Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshops

By Qingyun Duan, J. Schaake, Vazken Andréassian, S. Franks, G. Goteti, Hoshin V. Gupta, Y. Gusev, F. Habets, A. Hall, Lauren E. Hay and 10 more. 2006

441 citations recorded by the source corpus.

The Model Parameter Estimation Experiment (MOPEX) is an international project aimed at developing enhanced techniques for the a priori estimation of parameters in hydrologic models and in land surface parameterization schemes of atmospheric models. The MOPEX science strategy involves three major steps: data preparation, a priori parameter estimation methodology development, and demonstration of parameter transferability. A comprehensive MOPEX database has been developed that contains historical hydrometeorological data and land surface characteristics data for many hydrologic basins in the United States (US) and in other countries. This database is being continuously expanded to include more basins in all parts of the world. A number of international MOPEX workshops have been convened to bring together interested hydrologists and land surface modelers from all over world to exchange knowledge and experience in developing a priori parameter estimation techniques. This paper describes the results from the second and third MOPEX workshops. The specific objective of these workshops is to examine the state of a priori parameter estimation techniques and how they can be potentially improved with observations from well-monitored hydrologic basins. Participants of the second and third MOPEX workshops were provided with data from 12 basins in the southeastern US and were asked to carry out a series of numerical experiments using a priori parameters as well as calibrated parameters developed for their respective hydrologic models. Different modeling groups carried out all the required experiments independently using eight different models, and the results from these models have been assembled for analysis in this paper. This paper presents an overview of the MOPEX experiment and its design. The main experimental results are analyzed. A key finding is that existing a priori parameter estimation procedures are problematic and need improvement. Significant improvement of these procedures may be achieved through model calibration of well-monitored hydrologic basins. This paper concludes with a discussion of the lessons learned, and points out further work and future strategy.

Subfields: Atmospheric Science, Environmental Engineering, Water Science and Technology

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Citations in the corpus

An evaluation of adaptive surrogate modeling based optimization with two benchmark problems (2014, methodology): “Historical precipitation, potential evapotranspiration and streamflow observations from January 1st, 1960 to December 31st, 1979 were obtained from the MOPEX database for this study (Duan et al., 2006).”
Flow Prediction in Ungauged Catchments Using Probabilistic Random Forests Regionalization and New Statistical Adequacy Tests (2019, background): “…regionalization relationships are difficult or impossible to derive (Blöschl et al., 2013), in no small part due to difficulties in establishing correspondence between model parameters and physical catchment attributes (Duan et al., 2006; Koren et al., 2003; see also Fenicia et al., 2014).”
Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modeling heteroscedastic residual errors (2017, background): “Similarly, the MOPEX catchments are broadly representative of USA conditions [Duan et al., 2006].”
Markov chain Monte Carlo simulation using the DREAM software package: Theory, concepts, and MATLAB implementation (2016, methodology): “D R EA M M A N U A L Daily discharge, mean areal precipitation, and mean areal potential evapotranspiration were derived from Duan et al. (2006) and used for diagnostic model evaluation with DREAM(ABC) (Sadegh and Vrugt, 2014).”
A one‐parameter Budyko model for water balance captures emergent behavior in darwinian hydrologic models (2014, methodology): “An additional 246 watersheds from the Model Parameter Estimation Experiment (MOPEX) data set [Duan et al., 2006] provide a second data set for verifying the lower bound, as is shown in Figure 2b, along with the best fit curve of equation (10) where ε= 0.55.”
Large-sample hydrology: a need to balance depth with breadth (2013, methodology): “Subsequently, the Model Parameter Experiment (MOPEX; see e.g., Schaake et al., 2001; Chahinian et al., 2006; 10 Duan et al., 2006; Schaake and Duan, 2006) organized modeling experiments using a large sample of catchment data sets from the USA and France.”