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1
Sadeghi, Hamed, Farshad Yazdani Bene Kohal, Mostafa Gholami, Pouya Alipanahi, and Dongri Song. "Hydro-mechanical modeling of a vegetated slope subjected to rainfall." E3S Web of Conferences 382 (2023): 13004. http://dx.doi.org/10.1051/e3sconf/202338213004.
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Shallow landslides triggered by heavy rainfalls have caused casualties and economic losses to domestic infrastructures and industries worldwide. Rainfall mainly reduces the soil matric suction and the shear resistance, resulting in shallow landslides. Vegetation is an eco-friendly and cost-effective method for stabilizing slopes prone to shallow landslides. This research aims to investigate the hydrological and mechanical effects of vegetation on slope stability through a numerical study approach. Vegetated and bare slopes were subjected to a recorded climate condition and two rainfall scenarios of high intensity (HI) and low intensity (LI). Matric suction and factor of safety of vegetated and bare slopes subjected to rainfall were investigated. The matric suction of the vegetated slope at the surface was approximately four times greater than the bare slope after the HI scenario. However, the matric suction is about three times greater in the LI scenario. The results indicate that planting on slopes would reduce the vulnerability of bare slopes to the HI rainfall due to the higher matric suction and additional cohesion induced by the root system. These findings suggest that using vegetation in Rasht, Iran, where the climate data were collected, has considerable potential for stabilizing slopes.
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Widowati, Adi Putri Anisa. "Hydraulic and Hydrologic Modeling of Steep Channel of Putih River, Magelang District, Central Java Province, Indonesia." Journal of the Civil Engineering Forum 3, no. 3 (September 18, 2017): 125. http://dx.doi.org/10.22146/jcef.26507.
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Hydrologic and hydraulic modeling are important to be conducted to examine the watershed response based on a rainfall input, especially over disaster-prone watershed such as Putih River watershed in Magelang, Central Java Province. A GIS-based grid-based distributed rainfall-runoff model was used to simulate the rainfall-runoff transformation. A two-dimensional hydrodynamic flow modeling was then carried out to simulate the flood processes on the stream and floodplain area. A sensitivity analysis was conducted on infiltration rate, Manning’s n value, and rainfall intensity. Infiltration rate, Manning’s n value, and rainfall intensity give considerable effects to the resulted flow hydrographs. The modeling results show that the results of hydrologic-hydraulic modeling is in good agreement with the observed results.
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Sumargo, Bagus, Dian Handayani, Alvi Pauziah Lubis, Irman Firmasyah, and Ika Yuni Wulansari. "Detection of Factors Affecting Rainfall Intensity in Jakarta." Jurnal Ilmu Lingkungan 23, no. 1 (January 8, 2024): 133–40. https://doi.org/10.14710/jil.23.1.133-140.
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The increased intensity of rainfall is becoming one of the most pressing climate-related issues in many parts of the world. Detecting the factors that affect rainfall intensity requires a combination of modern technologies, such as weather satellites, radar systems, and advanced atmospheric models. Extreme conditions (outliers) often occur. This study aims to model data that is not symmetric or contains outliers. This study examines and models quantile regression on daily rainfall intensity in Jakarta which has extreme rainfall events. The results of the study found that the extreme values in the daily rainfall intensity data in Jakarta are outliers and the assumptions on modeling using linear regression are not satisfied so that the characteristics of the parameter estimator based on OLS do not have BLUE characteristic. In modeling with quantile regression using six quantiles 0.25, 0.50, 0.75, 0.95, 0.99, and 0.9999 with consideration of these quantile values representing all parts of the data distribution including extreme values, it was found that the factors affecting rainfall intensity in Jakarta are different in each rainfall intensity condition. The best model is shown by quantile 0.999 with a coefficient of determination of 58.21%. Based on the best model, it is known that the factors affecting extreme rainfall are maximum temperature, dew point temperature, air humidity, wind speed, air pressure, and length of irradiation. This study indicates that quantile regression can provide a more detailed insight into how these variables affect rainfall intensity in various rainfall conditions ranging from low rainfall to extreme rainfall.
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Négyesi, Klaudia, and Eszter Dóra Nagy. "The connection between time of concentration and rainfall intensity based on rainfall-runoff modeling." Időjárás 128, no. 4 (2024): 439–50. https://doi.org/10.28974/idojaras.2024.4.3.
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The study aims to examine the relation between rainfall intensities and times of concentration based on rainfall-runoff modeling using the recently developed features of the Hydrologic Engeneering Center – Hydrologic Modeling System (HEC-HMS) modeling software. The time of concentration is generally considered a constant characteristic of a catchment. However, various publications have shown that response time is a dynamic property and a function of rainfall intensity. Model simulations were performed to gain more insight into the relationship mentioned. The applicability of the dynamic time of concentration was examined with the help of a recent version of the HECHMS software that can interpret the dynamic relationship between time of concentration and rainfall intensity. The models were built for characteristic and dynamic cases. In the characteristic case, the time of concentration values of the catchments were calculated using the commonly applied Wisnovszky empirical equation, while in the dynamic case, the applicability of the rainfall intensity, i.e., the time of concentration function, was examined. The applicability of the new HEC-HMS feature was reviewed, and the relationship between the time of concentration and rainfall intensity was confirmed. The dynamic approach improved the models’ performance, especially where the Wisnovszky equation yields an inadequate estimation of the time of concentration based on the results.
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Hermawan, Koko, Khori Sugianti, Antonina Martireni, Nugroho Aji Satrio, and Yunarto. "Spatial and Temporal Analysis Prediction of Landslide Susceptibility Using Rainfall Infiltration and Grid-based Slope Stability Methods in West Bandung area of West Java-Indonesia." IOP Conference Series: Earth and Environmental Science 1173, no. 1 (May 1, 2023): 012031. http://dx.doi.org/10.1088/1755-1315/1173/1/012031.
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Abstract West Bandung, West Java, is an area with a high level of landslide susceptibility. Landslides in West Bandung occurred 142 times during rainfall in the last ten years. This paper presents the results of landside susceptibility modeling in the West Bandung area of West Java Province, Indonesia, considering the spatial characteristics of the rainfall data, slope and soil properties using the TRIGRS model. This research is based on conditions in the field in the form of landslide locations, soil engineering properties, soil thickness, Digital Elevation Model, and rainfall data. The effect of one-day antecedent rainfall intensity was considered in this study, i.e., 12 hours of antecedent rainfall. The results of the TRIGRS modelling showed that the intensity of rainfall antecedent of rainfall influenced the slope stability in the study area. The TRIGRS model results indicate that the predicted landslide susceptibility distribution agrees with the historical landslide events.
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Dikko, H. G. "Modeling the Distribution of Rainfall Intensity using Quarterly Data." IOSR Journal of Mathematics 9, no. 1 (2013): 11–16. http://dx.doi.org/10.9790/5728-0911116.
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Dan'azumi. "Modeling the Distribution of Rainfall Intensity using Hourly Data." American Journal of Environmental Sciences 6, no. 3 (March 1, 2010): 238–43. http://dx.doi.org/10.3844/ajessp.2010.238.243.
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Kumar, Pappu, Madhusudan Narayan, and Mani Bhushan. "Rainfall Intensity Duration Frequency Curve Statistical Analysis and Modeling for Patna, Bihar." BOHR International Journal of Civil Engineering and Environmental Science 2, no. 1 (2023): 65–73. http://dx.doi.org/10.54646/bicees.008.
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Using data from 41 years in Patna, India, the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981–2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall, the historical rainfall data set for Patna, India, during a 41-year period (1981–2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 hours and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval. Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall. Originality and Value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
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Kumar, Pappu, Madhusudan Narayan, and Mani Bhushan. "Rainfall Intensity Duration Frequency Curve Statistical Analysis and Modeling for Patna, Bihar." BOHR International Journal of Civil Engineering and Environmental Science 2, no. 1 (2023): 65–73. http://dx.doi.org/10.54646/bijcees.008.
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Using data from 41 years in Patna, India, the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981–2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall, the historical rainfall data set for Patna, India, during a 41-year period (1981–2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 hours and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval. Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall. Originality and Value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
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Kumar, Pappu, Madhusudan Narayan, and Mani Bhushan. "Rainfall intensity duration frequency curve statistical analysis and modeling for Patna, Bihar." BOHR International Journal of Civil Engineering and Environmental Science 1, no. 2 (2023): 66–75. http://dx.doi.org/10.54646/bijcees.2023.08.
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Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on aweekly, seasonal, and annual basis (19812020). First, utilizing the intensity-duration-frequency (IDF) curve and therelationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period(19812020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhousegas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. Onestrategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal,normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and returntimes of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall andrecurrence interval. Findings:Based on findings, the Gumbel approach produced the highest intensity values, whereas the otherapproaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell duringthe monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall,92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that theyearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examinerainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence intervalmathematical correlations were also developed. Further regression analysis revealed that short wave irrigation,wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall. Originality and value:The results of the rainfall IDF curves can provide useful information to policymakers inmaking appropriate decisions in managing and minimizing floods in the study area
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Shao, W., T. A. Bogaard, M. Bakker, and R. Greco. "Quantification of the influence of preferential flow on slope stability using a numerical modeling approach." Hydrology and Earth System Sciences Discussions 11, no. 11 (November 26, 2014): 13055–99. http://dx.doi.org/10.5194/hessd-11-13055-2014.
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Abstract. The effect of preferential flow on the stability of landslides is studied through numerical simulation of two types of rainfall events on a hypothetical hillslope. A model is developed that consists of two parts. The first part is a model for combined saturated/unsaturated subsurface flow and is used to compute the spatial and temporal water pressure response to rainfall. Preferential flow is simulated with a dual-permeability continuum model consisting of a matrix domain coupled to a preferential flow domain. The second part is a~soil mechanics model and is used to compute the spatial and temporal distribution of the local factor of safety based on the water pressure distribution computed with the subsurface flow model. Two types of rainfall events were considered: long duration, low-intensity rainfall, and short duration, high-intensity rainfall. The effect of preferential flow on slope stability is assessed through comparison of the failure area when subsurface flow is simulated with the dual-permeability model as compared to a single-permeability model (no preferential flow). For the low-intensity rainfall case, preferential flow has a positive effect on the slope stability as it drains the water from the matrix domain resulting in a smaller failure area. For the high-intensity rainfall case, preferential flow has a negative effect on the slope stability as the majority of rainfall infiltrates into the preferential flow domain when rainfall intensity exceeds the infiltration capacity of the matrix domain, resulting in larger water pressure and a larger failure area.
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Yang, Ming-Jen, Da-Lin Zhang, and Hsiao-Ling Huang. "A Modeling Study of Typhoon Nari (2001) at Landfall. Part I: Topographic Effects." Journal of the Atmospheric Sciences 65, no. 10 (October 2008): 3095–115. http://dx.doi.org/10.1175/2008jas2453.1.
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Although there have been many observational and modeling studies of tropical cyclones, understanding of their intensity and structural changes after landfall is rather limited. In this study, several 84-h cloud-resolving simulations of Typhoon Nari (2001), a typhoon that produced torrential rainfall of more than 1400 mm over Taiwan, are carried out using a quadruply nested–grid mesoscale model whose finest grid size was 2 km. It is shown that the model reproduces reasonably well Nari’s kinematic and precipitation features as well as structural changes, as verified against radar and rain gauge observations. These include the storm track, the contraction and sizes of the eye and eyewall, the spiral rainbands, the rapid pressure rise (∼1.67 hPa h−1) during landfall, and the nearly constant intensity after landfall. In addition, the model captures the horizontal rainfall distribution and some local rainfall maxima associated with Taiwan’s orography. A series of sensitivity experiments are performed in which Taiwan’s topography is reduced to examine the topographic effects on Nari’s track, intensity, rainfall distribution, and amount. Results show that the impact of island terrain on Nari’s intensity is nearly linear, with stronger storm intensity but less rainfall in lower-terrain runs. In contrast, changing the terrain heights produces nonlinear tracks with circular shapes and variable movements associated with different degrees of blocking effects. Parameter and diagnostic analyses reveal that the nonlinear track dependence on terrain heights results from the complex interactions between the environmental steering flow, Nari’s intensity, and Taiwan’s topography, whereas the terrain-induced damping effects balance the intensifying effects of latent heat release associated with the torrential rainfall in maintaining the near-constant storm intensity after landfall.
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Abd Alelah, Zainb. "Modeling of Short Duration Rainfall Intensity Duration Frequency(SDR-IDF) Equation for Basrah City." University of Thi-Qar Journal for Engineering Sciences 7, no. 2 (December 1, 2016): 56–68. http://dx.doi.org/10.31663/utjes.v7i2.62.
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The Rainfall Intensity-Duration-Frequency (IDF) relationship is one of the most commonly used tools in water resources engineering, either for planning, designing and operating of water resource projects or for various engineering projects against floods. The objective of this study is to develop an empirical formula to estimate rainfall intensity for any duration and any return period with minimum effort. Daily rainfall data for years 1980-2010 from Iraqi Metrological Organization and Seismology was used in this study. Hershfeildʼs method was used to estimate the short duration rainfall intensity from daily rainfall data. Various distribution functions were used for analysis and Chi-Square goodness to fit test were used to identify the best statistical distribution among them. Study showed that Log Pearson type III is the best probability distribution and the best (IDF)empirical formula was in the form [i=a/(b=td)]
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Yendra, Rado, Ari Pani Desvina, Rahmadeni Rahmadeni, Abdul Aziz Jemain, Wan Zawiah Wan Zin, and Ahmad Fudholi. "Rainfall Storm Modeling of Neyman-Scott Rectangular Pulse (NSRP) using Rainfall Cell Intensity Distributions." Research Journal of Applied Sciences, Engineering and Technology 11, no. 9 (November 25, 2015): 969–74. http://dx.doi.org/10.19026/rjaset.11.2136.
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Hakim, Arief Rachman, Rukun Santoso, Hasbi Yasin, and Masithoh Yessi Rochayani. "MAX-STABLE PROCESS WITH GEOMETRIC GAUSSIAN MODEL ON RAINFALL DATA IN SEMARANG CITY." MEDIA STATISTIKA 16, no. 1 (September 20, 2023): 59–66. http://dx.doi.org/10.14710/medstat.16.1.59-66.
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Spatial extreme value (SEV) is a statistical technique for modeling extreme events at multiple locations with spatial dependencies between locations. High intensity rainfall can cause disasters such as floods and landslides. Rainfall modelling is needed as an early detection step. SEV was developed from the univariate Extreme Value Theory (EVT) method to become multivariate. This work uses the SEV approach, namely the Max-stable process, which is an extension of the multivariate EVT into infinite dimensions. There are 4 Max-stable process models, namely Smith, Schlater, Brown Resnik, and Geometric Gaussian, which have the Generalized Extreme Value (GEV) distribution. This study models extreme rainfall, using rainfall data in the city of Semarang. This research was carried out by modeling data using the Geometric Gaussian model. This method is developed from the Smith and Schlater model, so this model can get better modeling results than the previous model. The maximum extreme rainfall prediction results for the next two periods are Semarang climatology station 129.30 mm3, Ahmad Yani 121.40 mm3, and Tanjung Mas 111.00 mm3. The result from this study can be used as an alternative for the government for early detection of the possibility of extreme rainfall.
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Zhang, Zhen, Liangkai Qin, Guanbao Ye, Wei Wang, and Jiafeng Zhang. "Physical Modeling and Intelligent Prediction for Instability of High Backfill Slope Moisturized under the Influence of Rainfall Disasters." Applied Sciences 13, no. 7 (March 27, 2023): 4218. http://dx.doi.org/10.3390/app13074218.
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The stability of high backfill slopes emerges in practice due to the expansion of transportation infrastructures. The seepage and infiltration of rainfall into the backfills brings challenges to engineers in predicting the stability of the slope, weakening the shear strength and modulus of the soil. This study carried out a series of model tests under a plane strain condition to investigate the stability of a high backfill slope moisturized by rainfalls, considering the influences of rainfall duration and intensity. The slope displacements were monitored by a laser displacement sensor and the moisture content in the backfill mass were obtained by a soil moisture sensor. The test results show that increasing the rainfall intensity and duration caused the slope near the surface to be saturated, resulting in significant influences on the lateral displacement of the slope and the reduction of stability as well as the sizes of the sliding mass. Based on the model tests, the numerical analysis was adopted to extend the analysis cases, and the backpropagation (BP) neural network model was further adopted to build a model for predicting the stability of a high backfill slope under rainfall. The trained BP model shows the average relative error of 1.02% and the goodness of fitness of 0.999, indicating a good prediction effect.
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Dorneles, Viviane R., Rita de C. F. Damé, Claudia F. A. Teixeira-Gandra, Letícia B. Méllo, Mario A. A. Ramirez, and Emanuele B. Manke. "Intensity-duration-frequency relationships of rainfall through the technique of disaggregation of daily rainfall." Revista Brasileira de Engenharia Agrícola e Ambiental 23, no. 7 (July 2019): 506–10. http://dx.doi.org/10.1590/1807-1929/agriambi.v23n7p506-510.
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ABSTRACT Rainfall intensity-duration-frequency (IDF) relationships are a tool that can be used in modeling the transformation of rainfall to runoff, required for the design of hydraulic works. The objective of this study was to verify if there is a significant difference between the intensity-duration-frequency relationships generated using pluviographic records and those determined from pluviometric data. Maximum annual rainfall intensity values were obtained from the disaggregation of maximum daily rainfall and rainfall records in the durations of 5, 10, 15, 20, 30, 60, 120, 360, 720 and 1440 min and for the return periods of 2, 5, 10, 20, 25, 50 and 100 years, in the locality of Pelotas, Rio Grande do Sul state, Brazil (31° 46’ 34’’ S; 52° 21’ 34’’ W, altitude of 13.2 m). By Student’s t-test, it was verified that there is no significant difference between the values of maximum rainfall intensity obtained from pluviographic records and those determined from pluviometric data.
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Guideli, Leandro Canezin, André Lucas dos Reis Cuenca, Milena Arruda Silva, and Larissa de Brum Passini. "Road crashes and field rainfall data: mathematical modeling for the Brazilian mountainous highway BR-376/PR." TRANSPORTES 29, no. 4 (December 2, 2021): 2498. http://dx.doi.org/10.14295/transportes.v29i4.2498.
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Recent studies analyze the influence of rainfall on traffic crashes, indicating that precipitation intensity is an important factor, for modeling crashes occurrence. This research presents a relationship between daily-basis traffic crashes and precipitation, from 2014 to 2018, in a rural mountainous Brazilian Highway (BR-376/PR), where field rain gauges were used to obtain precipitation data. Data modeling considered a Negative Binomial regression for precipitation influence in crash frequency. Separate regression models were estimated to account for the rainfall effect in different seasons, and for different vehicle types. All models analyzed presented a positive relationship between daily rainfall intensity and daily crashes number. This can indicate that generally rainfall presence is a hazardous factor. Different critical seasons for rainfall influence were also highlighted, alerting for the possible necessity of distinct road safety policies concerning seasonality. Finally, for the vehicle type analysis, typically, rainfall seemed to have a greater effect in lighter vehicles. Moreover, results are useful for traffic control, in order to increase safety conditions.
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Huang, J. C., S. J. Kao, M. L. Hsu, and Y. A. Liu. "Influence of Specific Contributing Area algorithms on slope failure prediction in landslide modeling." Natural Hazards and Earth System Sciences 7, no. 6 (December 6, 2007): 781–92. http://dx.doi.org/10.5194/nhess-7-781-2007.
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Abstract. This study anatomized algorithm effects of specific contributing area (SCA) on soil wetness estimation, consequently landslide prediction, in SHALSTAB. A subtropical mountainous catchment during three typhoon invasions is targeted. The peak 2-day rainfall intensity of the three typhoons: Haitang, Mindulle and Herb are 144, 248 and 327 mm/day, respectively. We use modified success rate (MSR) to retrieve the most satisfying mean condition for model parameters in SHALSTAB at three rainfall intensities and respective pre-typhoon NDVI themes. Simulation indicates that algorithm affects the prediction of landslide susceptibility (i.e. FS, Factor of Safety) significantly. Based on fixed NDVI and the mean condition, we simulate by using full scale rainfall intensity from 0 to 1200 mm/day. Simulations show that predicted unstable area coverage increases non-linearly as rainfall intensity increases for all algorithms yet with different increasing trends. Compared to Dinf, D8 always gives lower coverage of predicted unstable area during three typhoons. By contrast, FD8 gives higher coverage areas. The absolute difference (compared to Dinf) in predicted unstable area ranges from ~−3% to +4% (percent watershed area). The relative difference (compared to Dinf) ranges from −15% to as high as +40%. The maximum absolute and relative differences in unstable area prediction occur around the condition of 100–300 mm/day, which is common in subtropical mountainous region. Theoretical relationship among slope, rainfall intensity, SCA and FS value was derived in which FS values are very sensitive to algorithms in the field of slope from 37 to 52degree. Results imply any comparison among SCA-related landslide models or engineering application of rainfall return period analysis must base on the same algorithm to obtain comparable results. This study clarifies the SCA algorithm effect on FS prediction and deepens our understanding on landslide modeling.
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Shi, Li Juan, Yang Cheng, Dong Xiu Ou, and Xiao Hong Chen. "Modeling the Effects of Rainfall on Urban Freeway Free-Flow Speeds." Applied Mechanics and Materials 178-181 (May 2012): 2577–85. http://dx.doi.org/10.4028/www.scientific.net/amm.178-181.2577.
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This paper presents an investigation of the effects of rainfall with varying precipitation intensity at every millimeter interval on urban freeway free-flow speeds. The traffic data and corresponding weather information data from the Inner Ring in Shanghai for more than one year were used. Statistical and regression analysis were applied to investigate the effects quantitatively. There are three major contributions of this paper. Firstly, statistical analysis indicates that the rainfall does not significantly affect the speeds variability until the flow rate reaches to a certain level, such as 400veh/h/ln in this study. Secondly, the variation pattern of mean speeds at every millimeter interval of precipitation intensity was investigated. Thirdly, it is the first study to model the effects of precipitation intensity at every millimeter interval on free-flow speeds. Both piecewise linear model and natural logarithm model were used to model the effects of precipitation intensity. By comparing the two models, the piecewise linear model is proposed in this study.
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Jamel, Asmaa Abdul Jabbar. "The Effect of Rainfall Intensity on Slope Stability: An Analytical Study using Numerical Modeling." Engineering, Technology & Applied Science Research 15, no. 2 (April 3, 2025): 21203–7. https://doi.org/10.48084/etasr.10257.
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Slope instability causes landslides, which have a detrimental effect on infrastructure and the environment while contributing to significant damage both in terms of people and property. The present article offers a thorough examination of slope stability by SEEP/W and SLOPE/W software programs. Using numerical simulations based on three different models, the work plan analyzed changes in moisture content, Pore Water Pressure (PWP), and factor of safety (F.S.) to assess the impact of a set of hydrological and engineering factors, such as rainfall intensity (I), soil permeability (K), and slope angles (S). Based on the results, PWP rises to 185.84 kPa and the F.S. drops to 1.233 as rainfall intensity exceeds 80 mm/h. Additionally, longer rainfall intervals (3 days) result in a 20% reduction in F.S. as compared to short rainfall periods. The study also found that steep slopes (30° or more) greatly enhance the chance of falling apart, particularly in highly permeable soils, while the rapid water seepage along gradients caused by highly permeable soils increases the danger of collapse. The findings suggest that, in addition to enhancing soil qualities in high-permeability areas and utilizing efficient drainage systems to lower pore pressure, engineering projects should consider the impact of heavy rainfall and extended precipitation. Furthermore, a novel mathematical equation was developed to calculate the F.S. of slopes, incorporating key parameters, such as rainfall intensity, slope angle, and soil type. This equation underwent rigorous statistical analysis, achieving the highest accuracy rate, and can serve as a robust tool for slope stability assessment in diverse environmental and engineering scenarios.
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Lindgren, Ville, Tero Niemi, Harri Koivusalo, and Teemu Kokkonen. "Value of Spatially Distributed Rainfall Design Events—Creating Basin-Scale Stochastic Design Storm Ensembles." Water 15, no. 17 (August 27, 2023): 3066. http://dx.doi.org/10.3390/w15173066.
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Current design storms used in hydrological modeling, urban planning, and dimensioning of structures are typically point-scale rainfall events with a steady rainfall intensity or a simple temporal intensity pattern. This can lead to oversimplified results because real rainfall events have more complex patterns than simple design series. In addition, the interest of hydrologists is usually in areal estimates rather than point values, most commonly in river-basin-wide areal mean rainfall estimates. By utilizing weather radar data and the short-term ensemble prediction system pySTEPS, which has so far been used for precipitation nowcasting, ensembles of high-resolution stochastic design storms with desired statistical properties and spatial structure evolving in time are generated. pySTEPS is complemented by adding time-series models for areal average rainfall over the simulation domain and field advection vectors. The selected study area is the Kokemäenjoki river basin located in Western Finland, and the model parametrization is carried out utilizing the Finnish Meteorological Institute’s weather radar data from the years 2013 to 2016. The results demonstrate how simulated events with similar large-scale mean areal rainfall can produce drastically different total event rainfalls in smaller scales. The sampling method, areal vs. gauge estimate, is also shown to have a prominent effect on total event rainfall across different spatial scales. The outlined method paves the way towards a more thorough and wide-spread assessment of the hydrological impacts of spatiotemporal rainfall characteristics.
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Liu, Zhangwen, Yongxin Tian, Jinxian Qi, Zhiying Dang, Rensheng Chen, Chuntan Han, and Yong Yang. "Rainfall Partitioning by Two Alpine Shrubs in the Qilian Mountains, Northwest China: Implications for Hydrological Modeling in Cold Regions." Forests 16, no. 4 (April 10, 2025): 658. https://doi.org/10.3390/f16040658.
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Understanding rainfall partitioning by shrub canopies is essential for assessing water balance and improving hydrological models in cold regions. From 2010 to 2012, field experiments were conducted in the Hulu catchment of the Qilian Mountains, focusing on Potentilla fruticosa and Caragana jubata during the growing season. Throughfall, stemflow, and interception loss were measured using rain gauges, stemflow collars, and a water balance approach. A total of 197 natural rainfall events were recorded, and precipitation partitioning characteristics were analyzed in relation to rainfall intensity, amount, and vegetation traits. One-way ANOVA and regression analyses were used to test differences and correlations. The results showed that the critical rainfall threshold for generating throughfall and stemflow was 1.9 mm. For P. fruticosa, throughfall, stemflow, and interception loss accounted for 66.96%, 3.51%, and 29.53% of gross rainfall, respectively; the corresponding values for C. jubata were 67.31%, 7.27%, and 25.42%. Significant differences (p < 0.05) in stemflow were observed between species. Partitioning components were positively correlated with rainfall amount and stabilized at ~4 mm h−1 intensity. Interception loss percentage decreased with intensity and plateaued at 2 mm h−1 for P. fruticosa and 5 mm h−1 for C. jubata. These findings provide empirical evidence for modeling shrub canopy rainfall redistribution in alpine environments.
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Liu, Zheng, Fu-an Sun, and Bin Zhou. "Modeling of the Marine atmosphere and its impact on Ka-band channels." MATEC Web of Conferences 355 (2022): 03046. http://dx.doi.org/10.1051/matecconf/202235503046.
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The sea atmosphere environment will affect the Ka frequency channel in TT&C. Firstly, this paper briefly introduces the Marine atmospheric environment. Attenuation models of water vapor solubility and rainfall intensity are established. The variation characteristics of atmospheric environment and the estimation method of rainfall intensity are studied. Finally, the influence of Marine atmosphere on Ka-band channel is simulated and analyzed. The simulation results show that different elevation angles have different effects on Ka-band channels. The influence result decreases gradually with the elevation Angle increasing.
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Juliastuti, Yuliastuti, Yureana Wijayanti, Mohamad Fajar, and Martin Anda. "Hydraulic Modeling-Based Design of Retaining Wall Height for Flood Mitigation." Journal of Engineering and Sustainable Development 28, no. 6 (November 1, 2024): 710–16. http://dx.doi.org/10.31272/jeasd.28.6.3.
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The Bekasi River in Jakarta, Indonesia, faces significant flood risks due to high rainfall intensity, extensive urban development, and climate change. This paper aims to reduce the impact of floods by implementing efficient flood management measures, such as constructing retaining walls along the river. The appropriate height and stability of retaining walls were determined by conducting hydrological and hydraulic analyses using HEC-HMS and HEC-RAS, respectively, accounting for maximum rainfall and flood discharge levels. The results showed that the rainfall intensity in the Bekasi watershed with a return period of 2 years obtained a designed rainfall of 132 mm/hour using the Log Pearson III distribution, the maximum flood discharge for the return period Q50 is 1155 m3/second, the retaining wall design dimensions will be obtained 3-meter height with cross-section slope 0.002. Results indicated that almost all river channels overflow except near the Bekasi Dam, necessitating riverbank restoration and increased channel capacity. The paper highlights the need for reinforced retaining walls to protect the riverbank and improve flood resilience
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Kim, Sangdan, and M. Levent Kavvas. "Stochastic Point Rainfall Modeling for Correlated Rain Cell Intensity and Duration." Journal of Hydrologic Engineering 11, no. 1 (January 2006): 29–36. http://dx.doi.org/10.1061/(asce)1084-0699(2006)11:1(29).
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Hussein, Mohammad H. "A sheet erodibility parameter for water erosion modeling in regions with low intensity rain." Hydrology Research 44, no. 6 (January 16, 2013): 1013–21. http://dx.doi.org/10.2166/nh.2013.029.
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Soil erodibility reflects the soil effect on the detachment process by rainfall and runoff; an evaluation of this parameter for single storm events was carried out using natural runoff plot data collected for two rainfall seasons in northern Iraq. The region is characterized by a semiarid Mediterranean-type climate with normal rainfall intensity below 20 mm/h and dominant sheet erosion on agricultural land. The plots were three 30 × 3 m and three 10 × 3 m, in fallow, situated on a 6% uniform slope; the soil at the site has a silty clay loam texture and belongs to the Calciorthid suborder. Sheet erosion rate was assumed linearly proportional to the storm power and the sheet flow power; a steady-state turbulent and kinematic sheet flow was also assumed. The results indicated a dominant detachment by rainfall with a substantial variability in storm by storm calculated sheet erodibility. The two-parameter lognormal probability distribution fitted the obtained sheet erodibility values reasonably well. Using this probability distribution, a representative sheet erodibility value of 0.056 × 10−3kg/J was obtained for use at the experimental site.
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Guo, Bin, Xiangjun Pei, Min Xu, and Tiantao Li. "Analyzing Rainfall Threshold for Shallow Landslides Using Physically Based Modeling in Rasuwa District, Nepal." Water 14, no. 24 (December 13, 2022): 4074. http://dx.doi.org/10.3390/w14244074.
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On 25 April 2015, an M7.8 large earthquake happened in Nepal, and 4312 landslides were triggered during or after the earthquake. The 2015 earthquake happened years ago, but the risk of rainfall-induced landslides is still high. Rainfall-induced shallow landslides threaten both human lives and economy development, especially in the Rasuwa area. Due to financial conditions and data availability, a regional-scale rainfall threshold can be an effective method to reduce the risk of shallow landslides. A physically based model was used with limited data. The dynamic hydrological model provides the soil moisture and groundwater change, and the infinite slope stability model produces the factor of safety. Remote sensing data, field investigation, soil sample tests, and literature review were used in the model parameterization. The landslide stability condition of 2016 was simulated. In addition, intensity-antecedent rainfall thresholds were defined based on the physically based modelling output. Sixty groups of data were used for validation, and the 15-day intensity-antecedent rainfall threshold has the best performance with an accuracy of 88.33%.
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Wei, Zhen Lei, Yue Quan Shang, Qiu Hua Liang, and Xi Lin Xia. "A coupled hydrological and hydrodynamic modeling approach for estimating rainfall thresholds of debris-flow occurrence." Natural Hazards and Earth System Sciences 24, no. 10 (October 1, 2024): 3357–79. http://dx.doi.org/10.5194/nhess-24-3357-2024.
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Abstract. Rainfall-induced hydrological processes and surface-water flow hydrodynamics may play a key role in initiating debris flows. In this study, a new framework based on an integrated hydrological and hydrodynamic model is proposed to estimate the intensity–duration (ID) rainfall thresholds that trigger debris flows. In the new framework, intensity–duration–frequency (IDF) analysis is carried out to generate design rainfall to drive the integrated models and calculate grid-based hydrodynamic indices (i.e., unit-width discharge). The hydrodynamic indices are subsequently compared with hydrodynamic thresholds to indicate the occurrence of debris flows and derive rainfall thresholds through the introduction of a zone threshold. The capability of the new framework in predicting the occurrence of debris flows is verified and confirmed by application to a small catchment in Zhejiang Province, China, where observed hydrological data are available. Compared with the traditional statistical approaches to derive intensity–duration (ID) thresholds, the current physically based framework can effectively take into account the hydrological processes controlled by meteorological conditions and spatial topographic properties, making it more suitable for application in ungauged catchments where historical debris-flow data are lacking.
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Chen, G. F., D. Y. Qin, R. Ye, Y. X. Guo, and H. Wang. "A new method of rainfall temporal downscaling: a case study on sanmenxia station in the Yellow River Basin." Hydrology and Earth System Sciences Discussions 8, no. 2 (March 3, 2011): 2323–44. http://dx.doi.org/10.5194/hessd-8-2323-2011.
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Abstract. Distributed hydrological models are effective tools for Predictions in Ungauged Basins (PUB). The rainfall input uncertainty is an important source of hydrological model uncertainty. With the improvement of hydrological model accuracy, the requirements of the accuracy of input data are correspondingly improved. Daily rainfall data is the most common data that the researchers can get, however this cannot satisfy the requirement of hydrological simulation. Therefore, researches of daily rainfall temporal downscaling method is focus in distributed hydrological models. In the Yellow River Basin, the random distribution method, the sinusoidal distribution method and the normal distribution method all underestimate the maximum rainfall intensity. This paper raises a new daily rainfall downscaling method called proportional method based on the rainfall hyetograph of 28 years. This method significantly improves the accuracy of the maximum rainfall intensity simulation and the rainfall process curves, so this method can improve the accuracy of modeling the hydrology process and reducing the input uncertainty of the rainfall data.
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Kumar, V. Rajesh, S. Guganesh, D. Hussain Babu, and P. Kumaresan. "Flood Risk Assessment for an Irrigation Project in Odissa, India." Indian Journal Of Science And Technology 17, no. 13 (March 25, 2024): 1304–14. http://dx.doi.org/10.17485/ijst/v17i13.2588.
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Objectives: Flood risk assessment is a fundamental aspect of disaster management, particularly in regions heavily reliant on irrigation infrastructure for agriculture. This study employs advanced hydrological and hydraulic modeling techniques to evaluate flood risk for the Lower Suktel region in Odisha, India. Methods: The methodology integrates Intensity-Duration-Frequency (IDF) curves, Isopluvial maps, and the Hydrologic Engineering Center-River Analysis System (HEC-RAS) to comprehensively analyze flood risk and its implications. Findings: IDF curves further reveal that the design rainfall intensity for a one-hour duration with a 100-year return period is 152 mm/h, aiding in characterizing rainfall intensity for specific return periods. Model simulation identifies the pump house's susceptibility to flooding, with maximum flood depths ranging from 0 to 2 meters. These findings underscore the significance of employing advanced modeling techniques and Isopluvial maps for precise flood risk assessment. Novelty: The novelty of this paper lies in its pioneering effort to introduce a comprehensive flood risk assessment in an area where it has not been previously conducted. The integration of advanced modeling techniques and spatial analysis tools contributes to the novelty of the research, making it a valuable and innovative contribution to the field of flood risk management. Understanding extreme rainfall events, hydraulic behavior, and potential flood depths is imperative for developing effective flood mitigation strategies. Keywords: Flood risk assessment, Irrigation infrastructure, IDF curves, Hydrological modeling, Hydraulic modeling, GIS
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Nguyen, Phu Minh Vuong, Aleksander Wrana, Sylwester Rajwa, Zenon Różański, and Robert Frączek. "Slope Stability Numerical Analysis and Landslide Prevention of Coal Mine Waste Dump under the Impact of Rainfall—A Case Study of Janina Mine, Poland." Energies 15, no. 21 (November 7, 2022): 8311. http://dx.doi.org/10.3390/en15218311.
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In Poland, the mining waste from underground coal mines is commonly deposited in surface dump sites, forming slopes or piles of materials dozens of meters high. Because of the loose structure of a mine waste dump slope, landslides may occur after a heavy rainfall. This requires significant labor costs in reforming the mine waste dump sites and disturbs the continuity of the depositing operations. Moreover, if the mine waste dump sites located in the built-up areas, such as in the Janina mine waste dump, landslides apparently can threaten even lives and properties. Therefore, a mine waste dump stability analysis is necessary for ensuring safety. In this paper, slope stability analysis was conducted using numerical modeling under the impact of rainfall for the Janina mine waste dump, located in Libiąż, Poland. The results indicated that slope tends to loose stability in case of high rainfall intensity and short duration. Then, slope reinforcement using soil nailing and steel mesh was proposed to prevent landslide under the impact of high rainfall intensity. Once again, slope stability analysis was carried out with selected reinforcement. Meanwhile, slope monitoring was performed to assess the slope reinforcement implementation at the Janina mine waste dumps against the impact of high rainfall intensity. Based on the modeling and monitoring outcomes, assessments of slope stability and selected landslide prevention measures for the Janina mine waste dump under the impact of rainfall were presented.
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Lee, Kang, Joo, Kim, Kim, and Lee. "Hydrological Modeling Approach Using Radar-Rainfall Ensemble and Multi-Runoff-Model Blending Technique." Water 11, no. 4 (April 23, 2019): 850. http://dx.doi.org/10.3390/w11040850.
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The purpose of this study is to reduce the uncertainty in the generation of rainfall data and runoff simulations. We propose a blending technique using a rainfall ensemble and runoff simulation. To create rainfall ensembles, the probabilistic perturbation method was added to the deterministic raw radar rainfall data. Then, we used three rainfall-runoff models that use rainfall ensembles as input data to perform a runoff analysis: The tank model, storage function model, and streamflow synthesis and reservoir regulation model. The generated rainfall ensembles have increased uncertainty when the radar is underestimated, due to rainfall intensity and topographical effects. To confirm the uncertainty, 100 ensembles were created. The mean error between radar rainfall and ground rainfall was approximately 1.808–3.354 dBR. We derived a runoff hydrograph with greatly reduced uncertainty by applying the blending technique to the runoff simulation results and found that uncertainty is improved by more than 10%. The applicability of the method was confirmed by solving the problem of uncertainty in the use of rainfall radar data and runoff models.
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Mendes, Thiago Augusto, Roberto Dutra Alves, Gilson de Farias Neves Gitirana, Sávio Aparecido dos Santos Pereira, Juan Félix Rodriguez Rebolledo, and Marta Pereira da Luz. "Evaluation of Rainfall Interception by Vegetation Using a Rainfall Simulator." Sustainability 13, no. 9 (May 1, 2021): 5082. http://dx.doi.org/10.3390/su13095082.
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Interception by vegetation is one of the main variables controlling hydrological and geo-environmental problems such as erosion, landslides and floods. Interception, along with precipitation and evapotranspiration, is required for the modeling of infiltration, percolation and runoff. Unfortunately, the measurement of interception in the field is time consuming, burdensome and subject to testing parameters with relatively high variability. In this context, experiments using rainfall simulators (RSs) have the potential to provide an alternative approach that addresses most of the limitations of field experiments. This paper presents a new approach to evaluate interception that combines a RS and the monitoring of the wetting front using pore-water pressure instrumentation at specific locations of the specimen. Two specimens are required, one with and another without vegetation. The proposed approach was applied to Paspalum notatum (bahiagrass) and a tropical soil. The results indicated an average interception of 5.1 mm of the simulated rainfall for a slope at 15 degrees, rainfall intensity of 86 mm h−1, and duration of 60 min. Furthermore, the vegetation decreased the surface runoff that contributes to erosion. The proposed method will enable studies on the interception mechanisms and the various involved variables, with benefits to the modeling of soil-vegetation-atmosphere interaction.
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Tan, Jinqiang, Hongqing Song, Hailong Zhang, Qinghui Zhu, Yi Xing, and Jie Zhang. "Numerical Investigation on Infiltration and Runoff in Unsaturated Soils with Unsteady Rainfall Intensity." Water 10, no. 7 (July 11, 2018): 914. http://dx.doi.org/10.3390/w10070914.
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Modeling infiltration into soil and runoff quantitative evaluations is very significant for hydrological applications. In this paper, a flow model of unsaturated soils was established. A computational process of soil water content and runoff prediction was presented that combines an analytical solution with numerical approaches. The solutions have good agreements with the experimental results and other infiltration solutions (Richards numerical solution and classical Green–Ampt solution). We analyzed the effects on cumulative infiltration and runoff under three conditions of rainfall intensity with same average magnitude. These rainfall conditions were (Case 1) decreasing rainfall, (Case 2) steady rainfall, and (Case 3) increasing rainfall, respectively. The results show that the cumulative infiltration in Case 1 is the highest among the three cases. The cumulative runoff under condition of Case 3 is smaller than that of decreasing rainfall at the initial stage, which then becomes larger at the later stage. The time of runoff under the conditions of Case 1 is earliest among the three rainfall conditions, which is about 50% earlier than Case 3. Therefore, project construction for urban flood control should pay more attention to urban flood defense in increasing rainfall weather than other rainfall intensities under the same average magnitude. The approaches presented can be utilized to easily and effectively evaluate infiltration and runoff as a theoretical foundation.
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Setyorini, Elisabeth Yeyen, and Endah R. M. Putri. "RAINFALL MODELLING IN EAST JAVA USING A MODIFIED ORNSTEIN-UHLENBECK MODEL." Jurnal Matematika UNAND 14, no. 1 (January 31, 2025): 46. https://doi.org/10.25077/jmua.14.1.46-61.2025.
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One of the current global issues is climate change and weather variability. This phenomenon has real impacts on various regions, including East Java Province. East Java is experiencing increased rainfall intensity as one of the effects of climate change. High and continuous rainfall intensity can trigger disasters such as flooding, which has the potential to cause significant financial losses for the community. Therefore, effective risk management becomes crucial. One possible solution to address these risks is through the use of financial derivatives. The initial step in risk management involves modeling the behavior of rainfall. It is assumed that the rainfall pattern follows a mean-reverting process, specifically the Ornstein-Uhlenbeck process. The existing Ornstein-Uhlenbeck model is then modified to ensure that the resulting model accurately reflects the rainfall conditions in East Java. To validate the modified model, simulations of the Ornstein-Uhlenbeck process were conducted using estimated parameter values. The Ornstein-Uhlenbeck simulation achieved a minimum MSE score that approaches zero. This MSE score indicate that the proposed modified Ornstein-Uhlenbeck model is accurate in representing the rainfall patterns in East Java.
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Zhan, Tony L. T., He Li, G. W. Jia, Y. M. Chen, and D. G. Fredlund. "Physical and numerical study of lateral diversion by three-layer inclined capillary barrier covers under humid climatic conditions." Canadian Geotechnical Journal 51, no. 12 (December 2014): 1438–48. http://dx.doi.org/10.1139/cgj-2013-0449.
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Southern China has a humid climate and often receives rainfalls that are of high intensity and (or) long duration. This paper investigates the performance of an inclined three-layer cover with capillary barrier effect (CCBE) comprising silt, sand, and gravel, for usage under humid climatic conditions. Physical modeling tests were carried out to observe the response of the three-layer CCBE system to a continuous heavy rainfall of about 70 mm/h. The layered cover model, housed in a 2 m long and 1 m wide instrumented box, is made up of 0.2 m thick silt, 0.1 m thick sand, and 0.1 m thick gravel, and the inclination of the model is 1V:3H. The movement of wetting front, changes in soil suction, and the primary components of water balance were measured during the operation of the physical models. The experimental data was used to calibrate the hydraulic parameters of the numerical model using the unsaturated flow software, SVFlux. Numerical modeling was subsequently carried out on a 60 m long inclined CCBE system to investigate the effective length of lateral diversion under prolonged rainfall. The main findings of the experimental and numerical studies are as follows: (i) the physical model tests showed that the response of the three-layer CCBE system to a heavy rainfall of 70 mm/h was different from the previous observations on experiments where the rainfall was less than 1.6 mm/h; (ii) correlation between the physical modeling and the numerical modeling indicated anisotropic behavior with respect to the hydraulic conductivity in the unsaturated sand layer; (iii) the long inclined, three-layer CCBE system (i.e., 0.6 m thick silt, 0.2 m thick sand, and 0.2 m thick gravel) had an effective length of lateral diversion over 10 m for 30 days of prolonged rainfall (i.e., 1080 mm in total).
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Peres, D. J., and A. Cancelliere. "Derivation and evaluation of landslide-triggering thresholds by a Monte Carlo approach." Hydrology and Earth System Sciences 18, no. 12 (December 8, 2014): 4913–31. http://dx.doi.org/10.5194/hess-18-4913-2014.
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Abstract. Assessment of landslide-triggering rainfall thresholds is useful for early warning in prone areas. In this paper, it is shown how stochastic rainfall models and hydrological and slope stability physically based models can be advantageously combined in a Monte Carlo simulation framework to generate virtually unlimited-length synthetic rainfall and related slope stability factor of safety data, exploiting the information contained in observed rainfall records and field-measurements of soil hydraulic and geotechnical parameters. The synthetic data set, dichotomized in triggering and non-triggering rainfall events, is analyzed by receiver operating characteristics (ROC) analysis to derive stochastic-input physically based thresholds that optimize the trade-off between correct and wrong predictions. Moreover, the specific modeling framework implemented in this work, based on hourly analysis, enables one to analyze the uncertainty related to variability of rainfall intensity within events and to past rainfall (antecedent rainfall). A specific focus is dedicated to the widely used power-law rainfall intensity–duration (I–D) thresholds. Results indicate that variability of intensity during rainfall events influences significantly rainfall intensity and duration associated with landslide triggering. Remarkably, when a time-variable rainfall-rate event is considered, the simulated triggering points may be separated with a very good approximation from the non-triggering ones by a I–D power-law equation, while a representation of rainfall as constant–intensity hyetographs globally leads to non-conservative results. This indicates that the I–D power-law equation is adequate to represent the triggering part due to transient infiltration produced by rainfall events of variable intensity and thus gives a physically based justification for this widely used threshold form, which provides results that are valid when landslide occurrence is mostly due to that part. These conditions are more likely to occur in hillslopes of low specific upslope contributing area, relatively high hydraulic conductivity and high critical wetness ratio. Otherwise, rainfall time history occurring before single rainfall events influences landslide triggering, determining whether a threshold based only on rainfall intensity and duration may be sufficient or it needs to be improved by the introduction of antecedent rainfall variables. Further analyses show that predictability of landslides decreases with soil depth, critical wetness ratio and the increase of vertical basal drainage (leakage) that occurs in the presence of a fractured bedrock.
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Raut, Jayant Raut, Prashant Pande, Avinash Vasudeo, Rajesh Bhagat, Boskey Bahoria, and Atul Kurjekar. "Experimental Tests of Slope Failure due to Rainfall using Physical Slope Modeling." Journal of Advanced Research in Applied Mechanics 126, no. 1 (October 30, 2024): 49–59. http://dx.doi.org/10.37934/aram.126.1.4959.
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In order to investigate the damage due to slope failure is very important. The main aim of this study is to found experimentally the effects of slope and rainfall intensity on stability of slope. We performed number of experimental tests using our varying slope model. To understand the failure mechanism of slopes there are various methods and also some models are been prepared for testing purpose. Slope failure can be occurred due to increase in pore water pressure, weathering of soil, cracking, decomposition of clayey rock fills, intensity of rainfall, duration of rainfall. By considering all these causes analysis of slope stability is most important to protect the slopes from failures. Slope stability analysis can be static, analytical methods to evaluate the stability of hills, natural slopes, excavated slopes etc. Analysis is generally done to understand the causes of failure or factors which affect the movement of slopes etc. Model development is also one of the ways to analyse the slope failure because of some specific reason. So understanding the rainfall effect on the slopes in hilly region is the major aspect to study. Our experimental result shows that vegetation is the effective and economical way of improving stability of slope. It increases that stability of slope by 15 to 25 %.
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Zong, Jingmei, Changjun Zhang, Leifei Liu, and Lulu Liu. "Modeling Rainfall Impact on Slope Stability: Computational Insights into Displacement and Stress Dynamics." Water 16, no. 4 (February 11, 2024): 554. http://dx.doi.org/10.3390/w16040554.
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The susceptibility of loess slopes to collapses, landslides, and sinkholes is a global concern. Rainfall is a key factor exacerbating these issues and affecting slope stability. In regions experiencing significant infrastructure and urban growth, understanding and mitigating rainfall effects on loess landslides is crucial. ADINA numerical software 9 was utilized to explore rain-induced erosion’s influence on landslide dynamics. The simulations were based on local rainfall trends. The rainfall intensities examined were as follows: 200 mm/day, 300 mm/day, and 400 mm/day. The results indicate a pronounced impact of rainfall intensity on both the movement and stress levels within the slope. Higher rainfall intensities lead to increased movement and a wider stress impact area at the base of the slope. It was observed that surface movement is minimal at the slope crest but increases towards the bottom, with the greatest movement seen at the slope’s base.
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Iliopoulou, Theano, Nikolaos Malamos, and Demetris Koutsoyiannis. "Regional Ombrian Curves: Design Rainfall Estimation for a Spatially Diverse Rainfall Regime." Hydrology 9, no. 5 (April 23, 2022): 67. http://dx.doi.org/10.3390/hydrology9050067.
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Ombrian curves, i.e., curves linking rainfall intensity to return period and time scale, are well-established engineering tools crucial to the design against stormwaters and floods. Though the at-site construction of such curves is considered a standard hydrological task, it is a rather challenging one when large regions are of interest. Regional modeling of ombrian curves is particularly complex due to the need to account for spatial dependence together with the increased variability of rainfall extremes in space. We develop a framework for the parsimonious modeling of the extreme rainfall properties at any point in a given area. This is achieved by assuming a common ombrian model structure, except for a spatially varying scale parameter which is itself modeled by a spatial smoothing model for the 24 h average annual rainfall maxima that employs elevation as an additional explanatory variable. The fitting is performed on the pooled all-stations data using an advanced estimation procedure (K-moments) that allows both for reliable high-order moment estimation and simultaneous handling of space-dependence bias. The methodology is applied in the Thessaly region, a 13,700 km2 water district of Greece characterized by varying topography and hydrometeorological properties.
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Dzupire, Nelson Christopher, Philip Ngare, and Leo Odongo. "A Poisson-Gamma Model for Zero Inflated Rainfall Data." Journal of Probability and Statistics 2018 (2018): 1–12. http://dx.doi.org/10.1155/2018/1012647.
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Rainfall modeling is significant for prediction and forecasting purposes in agriculture, weather derivatives, hydrology, and risk and disaster preparedness. Normally two models are used to model the rainfall process as a chain dependent process representing the occurrence and intensity of rainfall. Such two models help in understanding the physical features and dynamics of rainfall process. However rainfall data is zero inflated and exhibits overdispersion which is always underestimated by such models. In this study we have modeled the two processes simultaneously as a compound Poisson process. The rainfall events are modeled as a Poisson process while the intensity of each rainfall event is Gamma distributed. We minimize overdispersion by introducing the dispersion parameter in the model implemented through Tweedie distributions. Simulated rainfall data from the model shows a resemblance of the actual rainfall data in terms of seasonal variation, means, variance, and magnitude. The model also provides mechanisms for small but important properties of the rainfall process. The model developed can be used in forecasting and predicting rainfall amounts and occurrences which is important in weather derivatives, agriculture, hydrology, and prediction of drought and flood occurrences.
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Fuentes, Montserrat, Brian Reich, and Gyuwon Lee. "Spatial–temporal mesoscale modeling of rainfall intensity using gage and radar data." Annals of Applied Statistics 2, no. 4 (December 2008): 1148–69. http://dx.doi.org/10.1214/08-aoas166.
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Dilama Shamsudeen, Shamla, and Adarsh Sankaran. "Landslide hazard mapping of Wayanad District of Kerala, India, incorporating copula-based estimation of joint probability of rainfall." Proceedings of IAHS 387 (November 18, 2024): 79–86. http://dx.doi.org/10.5194/piahs-387-79-2024.
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Abstract. The development and integration of the spatial and temporal probabilities of landslides are required for complete landslide hazard mapping at any location. Under changing climate, the computation of the temporal probability of landslides with rainfall magnitude alone is inaccurate. This research proposes a framework based on copula functions to develop a landslide probability map using multi-site rainfall data by accounting for the rainfall variables of intensity and duration using a joint-probability approach. The proposed technique is used for Wayanad District, Kerala, India, considering extreme rainfall events in 2018. Firstly, the landslide susceptibility map of the district was developed using a robust random forest (RF) model. Based on regional geology, geomorphology, and climate, different regions of Wayanad have varying rainfall thresholds assessed according to the intensity and duration of the rainfall. Then, the temporal probability of landslides was developed, accounting for the intensity and duration of rainfall events using the joint-probability estimation using copula. Through the integration of the landslide spatial probability map with the temporal probability, landslide hazard maps (LHMs) for Wayanad were developed for time periods ranging from 1 to 50 years. The results of the study indicate the need for bi- or multi-variate landslide probability modeling in studies on regional landslide hazard assessments.
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Dorneles, Viviane R., Rita de C. F. Damé, Claudia F. A. Teixeira-Gandra, Patrick M. Veber, Gustavo B. Klumb, and Mario A. A. Ramirez. "Modeling of probability in obtaining intensity-duration-frequency relationships of rainfall occurrence for Pelotas, RS, Brazil." Revista Brasileira de Engenharia Agrícola e Ambiental 23, no. 7 (July 2019): 499–505. http://dx.doi.org/10.1590/1807-1929/agriambi.v23n7p499-505.
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ABSTRACT Based on historical series, for each locality, equations can characterize the relationship between intensity, duration and frequency of rainfall occurrence. The objective of this study was to present two equations that can describe the occurrence of intense rainfall in Pelotas, RS state, over the period 1982-2015. The two equations were denominated conventional and hybrid, depending on the probabilistic model used. Following the conventional methodology, the parameters of Normal, Log-Normal, Gumbel and Gamma probability distributions were adjusted by the maximum likelihood method for return periods of 2, 5, 10, 20, 25, 50 and 100 years. The maximum intensity values for the hybrid equation were obtained using the empirical model of Weibull, considering return periods of 2, 5, 10, 20 and 25 years. On the other hand, the same theoretical distributions used in the conventional equation were applied to return periods of 50 and 100 years. The Kolmogorov-Smirnov test was used to select the best fitting distribution for the data. In order to verify the information acquired through the Weibull empirical model in comparison to the theoretical distributions, the t-test was applied to the angular coefficients. Significant differences were not verified between the values of maximum rainfall intensities obtained using the two methodologies, for the pre-established durations and return periods. Thus, considering the maximum rainfall intensities values (durations of 5-1440 min) and return periods of 2-100 years in the municipality of Pelotas, RS, Brazil, both the hybrid and the conventional intense rainfall equations can be used.
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Starzec, Mariusz, Sabina Kordana-Obuch, and Daniel Słyś. "Assessment of the Feasibility of Implementing a Flash Flood Early Warning System in a Small Catchment Area." Sustainability 15, no. 10 (May 19, 2023): 8316. http://dx.doi.org/10.3390/su15108316.
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The occurrence of flash floods is an increasingly common phenomenon. In many parts of the world, it is associated with an increase in the intensity of rainfall. Reducing the financial and social losses caused by the occurrence of local urban floods is possible through the use of hydrodynamic modeling and real-time flood forecasting. The purpose of this study is to assess the ability of the modeling technique to simulate the flow in a small catchment area and to determine the time remaining to reach the set warning and danger levels. SWMM 5.2 and QuantumGIS software were used in the study. The analysis showed that for the considered catchment area with a short length of the main stream (1612 m), the time possible for implementing countermeasures and evacuating the population is 70 to 120 min. The study also confirmed that short-term rainfall requires less depth to reach high stormwater elevations than long-term rainfall. In addition, a relationship was noted between the preceding rainfall and the height of stormwater and the forecast time. There was an unfavorable reduction in forecasting time as the depth of rainfall increased and its duration shortened. In the case of the analyzed catchment, the maximum elevation of stormwater (Esw,max) is generated by rainfall that is characterized by the highest intensity in the final phase of their duration. Similarly, the longest forecast time (tf) for the maximum stormwater elevation is caused by rainfall, which is characterized by the highest intensity in its final phase. The results of the study can significantly assist local governments when developing a catchment management plan and when trying to implement practices to minimize the negative effects of flash floods.
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Hu, Tengfei, Jingqiao Mao, Peipei Zhang, Diandian Xu, Weiyu Chen, and Huichao Dai. "Hydrological utilization of satellite precipitation estimates in a data-scarce lake region." Water Supply 18, no. 5 (November 13, 2017): 1581–89. http://dx.doi.org/10.2166/ws.2017.223.
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Abstract In developing regions, accurate rain gauge measurements and satellite precipitation estimates that effectively capture rainfall spatial variability are promising sources of rainfall information. In this study, the latest Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) research product, 3B42V7, was validated against ground measurements in the region surrounding the Dongting Lake in China. In the subsequent model-based evaluation and comparison, the two precipitation datasets were separately included as the inputs for data-driven predictive models of the daily Dongting Lake level. The results show that (i) the daily 3B42V7 agrees well with the gauge measurements (correlation coefficient: 0.64–0.73); (ii) 3B42V7 underestimates the frequency of low-intensity (0–30 mm/day) rainfall and the contribution of low-intensity rainfall to the total rainfall volume, but slightly overestimates those of more intense rainfall; (iii) the lake level models driven by rainfall data from the two sources have similar performance, highlighting the potential of using 3B42V7 in data-driven modeling and prediction of hydrological variables in data-scarce regions; and (iv) the inclusion of rainfall as the model input helps achieve a balance between underestimation and overestimation of the lake levels in terms of both magnitude and quantity.
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Szeląg, Bartosz, Adam Kiczko, and Lidia Dąbek. "Stormwater Reservoir Sizing in Respect of Uncertainty." Water 11, no. 2 (February 14, 2019): 321. http://dx.doi.org/10.3390/w11020321.
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The sizing of the stormwater reservoir, as the design of its properties, usually requires simulations of a basin runoff for a long rainfall series using a hydrodynamic model. In the case of insufficient observations, the rainfall series can be reproduced using empirical approaches. One of the crucial elements in the sizing of the stormwater reservoir is determination of duration time and intensity of rainfall (design rainfall event), for which the maximum reservoir capacity is being obtained. The outcome is, however, affected by significant uncertainty of runoff modeling. The aim of the study is to analyze the effect of the uncertainty of a rainfall-runoff model on calculated capacities of stormwater reservoirs, along with estimated duration times of the design rainfall. The characteristics of the rainfall events—intensity, duration, and frequency—were reproduced using an empirical approach of IDF (Intensity–Duration–Frequency). The basin response to the precipitation was modeled using the SWMM (Storm Water Management Model) and its uncertainty was estimated on the basis of the GLUE (Generalized Likelihood Uncertainty Estimation) method. The obtained probabilistic solution was compared with the deterministic one, neglecting the uncertainty. Duration times of the design rainfall determined in respect of the reservoir outflow using the probabilistic model were longer than those found with a deterministic approach. This has an effect on the desired capacities of the stormwater reservoir, which were overestimated when uncertainty was neglected.
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Zinevich, A., H. Messer, and P. Alpert. "Prediction of rainfall intensity measurement errors using commercial microwave communication links." Atmospheric Measurement Techniques 3, no. 5 (October 12, 2010): 1385–402. http://dx.doi.org/10.5194/amt-3-1385-2010.
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Abstract. Commercial microwave radio links forming cellular communication networks are known to be a valuable instrument for measuring near-surface rainfall. However, operational communication links are more uncertain relatively to the dedicated installations since their geometry and frequencies are optimized for high communication performance rather than observing rainfall. Quantification of the uncertainties for measurements that are non-optimal in the first place is essential to assure usability of the data. In this work we address modeling of instrumental impairments, i.e. signal variability due to antenna wetting, baseline attenuation uncertainty and digital quantization, as well as environmental ones, i.e. variability of drop size distribution along a link affecting accuracy of path-averaged rainfall measurement and spatial variability of rainfall in the link's neighborhood affecting the accuracy of rainfall estimation out of the link path. Expressions for root mean squared error (RMSE) for estimates of path-averaged and point rainfall have been derived. To verify the RMSE expressions quantitatively, path-averaged measurements from 21 operational communication links in 12 different locations have been compared to records of five nearby rain gauges over three rainstorm events. The experiments show that the prediction accuracy is above 90% for temporal accumulation less than 30 min and lowers for longer accumulation intervals. Spatial variability in the vicinity of the link, baseline attenuation uncertainty and, possibly, suboptimality of wet antenna attenuation model are the major sources of link-gauge discrepancies. In addition, the dependence of the optimal coefficients of a conventional wet antenna attenuation model on spatial rainfall variability and, accordingly, link length has been shown. The expressions for RMSE of the path-averaged rainfall estimates can be useful for integration of measurements from multiple heterogeneous links into data assimilation algorithms.
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Ekwueme, Chimeme, Ify Nwaogazie, Chiedozie Ikebude, Godwin Amuchi, Jonathan Irokwe, and Diaa Hourani. "Modeling Rainfall Intensity-Duration-Frequency (IDF) and Establishing Climate Change Existence in Umuahia - Nigeria Using Non-Stationary Approach." Hydrology 13, no. 1 (March 7, 2025): 83–89. https://doi.org/10.11648/j.hyd.20251301.19.
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The aim of this study is to develop non-stationary rainfall Intensity-Duration-Frequency (IDF) models or curves for Umuahia, in South East Nigeria. The IDF model development was actualized using a 31-year rainfall record (1992-2022), obtained from the Nigerian Meteorological Agency, NIMET. The research employed trend analysis using Mann-Kendall test and change point detection through CUSUM and Sequential Mann Kendall tests to establish the presence of non-stationarity in rainfall patterns. Three different General Extreme Value (GEV) distribution models were evaluated to determine the best-fit non-stationary model using Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). Results revealed a significant increasing trend in rainfall intensity (p-value = 0.006) with change points identified in 2002-2003. The GEVt-I model consistently demonstrated superior performance across all duration intervals (5-1440 minutes) with the lowest AIC values. A generalized non-stationary IDF model was developed, showing excellent predictive capability (R² = 0.992, MSE = 38.09). The findings highlight the importance of adopting non-stationary approaches for infrastructure design in Umuahia, as traditional stationary methods may significantly underestimate rainfall intensities in the context of climate change. The result from the trend and change point revealed that climate change influences rainfall pattern in Umuahia. Interestingly, the findings of this study align with global trends in climate change impacts on precipitation patterns and underscore the urgent need to update design standards and infrastructure planning approaches in Umuahia, South East of Nigeria.