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Assessing Recession Constant Sensitivity and Its Interaction with Data Adjustment Parameters in Continuous Hydrological Modeling in Data Scarce Basins: A Case Study Using the Xinanjiang Model
Zin, T.T.; Lu, M.; Ogura, T. Assessing Recession Constant Sensitivity and Its Interaction with Data Adjustment Parameters in Continuous Hydrological Modeling in Data-Scarce Basins: A Case Study Using the Xinanjiang Model. Water2024, 16, 286.
Zin, T.T.; Lu, M.; Ogura, T. Assessing Recession Constant Sensitivity and Its Interaction with Data Adjustment Parameters in Continuous Hydrological Modeling in Data-Scarce Basins: A Case Study Using the Xinanjiang Model. Water 2024, 16, 286.
Zin, T.T.; Lu, M.; Ogura, T. Assessing Recession Constant Sensitivity and Its Interaction with Data Adjustment Parameters in Continuous Hydrological Modeling in Data-Scarce Basins: A Case Study Using the Xinanjiang Model. Water2024, 16, 286.
Zin, T.T.; Lu, M.; Ogura, T. Assessing Recession Constant Sensitivity and Its Interaction with Data Adjustment Parameters in Continuous Hydrological Modeling in Data-Scarce Basins: A Case Study Using the Xinanjiang Model. Water 2024, 16, 286.
Abstract
While considering the sensitivity over the parameter optimization, it is essential to determine which parameters have the most significant implications on model performance. This study focuses on the baseflow recession constant as one of the independent basin parameters to forecast low flows, perform hydrograph analysis, and calibrate rainfall-runoff models for significant improvement. Prior studies examined that the optimization of data adjustment parameters can improve the hydrological model performance and determine the minimum acceptable data length for data scarce regions using the Xinanjaing model. However, it is essential to pay special attention to the sensitivity of the recession constant, which can also impact the model performance during the data scarcity. Therefore, this study extends the research to comprehend the recession constant sensitivity over data adjustment parameters in the shorter datasets leading to more reliable parameter estimation. In terms of that, this study explores how recession constant affects hydrological parameter estimation on annual scale while keeping data adjustment parameters constant in continuous hydrological modeling, employing the Xinanjiang (XAJ) model as a case study. This study considered two approaches of recession constant (cg); (i) assessing the relationship between cg and the data adjustment parameter (Cep), for the 28-year datasets, (ii) investigating the significant impacts of the sensitivity of cg over Cep in shorter datasets which can affect the estimation of the acceptable minimum data length in the data scarce basins. The study underscores the importance of the recession constant sensitivity for reliable continuous hydrological model predictions, especially in data-scared areas. The study’s outcomes enhance the understanding of the importance of parameter sensitivity and its relationship in conceptual hydrological modeling during the data limitations.
Keywords
XAJ model; Recession constant; Data adjustment parameter; Model performance; Sensitivity
Subject
Environmental and Earth Sciences, Water Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.