Literatura académica sobre el tema "Rainfall Intensity Modeling"

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Artículos de revistas sobre el tema "Rainfall Intensity Modeling"

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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 scenari
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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 (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,
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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 (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
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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 o
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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 (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 effec
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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 (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 lesse
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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 lesse
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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 vulne
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Tesis sobre el tema "Rainfall Intensity Modeling"

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Mayeux, Brian Clifford, and Brian Clifford Mayeux. "The relative importance of rainfall intensity versus saturated hydraulic conductivity for runoff modeling of semi-arid watersheds." Thesis, The University of Arizona, 1995. http://hdl.handle.net/10150/626771.

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When using distributed rainfall runoff models in order to simulate the runoff volume and time distribution, one faces the problem of how to represent the spatial distribution of rainfall intensity and soil characteristics when the actual continuous distributions are unknown. There are two objectives for this thesis. The first is to investigate, for semi-arid regions, how the scale of rainfall intensity and soil features affects the simulation of rainfall excess and which is of more importance. The second is to utilize probability distribution theory to develop a scheme which rep
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Martini, Tommaso. "statistical and probabilistic approaches to hydrological data analysis : rainfall patterns, copula-like models and first passage timeapproximations." Electronic Thesis or Diss., Pau, 2024. http://www.theses.fr/2024PAUU3051.

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L'analyse des données de précipitations et la modélisation des nombreuses variables associées sont essentielles dans des domaines tels que l'agriculture, l'écologie et l'ingénierie, et reposent sur des archives historiques en raison de la complexité des systèmes hydrologiques. Les séries de précipitations quotidiennes obtenues à partir de réseaux de pluviomètres sont parmi les plus utilisées. Un modèle fiable et flexible pour un site unique est crucial pour développer des modèles multi-sites plus complexes tenant compte des corrélations spatiales observées dans un réseau dense de stations. Com
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DI, NAPOLI MARIANO. "Spatial prediction of landslide susceptibility/intensity through advanced statistical approaches implementation: applications to the Cinque Terre (Eastern Liguria, Italy)." Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1076506.

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Landslides are frequently responsible for considerable huge economic losses and casualties in mountainous regions especially nowadays as development expands into unstable hillslope areas under the pressures of increasing population size and urbanization (Di Martire et al. 2012). People are not the only vulnerable targets of landslides. Indeed, mass movements can easily lay waste to everything in their path, threatening human properties, infrastructures and natural environments. Italy is severely affected by landslide phenomena and it is one of the most European countries affected by this kind
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Masingi, Vusi Ntiyiso. "Modeling long-term monthly rainfall variability in selected provinces of South Africa using extreme value distributions." Thesis, 2021. http://hdl.handle.net/10386/3457.

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Thesis (M.Sc. (Statistics)) -- University of Limpopo, 2020<br>Several studies indicated a growing trend in terms of frequency and severity of extreme events. Extreme rainfall could cause disasters that lead to loss of property and life. The aim of the study was to model the monthly rainfall variability in selected provinces of South Africa using extreme value distributions. This study investigated the best-fit probability distributions in the five provinces of South Africa. Five probability distributions: gamma, Gumbel, log-normal, Pareto and Weibull, were fitted and the best was selecte
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Mashishi, Daniel. "Modeling average monthly rainfall for South Africa using extreme value theory." Thesis, 2020. http://hdl.handle.net/10386/3399.

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Thesis (M. Sc. (Statistics)) -- University of Limpopo, 2020<br>The main purpose of modelling rare events such as heavy rainfall, heat waves, wind speed, interest rate and many other rare events is to try and mitigate the risk that might arise from these events. Heavy rainfall and floods are still troubling many countries. Almost every incident of heavy rainfall or floods might result in loss of lives, damages to infrastructure and roads, and also financial losses. In this dissertation, the interest was in modelling average monthly rainfall for South Africa using extreme value theory (EVT
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Capítulos de libros sobre el tema "Rainfall Intensity Modeling"

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Hashino, Michio. "Stochastic Formulation of Storm Pattern and Rainfall Intensity-Duration Curve for Design Flood." In Hydrologic Frequency Modeling. Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3953-0_21.

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Bandara, H. A. A. I. S., and Ryo Onishi. "High Resolution Numerical Weather Simulation for Orographic Precipitation as an Accurate Early Warning Tool for Landslide Vulnerable Terrains." In Progress in Landslide Research and Technology. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-44296-4_11.

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AbstractAccurate early warning for rain-induced landslides is still challenging due to regional and local variations of rainfall prediction due to low accuracy, and resolution. The “Multi-Scale Simulator for the Geoenvironment (MSSG)” system, developed by the Tokyo Institute of Technology, Japan Agency for Marine-Earth Science and Technology and Waseda University allows for high-resolution simulations and seamless modeling of weather and climate interactions, and employs advanced meteorological aspects.MSSG simulations compared with rainfall data recorded in the Aranayaka automated rain gauge for past events, including the devastating landslide in 2016. The simulations achieved satisfactory results in reproducing rainfall events. Higher-resolution simulations exhibited higher maximum rainfall intensity and cumulative rainfall accumulation. This study emphasizes the importance of considering finer scales in meteorological simulations to effectively capture the intricate variations associated with extreme rainfall events. This study places significant emphasis on the importance of considering finer scales in meteorological simulations in order to confirm the necessity of high resolutions to capture the temporal and spatial variations of orographic rainfall.
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Erzagian, Egy, Wahyu Wilopo, and Teuku Faisal Fathani. "Landslide Susceptibility Zonation Using GIS-Based Frequency Ratio Approach in the Kulon Progo Mountains Area, Indonesia." In Progress in Landslide Research and Technology. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-44296-4_3.

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AbstractLandslides cause many casualties, environmental damage, property losses, and psychological impacts. Landslides frequently occur in the Kulon Progo Mountains area of Indonesia and are especially triggered by high-intensity rainfall between November and March. Research on landslide susceptibility in the Kulon Progo Mountains area can be a relevant tool to prevent or reduce the risk of landslide potential. Therefore, this research aims to develop a landslide susceptibility map using the frequency ratio (FR) method. Controlling factors, namely, elevation, slope, aspect, lithology, lineament density, distance from streams, distance from roads, land use, and rainfall, were combined with landslide data to develop a landslide susceptibility map by GIS software. Seven hundred and forty-four landslide data points were acquired from field surveys, Google Earth image interpretation, and the Regional Disaster Management Agency (BPBD) of the Kulon Progo, Purworejo, and Magelang regencies. Landslide data were randomly selected for map modeling (80%) and validation (20%). The FR analysis shows that the research area can be classified into four landslide susceptibility zones based on the LSI value: low (LSI 4.05–7.85), moderate (LSI 7.86–9.85), high (LSI 9.86–12.81), and very high (LSI 12.82–19.46). The landslide susceptibility map was validated using the area under the curve (AUC) method, resulting in a success rate of 80.1% and a predictive rate of 81.3%.
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Osorio, Andrés F., Rubén Montoya, Franklin F. Ayala, and Juan D. Osorio-Cano. "Reconstructing the Eta and Iota Events for San Andrés and Providencia: A Focus on Urban and Coastal Flooding." In Disaster Risk Reduction. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-6663-5_3.

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AbstractHurricanes Eta and Iota were the most intense events during the 2020 Atlantic hurricane season, and their passage caused serious infrastructure affectations and even human losses in the Archipelago of San Andrés, Providencia, and Santa Catalina due to the extreme winds, storm surge flooding, and rainfall flooding. Numerical modeling and field measurements were used to reconstruct the effects of these events on the archipelago. The simulations were conducted with WAVEWATCHIII, SWAN, XBeach, Storm Water Management Model (SWMM), and a parametric model for hurricane winds. A differentiated contribution of each hazard on physical infrastructure, coastal ecosystems, and population is represented through: winds up to 50 m/s, significant wave heights (Hs) between 1 and 6 m in intermediate waters (around 10 m deep) associated with flood levels in the order of 2 m on the coast, and flood distances varying between 12 and 904 m. A spatial distribution of Hs and the contribution of wave run-up and storm surge in some areas of the archipelago showed the importance of mangrove and coral reef ecosystems to mitigate the intensity of Eta and Iota on the coast. This study encourages science-based decision-making and provides information for policymakers to consolidate risk assessments in vulnerable zones like the archipelago.
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Shiba, S., R. Ito, and T. Sueishi. "Effect of Rainfall Intensity on Acid Rain Formation by Absorption of Sulfur Dioxide." In Water Pollution: Modelling, Measuring and Prediction. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3694-5_51.

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Kalsnes, Bjørn, and Vittoria Capobianco. "Use of Vegetation for Landslide Risk Mitigation." In Springer Climate. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-86211-4_10.

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AbstractLandslide risk management involves several activities, modelling being a required premise for most of them. Modelling of climate-induced landslides include both the analysis of the triggering process, i.e. static slope stability analysis and dynamic propagation (run-out) analysis. These analyses are vital for mapping purposes, as well as for selection of effective means to reduce the landslide risk when this exceeds a certain value of tolerance. With the prospect of increasing rainfall duration and intensity in parts of Europe, the need for further development of modelling tools is evident. In recent years, the use of Nature-Based Solutions (NBS) for mitigation of natural hazards has further demonstrated the need for developing the modelling tools. The use of vegetation as NBS is increasingly being used for erosion protection and shallow landslide mitigation. For slope stability analyses, the use of vegetation makes the modelling more complex for a number of reasons, mostly linked to the influence of vegetation on both the soil–atmosphere interaction (i.e. rainfall interception, evapotranspiration) and the soil hydro-mechanical properties. All effects that are difficult to model due to lack of knowledge and to large variations in time and space. Even though there is an increasing activity in the geotechnical environment to incorporate the effects of vegetation in the modelling for quantifying the change in slope stability (i.e. calculate slope safety factor), the status is far from being at the level of traditional landslide modelling tools. More efforts are therefore needed in the years to come to demonstrate that the use of vegetation as a viable and effective measure in landslide risk mitigation management can be verified in a more quantifiable manner.
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Koutsoyiannis, Demetris, and Theano Iliopoulou. "Ombrian curves advanced to stochastic modeling of rainfall intensity." In Rainfall. Elsevier, 2022. http://dx.doi.org/10.1016/b978-0-12-822544-8.00003-2.

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Lazzari, Maurizio, Marco Piccarreta, Ram L. Ray, and Salvatore Manfreda. "Modeling Antecedent Soil Moisture to Constrain Rainfall Thresholds for Shallow Landslides Occurrence." In Landslides - Investigation and Monitoring. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.92730.

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Rainfall-triggered shallow landslide events have caused losses of human lives and millions of euros in damage to property in all parts of the world. The need to prevent such hazards combined with the difficulty of describing the geomorphological processes over regional scales led to the adoption of empirical rainfall thresholds derived from records of rainfall events triggering landslides. These rainfall intensity thresholds are generally computed, assuming that all events are not influenced by antecedent soil moisture conditions. Nevertheless, it is expected that antecedent soil moisture conditions may provide critical support for the correct definition of the triggering conditions. Therefore, we explored the role of antecedent soil moisture on critical rainfall intensity-duration thresholds to evaluate the possibility of modifying or improving traditional approaches. The study was carried out using 326 landslide events that occurred in the last 18 years in the Basilicata region (southern Italy). Besides the ordinary data (i.e., rainstorm intensity and duration), we also derived the antecedent soil moisture conditions using a parsimonious hydrological model. These data have been used to derive the rainfall intensity thresholds conditional on the antecedent saturation of soil quantifying the impact of such parameters on rainfall thresholds.
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Panda, Sudhanshu S., Debasmita Misra, Devendra M. Amatya, Johnny M. Grace III, and Anita Thompson. "Advances in modeling soil erosion risk." In Burleigh Dodds Series in Agricultural Science. Burleigh Dodds Science Publishing, 2024. http://dx.doi.org/10.19103/as.2023.0131.09.

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Soil erosion is particularly affected by climate change, especially increases in the amount and intensity of rainfall. The Revised Universal Soil Loss Equation (RUSLE2) developed by USDA-ARS has been developed to quantify soil erosion. However, it does not consider current climate and topographic conditions for estimating those factors, including the rainfall erosivity factor (R-factor) which is particularly significant given more frequent extreme storm events resulting from climate change. This chapter reviews developing a modified RUSLE model using ArcGIS ModelBuilder automation to develop processes for improving USLE factors so that soil erosion quantification can be estimated more precisely in both temporal and spatial dimensions.
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Degefe Merga, Damtew. "Perspective chapter: Responses of the water balance components under land use/land cover and climate change using Geospatial and hydrologic modeling in the Dhidhessa Sub-Basin, Ethiopia." In Global Warming - A Concerning Component of Climate Change [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.1001907.

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The multiple key causes of the hydrological cycle are LULC variability and climate change. The issues of LULC effect on water balances like soil water, evapotranspiration, percolation, base flow, discharge, and water yield through changing land environmental factors and altering soil as well as atmospheric limitations. Climate change, and the other, can direct effect rainfall as well as temperature, causing shifts in watersheds and water resource distribution. Changes of intensity, amplitude, and duration of rainfall influence the amount and variation of river flow, which often exacerbates floods and droughts while also having a negative impact on local and regional water resources. As a result, evaluating the effects of water balance may be vital for water policy and administration. The scientific community and policymakers have paid close attention to LULC research and evaluating the climate impacts
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Actas de conferencias sobre el tema "Rainfall Intensity Modeling"

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Thomas, M., T. G. Schmitt, U. Leinweber, and H. Gysi. "Usage of Radar Measured Rainfall Intensity Distributions in Urban Runoff Modelling." In Specialty Symposium on Urban Drainage Modeling at the World Water and Environmental Resources Congress 2001. American Society of Civil Engineers, 2001. http://dx.doi.org/10.1061/40583(275)37.

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Konuk, I., U. O. Akpan, and D. P. Brennan. "Random Field Modeling of Rainfall-Induced Soil Movement." In 2002 4th International Pipeline Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/ipc2002-27165.

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Natural oil and gas transmission pipeline networks often traverse regions where potential slow ground movements may affect pipeline structural integrity. One of the primary causes of slow ground movement in any region involves the duration, amount, and intensity of rainfall. The phenomenon of rainfall-induced slow ground movement is characterized by both spatial and temporal variability, and involves uncertainties that are best modeled using a probabilistic methodology. A random field modeling strategy is formulated in this study, in which spatial and temporal correlations between rainfall and
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Heshani, P. H. T. D., H. G. L. N. Gunawardhana, and J. Sirisena. "Incorporating rainfall projections into hydrological modeling for enhanced design hydrograph estimation." In Civil Engineering Research Symposium 2024. Department of Civil Engineering, University of Moratuwa, 2024. http://dx.doi.org/10.31705/cers.2024.26.

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In the context of changing climate conditions, the design of hydrographs faces increasing uncertainties due to shifts in precipitation patterns, hydrological regimes, and a rise in extreme weather events. This study assesses potential uncertainties in design hydrographs linked to future climate change in the Kalu River Basin, Sri Lanka, focusing on the Ellagawa sub-basin. The Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS) was selected based on a comprehensive literature review to account for anticipated changes in rainfall patterns and their impact on streamflow. Seven pr
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Hassanpour, Pezhman. "Model of a Fluid-Level System for the Design and Analysis of Detention Basins Considering Recent Weather Extreme Events and Historic Precipitation Data." In ASME 2023 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/imece2023-116564.

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Abstract Engineering systems such as flood control dams and storm drain systems are designed to adhere to specific requirements outlined in engineering design codes. These codes heavily rely on local historic climate and precipitation data, which are updated every few years. However, the revision cycles of engineering codes and climate data are not necessarily synchronized. Consequently, it can take a decade or more for a shift in historic climate data to be reflected in the engineering codes. Meanwhile, climate change has increased the frequency and severity of extreme weather conditions. To
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Niranjana, J. S., Feba Paul, Hridya D. Nambiar, Ashly Joy, and Neethu Roy. "Flood Risk Assessment of Thiruvananthapuram City, Kerala." In International Web Conference in Civil Engineering for a Sustainable Planet. AIJR Publisher, 2021. http://dx.doi.org/10.21467/proceedings.112.21.

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Flood is one of the most dangerous and deadliest natural hazards in the world which devastates both life and economy to a very large extent. In Kerala, climate change induced floods are becoming an annual problem. In the midyear of 2018 and 2019, Thiruvananthapuram, the capital city of Kerala, witnessed heavy rainfall and strong winds which resulted in widespread damage in various parts of the City. Flood risk assessment study provides a comprehensive detail of geographic areas and elements that are vulnerable to the particular hazard. As far as Thiruvananthapuram is considered, most of the fl
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BEILICCI, Erika Beata Maria, and Robert BEILICCI. "Influence of Rainfall Characteristics on Runoff in a Small Watershed." In Air and Water – Components of the Environment 2021 Conference Proceedings. Casa Cărţii de Ştiinţă, 2021. http://dx.doi.org/10.24193/awc2021_13.

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Due to climate change, extreme rainfall is more frequent, and the phenomenon of drought and desertification in some parts of the world is accentuated. Scientists forecast that these trends to continue as the planet continue to warm. An increasingly common phenomenon is the occurrence of flash floods in areas where human intervention on natural conditions has been significant. Over this intervention is superimposed the modification of the characteristics of extreme rainfalls (duration, intensity, height), resulting a series of negative consequences on the ecosystems of the watersheds. For their
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Molikevych, Roman S. "CURRENT FLOODING CONDITIONS OF SETTLEMENTS IN THE KHERSON REGION (UKRAINE)." In 22nd International Multidisciplinary Scientific GeoConference 2022. STEF92 Technology, 2022. http://dx.doi.org/10.5593/sgem2022v/3.2/s12.05.

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Kherson region has the largest share of irrigated land among all regions of Ukraine. At the same time, it is the largest arid region with a significant area of drainageless massifs. All this contributes to the occurrence of flooding of territories. The main task of the research is to identify modern factors of flooding of settlements in the Kherson region (Ukraine). The goals of the study were to analyze the hydrogeological conditions in the places of flooding, to identify modern changes in the rainfall regime and their impact on the frequency and intensity of flooding in the region, to determ
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"Improved rainfall frequency analysis through separation of storm intensity and storm arrival frequency." In 25th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, 2023. http://dx.doi.org/10.36334/modsim.2023.oshea.

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Razali, Irfan Haziq, Aizat Mohd Taib, Wan Hanna Melini Wan Mohtar, Norinah Abd Rahman, and Siti Amirah Aziz. "Numerical modelling on the effect of rainfall intensity on slope stability." In ADVANCES IN FRACTURE AND DAMAGE MECHANICS XX. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0133892.

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"Changes in intensity-frequency-duration relationship of heavy rainfalls at a station in Melbourne." In 20th International Congress on Modelling and Simulation (MODSIM2013). Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2013. http://dx.doi.org/10.36334/modsim.2013.l12.yilmaz.

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Informes sobre el tema "Rainfall Intensity Modeling"

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Wagner, Anna, Christopher Hiemstra, Glen Liston, Katrina Bennett, Dan Cooley, and Arthur Gelvin. Changes in climate and its effect on timing of snowmelt and intensity-duration-frequency curves. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41402.

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Snow is a critical water resource for much of the U.S. and failure to account for changes in climate could deleteriously impact military assets. In this study, we produced historical and future snow trends through modeling at three military sites (in Washington, Colorado, and North Dakota) and the Western U.S. For selected rivers, we performed seasonal trend analysis of discharge extremes. We calculated flood frequency curves and estimated the probability of occurrence of future annual maximum daily rainfall depths. Additionally, we generated intensity-duration-frequency curves (IDF) to find r
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Matus, Sean, and Daniel Gambill. Automation of gridded HEC-HMS model development using Python : initial condition testing and calibration applications. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/46126.

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The US Army Corps of Engineers’s (USACE) Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) rainfall-runoff model is widely used within the research community to develop both event-based and continuous rainfall-runoff models. The soil moisture accounting (SMA) algorithm is commonly used for long-term simulations. Depending on the final model setup, 12 to 18 parameters are needed to characterize the modeled watershed’s canopy, surface, soil, and routing processes, all of which are potential calibration parameters. HEC-HMS includes optimization tools to facilitate model calibrati
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