How Is the Intensity of Rainfall Events Best Characterised? A Brief Critical Review and Proposed New Rainfall Intensity Index for Application in the Study of Landsurface Processes

Minimum Rainfall Inter-Event Time to Separate Rainfall Events in a Low Latitude Semi-Arid Environment

Water scarcity in dry tropical regions is expected to intensify due to climate change. Characterization of rainfall events is needed for a better assessment of the associated hydrological processes, and the proposition of adaptation strategies. There is still no consensus on the most appropriate method to separate rainfall events from a continuous database, although the minimum inter-event time (MIET) is a commonly used criterion. Semi-arid regions of low latitudes hold a distinct rainfall pattern compared to their equivalent at higher latitudes; these seasonally dry tropical forests experience strong spatial–temporal variability with intense short-duration rainfall events, which, in association with high energy surplus and potential evaporation, leads to an atmospheric water deficit. In this study, we identified the most adequate MIET based on rainfall data continuously measured at 5-min intervals over the last decade (2009–2020) in the semi-arid northeast of Brazil. The rainfall events were grouped according to different MIETs: 15 min, 1 h, 2 h, 3 h, 6 h, 12 h, and 24 h to determine rainfall depth, duration and intensity at intervals of 5, 30, and 60 min, time between events, and respective temporal distribution, with and without single tip events. Including single tip events in the dataset affected the number of rainfall events and respective characteristics up to a MIET of 3 h. A MIET of 6 h is the most appropriate to characterize the rainfall distribution in this tropical semi-arid region. Three classes were defined based on rainfall depth, duration, and intensity: I-small events (77% below 40 mm and 32 mm/h), II-high intensity events (3% between 36 and 76 mm/h), III-longer events of higher depth (20%). This study is useful for understanding how the MIET relates to other ecohydrological processes and provides more precise information on the rainfall characteristics at the event scale.

Drought Characterization and Trend Detection Using the Reconnaissance Drought Index for Setsoto Municipality of the Free State Province of South Africa and the Impact on Maize Yield

The reconnaissance drought index (RDI) for the Setsoto municipality of the Free State province in South Africa was calculated for the period between 1985 and 2019 at 3 month (October–December), 6 month (October–March), and 12 month (October–September) intervals. Rainfall and minimum and maximum temperature data from four weather stations (Clocolan, Ficksburg, Marquard, and Senekal) were used for this study to characterize drought using “DrinC” software together with the Mann Kendall test with Sen’s slope to detect drought trends and the rate of change. Extreme, severe, and moderate droughts were recorded for all the stations, with RDIs ranging from −3.6 to −1.0 at different temporal scales. The years 1991, 1994, 2006, 2011, and 2015 were highlighted using the RDI 3, 6, and 12 month calculations. Results showed that the yield decreased either in the year of the drought or in the subsequent year, due to the exact timing of the low-rainfall events in the season and soil moisture storage. Yields were low, on average 2.5 tons ha−1 year−1, with high variability. Optimal growing conditions are essential in the early part of the season, October–December, for maximizing yield; if droughts are experienced at this time then the yield is more greatly impacted than if the droughts occur later in the season. Spatial analysis shows a large variability of drought patterns across the Municipality, over the years, with the 3 month RDI values giving a more detailed picture of this variability than the 6 and 12 month RDI values.