Ranking Sensitive Calibrating Parameters of UBC Watershed Model

Usman Ali Naeem,Habib-ur-Rehman,Hashim Nisar Hashmi,Abdul Sattar Shakir,Abdul Razzaq Ghumman,Muhammad Ali Shamim 대한토목학회 2015 KSCE JOURNAL OF CIVIL ENGINEERING Vol.19 No.5

Almost in all hydrological models, calibrating parameters are tuned to best match the simulated results with the observed. In the present study sensitivity analysis was carried on the fifteen calibrating parameters of University of British Columbia Watershed Model (UBCWM). The study focuses to impart information to the modelers while calibrating UBCWM. To achieve the objectives of the study, UBC Watershed Model was applied on Chitral watershed in Pakistan. UBC Watershed Model is a semi distributed Hydrological model which divides the entire watershed in several elevation bands. The model was calibrated for the year 2006 with the coefficient of efficiency as well as the coefficient of determination equal to 0.94. The numerical values of the calibrating parameters were changed by increasing 20% and then by decreasing 20% of the standard calibrated values one by one. Sensitivity of the model was evaluated by computing the Absolute Sensitivity Index for each parameter. The sensitivity analysis results showed that the P0SREPO as the most sensitive parameter with 3.31525 Absolute Sensitivity Index (ASI) whereas C0IMPA found to be least sensitive giving a value of 0.0452 as Absolute Sensitivity Index (ASI). The logical trends in the results of sensitivity analysis show the robustness of the model.

분포형 모형에서의 유출 매개변수 추정에 관한 연구

이재준,이성호,곽창재 한국방재학회 2016 한국방재학회논문집 Vol.16 No.3

The purpose of this study is to estimate some runoff parameters for using COBRA model which is distributed rainfall-runoff model. COBRA model has been developed to estimate the runoff of composite urban basin in 2012. Some runoff parameter which are total porosity, residual water contents, and pore-size distributions are analyzed for the validity about the their estimates. The Guryang watershed of Yongdam test bed is selected as experimental region. Runoff hydrograph between observed one and simulated one which is used mean value of runoff parameters are compared for 8 historic rainfall-runoff events. It is shown that simulated one is underestimated in comparison with the observed one in terms of peak discharge in this case. Therefore an additional sensitivity analysis is fulfilled to seize the sensitivity of some runoff parameters. The range of runoff parameters is covered from 75% to -75% of their mean values. The COBRA model is considered to be drawn properly as following results that are Total porosity and pore-size distributions were shown in inverse relation to the peak discharge, and otherwise residual water contents was shown in proportional relation. By applying the sensitivity analysis is classified according to the parameters sets in terms of 6 kinds of soil drainage classes in Guryang watershed, a default value of some runoff parameters is proposed for using COBRA model. The fitness of runoff hydrograph between observed one and newly simulated one was examined to be higher than that of before correction in accuracy. 본 연구에서는 산지와 도시가 혼재된 복합유역의 유출분석을 위해 2012년 개발된 분포형 강우-유출 모형인 COBRA 모형을 사용하여 유출 매개변수 추정에 관한 연구를 진행하였다. 용담 시험유역의 구량천 유역을 대상유역으로 선정하여 공극률, 잔류함수비, 공극분포와 같은 유출 매개변수 추정에 대한 타당성 분석을 실시하였다. 유출 매개변수의 평균값을 사용하여 8개 강우사상에 대한 관측 유출수의 첨두유량이 약간 작게 산정되는 것으로 나타났다. 따라서 공극률, 잔류함수비와 공극분포의 민감도 분석을 실시하였고 민감도 분석을 위한 유출 매개변수의 범위는 평균값의 75%에서 -75%의 범위로 설정하였다. 민감도 분석 결과 공극률과 공극분포는 첨두유량과 반비례관계이고 잔류함수비는 첨두유량과 비례관계인 것으로 분석되어 COBRA 모형의 결과가 정상적으로 도출되는 것으로 검토되었다. 민감도 분석 결과를 바탕으로 구량천 유역의 6가지 배수등급에 따라 매개변수의 값을 분류하였고 COBRA 모형에 유출 매개변수의 제안된 값을 적용하였으며, 관측 유출수문곡선과 매개변수 설정 후 유출수문곡선의 적합도 분석결과 매개변수 설정 전에 비해 적합도가 높은 것으로 검토되었다.

수공구조물의 적정설계를 위한 유출모형 매개변수의 민감도 분석

이정훈,김문모,여운광,Lee. Jung-Hoon,Kim. Mun-Mo,Yeo. Woon-Kwang 한국방재학회 2008 한국방재학회 학술발표대회논문집 Vol.2008 No.1

Currently, the increased run-off and the shortened arrival time are one of the causes of the city environmental disasters in urbanization. Therefore, it is necessary to properly design the hydrologic structures, but it is very difficult to forecast the values necessary to design from the planning stage. Moreover, as the parameter is changed due to the urban development, it is difficult not only to analyze the run-off influences but also to find the related studies and literatures. The purpose of this study is to utilize the results as the important basic data of the hydrologic structures, its proper design and run-off influences through the sensibility analysis of the model parameter variables. In this study, the absolute and relative sensibility analysis method were used to find out the correlation through the sensibility analysis of the topology and hydrology parameters. Especially, in this study, the changes in the run-off amount and volume were calculated according to increase/decrease in CN, the coefficient of discharge, and the empirical formula is prepared and proposed through the regressive analysis among the parameters. In the meantime, the parameter sensibility analysis was performed through the simulation HEC-HMS that is used and available in Korea. From the results of this study, it was found that the run-off amount is increased about by 10% when the CN value is increased by 5% before and after the development through the HEC-HMS simulation and data analysis. As long as there will be additional data collection analysis and result verification, and continuous further studies to find out the parameters proper to the domestic circumstances, it is expected to considerably contribute to the proper design of the hydrologic structures with respect to the ungauged basin.

Modeling metal-sediment interaction processes: Parameter sensitivity assessment and uncertainty analysis

Cho, Eunju,Arhonditsis, George B.,Khim, Jeehyeong,Chung, Sewoong,Heo, Tae-Young Elsevier 2016 Environmental modelling & software Vol.80 No.-

<P><B>Abstract</B></P> <P>Sensitivity and uncertainty analysis of contaminant fate and transport modeling have received considerable attention in the literature. In this study, our objective is to elucidate the uncertainty pertaining to micropollutant modeling in the sediment-water column interface. Our sensitivity analysis suggests that not only partitioning coefficients of metals but also critical stress values for cohesive sediment affect greatly the predictions of suspended sediment and metal concentrations. Bayesian Monte Carlo is used to quantify the propagation of parameter uncertainty through the model and obtain the posterior parameter probabilities. The delineation of periods related to different river flow regimes allowed optimizing the characterization of cohesive sediment parameters and effectively reducing the overall model uncertainty. We conclude by offering prescriptive guidelines about how Bayesian inference techniques can be integrated with contaminant modeling and improve the methodological foundation of uncertainty analysis.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Sensitivity and uncertainty analysis was performed for sediment-metal modeling. </LI> <LI> Suspended sediment predictions are sensitive to critical erosion stress. </LI> <LI> Sediment bed-water partitioning coefficient is critical for metal predictions. </LI> <LI> River flow dynamics affect contaminant fate and model parameter sensitivity. </LI> <LI> Strategies to improve uncertainty analysis of sediment-metal modeling are discussed. </LI> </UL> </P>

Sensitivity Analysis of the Model Parameters for an Anaerobic Fluidized Bed Bioreactor

석종혁 한국수처리학회 2019 한국수처리학회지 Vol.27 No.1

Sensitivity analysis for the model parameters determined from the experimental data of the propylene glycol biomethanization process was presented. The mathematical model developed was assumed as a completely mixed stirred tank reactor(CMSTR) and composed of 13 differential equations associated with 18 parameters. Basic model parameters determined from an initial experimental data set using one bioreactor were then verified with the results from a second bioreactor. Unknown parameters were then estimated in a sequential manner by means of an optimization technique. The computational effort can be significantly reduced by obtaining the most sensitive parameter combinations, where the eigenvector corresponding to the largest eigenvalue indicates the most sensitive direction. This parameter combination technique was successfully applied to the sensitivity analysis of the CMSTR model parameters and the results were verified using the novel technique developed for this purpose. The result indicates that parameters related to the propionate significantly influence the model behavior. In general, any decay coefficients are shown to be insignificant.

Sensitivity analysis for parameter classification of energy balance-integrated single particle model for battery cells

홍창범,오세규,김연수 한국화학공학회 2022 Korean Journal of Chemical Engineering Vol.39 No.6

With the increasing use of electric vehicles (EVs), there is a growing interest in the thermal management ofEVs. In this study, we first reduced the computational complexity of single particle model (SPM) for the battery cell byintroducing a 4th order approximation for Li-ion concentration in the solid phase. In addition, by integrating it with anenergy balance, the constructed model can calculate the battery temperature along with the terminal voltage and stateof charge. To develop a model compatible with the experimental data requires parameter estimation. However, the estimationaccuracy for each parameter depends on its sensitivity. We investigated the influence of 16 parameters on themeasured data under general experimental conditions (constant C-rate discharge) through simulations and sensitivityanalysis. We classified the radius of the particle, total active surface areas, electrode maximum concentration, and a heattransfer coefficient as dominant parameters. When dominant parameters were estimated using the virtual experimentaldata, the percent error was smaller than 3.1%. For the parameters with minor influence, the estimation error waslarge even with the excellent agreement of the experimental data. We confirmed which parameter could be estimatedusing the C-rate experimental data accurately and which parameter should be estimated with additional experiments.

가중유출수질지표를 이용한 활성오니공정모델의 민감도 분석과 매개변수 보정

이원영(Won Young Lee),김민한(Min Han Kim),김영황(Young Whang Kim),이인범(In-Beum Lee),유창규(Chang Kyoo Yoo) 제어로봇시스템학회 2008 제어·로봇·시스템학회 논문지 Vol.14 No.11

Many modeling and calibration methods have been developed to analyze and design the biological wastewater treatment process. For the systematic use of activated sludge model (ASM) in a real treatment process, a most important step in this usage is a calibration which can find a key parameter set of ASM, which depends on the microorganism communities and the process conditions of the plants. In this paper, a standardized calibration protocol of the ASM model is developed. First, a weighted effluent quality index(WEQI) is suggested for a calibration protocol. Second, the most sensitive parameter set is determined by a sensitive analysis based on WEQI and then a parameter optimization method are used for a systematic calibration of key parameters. The proposed method is applied to a calibration problems of the single carbon removal process. The results of the sensitivity analysis and parameter estimation based on a WEQI shows a quite reasonable parameter set and precisely estimated parameters, which can improve the quality and the efficiency of the modeling and the prediction of ASM model. Moreover, it can be used for a calibration scheme of other biological processes, such as sequence batch reactor, anaerobic digestion process with a dedicated methodology.

저류함수모형의 매개변수 보정 및 추정

김범준(Kim Bum Jun),곽재원(Kawk Jae Won),이진희(Lee Jin Hee),김형수(Kim Hung Soo) 대한토목학회 2008 대한토목학회논문집 B Vol.28 No.1B

홍수예보는 홍수로 인한 인명과 재산피해를 저감하기 위한 비구조적 대책으로 그 정확성은 매우 중요한 요소이다. 그러나 우리나라 홍수예보에서 주로 쓰이는 저류함수모형은 그 적용에 있어서 매개변수의 결정이 매우 중요하지만 이를 결정하는 것은 매우 어렵다. 그래서 현재에는 주로 경험식을 이용하거나 수문 기술자의 판단에 의해 보정이 이루어지고 있는 실정이다. 이에 본 연구에서는 저류함수모형 매개변수의 특성을 알고 범위를 설정하기 위해서 민감도 분석을 수행하였으며, 보정을 위해 다양한 보정방법과 목적함수를 적용하여 그 성능을 평가하였다. 또한 유역에 맞는 매개변수를 결정하기 위한 방법을 제시하고, 결정된 매개변수를 이용하여 검증홍수사상에 대해 검증을 수행하였다. 본 연구의 결과와 기존에 제시된 매개변수를 사용한 결과를 비교하였다. 기존에 제시된 대상유역의 저류함수모형 매개변수도 좋은 결과를 나타내었으나, 새롭게 추정된 매개변수는 보다 더 좋은 결과를 도출하였다. Flood forecasting is a very important tool as one of nonstructural measures for reduction of flood damages in life and property and its accuracy is also an important factor. However, when we apply the Storage Function Model(SFM) which is mainly used for the flood forecasting system in Korea, the determination of the parameters is very important but it is difficult. So, the parameters have been calibrated by using an empirical formulas and judgement of hydrologist. Hence, in this study we perform the sensitivity analysis to understand the parameter characteristics and establish the ranges of parameters of the SFM. Also we do the parameter calibration by using the optimization techniques and objective functions, and evaluate their performances. Especially, we suggest a method to determine proper parameters by using a objective function which can be obtained from flood events. So, we use the suggested method for parameter estimation and compare the estimated parameters with the previously reported parameters. As a result of the application, the estimated parameters by the suggested method showed better than them from the previously reported parameters.

Streamflow, stomata, and soil pits: Sources of inference for complex models with fast, robust uncertainty quantification

Dwelle, M. Chase,Kim, Jongho,Sargsyan, Khachik,Ivanov, Valeriy Y. C.M.L. Publications 2019 ADVANCES IN WATER RESOURCES Vol. No.

<P><B>Abstract</B></P> <P>The scale and complexity of environmental and earth systems introduce an array of uncertainties that need to be systematically addressed. In numerical modeling, the ever-increasing complexity of representation of these systems confounds our ability to resolve relevant uncertainties. Specifically, the numerical representation of the governing processes involve many inputs and parameters that have been traditionally treated as deterministic. Considering them as uncertain introduces a large computational burden, stemming from the requirement of a prohibitive number of model simulations. Furthermore, within hydrology, most catchments are sparsely monitored, and there are limited, heterogeneous types of data available to confirm the model’s behavior. Here we present a blueprint of a general approach to uncertainty quantification for complex hydrologic models, taking advantage of recent methodological developments. We rely on polynomial chaos machinery to construct accurate surrogates that can be efficiently sampled for the ecohydrologic model tRIBS-VEGGIE to mimic its behavior with respect to a selected set of quantities of interest. The use of the Bayesian compressive sensing technique allows for fewer evaluations of the computationally expensive tRIBS-VEGGIE. The approach enables inference of model parameters using a set of observed hydrologic quantities including stream discharge, water table depth, evapotranspiration, and soil moisture from the Asu experimental catchment near Manaus, Brazil. The results demonstrate the flexibility of the framework for hydrologic inference in watersheds with sparse, irregular observations of varying accuracy. Significant computational savings imply that problems of greater computational complexity and dimension can be addressed using accurate, computationally cheap surrogates for complex hydrologic models. This will ultimately yield probabilistic representation of model behavior, robust parameter inference, and sensitivity analysis without the need for greater investment in computational resources.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A general approach to uncertainty quantification with a complex, process-rich model. </LI> <LI> Construction of efficient surrogate models with Bayesian compressive sensing. </LI> <LI> Robust parametric inference using heterogeneous sources of process-scale data. </LI> <LI> Simultaneous characterization of sensitivity of hydrologic outputs to uncertain variables. </LI> </UL> </P>

변화민감도 문항 모수의 능력 검사에서의 적용 가능성 탐색

이소라(Sora Lee) 한국교육평가학회 2021 교육평가연구 Vol.34 No.2

학생 능력의 변화를 측정하는 검사를 개발할 때, 문항이 변화/성장을 얼마나 잘 감지하는지 확인하는 것은 검사 목적의 타당성을 높이기 위해 중요하다. 본 연구는 종단 데이터에 적용된 다차원 문항반응모형의 모수가 변화에 민감한 정도를 나타낼 수 있음을 소개하고, 모수 추정의 정확성을 살펴보았다. 구체적으로, 1년의 시간 간격을 두고 시행된 능력검사 데이터를 이용하여 변별도와 변화에 민감한 정도를 나타내는 모수가 별개의 특성임을 확인하였다. 또한 세 가지 조건(요인 간 상관, 기울기 모수 간 차이, 피험자 수)을 고려한 모의 데이터를 생성하여, 두 문항 특성이 안정적으로 분리되어 추정되는지 확인하였다. 연구 결과, 문항 모수는 대체로 안정적으로 추정되었으나, 요인 간 상관이 부적일 때와 사례수가 적을 때는 추정성이 떨어졌다. 두 문항 모수 간의 차이가 클수록 문항 모수의 추정성은 높아지나, 잠재특성 모수의 추정성은 낮아지는 경향이 있었다. When developing test items that measure changes in student abilities over time, it is important to increase the validity of the test objectives to determine how well the items detect changes/growth. In this study, three conditions of the multidimensional item response model (correlation between factors, difference between slope parameters, and the number of subjects) are considered for simulation study by referring to the characteristics of the actual longitudinal ability test data used to grasp how much students have grown at a time interval of one year. First, we introduced that the item parameter of the multi-dimensional item response model can provide information about the degree of sensitivity to ability change, and examined its function through the accuracy of parameter estimation. As a result of the study, the latent trait parameter and the item parameter were generally estimated to be stable, but the accuracy was poor when the correlation between the two latent factors was negatively related and the number of cases was small. The greater the difference between the two slope parameters, the higher the accuracy of the item parameter, but the lower the accuracy of the latent trait parameter.