@Article{rig.2024.058265,
AUTHOR = {Nilotpal Kalita, Ashok Kumar Bora, Rana Sarmah, Dhrubajyoti Sahariah, Manash Jyoti Nath},
TITLE = {Comparative Flood Hazard Assessment in Assam’s Belsiri River Basin Using AHP and MaxEnt Models},
JOURNAL = {Revue Internationale de Géomatique},
VOLUME = {34},
YEAR = {2025},
NUMBER = {1},
PAGES = {37--51},
URL = {http://www.techscience.com/RIG/v34n1/59283},
ISSN = {2116-7060},
ABSTRACT = {Flooding is a natural event often associated with floodplain areas, characterised by large, sudden and significant rises in river water levels that drastically alters the surrounding landscape. The research employs ArcGIS tools, multi-criteria evaluation techniques and the Maximum Entropy (MaxEnt) model to assess flood hazard zones. The key physical elements of slope, elevation, rainfall, drainage density, land use, and soil types have been integrated to identify areas vulnerable to flooding. Overlay analysis has been used to construct zones specifically designated for flood hazards. Additionally, pairwise comparison using Saaty’s scale was employed to calculate the Eigenvector weights for each physical factor. A comparison of AUC values is estimated to find the most effective method for delineating flood hazard zones. The MaxEnt model achieved an Area Under Curve (AUC) of 0.978, outperforming the Analytical hierarchy Process (AHP) model with an AUC of 0.967. The higher AUC indicates that the MaxEnt model is better at distinguishing between positive and negative occurrences. This could lead to more reliable predictions of the flood hazard zones. Overall, the higher AUC of the MaxEnt model suggests greater reliability and robustness.},
DOI = {10.32604/rig.2024.058265}
}