Hydrologic Model Evaluation and Assessment of Projected Climate Change Impacts Using Bias-Corrected Stream Flows

Joseph A Daraio

doi:10.3390/w12082312

Abstract

Hydrologic models driven by downscaled meteorologic data from general circulation models (GCM) should be evaluated using long-term simulations over a historical period. However, simulations driven by GCM data cannot be directly evaluated using observed flows, and the confidence in the results can be relatively low. The objectives of this paper were to bias correct simulated stream flows from calibrated hydrologic models for two basins in New Jersey, USA, and evaluate model performance in comparison to uncorrected simulations. Then, we used stream flow bias correction and flow duration curves (FDCs) to evaluate and assess simulations driven by statistically downscaled GCMs for the historical period and the future time slices 2041–2070 and 2071–2099. Bias correction of stream flow from simulations increased confidence in the performance of two previously calibrated hydrologic models. Results indicated there was no difference in projected FDCs for uncorrected and bias-corrected flows in one basin, while this was not the case in the second basin. This result provided greater confidence in projected stream flow changes in the former basin and implied more uncertainty in projected stream flows in the latter. Applications in water resources can use the methods described to evaluate the performance of GCM-driven simulations and assess the potential impacts of climate change with an appropriate level of confidence in the model results.

Highlights

Estimation and simulation of the flow regime and hydrologic indices require longer time periods, especially for annual time series, which can ensure natural climate variability is included in model calibration and evaluation [1,2]
Hydrologic simulations for climate change impact analysis are driven by downscaled general circulation models (GCM) [6,7,8], and such simulations cannot be directly calibrated with observed flows since the inputs differ for historical simulations
The objectives of this paper were to use flow duration curves (FDCs) (1) to bias correct simulated stream flows from calibrated precipitation-runoff modeling system (PRMS) models for two basins in New Jersey (NJ) and evaluate model performance in comparison to uncorrected simulations, (2) to use bias correction and FDCs to evaluate the performance of rainfall-runoff simulations driven by statistically downscaled GCMs over the historical period 1956–2005, and (3) to assess potential changes to FDCs using uncorrected and bias-corrected stream flows from climate change projections of the future time slices 2041–2070 and 2071–2099

Summary

Introduction

Estimation and simulation of the flow regime and hydrologic indices require longer time periods, especially for annual time series, which can ensure natural climate variability is included in model calibration and evaluation [1,2]. There are no future observed data; it is not possible to calibrate or evaluate the model performance of hydrologic simulations for potential future climates. The absence of such data creates a situation similar to the development of models for ungauged basins [9,10,11], where regionally applicable measures of stream flows are required for model calibration and evaluation. A potential solution to this problem is to use flow duration curves (FDC) and bias correction of stream flows for the evaluation of hydrologic models driven by statistically downscaled meteorological data

Objectives

Methods

Results

Discussion

Conclusion