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High-resolution modelling of the grass swale response to runoff inflows with Mike SHE
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.ORCID iD: 0000-0002-2321-164x
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.ORCID iD: 0000-0003-0367-3449
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.ORCID iD: 0000-0001-9938-8217
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.ORCID iD: 0000-0003-1725-6478
2018 (English)In: Journal of Hydrology, ISSN 0022-1694, E-ISSN 1879-2707, Vol. 562, p. 411-422Article in journal (Refereed) Published
Abstract [en]

The feasibility of simulating the hydrological response of a grass swale to runoff inflows was examined using the hydrological model Mike SHE and the available input data from 12 irrigation events mimicking runoff from block rainfalls. The test swale channel had a trapezoidal cross-section, bottom slope of 1.5%, length of 30 m, and was built in loamy fine sand. The irrigation events consisted in releasing two equal constant inflows to the swale: a concentrated longitudinal flow at the upstream end and a distributed lateral inflow along the swale side slope adjacent to the contributing drainage area. The total inflows approximated runoff from two events with return periods of 2 months and 3 years, respectively, for durations of 30 min. Irrigation experiments were done for two states of the initial soil moisture, dry or wet antecedent moisture conditions (AMC). Mike SHE has been extensively used on catchments of various sizes, but rarely for small stormwater management facilities and their detailed topography investigated in this study. The latter application required high spatial and temporal resolutions, with computational cells of 0.2 × 0.2 m and time steps as short as 0.6 s to avoid computational instabilities. For dominant hydrological processes, the following computational options in Mike SHE were chosen: Soil infiltration – the van Genuchten equation, unsaturated zone flow – the one-dimensional Richards equation, and overland flow – the diffusive wave approximation of the St. Venant equations. For study purposes, the model was calibrated for single events representing one of four combinations of low and high inflows, and dry and wet AMC, and then applied to the remaining 11 events. This was complemented by calibration for two events, representing high inflow on wet AMC and low inflow in dry AMC. The goodness of fit was statistically assessed for observed and simulated peak flows, hydrograph volumes, Nash-Sutcliffe model efficiencies (NSE), and soil water content (SWC) in swale soil layers. The best fit (NSE > 0.8) was obtained for high inflows and wet AMC (i.e., when the primary swale function is flow conveyance); the least fit was noted for low inflows and dry AMC, when the primary swale function is flow attenuation. Furthermore, this observation indicates the overall importance of correct modelling of the soil infiltration. The effects of spatial variation of SWC on the swale discharge hydrograph could not be confirmed from simulation results, but high topographical accuracy was beneficial for reproducing well the locations of the observed water ponding. No significant increases in simulated SWC at 0.3 m or greater depths were noted, which agreed with field observations. Overall, the results indicated that Mike SHE was effective in process-oriented small-scale modelling of grass swale flow hydrographs.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 562, p. 411-422
Keywords [en]
Grass swale, Distributed modelling, Mike SHE, Soil water content, Stormwater management
National Category
Oceanography, Hydrology and Water Resources Water Engineering
Research subject
Urban Water Engineering; Centre - Centre for Stormwater Management (DRIZZLE)
Identifiers
URN: urn:nbn:se:ltu:diva-68751DOI: 10.1016/j.jhydrol.2018.05.024ISI: 000438003000031Scopus ID: 2-s2.0-85046868673OAI: oai:DiVA.org:ltu-68751DiVA, id: diva2:1206292
Projects
GrönNano
Funder
Swedish Research Council Formas, 2015-778
Note

Validerad;2018;Nivå 2;2018-05-16 (andbra)

Available from: 2018-05-16 Created: 2018-05-16 Last updated: 2023-09-05Bibliographically approved

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Rujner, HendrikLeonhardt, GüntherMarsalek, Jiri

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