Surface Water Flow Balance of a River Basin Using a Shallow Water Approach and GPU Parallel Computing—Pescara River (Italy) as Test Case

The analysis and prevention of hydrogeological risks plays a very important role and, currently, much attention is paid to advanced numerical models that correspond more to physical reality and whose aim is to reproduce complex environmental phenomena even for long times and on large spatial scales....

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Main Authors: Antonio Pasculli, Roberto Longo, Nicola Sciarra, Carmine Di Nucci
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Water
Subjects:
Online Access:https://www.mdpi.com/2073-4441/14/2/234
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author Antonio Pasculli
Roberto Longo
Nicola Sciarra
Carmine Di Nucci
author_facet Antonio Pasculli
Roberto Longo
Nicola Sciarra
Carmine Di Nucci
author_sort Antonio Pasculli
collection DOAJ
description The analysis and prevention of hydrogeological risks plays a very important role and, currently, much attention is paid to advanced numerical models that correspond more to physical reality and whose aim is to reproduce complex environmental phenomena even for long times and on large spatial scales. Within this context, the feasibility of performing an effective balance of surface water flow relating to several months was explored, based on accurate hydraulic and mathematical-numerical models applied to a system at the scale of a hydrographic basin. To pursue this target, a 2D Riemann–Godunov shallow-water approach, solved in parallel on a graphical processing unit (GPU), able to drastically reduce calculation time, and implemented into the RiverFlow2D code (2017 version), was selected. Infiltration and evapotranspiration were included but in a simplified way, in order to face the calibration and validation simulations and because, despite the parallel approach, it is very demanding even for the computer time requirement. As a test case the Pescara river basin, located in Abruzzo, Central Italy, covering an area of 813 km<sup>2</sup> and well representative of a typical medium-sized basin, was selected. The topography was described by a 10 <i>×</i> 10 m digital terrain model (DTM), covered by about 1,700,000 triangular elements, equipped with 11 rain gauges, distributed over the entire area, with some hydrometers and some fluviometric stations. Calibration, and validation were performed considering the flow data measured at a station located in close proximity to the mouth of the river. The comparison between the numerical and measured data, and also from a statistical point of view, was quite satisfactory. A further important outcome was the capability to highlight any differences between the numerical flow-rate balance carried out on the basis of the contributions of all known sources and the values actually measured. This characteristic of the applied modeling allows better calibration and verification not only of the effectiveness of much more simplified approaches, but also the entire network of measurement stations and could suggest the need for a more in-depth exploration of the territory in question. It would also enable the eventual identification of further hidden supplies of water inventory from underground sources and, accordingly, to enlarge the hydrographic and hydrogeological border of the basin under study. Moreover, the parallel computing platform would also allow the development of effective early warning systems, for example, of floods.
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spelling doaj.art-bd9c776a1fb34a7c9fae5c5602277fe52023-11-23T15:45:04ZengMDPI AGWater2073-44412022-01-0114223410.3390/w14020234Surface Water Flow Balance of a River Basin Using a Shallow Water Approach and GPU Parallel Computing—Pescara River (Italy) as Test CaseAntonio Pasculli0Roberto Longo1Nicola Sciarra2Carmine Di Nucci3Department of Engineering and Geology (INGEO), University of “G. D’Annunzio”, Chieti-Pescara, 66013 Chieti, ItalyDepartment of Engineering and Geology (INGEO), University of “G. D’Annunzio”, Chieti-Pescara, 66013 Chieti, ItalyDepartment of Engineering and Geology (INGEO), University of “G. D’Annunzio”, Chieti-Pescara, 66013 Chieti, ItalyAcademy of Sciences of Abruzzo Region, Via Santa Giusta 23, 67100 L’Aquila, ItalyThe analysis and prevention of hydrogeological risks plays a very important role and, currently, much attention is paid to advanced numerical models that correspond more to physical reality and whose aim is to reproduce complex environmental phenomena even for long times and on large spatial scales. Within this context, the feasibility of performing an effective balance of surface water flow relating to several months was explored, based on accurate hydraulic and mathematical-numerical models applied to a system at the scale of a hydrographic basin. To pursue this target, a 2D Riemann–Godunov shallow-water approach, solved in parallel on a graphical processing unit (GPU), able to drastically reduce calculation time, and implemented into the RiverFlow2D code (2017 version), was selected. Infiltration and evapotranspiration were included but in a simplified way, in order to face the calibration and validation simulations and because, despite the parallel approach, it is very demanding even for the computer time requirement. As a test case the Pescara river basin, located in Abruzzo, Central Italy, covering an area of 813 km<sup>2</sup> and well representative of a typical medium-sized basin, was selected. The topography was described by a 10 <i>×</i> 10 m digital terrain model (DTM), covered by about 1,700,000 triangular elements, equipped with 11 rain gauges, distributed over the entire area, with some hydrometers and some fluviometric stations. Calibration, and validation were performed considering the flow data measured at a station located in close proximity to the mouth of the river. The comparison between the numerical and measured data, and also from a statistical point of view, was quite satisfactory. A further important outcome was the capability to highlight any differences between the numerical flow-rate balance carried out on the basis of the contributions of all known sources and the values actually measured. This characteristic of the applied modeling allows better calibration and verification not only of the effectiveness of much more simplified approaches, but also the entire network of measurement stations and could suggest the need for a more in-depth exploration of the territory in question. It would also enable the eventual identification of further hidden supplies of water inventory from underground sources and, accordingly, to enlarge the hydrographic and hydrogeological border of the basin under study. Moreover, the parallel computing platform would also allow the development of effective early warning systems, for example, of floods.https://www.mdpi.com/2073-4441/14/2/234shallow water modelingbasin hydrological balancefinite volume methodhydrological riskparallel modeling GPU
spellingShingle Antonio Pasculli
Roberto Longo
Nicola Sciarra
Carmine Di Nucci
Surface Water Flow Balance of a River Basin Using a Shallow Water Approach and GPU Parallel Computing—Pescara River (Italy) as Test Case
Water
shallow water modeling
basin hydrological balance
finite volume method
hydrological risk
parallel modeling GPU
title Surface Water Flow Balance of a River Basin Using a Shallow Water Approach and GPU Parallel Computing—Pescara River (Italy) as Test Case
title_full Surface Water Flow Balance of a River Basin Using a Shallow Water Approach and GPU Parallel Computing—Pescara River (Italy) as Test Case
title_fullStr Surface Water Flow Balance of a River Basin Using a Shallow Water Approach and GPU Parallel Computing—Pescara River (Italy) as Test Case
title_full_unstemmed Surface Water Flow Balance of a River Basin Using a Shallow Water Approach and GPU Parallel Computing—Pescara River (Italy) as Test Case
title_short Surface Water Flow Balance of a River Basin Using a Shallow Water Approach and GPU Parallel Computing—Pescara River (Italy) as Test Case
title_sort surface water flow balance of a river basin using a shallow water approach and gpu parallel computing pescara river italy as test case
topic shallow water modeling
basin hydrological balance
finite volume method
hydrological risk
parallel modeling GPU
url https://www.mdpi.com/2073-4441/14/2/234
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