Multi-Model Approach for Assessing the Influence of Calibration Criteria on the Water Balance in Ouémé Basin

Hydrological models are very useful tools for evaluating water resources, and the hydroclimatic hazards associated with the water cycle. However, their calibration and validation require the use of performance criteria which choice is not straightforward. This paper aims to evaluate the influence of the performance criteria on water balance components and water extremes using two global rainfall-runoff models (HBV and GR4J) over the Ouémé watershed at the Bonou and Savè outlets. Three (3) Efficacy criteria (Nash, coefficient of determination, and KGE) were considered for calibration and validation. The results show that the Nash criterion provides a good assessment of the simulation of the different parts of the hydrograph. KGE is better for simulating peak flows and water balance elements than other efficiency criteria. This study could serve as a basis for the choice of performance criteria in hydrological modelling.

Assessment of Groundwater Physico-Chemical Quality in the Ouémé Delta (Southern-Benin)

Groundwater resources are the main sources of water used to supply drinking water to the population of the Ouémé Delta via the Continental Terminal aquifer. Urbanization, population growth, and agricultural and industrial activities have resulted in a deterioration in the quality of these resources. To assess the quality of the delta’s groundwater and its suitability for human consumption and irrigation, a total of fourteen (14) physico-chemical parameters were analyzed in some forty existing water points between September 2020 and March 2021, using standard water analysis techniques. The values obtained were compared with the potability standards recommended by the World Health Organization (WHO) and the Republic of Benin and were subjected to statistical analysis (principal component analysis (PCA)). In addition, methods for determining the suitability of water for irrigation were used. The results showed that the waters are acidic to slightly neutral and influenced by ambient temperature. In addition, the waters are moderately mineralized, with conductivities (24 - 1205 μS/cm) in line with WHO standards. A comparison of the analytical results of the WHO (2017) and Benin (2001) standards indicates that the majority of the waters studied are of good quality for all the chemical parameters considered. Nevertheless, some samples show levels of nitrates (21%), potassium (14% to 16%), calcium (13%), ammonium (12%), nitrites (8%) and bicarbonates (10%) over their respective standards. The Wilcox and Riverside diagrams indicate that the majority of waters (90%) have excellent suitability for irrigation and no negative effect on soil fertilization.

Evaluation of Agricultural Contamination Level by Heavy Metals and Pesticides in Sediments of Rivers and Water Bodies for Shrimp Fishing in the Lower Ouémé: Case of the Aguigadji, Ahlan and Sele Stations in Benin

This study assessed sediment contamination by heavy metals and pesticide active ingredients linked to chemical inputs used in agricultural activities in the lower Ouémé. Pesticide residues from the organochlorine, pyrethroid and organophosphorus families were investigated by gas chromatography, and heavy metals (Cd, Pb, As, Ni, Zn, Fe, Mg, Cr and Hg) by atomic absorption spectrophotometry. The metallic pollution indices, the contamination factor (CF) and the ecological risk index were calculated. The results revealed 8 active ingredients in the rainy season and 9 in the dry season. Glyphosate was the active ingredient with the highest concentration at all stations, 9.65 ± 0.84 mg/kg recorded in the dry season at the Aguigadji station. All glyphosate values were above the EQS. DDT, Atrazine and Endosulfan also showed high concentrations in the dry and rainy seasons. Emamectin, Abamectin and Lambda Cyhalothrin also showed high concentrations in the dry season at Aguigadji, Ahlan and Sele. Only glyphosate was recorded at the control station (Toho), but in very low concentrations. Lead showed the highest concentrations at all the stations, 265.96 ± 21.02 mg/Kg in the rainy season and 255.38 ± 79.09 mg/Kg in the dry season, all detected at the Aguigadji station and above the EQS. Zn, Ni, Fe, Cu and Cr were all representative in both the dry and rainy seasons at the contaminated stations. Manganese showed high concentrations in the rainy season. Pb showed very high contamination (FC ≥ 6) at the Aguigadji and Ahlan stations and significant contamination (3 ≤ FC 6) at the Sele station in both the rainy and dry seasons. Ni, Hg and Cd, showed either moderate or significant contamination at the contaminated stations. The risk values showed a considerable ecological Ri (190 ≤ Ri < 380) in the rainy season and a moderate ecological Ri (95 ≤ Ri < 190) in the dry season at these contaminated stations.

Flood Risk Assessment in the Lower Valley of Ouémé, Benin

In response to the increased frequency of flood events in recent years, it has become crucial to enhance preparedness and anticipation through precise flood risk assessments. To this end, this study aims to produce updated and precise flood risk maps for the Lower Valley of Ouémé River Basin, located in the South of Benin. The methodology used consisted of a combination of geographical information systems (GIS) and multi-criteria analysis, including Analytical Hierarchy Process (AHP) methods to define and quantify criteria for flood risk assessment. Seven hydro-geomorphological indicators (elevation, rainfall, slope, distance from rivers, flow accumulation, soil type, and drainage density), four socio-economic vulnerability indicators (female population density, literacy rate, poverty index, and road network density), and two exposure indicators (population density and land use) were integrated to generate risk maps. The results indicate that approximately 21.5% of the Lower Valley is under high and very high flood risk, mainly in the south between Dangbo, So-Ava, and Aguégués. The study findings align with the historical flood pattern in the region, which confirms the suitability of the used method. The novelty of this work lies in its comprehensive approach, the incorporation of AHP for weighting factors, and the use of remote sensing data, GIS technology, and spatial analysis techniques which adds precision to the mapping process. This work advances the scientific understanding of flood risk assessment and offers practical insights and solutions for flood-prone regions. The detailed flood risk indicator maps obtained stand out from previous studies and provide valuable information for effective flood risk management and mitigation efforts in the Lower Valley of Ouémé.

Assessment of the Recent Hydromorphological Features of Nokoue Lake and Its Channels (South-East Benin)

Based on 2022 and 2023 hydrometric data and satellite images (Sentinel 2022, SPOT 2010), this study aims to present the Nokoué Lake and its channels’ re-cent hydromorphological characteristics. Integrating flow, tributary morphology, and topography data determined specific power values along the axes studied. The values obtained range from 2.69 to 12.92 W/m2 for Ouémé River and 2.46 to 10.99 W/m2 for Sô River. The resulting water erosion on banks and bottoms is of linear, areolar, or gully and claw types. Lake bathymetry varies from -0.5 to -2.6 m (low flow period) and -1 to -4 m;in the Ouémé, Sô, and Totchè rivers, it varies from -5 m to -7 m, reaching -10 m at the Cotonou channel entrance (flood period). Bathymetric profiles reveal varied “U”, “V” and “Intermediate” bottom morphologies, influenced by erosion/sedimentation processes and human activities. The flow facies identified are lentic in the northern tributaries and lotic in the Cotonou and Totchè canals. Spatial analysis identified nine (09) thematic classes. In 2022, the surface area of the water body has increased from 274 km2 at low water to 280 km2 at high water, whereas in 2010 (a recent year of exceptional flooding), the surface area was 270 km2 at low water and 277 km2 at high water. Significant changes in land use are observed between 2010 and 2022. The floodplain area decreased slightly, from 421 km2 in 2010 (year of exceptional flooding) to 419 km2 in 2022. The evolution of land use shows a progressive expansion of the urban environment to the detriment of the natural environment. In the medium to long term, this trend could threaten the hydromorphological balance and even the existence of this important lagoon ecosystem.

Assessment of the Contribution of Flooded Rice Cultivation Systems to Methane Emissions in the Lower OuéméValley, in Benin Republic

Flooded rice cultivation fields appear to be the major source of methane emission. In Benin Republic, flooded rice is cultivated in the Niger River and Ouémé River Basins. The present study aims to assess the contribution of flooded rice cultivation systems to methane emissions in the lower Ouémé Valley. Methane emission calculation was based on Activity Data which is the flooded rice harvested surface area from 2008 to 2017. The Tier 2 methodology of the IPCC 2006 Guidelines’ and the complements of the “Refinement 2019” have been used to elaborate the specific emission factors for the lower valley of Ouémé and to estimate the emission of methane in this zone. Semi-structured interviews were conducted with producers in order to elaborate on their perceptions of gas emissions in the flooded rice fields. The EX-ACT tool was used to estimate the carbon footprint of the intensive rice cultivation system “SRI” and the conventional rice cultivation system “SRC”. It is shown that producers have a strong perception of gas emissions in rice fields but are totally unaware of the nature of the gas. Methane emitted in the lower valley of the Ouémé is around 528 tons/year between 2008 and 2017 while the carbon footprint resulting from the results of EX-ACT for the adoption of the SRI rises to the level of sequestration of approximately 0.4 tCH4/ha/year. The intensive rice cultivation system has been identified as the production system that minimizes methane emissions and maximizes rice production.