Sensitivity Analysis to Investigate the Reliability of the Grid-Based Rainfall-Runoff Model

Shin, Mun-Ju; Choi, Yun Seok

doi:10.3390/w10121839

Cited by 9 publications

(5 citation statements)

References 51 publications

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“…We employed the Sobol' method [31] for the sensitivity analysis of the parameters, which is a variance-based quantitative global sensitivity analysis method. The usefulness of this method was demonstrated in various studies (e.g., [32][33][34]). This method quantifies the relative contributions of the individual parameters and parameter interactions to the model output variance by the decomposition of the output variance.…”

Section: Sensitivity Analysis Methodsmentioning

confidence: 98%

Component Combination Test to Investigate Improvement of the IHACRES and GR4J Rainfall–Runoff Models

Shin¹,

Kim

2021

Water

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Rainfall–runoff models are not perfect, and the suitability of a model structure depends on catchment characteristics and data. It is important to investigate the pros and cons of a rainfall–runoff model to improve both its high- and low-flow simulation. The production and routing components of the GR4J and IHACRES models were combined to create two new models. Specifically, the GR_IH model is the combination of the production store of the GR4J model and the routing store of the IHACRES model (vice versa in the IH_GR model). The performances of the new models were compared to those of the GR4J and IHACRES models to determine components improving the performance of the two original models. The suitability of the parameters was investigated with sensitivity analysis using 40 years’ worth of spatiotemporally different data for five catchments in Australia. These five catchments consist of two wet catchments, one intermediate catchment, and two dry catchments. As a result, the effective rainfall production and routing components of the IHACRES model were most suitable for high-flow simulation of wet catchments, and the routing component improved the low-flow simulation of intermediate and one dry catchments. Both effective rainfall production and routing components of the GR4J model were suitable for low-flow simulation of one dry catchment. The routing component of the GR4J model improved the low- and high-flow simulation of wet and dry catchments, respectively, and the effective rainfall production component improved both the high- and low-flow simulations of the intermediate catchment relative to the IHACRES model. This study provides useful information for the improvement of the two models.

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Section: Sensitivity Analysis Methodsmentioning

confidence: 98%

Component Combination Test to Investigate Improvement of the IHACRES and GR4J Rainfall–Runoff Models

Shin¹,

Kim

2021

Water

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“…This analysis has been applied in different levels of watersheds. Shin and Choi [25] found that the size of the catchment makes a difference in the parameter sensitivity between rainfall events.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity Analysis of the Rainfall–Runoff Modeling Parameters in Data-Scarce Urban Catchment

et al. 2020

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Rainfall–runoff phenomena are among the main processes within the hydrological cycle. In urban zones, the increases in imperviousness cause increased runoff, originating floods. It is fundamental to know the sensitivity of parameters in the modeling of an urban basin, which makes the calibration process more efficient by allowing one to focus only on the parameters for which the modeling results are sensitive. This research presents a formal sensitivity analysis of hydrological and hydraulic parameters—absolute–relative, relative–absolute, relative–relative sensitivity and R2—applied to an urban basin. The urban basin of Tuxtla Gutiérrez, Chiapas, in Mexico is an area prone to flooding caused by extreme precipitation events. The basin has little information in which the records (with the same time resolution) of precipitation and hydrometry match. The basin model representing an area of 355.07 km2 was characterized in the Stormwater Management Model (SWMM). The sensitivity analysis was performed for eight hydrological parameters and one hydraulic for two precipitation events and their impact on the depths of the Sabinal River. Based on the analysis, the parameters derived from the analysis that stand out as sensitive are the Manning coefficient of impervious surface and the minimum infiltration speed with R2 > 0.60. The results obtained demonstrate the importance of knowing the sensitivity of the parameters and their selection to perform an adequate calibration.

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“…where X i (i = 1, 2, 3) are uniformly distributed on interval [−π, π]. (11). The definitions of the Sobol' main index and the presented measure have a similar form, thus leading to a certain relationship between them.…”

Section: Numerical Example 3: Ishigami Functionmentioning

confidence: 98%

“…Step 4: Calculate the expectation of all conditional PWMs, i.e., E X i β k X ∼i (Y|X i ) , and ω k i can be easily obtained using Equation (11). After finishing the calculation of ω k i of all variables, the normalized versions also can be evaluated in Equation (12).…”

Section: Double-loop-repeated-set Numerical Estimatorsmentioning

confidence: 99%

“…Besides, there are several mature techniques available to solve the above indices, for instance, Monte Carlo simulation, quasi-Monte Carlo simulation, high-dimensional model representation (HDMR), Markovian integration [6], and the surrogate-assisted method [7,8]. Variance-based global sensitivity measures have been widely applied in various fields such as the spray-drying process [9], heap leaching [10], the rainfall-runoff model [11], and polymeric material [12]. However, the variance is not fully representative of uncertainty, especially in some problems where higher moments have more of an effect.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Global Sensitivity Measure Based on Probability Weighted Moments

Song

Wang

2021

Symmetry

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Global sensitivity analysis (GSA) is a useful tool to evaluate the influence of input variables in the whole distribution range. Variance-based methods and moment-independent methods are widely studied and popular GSA techniques despite their several shortcomings. Since probability weighted moments (PWMs) include more information than classical moments and can be accurately estimated from small samples, a novel global sensitivity measure based on PWMs is proposed. Then, two methods are introduced to estimate the proposed measure, i.e., double-loop-repeated-set numerical estimation and double-loop-single-set numerical estimation. Several numerical and engineering examples are used to show its advantages.

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Sensitivity Analysis to Investigate the Reliability of the Grid-Based Rainfall-Runoff Model

Cited by 9 publications

References 51 publications

Component Combination Test to Investigate Improvement of the IHACRES and GR4J Rainfall–Runoff Models

Component Combination Test to Investigate Improvement of the IHACRES and GR4J Rainfall–Runoff Models

Sensitivity Analysis of the Rainfall–Runoff Modeling Parameters in Data-Scarce Urban Catchment

A Novel Global Sensitivity Measure Based on Probability Weighted Moments

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