Multimodel Combination Techniques for Analysis of Hydrological Simulations: Application to Distributed Model Intercomparison Project Results

Newsha K Ajami,Xiaogang Gao,Soroosh Sorooshian,Qingyun Duan

doi:10.1175/jhm519.1

Abstract

Abstract This paper examines several multimodel combination techniques that are used for streamflow forecasting: the simple model average (SMA), the multimodel superensemble (MMSE), modified multimodel superensemble (M3SE), and the weighted average method (WAM). These model combination techniques were evaluated using the results from the Distributed Model Intercomparison Project (DMIP), an international project sponsored by the National Weather Service (NWS) Office of Hydrologic Development (OHD). All of the multimodel combination results were obtained using uncalibrated DMIP model simulations and were compared against the best-uncalibrated as well as the best-calibrated individual model results. The purpose of this study is to understand how different combination techniques affect the accuracy levels of the multimodel simulations. This study revealed that the multimodel simulations obtained from uncalibrated single-model simulations are generally better than any single-member model simulations, even the best-calibrated single-model simulations. Furthermore, more sophisticated multimodel combination techniques that incorporated bias correction step work better than simple multimodel average simulations or multimodel simulations without bias correction.

Highlights

Many hydrologists have been working to develop new hydrologic models or to try improving the existing ones
This paper extends the work of Georgakakos et al (2004) and Shamseldin et al (1997) by examining several multimodel combination techniques, including simple model average (SMA), multimodel superensemble (MMSE), weighted average method (WAM), and modified multimodel average (M3SE) a variant of MMSE
We have tested four different multimodel combination techniques to the streamflow simulation results from the Distributed Model Intercomparison Project (DMIP), an international project sponsored by the National Weather Service (NWS) Office of Hydrologic Development, to intercompare seven state-of-the-art distributed hydrologic models in use today (Smith et al 2004)

Summary

Introduction

Many hydrologists have been working to develop new hydrologic models or to try improving the existing ones. With the advancement of the geographic information system (GIS), a class of models, known as distributed hydrologic models, has become popular (Russo et al 1994; Vieux 2001; Ajami et al 2004). These models explicitly account for spatial variations in topography, meteorological inputs, and water movement. The multimodel combination approach, on the other hand, works in essentially a different paradigm in which the modeler aims to extract as much information as possible from the existing models. These errors would act to cancel each other out, resulting in better overall predictions

Objectives

Findings

Conclusion