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1
Mazurkiewicz, Karolina, and Marcin Skotnicki. "A determination of the synthetic hyetograph parameters for flow capacity assessment concerning stormwater systems." E3S Web of Conferences 45 (2018): 00053. http://dx.doi.org/10.1051/e3sconf/20184500053.
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The paper presents the results of an analysis of the influence of synthetic rainfall duration and location of rainfall intensity peak on the rate of the flood volume in surcharged storm sewers. The analyzed rainfalls had durations from 15 minutes to 180 minutes. It was assumed, that the rainfall peak location would change between the beginning and the end of the rainfall with increments of 10% of the rainfall duration. Outflow simulations were performed with the use of SWMM5.1.012 for three models of real urban catchments with surfaces from 1.6 km2 to 6.7 km2. An assessment of the influence of rainfall parameters was made on the basis of the flood volume rates. Short rainfalls with peaks located at the beginning of rainfall duration do not generate flooding. For other rainfalls it was found that for a specified rainfall duration the flood volume increases with the increase of time of the rainfall peak location. The maximum flood volume varied from 5% to 12% of the total runoff volume, depending on the catchment area, and is generated by the rainfall, whose intensity peak occurs right after the time corresponding to the flow time through the catchment.
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Brychta, Jiří, and Miloslav Janeček. "Determination of erosion rainfall criteria based on natural rainfall measurement and its impact on spatial distribution of rainfall erosivity in the Czech Republic." Soil and Water Research 14, No. 3 (May 27, 2019): 153–62. http://dx.doi.org/10.17221/91/2018-swr.
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Rainfall erosivity is the main factor of the USLE or RUSLE equations. Its accuracy depends on recording precision and its temporal resolution, number of stations and their spatial distribution, length of recorded period, recorded period, erosion rainfall criteria, time step of rainfall intensity and interpolation method. This research focuses on erosion rainfall criteria. A network of 32 ombrographic stations, 1-min temporal resolution rainfall data, 35.6-year period and experimental runoff plots were used. We analysed 8951 rainfalls from ombrographic stations, 100 rainfalls and caused soil losses and runoffs from experimental runoff plots. Main parameter which influenced the number of erosion rainfalls was the precondition AND/OR which determines if conditions of rainfall total (H) have to be fulfilled simultaneously with rainfall intensity (I<sub>15</sub> or I<sub>30</sub>) or not. We proved that if parameters I<sub>15 </sub>> 6.25 mm/15 min AND H > 12.5 mm were fulfilled, then 84.2% of rainfalls caused soil loss > 0.5 t/ha and 73.7% ≥ 1 t/ha. In the case of precondition OR only 44.6% of rainfalls caused soil loss > 0.5 t/ha and 33.9% ≥ 1 t/ha. If the precondition AND was fulfilled, there were on average 75.5 rainfalls, average R factor for each rainfall was 21 MJ/ha·cm/h (without units below in the text, according international unit: 210 MJ/ha·mm/h) and average annual R factor was 45.4. In the case of precondition OR there were on average 279 rainfalls but average R factor for each rainfall was only 9.1 and average annual R factor was 67.4. Therefore if the precondition OR is used, R factor values are overestimated due to a high number of rainfalls with no or very low erosive potential. The resulting overestimated soil losses calculated using USLE/RUSLE subsequently cause an overestimation of financial expenses for erosion-control measures.
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RAGHAVENDRA, V. K. "Trends and periodicities of rainfall in sub-divisions of Maharashtra State." MAUSAM 25, no. 2 (February 7, 2022): 197–210. http://dx.doi.org/10.54302/mausam.v25i2.5194.
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The Maharashtra State of India is divided into four meteorological sub-divisions, viz., Konkan, Madhya Maharashtra, Marathwada and Vidarbha. Of these, Madhya Maharashtra and Marathwada are prone to droughts. The principal rainy season is the monsoon season of June to September when over 80 per cent of the annual rainfall is received. The coefficient of variation is about 20 per cent for the annual and monsoon rainfall except in Marathwada where it is 25 per cent. The annual and monsoon rainfalls follow the normal distribution for their yearly frequencies. In this region the annual and the monsoon rainfall series are highly correlated. In the loss drought prone sub-division of Konkan, the annual and monsoon rainfalls show a 100 year cycle. In all the sub-divisions the successive years' rainfalls are not dependent. The trend as revealed by fitting of orthogonal polynomials is shown as a quadratic curve for the annual and monsoon rainfalls of Konkan and Madhya, Maharashtra, the sub-divisions on either side of the Western Ghats. The low pass filter and Mann-Kendall test against randomness confirmed the trend in Konkan rainfall. The power spectral analysis of the data indicates the existence of long term trend for monsoon rainfall of Konkan, 60 year cycle for the annual rainfall of Konkan and Madhya Maharashtra, 30.year cycle for the annual and monsoon rainfall or Vidarbha, 20-year cycle for the monsoon rainfall of Marathwada, 15-year cycle for the monsoon rainfall of Madhya Maharashtra, 7.5-year cycle for the annual and monsoon rainfall of Marathwada.
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Stefanidis, Stefanos, and Dimitrios Stathis. "Spatial and Temporal Rainfall Variability over the Mountainous Central Pindus (Greece)." Climate 6, no. 3 (September 6, 2018): 75. http://dx.doi.org/10.3390/cli6030075.
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In this study, the authors evaluated the spatial and temporal variability of rainfall over the central Pindus mountain range. To accomplish this, long-term (1961–2016) monthly rainfall data from nine rain gauges were collected and analyzed. Seasonal and annual rainfall data were subjected to Mann–Kendall tests to assess the possible upward or downward statistically significant trends and to change-point analyses to detect whether a change in the rainfall time series mean had taken place. Additionally, Sen’s slope method was used to estimate the trend magnitude, whereas multiple regression models were developed to determine the relationship between rainfall and geomorphological factors. The results showed decreasing trends in annual, winter, and spring rainfalls and increasing trends in autumn and summer rainfalls, both not statistically significant, for most stations. Rainfall non-stationarity started to occur in the middle of the 1960s for the annual, autumn, spring, and summer rainfalls and in the early 1970s for the winter rainfall in most of the stations. In addition, the average magnitude trend per decade is approximately −1.9%, −3.2%, +0.7%, +0.2%, and +2.4% for annual, winter, autumn, spring, and summer rainfalls, respectively. The multiple regression model can explain 62.2% of the spatial variability in annual rainfall, 58.9% of variability in winter, 75.9% of variability in autumn, 55.1% of variability in spring, and 32.2% of variability in summer. Moreover, rainfall spatial distribution maps were produced using the ordinary kriging method, through GIS software, representing the major rainfall range within the mountainous catchment of the study area.
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Jun, Changhyun, Xiaosheng Qin, Yeou-Koung Tung, and Carlo De Michele. "Storm event-based frequency analysis method." Hydrology Research 49, no. 3 (November 9, 2017): 700–710. http://dx.doi.org/10.2166/nh.2017.175.
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Abstract In this study, a storm event-based frequency analysis method was proposed to mitigate the limitations of conventional rainfall depth–duration–frequency (DDF) analysis. The proposed method takes the number, rainfall depth, and duration of rainstorm events into consideration and is advantageous in estimation of more realistic rainfall quantiles for a given return period. For the purpose of hydraulics design, the rainfall depth thresholds are incorporated to retrieve the rainstorm events for estimating design rainfalls. The proposed method was tested against the observed rainfall data from 1961 to 2010 at Seoul, Korea and the computed rainfall quantiles were compared with those estimated using the conventional frequency analysis method. The study results indicated that the conventional method was likely to overestimate the rainfall quantiles for short rainfall durations. It represented that the conventional method could reflect rainfall characteristics of actual rainstorm events if longer durations (like 24 hours) were considered for estimation of design rainfalls.
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Li, Liye, and Fan Zhang. "Hourly and Sub-Hourly Rainfall under Synoptic Patterns during the Anomalous Meiyu Season 2020." Atmosphere 14, no. 4 (April 18, 2023): 727. http://dx.doi.org/10.3390/atmos14040727.
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The 2020 Meiyu season has received extensive attention due to its record-breaking rainfall in the Yangtze–River Huai Basin (YHRB) region of China. Although its rainfall features have been well studied on various time scales, the sub-hourly/hourly rainfall features are unknown. In this study, a wavelet analysis was applied to 1 min rainfall data from 480 national rain gauges across the YHRB, and hourly synoptic patterns during the Meiyu season were grouped using an obliquely rotated principal component analysis in T-mode (PCT). The results suggest that variances on the sub-hourly and hourly scales contributed 63.4% of the 2020 Meiyu rainfall. The hourly synoptic variations in the Meiyu season can be categorized into three major patterns: weak synoptic forcing (P1), a convergence line (P2), and a vortex (P3). The rainfalls under P1 were spatially dispersed over the YHRB and on the shortest time scale, with a 70.4% variance from sub-hourly to hourly rainfalls. P2 had a peak wavelet variance around 30 min–1 h, with rainfalls concentrated to the south of the convergent line. The rainfalls under P3 were locally distributed with a longer duration of around 1–4 h. Compared with the climate mean, hourly rainfall frequencies are indispensable to understanding the 2020 accumulated Meiyu rainfall anomaly. This research highlights the dominant role of synoptic patterns on the temporal and spatial features of the Meiyu rainfall.
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Thompson, S., I. M. Sanni, U. A. Abubakar, and B. S. Sani. "Preliminary Analysis of Daily Rainfall Data from Kano State using Statistical Techniques." October 2022 6, no. 2 (October 1, 2022): 317–24. http://dx.doi.org/10.36263/ijest.2022.02.0366.
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A 35-year annual rainfall was collected from NIMET to determine the Standard Precipitation Index (SPI) and also to study the trend of rainfall parameter in the Kano State, Northern Nigeria. The paper captures the average rainfall (normal rainfall) data for thirty-five years period which implies a rainfall of about 1081.56mm. The positive values (above zero) signify rainfalls that were higher than normal (wet); while the negative values (below zero) imply rainfalls that were lower than normal (dry). From the rainfall anomaly, 18 years (52.9%) recorded wet due to the fact that rainfall occurred in those years were greater than the normal rainfall of 1081.56; while 16 years (47.1%) recorded dry because the rainfalls that occurred in those years were below normal rainfall. In the study, Weilbul method was used to determine the return period in order to predict the year of occurrence of maximum rainfall. In addition, Standard Precipitation Index was used to determine periods of dry, normal or wet temperatures. September 1991 recorded the minimum SPI value of -0.86 (moderately dry), while October 2011 recorded the maximum SPI value of 1.88 (moderately wet). This study is carried out because of the importance of agriculture in the region and to Nigeria at large. Kano state is well known to support food production in the country. Also, the presence of dams further buttresses this study. Dams have many purposes; one is agriculture during dry and wet season. It is observed that the rainfall in the basin has no definite pattern.
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Thompson, S., I. M. Sanni, U. A. Abubakar, and B. S. Sani. "Preliminary Analysis of Daily Rainfall Data from Kano State using Statistical Techniques." October 2022 6, no. 2 (October 1, 2022): 317–24. http://dx.doi.org/10.36263/nijest.2022.02.0366.
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A 35-year annual rainfall was collected from NIMET to determine the Standard Precipitation Index (SPI) and also to study the trend of rainfall parameter in the Kano State, Northern Nigeria. The paper captures the average rainfall (normal rainfall) data for thirty-five years period which implies a rainfall of about 1081.56mm. The positive values (above zero) signify rainfalls that were higher than normal (wet); while the negative values (below zero) imply rainfalls that were lower than normal (dry). From the rainfall anomaly, 18 years (52.9%) recorded wet due to the fact that rainfall occurred in those years were greater than the normal rainfall of 1081.56; while 16 years (47.1%) recorded dry because the rainfalls that occurred in those years were below normal rainfall. In the study, Weilbul method was used to determine the return period in order to predict the year of occurrence of maximum rainfall. In addition, Standard Precipitation Index was used to determine periods of dry, normal or wet temperatures. September 1991 recorded the minimum SPI value of -0.86 (moderately dry), while October 2011 recorded the maximum SPI value of 1.88 (moderately wet). This study is carried out because of the importance of agriculture in the region and to Nigeria at large. Kano state is well known to support food production in the country. Also, the presence of dams further buttresses this study. Dams have many purposes; one is agriculture during dry and wet season. It is observed that the rainfall in the basin has no definite pattern.
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S, Dhamodaran. "Implementing Dynamic Rainfall Prediction Algorithm (DRPA) For Forecasting Rainfall by Analyzing World Rainfall Records." Journal of Advanced Research in Dynamical and Control Systems 12, no. 01-Special Issue (February 13, 2020): 317–23. http://dx.doi.org/10.5373/jardcs/v12sp1/20201078.
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Rahardjo, H., T. T. Lee, E. C. Leong, and R. B. Rezaur. "Response of a residual soil slope to rainfall." Canadian Geotechnical Journal 42, no. 2 (April 1, 2005): 340–51. http://dx.doi.org/10.1139/t04-101.
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Rainfall-induced landslides are a common problem in residual soil slopes of the tropics. It is widely known that rainfall-induced slope failures are mainly caused by infiltration of rainwater; however, the response of a residual soil slope to infiltration is not fully understood. The difficulties lie in the quantification of the flux boundary condition across the slope surface with respect to infiltration and its effect on the pore-water pressure conditions in the slope. Therefore, it is important to understand the response of a slope to different rainfall conditions and the resulting changes in pore-water pressures and water contents. A residual soil slope in Singapore was instrumented with pore-water pressure, water content, and rainfall measuring devices, and studies were carried out under natural and simulated rainfalls. Results indicate that significant infiltration may occur in a residual soil slope during a rainfall. Small total rainfalls can contribute a larger infiltration percentage than large total rainfalls. The percentage of infiltration usually decreases with increasing total rainfalls. The study has indicated the existence of a threshold rainfall of about 10 mm for runoff generation to commence. Infiltration during wet periods may lead to the development of positive pore-water pressures as a consequence of a perched water table condition. Matric suctions are recovered gradually during dry periods due to redistribution. Soil water contents tend to be higher near the toe of the slope than at the crest irrespective of rainfall events, indicating subsurface movement of water in the downslope direction. The study has also indicated a correlation between rainfall amount and relative increase in pore-water pressure. The results can be used to quantify the flux boundary conditions required for the seepage analyses associated with rainfall-induced slope failures.Key words: infiltration, pore-water pressure, water content, residual soil, rainfall-induced slope failures.
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Nguyen, V.-T.-V., T. D. Nguyen, and F. Ashkar. "Regional frequency analysis of extreme rainfalls." Water Science and Technology 45, no. 2 (January 1, 2002): 75–81. http://dx.doi.org/10.2166/wst.2002.0030.
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This study proposes two alternative methods for estimating the distribution of extreme rainfalls for sites where rainfall data are available (gaged sites) and for locations without data (ungaged sites). The first method deals with the estimation of short-duration rainfall extremes from available rainfall data for longer durations using the “scale-invariance” concept to account for the relationship between statistical properties of extreme rainfall processes for different time scales. The second method is concerned with the estimation of extreme rainfalls for ungaged sites. This method relies on a new definition of homogeneous sites. Results of the numerical application using data from a network of 10 recording rain gauges in Quebec (Canada) indicate that the proposed methods are able to provide extreme rainfall estimates that are comparable with those based on observed at-site rainfall data.
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Tayşi, H., and M. Özger. "Disaggregation of future GCMs to generate IDF curves for the assessment of urban floods." Journal of Water and Climate Change 13, no. 2 (October 29, 2021): 684–706. http://dx.doi.org/10.2166/wcc.2021.241.
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Abstract Urbanization and industrialization cause an increase in greenhouse gas emissions, which in turn causes changes in the atmosphere. Climate change is causing extreme rainfalls and these rainfalls are getting stronger day after day. Floods are threatening urban areas, and short-duration rainfall and outdated drainages are responsible for urban floods. Intensity–Duration–Frequency (IDF) curves are crucial for both drainage system design and assessment of flood risk. Once IDF curves are determined from historical data, they are assumed to be stationary. However, IDF curves must be non-stationary and time varying based on preparation for extreme events. This study generates future IDF curves with short-duration rainfalls under climate change. To represent future rainfall, an ensemble of four Global Climate Models generated under Representative Concentration Pathways (RCP) 4.5 and 8.5 were used in this study. A new approach to the HYETOS disaggregation model was applied to disaggregate daily future rainfall into sub-hourly using disaggregation parameters of hourly measured rainfalls. Hence, sub-hourly future rainfalls will be obtained capturing historical rainfall patterns instead of random rainfall characteristics. Finally, historical and future IDF curves were compared. The study concludes that increases in short-duration rainfalls will be highly intensified in both the near and distant futures with a high probability.
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Van Nguyen, Van-Thanh, and Ganesh Raj Pandey. "Estimation of Short-Duration Rainfall Distribution Using Data Measured at Longer Time Scales." Water Science and Technology 29, no. 1-2 (January 1, 1994): 39–45. http://dx.doi.org/10.2166/wst.1994.0649.
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An investigation on how to estimate the distribution of short-duration (hours or shorter) rainfalls based on available daily rainfall measurements was undertaken. On the basis of the theory of multifractal multiplicative cascades, a scale-independent mathematical model was proposed to represent the probability distribution of rainfalls at various time scales. Using rainfall records from a network of seven recording gauges in the Montreal region in Quebec (Canada), it was found that the proposed model could provide adequate estimates of the distribution of hourly rainfalls at locations where these short-duration rainfall data are not available. Further, it has been observed that one single regional model can be developed to describe the scaling nature of rainfall distributions within the whole study area.
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Kobayashi, Kenichiro, Shigenori Otsuka, and Kazuo Saito. "Ensemble flood simulation for a small dam catchment in Japan using 10 and 2 km resolution nonhydrostatic model rainfalls." Natural Hazards and Earth System Sciences 16, no. 8 (August 9, 2016): 1821–39. http://dx.doi.org/10.5194/nhess-16-1821-2016.
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Abstract. This paper presents a study on short-term ensemble flood forecasting specifically for small dam catchments in Japan. Numerical ensemble simulations of rainfall from the Japan Meteorological Agency nonhydrostatic model (JMA-NHM) are used as the input data to a rainfall–runoff model for predicting river discharge into a dam. The ensemble weather simulations use a conventional 10 km and a high-resolution 2 km spatial resolutions. A distributed rainfall–runoff model is constructed for the Kasahori dam catchment (approx. 70 km2) and applied with the ensemble rainfalls. The results show that the hourly maximum and cumulative catchment-average rainfalls of the 2 km resolution JMA-NHM ensemble simulation are more appropriate than the 10 km resolution rainfalls. All the simulated inflows based on the 2 and 10 km rainfalls become larger than the flood discharge of 140 m3 s−1, a threshold value for flood control. The inflows with the 10 km resolution ensemble rainfall are all considerably smaller than the observations, while at least one simulated discharge out of 11 ensemble members with the 2 km resolution rainfalls reproduces the first peak of the inflow at the Kasahori dam with similar amplitude to observations, although there are spatiotemporal lags between simulation and observation. To take positional lags into account of the ensemble discharge simulation, the rainfall distribution in each ensemble member is shifted so that the catchment-averaged cumulative rainfall of the Kasahori dam maximizes. The runoff simulation with the position-shifted rainfalls shows much better results than the original ensemble discharge simulations.
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Kobayashi, K., S. Otsuka, and K. Saito. "Ensemble flood forecasting to support dam water release operation using 10 and 2 km-resolution JMA Nonhydrostatic Model ensemble rainfalls." Natural Hazards and Earth System Sciences Discussions 3, no. 12 (December 18, 2015): 7411–56. http://dx.doi.org/10.5194/nhessd-3-7411-2015.
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Abstract. This paper presents a study on short-term ensemble flood forecasting specifically for small dam catchments in Japan. Numerical ensemble simulations of rainfall from the Japan Meteorological Agency Nonhydrostatic Model are used as the input data to a rainfall–runoff model for predicting river discharge into a dam. The ensemble weather simulations use a conventional 10 km and a high-resolution 2 km spatial resolution. A distributed rainfall–runoff model is constructed for the Kasahori dam catchment (approx. 70 km2) and applied with the ensemble rainfalls. The results show that the hourly maximum and cumulative catchment-average rainfalls of the 2 km-resolution JMA-NHM ensemble simulation are more appropriate than the 10 km-resolution rainfalls. All the simulated inflows based on the 2 and 10 km rainfalls become larger than the flood discharge of 140 m3 s−1; a threshold value for flood control. The inflows with the 10 km-resolution ensemble rainfall are all considerably smaller than the observations, while, at least one simulated discharge out of 11 ensemble members with the 2 km-resolution rainfalls reproduces the first peak of the inflow at the Kasahori dam with similar amplitude to observations, although there are spatiotemporal lags between simulation and observation. To take positional lags into account of the ensemble discharge simulation, the rainfall distribution in each ensemble member is shifted so that the catchment-averaged cumulative rainfall of the Kasahori dam maximizes. The runoff simulation with the position-shifted rainfalls show much better results than the original ensemble discharge simulations.
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Yu, Yang, Keisuke Kojima, Kyoungjin An, and Hiroaki Furumai. "Cluster analysis for characterization of rainfalls and CSO behaviours in an urban drainage area of Tokyo." Water Science and Technology 68, no. 3 (August 1, 2013): 544–51. http://dx.doi.org/10.2166/wst.2013.253.
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Combined sewer overflow (CSO) from urban areas is recognized as a major pollutant source to the receiving waters during wet weather. This study attempts to categorize rainfall events and corresponding CSO behaviours to reveal the relationship between rainfall patterns and CSO behaviours in the Shingashi urban drainage areas of Tokyo, Japan where complete service by a combined sewer system (CSS) and CSO often takes place. In addition, outfalls based on their annual overflow behaviours were characterized for effective storm water management. All 117 rainfall events recorded in 2007 were simulated by a distributed model InfoWorks CS to obtain CSO behaviours. The rainfall events were classified based on two sets of parameters of rainfall pattern as well as CSO behaviours. Clustered rainfall and CSO groups were linked by similarity analysis. Results showed that both small and extreme rainfalls had strong correlations with the CSO behaviours, while moderate rainfall had a weak relationship. This indicates that important and negligible rainfalls from the viewpoint of CSO could be identified by rainfall patterns, while influences from the drainage area and network should be taken into account when estimating moderate rainfall-induced CSO. Additionally, outfalls were finally categorized into six groups indicating different levels of impact on the environment.
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Manike, M. M. A. P., and M. Rajendran. "Analysis of Rainfall Distribution in Kurunegala District, Sri Lanka." Asian Journal of Research in Agriculture and Forestry 10, no. 1 (February 12, 2024): 48–60. http://dx.doi.org/10.9734/ajraf/2024/v10i1268.
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Investigating the dynamics of rainfall has become very crucial in managing water resources efficiently for sustainable development. The present study aimed to analyze the rainfall distribution in Kurunegala district. Historical rainfall data collected from four gauging stations were subjected to both mathematical and statistical analysis. In addition, trends of rainfall, probability of exceedance and meteorological drought conditions were studied. Rainfall distribution in the district shows high variations. Bathalagoda records the highest mean annual rainfall of 1843 mm. The corresponding values for Wariyapola, Mediyawa and Siyambalagamuwa are 1629 mm, 1315 mm and 1222 mm, respectively. Rainfall is concentrated only in certain months in a year. Annual rainfall exceedance at 50% probability is 1825 mm at Bathalagoda. The corresponding figures for Wariyapola, Mediyawa and Siyambalagamuwa are 1662 mm, 1284 mm and 1226 mm, respectively. Mediyawa, Wariyapola, and Siyambalagamuwa show a decreasing trend in annual rainfall while Bathalagoda shows an increasing trend. Southwest monsoonal (SWM) and 2nd inter-monsoonal (IM2) rainfalls show a decreasing trend at all gauging stations. Mediyawa and Bathalagoda show a positive trend in both 1st inter-monsoonal (IM1) and Northeast monsoonal (NEM) rainfalls. A negative trend in Maha seasonal rainfall is observed in all regions except Bathalagoda. A positive trend of Yala seasonal rainfall is observed at Mediyawewa and Bathalogoda. Further, severe drought conditions were experienced in the recent years at Wariyapola, Mediyawa, and Siyambalagamuwa. Compared to other regions, rainfall at Mediyawa and Siyambalagamuwa highly deviates from the long-term mean. In the study area, rainfall distribution shows a cyclic pattern over time. However, the amount of rainfall received in the recent years is lower than the amount received in the immediate past decade at all stations except Bathalagoda. Hence, proper management decisions based on rainfall distribution patterns is vital for the efficient management of water resources while guaranteeing sustainable agricultural production in this district.
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Alhamshry, Asmaa, Ayele Almaw Fenta, Hiroshi Yasuda, Reiji Kimura, and Katsuyuki Shimizu. "Seasonal Rainfall Variability in Ethiopia and Its Long-Term Link to Global Sea Surface Temperatures." Water 12, no. 1 (December 21, 2019): 55. http://dx.doi.org/10.3390/w12010055.
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Investigating the influence of sea surface temperatures (SSTs) on seasonal rainfall is a crucial factor for managing Ethiopian water resources. For this purpose, SST and rainfall data were used to study a wide range of inhomogeneous areas in Ethiopia with uneven distribution of rainfall for both summer (1951–2015) and spring (1951–2000) seasons. Firstly, a preliminary subdivision of rainfall grid points into zones was applied depending on spatial homogeneity and seasonality of rainfall. This introduced new clusters, including nine zones for summer rainfall peak (July/August) and five zones for spring rainfall peak (April/May). Afterward, the time series for each zone was derived by calculating the rainfall averaged over grid points within the zone. Secondly, the oceanic regions that significantly correlated with the Ethiopian rainfall were identified through cross-correlations between rainfalls averaged over every homogeneous zone and the monthly averaged SST. For summer rainfall as a main rainy season, the results indicated that the Gulf of Guinea and southern Pacific Ocean had a significant influence on rainfall zones at a lag time of 5–6 and 6–7 months. Besides, for summer rainfall zones 8 and 9 at lag time 5–6 months, the common SST regions of the southern Pacific Ocean showed the opposite sense of positive and negative correlations. Thus, the difference in SSTs between the two regions was more strongly correlated (r ≥ 0.46) with summer rainfall in both zones than others. For the spring season, the results indicated that SST of the northern Atlantic Ocean had a strong influence on spring rainfall zones (3 and 5) at a lag time 6–7 months, as indicated by a significant correlation (r ≥ −0.40). Therefore, this study suggests that SSTs of southern Pacific and northern Atlantic oceans can be used as effective inputs for prediction models of Ethiopian summer and spring rainfalls, respectively.
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Takahashi, H. G. "Seasonal changes in diurnal rainfall cycle over and around the Indochina Peninsula observed by TRMM-PR." Advances in Geosciences 25 (March 8, 2010): 23–28. http://dx.doi.org/10.5194/adgeo-25-23-2010.
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Abstract. This study used TRMM-PR data to examine seasonal changes in rainfall characteristics over the Indochina Peninsula, with a focus on the diurnal rainfall cycle. No distinct seasonal changes in the phases of diurnal variations of rainfall were found, even though low-level wind fields changed largely with the seasonal march. Regions with an afternoon maximum received large amounts of rainfall during the pre-monsoon season, whereas regions with a nocturnal or morning rainfall maximum received little rainfall during the pre-monsoon season. This result suggests that the difference in diurnal rainfall variations may be associated with the regional differences in seasonal march of monsoon rainfall over and around the Indochina Peninsula, through the different mechanism between evening and morning rainfalls.
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Mekanik, F., and M. A. Imteaz. "Variability of cool seasonal rainfall associated with Indo-Pacific climate modes: case study of Victoria, Australia." Journal of Water and Climate Change 9, no. 3 (February 22, 2018): 584–97. http://dx.doi.org/10.2166/wcc.2018.146.
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Abstract This study focused on diagnosing the relative and independent role of El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) on austral cool seasonal rainfall by stratifying the cool seasonal rainfall into winter (June–August) and spring (September–November). Partial regression and classification analysis was used to investigate the effect of the climate modes on rainfall in the state of Victoria in southeast Australia. Partial regression analyses revealed that when the influence of IOD is removed from ENSO, sea surface temperature (SST) anomalies in the Pacific Ocean have no significant effect on spring rainfall across Victoria and affect winter rainfall mildly in west Victoria. By removing the inter-correlations between ENSO and IOD, SST anomalies in the Indian Ocean and SLP anomalies in the Pacific Ocean showed weak relationships with Victoria's spring and winter rainfall. Classification analysis demonstrated the effects of phases of ENSO and IOD on Victoria's seasonal rainfall; the dry phases of the climate modes have more effect on spring rainfall compared to the wet phases and both show no significant effect on winter rainfalls. It is recommended that for water availability forecasting in Victoria, water managers should focus on the effect of climate modes on spring rainfalls, particularly during the dry phases of ENSO and IOD.
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Liao, Yifan, Bingzhang Lin, Xiaoyang Chen, and Hui Ding. "A New Look at Storm Separation Technique in Estimation of Probable Maximum Precipitation in Mountainous Areas." Water 12, no. 4 (April 20, 2020): 1177. http://dx.doi.org/10.3390/w12041177.
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Storm separation is a key step when carrying out storm transposition analysis for Probable Maximum Precipitation (PMP) estimation in mountainous areas. The World Meteorological Organization (WMO) has recommended the step-duration-orographic-intensification-factor (SDOIF) method since 2009 as an effective storm separation technique to identify the amounts of precipitation caused by topography from those caused by atmospheric dynamics. The orographic intensification factors (OIFs) are usually developed based on annual maximum rainfall series under such assumption that the mechanism of annual maximum rainfalls is close to that of the PMP-level rainfall. In this paper, an alternative storm separation technique using rainfall quantiles, instead of annual maximum rainfalls, with rare return periods estimated via Regional L-moments Analysis (RLMA) to calculate the OIFs is proposed. Based on Taiwan’s historical 4- and 24-h precipitation data, comparisons of the OIFs obtained from annual maximum rainfalls with that from extreme rainfall quantiles at different return periods, as well as the PMP estimates of Hong Kong from transposing the different corresponding separated nonorographic rainfalls, were conducted. The results show that the OIFs obtained from rainfall quantiles with certain rare probabilities are more stable and reasonable in terms of stability and spatial distribution pattern.
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Huang, Ching-Yuang, Cher-Wei Chou, Shu-Hua Chen, and Jia-Hong Xie. "Topographic Rainfall of Tropical Cyclones past a Mountain Range as Categorized by Idealized Simulations." Weather and Forecasting 35, no. 1 (December 31, 2019): 25–49. http://dx.doi.org/10.1175/waf-d-19-0120.1.
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Abstract Topographic rainfall induced by westbound tropical cyclones past an island mountain is investigated using an idealized Weather Research and Forecasting (WRF) Model. Idealized simulations with varying vortex core size R (100–250 km), vortex intensity Vmax (20–35 m s−1), and steering wind speed U (4–10 m s−1) are conducted. The results show that the geometric distributions of major rainfall over the island are not greatly sensitive to cloud microphysics schemes using either single momentum or double momentum. Major rainfall is produced over northeastern and southwestern slopes of the mountain for smaller U. As U is doubled, the rainfall, however, is considerably weakened or is present only over southwestern slopes. For smaller U, a bifurcation of island rainfall with a sudden change in intensity or geometric shifting exists within a tiny range of R or Vmax. When the bifurcation occurs with small track deviations, geometric distributions of major rainfall are also more sensitive to cloud microphysics schemes. Such formation of bifurcation or double-peak rainfall, however, is significantly reduced when the terrain size is doubled. Systematic experiments are conducted to relate the topographical rainfalls over the northern half, southern half, and the whole of the mountain slopes to varying R, Vmax, and U. Larger U tends to produce much larger southern rainfall than northern rainfall. The average and maximum rainfalls generally increase with increased Vmax, except for large R. The decrease of average rainfall and maximum rainfall with increased U is more evident for smaller R, while not necessarily true for larger R.
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Back, Álvaro José, José Luiz Rocha Oliveira, and Alan Henn. "Duration-frequency relationships of heavy rainfall in Santa Catarina, Brazil." Revista Brasileira de Ciência do Solo 36, no. 3 (June 2012): 1015–22. http://dx.doi.org/10.1590/s0100-06832012000300031.
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The purpose of this study was to adjust equations that establish relationships between rainfall events with different duration and data from weather stations in the state of Santa Catarina, Brazil. In this study, the relationships between different duration heavy rainfalls from 13 weather stations of Santa Catarina were analyzed. From series of maximum annual rainfalls, and using the Gumbel-Chow distribution, the maximum rainfall for durations between 5 min and 24 h were estimated considering return periods from 2 to 100 years. The data fit to the Gumbel-Chow model was verified by the Kolmogorov-Smirnov test at 5 % significance. The coefficients of Bell's equation were adjusted to estimate the relationship between rainfall duration t (min) and the return period T (y) in relation to the maximum rainfall with a duration of 1 hour and a 10 year return period. Likewise, the coefficients of Bell's equation were adjusted based on the maximum rainfall with a duration of 1 day and a 10 year return period. The results showed that these relationships are viable to estimate short-duration rainfall events at locations where there are no rainfall records.
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Su, Yan, Jun Bing Qiu, and Yue Ting Du. "Rainfall Threshold of Rainfall-Induced Landslides Based on Laboratory Test." Applied Mechanics and Materials 353-356 (August 2013): 1011–14. http://dx.doi.org/10.4028/www.scientific.net/amm.353-356.1011.
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A landslide model test under the artificial rainfall was built according to the rainfll-induced landslide in Fujian mountainous area. The rainfall intensity, the slope types (mainly on vegetation coverage) and the grade of side slope were the main factors in the test. The rainfall threshold of rainfall-induced landslide on shallow bedrock was obtained from the test. The relationship between the cumulative precipitation and slope angle and slope surface types was analyzed from the orthogonal experiment by multiple regression analysis. Results show that most slope failures are caused by the infiltration of rainwater. Conclusion show that when the slope angle and vegetation cover are given, critical hazard threshold can be predicted, and the corresponding landslide sliding time can be gained by combining with the rainfall intensity.
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Pham, Quoc, Tao-Chang Yang, Chen-Min Kuo, Hung-Wei Tseng, and Pao-Shan Yu. "Combing Random Forest and Least Square Support Vector Regression for Improving Extreme Rainfall Downscaling." Water 11, no. 3 (March 3, 2019): 451. http://dx.doi.org/10.3390/w11030451.
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A statistical downscaling approach for improving extreme rainfall simulation was proposed to predict the daily rainfalls at Shih-Men Reservoir catchment in northern Taiwan. The structure of the proposed downscaling approach is composed of two parts: the rainfall-state classification and the regression for rainfall-amount prediction. Predictors of classification and regression methods were selected from the large-scale climate variables of the NCEP reanalysis data based on statistical tests. The data during 1964–1999 and 2000–2013 were used for calibration and validation, respectively. Three classification methods, including linear discriminant analysis (LDA), random forest (RF), and support vector classification (SVC), were adopted for rainfall-state classification and their performances were compared. After rainfall-state classification, the least square support vector regression (LS-SVR) was used for rainfall-amount prediction for different rainfall states. Two rainfall states (i.e., dry day and wet day) and three rainfall states (dry day, non-extreme-rainfall day, and extreme-rainfall day) were defined and compared for judging their downscaling performances. The results show that RF outperforms LDA and SVC for rainfall-state classification. Using RF for three-rainfall-states classification and LS-SVR for rainfall-amount prediction can improve the extreme rainfall downscaling.
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Ma, Yichun, Zhongwu Li, Liang Tian, Yifan Yang, Wenqing Li, Zijuan He, Xiaodong Nie, and Yaojun Liu. "Erosion of Granite Red Soil Slope and Processes of Subsurface Flow Generation, Prediction, and Simulation." International Journal of Environmental Research and Public Health 20, no. 3 (January 24, 2023): 2104. http://dx.doi.org/10.3390/ijerph20032104.
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A deeper understanding of the rainfall–flow processes can improve the knowledge of the rain-driven erosional processes in coarse-textured agricultural soil. In this study, on the red soil slope farmland developed from weathered granite, a simulated rainfall experiment was conducted to study the characteristics of rainfall redistribution, the processes of surface–subsurface flow generation and prediction, and sediment production. Rainfalls with three intensities of 45, 90, and 135 mm h−1 with a duration of 90 min were applied to the weathered granite red soil with the slope gradient of 10°. Under 45 mm h−1 rainfall intensity, the output of rainwater was composed by subsurface flow and bottom penetration, accounting for 35.80% and 39.01% of total rainfall, respectively. When the rainfall intensities increased to 90 and 135 mm h−1, the surface flow became the main output of rainwater, accounting for 83.94% and 92.42%, respectively. Coarsened soil exhibited strong infiltration-promoting but poor water-storage capacities under light rainfalls. With an increased rainfall intensity, the surface flow coefficient increased from 19.87% to 92.42%, while the amount of subsurface flow and bottom penetration decreased by 1.3 and 6.2 L, respectively. For sediment production, the sediment concentration was raised from 1.39 to 7.70 g L−1, and D10, D50, and D90 increased by 1.50, 1.83, and 1.40 times, respectively. The content of coarse particles (>1 mm) in surface soil increased by 12%, while the content of fine particles (<0.5 mm) decreased by 9.6%. Under strong rainfalls, severe soil and water loss, coarsening soil surface, and large loss of fine particles became major problems. During rainfall, the subsurface flow and bottom penetration could be predicted well through quadratic equations of rainfall time, which transformed into time-dependent exponential functions after rainfall. The results provide a theoretical basis and data reference for soil erosion prevention and water management in coarse-textured agricultural lands.
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Yilmaz, A. G., I. Hossain, and B. J. C. Perera. "Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne." Hydrology and Earth System Sciences 18, no. 10 (October 15, 2014): 4065–76. http://dx.doi.org/10.5194/hess-18-4065-2014.
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Abstract. The increased frequency and magnitude of extreme rainfall events due to anthropogenic climate change, and decadal and multi-decadal climate variability question the stationary climate assumption. The possible violation of stationarity in climate can cause erroneous estimation of design rainfalls derived from extreme rainfall frequency analysis. This may result in significant consequences for infrastructure and flood protection projects since design rainfalls are essential input for design of these projects. Therefore, there is a need to conduct frequency analysis of extreme rainfall events in the context of non-stationarity, when non-stationarity is present in extreme rainfall events. A methodology consisting of threshold selection, extreme rainfall data (peaks over threshold data) construction, trend and non-stationarity analysis, and stationary and non-stationary generalised Pareto distribution (GPD) models was developed in this paper to investigate trends and non-stationarity in extreme rainfall events, and potential impacts of climate change and variability on intensity–frequency–duration (IFD) relationships. The methodology developed was successfully implemented using rainfall data from an observation station in Melbourne (Australia) for storm durations ranging from 6 min to 72 h. Although statistically significant trends were detected in extreme rainfall data for storm durations of 30 min, 3 h and 48 h, statistical non-stationarity tests and non-stationary GPD models did not indicate non-stationarity for these storm durations and other storm durations. It was also found that the stationary GPD models were capable of fitting extreme rainfall data for all storm durations. Furthermore, the IFD analysis showed that urban flash flood producing hourly rainfall intensities have increased over time.
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Yilmaz, A. G., I. Hossain, and B. J. C. Perera. "Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne." Hydrology and Earth System Sciences Discussions 11, no. 6 (June 16, 2014): 6311–42. http://dx.doi.org/10.5194/hessd-11-6311-2014.
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Abstract. The increased frequency and magnitude of extreme rainfall events due to anthropogenic climate change, and decadal and multi-decadal climate variability question the stationary climate assumption. The possible violation of stationarity in climate can cause erroneous estimation of design rainfalls derived from extreme rainfall frequency analysis. This may result in significant consequences for infrastructure and flood protection projects since design rainfalls are essential input for design of these projects. Therefore, there is a need to conduct frequency analysis of extreme rainfall events in the context of non-stationarity, when non-stationarity is present in extreme rainfall events. A methodology consisting of, threshold selection, extreme rainfall data (peaks over threshold data) construction, trend and non-stationarity analysis, and stationary and non-stationary Generalized Pareto Distribution (GPD) models was developed in this paper to investigate trends and non-stationarity in extreme rainfall events, and potential impacts of climate change and variability on Intensity–Frequency–Duration (IFD) relationships. The developed methodology was successfully implemented using rainfall data from an observation station in Melbourne (Australia) for storm durations ranging from 6 min to 72 h. Although statistically significant trends were detected in extreme rainfall data for storm durations of 30 min, and 3 and 48 h, statistical non-stationarity tests and non-stationary GPD models did not indicate non-stationarity for these storm durations and other storm durations. It was also found that the stationary GPD models were capable of fitting extreme rainfall data for all storm durations. Furthermore, the IFD analysis showed that urban flash flood producing hourly rainfall intensities have increased over time.
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Islam, Md Nazrul, Someshwar Das, and Hiroshi Uyeda. "Calibration of TRMM Derived Rainfall Over Nepal During 1998-2007." Open Atmospheric Science Journal 4, no. 1 (January 19, 2010): 12–23. http://dx.doi.org/10.2174/1874282301004010012.
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In this study rainfall is calculated from Tropical Rainfall Measuring Mission (TRMM) Version 6 (V6) 3B42 datasets and calibrated with reference to the observed daily rainfall by rain-gauge collected at 15 locations over Nepal during 1998-2007. In monthly, seasonal and annual scales TRMM estimated rainfalls follow the similar distribution of historical patterns obtained from the rain-gauge data. Rainfall is large in the Southern parts of the country, especially in the Central Nepal. Day-to-day rainfall comparison shows that TRMM derived trend is very similar to the observed data but TRMM usually underestimates rainfall on many days with some exceptions of overestimation on some days. The correlation coefficient of rainfalls between TRMM and rain-gauge data is obtained about 0.71. TRMM can measure about 65.39% of surface rainfall in Nepal. After using calibration factors obtained through regression expression the TRMM estimated rainfall over Nepal becomes about 99.91% of observed data. TRMM detection of rainy days is poor over Nepal; it can approximately detect, under-detect and over-detect by 19%, 72% and 9% of stations respectively. False alarm rate, probability of detection, threat score and skill score are calculated as 0.30, 0.68, 0.53 and 0.55 respectively. Finally, TRMM data can be utilized in measuring mountainous rainfall over Nepal but exact amount of rainfall has to be calculated with the help of adjustment factors obtained through calibration procedure. This preliminary work is the preparation of utilization of Global Precipitation Measurement (GPM) data to be commencing in 2013.
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Yuan, Weihua, Rucong Yu, Minghua Zhang, Wuyin Lin, Jian Li, and Yunfei Fu. "Diurnal Cycle of Summer Precipitation over Subtropical East Asia in CAM5." Journal of Climate 26, no. 10 (May 8, 2013): 3159–72. http://dx.doi.org/10.1175/jcli-d-12-00119.1.
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Abstract The simulations of summertime diurnal cycle of precipitation and low-level winds by the Community Atmosphere Model, version 5, are evaluated over subtropical East Asia. The evaluation reveals the physical cause of the observed diurnal rainfall variation in East Asia and points to the source of model strengths and weaknesses. Two model versions with horizontal resolutions of 2.8° and 0.5° are used. The models can reproduce the diurnal phase of large-scale winds over East Asia, with an enhanced low-level southwesterly in early morning. Correspondingly, models successfully simulated the diurnal variation of stratiform rainfall with a maximum in early morning. However, the simulated convective rainfall occurs at local noontime, earlier than observations and with larger amplitude (normalized by the daily mean). As a result, models simulated a weaker diurnal cycle in total rainfall over the western plain of China due to an out-of-phase cancellation between convective and stratiform rainfalls and a noontime maximum of total rainfall over the eastern plain of China. Over the East China Sea, models simulated the early-morning maximum of convective precipitation and, together with the correct phase of the stratiform rainfall, they captured the diurnal cycle of total precipitation. The superposition of the stratiform and convective rainfalls also explains the observed diurnal cycle in total rainfall in East Asia. Relative to the coarse-resolution model, the high-resolution model simulated slight improvement in diurnal rainfall amplitudes, due to the larger amplitude of stratiform rainfall. The two models, however, suffer from the same major biases in rainfall diurnal cycles due to the convection parameterization.
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Ng, C. WW, B. Wang, and Y. K. Tung. "Three-dimensional numerical investigations of groundwater responses in an unsaturated slope subjected to various rainfall patterns." Canadian Geotechnical Journal 38, no. 5 (October 1, 2001): 1049–62. http://dx.doi.org/10.1139/t01-057.
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Three-dimensional (3D) numerical analyses were conducted to investigate groundwater responses in an initially unsaturated cut slope at Lai Ping Road in Hong Kong subjected to rainfalls with various patterns, durations, and return periods. Initial and boundary conditions were established from field monitoring data. The computed results show that rainfall pattern has a significant influence on pore-water pressures in soil layers near the ground surface but its influence gradually diminishes with depth. Rainfall with an advanced storm pattern of 24 h duration was found to be the most critical because it results in the highest pore-water pressure in the slope. At a given depth, the influence of rainfall pattern on pore-water pressures depends on the initial groundwater conditions: the higher the initial water table, the smaller the influence of rainfall pattern on pore-water pressures. Under a given rainfall duration, the rise of pore-water pressure at the study site is significant only when the return period increases from 10 years to 100 years, but not from 100 years to 1000 years. Short-duration, intense rainfall causes larger variations in pore-water pressure at shallow depths, whereas long-duration rainfall has a greater influence on groundwater in deep soils because of the generally greater amount of rainfall. For prolonged rainfalls, the difference in pore-water pressure distribution resulting from different rainfall patterns is less significant than that from short-duration, intense rainfalls.Key words: Lai Ping Road, rainfall patterns, pore-water pressure distributions, suction, unsaturated slope.
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Back, Álvaro J., Augusto C. Pola, Nilzo I. Ladwig, and Hugo Schwalm. "Erosive rainfall in the Rio do Peixe Valley in Santa Catarina, Brazil: Part II - Characteristics and temporal distribution pattern." Revista Brasileira de Engenharia Agrícola e Ambiental 21, no. 11 (November 2017): 780–84. http://dx.doi.org/10.1590/1807-1929/agriambi.v21n11p780-784.
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ABSTRACT Exploring the characteristics of erosive rain is an important aspect of studying erosive processes, and it allows researchers to create more natural and realistic hydrological simulations. The objective of this study was to analyse the characteristics of erosive rain and to determine the temporal distribution pattern of erosive rainfall in the Valley of Rio do Peixe in the state of Santa Catarina, Brazil. Daily pluviograms from the meteorological stations located in the cities Campos Novos, Videira, and Caçador in Santa Catarina from 1984 to 2014 were utilized for this study. By studying rainfall that is classified as erosive, the values of kinetic energy, maximum intensity in thirty minutes, and the value of EI30 erosivity index were determined. The rainfall was also classified according to the temporal distribution of rainfall in advanced, intermediate, and delayed patterns. Erosive rainfalls occur at a frequency of 53.3% advanced, 31.1% intermediate, and 15.6% delayed patterns. Erosive rainfall has an average precipitation amount of 25.5 mm, duration of 11.1 h, kinetic energy of 5.6 MJ ha-1, maximum intensity of 30 min of 17.7 mm h-1, and erosivity of 206.4 MJ mm ha-1 h-1. The highest frequency of erosive rainfall occurred in rainfalls lasting from 6 to 12 h (36.1%), followed by rainfalls lasting from 4 to 6 h (22.4%).
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Singh, Vishal, and Xiaosheng Qin. "Rainfall variability in Malay Peninsula region of Southeast Asia using gridded data." E3S Web of Conferences 81 (2019): 01002. http://dx.doi.org/10.1051/e3sconf/20198101002.
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Southeast Asia is recognized as a climate-change vulnerable region as it has been significantly affected by many extreme events in the past. This study carried out a rainfall analysis over the Malay Peninsula region of Southeast Asia utilizing historical (1981-2007) gridded rainfall datasets (0.5°×0.5°). The rainfall variability was analyzed in an intra-decadal time series duration. The uncertainty involved in all datasets was also checked based on the comparison of multiple global rainfall datasets. Rainfall gap filling analysis was conducted for producing more accurate rainfall time series after testing multiple mathematical functions. Frequency-based rainfall extreme indices such as Dry Days and Wet days are generated to assess the rainfall variability over the study area. Our results revealed a notable variation existed in the rainfalls over Malay Peninsula as per the long historical duration (1981-2007).
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Park, Joon-Young, Seung-Rae Lee, Seboong Oh, Jung Hyun Lee, Jun-Seo Jeon, Young-Suk Song, and Hyun-Su Park. "Critical Continuous Rainfall Map for Forecasting Shallow Landslide Initiations in Busan, Korea." Water 12, no. 9 (August 27, 2020): 2404. http://dx.doi.org/10.3390/w12092404.
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In recent years, precipitation patterns in Korea have shifted to be characterized as short and intense rainfalls. In consideration of shallow landslide initiations primarily governed by heavy rainfalls at short-time scales that diminish drainage effects, the concept of critical continuous rainfall is proposed as a single-rainfall-variable threshold for shallow landslide forecasting. To generate a critical continuous rainfall map for hillslope areas in a city of Korea (Busan), this study designed and applied a systematic modeling process. As a preparatory stage, input datasets of geo-hydraulic properties and geotechnical properties were assembled using estimation techniques based on experiment data of field samples. The inherent and fixed critical continuous rainfall values for hillslope areas in Busan were derived through one-dimensional infiltration analysis coupled with infinite slope stability calculations. As a result of a detailed analysis of historical rainfall records in a case study area over a period of 11 years, three false forecasting cases were recorded, whereas all landslide-triggering rainfall events were correctly captured with no missed forecasting cases. The results of the case study indicate that the proposed critical continuous rainfall may be useful as an effective and straightforward indicator for forecasting the initiation of shallow landslides.
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Wang, Shixin, Hongchao Zuo, Yixing Yin, Chundi Hu, Jun Yin, Xieyao Ma, and Jujie Wang. "Interpreting Rainfall Anomalies Using Rainfall's Nonnegative Nature." Geophysical Research Letters 46, no. 1 (January 8, 2019): 426–34. http://dx.doi.org/10.1029/2018gl081190.
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Qiu, Y., Z. Xie, and Y. Wang. "Influence of gravel mulch on rainfall interception under simulated rainfall." Soil and Water Research 13, No. 2 (April 13, 2018): 115–18. http://dx.doi.org/10.17221/172/2016-swr.
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To understand the hydrological outcomes of interception by gravel mulches, rainfall simulation experiments were conducted in the loess regions of northwestern China. The rainfall interception decreased with gravel size but increased with the thickness of the gravel mulch layer, following two exponential functions. Interception was 15.1% of the gross rainfall at 1 cm thickness, followed by 17.2, 20.9, 30.5 and 45.6 % at 3, 5, 7 and 10 cm thickness, respectively. For the equivalent gravel grain size of 3.43 mm, relative interception was 45.6%, which was about 1.1, 1.2, 1.4 and 2.3 times higher than that for the equivalent grain size of 11.01, 19.31, 32.8 and 43.72 mm, respectively.
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I Gusti Ngurah Putu Dharmayasa, Cathleen Ariella Simatupang, and Doni Marisi Sinaga. "NASA Power’s: an alternative rainfall data resources for hydrology research and planning activities in Bali Island, Indonesia." Journal of Infrastructure Planning and Engineering (JIPE) 1, no. 1 (April 13, 2022): 1–7. http://dx.doi.org/10.22225/jipe.1.1.2022.1-7.
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Rainfall data is critical for planning and research in the field of hydrology. Rainfall data must be available continuously, which means it must be recorded continuously. This recording will continue since numerous projects in the field of hydrology require continuous rainfall data. Although rainfall data are collected and recorded daily, some stations frequently have insufficient rainfall records, particularly in developing countries such as Bali, Indonesia. These issues may impair the quality of rainfall data, resulting in inaccuracies in the analysis results. To address this issue, we need a reliable source of rainfall data, one of which is NASA Power, which provides rainfall data for free. NASA Power rainfall data is then compared to observed rainfall data. The comparison of the two rainfalls is measured by a statistical parameter, namely the correlation coefficient. Based on the comparison between lowland and highland areas, the average daily rainfall from NASA Power tends to be lower than the average daily rainfall from observation stations. Meanwhile, from the correlation coefficient value (r) of the comparison of rainfall observations and NASA Power, a considerably high correlation coefficient value (> 0.7) was observed. Thus, it can be suggested that the rainfall data from NASA Power for hydrology research and planning activities in Bali Island, Indonesia.
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Floris, M., A. D'Alpaos, C. Squarzoni, R. Genevois, and M. Marani. "Recent changes in rainfall characteristics and their influence on thresholds for debris flow triggering in the Dolomitic area of Cortina d'Ampezzo, north-eastern Italian Alps." Natural Hazards and Earth System Sciences 10, no. 3 (March 26, 2010): 571–80. http://dx.doi.org/10.5194/nhess-10-571-2010.
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Abstract. In this paper, we examine variations in climate characteristics near the area of Cortina d'Ampezzo (Dolomites, Eastern Italian Alps), with particular reference to the possible implications for debris-flow occurrence. The study area is prone to debris-flow release in response to summer high-intensity short-duration rainfalls and, therefore, it is of the utmost importance to investigate the potential increase in debris-flow triggering rainfall events. The critical rainfall threshold is agreed to be a crucial triggering factor for debris-flows. Data from a monitoring system, placed in a catchment near Cortina (Acquabona), show that debris-flows were triggered by rainfalls with peak rainfall intensities ranging from 4.9 to 17.4 mm/10 min. The analyses of meteorological data, collected from 1921 to 1994 at several stations in the study area, show a negative trend of annual rainfall, a considerable variation in the monthly rainfall distribution, and an increase in the temperature range, possibly related to global climate changes. Moreover, high-intensity and short-duration rainfall events, derived from data collected from 1990 and 2008, show an increase in exceptional rainfall events. The results obtained in a peak-over-threshold framework, applied to the rainfall data measured at the Faloria rain gauge station from 1990 to 2008, clearly show that the interarrival time of over-threshold events computed for different threshold values decreased in the last decade. This suggests that local climatic changes might produce an increase in the frequency of rainfall events, potentially triggering debris flows in the study area.
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Ramos, M. H., E. Leblois, and J. D. Creutin. "From point to areal rainfall: linking the different approaches for the frequency characterisation of rainfalls in urban areas." Water Science and Technology 54, no. 6-7 (September 1, 2006): 33–40. http://dx.doi.org/10.2166/wst.2006.613.
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In urban water design and management, many hydrologic problems involve the frequency characterisation of rainfalls. Hydrologists are commonly asked to evaluate rainfall intensities for given recurrence frequencies or to indicate how rare an observed event is by estimating its return period. This study aims to improve the characterisation of rainfall hazard over a city by linking point to areal rainfall frequency analysis. We use a stochastic rainfall field generator based on the turning-bands method directly to assess areal rainfall distributions and to illustrate the link between different approaches. The simulating algorithm is applied to rainfall data from the city of Marseilles. The frequency analysis of simulated fields provides the elements to deal with the notions of return period and severity of observed storm events. The study concludes on the importance of a unified approach to assess rainfall better.
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Ledingham, Jamie, David Archer, Elizabeth Lewis, Hayley Fowler, and Chris Kilsby. "Contrasting seasonality of storm rainfall and flood runoff in the UK and some implications for rainfall-runoff methods of flood estimation." Hydrology Research 50, no. 5 (August 14, 2019): 1309–23. http://dx.doi.org/10.2166/nh.2019.040.
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Abstract Using data from 520 gauging stations in Britain and gridded rainfall datasets, the seasonality of storm rainfall and flood runoff is compared and mapped. Annual maximum (AMAX) daily rainfall occurs predominantly in summer, but AMAX floods occur most frequently in winter. Seasonal occurrences of annual daily rainfall and flood maxima differ by more than 50% in dry lowland catchments. The differences diminish with increasing catchment wetness, increase with rainfalls shorter than daily duration and are shown to depend primarily on catchment wetness, as illustrated by variations in mean annual rainfall. Over the whole dataset, only 34% of AMAX daily flood events are matched to daily rainfall annual maxima (and only 20% for 6-hour rainfall maxima). The discontinuity between rainfall maxima and flooding is explained by the consideration of coincident soil moisture storage. The results have serious implications for rainfall-runoff methods of flood risk estimation in the UK where estimation is based on a depth–duration–frequency model of rainfall highly biased to summer. It is concluded that inadequate treatment of the seasonality of rainfall and soil moisture seriously reduces the reliability of event-based flood estimation in Britain.
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Clarke, Allan J., Stephen Van Gorder, and Yvette Everingham. "Forecasting Long-Lead Rainfall Probability with Application to Australia’s Northeastern Coast." Journal of Applied Meteorology and Climatology 49, no. 7 (July 1, 2010): 1443–53. http://dx.doi.org/10.1175/2010jamc2373.1.
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Abstract The authors develop a method for the long-lead forecasting of El Niño–influenced rainfall probability and illustrate it using the economically important prediction, from the beginning of the year, of September–November (SON) rainfall in the coastal sugarcane producing region of Australia’s northeastern coast. The method is based on two probability distributions. One is the Gaussian error distribution of the long-lead prediction of the El Niño index Niño-3.4 by the Clarke and Van Gorder forecast method. The other is the relationship of the rainfall distribution to the Niño-3.4 index. The rainfall distribution can be approximated by a gamma distribution whose two parameters depend on Niño-3.4. To predict the rainfall at, say, the Tully Sugar, Ltd., mill on the north Queensland coast in SON 2009, the June–August (JJA) value of Niño-3.4 is predicted and then 1000 possible “observed” JJA Niño-3.4 values calculated from the error distribution. Each one of these observed Niño-3.4 values is then used, with the Niño-3.4-dependent gamma distribution for that location, to calculate 1000 possible SON rainfall totals. The result is one million possible SON rainfalls. A histogram of these rainfalls is the required probability distribution for the rainfall at that location predicted from the beginning of the year. Cross-validated predictions suggest that the method is successful.
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Rebora, Nicola, Luca Ferraris, Jost von Hardenberg, and Antonello Provenzale. "RainFARM: Rainfall Downscaling by a Filtered Autoregressive Model." Journal of Hydrometeorology 7, no. 4 (August 1, 2006): 724–38. http://dx.doi.org/10.1175/jhm517.1.
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Abstract A method is introduced for stochastic rainfall downscaling that can be easily applied to the precipitation forecasts provided by meteorological models. Our approach, called the Rainfall Filtered Autoregressive Model (RainFARM), is based on the nonlinear transformation of a Gaussian random field, and it conserves the information present in the rainfall fields at larger scales. The procedure is tested on two radar-measured intense rainfall events, one at midlatitude and the other in the Tropics, and it is shown that the synthetic fields generated by RainFARM have small-scale statistical properties that are consistent with those of the measured precipitation fields. The application of the disaggregation procedure to an example meteorological forecast illustrates how the method can be implemented in operational practice.
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SEETHARAM, K. "Rainfall models – a study over Gangtok." MAUSAM 61, no. 2 (November 27, 2021): 225–28. http://dx.doi.org/10.54302/mausam.v61i2.819.
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In this paper, the Pearsonian system of curves were fitted to the monthly rainfalls from January to December, in addition to the seasonal as well as annual rainfalls totalling to 14 data sets of the period 1957-2005 with 49 years of duration for the station Gangtok to determine the probability distribution function of these data sets. The study indicated that the monthly rainfall of July and summer monsoon seasonal rainfall did not fit in to any of the Pearsonian system of curves, but the monthly rainfalls of other months and the annual rainfalls of Gangtok station indicated to fit into Pearsonian type-I distribution which in other words is an uniform distribution. Anderson-Darling test was applied to for null hypothesis. The test indicated the acceptance of null-hypothesis. The statistics of the data sets and their probability distributions are discussed in this paper.
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Fontanazza, C. M., G. Freni, G. La Loggia, and V. Notaro. "Uncertainty evaluation of design rainfall for urban flood risk analysis." Water Science and Technology 63, no. 11 (June 1, 2011): 2641–50. http://dx.doi.org/10.2166/wst.2011.169.
Full textAbstract:
A reliable and long dataset describing urban flood locations, volumes and depths would be an ideal prerequisite for assessing flood frequency distributions. However, data are often piecemeal and long-term hydraulic modelling is often adopted to estimate floods from historical rainfall series. Long-term modelling approaches are time- and resource-consuming, and synthetically designed rainfalls are often used to estimate flood frequencies. The present paper aims to assess the uncertainty of such an approach and for suggesting improvements in the definition of synthetic rainfall data for flooding frequency analysis. According to this aim, a multivariate statistical analysis based on a copula method was applied to rainfall features (total depth, duration and maximum intensity) to generate synthetic rainfalls that are more consistent with historical events. The procedure was applied to a real case study, and the results were compared with those obtained by simulating other typical synthetic rainfall events linked to intensity–duration–frequency (IDF) curves. The copula-based multi-variate analysis is more robust and adapts well to experimental flood locations even if it is more complex and time-consuming. This study demonstrates that statistical correlations amongst rainfall frequency, duration, volume and peak intensity can partially explain the weak reliability of flood-frequency analyses based on synthetic rainfall events.
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Jiang, Xinyu, Lijiao Yang, and Hirokazu Tatano. "Assessing Spatial Flood Risk from Multiple Flood Sources in a Small River Basin: A Method Based on Multivariate Design Rainfall." Water 11, no. 5 (May 17, 2019): 1031. http://dx.doi.org/10.3390/w11051031.
Full textAbstract:
A key issue in assessing the spatial distribution of flood risk is considering risk information derived from multiple flood sources (river flooding, drainage inundation, etc.) that may affect the risk assessment area. This study proposes a method for assessing spatial flood risk that includes flooding and inundation in small-basin areas through multivariate design rainfall. The concept of critical rainfall duration, determined by the time of concentration of flooding, is used to represent the characteristics of flooding from different sources. A copula method is adopted to capture the correlation of rainfall amounts in different critical rainfall durations to reflect the correlation of potential flooding from multiple flood sources. Rainfalls for different return periods are designed based on the copula multivariate analysis. Using the design rainfalls as input, flood risk is assessed following the rainfall–runoff–inundation–loss estimation procedure. A case study of the Otsu River Basin, Osaka Prefecture, Japan, was conducted to demonstrate the feasibility and advantages of this method. Compared to conventional rainfall design, this method considers the response characteristics of multiple flood sources, and solves the problem of flood risk assessment from multiple flood sources. It can be applied to generate a precise flood risk assessment to support integrated flood risk management.
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Obi, Lawrence Echefulechukwu. "Application of Hydrological Computations in Predicting Rainfall Trends in Imo State of Nigeria." European Journal of Engineering Research and Science 2, no. 9 (September 23, 2017): 36. http://dx.doi.org/10.24018/ejers.2017.2.9.367.
Full textAbstract:
This research employed the empirical method in its approach and workings. Empirical data were collected and various hydrological computations and graphs were engaged through the application of the collected data. The mass curve of rainfall, hyetograph, moving average of annual rainfalls and the computations of recurrence intervals were done by applying the Weibul formular. With computations and its analysis, the recurrent intervals of rainfall magnitudes were determined and rainfall pattern within Imo State were predicted.
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Obi, Lawrence Echefulechukwu. "Application of Hydrological Computations in Predicting Rainfall Trends in Imo State of Nigeria." European Journal of Engineering and Technology Research 2, no. 9 (September 23, 2017): 36–41. http://dx.doi.org/10.24018/ejeng.2017.2.9.367.
Full textAbstract:
This research employed the empirical method in its approach and workings. Empirical data were collected and various hydrological computations and graphs were engaged through the application of the collected data. The mass curve of rainfall, hyetograph, moving average of annual rainfalls and the computations of recurrence intervals were done by applying the Weibul formular. With computations and its analysis, the recurrent intervals of rainfall magnitudes were determined and rainfall pattern within Imo State were predicted.
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Mahmmud, Rebar Muhammad Jaza. "Rainfall Event Analysis for Urban Flooding Study Using Radar Rainfall Data." Journal of Zankoy Sulaimani - Part A 17, no. 3 (April 19, 2015): 137–48. http://dx.doi.org/10.17656/jzs.10407.
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Lin, Chen-Chih, Yi-Jiun Liou, and Shih-Jen Huang. "Impacts of Two-Type ENSO on Rainfall over Taiwan." Advances in Meteorology 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/658347.
Full textAbstract:
Impacts of two-type ENSO (El Niño/Southern Oscillation), canonical ENSO and ENSO Modoki, on rainfall over Taiwan are investigated by the monthly mean rainfall data accessed from Taiwan Central Weather Bureau. The periods of the two-type ENSO are distinguished by Niño 3.4 index and ENSO Modoki index (EMI). The rainfall data in variously geographical regions are analyzed with the values of Niño 3.4 and EMI by correlation method. Results show that the seasonal rainfalls over Taiwan are different depending on the effects of two-type ENSO. In canonical El Niño episode, the rainfall increases in winter and spring while it reduces in summer and autumn. On the contrary, the rainfall increases in summer and autumn but reduces in winter and spring in El Niño Modoki episode. Nevertheless, two types of La Niña cause similar effects on the rainfall over Taiwan. It increases in autumn only. The rainfall variations in different types of ENSO are mainly caused by the monsoon and topography.
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PASUPALAK, S., G. PANIGRAHI, T. PANIGRAHI, S. MOHANTY, and K. K. SINGH. "Extreme rainfall events over Odisha state, India." MAUSAM 68, no. 1 (November 30, 2021): 131–38. http://dx.doi.org/10.54302/mausam.v68i1.442.
Full textAbstract:
Extreme rainfall events are a significant cause of loss of life and livelihoods in Odisha. Objectives of the present study are to determine the trend of the extreme rainfall events during 1991-2014 and to compare the events between two periods before and after 1991. Block level daily rainfall data were used in identifying the extreme rainfall events, while district level aggregation was used in analysing the trend in three categories, viz., heavy, very heavy and extremely heavy rainfall as per criteria given by India Meteorological Department (IMD). The state as a whole received one extremely heavy, nine very heavy, and forty heavy rainfall events in a year. When percentage of occurrence of each category out of the total extreme events over different districts was considered, maximum % of extremely heavy rainfall occurred in Kalahandi (5.8%), very heavy rainfall in Bolangir (23.8%) and heavy rainfall in Keonjhargarh (85.4%). Trend analysis showed that number of extreme rainfall events increased in a few districts, namely, Bolangir, Nuapada, Keonjhargarh, Koraput, Malkangiri, and Nawarangapur and did not change in other districts. In Puri district, extremely heavy rainfall frequency decreased. New all-time record high one-day rainfall events were observed in twenty districts during 1992 to 2014, surpassing the earlier records, which could be attributed to climate change induced by global warming. Interior south Odisha was found as the hot spot for extreme rainfalls.