Keywords
ihacres, regionalisation, lake erie, integrated assessment, hydrologic modelling, least squares
Start Date
1-7-2006 12:00 AM
Abstract
The IHACRES model is being applied in a regionalization approach to develop streamflow predic-tions within the region of Northern Ohio, U.S.A. that drains into Lake Erie, located on the border between the U.S. and Canada. The approach to-date is based on independent univariate regressions of model parameters on watershed attributes for a collection of 11 watersheds. Anderson et al. (2005) used one of these regression relationships to represent possible effects of declining forest cover on streamflow, but did not obtain regional models for the parameters of the routing model of IHACRES. Here we apply and “validate” a regionaliza-tion approach to estimating the full set of parameters of the IHACRES hydrologic model for integrated as-sessment across the Lake Erie, northern Ohio USA basin. We also propose that future research should focus on (1) increasing the quality of rainfall estimates as an important way to potentially improve simulation per-formance; (2) developing joint probability distributions over the full set of IHACRES model parameters to improve estimates of predictive uncertainty; and (3) developing estimates of actual forest cover trends to ob-tain more useful predictions of future trends in streamflow.
Regionalization of IHACRES Model Parameters for In-tegrated Assessment across the Lake Erie, northern Ohio USA basin
The IHACRES model is being applied in a regionalization approach to develop streamflow predic-tions within the region of Northern Ohio, U.S.A. that drains into Lake Erie, located on the border between the U.S. and Canada. The approach to-date is based on independent univariate regressions of model parameters on watershed attributes for a collection of 11 watersheds. Anderson et al. (2005) used one of these regression relationships to represent possible effects of declining forest cover on streamflow, but did not obtain regional models for the parameters of the routing model of IHACRES. Here we apply and “validate” a regionaliza-tion approach to estimating the full set of parameters of the IHACRES hydrologic model for integrated as-sessment across the Lake Erie, northern Ohio USA basin. We also propose that future research should focus on (1) increasing the quality of rainfall estimates as an important way to potentially improve simulation per-formance; (2) developing joint probability distributions over the full set of IHACRES model parameters to improve estimates of predictive uncertainty; and (3) developing estimates of actual forest cover trends to ob-tain more useful predictions of future trends in streamflow.
