To see the other types of publications on this topic, follow the link: Daily rainfall.
Journal articles on the topic 'Daily rainfall'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Daily rainfall.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Thompson, S., I. M. Sanni, U. A. Abubakar, and B. S. Sani. "Preliminary Analysis of Daily Rainfall Data from Kano State using Statistical Techniques." October 2022 6, no. 2 (2022): 317–24. http://dx.doi.org/10.36263/ijest.2022.02.0366.
Full textAbstract:
A 35-year annual rainfall was collected from NIMET to determine the Standard Precipitation Index (SPI) and also to study the trend of rainfall parameter in the Kano State, Northern Nigeria. The paper captures the average rainfall (normal rainfall) data for thirty-five years period which implies a rainfall of about 1081.56mm. The positive values (above zero) signify rainfalls that were higher than normal (wet); while the negative values (below zero) imply rainfalls that were lower than normal (dry). From the rainfall anomaly, 18 years (52.9%) recorded wet due to the fact that rainfall occurred in those years were greater than the normal rainfall of 1081.56; while 16 years (47.1%) recorded dry because the rainfalls that occurred in those years were below normal rainfall. In the study, Weilbul method was used to determine the return period in order to predict the year of occurrence of maximum rainfall. In addition, Standard Precipitation Index was used to determine periods of dry, normal or wet temperatures. September 1991 recorded the minimum SPI value of -0.86 (moderately dry), while October 2011 recorded the maximum SPI value of 1.88 (moderately wet). This study is carried out because of the importance of agriculture in the region and to Nigeria at large. Kano state is well known to support food production in the country. Also, the presence of dams further buttresses this study. Dams have many purposes; one is agriculture during dry and wet season. It is observed that the rainfall in the basin has no definite pattern.
2
Thompson, S., I. M. Sanni, U. A. Abubakar, and B. S. Sani. "Preliminary Analysis of Daily Rainfall Data from Kano State using Statistical Techniques." October 2022 6, no. 2 (2022): 317–24. http://dx.doi.org/10.36263/nijest.2022.02.0366.
Full textAbstract:
A 35-year annual rainfall was collected from NIMET to determine the Standard Precipitation Index (SPI) and also to study the trend of rainfall parameter in the Kano State, Northern Nigeria. The paper captures the average rainfall (normal rainfall) data for thirty-five years period which implies a rainfall of about 1081.56mm. The positive values (above zero) signify rainfalls that were higher than normal (wet); while the negative values (below zero) imply rainfalls that were lower than normal (dry). From the rainfall anomaly, 18 years (52.9%) recorded wet due to the fact that rainfall occurred in those years were greater than the normal rainfall of 1081.56; while 16 years (47.1%) recorded dry because the rainfalls that occurred in those years were below normal rainfall. In the study, Weilbul method was used to determine the return period in order to predict the year of occurrence of maximum rainfall. In addition, Standard Precipitation Index was used to determine periods of dry, normal or wet temperatures. September 1991 recorded the minimum SPI value of -0.86 (moderately dry), while October 2011 recorded the maximum SPI value of 1.88 (moderately wet). This study is carried out because of the importance of agriculture in the region and to Nigeria at large. Kano state is well known to support food production in the country. Also, the presence of dams further buttresses this study. Dams have many purposes; one is agriculture during dry and wet season. It is observed that the rainfall in the basin has no definite pattern.
3
Ledingham, Jamie, David Archer, Elizabeth Lewis, Hayley Fowler, and Chris Kilsby. "Contrasting seasonality of storm rainfall and flood runoff in the UK and some implications for rainfall-runoff methods of flood estimation." Hydrology Research 50, no. 5 (2019): 1309–23. http://dx.doi.org/10.2166/nh.2019.040.
Full textAbstract:
Abstract Using data from 520 gauging stations in Britain and gridded rainfall datasets, the seasonality of storm rainfall and flood runoff is compared and mapped. Annual maximum (AMAX) daily rainfall occurs predominantly in summer, but AMAX floods occur most frequently in winter. Seasonal occurrences of annual daily rainfall and flood maxima differ by more than 50% in dry lowland catchments. The differences diminish with increasing catchment wetness, increase with rainfalls shorter than daily duration and are shown to depend primarily on catchment wetness, as illustrated by variations in mean annual rainfall. Over the whole dataset, only 34% of AMAX daily flood events are matched to daily rainfall annual maxima (and only 20% for 6-hour rainfall maxima). The discontinuity between rainfall maxima and flooding is explained by the consideration of coincident soil moisture storage. The results have serious implications for rainfall-runoff methods of flood risk estimation in the UK where estimation is based on a depth–duration–frequency model of rainfall highly biased to summer. It is concluded that inadequate treatment of the seasonality of rainfall and soil moisture seriously reduces the reliability of event-based flood estimation in Britain.
4
Hershenhorn, J., and D. A. Woolhiser. "Disaggregation of daily rainfall." Journal of Hydrology 95, no. 3-4 (1987): 299–322. http://dx.doi.org/10.1016/0022-1694(87)90008-4.
Full text
5
MALEKINEZHAD, HOSSEIN, and ARASH ZARE-GARIZI. "Regional frequency analysis of daily rainfall extremes using L-moments approach." Atmósfera 27, no. 4 (2015): 411–27. http://dx.doi.org/10.20937/atm.2014.27.04.07.
Full textAbstract:
Daily extreme precipitation values are among environmental events with the most disastrous consequences for human society. Information on the magnitudes and frequencies of extreme precipitations is essential for sustainable water resources management, planning for weather-related emergencies, and design of hydraulic structures. In the present study, regional frequency analysis of maximum daily rainfalls was investigated for Golestan province located in the northeastern Iran. This study aimed to find appropriate regional frequency distributions for maximum daily rainfalls and predict the return values of extreme rainfall events (design rainfall depths) for the future. L-moment regionalization procedures coupled with an index rainfall methodwere applied to maximum rainfall records of 47 stations across the study area. Due to complex geographicand hydro-climatological characteristics of the region, an important research issue focused on breaking downthe large area into homogeneous and coherent sub-regions. The study area was divided into five homogeneousregions, based on the cluster analysis of site characteristics and tests for the regional homogeneity.The goodness-of-fit results indicated that the best fitting distribution is different for individual homogeneousregions. The difference may be a result of the distinctive climatic and geographic conditions. The estimatedregional quantiles and their accuracy measures produced by Monte Carlo simulations demonstrate that theestimation uncertainty as measured by the RMSE values and 90% error bounds is relatively low when returnperiods are less than 100 years. But, for higher return periods, rainfall estimates should be treated withcaution. More station years, either from longer records or more stations in the regions, would be required forrainfall estimates above T=100 years. It was found from the analyses that, the index rainfall (at-site averagemaximum rainfall) can be estimated reasonably well as a function of mean annual precipitation in Golestanprovince. Index rainfalls combined with the regional growth curves, can be used to estimate design rainfallsat ungauged sites. Overall, it was found that cluster analysis together with the L-moments based regional frequencyanalysis technique could be applied successfully in deriving design rainfall estimates for northeasternIran. The approach utilized in this study and the findings are of great scientific and practical merit, particularlyfor the purpose of planning for weather-related emergencies and design of hydraulic engineering structures
6
Haddad, Khaled, and Ataur Rahman. "Derivation of short-duration design rainfalls using daily rainfall statistics." Natural Hazards 74, no. 3 (2014): 1391–401. http://dx.doi.org/10.1007/s11069-014-1248-7.
Full text
7
Sirangelo, B., E. Ferrari, and D. L. De Luca. "Occurrence analysis of daily rainfalls through non-homogeneous Poissonian processes." Natural Hazards and Earth System Sciences 11, no. 6 (2011): 1657–68. http://dx.doi.org/10.5194/nhess-11-1657-2011.
Full textAbstract:
Abstract. A stochastic model based on a non-homogeneous Poisson process, characterised by a time-dependent intensity of rainfall occurrence, is employed to explain seasonal effects of daily rainfalls exceeding prefixed threshold values. The data modelling has been performed with a partition of observed daily rainfall data into a calibration period for parameter estimation and a validation period for checking on occurrence process changes. The model has been applied to a set of rain gauges located in different geographical areas of Southern Italy. The results show a good fit for time-varying intensity of rainfall occurrence process by 2-harmonic Fourier law and no statistically significant evidence of changes in the validation period for different threshold values.
8
I Gusti Ngurah Putu Dharmayasa, Cathleen Ariella Simatupang, and Doni Marisi Sinaga. "NASA Power’s: an alternative rainfall data resources for hydrology research and planning activities in Bali Island, Indonesia." Journal of Infrastructure Planning and Engineering (JIPE) 1, no. 1 (2022): 1–7. http://dx.doi.org/10.22225/jipe.1.1.2022.1-7.
Full textAbstract:
Rainfall data is critical for planning and research in the field of hydrology. Rainfall data must be available continuously, which means it must be recorded continuously. This recording will continue since numerous projects in the field of hydrology require continuous rainfall data. Although rainfall data are collected and recorded daily, some stations frequently have insufficient rainfall records, particularly in developing countries such as Bali, Indonesia. These issues may impair the quality of rainfall data, resulting in inaccuracies in the analysis results. To address this issue, we need a reliable source of rainfall data, one of which is NASA Power, which provides rainfall data for free. NASA Power rainfall data is then compared to observed rainfall data. The comparison of the two rainfalls is measured by a statistical parameter, namely the correlation coefficient. Based on the comparison between lowland and highland areas, the average daily rainfall from NASA Power tends to be lower than the average daily rainfall from observation stations. Meanwhile, from the correlation coefficient value (r) of the comparison of rainfall observations and NASA Power, a considerably high correlation coefficient value (> 0.7) was observed. Thus, it can be suggested that the rainfall data from NASA Power for hydrology research and planning activities in Bali Island, Indonesia.
9
Connolly, R. D., J. Schirmer, and P. K. Dunn. "A daily rainfall disaggregation model." Agricultural and Forest Meteorology 92, no. 2 (1998): 105–17. http://dx.doi.org/10.1016/s0168-1923(98)00088-4.
Full text
10
Sumner, G., C. Ramis, and J. A. Guijarro. "Daily rainfall domains in Mallorca." Theoretical and Applied Climatology 51, no. 4 (1995): 199–221. http://dx.doi.org/10.1007/bf00867280.
Full text
11
Yoo, Chulsang, Jae-Soo Lee, and Yong-Nam Yoon. "Climatological Thresholds of Daily Rainfall." Journal of Hydrologic Engineering 6, no. 5 (2001): 443–49. http://dx.doi.org/10.1061/(asce)1084-0699(2001)6:5(443).
Full text
12
Palumbo, A. "Lunar daily variations in rainfall." Journal of Atmospheric and Terrestrial Physics 48, no. 2 (1986): 145–48. http://dx.doi.org/10.1016/0021-9169(86)90078-4.
Full text
13
Jakubowski, W. "A daily rainfall occurrence process." Stochastic Hydrology and Hydraulics 2, no. 1 (1988): 1–16. http://dx.doi.org/10.1007/bf01544190.
Full text
14
JOLLIFFE, IAN T., and PETER B. HOPE. "REPRESENTATION OF DAILY RAINFALL DISTRIBUTIONS USING NORMALIZED RAINFALL CURVES." International Journal of Climatology 16, no. 10 (1996): 1157–63. http://dx.doi.org/10.1002/(sici)1097-0088(199610)16:10<1157::aid-joc71>3.0.co;2-r.
Full text
15
DOMRQES, MANFRED, and EDMOUND RANATUNGE. "Daily rainfall persistence over Sri Lanka." MAUSAM 44, no. 3 (2022): 281–86. http://dx.doi.org/10.54302/mausam.v44i3.3869.
Full textAbstract:
The spatial distribution of daily rainfall persistence is examined adopting Besson's persistence coefficient and using daily rainfall data for 15 consecutive years (1971-1985). The daily rainfall persistence coefficients have been studied separately for all the twelve months individually and for the whole year. Where January and February indicate the lowest rainfall persistence coefficients the period from October to December indicates the highest coefficients over Sri Lanka. Besides the monsoonal atmospheric conditions, the topography has a strong influence on the rainfall persistence distribution over space and time. The daily rainfall persistence coefficients record higher values in the wet zone then in the dry zone of Sri Lanka. Regression analysis shows a better linear relationship between mean length of wet spell~ and the daily rainfall persistence coefficients and the resultant final equation is y.4' =0.1093+0.1600+X M having the correlation coefficient of 0.721 which is significant at the 0.01% level.
16
Laz, Orpita U., Ataur Rahman, Abdullah Yilmaz, and Khaled Haddad. "Trends in sub-hourly, sub-daily and daily extreme rainfall events in eastern Australia." Journal of Water and Climate Change 5, no. 4 (2014): 667–75. http://dx.doi.org/10.2166/wcc.2014.035.
Full textAbstract:
Intensity and frequency of extreme rainfall are expected to change in future due to anthropogenic climate change; however, this change may not be uniform across spatial and temporal scale. This paper examines the trends of sub-hourly, sub-daily and daily extreme rainfall events from 38 rainfall stations located in southeast Australia. Two non-parametric tests (Mann–Kendall and Spearman Rho) were applied to detect trends at 10, 5 and 1% significance levels. The sub-hourly (6, 12, 18 and 30 min) and sub-daily (1, 2 and 6 h) annual maximum rainfall events generally showed an upward (positive) trend. However, the longer duration rainfall events (12–72 h) generally showed a downward (negative) trend. It was found that stations showing positive trends were characterized by higher elevations compared with the stations showing negative trends. This finding has important implications for urban stormwater management in the near future as most urban stormwater systems operate on a smaller catchment scale where sub-hourly and sub-daily rainfall events are used in their design.
17
Yue, Sheng, and Michio Hashino. "Cumulant estimation of daily runoff from daily rainfall sequences." Doboku Gakkai Ronbunshu, no. 533 (1996): 41–50. http://dx.doi.org/10.2208/jscej.1996.533_41.
Full text
18
Suaydhi, Suaydhi. "Characteristics of daily rainfall over the Maritime Continent." Journal of Science and Science Education 2, no. 1 (2018): 29–39. http://dx.doi.org/10.24246/josse.v2i1p29-39.
Full textAbstract:
Daily rainfall characteristics is important in the anticipation of natural hazard events, such as floods and landslides. In this study, daily rainfall data from the Global Precipitation Climatology Project One Degree Daily (GPCP1DD) dataset are used to analyze the rainfall frequency, intensity and extreme rainfall indicators over the Indonesian Maritime Continent. A threshold of 1 mm is used to define a wet day. The analysis is conducted over the whole domain and several sub domains. It is revealed that the rainfall patterns over Indonesia are shaped by the frequency distribution of rainfall intensity over different seasons. Heavy rainfall (greater than 15 mm/day) generally determines the rainfall peak season over a specific region. It is also shown that the land areas receive more frequent and more intense rainfall than the ocean areas.
19
Ram, Bhavin, Murari Lal Gaur, and Devraj Thakor. "Investigation on Variability, Broader Types and Patterns of Daily and Sub-daily Rains Using Satellite Sub-Daily Rainfall Records based in Western Indian Province." International Journal of Bio-resource and Stress Management 14, Feb, 2 (2023): 229–36. http://dx.doi.org/10.23910/1.2023.3282a.
Full textAbstract:
The present study was conducted during 2021 at middle Gujarat. The objectives of the study remained inclined towards the challenging task, where limited observed rainfall records (daily and sub-daily both) were utilized to project corresponding regional design hyetographs for providing the design hyetographs at similar ungauged sites in the region. This script explores suitability, appropriateness and end efficacies of blended (ground based as well as remotely sensed) precipitation data attained for a data deprived region, which was ultimately utilized to derive location specific rainfall curves adopting satellite based observed rainfall records. A set of representative type curves on rainfall (daily & sub-daily) for study region were conceived, which could be potentially utilized for better rainfall-runoff modelling even under purely ungauged scenarios. Voluminous precipitation data retrieved via GPM (IMREG) satellite precipitation products was endeavoured and used to create values envelope of design curves for use in ungauged situations. 21 years of daily & sub-daily rainfall records (2000–2020) were thoroughly examined and used to retrieve valid understanding towards annual, monthly, daily and even hourly based variability of rainfall across six different stations as adopted in the study. The net magnitude of dispersals in all the derived sets of mass curves/Hyetographs were worked out and suitably compared across 6 specific locations as well as their categorization in terms of storm depths, storm durations and peak rain intensities which could be of high practical importance for water resource planners other relevant research and development.
20
Oh, Tae-Suk, and Young-Il Moon. "Characteristic Change Analysis of Rainfall Events using Daily Rainfall Data." Journal of Korea Water Resources Association 42, no. 11 (2009): 933–51. http://dx.doi.org/10.3741/jkwra.2009.42.11.933.
Full text
21
Yu, B., and CJ Rosewell. "Rainfall erosivity estimation using daily rainfall amounts for South Australia." Soil Research 34, no. 5 (1996): 721. http://dx.doi.org/10.1071/sr9960721.
Full textAbstract:
The rainfall erosivity model relating storm erosivity to daily rainfall amounts was tested for 4 sites in South Australia where seasonal rainfall erosivity is generally out of phase with seasonal rainfall because of the predominant winter rainfall. The model worked reasonably well, with the coefficient of efficiency varying from 0.54 to 0.77, and the average discrepancy between actual and estimated monthly distribution was no more than 3%. The model performance in the winter rainfall area is similar to that in the uniform and summer rainfall areas. A set of regional parameter values estimated using a combined dataset is recommended for other sites in the agricultural and viticultural areas of South Australia where the mean annual rainfall ranges from 300 to 500 mm. The R-factor and its seasonal distribution were estimated for 99 sites in South Australia using long-term daily rainfall data. The R-factor varies mostly between 250 and 500 MJ . mm/(ha . h . year). Rainfall erosivity peaks in winter in the southern part of the western agricultural area and the south-east corner of the State, while it peaks in summer in the inland area east of the South Flinders and Mount Lofty Ranges.
22
Mpelasoka, Freddie S., and Francis H. S. Chiew. "Influence of Rainfall Scenario Construction Methods on Runoff Projections." Journal of Hydrometeorology 10, no. 5 (2009): 1168–83. http://dx.doi.org/10.1175/2009jhm1045.1.
Full textAbstract:
Abstract The future rainfall series used to drive hydrological models in most climate change impact studies is informed by global climate models (GCMs). This paper compares future runoff projections in ∼11 000 0.25° grid cells across Australia from a daily rainfall–runoff model driven with future daily rainfall series obtained using three simple scaling methods, informed by 14 GCMs. In the constant scaling and daily scaling methods, the historical daily rainfall series is scaled by the relative difference between GCM simulations for the future and historical climates. The constant scaling method scales all the daily rainfall by the same factor, and the daily scaling method takes into account changes in the daily rainfall distribution by scaling the different daily rainfall amounts differently. In the daily translation method, the GCM future daily rainfall series is translated to a 0.25° gridcell rainfall series using the relationship established between the historical GCM-scale rainfall and 0.25° gridcell rainfall data. The daily scaling and daily translation methods generally give higher extreme and annual runoff than the constant scaling method because they take into account the increase in extreme daily rainfall (which generates significant runoff) simulated by the large majority of the GCMs. However, the difference between the mean annual runoff simulated with future daily rainfall series obtained using the constant versus daily scaling methods is generally less than 5%, which is relatively smaller than the range of runoff results from the different GCMs of 30%–40%.
23
Van Nguyen, Van-Thanh, and Ganesh Raj Pandey. "Estimation of Short-Duration Rainfall Distribution Using Data Measured at Longer Time Scales." Water Science and Technology 29, no. 1-2 (1994): 39–45. http://dx.doi.org/10.2166/wst.1994.0649.
Full textAbstract:
An investigation on how to estimate the distribution of short-duration (hours or shorter) rainfalls based on available daily rainfall measurements was undertaken. On the basis of the theory of multifractal multiplicative cascades, a scale-independent mathematical model was proposed to represent the probability distribution of rainfalls at various time scales. Using rainfall records from a network of seven recording gauges in the Montreal region in Quebec (Canada), it was found that the proposed model could provide adequate estimates of the distribution of hourly rainfalls at locations where these short-duration rainfall data are not available. Further, it has been observed that one single regional model can be developed to describe the scaling nature of rainfall distributions within the whole study area.
24
Lewis, Elizabeth, Hayley Fowler, Lisa Alexander, et al. "GSDR: A Global Sub-Daily Rainfall Dataset." Journal of Climate 32, no. 15 (2019): 4715–29. http://dx.doi.org/10.1175/jcli-d-18-0143.1.
Full textAbstract:
Abstract Extreme short-duration rainfall can cause devastating flooding that puts lives, infrastructure, and natural ecosystems at risk. It is therefore essential to understand how this type of extreme rainfall will change in a warmer world. A significant barrier to answering this question is the lack of sub-daily rainfall data available at the global scale. To this end, a global sub-daily rainfall dataset based on gauged observations has been collated. The dataset is highly variable in its spatial coverage, record length, completeness and, in its raw form, quality. This presents significant difficulties for many types of analyses. The dataset currently comprises 23 687 gauges with an average record length of 13 years. Apart from a few exceptions, the earliest records begin in the 1950s. The Global Sub-Daily Rainfall Dataset (GSDR) has wide applications, including improving our understanding of the nature and drivers of sub-daily rainfall extremes, improving and validating of high-resolution climate models, and developing a high-resolution gridded sub-daily rainfall dataset of indices.
25
Muna, Siti Umamah Naili. "Crop Insurance Model Based on Maximum Daily Rainfall and Maximum Daily Temperature Index." ASTONJADRO 12, no. 2 (2023): 599–612. http://dx.doi.org/10.32832/astonjadro.v12i2.13207.
Full textAbstract:
A loss insurance model of risk for agricultural commodities that considers maximum daily rainfall and maximum daily temperature is introduced in this paper. This model requires bivariate distribution of maximum daily rainfall and maximum daily temperature in a specific region. Characteristics of particular agricultural commodity is also needed in the region where the two variables are being insured. The bivariate distribution and commodity characteristics are combined to obtain exit. exit is a benchmark value that causes the total crop failure and gives full benefit claim to policyholder. The case study was demonstrated by using data on maximum daily rainfall and temperature in Dramaga Bogor from September to December during 38 years (1984-2021) . Data was collected from Jawa Barat Climatology Station. Frank Copula is better to represent the bivariate distribution of data. Furthermore, two scenarios had given the premiums as IDR 2 482 925 per hectare and IDR 1 495 660 per hectare. This crop insurance model based on maximum daily rainfall and maximum daily temperature index could be the basis for the next developing of crop insurance model.
26
Bhonde, Kanchan A., Snehal Yeole, Kartik Jawanjal, Mayank Modi, Aditya Panchwagh, and Aditya Paprunia. "Assessment of Accuracy of Indian Almanac for Daily Rainfall Prediction." Indian Journal Of Science And Technology 15, no. 32 (2022): 1548–60. http://dx.doi.org/10.17485/ijst/v15i32.1743.
Full text
27
KRISHNAN, R., N. GOPALASWAMY, C. R. RANGANATHAN, S. NATARAJAN, and T. N. BALASUBRAMANIAN. "ANALYSIS OF DAILY RAINFALL OF COIMBATORE." MAUSAM 46, no. 1 (2022): 89–92. http://dx.doi.org/10.54302/mausam.v46i1.3208.
Full text
28
Permai, S. D., M. Ohyver, and M. K. B. M. Aziz. "Daily rainfall modeling using Neural Network." Journal of Physics: Conference Series 1988, no. 1 (2021): 012040. http://dx.doi.org/10.1088/1742-6596/1988/1/012040.
Full text
29
Smith, James A. "Statistical modeling of daily rainfall occurrences." Water Resources Research 23, no. 5 (1987): 885–93. http://dx.doi.org/10.1029/wr023i005p00885.
Full text
30
Nadarajah, Saralees, and Dongseok Choi. "Maximum daily rainfall in South Korea." Journal of Earth System Science 116, no. 4 (2007): 311–20. http://dx.doi.org/10.1007/s12040-007-0028-0.
Full text
31
Teng, Tse-Yu, Tzu-Ming Liu, Yu-Shiang Tung, and Ke-Sheng Cheng. "Converting Climate Change Gridded Daily Rainfall to Station Daily Rainfall—A Case Study at Zengwen Reservoir." Water 13, no. 11 (2021): 1516. http://dx.doi.org/10.3390/w13111516.
Full textAbstract:
With improvements in data quality and technology, the statistical downscaling data of General Circulation Models (GCMs) for climate change impact assessment have been refined from monthly data to daily data, which has greatly promoted the data application level. However, there are differences between GCM downscaling daily data and rainfall station data. If GCM data are directly used for hydrology and water resources assessment, the differences in total amount and rainfall intensity will be revealed and may affect the estimates of the total amount of water resources and water supply capacity. This research proposes a two-stage bias correction method for GCM data and establishes a mechanism for converting grid data to station data. Five GCMs were selected from 33 GCMs, which were ranked by rainfall simulation performance from a baseline period in Taiwan. The watershed of the Zengwen Reservoir in southern Taiwan was selected as the study area for comparison of the three different bias correction methods. The results reveal that the method with the wet-day threshold optimized by objective function with observation rainfall wet days had the best result. Error was greatly reduced in the hydrology model simulation with two-stage bias correction. The results show that the two-stage bias correction method proposed in this study can be used as an advanced method of data pre-processing in climate change impact assessment, which could improve the quality and broaden the extent of GCM daily data. Additionally, GCM ranking can be used by researchers in climate change assessment to understand the suitability of each GCM in Taiwan.
32
Zakaria, Ahmad. "Correlation of BMKG with TRMM for daily and monthly rainfall series in Banten region." Journal of Engineering and Scientific Research 4, no. 1 (2022): 1–7. http://dx.doi.org/10.23960/jesr.v4i1.78.
Full textAbstract:
Daily and monthly rainfall data series are necessary data for planning purposes in Civil Engineering and other fields. Incomplete rainfall data often occurs, so that rainfall data must be estimated based on rainfall data from several other nearby locations. The addition of rainfall data can lead to inaccurate planning.
 Rainfall data used for planning in the civil engineering sector is usually taken from the BMKG station. This data is taken from the rainfall station above the ground. Besides, that can also produce rainfall data from TRMM. Can take rainfall data from TRMM at all locations according to a coordinate of location. This rainfall data denotes an average rainfall taken from the satellite approximately 250 meters above the ground surface.
 An equation will be obtained by comparing the daily and monthly rainfall data from the two data sources. Based on TRMM rainfall, we can use the equation to estimate ground rainfall in a location.
 In this study, daily rainfall, monthly rainfall, the spectrum of daily and monthly rainfall data from BMKG are compared with rainfall and the spectrum of daily and monthly rainfall data from TRMM. The analysis results show that the monthly rainfall data from TRMM and BMKG correlate better than daily rainfall data.
33
Tait, Andrew, and Richard Turner. "Generating Multiyear Gridded Daily Rainfall over New Zealand." Journal of Applied Meteorology 44, no. 9 (2005): 1315–23. http://dx.doi.org/10.1175/jam2279.1.
Full textAbstract:
Abstract Daily rainfall totals are a key input for hydrological models that are designed to simulate water and pollutant flow through both soil and waterways. Within New Zealand there are large areas and many river catchments where no long-term rainfall observations exist. A method for estimating daily rainfall over the whole of New Zealand on a 5-km grid is described and tested over a period from January 1985 to April 2002. Improvement over a spatial interpolation method was gained by scaling high-elevation rainfall estimates using simulated mesoscale model rainfall surfaces that are generated for short periods in 1994 and 1996. This method is judged to produce reasonable and useful estimates of daily rainfall.
34
Silva Neto, Virgilio Lourenço da, Marcelo Ribeiro Viola, Demetrius David da Silva, Carlos Rogério de Mello, Silvio Bueno Pereira, and Marcos Giongo. "Daily rainfall disaggregation for Tocantins State, Brazil." Ambiente e Agua - An Interdisciplinary Journal of Applied Science 12, no. 4 (2017): 605. http://dx.doi.org/10.4136/ambi-agua.2077.
Full textAbstract:
In order to design effective Brazilian hydraulic structures, it is necessary to obtain data relating to short-duration intense rainfall from historical series of daily rainfall. This recurring need can be fulfilled by rainfall disaggregation methodology. The objective of this study was to determine the intense rainfall disaggregation constants for the State of Tocantins and to compare these constants with those obtained for other regions of Brazil. For the modeling of the frequency of intense rainfall of different durations of less than 24 hours, the Gumbel probability distribution (GPD) was employed using rainfall series from 10 locations in Tocantins state. The results showed that the GPD was adequate by the Kolmogorov-Smirnov and Chi-square tests. The disaggregation constants presented low variability values for different return periods (from 10 to 100 years); the values for Tocantins state are: h12h/h24h=0.93, h6h/h24h=0.86, h4h/h24h=0.82, h3h/h24h=0.78, h2h/h24h=0.72, h1h/h24h=0.61, h50min/h1h=0.92, h40min/h1h=0.83, h30min/h1h=0.68, h20min/h30min=0.76 e h10min/h30min=0.46. The comparison of the results with those from studies developed for other Brazilian regions showed variations of up to -62.30%, allowing us to conclude that the use of local constants is important in the process of rainfall disaggregation.
35
Vemula, Swathi, K. Srinivasa Raju, and S. Sai Veena. "Modelling impact of future climate and land use land cover on flood vulnerability for policy support – Hyderabad, India." Water Policy 22, no. 5 (2020): 733–47. http://dx.doi.org/10.2166/wp.2020.106.
Full textAbstract:
Abstract The study analyses the impact of climate change and land use land cover (LULC) on runoff of Hyderabad city, India for the years 1995, 2005, 2016 and 2031. Flood vulnerability was evaluated for extreme historic and future rainfall events. Maximum daily rainfalls of 132, 181 and 165 mm that occurred in the decades of 1990–2000, 2001–2010 and 2011–2016 were considered for historic rainfall–runoff modelling. Complementarily in climate change, maximum daily rainfall of 266 mm predicted during 2020–2040 by Geophysical Fluid Dynamics Laboratory-Coupled Model 3 (GFDL-CM3) Representative Concentration Pathway (RCP) 2.6, was analysed for rainfall-runoff scenario in 2031. LULC was assessed from historic maps and the master plan of the city. Peak runoff was modelled in Storm Water Management Model (SWMM) for corresponding daily rainfall and LULC. The floodplain of the river Musi was modelled in Hydrological Engineering Center-River Analysis System (HEC-RAS). Results showed that changing rainfall and LULC increased peak runoff by three times, and flood depth in the river increased by 22% from 1995 to 2031. In 2016 and 2031, 48 and 51% of the city was highly vulnerable. Five detention basins were proposed to combat increasing runoff, due to which highly vulnerable areas reduced by 8% in 2016 and 9% in 2031.
36
Moate, Peter J., Jennie E. Pryce, Leah C. Marett, et al. "Measurement of Enteric Methane Emissions by the SF6 Technique Is Not Affected by Ambient Weather Conditions." Animals 11, no. 2 (2021): 528. http://dx.doi.org/10.3390/ani11020528.
Full textAbstract:
Despite the fact that the sulphur hexafluoride (SF6) tracer technique was developed over 25 years ago to measure methane production from grazing and non-housed animals, no studies have specifically investigated whether ambient wind speed, temperature, relative humidity and rainfall influence the accuracy of the method. The aim of this research was to investigate how these weather factors influence the measurement of enteric methane production by the SF6 technique. Six different cohorts of dairy cows (40 per cohort) were kept outdoors and fed a common diet during spring in 3 consecutive years. Methane production from individual cows was measured daily over the last 5 days of each 32-day period. An automated weather station measured air temperature, wind speed, relative humidity and rainfall every 10 min. Regression analyses were used to relate the average daily wind speed, average daily temperature, average daily relative humidity and total daily rainfall measurements to dry matter intake, average daily methane production and methane yield of each cohort of cows. It was concluded that the modified SF6 technique can be used outdoors during a range of wind speeds, ambient temperatures, relative humidities and rainfall conditions without causing a significant effect on the measurement of methane production or methane yield of dairy cows.
37
AGASHE, P. S., and K. V. PADGALWAR. "On some characteristic features of daily rainfall over Madhya Maharashtra." MAUSAM 56, no. 3 (2022): 571–80. http://dx.doi.org/10.54302/mausam.v56i3.986.
Full textAbstract:
Information in processed form, is often needed to meet the demands in agriculture, hydrology and other water-related human activities. In this context, daily rainfall continue to be of prime importance since it is the daily rainfall which, when accumulated gives weekly, monthly or seasonal totals. This paper deals with some of the characteristic features of daily rainfall at nine selected stations in Madhya Maharashtra. The study is based on daily rainfall data of June to September months for 10 years (1991-2000).
 Depending upon rainfall amounts (or lack of it), a day has been categorized as rainy day, drizzle day or dry day. Making use of the concept of evapotranspiration, rainy day has been further divided into crop rainy day. Distribution of these various classes of days, their contribution to monthly totals and relationship among them, have been obtained and discussed. The rainy days have been used to obtain mean daily rainfall intensity and its association with monthly rainfall, examined through a series of regression equations. Frequency of heavy falls i.e., rainfall exceeding 25 mm in a day have been determined and its contribution to monthly rainfall, evaluated.
 There seems to be a tendency for the rainy days and the rainfall to be below normal in recent years. Perfectly dry weather could prevail nearly half of June and July months over the region. Heavy rainfall contributes substantially to the monthly total. During June and September mean daily rainfall intensity is perhaps weakly related with the monthly rainfall.
38
Diez-Sierra, Javier, and Manuel del Jesus. "Subdaily Rainfall Estimation through Daily Rainfall Downscaling Using Random Forests in Spain." Water 11, no. 1 (2019): 125. http://dx.doi.org/10.3390/w11010125.
Full textAbstract:
Subdaily rainfall data, though essential for applications in many fields, is not as readily available as daily rainfall data. In this work, regression approaches that use atmospheric data and daily rainfall statistics as predictors are evaluated to downscale daily-to-subdaily rainfall statistics on more than 700 hourly rain gauges in Spain. We propose a new approach based on machine learning techniques that improves the downscaling skill of previous methodologies. Results are grouped by climate types (following the Köppen–Geiger classification) to investigate possible missing explanatory variables in the analysis. The methodology is then used to improve the ability of Poisson cluster models to simulate hourly rainfall series that mimic the statistical behavior of the observed ones. This approach can be applied for the study of extreme events and for daily-to-subdaily precipitation disaggregation in any location of Spain where daily rainfall data are available.
39
Lee, Jeonghoon, and Sangdan Kim. "Temporal Disaggregation of Daily Rainfall data using Stochastic Point Rainfall Model." Journal of the Korean Society of Hazard Mitigation 18, no. 2 (2018): 493–503. http://dx.doi.org/10.9798/kosham.2018.18.2.493.
Full text
40
Diodato, Nazzareno, and Gianni Bellocchi. "Using Historical Precipitation Patterns to Forecast Daily Extremes of Rainfall for the Coming Decades in Naples (Italy)." Geosciences 8, no. 8 (2018): 293. http://dx.doi.org/10.3390/geosciences8080293.
Full textAbstract:
The coasts of the Italian peninsula have been recently affected by frequent damaging hydrological events driven by intense rainfall and deluges. The internal climatic mechanisms driving rainfall variability that generate these hydrological events in the Mediterranean are not fully understood. We investigated the simulation skill of a soft-computing approach to forecast extreme rainfalls in Naples (Italy). An annual series of daily maximum rainfall spanning the period between 1866 and 2016 was used for the design of ensemble projections in order to understand and quantify the uncertainty associated with interannual to interdecadal predictability. A predictable structure was first provided, and then elaborated by exponential smoothing for the purposes of training, validation, and forecast. For the time horizon between 2017 and 2066, the projections indicate a weak increase of daily maximum rainfalls, followed by almost the same pace as it was in the previous three decades, presenting remarkable wavelike variations with durations of more than one year. The forecasted pattern is coupled with variations attributed to internal climate modes, such as the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO).
41
Perdana, Damar Adi, Ahmad Zakaria, and Sumiharni Sumiharni. "Studi Pemodelan Curah hujan sintetik dari beberapa stasiun di wilayah Pringsewu." Jurnal Rekayasa Sipil dan Desain 3, no. 1 (2015): 45–56. https://doi.org/10.23960/jrsdd.v3i1.386.
Full textAbstract:
This research conducted to study the characteristics of daily rainfall and model making ofsynthetic daily rainfall in Pringsewu regency using periodic model, stochastic model and periodicstochastic models. This research conducted using daily rainfall data with length of 1984-2013from three rainfall stations, Pringsewu, Wonokriyo and Banyuwangi rainfall stations.These models performed by using 512 days annual data. Using rainfall frequency obtained andapplying the spectral method and the least squares method, it can be generated the daily rainfallperiodic models. Rainfall stochastic model assumed as the difference between rainfall data withperiodic rainfall models. Based on data from the series of stochastic, the component wascalculated using the approach of autoregressive models. Stochastic model was presented by usingthe autoregressive model of order three. Periodic stochastic model obtained by merging periodicmodel and stochastic model. Model validation and data obtained by calculating the correlationcoefficient. Based on the results of this research, it can be concluded that daily rainfall time seriescan be very significantly approximately recorded rainfall data. With the the average value ofcoefficient correlation of periodic model is 0.98019, coefficient correlation of stochastic model is0.99808, and coefficient correlation stochastic of periodic model is 0.99993keywords: daily rainfall, autoregresif models, stochastic component.
42
Caçadini Bizerra da Silva, Leonardo, Juliana Vilardo Mendes, Patrick do Nascimento da Silva, and Nubia Beray Armond. "Spatial analysis of daily rainfall concentration in Paraíba State, Brazil." RAEGA - O Espaço Geográfico em Análise 61 (December 18, 2024): 3–28. https://doi.org/10.5380/raega.v61i1.97551.
Full textAbstract:
Recent studies indicate a reduction of total rainfall and an increase of extreme rainfall events in the Brazilian Northeast region. It is crucial to understand the concentration of daily rainfall for environmental planning and land management. This study performs the analysis of the daily rainfall concentration for the Paraíba State in the period between 1970 and 2019, using data from 26 rainfall stations across the State. Additionally, to the total annual precipitation (PP), the following concentration indicators were applied: frequency of days with precipitation up to 20mm (R20MM), maximum daily rainfall (Rx1Day), maximum rainfall over 5 days (Rx5Day), frequency of days with precipitation in the 10th (P10), 90th (P90), 95th (P95), and 99th (P99) percentiles, number of rainy days (NRD), and the Concentration Index (CI), which estimates the contribution of daily rainfall to the annual total. The Mann-Kendall test and Sen's slope were applied to identify possible trends in the time series and its magnitude. Spatially, the highest concentration values were observed in the Litoral and Brejo regions, decreasing towards the State hinterland. Temporally, most indicators displayed negative trends, suggesting reductions in both annual rainfall totals and rainfall on isolated days or groups of days. However, the CI showed predominantly an upward trend, indicating increased rainfall concentration. P10 values also exhibited an increase tendency, suggesting that days with the lowest rainfall amounts are becoming more frequent.
43
Giarno, G., Muhammad Pramono Hadi, Slamet Suprayogi, and Sigit Heru Murti. "Distribution of Accuracy of TRMM Daily Rainfall in Makassar Strait." Forum Geografi 32, no. 1 (2018): 38–52. http://dx.doi.org/10.23917/forgeo.v32i1.5774.
Full textAbstract:
This research aims to evaluate rainfall estimates of satellite products in regions that have high variations of rainfall pattern. The surrounding area of Makassar Strait have chosen because of its distinctive rainfall pattern between the eastern and western parts of the Makassar Strait. For this purpose, spatial distribution of Pearson’s coefficient correlation and Root Mean Square Error (RMSE) is used to evaluate accuracy of rainfall in the eastern part of Kalimantan Island and the western part of Sulawesi Island. Moreover, we also used the contingency table to complete the parameter accuracy of the TRMM rainfall estimates. The results show that the performance of TRMM rainfall estimates varies depending on space and time. Overall, the coefficient correlation between TRMM and rain observed from no correlation was -0.06 and 0.78 from strong correlation. The best correlation is on the eastern coast of South West Sulawesi located in line with the Java Sea. While, no variation in the correlation was related to flatland such as Kalimantan Island. On the other hand, in the mountain region, the correlation of TRMM rainfall estimates and observed rainfall tend to decrease. The RMSE distribution in this region depends on the accumulation of daily rainfall. RMSE tends to be high where there are higher fluctuations of fluctuating rainfall in a location. From contingency indicators, we found that the TRMM rainfall estimates were overestimate. Generally, the absence of rainfall during the dry season contributes to improving TRMM rainfall estimates by raising accuracy (ACC) in the contingency table.
44
Cheng, Chad Shouquan, Guilong Li, Qian Li, and Heather Auld. "A Synoptic Weather Typing Approach to Simulate Daily Rainfall and Extremes in Ontario, Canada: Potential for Climate Change Projections." Journal of Applied Meteorology and Climatology 49, no. 5 (2010): 845–66. http://dx.doi.org/10.1175/2010jamc2016.1.
Full textAbstract:
Abstract An automated synoptic weather typing and stepwise cumulative logit/nonlinear regression analyses were employed to simulate the occurrence and quantity of daily rainfall events. The synoptic weather typing was developed using principal component analysis, an average linkage clustering procedure, and discriminant function analysis to identify the weather types most likely to be associated with daily rainfall events for the four selected river basins in Ontario. Within-weather-type daily rainfall simulation models comprise a two-step process: (i) cumulative logit regression to predict the occurrence of daily rainfall events, and (ii) using probability of the logit regression, a nonlinear regression procedure to simulate daily rainfall quantities. The rainfall simulation models were validated using an independent dataset, and the results showed that the models were successful at replicating the occurrence and quantity of daily rainfall events. For example, the relative operating characteristics score is greater than 0.97 for rainfall events with daily rainfall ≥10 or ≥25 mm, for both model development and validation. For evaluation of daily rainfall quantity simulation models, four correctness classifications of excellent, good, fair, and poor were defined, based on the difference between daily rainfall observations and model simulations. Across four selected river basins, the percentage of excellent and good simulations for model development ranged from 62% to 84% (of 20 individuals, 16 cases ≥ 70%, 7 cases ≥ 80%); the corresponding percentage for model validation ranged from 50% to 76% (of 20 individuals, 15 cases ≥ 60%, 6 cases ≥ 70%).
45
Vaze, J., D. A. Post, F. H. S. Chiew, J. M. Perraud, J. Teng, and N. R. Viney. "Conceptual Rainfall–Runoff Model Performance with Different Spatial Rainfall Inputs." Journal of Hydrometeorology 12, no. 5 (2011): 1100–1112. http://dx.doi.org/10.1175/2011jhm1340.1.
Full textAbstract:
Abstract Different methods have been used to obtain the daily rainfall time series required to drive conceptual rainfall–runoff models, depending on data availability, time constraints, and modeling objectives. This paper investigates the implications of different rainfall inputs on the calibration and simulation of 4 rainfall–runoff models using data from 240 catchments across southeast Australia. The first modeling experiment compares results from using a single lumped daily rainfall series for each catchment obtained from three methods: single rainfall station, Thiessen average, and average of interpolated rainfall surface. The results indicate considerable improvements in the modeled daily runoff and mean annual runoff in the model calibration and model simulation over an independent test period with better spatial representation of rainfall. The second experiment compares modeling using a single lumped daily rainfall series and modeling in all grid cells within a catchment using different rainfall inputs for each grid cell. The results show only marginal improvement in the “distributed” application compared to the single rainfall series, and only in two of the four models for the larger catchments. Where a single lumped catchment-average daily rainfall series is used, care should be taken to obtain a rainfall series that best represents the spatial rainfall distribution across the catchment. However, there is little advantage in driving a conceptual rainfall–runoff model with different rainfall inputs from different parts of the catchment compared to using a single lumped rainfall series, where only estimates of runoff at the catchment outlet is required.
46
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.
Full textAbstract:
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.
47
د. فهدة فلاح بن حشر, د. فهدة فلاح بن حشر. "Estimation and analysis of the effective rainfall In Tabuk area – Saudi Arabia." journal of King Abdulaziz University Arts And Humanities 28, no. 14 (2020): 142–86. http://dx.doi.org/10.4197/art.28-14.4.
Full textAbstract:
this study examined the effective rainfall in Tabuk area by applying the Lang rainfall factor, De Martonne Index and the (UNEP) arid index. The study methodology was based on a statistical tests using the Normality test (Shapiro-Wilk), the Homogeneity test (Leven test), the ANOVA (LSD test) of the monthly mean of rainfall, the daily maximum rainfall and the total number of rainfall days. The multiple comparison (Tehmane’s Test) had been applied between the studied stations. The results of the Shapiro-Wilk test shows that the distribution of monthly rainfall averages follows normal distribution in all stations except stations Tabuk and Al Bad’ and that the maximum daily rainfall distribution at Duba, Shuw?q, Al Kurr stations is also normal distribution. The Leven test results showed that the significance level was greater than 0.05 and the Leven Test was greater than 0.05 for the average monthly precipitation, for the daily maximum rainfall and for the number of rain days and it indicates the homogeneity of the rainfall variances in the studied stations.The ANOVA analysis of the averages and maximum daily rainfall, shows that the significance level is greater than 0.05 and the LSD test is greater than 0.05 indicating that the differences are not significant. While the LSD was greater than 0.05 for the number of rain days, indicating that the differences between the number of rain days and their distribution at the studied stations are statistically significant differences, and therefore there is no homogeneity in their differences. The results of the Tamhane’s Test of multiple comparison confirmed that the mean level of monthly mean rainfall and daily maximum rainfall is greater than 0.05 indicates that the differences between the monthly rain averages of and the daily maximum rainfall amounts are not significant for 22.2% of total comparisons.The effective rainfall estimate of Lang’s rainfall index shows that the threshold of effective mean rainfall is between 1.3 and 27.4 mm and that the threshold of maximum daily rainfall is 154.1 mm at the station (Al Bad’). Also, the effective rainfall estimate by the DeMartonne index shows that the threshold of average effective rainfall is between 1.2 and 15.2 mm and that the threshold of maximum daily rainfall is 80.4 mm at the station (Al Bad’). Therefore, the effective rainfall estimate by the UNEP index shows that the threshold of average effective rainfall is between 1.8 and 30.3 mm and that the threshold of maximum daily rainfall is 130.5 mm at the station (Al Bad’). Finally, the effective rainfall estimate by the difference between the rainfall and Pan Class“A” Evaporation shows that the threshold of average effective rainfall is between 1.2 and 25.8 mm and that the threshold of maximum daily rainfall is 137.1 mm at the station (Al Bad’).- Key Words:Effective rainfall average, Effective maximum daily rainfall , Number of rainy days, Statistical tests, Lang rainfall factor, DeMartonne index, UNEP arid index, Tabuk area, Saudi Arabia.
48
Vishnu, Chakrapani Lekha, Thomas Oommen, Snehamoy Chatterjee, and Kochappi Sathyan Sajinkumar. "Addressing the Effect of Intra-Seasonal Variations in Developing Rainfall Thresholds for Landslides: An Antecedent Rainfall-Based Approach." GeoHazards 5, no. 3 (2024): 634–51. http://dx.doi.org/10.3390/geohazards5030033.
Full textAbstract:
We developed a rainfall threshold model with the objective of limiting the effects of uncertainties typically associated with them, such as a lack of robust landslide database, the selection of the contributing rain gauge, seasonal variations in rainfall patterns, and the effect of extreme rainfall conditions. With the aid of gauge-corrected satellite precipitation data and a landslide database compiled from various sources, separate rainfall thresholds were developed for two waves of the monsoon season in the Western Ghats, India. The daily vs. antecedent rainfall distributions for different scenarios of antecedent rainfall were analyzed for landslide occurrence. The different scenarios considered included 1, 2, 3, 5, 10-, 20-, 30- and 40-day antecedent rainfalls along with the monsoon antecedent defined as the cumulative rainfall from the start of the monsoon to the day prior to landslide occurrence, and the event antecedent defined as the cumulative rainfall from the start of a rainfall event to the day prior to landslide occurrence. A statistically defined critical value was used to define the thresholds for extreme rainfall conditions, while ordinary least squares and quantile regression models were compared to identify the best-fit model for the non-extreme rainfall threshold. Receiver Operating Characteristic (ROC) analysis was performed on all these models and the best model was chosen based on the efficiency values. The daily vs. monsoon antecedent threshold was the best model for the first monsoon wave, and the daily vs. event antecedent model was the best model for the second monsoon wave. A separate rainfall threshold was defined for the entire monsoon without subdivision into separate waves, and corresponding ROC statistics were compared with the former approach to analyze the efficacy of intra-seasonal variations in rainfall threshold development. The results suggest that cumulative rainfall makes a significant contribution towards landslide initiation and that intra-seasonal variations should be necessarily considered in rainfall threshold modeling.
49
Espinosa, Luis Angel, Maria Manuela Portela, João Dehon Pontes Filho, and Martina Zelenakova. "Bivariate Modelling of a Teleconnection Index and Extreme Rainfall in a Small North Atlantic Island." Climate 9, no. 5 (2021): 86. http://dx.doi.org/10.3390/cli9050086.
Full textAbstract:
This paper explores practical applications of bivariate modelling via copulas of two likely dependent random variables, i.e., of the North Atlantic Oscillation (NAO) coupled with extreme rainfall on the small island of Madeira, Portugal. Madeira, due to its small size (∼740 km2), very pronounced mountain landscape, and location in the North Atlantic, experiences a wide range of rainfall regimes, or microclimates, which hamper the analyses of extreme rainfall. Previous studies showed that the influence of the North Atlantic Oscillation (NAO) on extreme rainfall is at its largest in the North Atlantic sector, with the likelihood of increased rainfall events from December through February, particularly during negative NAO phases. Thus, a copula-based approach was adopted for teleconnection, aiming at assigning return periods of daily values of an NAO index (NAOI) coupled with extreme daily rainfalls—for the period from December 1967 to February 2017—at six representative rain gauges of the island. The results show that (i) bivariate copulas describing the dependence characteristics of the underlying joint distributions may provide useful analytical expressions of the return periods of the coupled previous NAOI and extreme rainfall and (ii) that recent years show signs of increasing climate variability with more anomalous daily negative NAOI along with higher extreme rainfall events. These findings highlight the importance of multivariate modelling for teleconnections of prominent patterns of climate variability, such as the NAO, to extreme rainfall in North Atlantic regions, especially in small islands that are highly vulnerable to the effects of abrupt climate variability.
50
Jakob, D., D. J. Karoly, and A. Seed. "Non-stationarity in daily and sub-daily intense rainfall – Part 2: Regional assessment for sites in south-east Australia." Natural Hazards and Earth System Sciences 11, no. 8 (2011): 2273–84. http://dx.doi.org/10.5194/nhess-11-2273-2011.
Full textAbstract:
Abstract. Using data for a common period (1976–2005) for a set of 31 sites located in south-east Australia, variations in frequency and magnitude of intense rainfall events across durations from 6 min to 72 h were assessed. This study was driven by a need to clarify how variations in climate might affect intense rainfall and the potential for flooding. Sub-daily durations are of particular interest for urban applications. Worldwide, few such observation-based studies exist, which is mainly due to limitations in data. Analysis of seasonality in frequency and magnitude of events revealed considerable variation across the set of sites, implying different dominating rainfall-producing mechanisms and/or interactions with local topography. Both these factors are relevant when assessing the potential effects of climate variations on intense rainfall events. The set of sites was therefore split into groups ("north cluster" and "south cluster") according to the characteristics of intense rainfall events. There is a strong polarisation in the nature of changes found for the north cluster and south cluster. While sites in the north cluster typically exhibit decrease in frequency of events, particularly in autumn and at durations of 1 h and longer; sites in the south cluster experience an increase in frequency of events, particularly for summer and sub-hourly durations. Non-stationarity found in historical records has the potential to significantly affect design rainfall estimates. An assessment of quantile estimates derived using a standard regionalisation technique and periods representative of record lengths available for practical applications show that such estimates may not be representative of long-term conditions, so alternative approaches need to be considered, particularly where short records are concerned. Additional rainfall information, in particular radar data, could be used for an in-depth spatial analysis of intense rainfall events.