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Samat, S. R., N. Othman, and N. F. M. Zaidi. "The Development of Rainfall Temporal Pattern for Kuantan River Basin." International Journal of Engineering Technology and Sciences 5, no. 2 (2018): 14–21. http://dx.doi.org/10.15282/ijets.v5i2.1376.
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One of the design rainfall event used in flood estimation is rainfall temporal pattern that gives the proportion of total rainfall in different periods within a given duration. The study focuses on developing a temporal rainfall pattern for the Kuantan River Basin in Pahang. According to Urban Stormwater Manual Second Edition (MSMA 2) that used as guideline for designing stormwater in Malaysia, rainfall temporal patterns are divided by region. In this study, the developments of rainfall temporal pattern in Kuantan River Basin are based specifically on rainfall station in this river basin. The Average Variability Method (AVM) that used in MSMA 2 and recommended by the Australian Rainfall and Runoff were used in developing rainfall temporal pattern for this study. The rainfall data of every 5 minutes for 16 years starting from 2000 to 2015 were gathered from Department of Irrigation and Drainage (DID) for purpose of study. In this study, the rainfall temporal pattern is deriving for 15 minutes, 30 minutes, 60 minutes, 120 minutes, 180 minutes and 360 minutes. The results show the significance differences of the rainfall temporal patterns between the results from this study and available value in MSMA 2 for the region of Pahang (Region 2). Therefore, each specific rainfall station has its own reliable rainfall temporal pattern that crucially important for flood estimation in Kuantan River Basin for future development plan
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Ali, Noorfathiah Che, Yuliarahmadila Erfen, Nurul Farehah Amat, Zawani Mohd Zahudi, and Mohd Shalahuddin Adnan. "Development of Temporal Rainfall Pattern for Segamat District." Applied Mechanics and Materials 773-774 (July 2015): 1205–9. http://dx.doi.org/10.4028/www.scientific.net/amm.773-774.1205.
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The designing of rainfall temporal pattern is very important in displaying the diversity and intensity of rainfall in addition to flood estimation and planning. The main purpose of this study was to develop a temporal rainfall pattern for Segamat District. Average Variability Method, AVM which had recommended by the Australian Rainfall and Runoff were used to derive design rainfall temporal patterns for this study. The survey data for 5 minute interval from 2003 to 2012 for 4 selected rainfall stations that obtained from the Drainage and Irrigation Department, DID have been selected. In this study, the temporal rainfall pattern is built for 10 minutes, 15 minutes, 30 minutes, 60 minutes, 120 minutes, 180 minutes, and 360 minutes. The results shows the actual rainfall on the field in the form of temporal rainfall pattern. Up to 75% of the temporal patterns in the region can be classified as intermediate type while the advance and delay type are 11% and 14%, respectively. From the temporal rainfall pattern, the duration of rainfall occurs can be predicted, therefore, the probability of the flooding during the period can be estimated.
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A. Bustami, Rosmina, Nor Azalina Rosli, Jethro Henry Adam, and Kuan Pei Li. "Development of Temporal Rainfall Pattern for Southern Region of Sarawak." Journal of Civil Engineering, Science and Technology 3 (December 1, 2012): 17–23. http://dx.doi.org/10.33736/jcest.98.2012.
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In the process of a design rainfall, information on rainfall duration, average rainfall intensity and temporal rainfall pattern is important. This study focuses on developing a temporal rainfall pattern for the Southern region of Sarawak since temporal pattern for Sarawak is yet to be available in the Malaysian Urban Storm Water Management Manual (MSMA), which publishes temporal pattern for design storms only for Peninsular Malaysia. The recommended technique by the Australian Rainfall and Runoff (AR&R) known as the ‘Average Variability Method’ and method in Hydrological Procedure No.1-1982 are used to derive design rainfall temporal pattern for the study. Rainfall data of 5 minutes interval from year 1998 to year 2006 for 7 selected rainfall stations in the selected region is obtained from Department of Irrigation and Drainage (DID). The temporal rainfall patterns developed are for 10 minutes,15 minutes, 30 minutes, 60 minutes, 120 minutes, 180 minutes and 360 minutes duration. The results show that Southern region of Sarawak has an exclusive rainfall pattern, which is different from the pattern developed for Peninsular Malaysia.
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Grundmann, Jens, Sebastian Hörning, and András Bárdossy. "Stochastic reconstruction of spatio-temporal rainfall patterns by inverse hydrologic modelling." Hydrology and Earth System Sciences 23, no. 1 (2019): 225–37. http://dx.doi.org/10.5194/hess-23-225-2019.
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Abstract. Knowledge of spatio-temporal rainfall patterns is required as input for distributed hydrologic models used for tasks such as flood runoff estimation and modelling. Normally, these patterns are generated from point observations on the ground using spatial interpolation methods. However, such methods fail in reproducing the true spatio-temporal rainfall pattern, especially in data-scarce regions with poorly gauged catchments, or for highly dynamic, small-scale rainstorms which are not well recorded by existing monitoring networks. Consequently, uncertainties arise in distributed rainfall–runoff modelling if poorly identified spatio-temporal rainfall patterns are used, since the amount of rainfall received by a catchment as well as the dynamics of the runoff generation of flood waves is underestimated. To address this problem we propose an inverse hydrologic modelling approach for stochastic reconstruction of spatio-temporal rainfall patterns. The methodology combines the stochastic random field simulator Random Mixing and a distributed rainfall–runoff model in a Monte Carlo framework. The simulated spatio-temporal rainfall patterns are conditioned on point rainfall data from ground-based monitoring networks and the observed hydrograph at the catchment outlet and aim to explain measured data at best. Since we infer a three-dimensional input variable from an integral catchment response, several candidates for spatio-temporal rainfall patterns are feasible and allow for an analysis of their uncertainty. The methodology is tested on a synthetic rainfall–runoff event on sub-daily time steps and spatial resolution of 1 km2 for a catchment partly covered by rainfall. A set of plausible spatio-temporal rainfall patterns can be obtained by applying this inverse approach. Furthermore, results of a real-world study for a flash flood event in a mountainous arid region are presented. They underline that knowledge about the spatio-temporal rainfall pattern is crucial for flash flood modelling even in small catchments and arid and semiarid environments.
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BONG, CHARLES HIN JOO, ABIGAIL JOSEP, MATTHEW RUJI EDNA, and DARMESAH GABDA. "SITE SPECIFIC RAINFALL TEMPORAL PATTERN (RTP) FOR SUSTAINABLE DEVELOPMENT OF KUCHING CITY, SARAWAK, MALAYSIA." JOURNAL OF SUSTAINABILITY SCIENCE AND MANAGEMENT 17, no. 6 (2022): 52–65. http://dx.doi.org/10.46754/jssm.2022.06.005.
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An understanding of rainfall temporal patterns is important for flood estimation and planning for sustainable flood designs and management. However, current published rainfall temporal patterns in design manuals are mostly generalised for a region which covers large areas. This raises doubts regarding its accuracy, especially for sensitive urban areas which are prone to flash floods. In the current study, a site-specific rainfall temporal pattern has been developed for Kuching using the Average Variability Method. The data of 5 minutes interval from year 2010 to 2018 for Kuching Airport rainfall station was used in the current study. Both the normalized and non-normalised rainfall temporal patterns were developed for 10 minutes, 15 minutes, 30 minutes, 60 minutes, 120 minutes, 180 minutes and 360 minutes. The developed rainfall temporal patterns were then compared with the recommendations from two other published design manuals. Results showed that most of the fractions in the published rainfall temporal patterns have more than 20% differences when compared with the current study. The developed rainfall temporal patterns from the current study can be adopted for flood design purposes in the city of Kuching in Sarawak. This fulfils Sustainable Development Goal 11 by reducing the adverse effects of flood in the city.
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Back, Álvaro J., Augusto C. Pola, Nilzo I. Ladwig, and Hugo Schwalm. "Erosive rainfall in the Rio do Peixe Valley in Santa Catarina, Brazil: Part II - Characteristics and temporal distribution pattern." Revista Brasileira de Engenharia Agrícola e Ambiental 21, no. 11 (2017): 780–84. http://dx.doi.org/10.1590/1807-1929/agriambi.v21n11p780-784.
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ABSTRACT Exploring the characteristics of erosive rain is an important aspect of studying erosive processes, and it allows researchers to create more natural and realistic hydrological simulations. The objective of this study was to analyse the characteristics of erosive rain and to determine the temporal distribution pattern of erosive rainfall in the Valley of Rio do Peixe in the state of Santa Catarina, Brazil. Daily pluviograms from the meteorological stations located in the cities Campos Novos, Videira, and Caçador in Santa Catarina from 1984 to 2014 were utilized for this study. By studying rainfall that is classified as erosive, the values of kinetic energy, maximum intensity in thirty minutes, and the value of EI30 erosivity index were determined. The rainfall was also classified according to the temporal distribution of rainfall in advanced, intermediate, and delayed patterns. Erosive rainfalls occur at a frequency of 53.3% advanced, 31.1% intermediate, and 15.6% delayed patterns. Erosive rainfall has an average precipitation amount of 25.5 mm, duration of 11.1 h, kinetic energy of 5.6 MJ ha-1, maximum intensity of 30 min of 17.7 mm h-1, and erosivity of 206.4 MJ mm ha-1 h-1. The highest frequency of erosive rainfall occurred in rainfalls lasting from 6 to 12 h (36.1%), followed by rainfalls lasting from 4 to 6 h (22.4%).
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Li, Haichao, Hiroshi Ishidaira, Yanqi Wei, Kazuyoshi Souma, and Jun Magome. "Assessment of Sponge City Flood Control Capacity According to Rainfall Pattern Using a Numerical Model after Muti-Source Validation." Water 14, no. 5 (2022): 769. http://dx.doi.org/10.3390/w14050769.
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Urban floods are a common urban disaster that threaten the economy and development of cities. Sponge cities can improve flood resistance ability and reduce floods by setting low-impact development measures (LID). Evaluating flood reduction benefits is the basic link in the construction of sponge cities. Therefore, it is of great significance to evaluate the benefits of sponge cities from the perspective of different rain patterns. In this study, we investigated the urban runoff of various rainfall patterns in Mianyang city using the Strom Water Management Model (SWMM). We employed 2–100-year return periods and three different temporal rainfall downscaling methods to evaluate rain patterns and simulate urban runoff in Mianyang, with and without the implementation of sponge city measures. After calibration, model performance was validated using multi-source data concerning flood peaks and inter-annual variations in flood magnitude. Notably, the effects of peak rainfall patterns on historical floods were generally greater than the effects of synthetic rainfalls generated by temporal downscaling. Compared to the rainfall patterns of historical flood events, the flood protection capacities of sponge cities can be easily overestimated when using the synthetic rainfall patterns generated by temporal downscaling. Overall, an earlier flood peak was associated with better flood sponge city protection capacity. In this context, the results obtained in this study provide useful reference information about the impact of rainfall pattern on urban flood control by LID, and can be used for sponge city design in other part of China.
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Ran, Qihua, Feng Wang, and Jihui Gao. "Modelling Effects of Rainfall Patterns on Runoff Generation and Soil Erosion Processes on Slopes." Water 11, no. 11 (2019): 2221. http://dx.doi.org/10.3390/w11112221.
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Rainfall patterns and landform characteristics are controlling factors in runoff and soil erosion processes. At a hillslope scale, there is still a lack of understanding of how rainfall temporal patterns affect these processes, especially on slopes with a wide range of gradients and length scales. Using a physically-based distributed hydrological model (InHM), these processes under different rainfall temporal patterns were simulated to illustrate this issue. Five rainfall patterns (constant, increasing, decreasing, rising-falling and falling-rising) were applied to slopes, whose gradients range from 5° to 40° and projective slope lengths range from 25 m to 200 m. The rising-falling rainfall generally had the largest total runoff and soil erosion amount; while the constant rainfall had the lowest ones when the projective slope length was less than 100 m. The critical slope of total runoff was 15°, which was independent of rainfall pattern and slope length. However, the critical slope of soil erosion amount decreased from 35° to 25° with increasing projective slope length. The increasing rainfall had the highest peak discharge and erosion rate just at the end of the peak rainfall intensity. The peak value discharges and erosion rates of decreasing and rising-falling rainfalls were several minutes later than the peak rainfall intensity.
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Vantas, Konstantinos, and Epaminondas Sidiropoulos. "Intra-Storm Pattern Recognition through Fuzzy Clustering." Hydrology 8, no. 2 (2021): 57. http://dx.doi.org/10.3390/hydrology8020057.
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The identification and recognition of temporal rainfall patterns is important and useful not only for climatological studies, but mainly for supporting rainfall–runoff modeling and water resources management. Clustering techniques applied to rainfall data provide meaningful ways for producing concise and inclusive pattern classifications. In this paper, a timeseries of rainfall data coming from the Greek National Bank of Hydrological and Meteorological Information are delineated to independent rainstorms and subjected to cluster analysis, in order to identify and extract representative patterns. The computational process is a custom-developed, domain-specific algorithm that produces temporal rainfall patterns using common characteristics from the data via fuzzy clustering in which (a) every storm may belong to more than one cluster, allowing for some equivocation in the data, (b) the number of the clusters is not assumed known a priori but is determined solely from the data and, finally, (c) intra-storm and seasonal temporal distribution patterns are produced. Traditional classification methods include prior empirical knowledge, while the proposed method is fully unsupervised, not presupposing any external elements and giving results superior to the former.
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Wang, Fan. "Temporal Pattern Analysis of Local Rainstorm Events in China During the Flood Season Based on Time Series Clustering." Water 12, no. 3 (2020): 725. http://dx.doi.org/10.3390/w12030725.
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Similar to the rainfall depth, duration and intensity, the temporal pattern is also an important characteristic of rainstorm events. Studies have shown that temporal patterns will influence runoff modelling, flash flood warning thresholds as well as urban and infrastructure flood inundation simulations. In this study, a time series clustering method using dynamic time warping (DTW) as similarity measurement criteria is proposed to analyze rainfall temporal patterns. Compared with the existing approaches, it can better reflect the real rainfall processes. Based on this novel method, five representative temporal patterns were extracted from 13,299 rainstorm events during the flood season in China. Through the analysis of their statistical characteristics, the disaster-causing risks of each temporal pattern were compared. Furthermore, we found that for rainstorm events whose durations are less than 24 h, the rainfall is mainly concentrated in 3 to 6 h, which proposes higher requirements for the design of flood control and drainage projects compared with those using average intensities of 12 or 24 h as design standards. Finally, through regional analysis, we found that the rainfall depth, intensity and peak value are affected by the macroclimate. However, the temporal patterns are not strongly related to the macroclimate but are more likely to be affected by the local climate and topography, which needs further studies at smaller scales.
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Thoảng, Trần Thanh, La Tài, Trịnh Vĩnh Quân, et al. "Assessment of Potential Rainfall Distribution Patterns and Their Relationship with Inundation in Tra Vinh Province, Vietnam." Journal of Climate Change 8, no. 4 (2022): 51–61. http://dx.doi.org/10.3233/jcc220030.
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This study aimed to develop temporal rainfall distribution patterns of 1-day, 3-, 5-, and 7-consecutive rain days for three meteorological stations in Tra Vinh province (Cang Long, Tieu Can, and Tra Cu), using daily rainfall data from 1978 to 2017. The study follows the Vietnamese National Standards (TCVN 10406:2015:Irrigation Works – Calculation of Design Drainage Coefficients) to determine the frequency of events of various rainfall distribution drainage patterns. Thereafter, the probability method was conducted to identify rainfall pattern design according to a 10-year return period. Only Cang Long meteorological station exhibited enough single events of rainfall patterns (>10) for 3 consecutive days to determine a rainfall distribution drainage pattern, fitting in pattern type 1 and distribution types 2 and 3. However, for all distribution types of rainfall patterns, the one with the highest last-day rainfall is the most adverse pattern. Therefore, this study recommends building a 3-consecutive day design rainfall for Cang Long station of pattern type 1 and distribution type 3 for precautionary purposes.
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Liu, Yuanyuan, Yesen Liu, Hancheng Ren, et al. "Spatial and Temporal Pattern of Rainstorms Based on Manifold Learning Algorithm." Water 15, no. 1 (2022): 37. http://dx.doi.org/10.3390/w15010037.
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Identifying the patterns of rainstorms is essential for improving the precision and accuracy of flood forecasts and constructing flood disaster prevention systems. In this study, we used a manifold learning algorithm method of machine learning to analyze rainstorm patterns. We analyzed the spatial–temporal characteristics of heavy rain in Beijing and Shenzhen. The results showed a strong correlation between the spatial–temporal pattern of rainstorms and underlying topography in Beijing. However, in Shenzhen, the spatial–temporal distribution characteristics of rainstorms were more closely related to the source of water vapor causing the rainfall, and the variation in characteristics was more complex and diverse. This method may be used to quantitatively describe the development and dynamic spatial–temporal patterns of rainfall. In this study, we found that spatial–temporal rainfall distribution characteristics, extracted by machine learning technology could be explained by physical mechanisms consistent with the climatic characteristics and topographic conditions of the region.
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Burian, S. J., and S. R. Durrans. "Evaluation of an artificial neural network rainfall disaggregation model." Water Science and Technology 45, no. 2 (2002): 99–104. http://dx.doi.org/10.2166/wst.2002.0033.
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Previous research produced an artificial neural network (ANN) temporal rainfall disaggregation model. After proper training the model can disaggregate hourly rainfall records into sub-hourly time increments. In this paper we present results from continued evaluations of the performance of the ANN model specifically examining how the errors in the disaggregated rainfall hyetograph translate to errors in the prediction of the runoff hydrograph. Using a rainfall-runoff model of a hypothetical watershed we compare the runoff hydrographs produced by the ANN-predicted 15-minute increment rainfall pattern to runoff hydrographs produced by (1) the observed 15-minute increment rainfall pattern, (2) the observed hourly-increment rainfall pattern, and (3) the 15-minute increment rainfall pattern produced by a disaggregation model based on geometric similarity. For 98 test storms the peak discharges produced by the ANN model rainfall pattern had a median under-prediction of 16.6%. This relative error was less than the median under-prediction in peak discharge when using the observed 15-minute rainfall patterns aggregated to hourly increments (40.8%), and when using rainfall patterns produced by the geometric similarity rainfall disaggregation model (21.9%).
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Wu, Yuze, Ming Tang, Zuhao Zhou, et al. "Rainfall Pattern Construction Method Based on DTW-HCA and Urban Flood Simulation: A Case Study of Nanchang City, China." Water 16, no. 1 (2023): 65. http://dx.doi.org/10.3390/w16010065.
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Due to the different design standards of urban drainage and water conservancy facilities, numerous coordination and linkage issues arise when confronting extreme rainfall. In this paper, three clustering methods were used to cluster rainfall events, and the results demonstrate that the dynamic time warping-hierarchical clustering algorithm (DTW-HCA) effectively captures the temporal similarity of time series. Then, the Pilgrim and Cordery rainfall distribution method was utilized to extract the characteristics of eight clusters of rainfall events, and eight kinds of rainfall patterns were obtained. Last, after importing the rainfall patterns into the MIKE model of Qingshan Lake to conduct flood simulations, the impacts of different rainfall patterns on municipal systems and water conservancy systems were assessed by the depth and area of urban waterlogging, as well as the water levels and discharge of rivers. Based on this, three rainfall patterns are proposed as a designed rainfall pattern (DRP), an extreme rainfall pattern for urban drainage facilities verification (ERPUDFV) and an extreme rainfall pattern for water conservancy facilities verification (ERPWCFV), which aim to provide a reference basis for designing region-specific extreme rainfall patterns, as well as the verification of urban drainage and water conservancy facilities.
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Akbari, A., F. Othman, and A. Abu Samah. "Probing on suitability of TRMM data to explain spatio-temporal pattern of severe storms in tropic region." Hydrology and Earth System Sciences Discussions 8, no. 5 (2011): 9435–68. http://dx.doi.org/10.5194/hessd-8-9435-2011.
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Abstract. Spatial and temporal pattern of rainfall play an important role in runoff generation. Raingauge density influences the accuracy of spatial pattern and time interval influence the accuracy of temporal pattern of storms. Usually due to practical and financial limitation the perfect distribution is not achievable. Several sources of data are used to define the behavior of rainfall over a watershed. Raingauges station, radar operation and satellite sensor are the main source of rainfall estimation over the space and time. Recording raingauges are the most common source of rainfall data in many countries. However raingauge network has not adequate coverage in many watersheds spatially in developing countries. Therefore other global source of rainfall data may be useful for hydrological analysis such as flood modeling. This research assessed the ability of TRMM rainfall estimates for explain the Spatio-temporal pattern of severe storm over Klang watershed which is a hydrologically well instrumented watershed. It was experienced that TRMM rainfall estimates are 35% less than actual data for the investigated events. Due to coarse temporal resolution of TRMM (3 h) compare to gauge rainfall (15 min), significant uncertainty influences identifying the start and end of storm event and consequently their resultant time to peak of flood hydrograph which is extremely important in flood forecasting systems. Due to coarse pixel size of TRMM data, watershed scale is important issue.
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Aryal, Santosh K., Bryson C. Bates, Edward P. Campbell, Yun Li, Mark J. Palmer, and Neil R. Viney. "Characterizing and Modeling Temporal and Spatial Trends in Rainfall Extremes." Journal of Hydrometeorology 10, no. 1 (2009): 241–53. http://dx.doi.org/10.1175/2008jhm1007.1.
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Abstract A hierarchical spatial model for daily rainfall extremes that characterizes their temporal variation due to interannual climatic forcing as well as their spatial pattern is proposed. The model treats the parameters of at-site probability distributions for rainfall extremes as “data” that are likely to be spatially correlated and driven by atmospheric forcing. The method is applied to daily rainfall extremes for summer and winter half years over the Swan–Avon River basin in Western Australia. Two techniques for the characterization of at-site extremes—peaks-over-threshold (POT) analysis and the generalized extreme value (GEV) distribution—and three climatic drivers—the El Niño–Southern Oscillation as measured by the Southern Oscillation index (SOI), the Southern Hemisphere annular mode as measured by an Antarctic Oscillation index (AOI), and solar irradiance (SI)—were considered. The POT analysis of at-site extremes revealed that at-site thresholds lacked spatial coherence, making it difficult to determine a smooth spatial surface for the threshold parameter. In contrast, the GEV-based analysis indicated smooth spatial patterns in daily rainfall extremes that are consistent with the predominant orientation of storm tracks over the study area and the presence of a coastal escarpment near the western edge of the basin. It also indicated a linkage between temporal trends in daily rainfall extremes and those of the SOI and AOI. By applying the spatial models to winter and summer extreme rainfalls separately, an apparent increasing trend in return levels of summer rainfall to the northwest and decreasing trends in return levels of winter rainfall to the southwest of the region are found.
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Rebora, N., L. Ferraris, J. von Hardenberg, and A. Provenzale. "Rainfall downscaling and flood forecasting: a case study in the Mediterranean area." Natural Hazards and Earth System Sciences 6, no. 4 (2006): 611–19. http://dx.doi.org/10.5194/nhess-6-611-2006.
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Abstract. The prediction of the small-scale spatial-temporal pattern of intense rainfall events is crucial for flood risk assessment in small catchments and urban areas. In the absence of a full deterministic modelling of small-scale rainfall, it is common practice to resort to the use of stochastic downscaling models to generate ensemble rainfall predictions to be used as inputs to rainfall-runoff models. In this work we present an application of a new spatial-temporal downscaling procedure, called RainFARM, to an intense precipitation event predicted by the limited-area meteorological model Lokal Model over north-west Italy. The uncertainty in flood prediction associated with the small unresolved scales of forecasted precipitation fields is evaluated by using an ensemble of downscaled fields to drive a semi-distributed rainfall-runoff model.
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Trinugroho, Muchamad Wahyu, Sigit Supadmo Arif, Sahid Susanto, Bayu Dwi Apri Nugroho, and Abi Prabowo. "Changes in Rainfall Pattern in Bengawan Solo Sub-Watershed." SAINS TANAH - Journal of Soil Science and Agroclimatology 19, no. 2 (2022): 249. http://dx.doi.org/10.20961/stjssa.v19i2.61640.
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<p>Rainfed farming is vulnerable to climate variability, which changes rainfall patterns. Rainfall variability disrupts rainfed rice cultivation because a change in rainfall will affect the rice crop calendar. An analysis of long-term trends over a specific area is required to understand rainfall variability. The aim of this study was to assess climate variability in terms of rainfall magnitude and frequency by analyzing spatial and temporal rainfall trends in Bengawan Solo Sub-Watershed as well as the rainfed rice production. Daily rainfall data from 10 rain gauge stations over the sub-watershed area from the years 1975 to 2020 were used. The data was managed and collected by the Bengawan Solo Watershed authority. Pearson, Mann-Kendall, and Sen’s Slope tests were applied to assess the recorded data correlation, rainfall trends, and magnitude of trends into annual, monthly, and 10-day. The findings of the study indicated the spatial and temporal inhomogeneous rainfall pattern for all locations for 10-day, monthly and annual patterns. The mountainous regions at Tawang Mangu and Ngrambe stations tend to experience an upward trend (positive magnitude), while the coastal regions at Nglirip and Bojonegoro stations have a downward trend(negative magnitude). Those trends also confirmed that coastal regions would be drier than mountainous regions in the future. Understanding this rainfall trend can assist with rainfed farming strategic planning.</p>
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Ampitiyawatta, A. D., R. M. S. M. Wijenayake, E. P. R. H. H. W. Nilmalgoda, Eranga M. Wimalasiri, and K. C. Kaushalya. "Temporal Rainfall Trends in the Northern and Eastern Coastal Regions of Sri Lanka: An Analysis Spanning from 1981 to 2019." Journal of Food and Agriculture 17, no. 2 (2024): 16–35. https://doi.org/10.4038/jfa.v17i2.5312.
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The annual and seasonal rainfall trends and patterns along the Northern and Eastern coastal belt of Sri Lanka were analyzed by studying the daily rainfall records from 1981 to 2019 from five locations: Jaffna, Kanukkerny Tank, Trincomalee, Batticaloa, and Pottuvil, because no such pattern has been addressed previously. The Mann-Kendall test and Sen’s slope estimator were used to detect the annual and seasonal rainfall trends and the magnitude of the trend, respectively. The findings indicate that the eastern coastal belt exhibits more consistent rainfall patterns both annually and seasonally. The rainfall pattern of Jaffna, situated in the Northern coastal region, differs from the aforementioned locations. The long-term mean annual rainfall of all locations was less than 1750 mm. The lowest seasonal rainfall occurs during the first inter-monsoon (FIM) season, amounting to less than 200 mm. During the second inter-monsoon (SIM) season, the entire area experiences its peak monthly rainfall, reaching up to 280 mm/month. The Northeast monsoon (NEM) is distinctly wet season for the entire Northern and Eastern coastal belt, with rainfall surpassing 100 mm/month. Trend investigations reveal that only the Batticaloa has a significantly increasing trend of 17.5 mm/year. This annual significant (p <0.05) trend primarily stems from the noteworthy trend during the SIM, with an increase of 7.3 mm/season. Although converse trends are evident during other seasons across all locations, none of them are statistically significant (p >0.05). In conclusion, the eastern coastal belt demonstrates a more consistent rainfall pattern both annually and seasonally, whereas the rainfall pattern of the northern region differs from it. Furthermore, only the Batticaloa region shows a statistically significant trend with an increment of 17.5 mm/year.
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Conradie, Willem Stefaan, Piotr Wolski, and Bruce Charles Hewitson. "Spatial heterogeneity in rain-bearing winds, seasonality and rainfall variability in southern Africa's winter rainfall zone." Advances in Statistical Climatology, Meteorology and Oceanography 8, no. 1 (2022): 31–62. http://dx.doi.org/10.5194/ascmo-8-31-2022.
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Abstract. A renewed focus on southern Africa's winter rainfall zone (WRZ) following the Day Zero drought and water crisis has not shed much light on the spatial patterns of its rainfall variability and climatological seasonality. However, such understanding remains essential in studying past and potential future climate changes. Using a dense station network covering the region encompassing the WRZ, we study spatial heterogeneity in rainfall seasonality and temporal variability. These spatial patterns are compared to those of rainfall occurring under each ERA5 synoptic-scale wind direction sector. A well-defined “true” WRZ is identified with strong spatial coherence between temporal variability and seasonality not previously reported. The true WRZ is composed of a core and periphery beyond which lies a transition zone to the surrounding year-round rainfall zone (YRZ) and late summer rainfall zone. In places, this transition is highly complex, including where the YRZ extends much further westward along the southern mountains than has previously been reported. The core receives around 80 % of its rainfall with westerly or north-westerly flow compared to only 30 % in the south-western YRZ incursion, where below-average rainfall occurs on days with (usually pre-frontal) north-westerly winds. This spatial pattern corresponds closely to those of rainfall seasonality and temporal variability. Rainfall time series of the core and surroundings are very weakly correlated (R2<0.1), also in the winter half-year, implying that the YRZ is not simply the superposition of summer and winter rainfall zones. In addition to rain-bearing winds, latitude and annual rain day climatology appear to influence the spatial structure of rainfall variability but have little effect on seasonality. Mean annual rainfall in the true WRZ exhibits little association with the identified patterns of seasonality and rainfall variability despite the driest core WRZ stations being an order of magnitude drier than the wettest stations. This is consistent with the general pattern of near homogeneity within the true WRZ, in contrast to steep and complex spatial change outside it.
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Libina, R. S., R. Jegankumar, K. Prakash, D. Venkita Surya, S. P. Dhanabalan, and M. A. Arya. "Spatial and Temporal Trend Analysis of Rainfall Distribution in Nambiyar Watershed, Tamil Nadu." Geo-Eye 10, no. 2 (2021): 18–25. https://doi.org/10.53989/bu.ge.v10i2.4.
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This study is an attempt to comprehend the spatial and temporal trend of rainfall distribution in the Nambiyar watershed. The daily rainfall data was processed for the period from 1988 to 2018 to map the spatial distribution and analyse the temporal trend of rainfall. The results reveals that mean annual rainfall received in the watershed is 1026.81 mm. Statistical techniques like Mann- Kendall test and Sen’s Slope estimator were used to analyse presence of trend and correlation of variables. Among four seasons northeast monsoon contributes around 47 per cent (482.57 mm) of the total rainfall. The results brought out the fact that annual rainfall of the watershed does not exhibit any significant trend at α=0.05 or 95% of confidence level. Agricultural and allied activities which requires adequate irrigation is determined by the rainfall received in this watershed. Hence this study brings out the spatial and temporal pattern of rainfall distribution in Nambiyar watershed. Keywords: Rainfall trend, GIS, Sen's slope, Mann-Kendall test
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Ayyoob, K. C., and S. Saravanan. "Spatio-temporal analysis of pattern of rainfall in Kerala." INTERNATIONAL RESEARCH JOURNAL OF AGRICULTURAL ECONOMICS AND STATISTICS 9, no. 2 (2018): 378–82. http://dx.doi.org/10.15740/has/irjaes/9.2/378-382.
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Wang, Yong, Yulian Jin, Jiaqi Wang, Zhenzhen Ma, Xing Liu, and Xinlan Liang. "Laboratory-Scaled Investigation into Combined Impacts of Temporal Rainfall Patterns and Intensive Tillage on Soil and Water Loss." Agronomy 13, no. 6 (2023): 1472. http://dx.doi.org/10.3390/agronomy13061472.
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Many studies have focused on the impacts of rainfall duration and intensity, while overlooking the role of rainfall patterns on intensive tillage erosion in hilly agricultural landscapes. The objective of this study was to determine the combined effects of rainfall patterns and tillage erosion on surface runoff and soil loss on sloping farmland in the purple soil area of China. Five simulated rainfall patterns (constant, rising, falling, rising–falling, and falling–rising) with the same total precipitation were designed, and the intensive tillage treatment (IT) and no-tillage treatment (NT) were subjected to simulated rainfall using rectangular steel tanks (2 m × 5 m) with a slope of 15°. To analyse the differences in the hydrological characteristics induced by tillage erosion, we calculated the flow velocity (V), Reynolds number (Re), Froude number (Fr), and Darcy–Weisbach resistance coefficient (f). The results indicate that significant differences in surface runoff and sediment yield were found among different rainfall patterns and rainfall stages (p < 0.05). The falling pattern and falling–rising pattern had a shorter time gap between the rainfall initiation and runoff occurrence as well as a larger sediment yield than those of the other rainfall patterns. The value of f varied from 0.30 to 9.05 for the IT and 0.48 to 11.57 for the NT and exhibited an approximately inverse trend to V and Fr over the course of the rainfall events. Compared with the NT, the mean sediment yield rates from the IT increased the dynamic range of 8.34–16.21% among the different rainfall patterns. The net contributions of the IT ranged from 2.77% to 46.39% in terms of surface runoff and 10.14–78.95% in terms of sediment yield on sloping farmland. The surface runoff and sediment yield were positively correlated with rainfall intensity, V, and Fr, but negatively correlated with f irrespective of tillage operation (p < 0.05). The results showed that the tillage erosion effects on soil and water loss were closely related to rainfall patterns in hilly agricultural landscapes. Our study not only sheds light on the mechanism of tillage erosion and rainfall erosion but also provides useful insights for developing tillage water erosion prediction models to evaluate soil and water loss on cultivated hillslopes.
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Máca, P., and P. Torfs. "The influence of temporal rainfall distribution in the flood runoff modelling." Soil and Water Research 4, Special Issue 2 (2010): S102—S110. http://dx.doi.org/10.17221/471-swr.
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The rainfall input is one of the main factors influencing the magnitude of the runoff response during a flood event. Its temporal and spatial distribution significantly contributes to the formation of hydrograph shape, peak discharge and flood volume. A novel approach to the evaluation of the role of the temporal rainfall pattern of hydrograph is presented in this contribution. The methodology shown is based on the coupling of the deterministic event based runoff model with the stochastic rainfall disaggregation model. The rainfall model simulates the hyetograph ensemble, which is the direct input to the calibrated event based runoff model. The event based runoff model calibration is based on the evaluation of real flood events. The rainfall ensemble is simulated according to the preservation of important statistical properties, which are estimated from the real rainfall data inputs. The proposed combination of two simulation techniques enables to generate the hydrograph ensemble upon a single flood event. The evaluation of the temporal rainfall distribution impact on the flood runoff response is performed through the determination of the selected rainfall runoff characteristics of the simulated hydrograph ensemble. The main result confirms the importance of the rainfall volume inputs and its temporal distribution on the flood runoff generation. The methodology shown enables to evaluate the potential of the real flood event to generate the flood event within the conditions of the small catchment scale.
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Langat, Amos Kipkorir, and John Kamwele Mutinda. "Rainfall Pattern in Kenya: Bayesian Non-parametric Model Based on the Normalized Generalized Gamma Process." Asian Journal of Probability and Statistics 26, no. 7 (2024): 34–47. http://dx.doi.org/10.9734/ajpas/2024/v26i7628.
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Understanding the pattern of rainfall in Kenya is crucial for a range of sectors, including agriculture, water management, and disaster risk reduction. In this research, we propose a Bayesian non-parametric approach to model the rainfall patterns in Kenya. Specifically, we use a hierarchical Dirichlet process mixture model to cluster the rainfall stations and identify groups of stations with similar rainfall patterns. We then model the rainfall distribution within each group using a Bayesian non-parametric model based on the normalized generalized gamma process. We apply our method to a dataset of daily rainfall measurements from 150 stations across Kenya for the period 1980-2021. Our results reveal distinct regional patterns of rainfall, with some regions experiencing bimodal rainfall patterns while others have unimodal patterns. We also find that the rainfall distribution within each region exhibits heavy tails and skewedness, which cannot be accurately captured by parametric models. In conclusion, our approach provides a flexible and interpretable framework for modeling complex spatio-temporal data such as rainfall patterns, and can inform decision-making in various sectors.
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Na, Wooyoung, and Chulsang Yoo. "Evaluation of Rainfall Temporal Distribution Models with Annual Maximum Rainfall Events in Seoul, Korea." Water 10, no. 10 (2018): 1468. http://dx.doi.org/10.3390/w10101468.
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This study evaluated five models of rainfall temporal distribution (i.e., the Yen and Chow model, Mononobe model, alternating block method, Huff model, and Keifer and Chu model), with the annual maximum rainfall events selected from Seoul, Korea, from 1961 to 2016. Three different evaluation measures were considered: the absolute difference between the rainfall peaks of the model and the observed, the root mean square error, and the pattern correlation coefficient. Also, sensitivity analysis was conducted to determine whether the model, or the randomness of the rainfall temporal distribution, had the dominant effect on the runoff peak flow. As a result, the Keifer and Chu model was found to produce the most similar rainfall peak to the observed, the root mean square error was smaller for the Yen and Chow model and the alternating block method, and the pattern correlation was larger for the alternating block method. Overall, the best model to approximate the annual maximum rainfall events observed in Seoul, Korea, was found to be the alternating block method. Finally, the sensitivity of the runoff peak flow to the model of rainfall temporal distribution was found to be much higher than that to the randomness of the rainfall temporal distribution. In particular, in small basins with a high curve number (CN) value, the sensitivity of the runoff peak flow to the randomness of the rainfall temporal distribution was found to be insignificant.
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Lin, Fu-Ru, Nan-Jing Wu, and Ting-Kuei Tsay. "Applications of Cluster Analysis and Pattern Recognition for Typhoon Hourly Rainfall Forecast." Advances in Meteorology 2017 (2017): 1–17. http://dx.doi.org/10.1155/2017/5019646.
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Based on the factors of meteorology and topography, it is assumed that there exist some certain patterns in spatial and temporal rainfall distribution of a watershed. A typhoon rainfall forecasting model is developed under this assumption. If rainfall patterns can be analyzed and recognized in terms of individual watershed topography, only the spatial rainfall distribution prior to a specific moment is needed to forecast the rainfall in the next coming hours. It does not need any other condition in meteorology and climatology. Besides, supplement techniques of missing rainfall gage data are also considered to build an all-purpose forecast model. By integrating techniques of cluster analysis and pattern recognition, present proposed rainfall forecasting model is tested using historical data of Tamsui River Basin in Northern Taiwan. Good performance is validated by checking on coefficient of correlation and coefficient of efficiency.
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Bonfils, Céline J. W., Benjamin D. Santer, Thomas J. Phillips, et al. "Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate*." Journal of Climate 28, no. 24 (2015): 9997–10013. http://dx.doi.org/10.1175/jcli-d-15-0341.1.
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Abstract El Niño–Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with coupled general circulation models (CGCMs) to investigate how regional precipitation in the twenty-first century may be affected by changes in both ENSO-driven precipitation variability and slowly evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of twentieth-century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in twenty-first-century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with twentieth-century observations and more stationary during the twenty-first century. Finally, the model-predicted twenty-first-century rainfall response to cENSO is decomposed into the sum of three terms: 1) the twenty-first-century change in the mean state of precipitation, 2) the historical precipitation response to the cENSO pattern, and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.
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Jothimani, Palanisamy, Paravel Nishanth, Chidamparam Poornachandhra, Palanivel Kavya, Shanmugam Vinothkanna, and Koothan Vanitha. "Impact of Temporal Variability of Rainfall on Groundwater Quality of Dindigul District, India." International Journal of Environment and Climate Change 15, no. 1 (2025): 376–87. https://doi.org/10.9734/ijecc/2025/v15i14699.
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The present study aims to provide information regarding the temporal distribution of important physical-chemical parameters that affect water chemistry. Graphical representation is recorded for important physiochemical variables to understand groundwater quality and ecological status of the groundwater systems over a period of time in Dindigul district, Tamil Nadu. The Dindigul District monthly rainfall data were collected from the Public Works Department (PWD), Surface and Groundwater Division, Govt. of Tamil Nadu. After 1995, that there was a gradual increase in the rainfall pattern and the excess rainfall was recorded as 1018.59 mm, 1052.82 mm, 1073.73mm during the years 1996, 2008, 2010 respectively. The lowest rainfall of 588.51mm was recorded in 2012. Apart from excess rainfall years, all the other cases recorded the minimum rainfall and showed the decreasing trend from1995 to 2012. After 1990s, release of untreated waste water from Tannery industry in to the water ways and lands - contaminated the groundwater. The change in the rainfall pattern and quantity played important role in the salinity of the groundwater. After 1995s, the NO3value of 16.8mg L-1 was recorded during 2010. Accordingly, it had the highest excess rainfall of 1073.73 mm, during 2010. Deficit rainfall in 2000 ranges from 337.67mm, the NO3 value of 68.8 mg L-1 was recorded. The chemical characteristics of ground water are determined by the level of contribution from the geological sources and infiltration water from the surface sources. Monitoring of pollution patterns and its trends with respect to urbanization is an important task for achieving sustainable management of groundwater.
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Mobeen, Muhammad, Haroon Ahmed, Fahad Ullah, et al. "Impact of climate change on the precipitation pattern of district Sargodha, Pakistan." International Journal of Climate Change Strategies and Management 9, no. 1 (2017): 21–35. http://dx.doi.org/10.1108/ijccsm-10-2015-0147.
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Purpose Spatio-temporal variations in precipitation pattern of district Sargodha is one of the most significant researchable questions because of the massive reliance on rainfall for agricultural practice in the study area. The pattern of current rainfall in the study area is unexpectedly changed. The purpose of the present study is to examine the changing precipitation pattern and to link it with climate change. Design/methodology/approach The study was conducted by using rainfall data of the past 30 years collected from 8 meteorological stations around the study area. The averages of rainfall on monthly basis were temporally arranged, and the fluctuation trends were studied using GIS and statistics. The temporal data of rainfall were compared and contrasted with the precipitation normals of the study area from 1981to 2010. The rainfall deviation in the present study was calculated. The spatial pattern of rainfall was plotted by interpolating the eight points of Punjab around the study area for the first two decades, whereas the past decade was analysed by incorporating five more points of Tehsils in the existing eight. The spatial and statistical representation of data were examined by compare and contrast with the previous findings. Findings The rainfall in the study area showed remarkable changes in magnitude and spatiality. The rainfall in the district is on the rise, whereas the spatial pattern of rainfall is becoming more complex and anomalous in character. This paper provides convincing evidence about the impact of climate change on the magnitude and spatial patterns of precipitation in the study area. Practical implications It will be helpful for understanding the shifts in the rainfall pattern in future as well as for the preparation of response to the issue of climate change and its impacts. Originality/value The current manuscript, for the very first time, provided detailed insights about the precipitation pattern shifting during the last 30 years in district Sargodha, Punjab, Pakistan. Furthermore, agricultural sector would likely get severally affected because of seasonal changes in climatic factors like rainfall and have strong food security implications. The current findings will be useful to manage the climate change-related issues in Pakistan and helpful for the policy makers to design a coping strategy for climate change impacts.
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Nuryanto, Danang Eko, Yuaning Fajariana, Radyan Putra Pradana, Rian Anggraeni, Imelda Ummiyatul Badri, and Ardhasena Sopaheluwakan. "Modeling of Heavy Rainfall Triggering Landslide Using WRF Model." Agromet 34, no. 1 (2020): 55–65. http://dx.doi.org/10.29244/j.agromet.34.1.55-65.
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This study revealed the behavior of heavy rainfall before landslide event based on the Weather Research Forecasting (WRF) model. Simulations were carried out to capture the heavy rainfall patterns on 27 November 2018 in Kulonprogo, Yogyakarta. The modeling was performed with three different planetary boundary layer schemes, namely: Yonsei University (YSU), Sin-Hong (SH) and Bougeault and Lacarrere (BL). Our results indicated that the variation of rainfall distribution were small among schemes. The finding revealed that the model was able to capture the radar’s rainfall pattern. Based on statistical metric, WRF-YSU scheme was the best outperforming to predict a temporal pattern. Further, the study showed a pattern of rainfall development coming from the southern coastal of Java before 13:00 LT (Local Time=WIB=UTC+7) and continued to inland after 13:00 LT. During these periods, the new clouds were developed. Based on our analysis, the cloud formation that generated rainfall started at 10:00 LT, and hit a peak at 13:00 LT. A starting time of cloud generating rainfall may be an early indicator of landslide.
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Su, Lei, Zongqiang Xie, Wenting Xu, and Changming Zhao. "Variability of throughfall quantity in a mixed evergreen-deciduous broadleaved forest in central China." Journal of Hydrology and Hydromechanics 67, no. 3 (2019): 225–31. http://dx.doi.org/10.2478/johh-2019-0008.
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Abstract Mixed evergreen-deciduous broadleaved forest is the transitional type of evergreen broadleaved forest and deciduous broadleaved forest, and plays a unique eco-hydrologic role in terrestrial ecosystem. We investigated the spatio-temporal patterns of throughfall volume of the forest type in Shennongjia, central China. The results indicated that throughfall represented 84.8% of gross rainfall in the forest. The mean CV (coefficient of variation) of throughfall was 27.27%. Inter-event variability in stand-scale throughfall generation can be substantially altered due to changes in rainfall characteristics, throughfall CV decreased with increasing rainfall amount and intensity, and reached a quasi-constant level when rainfall amount reached 25 mm or rainfall intensity reached 2 mm h−1. During the leafed period, the spatial pattern of throughfall was highly temporal stable, which may result in spatial heterogeneity of soil moisture.
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Wang, Y. T., T. Q. Zhang, Q. C. Hu, I. P. O'Halloran, C. S. Tan, and K. Reid. "Temporal patterns of soil phosphorus release to runoff during a rainfall event as influenced by soil properties and its effects on estimating soil P losses." Canadian Journal of Soil Science 91, no. 3 (2011): 339–47. http://dx.doi.org/10.4141/cjss09097.
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Wang, Y. T., Zhang, T. Q., Hu, Q. C., O'Halloran, I. P., Tan, C. S. and Reid, K. 2011. Temporal patterns of soil phosphorus release to runoff during a rainfall event as influenced by soil properties and its effects on estimating soil P losses. Can. J. Soil Sci. 91: 339–347. The phosphorus (P) released in soil runoff during a rainfall event varies as labile P is depleted, and the dynamic pattern can be a function of soil P content and other soil properties. This study was conducted to determine the temporal pattern of runoff dissolved reactive P (DRP) concentration during a simulated rainfall event and the controlling soil properties. Soil samples were collected from six soil types across the province of Ontario, with 10 sites for each, to provide a wide range of soil test P (STP) levels. The instantaneous DRP concentration in surface runoff created during the rainfall event could be predicted by time t (min, since the onset of surface runoff) through a power function: DRP=αt−β, where α and β are constants representing initial potential of soil P release to runoff as DRP at the onset of surface runoff and DRP decrease rate with time, respectively. The values of α and β for a given soil could be determined by DPSM3-2 (Mehlich-3 P/Mehlich-3 Al) using the following formulas:[Formula: see text] The description of the temporal pattern of runoff DRP concentration during a rainfall event with the constants estimated using DPSM3−2 can aid in the prediction of soil runoff DRP loss.
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Gintoron, Christharina S., and Fatimah Abang. "Temporal Diversity of the Nymphalids in Kubah National Park, Sarawak, Malaysia." Tropical Natural History 21, no. 2 (2021): 285–98. https://doi.org/10.58837/tnh.21.2.245056.
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Unique microhabitats caused temporal-space separation which also indicates that animals are constrained in their flexibility to adapt to the environment. Arthropods was recorded to be temporally patchy within seasons, and in the tropical region, rainfall fluctuations are somewhat varied although only in a considerable range. These minute variations are still however observed to provide unique microhabitats to the insects and thus knowledge on the effects of the rainfall is still much required. To determine any distribution patterns of the nymphalid butterflies, bait-trapping was conducted from May to November 2009 in Kubah National Park, Sarawak. Even though there was a linear relationship between the total rainfall and numbers of nymphalids, there was no significant correlation between the nymphalids and rainfall distribution (p-value > 0.05). Rainfall in the preceded month could increase the overall nymphalids abundance which coincides with the leaf-flushing peak, suitably for the larval stages. In contrast, heavy rainfall during the data collection could also lead to larval mortality. Rainfall parameter and possibly many more environmental variables are important, as the distribution pattern of the nymphalids are strongly related to the environment.
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Kuo, Yi-Chun, Ming-An Lee, and Mong-Ming Lu. "Association of Taiwan’s Rainfall Patterns with Large-Scale Oceanic and Atmospheric Phenomena." Advances in Meteorology 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/3102895.
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A 50-year (1960–2009) monthly rainfall gridded dataset produced by the Taiwan Climate Change Projection and Information Platform Project was presented in this study. The gridded data (5 × 5 km) displayed influence of topography on spatial variability of rainfall, and the results of the empirical orthogonal functions (EOFs) analysis revealed the patterns associated with the large-scale sea surface temperature variability over Pacific. The first mode (65%) revealed the annual peaks of large rainfall in the southwestern mountainous area, which is associated with southwest monsoons and typhoons during summertime. The second temporal EOF mode (16%) revealed the rainfall variance associated with the monsoon and its interaction with the slopes of the mountain range. This pattern is the major contributor to spatial variance of rainfall in Taiwan, as indicated by the first mode (40%) of spatial variance EOF analysis. The second temporal EOF mode correlated with the El Niño Southern Oscillation (ENSO). In particular, during the autumn of the La Niña years following the strong El Niño years, the time-varying amplitude was substantially greater than that of normal years. The third temporal EOF mode (7%) revealed a north-south out-of-phase rainfall pattern, the slowly evolving variations of which were in phase with the Pacific Decadal Oscillation. Because of Taiwan’s geographic location and the effect of local terrestrial structures, climate variability related to ENSO differed markedly from other regions in East Asia.
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Hettiarachchi, Suresh, Conrad Wasko, and Ashish Sharma. "Increase in flood risk resulting from climate change in a developed urban watershed – the role of storm temporal patterns." Hydrology and Earth System Sciences 22, no. 3 (2018): 2041–56. http://dx.doi.org/10.5194/hess-22-2041-2018.
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Abstract. The effects of climate change are causing more frequent extreme rainfall events and an increased risk of flooding in developed areas. Quantifying this increased risk is of critical importance for the protection of life and property as well as for infrastructure planning and design. The updated National Oceanic and Atmospheric Administration (NOAA) Atlas 14 intensity–duration–frequency (IDF) relationships and temporal patterns are widely used in hydrologic and hydraulic modeling for design and planning in the United States. Current literature shows that rising temperatures as a result of climate change will result in an intensification of rainfall. These impacts are not explicitly included in the NOAA temporal patterns, which can have consequences on the design and planning of adaptation and flood mitigation measures. In addition there is a lack of detailed hydraulic modeling when assessing climate change impacts on flooding. The study presented in this paper uses a comprehensive hydrologic and hydraulic model of a fully developed urban/suburban catchment to explore two primary questions related to climate change impacts on flood risk. (1) How do climate change effects on storm temporal patterns and rainfall volumes impact flooding in a developed complex watershed? (2) Is the storm temporal pattern as critical as the total volume of rainfall when evaluating urban flood risk? We use the NOAA Atlas 14 temporal patterns, along with the expected increase in temperature for the RCP8.5 scenario for 2081–2100, to project temporal patterns and rainfall volumes to reflect future climatic change. The model results show that different rainfall patterns cause variability in flood depths during a storm event. The changes in the projected temporal patterns alone increase the risk of flood magnitude up to 35 %, with the cumulative impacts of temperature rise on temporal patterns and the storm volume increasing flood risk from 10 to 170 %. The results also show that regional storage facilities are sensitive to rainfall patterns that are loaded in the latter part of the storm duration, while extremely intense short-duration storms will cause flooding at all locations. This study shows that changes in temporal patterns will have a significant impact on urban/suburban flooding and need to be carefully considered and adjusted to account for climate change when used for the design and planning of future storm water systems.
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Jana, C., N. M. Alam, D. Mandal, M. Shamim, and Rajesh Kaushal. "Spatio-temporal rainfall trends in the twentieth century for Bundelkhand region, India." Journal of Water and Climate Change 8, no. 3 (2017): 441–55. http://dx.doi.org/10.2166/wcc.2017.120.
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Globally, climate change and extreme weather events are occurring more frequently, impacting water resources and farming systems. Therefore, spatio-temporal analysis of long-term rainfall is much needed to understand the variability of rainfall occurrence. The present study attempts to analyse spatio-temporal rainfall change scenarios in the 20th century (1901–2000) over Bundelkhand, one of the drought hit regions of India. Analysis shows that major rainfall contributed from 3 months, i.e. July, August and September. However, decreasing rainfall trend during monsoon season and increasing trend during pre-monsoon and post-monsoon season indicates the scenario of shifting rainfall from normal occurrence. This result is supported by decreasing seasonality index (SI) (1.94–1.1). The northern part of the region witnessed positive annual and monsoon rainfall trend but the southern part observed negative trend. Pettitt's test indicates 1983 is the most probable change year with 0.95 probability, after which annual and monsoon rainfall was found decreasing. Wavelet analysis revealed that extreme rainfall occurrence was observed with a periodicity of 2–16 years. However, Bundelkhand rainfall pattern depicts declining rainfall trends, heading towards a further drier phase with more irregular rainfall in the coming era. The study will serve as future reference in similar regions in the world to determine vital weather patterns which may impact farming systems.
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Sok, Rachna. "Typical Rainfall Distribution Pattern of Flood Event Caused by Tropical Cyclone at Bima City, West Nusa Tenggara, Indonesia." Journal of the Civil Engineering Forum 5, no. 1 (2019): 1. http://dx.doi.org/10.22146/jcef.34604.
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Tropical cyclones are the most serious meteorological phenomena that hit Bima city in December 2016. The strong winds and heavy precipitation associated with a typhoon significantly affect the weather in this city. The impact of a tropical cyclone on precipitation variability in Bima is studied using rainfall data for analyzing hourly rainfall distribution pattern during the event. Depend on the geographic situation and climate characteristic, the hourly rainfall distribution pattern of one area is different to others area. The research aims to analyze hourly rainfall distribution pattern in the form of the rainfall intensity distribution. This research is conducted using one automatic rainfall gauge in Bima city, West Nusa Tenggara province that obtained from Regional Disaster Management Agency (BPBD). The results showed that two events of rainfall were recorded. The first rainfall event was on 20th to 21st December 2016 with a total rainfall 191.4 mm. The second rainfall event occurred on 22nd to 23rd December 2016 with a total rainfall 126.2 mm. The rainfall distribution pattern has rainfall intensity peak at 45% of duration with cumulative rainfall reached 70%. It was found there is no common pattern of temporal rainfall distribution for rainfall induced by tropical cyclones.
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Ibrahim, Adama, and B. Mochiah M. "Assessing the relationship between outbreaks of the African Armyworm and Climatic Factors in the Forest Transition Zone of Ghana." British Journal of Environment & Climate Change 7, no. 2 (2017): 69–82. https://doi.org/10.9734/BJECC/2017/30588.
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The African armyworm <em>Spodoptera exempta </em>(Walker) is an important migratory pest of cereal crops and grasslands in sub-Saharan Africa. It demonstrates great variability in the extent and severity of infestation of its host crops. The African armyworm is known to cause extensive damage to maize crops and rangeland in the transition zone of Ghana. The work reported here was an investigation of the relationship between the Normalized Difference Vegetation Index (NDVI), rainfall and temperature and how they influence the outbreak of this moth species in the Ejura-Sekyeredumase district of Ghana. The temporal patterns of the variables and their interrelationships were evaluated through graphical, logistic and standardization z-score transformations. A strong similarity between temporal patterns of vegetation index and rainfall was established. On the other hand, the temporal pattern of temperature runs opposite to NDVI and rainfall patterns. Standardized NDVI anomaly revealed periods of low vegetation index with corresponding high wetness denoting damage to vegetation due to the activities of the insects during outbreaks. These revelations confirm reports gathered from local famers. NDVI therefore appears to be a good predictor of armyworm outbreaks. Indeed a relationship was established between the occurrences of the moth species and multi-temporal 10-day NDVI signals. The study confirmed that rainfall and temperature influence the occurrence of armyworms.
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Mondal, M. Shahjahan, Sara Nowreen, and Mostofa Najmus Sakib. "Scale-Dependent Reliability of Projected Rainfalls over Bangladesh with the PRECIS Model." Climate 8, no. 2 (2020): 20. http://dx.doi.org/10.3390/cli8020020.
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The regional climate model, Providing REgional Climates for Impact Studies (PRECIS), has been widely used throughout the world to generate climate change projections for impact studies and adaptations. Its recent application in South Asia also includes the projection of rainfall extremes. In spite of its wide application, a stringent validation of the model is yet to be reported. In this study, we assessed the performance of the model in simulating annual, monthly and extreme rainfalls over Bangladesh by using a number of statistical techniques, e.g., pattern (both spatial and temporal) correlation, root mean square difference (RMSD), mean absolute difference (MAD), Student’s t-test for significance, probability density functions, etc. The results indicated that the PRECIS model could capture the overall spatial pattern of mean annual and monthly rainfalls very well. However, the inter-annual variability was poorly simulated by the model. In addition, the model could not capture the rainfall extremes. A spatial aggregation of rainfall data did not improve the reliability of the model as far as variability and extremes are concerned. Therefore, further improvements of the model and/or its driving global climate model are warranted for its practical use in the generation of rainfall scenarios.
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Pinheiro, Antonio G., Thais E. M. dos S. Souza, Suzana M. G. L. Montenegro, Abelardo A. de A. Montenegro, and Sérgio M. S. Guerra. "Rainfall pattern and erosion potential in the physiographic regions of the state of Pernambuco, Brazil." Revista Brasileira de Engenharia Agrícola e Ambiental 22, no. 12 (2018): 849–53. http://dx.doi.org/10.1590/1807-1929/agriambi.v22n12p849-853.
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ABSTRACT The objective of the present study was to characterize the spatial and temporal (2000-2015) rainfall pattern variability and erosive potential in the different physiographic regions of the state of Pernambuco, Brazil. Rainfall data series (3 to 12 years) from 25 weather stations of the state were analyzed. Erosive rainfall events (more than 10 mm depth) were considered to evaluate the annual erosivity index, monthly erosivity index (EI30), rainfall erosivity factor (R), and rainfall pattern. The inverse distance weighting (IDW) - inverse of the square of the distance - was used to create spatial interpolation and develop maps. The rainfall data from the weather stations showed average annual rainfall of 827 mm and average erosivity of 4,784 MJ mm ha-1 h-1. The Metropolitan region of Pernambuco presented the highest rainfall erosivity index, with annual average of 9,704 MJ mm ha-1 h-1; and the Sertão do São Francisco region had the lowest, with annual average of 4,902 MJ mm ha-1 h-1. The state of Pernambuco presented advanced (42%), intermediate (38%), and delayed (20%) rainfall patterns.
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Ponciano, Juan A., William Polanco, and Marlon Barrios. "Dengue outbreaks pattern in southern Guatemala." Ciencia, Tecnología y Salud 6, no. 2 (2019): 158–70. http://dx.doi.org/10.36829/63cts.v6i2.631.
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This study analyses time series of dengue occurrence in the southern region of Guatemala. Temporal patterns of epidemic outbreaks in the department of Escuintla were investigated using the official reports from 2001 to 2013. In order to identify underlying associations with climate behavior, the epidemiological data were compared with historical reports available for temperature, rainfall and humidity. Preliminary results reveal that waves of dengue outbreaks exhibit a periodic pattern modulated by climatic conditions. A hierarchical cluster analysis allowed to indirectly estimate the degree of association of each climatic variable with dengue occurrences, showing the dominance of rainfall in dengue outbreaks patterns in three different localities. A further prospective analysis was performed to check whether epidemic trends driven by rainfall are hold in the subsequent years. Results presented here give support to predictive models for dengue incidence driven by climate.
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Na, Wooyoung, Changhyun Jun, and Sang Yeob Kim. "Influence of Rainfall Pattern on Wetness Index for Infinite Slope Stability Analysis." Water 15, no. 14 (2023): 2535. http://dx.doi.org/10.3390/w15142535.
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Landslides are one of the riskiest disasters combining excessive rainfall and unstable slope that a wetness index can quantify. The wetness index generated by water infiltration considering the rainfall pattern such as cumulated rainfall, rainfall duration and rainfall intensity should be estimated for the slope stability analysis. Even though the infiltration capacity of soils has been largely focused to evaluate the slope stability, the temporal patterns of rainfall have commonly been ignored or assumed as a steady state for the prediction of the slope failure in the previous studies. Thus, this study focuses more on evaluating the influence of various rainfall patterns on the slope stability, and compares it with an actual landslide incident that occurred in 2011, in Korea. The factor of safety (FS) considering the time-dependent wetness index variation is used to determine the slope stability. For the various rainfall designs, the uniform rainfall distribution, Yen and Chow, Mononobe, alternating block and second quartile Huff models are adopted. Thereafter, the FS variations from five models are compared with an actual landslide incident in Seoul, Korea. Among the rainfall designs, the models that consider the abrupt rainfall intensity capture the landslide time with an FS < 1. Therefore, the appropriate adoption of a rainfall distribution model should be highlighted for landslide prediction.
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Balbastre-Soldevila, García-Bartual, and Andrés-Doménech. "A Comparison of Design Storms for Urban Drainage System Applications." Water 11, no. 4 (2019): 757. http://dx.doi.org/10.3390/w11040757.
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The present research develops a systematic application of a selected family of 11 well-known design storms, all of them obtained from the same rainfall data sample. Some of them are fully consistent with the intensity–duration–frequency (IDF) curves, while others are built according to typical observed patterns in the historical rainfall series. The employed data series consists on a high-resolution rainfall time series in Valencia (Spain), covering the period from 1990 to 2012. The goal of the research is the systematic comparison of these design storms, paying special attention to some relevant quantitative properties, as the maximum rainfall intensity, the total cumulative rainfall depth or the temporal pattern characterising the synthetic storm. For comparison purposes, storm duration was set to 1 hour and return period equal to 25 years in all cases. The comparison is enhanced by using each of the design storms as rainfall input to a calibrated urban hydrology rainfall–runoff model, yielding to a family of hydrographs for a given neighbourhood of the city of Valencia (Spain). The discussion and conclusions derived from the present research refer to both, the comparison between design storms and the comparison of resulting hydrographs after the application of the mentioned rainfall–runoff model. Seven of the tested design storms yielded to similar overall performance, showing negligible differences in practice. Among them, only Average Variability Method (AVM) and Two Parameter Gamma function (G2P) incorporate in their definition a temporal pattern inferred from empirical patterns identified in the historical rainfall data used herein. The remaining four design storms lead to more significant discrepancies attending both to the rainfall itself and to the resulting hydrograph. Such differences are ~8% concerning estimated discharges.
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Kaur, Leela, and Ajay Kumar Nehra. "RAINFALL ANALYSIS WITH REFERENCE TO SPATIAL AND TEMPORAL: A CASE STUDY OF JHUNJHUNU DISTRICT (RAJASTHAN)." Environment & Ecosystem Science 8, no. 1 (2024): 01–06. https://doi.org/10.26480/ees.01.2024.01.06.
Full textAbstract:
The current study aims to do rainfall analysis of Jhunjhunu district with reference to time and space for a period of 22 years by using quantum geographic information system (qGIS). The data collected were yearly rainfall and rainy days. These data were analysed in qGIS software. Inverse Distance Weighting (IDW) method of interpolation was adopted for the study. Thematic maps were generated. Rainfall maps displayed a growing tendency in rainfall amount while rainy days represented a slow increasing pattern. It was found that south, south-eastern and some part of north region of the Jhunjhunu get the utmost rainfall. However, north-eastern and western parts of the district receive the lowermost rainfall. It was observed that Khetri block received the highest rainfall during the average 20 years period. Though, Jhunjhunu block got the lowest rainfall during the whole period. Malsisar and Udaipurwati blocks got average rainfall. As ground water recharge rate is low in the study area, it is essential to collectively utilise surface water, available rainfall and groundwater for optimum irrigation and further agricultural management in the district. The rainfall analysis facilitated the understanding of the rainfall pattern which would be advantageous for strategic planning of efficient irrgiation and water availability in the study area.
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Lappas, I., I. Tsioumas, and V. Zorapas. "Spatial-temporal analysis, variation and distribution of precipitation in the water district of Central-Eastern Greece." Bulletin of the Geological Society of Greece 47, no. 2 (2017): 740. http://dx.doi.org/10.12681/bgsg.11110.
Full textAbstract:
In this study, the spatial and temporal distribution of precipitation in the Water District of Central – Eastern Greece is investigated for the 42-year period (1968 – 2009) by using monthly mean data from 35 rainfall gauges, with adequate spatial coverage. The basic objective is to infer the pattern of spatial variation of rainfall over the study area based on meteorological observations. The accurate estimation of rainfall’s spatial distribution is needed whenever hydrological modelling is undertaken at the watershed scale for model calibration and validation. By using timeseries analysis and geostatistical methods, the regional and seasonal precipitation change and regime of this region during over 40 years is analyzed. However, this input is subject to uncertainty due to the random nature of rainfall. For all stations, uniformity checking and appropriate completion (where needed) took place and it appears that orography plays significant role as far the amount of rainfall is concerned. The results indicate that high variations in regional rainfall estimation occur in the mountainous areas, while the variance decreases in shadow areas in all seasons. The analysis of rainfall showed that there exists a wide variation in the rainfall amounts with variation from 382.4mm to 1397mm with a significantly decreasing trend.
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Parab, S. S., S. S. Nagarkar, and B. L. Ayare. "Study of changes in temporal distribution pattern of rainfall at Dapoli station in Konkan region of Maharashtra." INTERNATIONAL JOURNAL OF AGRICULTURAL SCIENCES 20, no. 1 (2024): 249–56. http://dx.doi.org/10.15740/has/ijas/20.1/249-256.
Full textAbstract:
Dapoli situated in the Konkan region of Maharashtra is having average annual rainfall of 3587 mm with average number of rainy days 75. The yield of major Kharif season crop rice is affected by the erratic behavior of rainfall. Present study is an attempt to study the rainfall variations at the Dapoli station which will be useful for forecasting the future temporal availability of water. Comprehensive statistical tools were used to investigate trends in averages and monthly rainfall over the station on decadal basis. Forty years (year 1972-2011) daily rainfall data for Dapoli station was used for the analysis. Results of study showed that, decadal mean rainfall depths of June and August were found decreasing and those for September was found increasing. Mean rainfall depth variations for July as well as annual total rainfall were found random. Seven years moving averages showed that, rainfall depths for the months of June, July and August were found decreasing and for month of September was found increasing. In annual rainfall graph a slight decline was observed.
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Wang, Xiaorong, and Jichao Sun. "The Temporal Evolution Characteristics of Extreme Rainfall in Shenzhen City, China." Sustainability 17, no. 8 (2025): 3512. https://doi.org/10.3390/su17083512.
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Global climate change has led to frequent urban flooding, and extreme rainfall has become the main cause of urban flooding due to its short duration and rapid occurrence. The study of the trend of extreme rainfall can provide an important reference for the prevention, control, and management of urban flooding. At present, there are abundant studies on the evolution characteristics of rainfall in Shenzhen, but there are relatively few studies on the evolution characteristics of extreme rainfall. To analyze the interannual variation in extreme rainfall in Shenzhen and provide a scientific basis for water resource management, this paper systematically analyses the interannual evolutionary characteristics and cyclical patterns of rainfall in Shenzhen based on the daily rainfall data of the city from 1958 to 2022 using the 3-year moving average method, linear regression model, Mann–Kendall mutation test, and wavelet analysis. Hurst index analysis was also used to predict the future trends of extreme rainfall and its frequency. The results indicate that the intensity and frequency of extreme rainfall in Shenzhen exhibit frequent fluctuations, with an overall slow downward trend and no sudden changes causing a decline. Periodic analysis reveals that extreme rainfall intensity and frequency exhibit significant wet–dry alternation characteristics on a time scale of 10–65 years, with the most prominent change occurring on a 63-year scale; in the main cycle, the wet–dry alternation cycle is about 44 years. The trend of the main cycle and wet–dry alternation cycle indicates that in recent years, the rainfall pattern in Shenzhen has developed towards short-term rainfall. The Hurst index analysis shows that the H values of extreme rainfall intensity and frequency are 0.666 and 0.631, respectively, both only slightly greater than 0.5, indicating weak positive persistence of the two indicators. This suggests that extreme rainfall events in Shenzhen may show a downward trend, but this trend does not have strong certainty.
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Pawar, Uttam, Pasindu Karunathilaka, and Upaka Rathnayake. "Spatio-Temporal Rainfall Variability and Concentration over Sri Lanka." Advances in Meteorology 2022 (September 28, 2022): 1–14. http://dx.doi.org/10.1155/2022/6456761.
Full textAbstract:
Changes in precipitation patterns significantly affect flood and drought hazard management and water resources at local to regional scales. Therefore, the main motivation behind this paper is to examine the spatial and temporal rainfall variability over Sri Lanka by Standardized Rainfall Anomaly Index (SRAI) and Precipitation Concentration Index (PCI) from 1990 to 2019. The Mann–Kendall (MK) trend test and Sen’s slope (SS) were utilized to assess the trend in the precipitation concentration based on PCI. The Inverse Distance Weighting (IDW) interpolation method was incorporated to measure spatial distribution. Precipitation variability analysis showed that seasonal variations are more than those of annual variations. In addition, wet, normal, and dry years were identified over Sri Lanka using SRAI. The maximum SRAI (2.27) was observed for the year 2014 for the last 30 years (1990–2019), which shows the extremely wet year of Sri Lanka. The annual and seasonal PCI analysis showed moderate to irregular rainfall distribution except for the Jaffna and Ratnapura areas (annual scale-positive changes in Katugastota for 21.39% and Wellawaya for 17.6%; seasonal scale-Vavuniya for 33.64%, Trincomalee for 31.26%, and Batticaloa for 18.79% in SWMS). The MK test, SS-test, and percent change analyses reveal that rainfall distribution and concentration change do not show a significant positive or negative change in rainfall pattern in Sri Lanka, despite a few areas which experienced significant positive changes. Therefore, this study suggests that the rainfall in Sri Lanka follows the normal trend of precipitation with variations observed both annually and seasonally.
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Byun, Jongyun, Hyeon-Joon Kim, Narae Kang, Jungsoo Yoon, Seokhwan Hwang, and Changhyun Jun. "Optimizing Temporal Weighting Functions to Improve Rainfall Prediction Accuracy in Merged Numerical Weather Prediction Models for the Korean Peninsula." Remote Sensing 16, no. 16 (2024): 2904. http://dx.doi.org/10.3390/rs16162904.
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Accurate predictions are crucial for addressing the challenges posed by climate change. Given South Korea’s location within the East Asian summer monsoon domain, characterized by high spatiotemporal variability, enhancing prediction accuracy for regions experiencing heavy rainfall during the summer monsoon is essential. This study aims to derive temporal weighting functions using hybrid surface rainfall radar-observation data as the target, with input from two forecast datasets: the McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE) and the KLAPS Forecast System. The results indicated that the variability in the optimized parameters closely mirrored the variability in the rainfall events, demonstrating a consistent pattern. Comparison with previous blending results, which employed event-type-based weighting functions, showed significant deviation in the average AUC (0.076) and the least deviation (0.029). The optimized temporal weighting function effectively mitigated the limitations associated with varying forecast lead times in individual datasets, with RMSE values of 0.884 for the 1 h lead time of KLFS and 2.295 for the 4–6 h lead time of MAPLE. This blending methodology, incorporating temporal weighting functions, considers the temporal patterns in various forecast datasets, markedly reducing computational cost while addressing the temporal challenges of existing forecast data.