A novel application of data-based time series methods is proposed in this study to help overcome barriers to quantifying the impacts of Natural Flood Management measures from hydrological timeseries data which hitherto have prevented accurate assessment of the effectiveness of interventions. To demonstrate the value of this method, a transfer function noise model was fitted to stage data from a three year before-after-control-impact style monitoring study of leaky dams in an upland catchment in North Yorkshire, England. Using the data-based time series method, uncertainties associated with stage data were overcome. The models were able to simulate the peaks of flood events on one stream to within ±2 cm accuracy for 95% of events recorded during the baseline monitoring period. These simulations are used in this study’s companion paper to quantify leaky dam impacts on flood peak magnitude. The level of accuracy achieved in this study provides proof of concept for application of the approach to data from other environments and natural flood management interventions, which is crucial if natural flood management is to be used as a mainstream flood risk management measure.
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