PERSiST: a flexible rainfall-runoff modelling toolkit for use with the INCA family of models

Abstract

Abstract. Runoff generation processes and pathways vary widely between catchments. Credible simulations of solute and pollutant transport in surface waters are dependent on models which facilitate appropriate, catchment-specific representations of perceptual models of the runoff generation process. Here, we present a flexible, semi-distributed landscape-scale rainfall-runoff modelling toolkit suitable for simulating a broad range of user-specified perceptual models of runoff generation and stream flow occurring in different climatic regions and landscape types. PERSiST (the Precipitation, Evapotranspiration and Runoff Simulator for Solute Transport) is designed for simulating present-day hydrology; projecting possible future effects of climate or land use change on runoff and catchment water storage; and generating hydrologic inputs for the Integrated Catchments (INCA) family of models. PERSiST has limited data requirements and is calibrated using observed time series of precipitation, air temperature and runoff at one or more points in a river network. Here, we apply PERSiST to the river Thames in the UK and describe a Monte Carlo tool for model calibration, sensitivity and uncertainty analysis.

Impacts of climate change, land-use change and phosphorus reduction on phytoplankton in the River Thames (UK)

“…The flow cytometry data of these five groups were used to calibrate and validate the phytoplankton model developed in a previous study (Whitehead et al, 2015a). PERSiST (Futter et al, 2014) is a catchment-scale rainfall-runoff model which is specifically designed to provide input series for the INCA family of models. It is a semi-distributed model, i.e.…”

“…In this study, the calibrated PERSiST model of the River Thames catchment was used to produce altered series of SMDs and HERs using altered time series of precipitation and temperature as input. More information about the PERSiST model application to the River Thames catchment can be found in Futter et al (2014).…”

“…The uncertainty of the models employed in this study has been assessed separately in different studies. For example, Futter et al (2014) implemented a Monte Carlo-based approach for sensitivity and parameter uncertainty analysis of the PERSiST model for River Thames, finding that the model results were especially sensitive to evapotranspiration parameters and residence times. The uncertainty of the INCA model has been assessed in several papers, such as for example Raat et al (2004), who pointed out the problem of equifinality and suggested a multi-objective calibration approach, as well as the use of frequent measurements (fortnightly frequency) as reference values for calibration.…”

“…However, it can be assessed qualitatively. This modelling combination involves around 20-25 influential parameters, based on previous uncertainty assessments on the models used in this study (Dean et al, 2009;Futter et al, 2014;Raat et al, 2004;Rankinen et al, 2006;Whitehead et al, 2015b). However, as stated for example by Skeffington et al (2007), translating input uncertainties into uncertainty in the outputs is typically less than the summed uncertainty in the input parameters.…”

Modelling landscape controls on dissolved organic carbon sources and fluxes to streams

“…Moreover, within such models hydrological connectivity tends to be treated separately, using independently calibrated models to estimate water delivery (e.g. Band et al 1991;Futter et al 2008;Ledesma et al 2012;Oni et al 2014;Futter et al 2014). Other approaches have used simpler models that integrate both the key hydrological and biogeochemical processes to simulate the movement of DOC through soils, to the stream network, an example being the riparian profile flowconcentration integration model (RIM) (Seibert et al 2009).…”