Temporal variability of precipitation in the Upper Tennessee Valley

Abstract

a b s t r a c t Study region: Upper Tennessee River Basin, United States. Study focus: The temporal variation of precipitation in the Upper Tennessee River Basin was investigated by utilizing datasets from the Tennessee Valley Authority (TVA) rain gauge network consisting of 56 rain gauges , and the National Weather Service (NWS) analyzing mean areal precipitation values for 78 subbasins . The Mann-Kendall trend test, Mann-Kendall-Sneyers test, Yamamoto Method, and Morlet's wavelet were applied to reveal precipitation trends and abrupt changes in annual precipitation volumes. New hydrological insights for the region: Analyses indicated that: (a) 11% of the 78 subbasins experienced statistically significant increasing or decreasing precipitation over a 50-year period; (b) seasonal precipitation trends based on monthly volumes varied, with the summer and autumn series showing the largest significant increases; (c) abrupt changes in annual precipitation volumes were detected among subbasins corresponding to strong El Niño events; and (d) several subbasins displayed significant periodicities of 1, 6, 18, and 22 years in monthly volumes. These findings provide key information for regional precipitation down-scaling from global climate change models where the Appalachian mountainous terrain greatly impacts down-scaling results.

Precipitation Trends over Slovakia in the Period 1981–2013

“…Of the two methods most commonly used, the parametric and nonparametric methods, the latter has been favored over the former [49]. Among the nonparametric methods, the Mann-Kendall (MK) statistical test [51,52] has been frequently used to quantify the significance of trends in time series [1,23,[45][46][47][48][49][50][53][54][55][56][57][58][59][60]. It is also widely used in environmental science because it is simple, robust, and can cope with missing values and values below a detection limit.…”

“…An extension of the MK method, called the Sequential Mann-Kendall (SQMK) test, is widely used to detect the time (year) when a trend shows a shift (change in regime trend turning point) [1,20,47,49,56,58,60]. SQMK consists of sequential forward (u(t i )) and backward (u'(t i )) analyses of the MK test.…”

“…Observations show that changes are occurring in the amounts, intensity, and frequency of precipitation [1]. Changes in climate in recent years have led to an increased temporal variability of the hydrological cycle (precipitation, streamflow, evaporation) on global, regional, and local scales, (Zimbabwe).…”

Changes in the Intensity and Variability of Precipitation in the Central Region of Argentina between 1960 and 2012

“…Another important feature of the long-term changes is that they are not monotonic but rather fluctuate on a shorter temporal scale, similar to the temporal variation that [10] observed in North Carolina (USA) and [38] in the Upper Tennessee Valley (USA). Likewise, [12] showed this medium-term variation of the precipitation series in China and determined, from sequential MKS procedures and the moving average difference (mobile t-test), the occurrence of up to three jumps or breakpoints between 1960 and 2008. de la Casa and Nasello (2010) [5] observed a fluctuation of between 10 and 20 years in rainfall time series of Cordoba, Argentina, analyzed from the nonlinear method of partial slopes [20].…”

“…Similarly, Villafuerte et al (2014) [14] find that extreme rains in the Philippines exhibit spatially incoherent behavior, with mixed positive and negative trends even among neighboring weather stations. Also, assessing temporal variability of rainfall in the Upper Tennessee Valley, Jones et al (2015) [38] concluded that only 11% of the 78 sub-basins experienced statistically significant increasing or decreasing precipitation over a 50-year period. This reveals changes in the rainfall regime are not widespread in a region nor has the same sign necessarily, as was observed in central Argentina.…”