Runoff Estimation of the Kolong River Basin in Assam, India Using NRCS-Curve Number Method and Geospatial Techniques

Bhuyan, Manash Jyoti; Borah, Debashree; Nath, Binod Kumar; Deka, Nityananda; Bora, Ashok Kumar

doi:10.1007/978-3-030-79634-1_20

Cited by 6 publications

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The state's frequent and devastating floods are primarily caused by the construction of river dams, unscientific construction of embankments, bridges, roads, and railways, large‐scale deforestation in upper catchment areas, the expansion of human settlements to river banks, sand bars, and islands, the blockage of inlets and outlets of wetlands, the degradation of numerous wetlands, dead channels, and so on (Deka, 2012). The majority of surface runoff flows into rivers and tributaries during the peak monsoons, enabling them to carry a large load of water and sediment, resulting in high stage‐discharge of all the rivers in the state (Bhuyan et al., 2022). The floods cause damage to houses, roads, and other infrastructure, destroy crops, trigger erosion, breach embankments, and thus affect and disrupt normalcy (Dikshit & Dikshit, 2014).…”

Section: Introductionmentioning

confidence: 99%

Micro‐spatial flood risk assessment in Nagaon district, Assam (India) using GIS‐based multi‐criteria decision analysis (MCDA) and analytical hierarchy process (AHP)

Bhuyan¹,

Deka

Saikia³

2023

Risk Analysis

Self Cite

View full text Add to dashboard Cite

Nagaon is one of the highly flood‐prone districts of Assam, India that recurrently experiences devastating floods resulting in the loss of lives and property and wreaking havoc on the district's socioeconomic infrastructure. Identification and mapping of spatial patterns of flood hazards, flood vulnerability, and flood risk zones (FRZs) of the district are, therefore, crucial for flood management and mitigation. The present study, therefore, attempts to delineate the FRZs of more than 930 villages in the Nagaon district by integrating the flood hazard and vulnerability layers in the geospatial environment using the multi‐criteria decision analysis and analytical hierarchy process techniques. Here, seven flood hazard and vulnerability indicators are considered to derive each layer separately. The results indicate that about 15.14% of the district's total villages are in the very high FRZ, 27.93% in the high, 46.62% in the moderate, and 10.3% in the low FRZ. Further, bivariate correlation analysis is used to evaluate the results with the percentages of the population, cropland, and animals affected by floods at different temporal scales in order to ensure that the revenue circles with a higher percentage of area under high and very high FRZs genuinely have higher percentages of flood‐affected cropland, people, and livestock. The significance of this research is evident in its pragmatic findings that could aid the stakeholders in managing and reducing flood risk at micro‐spatial scales.

show abstract

Section: Introductionmentioning

confidence: 99%