Seasonal intensity-duration-frequency relationships for Pelotas, Rio Grande do Sul, Brazil

ABSTRACT Although several studies have evaluated the intensity-duration-frequency relationships of extreme rainfall events, these relationships under different seasonal conditions remain relatively unknown. Thus, this study aimed to determine whether the intensity-duration-frequency relationships obtained seasonally from the rainfall records in the winter and summer represent the maximum rainfall events for the city of Pelotas, Rio Grande do Sul state, Brazil. Pluviographic data from 1982 to 2015 were used to create two seasonal series: one for the summer from December 21 to March 20 and the other for the winter from June 21 to September 22. These seasonal relationships were compared with the annual pluviographic data. The intensity, duration, and frequency relationships obtained from the summer rain data adequately represented the maximum rainfall in Pelotas, Rio Grande do Sul state, Brazil. The maximum intensity values of rainfall obtained from the relationship of intensity, duration, and frequency for the winter did not adequately encapsulate the occurrence of rain with greater intensities.

Detecting Extreme Rainfall Events Using the WRF-ERDS Workflow: The 15 July 2020 Palermo Case Study

In this work, we describe the integration of Weather and Research Forecasting (WRF) forecasts produced by CIMA Research Foundation within ITHACA Extreme Rainfall Detection System (ERDS) to increase the forecasting skills of the overall early warning system. The entire workflow is applied to the heavy rainfall event that affected the city of Palermo on 15 July 2020, causing urban flooding due to an exceptional rainfall amount of more than 130 mm recorded in about 2.5 h. This rainfall event was not properly forecasted by meteorological models operational at the time of the event, thus not allowing to issue an adequate alert over that area. The results highlight that the improvement in the quantitative precipitation scenario forecast skills, supported by the adoption of the H2020 LEXIS computing facilities and by the assimilation of in situ observations, allowed the ERDS system to improve the prediction of the peak rainfall depths, thus paving the way to the potential issuing of an alert over the Palermo area.

Effects of sediment deposit on the hydraulic performance of the urban stormwater drainage system

Sediment deposit is a critical factor strongly affecting the drainage capacity of the conduits due to its cross-section area narrowing and roughness increasing. In this study, a numerical model was applied to investigate the influences of sediment deposit on the hydraulic performance of the drainage conduits. The Nhieu Loc - Thi Nghe (NL-TN) basin, located in Ho Chi Minh City, Vietnam, was selected as a case study. The drainage network of the NL-TN basin was simulated by using the EPA-SWMM model. The effects of sediment deposit were assessed by a non-dimensional comparison of the simulated peak flows of the sediment-deposited conduits and the clean ones. The results indicated that the sediment deposit significantly affects the flow capacity of the conduits and could cause severe inundation. Narrowing of the cross-section area has more impact on the hydraulic performance of the conduit than the increase in the roughness. A 40% increase in the Manning coefficient could decline the peak flow to approximately 80-90%, while a 40% increase in sediment thickness depth could degrade the peak flow by about 60-70% to compare with the peak flow of the clean conduit. The findings could support decision makings on the operation and maintenance of the sewer system and adaptation to extreme rainfall events.

Modeling of short duration extreme rainfall events over Lower Yamuna Catchment

Short duration rainfall estimates and their intensities for different return periods are required for many purposes such as for designing flood for hydraulic structures, urban flooding etc. An attempt has been made in this paper to Model extreme rainfall events of Short Duration over Lower Yamuna Catchment. Annual extreme rainfall series and their intensities were analysed using EVI distribution for rainstorms of short duration of 5, 10, 15, 30, 45 & 60 minutes and various return periods have been computed. The Self recording rainguage (SRRGs) data for the period 1988-2009 over the Lower Yamuna Catchment (LYC) have been used in this study. It has been found that EVI distribution fits well, tested by Kolmogorov-Smirnov goodness of fit test at 5 % level of significance for each of the station.

Depth area duration analysis of short duration rainfalls

Depth Area Duration (DAD) analysis for the extreme rainfall events forms an important step in the hydrological design for the water resources structures. Review of literature reveals that enormous amount of work has been done concerning the DAD analysis for large duration (i.e. one day or more) storms. However, no work is reported so far on this aspect for storms having shorter duration. i.e. less than one day: Hourly rainfall data for 36 rainfall stations have been analysed to develop simple DAD-relationship. This analysis pertains to the catchments of the rivers, namely Ramganga, Gomati, Yamuna and Ghaghara.

Impact of climate change on landslides in Slovenia in the mid-21st century

Slovenia is affected by extreme and intense rainfall that triggers numerous landslides every year, resulting in significant human impact and damage to infrastructure. Previous studies on landslides have shown how rainfall patterns can influence landslide occurrence, while in this paper, we present one of the first study in Slovenia to examine the impact of climate change on landslides in the mid-21st century. To do this, we used the Representative Concentration Pathway (RCP) 4.5 climate scenario and future climatology simulated by six climate models that differed from each other as much as possible while representing measured values of past climate variables as closely as possible. Based on baseline period (1981-2010) we showed the number of days with exceedance of rainfall thresholds and the area where landslides may occur more frequently in the projection period (2041-2070). We found that extreme rainfall events are likely to occur more frequent in the future, which may lead to a higher frequency of landslides in some areas.