Probability of flooding and vulnerability assessment in the Ajay River, Eastern India: implications for mitigation

Abstract

Estimation of flood intensity for a desired return period is of prime importance for flood management through flood plain zoning. Flood frequency analysis enables estimation of the probability of occurrence of a certain hydrological event of practical importance by fitting a probability distribution to one that is empirically obtained from recorded annual maximum discharge and/or stage data. This case study considers the use of four probability distributions, namely Gumbel's extreme value distribution (EV-I), extreme value distribution-III (EV-III), log-normal (LN) and Log-Pearson Type III (LPT-3) in flood modelling of monsoon-dominated Ajay River and illustrates the applicability of goodness of fit (GOF) and D-index tests procedures in identifying which distributional model is best for the specific data. Twenty-five years ) of existing and estimated annual peak discharge (Q max ) data have been used for analyzing the trend of flood occurrence. After identifying the best fit model, the peak gauge height data (h max ) are then analysed combining with geographic information systems (GIS) for predicting flood affected area and preparing inundation map at a specific return period (T). Results of the study showed that the LPT-3 distribution is better suited for modelling flood data for Ajay at Nutanhat in West Bengal. The computed Q max for LPT-3 distribution are slightly higher as compared to the results obtained by EV-I, EV-III and LN which are used for vulnerability assessment. The analysis also predicts that the affected area will be ranging from 235 to 290 km 2 in near future (at 25-to 200-year T). These findings provide clear picture for the pattern of hydrological fluxes and aftermath in the next decades in lower Ajay River Basin (ARB). Sustainable planning and developmental measures that consider the modelled pattern of hydrological fluxes of the study area were recommended for decision making.

Potential flood frequency analysis and susceptibility mapping using CMIP5 of MIROC5 and HEC-RAS model: a case study of lower Dwarkeswar River, Eastern India

“…In this study, DEM has been processed following standard procedure and after that, it was used for flood-prone area estimation. The calculation for demarcating flood-affected area was done following Bandyopadhyay et al [3]. Extraction of the flood-affected area has been used for 25, 50 and 75 year return period for all models as well as for all the RCPs.…”

“…A major portion of the world's populations resides in the flood plains and they are indirectly or directly dependent on the flood plains, thereby human encroachment, modification of river and degradation of the ecosystem has become unavoidable results [2]. Along with this, floods are possibly the most frequent, devastating and widespread event, responsible for the huge loss of life and economy [3]. Hwang et al [4] have found that due to global warming, over the past 25 or 30 years of twentieth-century witnessing numerous unprecedented floods globally which have increases the damage rate in a spectacular way [5].…”

“…Studies on the FFA is mainly based on certain popular probability frequency distribution functions, such as Extreme Value distribution (EV), Gumbel's Extreme Value distribution (GEV), Log-Pearson Type III, log-normal (LN), etc. [3]. Careful investigation on these methods has shown that suitability of frequency distribution functions varies with variation in a geographical area, such as GEV in Britain [39], LN distribution in China [40] and LPT-3 distribution in the USA [41,42].…”

Instantaneous Flood Events Data Analyses in Northern Pakistan

“…Water related issues in Pakistan are most crucial challenges for the policymakers, hydrologist and water resources engineers in the country (Akhtar, et al, 2008) and extreme flood events are one of the primary natural causes of economic losses in Asia. Natural hazard or calamity and all kind of flood are probably the most frequent and devastating, causing serious loss damages of economic, livelihood of people, and biodiversity (Mohapatra & Singh, 2003;Wang et al, 2011;Sharifi et al, 2012 ;Bandyopadhyay et al, 2016). The probabilities of occurrence of extreme events are determined by frequency analysis method.…”

“…(Mazhar Saeed, Ahmad, & Nabi, 2012) workout the flood frequency for Jhelum Basin's homogeneous regions and found Gumbel was the best distribution based on Chi-square test. (Bandyopadhyay et al, 2016) were performed vulnerability assessment in the Ajay River, Eastern India and workout LPT-3 best distribution for flood modeling. The magnitude of the flood was estimated by most affectively distribution Generalized Pareto, and Log Pearson type 3 of different period (Singo, Kundu, Odiyo, Mathivha, & Nkuna, 2012); (Bezak, Brilly, & Šraj, 2014); (Khattak et al, 2016); (Kamal et al, 2016) and, (Benameur, Benkhaled, Meraghni, Chebana, & Necir, 2017).…”