Regionalization of a Rainfall-Runoff Model: Limitations and Potentials

Abstract

Regionalized lumped rainfall-runoff (RR) models have been widely employed as a means of predicting the streamflow of an ungauged watershed because of their simple yet effective simulation strategies. Parameter regionalization techniques relate the parameter values of a model calibrated to the observations of gauged watersheds to the geohydrological characteristics of the watersheds. Thus, the accuracy of regionalized models is dependent on the calibration processes, as well as the structure of the model used and the quality of the measurements. In this study, we have discussed the potentials and limitations of hydrological model parameter regionalization to provide practical guidance for hydrological modeling of ungauged watersheds. This study used a Tank model as an example model and calibrated its parameters to streamflow observed at the outlets of 39 gauged watersheds. Multiple regression analysis identified the statistical relationships between calibrated parameter values and nine watershed characteristics. The newly developed regional models provided acceptable accuracy in predicting streamflow, demonstrating the potential of the parameter regionalization method. However, uncertainty associated with parameter calibration processes was found to be large enough to affect the accuracy of regionalization. This study demonstrated the importance of objective function selection of the RR model regionalization.

Assessing the Potential of Agricultural Reservoirs as the Source of Environmental Flow

“…The analysis framework proposed in this study will help improve the water use efficiency of the existing reservoirs under multiple operations objectives, improved agricultural and environmental sustainability. The proposed framework is based on simulation and scenario analysis implemented using a hydrological model, 3-Tank, which is known as applicable to a wide range of watersheds and thus expected to help explore the trade-off between irrigation and EF in other areas [36,44,45,70,71]. Reservoir operation scenarios for ET supply were evaluated using a 3-Tank model regionalized to the study areas in the analysis.…”

“…Parameter calibration is often not an option due to the absence of reservoir inflow measurements. In such a case (ungauged areas), model parameter values can be estimated from the statistical relationships between watershed characteristics and parameter values derived from gauged watersheds, often called regionalization [41][42][43][44]. In this study, we selected 3-Tank models regionalized to the study areas (R-Tank).…”

“…The R-Tank model is known to accurately predict streamflow of the Korean watersheds, and it has been widely used for reservoir water management and planning in ungauged watersheds [36,45,46]. Song et al [44] showed the R-Tank models could provide acceptable prediction performance (0.50 < , and | | < ± 15) at 9 of 10 watersheds in Korea.…”

Scenario-Based Real-Time Flood Prediction with Logistic Regression

“…The general purpose of regression analysis is to study the relationship between dependent and independent variables, from linear and nonlinear regression, parameter estimation to non-parametric models. This is one of the most widely used techniques for analyzing a set of well-known data because of its convenience in application, and especially in the field of water resources and environmental engineering [19,20]. Regression analysis is widely used for prediction using data interpolation and extrapolation, and for estimation of missing data.…”

Application of the Hidden Markov Bayesian Classifier and Propagation Concept for Probabilistic Assessment of Meteorological and Hydrological Droughts in South Korea

“…Many studies verified the application of the TANK model for runoff simulation. For example, Song et al [44] proved the accuracy of the TANK model in simulation of runoff at ungauged watersheds in South Korea, and Jaiswal et al [45] evaluated the accuracy of the TANK model in simulating runoff in Australian watersheds.…”