testing. The efficiencies of the K<inf>c</inf>models were observed as 82.32%. 92.47%, and 98.44% for daily, weekly, and monthly time phases, respectively. Thus, K<inf>c</inf>models could help predict K<inf>c</inf>values of sugarcane crops in the research area. It could be applied with a fair degree of precision in other places with similar climatic features to the research area.","PeriodicalId":389608,"journal":{"name":"2021 Third International Sustainability and Resilience Conference: Climate Change","volume":"240 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Third International Sustainability and Resilience Conference: Climate Change","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEECONF53624.2021.9668184","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The sustainability of water resources depends on various factors, out of which one is a precise assessment of crop water requirements, in turn, the crop coefficients. Therefore, in this research, efforts are being made to generate a precise crop coefficient model to determine crop coefficients. The sugarcane is one among several vital crops cultivated in the Anakapalle research area. This study focused primarily on the evolution of crop coefficient (Kc) models for sugarcane. The crop evapotranspiration (ETc) observed using a lysimeter, and reference evapotranspiration (ET0) assessed with the Penman-Monteith technique (proposed by FAO-56) was adopted in the study. The ETcand ET0values are substituted in Kc= ETc/ ET0to obtain Kcvalues. Graphs were plotted using the Kcvalues on the y-axis and the days, weeks, or months after sowing the crop on the x-axis. The best curve fitting for these values in the graph is observed as a third-order polynomial curve, and the equation of the curve is considered as the Kcmodel. The various statistical indicators are used to assess the capabilities of the Kcmodels. It has been inveterate that the Kcmodel functions effectively in both the phases of training and testing. The efficiencies of the Kcmodels were observed as 82.32%. 92.47%, and 98.44% for daily, weekly, and monthly time phases, respectively. Thus, Kcmodels could help predict Kcvalues of sugarcane crops in the research area. It could be applied with a fair degree of precision in other places with similar climatic features to the research area.