Quantifying the impacts of dams on riverine hydrology
Each year, the UF/IFAS Office of the Dean for Research highlights publications that are excellent examples of how UF/IFAS researchers at our Gainesville campus and our Research and Education Centers (RECs) are making a difference and impacting our world. Read on to learn more about one of the top 10 publications selected.
Quantifying the impacts of dams on riverine hydrology under non-stationary conditions using incomplete data and Gaussian copula models
Denis Valle and David Kaplan
Across the world, the assessment of environmental impacts attributable to infrastructure and development projects often require a comparison between observed post-impact outcomes with what “would have happened” in the absence of the impact (i.e., the counterfactual). Environmental impact assessment (EIA) methods can be particularly challenging to use in the context of substantial data gaps, a vexing problem when combining several time-series data from different sources.
The publication proposes and tests and a widely applicable statistical approach for quantifying environmental impacts: the Gaussian Copula (GC) model.
Valle and Kaplan assessed the hydrological impacts of the Tucuruí dam on the Tocantins River in the Brazilian Amazon. Using multi-source water level and climate data, GC predictions of pre-dam hydrology for the validation period were excellent. The GC model outperformed standard multiple regression models in representing predictive uncertainty while also avoiding the stationarity assumption and circumventing the issue of sparse and incomplete data, leading to the conclusion that the GC approach has wide utility for integrating disparate time-series data to quantify the impacts of dams and other anthropogenic phenomena on riverine hydrology globally.