Flood risk assessment along the River Niger

The dataset used to build a novel Flood Risk Assessment (FRA) for semi-arid rural areas is provided here. Our FRA aims to address the shortcomings in multi-hazard, participation, and risk reduction that have been recurring in the FRA for semi-arid rural regions published over the last decade. We hypothesise that assessing flood risk by integrating high-resolution geoinformation and local knowledge in a participatory process enables the identification of risk reduction measures, thereby contributing to flood risk assessment in risk management. Data show the flood-prone area of the River Niger upstream of the city of Niamey during local floods and Guinean floods, each according to three probabilities of occurrence (return periods of 10, 30, and 100 years). Moreover, the data include the basin of the Karma Wadi (the largest tributary of the Niger River, which is reported to flood crops along the River Niger) and the highlands requiring treatment. Further information provided in the dataset includes assets exposed to each flood, expected damage, risk level for each of the five municipalities along the river, potential risk reduction measures, and their cost-benefit analysis. The main findings of the FRA are: 1) River flooding during the dry season causes more damage than during the wet season 2) Expected damage to irrigated crops is greater than damage to buildings 3) High-resolution geoinformation and local knowledge identify a feasible risk reduction 4) Raising the levees of rice fields, hygiene, and sanitation are priorities 5) High land prices hinder resettlement and redirect land development The data consists of an Excel file reporting (i) crops, settlements, buildings (footprint and number) exposed to 6 flood scenarios organised by municipality; (ii) expected damage, (iii) SWOT analysis on measures; (iv) Measures priority; (v) Risk reduction; (vi) Cost-benefit analysis. Moreover, five folders contain shape files of flood-prone areas, categorised by six scenarios (two types of floods and three probabilities of occurrence each), water depth, and assets (crops and buildings). Finally, two figures in PNG format localise each flood-prone settlement mentioned in the tables. Data were gathered from daily river discharge data provided by the Ministry of Hydraulics and Sanitation of Niger, a digital elevation model extracted from Planet satellite images and Google Earth images, the Information System on Rural Markets (SIMA), field inspections, and focus groups conducted with the municipalities of Gothèye, Karma, Kourteye, and Namaro. The dataset can be used for flood recovery, an impact-based flood early warning system, local risk reduction planning, and local emergency planning.