Influence of climate variability on terrestrial hydrology in North America

A large-area basin-scale (LABs) model is developed for regional, continental and global hydrologic studies. The heterogeneity in the soil-moisture distribution within a basin is parameterized through the statistical moments of the probability distribution function of the topographic (wetness) index. The role of topographic influence in hydrologic prediction is studied using the LABs model and ISLSCP data for 1987 and 1988 in North America. Improvement in the terrestrial water balance and streamflow is observed due to improvements in the surface runoff and baseflow components achieved by incorporating the basin topographic features. These enhancements also impact the surface energy balance, Daily streamflow observations of the Mississippi river and its four tributaries are used for evaluating the LABs performance. It is observed that model baseflow has a significant contribution to the streamflow and is important in realistically capturing the seasonal and annual cycles.; To study the impacts of climate variations on the terrestrial hydrologic processes, ERA-15 dataset (1979–1993) is used to drive LABs for all basins over North America. The anomalies of the model forcing and output are correlated with climate anomalies, such as ENSO, NAO and PNA. It is found that the terrestrial hydrology has a delayed response to the ENSO signal, as compared to the precipitation, and the delay may range from a month to a season or longer. The soil moisture storage plays a very vital role in delaying the effects of the climate variability on the terrestrial hydrology and in extending the influences of the El Niña and La Niña events. The fluctuation of the soil temperature anomaly is correlated with ENSO in certain geographic regions, and the strength and the associated time lag of this correlation increase with increasing soil depth. In addition, the NAO and PNA correlations with downward longwave radiation, surface temperature and ground heat flux in North America show a seesaw (or wavelike) spatial pattern.