Sensitivity analysis of hydrological model parameters based on improved Morris method with the double-Latin hypercube sampling

Li, Delong; Ju, Qin; Jiang, Peng; Huang, Ping; Xu, Xiaohua; Wang, Qin; Hao, Zhenchun; Zhang, Yueguan

doi:10.2166/nh.2023.109

Cited by 5 publications

(2 citation statements)

References 12 publications

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“…Model sensitivity analysis is helpful in assessing how the different calibrated parameters are effective within the model and to which parameters the hydrological model outputs are sensitive [68][69][70]. In this study, we used a single one-at-a-time (OAT) approach to assess model sensitivity, where each parameter is updated within the range of ±25% of its optimal value by increments of ±5%.…”

Section: Sensitivity Analysismentioning

confidence: 99%

Daily Simulation of the Rainfall–Runoff Relationship in the Sirba River Basin in West Africa: Insights from the HEC-HMS Model

Souley Tangam,

Yonaba,

Niang

et al. 2024

Hydrology

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This study focuses on the Sirba River Basin (SRB), a transboundary West African catchment of 38,950 km2 shared by Burkina Faso and Niger, which contributes to flooding downstream in Niamey (Niger). The study uses the HEC-HMS hydrological model to explore the dynamics of the daily rainfall–runoff relationship over the period 2006–2020. The model is calibrated using observed rainfall at 13 meteorological stations within the river basin and observed discharges at the Garbey Kourou hydrometric station outlet. Two types of simulation are compared: (i) a continuous simulation (CS) over the period 2006–2020 and (ii) an event-based simulation (ES) using selected major flood events in 2010, 2012, 2013, 2015 and 2020. The results showed satisfactory model performance under both modeling schemes (R2 = 0.84–0.87 for CS and R2 = 0.94–0.98 for ES), with a superior performance of ES over CS. Also, significant differences in the distribution of calibrated model parameters for the percent impervious and the attenuation flood wave factor were observed. A sensitivity analysis revealed that the curve number, initial abstraction, lag time and routing time factors were influential on the model outputs. The study therefore underscores the model’s robustness and contributes crucial insights for flood control management and infrastructure planning in the SRB.

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Section: Sensitivity Analysismentioning

confidence: 99%

Daily Simulation of the Rainfall–Runoff Relationship in the Sirba River Basin in West Africa: Insights from the HEC-HMS Model

Souley Tangam,

Yonaba,

Niang

et al. 2024

Hydrology

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“…Qualitative analysis is to study the relative size of response of different parameters to output variables, such as Morris method, Delta Test method, etc. Quantitative analysis can obtain the contribution rate of different parameters to the output variables, such as Sobol method and EFAST method [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Sensitivity analysis of underwater launch based on Morris method

Xie,

Cheng,

Chang

et al. 2024

E3S Web Conf.

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The discharge velocity, pressure difference and acceleration of underwater launch performance are affected by many factors, including depth, sailing speed, burning rate, water temperature, density and other operating parameters. The existing underwater launch sensitivity analysis is a local sensitivity qualitative analysis based on single-step perturbation analysis, which can only investigate the influence of a single uncertain factor on the model results in a small range. In this paper, based on the underwater launch model under multi-factor coupling, 10 input parameters were selected to calculate the multi-factor sensitivity of the underwater launch model based on the three objectives of velocity, pressure difference and acceleration at the time of discharge, and the Morris global sensitivity analysis method was used to calculate the sensitivity of the underwater launch model, and the sensitivity of the 10 input parameters to the model results was sorted. The results show that the five input parameters of burning rate, depth, propellant temperature, density and water temperature have the highest sensitivity to velocity, pressure difference and acceleration, and the sensitivity order is slightly different. The influence of water temperature on the three targets is almost evenly distributed in the range of values, and the other parameters have different sensitive ranges for different targets.

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