EHSMu: a New Ecohydrological Streamflow Model to Estimate Runoff in Urban Areas
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EHSMu: a New Ecohydrological Streamflow Model to Estimate Runoff in Urban Areas Elena Cristiano 1
& Roberto Deidda
1
& Francesco Viola
1
Received: 28 May 2020 / Accepted: 14 October 2020/ # The Author(s) 2020
Abstract
A conceptual lumped ecohydrological streamflow model (EHSMu) is presented as a promising tool to simulate runoff in urban catchments. The model, based on the interaction between a soil bucket and two linear reservoirs, enables also evapotranspiration and aquifer recharge to be estimated. Notwithstanding its minimalism, EHSMu describes interactions among soil moisture dynamics, hydrological fluxes and ecological processes. The model was calibrated and validated within two densely urbanized sub-basins in Charlotte (US). A Monte Carlo procedure is used to investigate the efficiency of random sets of 8 model parameters. Results show the high model performance (NSE = 0.72). The influence of land use change is evaluated, by varying the imperviousness and crop coefficients. Synthetic experiments show that increasing urbanization triggers a linear decrease in evapotranspiration and aquifer recharge, while it increases the fast runoff. An opposite response is achieved by installing vegetation with higher potential evapotranspiration, which would contribute to the actual evapotranspiration making up 50–55% of the total water balance. Keywords Hydrological modelling . Rainfall-runoff modelling . Ecohydrology . Urban areas
1 Introduction Over the last decades, people have been moving to cities, contributing to an increase in urbanization, which is projected to keep growing in the future (UN Desa 2019). This is expected to lead to an increment in the runoff generation and, consequently, to an intensification of flood risk. In this framework, modelling can play a significant role in the runoff estimation and in the definition of flood mitigation strategies.
* Elena Cristiano [email protected]
1
Department of Civil and Environmental Engineering and Architecture, University of Cagliari, Cagliari, CA, Italy
Cristiano E. et al.
Urban areas, however, are complex systems and, due to the high spatial variability and heterogeneity, they are difficult to model (Fletcher et al. 2013; Salvadore et al. 2015). Several models have been proposed to estimate the urban runoff, trying to account for spatial and temporal variability of rainfall and catchment (Cristiano et al. 2017). Most of these models focus on the identification and representation of the stormwater drainage network (Zoppou 2001), and they combine it with surface dynamics, in order to estimate the amount of rainfall that reaches the sewer system (Bermúdez et al. 2018; Rubinato et al. 2013; Versini et al. 2016). Semi- and fully-distributed physically-based models have been developed for many urban areas, showing good performance in the runoff estimation (Aronica and Cannarozzo 2000; Pina et al. 2016). However, in most of the cases, these models require a long computational time and also spatially and temporally distributed input data (Cristiano e
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