Determinants of Rural Households’ Intensity of Flood Adaptation in the Fogera Rice Plain, Ethiopia: Evidence from Generalised Poisson Regression

Ndue, Kennedy; Baylie, Melese Mulu; Pál, Goda

doi:10.3390/su151411025

Cited by 6 publications

(3 citation statements)

References 115 publications

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“…the least number of respondents reported a lack of attention, this is crucial in ood mitigation decisions. Lamond & Proverbs (2009) and Ndue et al (2023) reported that for ood resilience efforts to be successful, coordination and commitment from ood-prone populations are the best requirements. In this study, 4.5% of the households reported that their absence of commitment to ood mitigation was one of the constraining factors in the study area.…”

Section: Challenges Of Flood Mitigation Strategies In Study Areasmentioning

confidence: 99%

Flood Impacts on Household Livelihoods and Its Mitigation Strategies: Focus of Gelana Woreda, Oromia, Ethiopia

Deresse,

Baye

2024

Preprint

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This study assessed the impact of floods on household livelihoods and mitigation strategies in Gelana Woreda, Oromia, Ethiopia. The study's goals included determining the contributing cause, calculating the flood's impact, evaluating household mitigation activities in reaction to the threat of flooding, and evaluating how household livelihoods were impacted by the risk of a flood. The results of the study indicate that different flood effect factors cause interpersonal flood variability to increase slightly. Over a ten-year period, seasonal migration (16.6%), disruption of human health (3%), and loss of life (1.5%) were the three most common shocks from flood-induced disasters in the study area; heavy rain/flash flooding (29.7%) and river flooding (49.2%) were the two main causes of these shocks. Based on the GIS-generated flood map, 46.5% of the kebeles chosen for the Gelana district were categorized as having a high risk of flooding; marginally more than 2.3%; and the remaining 22.1%, 19.5%, and 2.3% had extremely high, low, and moderately hazardous levels, respectively, indicating a greater risk of flooding. Whereas Jirme and Bore have areas with extremely low and medium flood threats, the areas surrounding Kersa, Metari, and Shamole Shida are classified as having highly hazardous and moderate hazardous flood danger. However, in the research region, the main obstacles to flood mitigation were informational gaps (15.6%), lack of funding (28.6%), absence of government support (18.6%), and reluctance to join farmer associations (14.1%). Raising farmers' knowledge of agricultural technologies, structural mitigation, environmental restoration, ease of access to credit services, diversification of income streams, building farmers' capacity, promoting multiple strategies as the main flood mitigation strategies, and raising household standards in the study area are therefore important.

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Section: Challenges Of Flood Mitigation Strategies In Study Areasmentioning

confidence: 99%

Flood Impacts on Household Livelihoods and Its Mitigation Strategies: Focus of Gelana Woreda, Oromia, Ethiopia

Deresse,

Baye

2024

Preprint

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“…GP models can handle both over-dispersion and under-dispersion in the data and are more flexible in handling crash data with low sample mean compared to NB models [44]. The applications of GP models for analysing count data could be found in other fields; for instance, vehicle insurance claims [44], shipping damage incidents [45], environmental sciences [46], transport demand management [47] and medical sciences [48]. However, only a handful of studies have used the GP model for developing SPFs in transportation safety literature [21,26,49].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Road Infrastructure and Traffic Factors Influencing Crash Frequency: Insights from Generalised Poisson Models

Khattak,

De Backer,

De Winne

et al. 2024

Infrastructures

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This research utilises statistical modelling to explore the impact of roadway infrastructure elements, primarily those related to cross-section design, on crash occurrences in urban areas. Cross-section design is an important step in the roadway geometric design process as it influences key operational characteristics like capacity, cost, safety, and overall functionality of the transport system entity. Evaluating the influence of cross-section design on these factors is relatively straightforward, except for its impact on safety, especially in urban areas. The safety aspect has resulted in inconsistent findings in the existing literature, indicating a need for further investigation. Negative binomial (NB) models are typically employed for such investigations, given their ability to account for over-dispersion in crash data. However, the low sample mean and under-dispersion occasionally exhibited by crash data can restrict their applicability. The generalised Poisson (GP) models have been proposed as a potential alternative to NB models. This research applies GP models for developing crash prediction models for urban road segments. Simultaneously, NB models are also developed to enable a comparative assessment between the two modelling frameworks. A six-year dataset encompassing crash counts, traffic volume, and cross-section design data reveals a significant association between crash frequency and infrastructure design variables. Specifically, lane width, number of lanes, road separation, on-street parking, and posted speed limit are significant predictors of crash frequencies. Comparative analysis with NB models shows that GP models outperform in cases of low sample mean crash types and yield similar results for others. Overall, this study provides valuable insights into the relationship between road infrastructure design and crash frequency in urban environments and offers a statistical approach for predicting crash frequency that maintains a balance between interpretability and predictive power, making it more viable for practitioners and road authorities to apply in real-world road safety scenarios.

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“…Over the past 20 years, the livelihoods of approximately 400 million people were annually affected by floods, resulting in 28,000 flood-related fatalities in Asia between 1987 and 1997 (United Nations University, WHO, 2001;National Disaster Management Authority NDMA, 2022). Studies documented that floods have widespread adverse effects globally (Alhassan, 2020;Ndue et al, 2023), exacerbating regional inequalities (Mohanty et al, 2020). Floods, a natural phenomenon, can have the most significant impact on the world's human population (Ahmadi et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

The impact of social capital to improve rural households’ resilience against flooding: evidence from Iran

Savari,

Jafari,

Sheheytavi

2024

Front. Water

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Floods have significantly affected many regions worldwide, imposing economic, social, and psychological consequences on human societies, in recent decades. Rural communities in Iran are particularly vulnerable to floods, and without effective risk reduction systems, the impact can be exacerbated. In this context, this study aims to investigate the role of social capital in enhancing the resilience of rural households against floods in the southwest of Iran. The statistical population includes all rural households in Shushtar County that have experienced floods at least once. The primary tool for data collection was a questionnaire and obtained data were analyzed using structural equation modeling. In examining the situation of confrontation between different groups of people based on the state of social capital and resilience, it can be said that men, older people and people with higher income had more resilience and social capital to deal with floods. In addition, the results revealed that components of social capital (social networks, social solidarity, social trust, social awareness, participation and collection action) explained 68.1% of the variance in the resilience of rural households against floods. Overall, our findings can provide new insights for policymakers in the area, contributing to the reduction of flood impacts and promoting safer living conditions in flood-prone areas.

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Determinants of Rural Households’ Intensity of Flood Adaptation in the Fogera Rice Plain, Ethiopia: Evidence from Generalised Poisson Regression

Cited by 6 publications

References 115 publications

Flood Impacts on Household Livelihoods and Its Mitigation Strategies: Focus of Gelana Woreda, Oromia, Ethiopia

Flood Impacts on Household Livelihoods and Its Mitigation Strategies: Focus of Gelana Woreda, Oromia, Ethiopia

Analysis of Road Infrastructure and Traffic Factors Influencing Crash Frequency: Insights from Generalised Poisson Models

The impact of social capital to improve rural households’ resilience against flooding: evidence from Iran

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