Abstract
The hydrological response of a medium-sized watershed with both rural and urban characteristics was investigated through event-based modeling. Different meteorological event conditions were examined, such as events of high precipitation intensity, double hydrological peak, and mainly normal to wet antecedent moisture conditions. Analysis of the hydrometric features of the precipitation events was conducted by comparing the different rainfall time intervals, the total volume of water, and the precedent soil moisture. Parameter model calibration and validation were performed for rainfall events under similar conditions, examined in pairs, in order to verify two hydrological models, the lumped HEC-HMS (Hydrologic Engineering Center’s Hydrologic Modeling System model) and the semi-distributed HBV-light (a recent version of Hydrologiska Byråns Vattenbalansavdelning model), at the exit of six individual gauged sub-basins. Model verification was achieved by using the Nash–Sutcliffe efficiency and volume error index. Different time of concentration (Tc) formulas are better applied to the sub-watersheds with respect to the dominant land uses, classifying the Tc among the most sensitive parameters that influence the time of appearance and the magnitude of the peak modeled flow through the HEC-HMS model. The maximum water content of the soil box (FC) affects most the peak flow via the HBV-light model, whereas the MAXBAS parameter has the greatest effect on the displayed time of peak discharge. The modeling results show that the HBV-light performed better in the events that had less precipitation volume compared to their pairs. The event with the higher total precipitated water produced better results with the HEC-HMS model, whereas the rest of the two high precipitation events performed satisfactorily with both models. April to July is a flood hazard period that will be worsened with the effect of climate change. The suggested calibrated parameters for severe precipitation events can be used for the prediction of future events with similar features. The above results can be used in the water resources management of the basin.
Highlights
The city of Toronto is exposed to severe weather systems, producing occasional flash floods mainly due to various thunderstorms over a district, or slow-moving storms crossing a domain [1]
In the calibration process of the six studied events examined in pairs, it was found that specific equations were more suitable to calculate the time of concentration (Tc) at each sub-basin, since the Tc was very sensitive, producing great time shifts and variance of the maximum modeled runoff
The Nash–Sutcliffe efficiency (NSE) coefficient [65] was used in all studied sub-basins in order to measure the efficiency of the model, which is given by the following equation: R2
Summary
The city of Toronto is exposed to severe weather systems, producing occasional flash floods mainly due to various thunderstorms over a district, or slow-moving storms crossing a domain [1]. The survey of various climate indices calculated by historical spatiotemporal daily precipitation observations across Southern Ontario during a 64-year period demonstrated that extreme rainfall became more frequent [4]. Researchers in another study, using the data of 133 stations all over Ontario, being recorded on average within 26 years, applying the regional time trend methodology for several durations of yearly peak precipitation intensities, concluded that the extreme rainfall intensity raised from 1.25% per decade for a 30 min storm to 1.82% per decade for a 24 h storm [5]. Paixao et al [7] suggested the simultaneous use of remotely sensed radar observations and tipping bucket rain gauges recording, to better identify areas with homogeneous severe precipitation. The effectiveness of radar quantitative precipitation estimates (QPEs) for the assessment of reliable rainfall intensity to be used to hydrological software was punctuated by Wijayarathne et al [8]
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