Possible Impacts of Climate Change on Daily Streamflow and Extremes at Local Scale in Ontario, Canada. Part I: Historical Simulation

Chad Shouquan Cheng,Heather Auld,Guilong Li,Qian Li

doi:10.4236/acs.2012.24036

Abstract

The paper forms the first part of an introduction to possible impacts of climate change on daily streamflow and extremes in the Province of Ontario, Canada. In this study, both conceptual and statistical streamflow simulation modeling theories were collectively applied to simulate daily streamflow volumes. Based on conceptual rainfall-runoff modeling principle, the predictors were selected to take into account several physical factors that affect streamflow, such as (1) current and previous quantities of rainfall over the watershed, (2) an index of pre-storm moisture conditions, (3) an index of pre-storm evapotranspiration capacities, and (4) a seasonal factor representing seasonal variation of streamflow volume. These rainfall-runoff conceptual factors were applied to an autocorrelation correction regression procedure to develop a daily streamflow simulation model for each of the four selected river basins. The streamflow simulation models were validated using a leave-one-year-out cross-validation scheme. The simulation models identified that the explanatory predictors are consistent with the physical processes typically associated with high-streamflow events. Daily streamflow simulation models show that there are significant correlations between daily streamflow observations and model validations, with model R2s of 0.68-0.71, 0.61-0.62, 0.71-0.74, and 0.95 for Grand, Humber, Upper Thames, and Rideau River Basins, respectively. The major reason for the model performance varying across the basins might be that rainfall-runoff response time and physical characteristics differ significantly among the selected river basins. The results suggest that streamflow simulation models can be used to assess possible impacts of climate change on daily streamflow and extremes at a local scale, which is major objective of a companion paper (Part II).

Highlights

Increased flooding risks from heavy rainfall events are recognized as the most important threat from climate change in many regions of the world (e.g., [1,2,3,4,5,6])
Several physical factors represented conceptualization of the perceived important underlying rainfall-runoff transfer processes were used as predictors in autocorrelation correction regression analysis. These daily streamflow simulation models developed in this current study are primarily applied to project changes in frequency of future daily high- and low-streamflow events, which is the major objective of a companion paper (Part II: future projection, Cheng et al [8])
Streamflow simulation models developed by autoregressive error correction regression for all selected river basins, of which one model for each river basin is shown in Table 3 as an example

Summary

Introduction

Increased flooding risks from heavy rainfall events are recognized as the most important threat from climate change in many regions of the world (e.g., [1,2,3,4,5,6]). To better understand whether the frequency of heavy rainfall-related flooding will continue to increase in the 21st century, Environment Canada, in partnerships with four local Conservation Authorities, Ontario Ministry of Natural Resources, and CGI Insurance Business Services, has completed a three-year research project. This project attempts to assess possible impacts of climate change on future daily heavy rainfall, high/low streamflow, and flooding risks in the 21st century for the four selected watersheds (Grand, Humber, Rideau, Upper Thames) in the Province of Ontario, Canada. This current paper and a companion paper (Part II: future projection, Cheng et al [8]) focus on projection of changes in frequency of future daily high-/low-streamflow events, using downscaled GCM simulations of future daily rainfall quantities derived by Cheng et al [9,10]

Objectives

Results

Conclusion