No abstract

Seasonal reconstructions of streamflow are valuable because they provide water planners, policy makers, and stakeholders with information on the range and variability of water resources before the observational period. In this study, we used streamflow data from five gages near the Alabama-Florida border and centuries-long tree-ring chronologies to create and analyze seasonal flow reconstructions. Prescreening methods included correlation and temporal stability analysis of predictors to ensure practical and reliable reconstructions. Seasonal correlation analysis revealed that several regional tree-ring chronologies were significantly correlated (p ≤ 0.05) with March–October streamflow, and stepwise linear regression was used to create the reconstructions. Reconstructions spanned 1203–1985, 1652–1983, 1725–1993, 1867–2011, and 1238–1985 for the Choctawhatchee, Conecuh, Escambia, Perdido, and Pascagoula Rivers, respectively, all of which were statistically skillful (R2 ≥ 0.50). The reconstructions were statistically validated using the following parameters: R2 predicted validation, the sign test, the variance inflation factor (VIF), and the Durbin–Watson (D–W) statistic. The long-term streamflow variability was analyzed for the Choctawhatchee, Conecuh, Escambia, and Perdido Rivers, and the recent (2000s) drought was identified as being the most severe in the instrumental record. The 2000s drought was also identified as being one of the most severe droughts throughout the entire reconstructed paleo-record developed for all five rivers. This information is vital for the consideration of present and future conditions within the system.

In this paper, we evaluate the impacts of historic strong El Niño events on the coastal Mississippi-Alabama (MS-AL) hydroclimate. The normal physical association is that the increase in soil moisture, as a result of greater precipitation, is also associated with increased streamflow. When compared to the historic (1960–2015) long-term average, January through August streamflow volumes for five unimpaired streamflow gages located in coastal MS-AL exhibit an average increase of ~20% following a strong El Niño event. This overall increase was due to above-average precipitation during the winter-spring (January through April) season, with the corresponding average increase in streamflow volume for the five gages ~32%. In evaluating the temporal (monthly) variability of streamflow, we observe that the summer (June through August) season was dry following strong El Niño events, with streamflow volumes for the five gages decreasing by an average of ~21%. The agricultural industry in coastal MS-AL produces a variety of crops including cotton and peanuts. The typical planting season for these crops ends in mid-June with harvesting occurring in early September. Thus, the primary growing season for these crops is June–August. Given the lack of impoundments and irrigated lands in coastal MS-AL, the agricultural sector would be severely impacted by an El Niño driven drier summer. When evaluating the influence of the 2015–2016 El Niño on January through August 2016 streamflow, a similar pattern was observed in which high winter–spring streamflow was followed by diminished summer streamflow.

Winter precipitation (snowpack) in the European Alps provides a critical source of freshwater to major river basins such as the Danube, Rhine, and Po. Previous research identified Atlantic Ocean variability and hydrologic responses in the European Alps. The research presented here evaluates Atlantic Sea Surface Temperatures (SSTs) and European Alps winter precipitation variability using Singular Value Decomposition. Regions in the north and mid-Atlantic from the SSTs were identified as being tele-connected with winter precipitation in the European Alps. Indices were generated for these Atlantic SST regions to use in prediction of precipitation. Regression and non-parametric models were developed using the indices as predictors and winter precipitation as the predictand for twenty-one alpine precipitation stations in Austria, Germany, and Italy. The proposed framework identified three regions in the European Alps in which model skill ranged from excellent (West Region–Po River Basin), to good (East Region) to poor (Central Region). A novel approach for forecasting future winter precipitation utilizing future projections of Atlantic SSTs predicts increased winter precipitation until ~2040, followed by decreased winter precipitation until ~2070, and then followed by increasing winter precipitation until ~2100.