The Mara Wetland in Tanzania has an important role in regulating the quality, timing and magnitude of the flow of water into Lake Victoria. In addition, the wetland provides natural resources for local communities and habitat for variety of species. The planned dam construction upstream of the wetland and projected changes in the local climate could affect the physical and ecological equilibrium of the system. Baseline information on seasonal inundation dynamics is necessary to sustainably manage these potential threats. The wetland is sparsely instrumented, which has hampered a thorough temporal and spatial understanding of the local water balance. In addition, the highly vegetated nature of the wetland, and relatively frequent cloud-coverage, motivates multi-source integration of remotely sensed data to capture flood patterns at a high resolution.
In this study, the spatiotemporal inundation pattern of the Mara Wetland in Tanzania is reconstructed using optical remote sensing data. The annual fluctuations in aerial wetland extent are analysed in parallel to the fluctuations of local water balance components: downstream water level of Lake Victoria, upstream discharge, direct precipitation and evaporation. The analyses aims to shed light on the underlying mechanisms and hydrological processes that control the hydric status of the wetland. Comparing the temporal changes in extent with surrounding physical processes provides insight on the responsiveness of the wetland to specific water balance components.
The intra- and inter-annual trends in inundation of the Mara Wetland are reproduced for the years 2017, 2018, 2019. The Random Forests (RF) algorithm is trained bi-seasonally (using bands and derived water and vegetation indices from Sentinel-2 data and a Digital Elevation Model (DEM) as input variables), and used to classify the land-covers of the wetland region in a semi-automated way for a total of 73 Sentinel-2 scenes. The scenes are classified into 7 individual land-cover classes; 3 wetland classes (open water, flooded vegetation, wet floodplain) and 4 dryland classes (dry floodplain, wet agriculture, dry agriculture, bare land). The overall classification accuracy achieved (based on an independent validation set, not used to train the classification algorithm) is 98.6 %. The spatiotemporal variability of the inundated area is used in combination with available hydrological field-data to reproduce the local water balance.
The seasonal expansion and contraction of the wetland follows a consistent bi-modal regime, and the results from the waterbalance affirm the importance of local precipitation in the seasonal expansion and contraction of the wetland. The base-flow supplied by the Mara River, together with the backwater from Lake Victoria appear to be at equilibrium at the extent of the permanent swamp during the dry season, insinuating the importance of the riverflow during these low-rainfall months. The occasional yet extreme flood events induced by high discharge rates are expected to play a specific ecological role in the wetland, and should be accounted for during future dam operations upstream.

Cape Town is a city with over four million people and a growing population. Due to three consecutive dry summers as a result of climate change, a growing population and an increased per capita water demand, the city’s main water supply was nearly depleted. Cape Town depends for 98% on surface water stored in dammed reservoirs, which is replenished by rainfall. There is a temporal mismatch between water availability and peak demand, and thus harvesting rainfall can be potentially become an additional source of water. Cape Town’s urban drainage system has 737 detention ponds, which are used to attenuate flooding in case of heavy rain events. These ponds can be used to harvest the stormwater and store it in the Cape Flats aquifer using managed aquifer recharge for seasonal availability. The complexity of retrofitting stormwater ponds into infiltration ponds calls for a systematic approach. This research offers a retrofitting framework for the context of Cape Town. The framework can be used to determine suitable detention ponds to allow managed aquifer recharge via infiltrating stormwater, and to retrofit these detention ponds into infiltration ponds. The framework consists of three phases; spatial assessment, physical assessment and conceptual design. It is highly flexible in usage due to the fact that every phase can be used separately. Additionally, the framework can be extended to include important socio-economic aspects. Following the framework standardizes the procedure of obtaining data on individual ponds, which allows for objective comparison in assessing their suitability for infiltration.