Theory and preliminary experimental verification of the directional difference of overland flow resistance in distributed hydrological models

Abstract Overland flow is influenced by the spatial variability of the watershed surface and the distribution of vegetation in the process of confluence. Thus, Manning's roughness coefficient, in different directions on the slope, has different values. This causes different effects on the resistance to flow in the downstream direction of each grid cell, affecting the flow distribution among the grid cells of a distributed hydrological model. To show that the spatial variation of the overland vegetation had the effect of directional difference resistance to the overland flow, this study used an indoor fixed-bed test. We used a cylinder to simulate the stems of the vegetation used in the study. We modeled the relationship between Manning's roughness coefficient and flow depth and studied this relationship for three types of vegetation distributed at three different slopes of 0.0%, 0.5%, and 1.0%. The slopes were based on three angles of 30°, 45°, and 90° between the vegetation rows and flow. The results showed that the resistance of overland flow had directional differences caused by the spatial variability of the vegetation distribution. At the same slope and flow depth, Manning's roughness coefficient decreased as the angle between flow and vegetation rows increased. At the same slope, the angle between flow and vegetation rows and Manning's roughness coefficient increased as flow depth increased. The slope did not affect the law of Manning's roughness coefficient with changes in the angle between flow and vegetation rows.

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Automated calibration of a two-dimensional overland flow model by estimating Manning's roughness coefficient using genetic algorithm

Journal of Hydroinformatics ◽

10.2166/hydro.2017.110 ◽

2017 ◽

Vol 20 (2) ◽

pp. 440-456

Author(s):

J. Drisya ◽

D. Sathish Kumar

Keyword(s):

Genetic Algorithm ◽

Flow Model ◽

Overland Flow ◽

Fitness Function ◽

Roughness Coefficient ◽

Model Parameters ◽

Automatic Data ◽

Automated Calibration ◽

Manning’S Roughness Coefficient ◽

Overland Flow Model

Abstract Calibration is an important phase in the hydrological modelling process. In this study, an automated calibration framework is developed for estimating Manning's roughness coefficient. The calibration process is formulated as an optimization problem and solved using a genetic algorithm (GA). A heuristic search procedure using GA is developed by including runoff simulation process and evaluating the fitness function by comparing the experimental results. The model is calibrated and validated using datasets of Watershed Experimentation System. A loosely coupled architecture is followed with an interface program to enable automatic data transfer between overland flow model and GA. Single objective GA optimization with minimizing percentage bias, root mean square error and maximizing Nash–Sutcliffe efficiency is integrated with the model scheme. Trade-offs are observed between the different objectives and no single set of the parameter is able to optimize all objectives simultaneously. Hence, multi-objective GA using pooled and balanced aggregated function statistic are used along with the model. The results indicate that the solutions on the Pareto-front are equally good with respect to one objective, but may not be suitable regarding other objectives. The present technique can be applied to calibrate the hydrological model parameters.

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Using DEM to quantify spatial variability of soil storage capacity: a semi-distributed hydrological model for Northern China

Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05. ◽

10.1109/igarss.2005.1525902 ◽

2005 ◽

Author(s):

Zhao Qiang ◽

Gong Huili ◽

Deng Wei ◽

Wang Shangyi ◽

ZhaoWenji ◽

...

Keyword(s):

Spatial Variability ◽

Hydrological Model ◽

Storage Capacity ◽

Northern China ◽

Distributed Hydrological Model ◽

Soil Storage ◽

Soil Storage Capacity

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Overland Flow Resistance Law under Sparse Stem Vegetation Coverage

Water ◽

10.3390/w13121657 ◽

2021 ◽

Vol 13 (12) ◽

pp. 1657

Author(s):

Jingzhou Zhang ◽

Shengtang Zhang ◽

Si Chen ◽

Ming Liu ◽

Xuefeng Xu ◽

...

Keyword(s):

Flow Resistance ◽

Overland Flow ◽

Vegetation Coverage ◽

Dominant Factor ◽

Roughness Coefficient ◽

Hydraulic Parameters ◽

Slope Condition ◽

Manning Roughness ◽

The Relationship ◽

Manning Roughness Coefficient

To explore the characteristics of overland flow resistance under the condition of sparse vegetative stem coverage and improve the basic theoretical research of overland flow, the resistance characteristics of overland flow were systematically investigated under four slope gradients (S), seven flow discharges (Q), and six degrees of vegetation coverage (Cr). The results show that the Manning roughness coefficient (n) changes with the ratio of water depth to vegetation height (h/hv) while the Reynolds number (Re), Froude number (Fr), and slope (S) are closely related to vegetation coverage. Meanwhile, h/hv, Re, and Cr have strong positive correlations with n, while Fr and S have strong negative correlations with n. Through data regression analysis, a power function relationship between n and hydraulic parameters was observed and sensitivity analysis was performed. It was concluded that the relationship between n and h/hv, Re, Cr, Q, and S shows the same law; in particular, for sparse stem vegetation coverage, Cr is the dominant factor affecting overland flow resistance under zero slope condition, while Cr is no longer the first dominant factor affecting overland flow resistance under non-zero slope condition. In the relationship between n and Fr, Cr has the least effect on overland flow resistance. This indicates that when Manning roughness coefficient is correlated with different hydraulic parameters, the same vegetation coverage has different effects on overland flow resistance. Therefore, it is necessary to study overland flow resistance under the condition of sparse stalk vegetation coverage.

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Coupling ensemble weather predictions based on TIGGE database with Grid-Xinanjiang model for flood forecast

Advances in Geosciences ◽

10.5194/adgeo-29-61-2011 ◽

2011 ◽

Vol 29 ◽

pp. 61-67 ◽

Cited By ~ 35

Author(s):

H.-J. Bao ◽

L.-N. Zhao ◽

Y. He ◽

Z.-J. Li ◽

F. Wetterhall ◽

...

Keyword(s):

Weather Prediction ◽

Grid Cell ◽

Flood Forecasting ◽

False Alarms ◽

Flood Forecast ◽

Distributed Hydrological Model ◽

Xinanjiang Model ◽

Numerical Weather ◽

Number Of False Alarms ◽

Promising Tool

Abstract. The incorporation of numerical weather predictions (NWP) into a flood forecasting system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and lead to a high number of false alarms. The availability of global ensemble numerical weather prediction systems through the THORPEX Interactive Grand Global Ensemble' (TIGGE) offers a new opportunity for flood forecast. The Grid-Xinanjiang distributed hydrological model, which is based on the Xinanjiang model theory and the topographical information of each grid cell extracted from the Digital Elevation Model (DEM), is coupled with ensemble weather predictions based on the TIGGE database (CMC, CMA, ECWMF, UKMO, NCEP) for flood forecast. This paper presents a case study using the coupled flood forecasting model on the Xixian catchment (a drainage area of 8826 km2) located in Henan province, China. A probabilistic discharge is provided as the end product of flood forecast. Results show that the association of the Grid-Xinanjiang model and the TIGGE database gives a promising tool for an early warning of flood events several days ahead.

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Manning’s roughness coefficient for the Doce River

RBRH ◽

10.1590/2318-0331.231820180013 ◽

2018 ◽

Vol 23 (0) ◽

Author(s):

Emmanuel Kennedy da Costa Teixeira ◽

Márcia Maria Lara Pinto Coelho ◽

Eber José de Andrade Pinto ◽

Jéssica Guimarães Diniz ◽

Aloysio Portugal Maia Saliba

Keyword(s):

River Flow ◽

Hydraulic Modeling ◽

Roughness Coefficient ◽

Local Approach ◽

Water Courses ◽

Time Variations ◽

The Subject ◽

Manning’S Roughness Coefficient ◽

Doce River ◽

Water Depths

ABSTRACT The Manning’s roughness coefficient is used for various hydraulic modeling. However, the decision on what value to adopt is a complex task, especially when dealing with natural water courses due to the various factors that affect this coefficient. For this reason, most of the studies carried out on the subject adopt a local approach, such as this proposal for the Doce River. Due to the regional importance of this river in Brazil, the objective of this article was to estimate the roughness coefficient of Manning along the river, in order to aid in hydraulic simulations, as well as to discuss the uncertainties and variations associated with this value. For this purpose, information on flow rates and water depths were collected at river flow stations along the river. With this information, the coefficients were calculated using the Manning equation, using the software Canal, and their space-time variations were observed. In addition, it was observed that the uncertainties in flow and depth measurements affect the value of the Manning coefficient in the case studied.

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Calibration of Manning’s roughness in non-instrumented rural basins using a distributed hydrological model

DYNA ◽

10.15446/dyna.v86n210.72506 ◽

2019 ◽

Vol 86 (210) ◽

pp. 164-173

Author(s):

Carlos Andrés Caro Camargo ◽

Oscar Fabián Pacheco Merchán ◽

Hans Paul Sánchez Tueros

Keyword(s):

Hydrological Model ◽

Numerical Study ◽

Research Work ◽

Roughness Coefficient ◽

Distributed Hydrological Model ◽

The Standard Model ◽

Saint Venant Equations ◽

Volume Method ◽

Best Fit ◽

Selection Of

The purpose of this research work was to calibrate the Manning's roughness coefficient in rural non-instrumented basins using a distributed hydrological model. The process consisted of the selection of several basins with vegetal cover of forests and grasslands, and its subsequent experimental numerical study, in which the hydrological response hydrograph of each reference basin was obtained from the HEC-HMS software and the hydrograph to be calibrated was the Iber software, which is a hydrodynamic model based on the two-dimensional Saint Venant equations, solved by the finite volume method. Once the calibration process was carried out, the roughness coefficients with the best fit for each basin were identified with increases in precipitation, identifying the limitations of these values and the standard model used.

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