Assessing Flood Risk Dynamics in Data-Scarce Environments—Experiences From Combining Impact Chains With Bayesian Network Analysis in the Lower Mono River Basin, Benin

Abstract

River floods are a common environmental hazard, often causing severe damages, loss of lives and livelihood impacts around the globe. The transboundary Lower Mono River Basin of Togo and Benin is no exception in this regard, as it is frequently affected by river flooding. To enable adequate decision-making in the context of flood risk management, it is crucial to understand the drivers of risk, their interconnections and how they co-produce flood risks as well as associated uncertainties. However, methodological advances to better account for these necessities in risk assessments, in data-scarce environments, are needed. Addressing the above, we developed an impact chain via desk study and expert consultation to reveal key drivers of flood risk for agricultural livelihoods and their interlinkages in the Lower Mono River Basin of Benin. Particularly, the dynamic formation of vulnerability and its interaction with hazard and exposure is highlighted. To further explore these interactions, an alpha-level Bayesian Network was created based on the impact chain and applied to an exemplary what-if scenario to simulate changes in risk if certain risk drivers change. Based on the above, this article critically evaluates the benefits and limitations of integrating the two methodological approaches to understand and simulate risk dynamics in data-scarce environments. The study finds that impact chains are a useful model approach to conceptualize interactions of risk drivers. Particularly in combination with a Bayesian Network approach, the method enables an improved understanding of how different risk drivers interact within the system and allows for dynamic simulations of what-if scenarios, for example, to support adaptation planning.

Assessment of inland flood hazard sensitivity to hydrological intensification in coastal watersheds

“…The utility of the relationship was demonstrated in the extrapolative mapping of relative flood sensitivities of various channels throughout SW LA region. This result provided a concrete example of how such relationships can be leveraged to address critical knowledge gaps in practical settings where region-wide risk assessments are required in data-scarce environments (Wetzel et al, 2022). The method further shows how a subset of numerical models and publicly-available datasets can be leveraged to estimate regional flood sensitivities.…”

An Integrated Multi-Risk Assessment for Floods and Drought in the Marrakech-Safi Region (Morocco)

“…During the course of a dedicated workshop with 31 local experts and stakeholders (held in October 2019 in Marrakech), drivers of risk were discussed and identified for each singlerisk, following the "impact chains" methodology (adapted from Fritzsche et al, 2014;Hagenlocher et al, 2018a;Zebisch et al, 2021). Impact chains are analytical tools designed to highlight the relational nature of drivers of risk through a participative process and have been increasingly used in climate risk assessments at various spatial scales in Europe (Buth et al, 2015;Greiving et al, 2015;Arabadzhyan et al, 2020;Lückerath et al, 2020), Benin (Wetzel et al, 2022), Bolivia (Zebisch et al, 2021, Burundi (Schneiderbauer et al, 2020), Pakistan (Zebisch et al, 2021), and Morocco alike (GIZ, 2014a,b). This exercise resulted in the creation of draft conceptual models describing the interrelationships between drivers of risk, which were subsequently complemented by additional literature research and bilateral consultations (Cotti et al, in progress): moreover, the models were used to inform the selection of indicators of hazard exposure and vulnerability for the multi-risk assessment (see Sections Multi-risk Hazard Exposure and Multirisk Vulnerability).…”

“…However, the weighting scheme employed for the index partially represents interactions by calculating different scores according the combination of risk (instead of for each risk separately). While for this application they only informed the selection of relevant indicators for the static composite indicator, future applications should explore modeling approaches to correctly represent the complex relationships between drivers of risk in a multi-risk context, expanding on recent efforts at the single-risk level (Wetzel et al, 2022).…”

Recovering from Financial Implications of Flood Impacts—The Role of Risk Transfer in the West African Context

“…Moreover, in the light of climate change, the annual maxima of daily precipitation in the area are expected to increase further, leading to a more substantial impact of heavy rainfall events on discharge within the river basin and thus to flood events of higher severity [5]. Apart from climatic changes, there are also other anthropogenic factors contributing to the flooding problem in the area, such as deforestation as well as the expansion of settlements, farmland, and infrastructure into exposed areas [57,66,67]. The floods in the largely rural LMRB usually cause extensive damage, for example, to houses, infrastructure, public buildings, and human health, due to the flood water remaining in the living environment for some time [6,55,56].…”

“…Additionally, they affect the The floods in the largely rural LMRB usually cause extensive damage, for example, to houses, infrastructure, public buildings, and human health, due to the flood water remaining in the living environment for some time [6,55,56]. Additionally, they affect the livelihoods and the productive assets of the population, who largely depend on agriculture as their primary livelihood source, followed by fishing, trading, palm oil production, and keeping livestock [66,68,69]. These impacts put an additional strain on the affected population's finances, and they are often left to figure out ways of dealing with the flood impacts in the long term with limited resources [70], aside from disaster assistance and relief activities by the government and NGOs.…”