TY - JOUR
T1 - UISCEmod
T2 - Open-source software for modelling water level time series in ephemeral karstic wetlands
AU - Campanyà, Joan
AU - McCormack, Ted
AU - Gill, Laurence William
AU - Johnston, Paul Meredith
AU - Licciardi, Andrea
AU - Naughton, Owen
N1 - Publisher Copyright:
© 2023 The Authors
PY - 2023/6/21
Y1 - 2023/6/21
N2 - Characterizing ephemeral karstic wetlands through hydrological modelling is key for sustainable protection of their ecosystems and to understand and mitigate the impact of flooding events. UISCEmod is a new open-source software for modelling water level time series, focused on ephemeral karstic wetlands, that requires minimal input information. UISCEmod contains both experimental and lumped hydrological models, and the calibration process is automated following a Bayesian approach. The main outputs of UISCEmod include volume, stage, inflow and outflow model time series, calibrated model parameters, and the associated uncertainties. UISCEmod was evaluated at 16 representative sites in Ireland obtaining Nash-Sutcliffe Efficiency (NSE) and Kling-Gupta Efficiency (KGE) above 0.85 for both stage and volume time series for most of the sites, showing its potential for covering the need for a simple, pragmatic, and flexible framework for modelling water levels in ephemeral karstic wetlands with relatively limited input data requirements.
AB - Characterizing ephemeral karstic wetlands through hydrological modelling is key for sustainable protection of their ecosystems and to understand and mitigate the impact of flooding events. UISCEmod is a new open-source software for modelling water level time series, focused on ephemeral karstic wetlands, that requires minimal input information. UISCEmod contains both experimental and lumped hydrological models, and the calibration process is automated following a Bayesian approach. The main outputs of UISCEmod include volume, stage, inflow and outflow model time series, calibrated model parameters, and the associated uncertainties. UISCEmod was evaluated at 16 representative sites in Ireland obtaining Nash-Sutcliffe Efficiency (NSE) and Kling-Gupta Efficiency (KGE) above 0.85 for both stage and volume time series for most of the sites, showing its potential for covering the need for a simple, pragmatic, and flexible framework for modelling water levels in ephemeral karstic wetlands with relatively limited input data requirements.
KW - Bayesian
KW - Groundwater
KW - Hydrology
KW - Karst
KW - Modelling
KW - Wetlands
UR - http://www.scopus.com/inward/record.url?scp=85163819655&partnerID=8YFLogxK
U2 - 10.1016/j.envsoft.2023.105761
DO - 10.1016/j.envsoft.2023.105761
M3 - Article
AN - SCOPUS:85163819655
SN - 1364-8152
VL - 167
JO - Environmental Modelling and Software
JF - Environmental Modelling and Software
M1 - 105761
ER -