Large-Scale Hydrological Modelling of the Upper Paraná River Basin

Rafee, Sameh Adib Abou; Uvo, Cíntia Bertacchi; Martins, Jorge Alberto; Domingues, Leonardo Moreno; Rudke, Anderson Paulo; Fujita, Thais; Freitas, Edmílson Dias de

doi:10.3390/w11050882

Cited by 33 publications

(13 citation statements)

References 42 publications

(52 reference statements)

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“…The Paraná River basin has an area of 876,600 km 2 , equivalent to 10.3% of Brazil's total area (Secretaria de Recursos Hídricos do Ministério do Meio Ambiente, ), and is the country's third largest in size (Abou Rafee et al ., ). This basin comprises the Brazilian stretch of one of the hydrographic units of the Rio de la Plata Basin and covers the most economically relevant states of Brazil: Goiás, Mato Grosso do Sul, Minas Gerais, Paraná, São Paulo, and Santa Catarina (Figure ).…”

Section: Methodsmentioning

confidence: 97%

Stationary and non‐stationary detection of extreme precipitation events and trends of average precipitation from 1980 to 2010 in the Paraná River basin, Brazil

Xavier

Rudke

Fujita

et al. 2019

Intl Journal of Climatology

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The main objective of this study was to investigate the trends on average and extreme events in time series of daily precipitation from 1980 to 2010 in the Paraná River basin, Brazil. The nonparametric Mann–Kendall test was applied to detect monotonic trend in the precipitation series. The occurrence of extreme values was analysed based on three generalized extreme values (GEV) models: Model 1 (stationary), Model 2 (non‐stationary for location parameter), and Model 3 (non‐stationary for location and scale parameters). The GEV parameters were estimated by the Generalized Maximum Likelihood method (GMLE) and for the non‐stationary models, the parameters were estimated as linear functions of time. To choose the most suitable model, the maximum likelihood ratio test (D) was used. From the results observed at the monthly scale, it was possible to infer that the months with the highest probability of an extreme weather event occurrence are February (climates Aw and Cfa), July (Cfa and Cfb), and October (Aw, Cfa, and Cfb). Approximately 90% of the 1,112 stations presented no trend regarding the GEV parameters. The non‐stationarity showed by other stations (Models 2 and 3) might be associated with several factors, such as the alteration of land use due to the north expansion of the agricultural border of the Paraná River basin.

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Section: Methodsmentioning

confidence: 97%

Stationary and non‐stationary detection of extreme precipitation events and trends of average precipitation from 1980 to 2010 in the Paraná River basin, Brazil

Xavier

Rudke

Fujita

et al. 2019

Intl Journal of Climatology

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“…Some questions raised (Herath and Dutta, 2000) were: How do we model large basins, how can we incorporate land use changes as a dynamic processes linked to water resources, what techniques can we use to derive physical watershed characteristics, what different types of models are required for modeling diverse hydrological processes, what are the difficulties in studying large basins? The significance of large basins in any region is also obvious of their contribution to provide water resources the the region indicating them as river basin production systems (Abou Rafee et al, 2019;Gawne et al, 2018;Liersch et al, 2019). The case of Java island, the three largest river basins out of hundreds of other major basins occupied areas approximately 40 percents of the island.…”

Section: Recent Developments In Hydrological Modelingmentioning

confidence: 99%

Non-linear Routing Scheme at Grid Cell Level for Large Scale Hydrologic Models: A Review

Pawitan

Taufik

2021

J.Agromet

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New tools and concepts in the form of mathematical models, remote sensing and Geographic Information System (GIS), communication and telemetering have been developed for the complex hydrologic systems that permit a different analysis of processes and allow watershed to be considered as an integrated planning and management unit. Hydrological characteristics can be generated through spatial analysis, and ready for input into a distributed hydrologic models to define adequately the hydrological response of a watershed that can be related back to the specific environmental, climatic, and geomorphic conditions. In the present paper, some recent development in hydrologic modeling will be reviewed with recognition of the role of horizontal routing scheme in large scale hydrologic modeling. Among others, these developments indicated the needs of alternative horizontal routing models at grid scale level that can be coupled to land surface parameterization schemes that presently still employed the linear routing model. Non-linear routing scheme will be presented and discussed in this paper as possible extension.

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“…RP and RC were calculated using the recession constant method [37] and also used in the model. Many meteorological variables have been considered in large-scale hydrological models and are applicable for long-term averages (e.g., mean monthly or annual discharges), although exceptions exist [47][48][49]. Hence, meteorological variables can play an important role during the long-term continuous simulation of a watershed.…”

Section: Model Set-upmentioning

confidence: 99%

The Role of the Spatial Distribution of Radar Rainfall on Hydrological Modeling for an Urbanized River Basin in Japan

Shakti

Nakatani

Misumi

2019

Water

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Recently, the use of gridded rainfall data with high spatial resolutions in hydrological applications has greatly increased. Various types of radar rainfall data with varying spatial resolutions are available in different countries worldwide. As a result of the variety in spatial resolutions of available radar rainfall data, the hydrological community faces the challenge of selecting radar rainfall data with an appropriate spatial resolution for hydrological applications. In this study, we consider the impact of the spatial resolution of radar rainfall on simulated river runoff to better understand the impact of radar resolution on hydrological applications. Very high-resolution polarimetric radar rainfall (XRAIN) data are used as input for the Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) to simulate runoff from the Tsurumi River Basin, Japan. A total of 20 independent rainfall events from 2012–2015 were selected and categorized into isolated/convective and widespread/stratiform events based on their distribution patterns. First, the hydrological model was established with basin and model parameters that were optimized for each individual rainfall event; then, the XRAIN data were rescaled at various spatial resolutions to be used as input for the model. Finally, we conducted a statistical analysis of the simulated results to determine the optimum spatial resolution for radar rainfall data used in hydrological modeling. Our results suggest that the hydrological response was more sensitive to isolated or convective rainfall data than it was to widespread rain events, which are best simulated at ≤1 km and ≤5 km, respectively; these results are applicable in all sub-basins of the Tsurumi River Basin, except at the river outlet.

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Large-Scale Hydrological Modelling of the Upper Paraná River Basin

Cited by 33 publications

References 42 publications

Stationary and non‐stationary detection of extreme precipitation events and trends of average precipitation from 1980 to 2010 in the Paraná River basin, Brazil

Stationary and non‐stationary detection of extreme precipitation events and trends of average precipitation from 1980 to 2010 in the Paraná River basin, Brazil

Non-linear Routing Scheme at Grid Cell Level for Large Scale Hydrologic Models: A Review

The Role of the Spatial Distribution of Radar Rainfall on Hydrological Modeling for an Urbanized River Basin in Japan

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