Assistant Professor FAMU-FSU College of Engineering
Periodic changes in water and sediment flow can alter river morphology. In addition to natural land use changes, humans also intervene by straightening and diverting rivers known as river channelization. These changes induce erosion and sedimentation rates to increase, resulting in sediment buildup in rivers and environmental changes. Sinuosity, Meander wavelength, and amplitude are key morphological parameters that can play a critical role in shaping limnological processes, with the potential to significantly impact rivers’ sediment transport, retention time, stratification, productivity, and resuspension. Understanding and managing rivers' morphological characteristics is vital for maintaining healthy aquatic ecosystems. Our methodology encompasses extracting morphological data: slope, sinuosity index, eroded and accreted area from Sentinel-2A satellite imagery along with land use and land cover maps, and discharge as a hydrological parameter using the physics-driven hydrological model: Hydrologic Engineering Center's - River Analysis System (HEC-RAS). This modeled data validated with observed data can be used to develop a deep neural network for predicting future river meanders. We plan to analyze our model on the Kissimmee River, South Florida, a newly restored river. Morphological parameters: meander wavelength, amplitude, and sinuosity from the previous time step alongside land use and land cover maps and hydrological data to be taken as independent variables, while morphological parameters for the subsequent time steps would be our dependent variables. In addition to predicting future river paths, our results can aid in predicting flood patterns, ensuring that the river is connected to floodplains which can help water managers to maintain healthy aquatic habitats.
