Exploring the fidelity of satellite precipitation products in capturing flood risks: A novel framework incorporating hazard and vulnerability dimensions over a sensitive coastal multi-hazard catchment.

Complexities involved in flood risks over global coastal multi-hazard catchments are a severe concern for vulnerable communities, infrastructure, and the environment. Data scarcity in these regions often hinders our holistic understanding of flood risks, especially when socio-economic and physical vulnerabilities are involved. The extent to which Satellite Precipitation Products (SPPs), which are looked upon as alternatives to ground-based observations, can influence flood risk dynamics remains unexplored. In an attempt to answer the most riveted questions in flood management literature, this study, for the first time, explores the suitability of two competent SPPs, i.e., CHIRPS v2.0 and PERSIANN-CDR, in multi-hazard flood risk mapping. The proposed framework is demonstrated over the sensitive flood-prone deltaic stretches of the Lower Mahanadi River Basin (India). A computationally efficient MIKE+ 1D2D hydrodynamic model is developed to account for the wave propagation of concurrent flood drivers and generate high-resolution flood hazard maps for three disastrous historical flood events (July 2019, September 2020, and August 2022). To understand the hidden characteristics of vulnerability, a comprehensive set of 24 physical and socio-economic indicators is considered in a Shannon-entropy and TOPSIS framework. The variations in flood risk from both SPPs at the finest administrative scale are represented using the novel concept of Bivariate Choropleth, which portrays the marginal and compound contributions of hazard and vulnerability. A superlative performance of CHIRPS v2.0 over PERSIANN-CDR was observed in capturing hydro-climatological behaviors. CHIRPS v2.0-derived flood hazards were found analogous to the SAR-derived maps for all the three events. >70 % of villages display large disparities in flood risk, thereby affirming the role of appropriate SPPs towards efficient flood management. The observations from the study add vital information to the existing flood management policies, especially over resource-constrained regions in low and middle-income nations.

A synergistic approach towards understanding flood risks over coastal multi-hazard environments: Appraisal of bivariate flood risk mapping through flood hazard, and socio-economic-cum-physical vulnerability dimensions.

The dynamics of flood risk over Coastal Multi-hazard Catchments (CMC) exhibit bizarre characteristics. In these regions, flood hazards are governed by a complex interaction of multiple flood-inducing sources; varying in magnitudes, origin, and direction of propagation. Our conventional understanding of vulnerability may be obscure within these catchments. This can be attributable to the heterogeneous nature of various physical and socio-economic entities. The study proposes a comprehensive framework to quantify bivariate flood risks over a severely flood-prone region in India. The study considers flood hazards, along with vulnerabilities transpiring from (a) physical, (b) socio-economic, and (c) composite (combination of both) groups of indicators. To overcome data scarcity prevalent in CMCs, CHIRPS v2.0, a high-resolution Satellite Precipitation Product, along with other ancillary datasets, are forced to 1D2D coupled MIKE+ hydrodynamic model to simulate flood hazards. A set of 24 indicators are considered within the Shannon Entropy-cum-TOPSIS framework to derive three types of vulnerability. The marginal and compound contributions of hazard and each vulnerability type are represented through a novel concept of bivariate flood risk classifier at the village scale. We notice high and very-high flood hazards over the coastline and floodplains. An equitable influence of socio-economic vulnerability and hazards is reflected, as they cover 41 % of villages together under varied degrees of flood risks. The impacts of hazards are underscored in the presence of physical vulnerability, as the latter contributes to risks in about 72 % of villages. Composite vulnerability prevails its impact over 53 % of villages, dominating its influence on flood risks over hazards. The study delivers vital information to the global flood management community on the prudent selection of indicators, as their influence is markedly noticed on the overall flood risks. The diversified characteristics of flood risk inspire a rationalized implementation of structural and non-structural options in resource-constrained conditions.

Are open-source hydrodynamic models efficient in quantifying flood risks over mountainous terrains? An exhaustive analysis over the Hindu-Kush-Himalayan region.

The Hindu-Kush-Himalaya is abode to numerous severely flood-prone mountainous stretches that distress vulnerable communities and cause massive destruction to physical entities such as hydropower projects. Adopting commercial flood models for replicating the dynamics of flood wave propagation over such regions is a major constraint due to the financial economics threaded to flood management. For the first instance, the present study attempts to investigate whether advanced open-source models are skillful in quantifying flood hazards and population exposure over mountainous terrains. While doing so, the performance of 1D-2D coupled HEC-RAS v6.3 (the most recent version developed by the U.S. Army Corps of Engineers) is reconnoitred for the first time in flood management literature. The most flood-prone region in Bhutan, the Chamkhar Chhu River Basin, housing large groups of communities and airports near its floodplains, is considered. HEC-RAS v6.3 setups are corroborated by comparing them with 2010 flood imagery derived from MODIS through performance metrics. The results indicate a sizable portion of the central part of the basin experiences very-high flood hazards with depth and velocities exceeding 3 m, and 1.6 m/s, respectively, during 50, 100, and 200-year return periods of floods. To affirm HEC-RAS, the flood hazards are compared with TUFLOW at 1D and 1D-2D coupled levels. The hydrological similarity within the channel is reflected at river cross-sections (NSE and KGE > 0.98), while overland inundation and hazard statistics differ, however, very less significant (<10 %). Later, flood hazards extracted from HEC-RAS are fused with the World-Pop population to estimate the degree of population exposure. The study ascertains that HEC-RAS v6.3 is an efficacious option for flood risk mapping over geographically arduous regions and can be preferred in resource-constrained environments ensuring a minimal degree of anomaly.