Rainfall Intensity Characteristics Research Articles

Analysis of the subsurface minerals of Bantimurung-Bulusaraung National Geopark: Leang Lonrong Cave in Maros-Pangkep regencies based on its characteristics of rainfall intensity

Leang Lonrong Cave with underground river flowing in it is located in Maros-Pangkep karst area known with a high level of annual rainfall. That condition affects the surrounding environment including water discharge and subsurface mineral types. This study aims at analyzing the impact of rainfall on sub-surface mineral types around the area of Leang Lonrong Cave. The data used are rainfall intensity of Tondong Tallasa, Bungoro and Ballocci stations in 2015-2019 which are analyzed using Oldeman and Schmidt-Ferguson methods to find out the characteristics of rainfall occuring in Pangkep Regency. As for water discharge in June 2020 and rock resistivity data, they are examined using geo-electric method by Wenner’s through IP2Win and Res2DinV. The results of this study show that the area is dominated by wet months in November to April with rainfall intensity above 100mm per year and dry months which generally occurring in July to September where the others are considered as humid months with low water discharge flows in dry months. Moreover, the subsurface minerals are dominated by groundwater, clay and sand with resistivity extends from 0 to 27Ωm.

Raindrop Size Distribution Parameters Retrieved from Xinfeng C-Band Polarimetric Radar Observations

The objective of this research was to acquire a raindrop size distribution (DSDs) retrieved from C-band polarimetric radar observations scheme for the first time in south China. An observation period of the precipitation process was selected, and the shape-slope (μ-Λ) relationship of this region was statistically analyzed using the raindrop sample observations from the two-dimensional video disdrometer (2DVD) at Xinfeng Station, Guangdong Province. Simulated data of the C-band polarimetric radar reflectivity ZHH and differential reflectivity ZDR were obtained through scattering simulation. The simulation data were combined with DSD fitting to determine the ZDR-Λ and log10(ZHH/N0)-Λ relationships. Using Xinfeng C-band polarimetric radar observations ZDR and ZHH, the raindrop Gamma size distribution parameters μ, Λ, and N0 were retrieved. A scheme for using C-band polarimetric radar to retrieve the DSDs was developed. This research revealed that during precipitation process, the DSDs obtained using the C-band polarimetric radar retrieval scheme are similar to the 2DVD observations, the precipitation characteristics of rainfall intensity (R), mass-weighted mean diameter (Dm) and intercept parameter (Nw) with time obtained by radar retrieval are basically consistent with the observational results of the 2DVD. This scheme establishes the relationship between the observations of the C-band polarimetric radar and the physical quantities of the numerical model. This method not only can test the prediction of the model data assimilation system on the convective scale and determine error sources, but also can improve the microphysical precipitation processes analysis and radar quantitative precipitation estimation. The present research will facilitate radar data assimilation in the future.

Characteristics of rainfall intensity, duration, and kinetic energy for landslide triggering in Taiwan

Rainfall intensity-duration (I-D) characteristics are widely used to study landslide triggering. Recent studies also propose that rainfall kinetic energy (ek) can be used to quantify the rate of soil erosion induced by strong precipitation events. In the present study, the Joss-Waldvogel Disdrometers (JWD) was utilized to measure ek data, and the relationship between rainfall kinetic energy and rainfall intensity was determined as the regression results of ekN=32.19×(1–0.725e(−0.029I)) for northern Taiwan and ekS=32.23×(1–0.643e(−0.022I)) for southern Taiwan. Additionally, by examining data from 76 landslide events from the landslide inventory for the period of 2006–2012, the study established an empirical power law I-D relationship, which is crucial for determining the rainfall threshold needed in forecasting landslides. Two rainfall thresholds, i.e., functions of rainfall intensity (I) and rainfall duration (D), were established for study areas in northern and southern Taiwan to be IN=13.81 D−0.31 and IS=66.44 D−0.57 respectively. Landslides in northern Taiwan usually occurred when D was over 10h and such events in southern Taiwan took place in two different D groups whose gap was between 16h and 20h. Two mechanisms were operative in triggering landslides in the two areas—water infiltration and high rainfall intensity. However, ek also proved to be an important rainfall parameter, and the present study further established that not only rainfall intensity-duration but also kinetic energy can provoke landslide triggering, thus allowing the compiling of more comprehensive information for more accurate landslide forecasting.

Precipitation intensity probability distribution modelling for hydrological and construction design purposes

The characteristics of rainfall intensity are important for many purposes, including design of sewage and drainage systems, tuning flood warning procedures, etc. Those estimates are usually statistical estimates of the intensity of precipitation realized for certain period of time (e.g. 5, 10 min., etc) with different return period (e.g. 20, 100 years, etc). The traditional approach in evaluating the mentioned precipitation intensities is to process the pluviometer's records and fit probability distribution to samples of intensities valid for certain locations ore regions. Those estimates further become part of the state regulations to be used for various economic activities. Two problems occur using the mentioned approach: 1. Due to various factors the climate conditions are changed and the precipitation intensity estimates need regular update; 2. As far as the extremes of the probability distribution are of particular importance for the practice, the methodology of the distribution fitting needs specific attention to those parts of the distribution. The aim of this paper is to make review of the existing methodologies for processing the intensive rainfalls and to refresh some of the statistical estimates for the studied areas. The methodologies used in Bulgaria for analyzing the intensive rainfalls and produce relevant statistical estimates: The method of the maximum intensity, used in the National Institute of Meteorology and Hydrology to process and decode the pluviometer's records, followed by distribution fitting for each precipitation duration period; As the above, but with separate modeling of probability distribution for the middle and high probability quantiles. Method is similar to the first one, but with a threshold of 0,36 mm/min of intensity; Another method proposed by the Russian hydrologist G. A. Aleksiev for regionalization of estimates over some territory, improved and adapted by S. Gerasimov for Bulgaria; Next method is considering only the intensive rainfalls (if any) during the day with the maximal annual daily precipitation total for a given year; Conclusions are drown on the relevance and adequacy of the applied methods.

Rainfall intensity characteristics at coastal and high altitude stations in Kerala

Rainfall intensities measured at a few stations in Kerala during 2001–2005 using a disdrometer were found to be in reasonable agreement with the total rainfall measured using a manual rain gauge. The temporal distributions of rainfall intensity at different places and during different months show that rainfall is of low intensity (< 10 mm/hr), 65% to 90% of the time. This could be an indication of the relative prevalence of stratiform and cumuliform clouds. Rainfall was of intensity < 5 mm/hr for more than 95% of the time in Kochi in July 2002, which was a month seriously deficient in rainfall, indicating that the deficiency was probably due to the relative absence of cumuliform clouds. Cumulative distribution graphs are also plotted and fitted with the Weibull distribution. The fit parameters do not appear to have any consistent pattern. The higher intensities also contributed significantly to total rainfall most of the time, except in Munnar (a hill station). In this analysis also, the rainfall in Kochi in July 2002 was found to have less presence of high intensities. This supports the hypothesis that the rainfall deficiency was probably caused by the absence of conditions that favoured the formation of cumuliform clouds.