Spatial and temporal analysis and trends of extreme precipitation over the Mississippi River Basin, USA during 1988–2017

Abstract

Study region

Mississippi River Basin.

Study focus

Using daily precipitation records of 769 meteorological stations over the Mississippi River Basin (MRB), the spatial-temporal variability and trend of nine extreme precipitation indices were estimated and statistically assessed using the Mann-Kendall test. Factors likely to influence the spatial pattern and trends of precipitation extremes indices were also checked.

New hydrological insights for the region

The spatial pattern of the extreme precipitation indices exhibits a southeast to Northwest dipole, with the maximum values recorded over the southeastern part of the domain (exception being for Consecutive Dry Days, CDD which shows otherwise) driven by the southerly moisture transport toward the southeast. The spatial pattern of the extreme precipitation is controlled by the topography. The results also show that, on average, almost all the indices (except CDD) exhibit an increasing trend. The total wet day precipitation exhibits a significant increasing trend. Spatially, most of the significant increasing (decreasing) trends of the extreme's precipitation-except CDD- are located over the Upper (South) MRB where there is a significant sign toward cooling (warming) conditions. This supports the view that changing climate towards warming (cooling) conditions is significantly affecting precipitations extremes over the MRB. The relationships between large-scale teleconnections and extreme precipitation show that Pacific North America significantly increases (decreases) frequency and intensity indices over the Northwest (southeast) MRB, whereas the Pacific Decadal Oscillation does increase the frequency and intensity indices over the southeast. El Niño Southern Oscillation significantly increases the frequency and intensity indices over the entire MRB, with consequences to infrastructure failures, increasing vulnerable populations, risk zones and relocations populations.