Author
Listed:
- Maurizio Tiepolo
(Department of Regional & Urban Studies and Planning (DIST), Politecnico di Torino, Viale Pier Andrea Mattioli 39, 10125 Turin, Italy)
- Giorgio Cannella
(Department of Environment, Land and Infrastructure Engineering (DIATI), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy)
- Muhammad Abraiz
(Department of Environment, Land and Infrastructure Engineering (DIATI), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy)
- Ousmane Baoua
(Direction de la Météorologie Nationale du Niger, 8 Rue du Grand Hôtel, Niamey BP 218, Niger)
- Elena Belcore
(Department of Environment, Land and Infrastructure Engineering (DIATI), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy)
- Daniele Ganora
(Department of Environment, Land and Infrastructure Engineering (DIATI), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy)
- Mohammed Ibrahim Housseini
(Ministère de l’Environnement, de l’Hydraulique et de l’Assainissement, Direction Générale des Ressources en Eau, Rond Point Hôpital de Niamey, Niamey BP 257, Niger)
- Alejandro Marmolejo Gutierrez
(Department of Environment, Land and Infrastructure Engineering (DIATI), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy)
- Marco Piras
(Department of Environment, Land and Infrastructure Engineering (DIATI), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy)
- Francesco Saretto
(Department of Environment, Land and Infrastructure Engineering (DIATI), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy)
- Riccardo Vesipa
(Department of Environment, Land and Infrastructure Engineering (DIATI), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy)
Abstract
Knowledge of river flood risk in semiarid rural areas is often based on outdated, low-resolution geoinformation. Consequently, identification of exposed settlements, assets and risk-reduction measures remains challenging. This dataset provides up-to-date, fine-grained information for a rural area spanning 931 km 2 that is exposed to flooding from the Niger River and the Karma Wadi. The dataset includes information on (i) areas exposed to the two flood types that characterise the river’s hydrological regime and flash floods from the wadi, (ii) flood-prone crops, buildings and (iii) measures for risk treatment. Discharge data, a 4 m horizontal-resolution digital elevation model, and two-dimensional hydraulic modelling with BASEMENT were used to identify flood-prone areas. Visual interpretation of high-resolution satellite imagery in Google Earth, together with field inspections, enabled the identification of exposed assets. The Information System on Rural Markets of Niger and house compensation values recognised during resettlement-related works enabled asset valuation. Risk was expressed in monetary terms as the product of flood probability and expected damage. Risk-reduction measures were identified with stakeholders through a SWOT analysis and prioritised using eight criteria. The dataset can support emergency plans, flood early warning systems, rescue and recovery operations and flood risk management.
Suggested Citation
Maurizio Tiepolo & Giorgio Cannella & Muhammad Abraiz & Ousmane Baoua & Elena Belcore & Daniele Ganora & Mohammed Ibrahim Housseini & Alejandro Marmolejo Gutierrez & Marco Piras & Francesco Saretto & , 2026.
"Dataset on Flood Risk Along the Niger River Upstream of Niamey,"
Data, MDPI, vol. 11(6), pages 1-16, June.
Handle:
RePEc:gam:jdataj:v:11:y:2026:i:6:p:139-:d:1964075
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