Water Use Analaysis for Irrigation Management using NDLI Measures

Agricultural management relies heavily on the early identification and measurement of plant responses to situations such as disease and water scarcity. The dimensionalfree Normalization Divided Moist Heat Index (NDLI) is being used to plant health for the first time in this study. To further examine crop conditions and water restrictions in rice-growing regions, we propose merging NDLI using infrared radiation and solar energy balance components. There is a strong association (r = 0.82) between the residual of the frequently employed Surface Radiation Balance Algorithm for Field model and crop evapotranspiration calculated through the integration of NDLI and land surface temperature. Significant relationships with the canopy plant biophysical variables generally described and anticipated by the a multispectral sensor indices were also found, suggesting that the ET method provides accurate information on the state of paddy fields. Optimization of the Soil-Adapted Vegetation Index (OSAVI) had a correlation coefficient of 0.84 with SEB-derived ET; NDVI and NDWI both had correlation values of 0.55; and NDVI had a correlation coefficient of 0.84 with NDLI. In most cases, the percentage of information that is different between NDLI- and SEB-derived ET and SEBAL-determined ET for the agricultural areas at issue is less than 10%. Disease-infected sections of paddy fields show unusually low ET signatures in NDLI and SEB derived ET maps, but not in SEBAL derived ET maps. This research shows promise for NDLI as an indication of crop health and stress from water for more efficient food supply management.