Root Zone Water Quality Model Sensitivity Analysis Using Monte Carlo Simulation

Ma, Liwang; Ascough, J. C.; Ahuja, Lajpat R.; Shaffer, M. J.; Hanson, Jon D.; Rojas, K. W.

doi:10.13031/2013.2984

Cited by 89 publications

(18 citation statements)

References 30 publications

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“…The simulated streamflow was then compared to the data observed at 16 stream gauges that are distributed near homogeneously and have no missing data. A sensitivity analysis was used to identify the key parameters required for model calibration [61]. Six parameters, that is, CN2, ALPHA_BF, CH_K2, CH_N2, CANMX, and CH_N1, were selected to calibrate the model.…”

Section: Swat Calibration and Validationmentioning

confidence: 99%

Evaluation of Multi-Satellite Precipitation Products for Streamflow Simulations: A Case Study for the Han River Basin in the Korean Peninsula, East Asia

Jun

2018

Water

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The accuracy and sufficiency of precipitation data play a key role in environmental research and hydrological models. They have a significant effect on the simulation results of hydrological models; therefore, reliable hydrological simulation in data-scarce areas is a challenging task. Advanced techniques can be utilized to improve the accuracy of satellite-derived rainfall data, which can be used to overcome the problem of data scarcity. Our study aims to (1) assess the accuracy of different satellite precipitation products such as Tropical Rainfall Measuring Mission (TRMM 3B42 V7), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), PERSIANN-Climate Data Record (PERSIANN-CDR), and China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) by comparing them with gauged rainfall data; and (2) apply them for runoff simulations for the Han River Basin in South Korea using the SWAT model. Based on the statistical measures, that is, the proportion correct (PC), the probability of detection (POD), the frequency bias index (FBI), the index of agreement (IOA), the root-mean-square-error (RMSE), the mean absolute error (MAE), the coefficient of determination (R 2 ), and the bias, the rainfall data of the TRMM and CMADS show a better accuracy than those of PERSIANN and PERSIANN-CDR when compared to rain gauge measurements. The TRMM and CMADS data capture the spatial rainfall patterns in mountainous areas as well. The streamflow simulated by the SWAT model using ground-based rainfall data agrees well with the observed streamflow with an average Nash-Sutcliffe efficiency (NSE) of 0.68. The four satellite rainfall products were used as inputs in the SWAT model for streamflow simulation and the results were compared. The average R 2 , NSE, and percent bias (PBIAS) show that hydrological models using TRMM (R 2 = 0.54, NSE = 0.49, PBIAS = [−52.70-28.30%]) and CMADS (R 2 = 0.44, NSE = 0.42, PBIAS = [−29.30-41.80%]) data perform better than those utilizing PERSIANN (R 2 = 0.29, NSE = 0.13, PBIAS = [38.10-83.20%]) and PERSIANN-CDR (R 2 = 0.25, NSE = 0.16, PBIAS = [12.70-71.20%]) data. Overall, the results of this study are satisfactory, given that rainfall data obtained from TRMM and CMADS can be used to simulate the streamflow of the Han River Basin with acceptable accuracy. Based on these results, TRMM and CMADS rainfall data play important roles in hydrological simulations and water resource management in the Han River Basin and in other regions with similar climate and topographical characteristics.

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Section: Swat Calibration and Validationmentioning

confidence: 99%

Evaluation of Multi-Satellite Precipitation Products for Streamflow Simulations: A Case Study for the Han River Basin in the Korean Peninsula, East Asia

Jun

2018

Water

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“…Global and local methods may yield different results because of how they select and prioritize parameters (Arnold et al, 2012) and address interactions among parameters (Wang et al, 2005;Tian et al, 2014). It is essential to identify key parameters and define their precision for effective model calibration (Ma et al, 2000;DeJonge et al, 2012). A companion article (Yuan et al, 2015) discusses sensitivity analysis in detail.…”

Section: Parameter Selectionmentioning

confidence: 99%

A Recommended Calibration and Validation Strategy for Hydrologic and Water Quality Models

2015

Trans. ASABE

166

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Hydrologic and water quality (H/WQ) models are widely used to support site-specific environmental assessment, design, planning, and decision making. Calibration and validation (C/V) are fundamental processes used to demonstrate that an H/WQ model can produce suitable results in a particular application. However, the lack of comprehensive guidelines has led to the use of ad hoc, inconsistent, and incomplete C/V processes, which have made it difficult to interpret the myriad of published modeling studies, reduced the utility of many modeling applications, and slowed the advancement of H/WQ modeling. The objective of this article is to provide a generalized structure and process to assist modelers in developing a C/V strategy for H/WQ modeling applications. These best practice recommendations were developed based on an expansive review of the modeling literature, including a special collection of articles on H/WQ model calibration, validation, and use, as well as extensive discussion and debate among the authors. The model C/V recommendations include careful consideration, execution, and documentation of the following elements: (1) goals of model use, (2) data and parameters used in C/V, and (3) model C/V processes. Considerations in element 3 include the warm-up period, C/V strategy complexity, C/V process staging, spatiotemporal allocation of C/V comparison data, manual vs. automatic C/V, and additional diagnostics. Notable examples from the literature are provided for each strategy element. The comprehensive C/V strategy described herein will allow for better interpretation of future modeling studies, improved utility of modeling applications, and more systematic advancement of H/WQ models.

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“…Parameter sensitivity analysis is an important step to effectively limit the number of parameters and identify key parameters [64]. The AAT method was applied to search optimize parameters.…”

Section: Appendix Amentioning

confidence: 99%

Using SWAT to Evaluate Streamflow and Lake Sediment Loading in the Xinjiang River Basin with Limited Data

Yuan

Forshay

2019

Water

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Soil erosion and lake sediment loading are primary concerns of watershed managers around the world. In the Xinjiang River Basin of China, severe soil erosion occurs primarily during monsoon periods, resulting in sediment flow into Poyang Lake and subsequently causing lake water quality deterioration. Here, we identified high-risk soil erosion areas and conditions that drive sediment yield in a watershed system with limited available data to guide localized soil erosion control measures intended to support reduced sediment load into Poyang Lake. We used the Soil and Water Assessment Tool (SWAT) model to simulate monthly and annual sediment yield based on a calibrated SWAT streamflow model, identified where sediment originated, and determined what geographic factors drove the loading within the watershed. We applied monthly and daily streamflow discharge and monthly suspended sediment load data (1985)(1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001) to Meigang station to conduct parameter sensitivity analysis, calibration, validation, and uncertainty analysis of the model. The coefficient of determination (R 2 ), Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), and RMSE -observation's standard deviation ratio (RSR) values of the monthly sediment load were 0.63, 0.62, 3.8%, and 0.61 during calibration, respectively. Spatially, the annual sediment yield rate ranged from 3 ton ha −1 year −1 on riparian lowlands of the Xinjiang main channel to 33 ton ha −1 year −1 on mountain highlands, with a basin-wide mean of 19 ton ha −1 year −1 . The study showed that 99.9% of the total land area suffered soil loss (greater than 5 ton ha −1 year −1 ). More sediment originated from the southern mountain highlands than from the northern mountain highlands of the Xinjiang river channel. These results suggest that specific land use types and geographic conditions can be identified as hotspots of sediment source with relatively scarce data; in this case, orchards, barren lands, and mountain highlands with slopes greater than 25 • were the primary sediment source areas. This study developed a reliable, physically-based streamflow model and illustrates critical source areas and conditions that influence sediment yield.

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Root Zone Water Quality Model Sensitivity Analysis Using Monte Carlo Simulation

Cited by 89 publications

References 30 publications

Evaluation of Multi-Satellite Precipitation Products for Streamflow Simulations: A Case Study for the Han River Basin in the Korean Peninsula, East Asia

Evaluation of Multi-Satellite Precipitation Products for Streamflow Simulations: A Case Study for the Han River Basin in the Korean Peninsula, East Asia

A Recommended Calibration and Validation Strategy for Hydrologic and Water Quality Models

Using SWAT to Evaluate Streamflow and Lake Sediment Loading in the Xinjiang River Basin with Limited Data

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