Atlas of precipitation extremes for South America and Africa based on depth-duration-frequency relationships in a stochastic weather generator dataset

Authors: Fullhart, Andrew; Goodrich, David - Dave; Meles, Menberu; OLIVEIRA, P.T. - Universidade Federal De Mato Grosso; ALMEIDA, C.N. - Universidade Federal Da Paraiba (UFPB); DE ARAUJO, J.C. - Universidade Federal Do Ceara (UFC); BURNS, I.S. - University Of Arizona

Submitted to: International Soil and Water Conservation Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/12/2023
Publication Date: 1/23/2023
Citation: Fullhart, A.T., Goodrich, D.C., Meles, M.B., Oliveira, P., Almeida, C., De Araujo, J., Burns, I. 2023. Atlas of precipitation extremes for South America and Africa based on depth-duration-frequency relationships in a stochastic weather generator dataset. International Soil and Water Conservation Research. 11(4):726-742. https://doi.org/10.1016/j.iswcr.2023.01.004.
DOI: https://doi.org/10.1016/j.iswcr.2023.01.004

Interpretive Summary: Extreme rainfall is a major challenge for water resource management. In regions of Africa and South America, there is a lack of climate information needed to estimate the magnitude of extreme rainfall events. An atlas of distributions of extreme rainfall in Africa and South America was created to address this issue. Rainfall distributions are presented in terms of rainfall magnitude for a wide range of time windows ranging from 10 minutes to 1 year. Rare rainfall magnitudes are determined for each time window with the rarest magnitudes being one-in-five-hundred years. Given this wide range of data, a number of applications may make use of the proposed atlas, such as civil engineering projects based on design storms. The precipitation timeseries were generated with a USDA tool called CLIGEN, which was involved in a novel approach to produce the spatial data needed for mapping. Assessing the suitability of CLIGEN for modeling applications—most commonly soil erosion models—is a secondary outcome of this study. Several issues were identified that may lead to better estimation of runoff and soil erosion during extreme rainfall events. The atlas will be made freely available for potential use in a variety of applications.

Technical Abstract: Information about extreme rainfall is lacking in regions of South America and Africa. This study attempts to fill this scientific gap by use of a gridded parameterization for the stochastic weather generator, CLIGEN, to map depth-duration-frequency (DDF) relationships. Analysis of 500-year point-scale precipitation timeseries generated at each grid point allowed maps of return level depths to be produced for a selection of sixteen durations ranging from 10-min to 1-year and for nine return periods ranging from 2 to 500 years. The generalized extreme value (GEV) probability distribution was fitted for all durations, and given GEV quantiles, an interpolation method was applied to produce maps at 0.1 deg resolution that better resolve small-scale spatial climate gradients. In addition to uncertainties related to GEV fitting, this study quantifies prediction intervals based on ground validation. This validation was important for identifying biases in CLIGEN, although uncertainties were not always satisfactorily defined due to sampling design and other factors. For daily/multi-day durations, 100 stations with daily observations and >50-year records were selected for validation against the 0.1 deg CLIGEN map series, resulting in a median and average absolute error of 13% and 16%, respectively. For sub-daily durations, prediction errors were larger overall. An analogy to available U.S. data established the degree of bias in CLIGEN for sub-daily durations, and three records in Brazil with high temporal resolutions were used to confirm that applied bias adjustments resulted in error ranges similar to the daily/multi-day cases. This Atlas is freely available for study of extreme precipitation.