(untitled) (International Journal of Food and Nutritional Sciences, 2022)
The main objective of the project is the development of a fuzzy logic model that will predict the Rann of Bhuj catchment area’s runoff values from rainfall data. To develop as well as test the model, the set of observations made on data covering ten years (June–October) between the periods of 2012 to 2022 is subdivided into training (70%) and validation. The FL models (1, 2, and 3) are made using nine linguistic variables that are used for each input and output in different datasets. This is done through the coefficient of determinate ion analysis and RMSE for evaluative purposes. However, FL Model 2 gives the best results among all the models, with an RMSE of 3.42 mm during training and 4.55 mm during validation, while providing correlation coefficient values of 0.9954 for training and 0.9921 for validation. This high-performing model shows its potential to forecast runoff for varying rainfall amounts. The study also defines a threshold of 27 mm as the minimum precipitation necessary for generating runoff from rainfall occurring in the Bhuj of the Rann of Kutch catchment area. In summary, the research introduces a fuzzy logic model that estimates runoff through different forms of rainfall. This output may be beneficial for predicting run-off within the assessed zone while determining the critical precipitation threshold that triggers the occurrence of runoff.