Water Balance Analysis over the Niger Inland Delta-Mali: Spatio-Temporal Dynamics of the Flooded Area and Water Losses

Abstract

Abstract:The Niger Inland Delta (NID) wetland comprises a large flooded area that plays an important role in the ecosystem services. This study provides a comprehensive understanding of the NID's hydro-climatological functioning using water balance approach. After a clear description of the water budget's elements specific to the NID catchment, a spatial and temporal dynamics of the annual flood across the NID over the period 2000-2009 was performed using data from satellite QuickSCAT and its associated sensor SeaWinds. The estimated areas were used along with observed discharge and remotely-sensed climatic data to quantitatively evaluate each water balance component. The results indicate: (i) a clear spatiotemporal of the flooded areas varied between 25,000 km 2 in wet periods and 2000 km 2 in dry periods; (ii) an average evapotranspiration loss of 17.31 km 3 (43% of the total inflow) was assessed in the catchment; (iii) precipitation's contribution to the NID's budget totals 5.16 km 3 (12.8% of the total inflow); and (iv) the contribution of return flow from irrigated fields totals 1.8 km 3 (4.5% of the total inflow, among which 1.2 km 3 are from Office du Niger) to the flooded areas, refined the NID's water balance estimates. Knowledge gained on NID's water balance analysis will be used to develop and calibrate hydrological models in the Niger Inland Delta of the basin.

Evolution of Surface Hydrology in the Sahelo-Sudanian Strip: An Updated Review

“…Specifically, it currently occurs 40 days earlier in Niamey, compared to its average date of occurrence in the 1950s. In turn, the major "black", or "Guinean", flood also occurs earlier and, overall, it finishes notably earlier (by 75 days); this is also observed in the Niger Inner Delta [55,56]. The double pattern of the annual flood has been more marked in recent decades.…”

“…It has not prevented the second flood from becoming more separated from the first one than previously after the Niger Inner Delta crossing. Ibrahim et al (2017) [56] significantly improved the knowledge of the NID hydrological processes by applying remote sensing methods to more accurately estimate evaporation in the delta.…”

Artificial Neural Network and Physical Based Models for Water-Level Forecasts Ofinner Niger Delta in Mali

“…The most common methods for river flow and WL forecasting are physical, conceptual and/or statistical rainfall-runoff methods [5][6][7]. In recent years, Artificial Intelligence (AI) has received a great deal of attention as a modern approach for data series analysis and for hydrology modeling, including Artificial Neural Networks (ANN) and the Adaptive Neuro-Fuzzy Inference System (ANFIS) [7][8][9][10][11][12][13].…”

Niger discharge from radar altimetry: Bridging gaps between gauge and altimetry time series

“…Hydrographs at Koulikouro exhibit sharp peaks around mid-September, and are affected by operating the Selingue dam on the Sankarani River, a tributary of the Niger in Southern Mali. Water moving along the Niger floods up to 25,000 km 2 of the inner delta during wet years and 2000 km 2 during dry years (Ibrahim et al, 2017). Downstream the inner delta, hydrographs are significantly flattened (e.g., Olomoda, 2012) and peak discharge is delayed (e.g., Aich et al, 2014).…”