Wetlands are dynamic ecosystems and important sources of natural resources that provide a large array of ecosystem services. Unfortunately, most wetlands are threatened by human and natural stressors, such as damming, irrigation, water abstraction, climate change and variability that compromise the sustainability of the whole system. The Inner Niger Delta (IND), Mali, West Africa, is one of the biggest floodplains in the world, has a vast natural resource that attracts many people to live in and around the delta. The IND is considered a hub of human activities that include agriculture, fishing, transport, and tourism and plays an important role in promoting sustainable development for food security, water management, and the environment. As for most wetlands in the world, the very existence of the IND is at stake with the ever-increasing number of dams and irrigation schemes that are built to feed the growing population in the region. Given the fragility of the system and the multiplicity of water uses in the IND, the current knowledge of the flood dynamics and its relation to ecosystem services and the productivity of economic activity is insufficient. There is no operational hydrodynamic model of the IND, and the Malian authorities rely on simplified models and empirical relations for water resources management in the area. This thesis contributes to a better water resources management of the IND by a) developing the first 2D hydrodynamic model based on a triangular adaptative mesh of the IND that performs well despite the poor quality of available topographic/bathymetric data b) developing an innovative way of accounting for the strong hysteresis phenomenon in the IND in the hydrodynamic modeling that allowed a better reproduction of the hydraulic connectivity between important lakes and the main river and c) developing the first non-stationary relationship between the water levels at a reference station and the flooded area in the IND. The first part of the thesis deals with the challenge of developing a hydrodynamic model using only two low-resolution satellite-derived Digital Elevation Models: the Shuttle Radar Topography Mission (SRTM), which has a 30m horizontal resolution, and the Multi-Error-Removed Improved-Terrain (MERIT). Given the low vertical accuracy of global DEMs, another DEM was derived using the waterline method, by combining water extent map from satellite images and local water level information. Channel depths were approximated using the hydraulic geometric relationship methods, while the friction coefficient was derived from the global land-use class classification (GLCC) data. The river network was extracted from the water extent map corresponding to the lowest water level. Six different hydrodynamic models were created by varying the DEM and downstream boundary conditions. Each of the models was calibrated for discharge and water levels. Bayesian Model Averaging (BMA) was finally used to combine the outputs of all six hydrodynamic models into one robust simulation. In the second part, the effect of hysteresis at the downstream boundary condition of the hydrodynamic model was examined. Existing hydrodynamic models of the IND use a static stage-discharge relationship as a downstream boundary condition during both the rise and recession of the flood, leading to potential inaccuracies in the simulation of the flood extent. This paper explores the improvement in the simulation of the flood and connectivity dynamics resulting from the use of a looped rating curve at the downstream boundary of a hydrodynamic model of the IND. The hysteresis effect is integrated into the rating curve using two methods, one based on dimensionless discharges and levels (DLRC) and the other based on the modified Jones formula (MJRC). Results show that the hysteresis effect is better represented using DLRC and that simulations using any of the modified rating curves improves the accuracy of floodplain extent simulations in the areas close to the downstream station, as well as the timing of the connectivity of the river system to one important lake in the IND. The improvement in water level simulation decreases steadily with distance from the downstream boundary of the modeled area. The third part of the thesis deals with the development of an improved relation between inundation extent and water levels in the IND. Accurate knowledge of the flooded extent considered crucial for the proper management of natural resources in the IND. Several authors have developed empirical relationships between water levels at key stations in the IND and the flooded extent in an attempt to provide simple tools to link hydraulic parameters to the performance socio-economic activities in the IND. However, simulations from a hydrodynamic model of the IND showed that the relationship between water levels and the inundation extents varies greatly from year to year, and cannot be adequately captured by static formulas. First, it is demonstrated in this paper that if the maximum water level area is known in advance, accurate relationships between water levels and inundation extents can be derived. In the second part of the paper, stepwise regression is used to develop a function that can forecast maximum water levels at Akka using observed streamflow and precipitation upstream of the Delta. The combination of the two results allows a realtime estimation of the inundated area in the IND using observed water levels, precipitation, and streamflow.

Climate change and urbanization causes the increasing challenges of flooding in urban watersheds. Even the rivers identified as non-vulnerable are causing catastrophic damage due to heavy flooding. So, several satellite and radar-based precipitation data are considered to study the watersheds with no gauge station or need recent precipitation data. Weather Radar (NEXRAD)arch, the accuracy of satellite-based precipitation data, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Climate Data Record (PERSIANN-CDR), and radar-based precipitation data, Next Generation Weather Radar (NEXRAD), is evaluated in rainfall-runoff simulation considering Hydrological Engineering Centre-Hydrologic Modeling System (HEC-HMS) and Personal Computer Storm Water Management Model (PCSWMM), respectively.The primary research proposes a framework for modeling the rainfall-runoff process using PERSIANN-CDR and a floodplain map in an ungauged urban watershed. The one-dimensional Hydrologic Engineering Centre-River Analysis System (HEC-RAS) model generates a flood inundation map for the pertinent flooding occurrences from the acquired peak hydrograph, providing a quantifiable display of the inundation extent percentage. The second research uses the PCSWMMs to show the extent of flooding. It also employs the compromise programming method (CPM) to rank the most critical sub-catchments based on three parameters: slope, surface area, and impervious area. Three low-impact development (LID) strategies over the watershed determine the best flood management option. Therefore, the overall study presents a comprehensive framework for flood management in urban watersheds that integrates satellite precipitation data, hydrologic modeling, and LID strategies. The framework can provide an accurate flood-prone zone and help prioritize critical sub-catchments for flood management options. The study proposes using HEC-HMS and PCSWMM models to simulate and analyze interactions between rainfall, runoff, and the extent of the flood zone. Furthermore, LID can be applied to reduce flooding in urban watersheds. Overall, the framework can be helpful for policymakers and system managers to build the watershed's resilience during catastrophic flooding events caused by climate change and urbanization.