Climate-related trends of within-storm intensities using dimensionless temporal storm distributions

Authors: GORDJI, LEILI - University Of Mississippi; Bonta, James - Jim; ALTINAKAR, MUSTAFA - University Of Mississippi

Submitted to: Journal Hydrologic Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/21/2019
Publication Date: 2/28/2020
Citation: Gordji, L., Bonta, J.V., Altinakar, M. 2020. Climate-related trends of within-storm intensities using dimensionless temporal storm distributions. Journal Hydrologic Engineering. 25(5): 13 pp. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001911.
DOI: https://doi.org/10.1061/(ASCE)HE.1943-5584.0001911

Interpretive Summary: The overall objective was to determine whether within-storm dimensionless Huff curve (HC) patterns (dimensionless storm patterns) are changing over a period of trending precipitation and temperature using the high density precipitation-gauge network on the 4.25-km2 North Appalachian Experimental Watershed in east-central Ohio. Gauge records from 1939 through 2010 from 10 gauges were separated into eight 9-yr periods to test for trends in HC patterns using rank correlation. Data were analyzed using: 1) individual gauges and computing rank correlation (RC), 2) averaging the individual gauges and then computing RC; and 3) averaging correlations and significance probabilities of the individual gauges. The data suggest that it is likely that there is little if any effect of precipitation trends on HCs over the 72-year period. Simple averages of RC coefficients and probabilities of individual gauges lead to a no-effect conclusion for central tendency and variability during trending precipitation. However, averaging nonindependent storms (same storms measured) for the gauge network led to a significant trend for variability but not for central tendency. The results of this study add to the robustness characteristics of Huff curves and to their potential use in hydrological practice as design storms, as the foundation of stochastic storm generation, and for storm disaggregation, and they deserve further investigation. These different forms of inputs to watershed models have the potential to improve runoff estimation. The results suggest that, if verified in other studies, they have applicability to provide useful stationary precipitation patterns across the US and other areas of the world in areas of nonstationary climate. Other results include: a lessening of storm intensities in the spring in early parts of storms and in the fall in later parts of storms; previous research on seasonal variation of HCs was confirmed; and data from an individual rain gauge may not be representative of trends over small areas. Some recommendations for further study are given including investigating averaging methods.

Technical Abstract: Huff curves are probabilistic time distributions of rainfall expressed as dimensionless cumulative percentages of storm depth and duration. Previous studies have documented development factors, spatial robustness, and the utility of Huff curves in practical applications. However, the effects of trending rainfall on Huff curve intensity patterns have not yet been studied. The goal of the paper is to fill this gap by studying Huff curves patterns in a watershed with demonstrating increasing trends of temperature and precipitation, with the intention that it can be generalized to other areas in the US and the world. To achieve the goal, the high temporal resolution precipitation data collected from a high spatial density, 72-year precipitation-gauge network on the 4.25-km2 North Appalachian Experimental Watershed in east-central Ohio were used. Seasonal storm pattern trends from 1939-2010 were investigated using dimensionless depth (with the frequency of 50%, d50) and the curve variability (V=d80 - d20) at three dimensionless within storms time periods (three verticals). The Spearman rank correlation procedure (correlation coefficient, ' and significance probability, p) was used to statistically determine trends over time using 8 periods of 4-season sets of Huff curves over the 72 years. Two averages of ' and p were computed; 1) by averaging of “individual” ' and p obtained from 10 gauges (AvgI) and 2) by “grouped” averaging of all individual gauge values of d50 and V and then computing ' and p (AvgG). The test results of individual gauges showed that 4 cases for d50 and 23 cases for V were significant for all seasons and verticals (total of 120 cases for each variable). The test results of AvgI for d50 and V and AvgG for d50 showed no significant trends in all seasons and verticals. Only the AvgG for V led to a significant trend for V in spring and fall at different times within storm patterns. The data do not provide sufficient evidence at the p=0.05 significance level to reject the null hypothesis of unchanging position of the dimensionless depth of the 50% Huff curves for individual or averages for all seasons and verticals. Also, there is not sufficient evidence to reject the null hypothesis of unchanging variability, V, using the average ' of individual gauges (AvgI for V) for all seasons and verticals. AvgG results showed a significant trend in V, however, this analysis may be affected by nonindependence of storm data. The results suggest that it is likely that there is little if any effect of trending climate over approximately 70 years on Huff curve patterns. The results of this study add to the robustness characteristics of Huff curves and to their potential use in hydrological practice as design storms, as the foundation of stochastic storm generation, and for storm disaggregation, and they deserve further investigation. These different forms of inputs to watershed models have the potential to improve runoff estimation. The results suggest that, if verified in other studies, they have applicability to provide useful stationary precipitation patterns across the US and other areas of the world in areas of nonstationary climate. Also, individual rain gauge data may not be representative of trends even over small areas, and seasonal differences were noticeable as found in other studies. Recommendations are provided.