Comparing Delphi-fuzzy AHP and fuzzy logic membership in soil fertility assessment: a study of an active Ganga Delta in Sundarban Biosphere Reserve, India

Abstract

The present study led to setting up a grid-based soil fertility map along with the best fit model in the coastal regions based on soil physical (coarse, sand, silt, clay, bulk density), chemical (CEC, pH, and soil organic carbon), topographic (elevation), and nutrient elements (P₂O₅, K₂O, Na, Zn, B) in the active Ganga deltaic region of Sundarban Biosphere Reserve, India. Soil samples have been collected from 30 soil grids, and 0-15 cm soil depth was preferred for fertility analysis because most essential soil chemical and nutrient elements affecting soil fertility are concentrated in this depth range. We have used the fuzzy-AHP-Delphi (FAHP) and fuzzy logic-Delphi (FL) methods to determine the soil fertility zone. The rules are generated on the MATLAB interface in the text form; the words "IF," "THEN," "IS," "AND," etc., are used to complete the mode-building process. The weights and the desirable limits for each criterion were set based on the expert opinions and existing literature. The kriging interpolation method and natural break classification were used to represent the soil fertility maps into five classes, namely very high fertility (0.80-1.0), high fertility (0.60-0.80), moderate fertility (0.40-0.60), low fertility (0.20-0.40), and very low fertility (0.00-0.20) respectively. Both the models show that soil fertility is respectively higher near the Hooghly River bank. In many cases, the results obtained from FAHP and FL are quite similar but huge dissimilarity has been noticed in grid numbers G2, G3, G4, F1, and F2. Since the FAHP method has been used for the weight of each criterion, therefore, it only prefers those more important parameters over others. The overall accuracy of the soil fertility map was 82.16% for the fuzzy logic model, and 79.62% for the FAHP model and the kappa coefficient value was determined as 0.82 for the fuzzy logic model and 0.79 for the FAHP model. The soil fertility map was validated using the success rate curve under the ROC technique, and the area under curve (AUC) was calculated as 84.02% for the fuzzy logic model and 81.60% for the FAHP model. Since the standard limits for each criterion were known, therefore, fuzzy logic was found to best fit the model for analyzing soil fertility for each grid.

Keywords: Delphi; Salinity; Soil fertility; Sundarban biosphere reserve; fuzzy logic; fuzzy-AHP.