Error Decomposition of Streamflow and Groundwater Projection Under Climate Change Information

Monday, 15 December 2014
Seung Beom Seo1, Tushar Sinha2, Kumar Mahinthakumar1 and Sankarasubramanian Arumugam1, (1)NC State Univ-Civil & Env Engr, Raleigh, NC, United States, (2)Texas A & M University Kingsville, Kingsville, TX, United States
Recent climate change projections from Climate Models Inter-comparison Project-5 (CMIP5) provide opportunities for incorporating climate change information in planning and management. Most of the climate change studies primarily focus on either projection of climate variables or sources of uncertainty associated with hydro-climatic variables. This study evaluates the sources of errors in developing near-term hydro-climatic projections for four watersheds across the Sunbelt. Common sources of error in obtaining hydro-climatic projections are decomposed into GCM/downscaling from CMIP5, temporal disaggregation, and hydrologic model error.. For this purpose, a fully coupled surface water and groundwater model, PIHM (Penn State Integrated Hydrologic Model) was used in order to simulate streamflow and groundwater depth simultaneously over the selected four watersheds from different hydro-climatic regimes. Study reveals that smaller watersheds have larger error due to GCM and low flow season shows larger hydrologic model error. Further, temporal disaggregation error is the primary source of error in projecting hydrologic extremes. The study also quantifies the ability of GCMs in capturing the observed changes in hydro-climatic attributes through retrospective analyses and also the different sources of errors that contribute to the inability in explaining the observed change.