H52A-07
Sensitivity of Extreme Hydrological Events to Spatial Resolution of Climate Forcings using a Macro-Scale Hydrologic Model

Friday, 18 December 2015: 11:50
3020 (Moscone West)
Bibi S Naz1, Shih-Chieh Kao2, Moetasim Ashfaq1, Deeksha Rastogi1, Rui Mei3 and Sudershan Gangrade2,3, (1)Oak Ridge National Lab, Oak Ridge, TN, United States, (2)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States, (3)Oak Ridge National Laboratory, Oak Ridge, TN, United States
Abstract:
The magnitude and frequency of hydrometeorological extremes are expected to increase in the conterminous United States over the coming century with significant implications for future water resource planning. However, future changes in the frequency and severity of extreme hydrological events is highly uncertain, in part because of under representation of fine scale topographic and weather features in the continental- to global-scale models. In this study, the influence of spatial resolution on both extremes (floods and droughts) and mean hydrologic conditions is investigated using the macro-scale Variable Infiltration Capacity (VIC) model, implemented and calibrated at 1/24th degree grid cell (~4km) resolution. The coarser resolution simulations are achieved by averaging the 1/24o forcing data to 1/8o which is then used to drive the VIC model. To investigate the sensitivity of simulated high and low runoff conditions to changes in precipitation and temperature at different spatial resolution, further simulations are conducted by (a) increasing both historic maximum and minimum daily temperature by 1° C, (b) increasing historic precipitation by 10%, and (c) decreasing historic precipitation by 10%. The results are further analyzed for various types of extreme precipitation events across different watershed scales and for different regions representing a variety of hydrometeorological characteristics. This work helps us to understand the sensitivity of runoff to spatial resolution of climate forcings and also its sensitivity to different watershed sizes and characteristics of extreme precipitation events in the future climate conditions.