scholarly journals Relationships between Rainy Days, Mean Daily Intensity, and Seasonal Rainfall over the Koyna Catchment during 1961–2005

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
S. Nandargi ◽  
S. S. Mulye
Keyword(s):  
Linear Relationship ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Seasonal Rainfall ◽  
Frequency Changes ◽  
Logarithmic Relationship ◽  
The Relationship ◽  
Rainfall Climatology ◽  
Rainy Days ◽  
Better Than

There are limitations in using monthly rainfall totals in studies of rainfall climatology as well as in hydrological and agricultural investigations. Variations in rainfall may be considered to result from frequency changes in the daily rainfall of the respective regime. In the present study, daily rainfall data of the stations inside the Koyna catchment has been analysed for the period of 1961–2005 to understand the relationship between the rain and rainy days, mean daily intensity (MDI) and seasonal rainfall over the catchment on monthly as well as seasonal scale. Considering the topographical location of the catchment, analysis of seasonal rainfall data of 8 stations suggests that a linear relationship fits better than the logarithmic relationship in the case of seasonal rainfall versus mean daily intensity. So far as seasonal rainfall versus number of rainy days is considered, the logarithmic relationship is found to be better.

scholarly journals Railway suicides are less likely to occur on rainy days: Evidence from Japan

2021 ◽  
Author(s):  
Hajime Sueki
Keyword(s):  
Incidence Rate ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Japan Meteorological Agency ◽  
Daily Data ◽  
Railroad Company ◽  
The Relationship ◽  
Rainy Days ◽  
Rule Out

Background: Patrols at stations and along railway lines can reduce the number of railway suicides; however, it is not sufficiently clear when railway suicides are most likely to occur. Aim: We examined the relationship between daily rainfall and the occurrence of railway suicides. Methods: We received the locations and daily data on the occurrence of railway suicides from a major railroad company in Japan. We also collected rainfall data from the Japan Meteorological Agency database for a roughly central locations of the railroad company. The study covered a period of five years, from April 2016 to March 2021. Results: Suicides occurred on 23 rainy days (3.9%) and 92 non-rainy days (7.4%). The incidence of suicides on rainy days was significantly lower than that on non-rainy days. Limitations: We were not able to obtain daily data on the number of rail passengers; therefore, could not rule out the possibility that the suicide incidence rate is lower on rainy days because the number of railroad users is lower on such days. Conclusion: Information about the weather could be used to improve the efficiency of patrols to prevent railway suicides.

scholarly journals Effect of rainfall on the yield of major cereals in Darchula District of Nepal

2014 ◽  
Vol 3 (1) ◽  
pp. 205-213 ◽  
Author(s):  
Govinda Bhandari
Keyword(s):  
Rainfall Data ◽  
Seasonal Rainfall ◽  
Poor Growth ◽  
The Relationship

Rainfall is one of the most important factors for the growth of cereals. Inadequate water results poor growth and reduced yield. This study is aimed to explore the relationship between rainfall and yield of major cereals in Darchula district of Nepal. The yield of individual cereals is correlated with the seasonal rainfall data using MS Excel to identify the effect of rainfall on yield of cereals. The amount of rainfall in the years 1974, 1977, 1980, 1985, 1986, 1987, 1991, 1992, 1994, 1996, 1997, 1999 and 2000 was reduced which has greatly affected the yield of rice, wheat and maize in 1986 and 1987. In the years 1976, 1977, 1999 and 2000, the decrease in the amount of rainfall has reduced the yield of all major cereals in Darchula district of Nepal. DOI: http://dx.doi.org/10.3126/ije.v3i1.9954 International Journal of Environment Vol.3(1) 2014: 205-213

Less rain and rainy days - lessons from 45 years of rainfall data (1971 to 2015) in the Kathmandu Valley, Nepal

2021 ◽  
Author(s):  
Rajaram Prajapati ◽  
Rocky Talchabhadel ◽  
Priya Silwal ◽  
Surabhi Upadhyay ◽  
Brandon Ertis ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Temporal Trends ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Kathmandu Valley ◽  
Light Rain ◽  
Mk Test ◽  
Spatio Temporal ◽  
Rainy Days

Abstract Understanding spatio-temporal variability in rainfall patterns is crucial for evaluating water balances needed for water resources planning and management. This paper investigates spatio-temporal variability in rainfall and assesses the frequency of daily rainfall observations from seven stations in the Kathmandu Valley, Nepal, from 1971–2015. Daily rainfall totals were classified into five classes, namely, A (light rain, daily rainfall < 10 mm in a day), B (between 10–50 mm), C (between 50–100 mm), D (between 100–150 mm) and E (> 150 mm). The relationship between daily rainfall and rainfall frequency of various rainfall rate classes were analysed. Kriging method was used for interpolation in interpreting seasonal and annual rainfall data and spatial maps were generated using QGIS. The Mann-Kendall (MK) test was performed to determine the temporal trends and Theil-Sen’s (TS) slope estimator was used in quantifying the magnitude of trends. Mountain stations showed a decreasing trend in rainfall for all seasons, ranging from − 8.4 mm/year at Sankhu to -21.8 mm/year at Thankot, whereas, a mixed pattern was found on the Valley floor. Mean annual rainfall in the Valley was 1610 mm. Both annual rainfall and the number of rainy days decreased in the Kathmandu Valley over the study period. The study indicated a significant reduction in rainfall after 2000. Since springs and shallow groundwater are the primary sources of water supply for residents in the Kathmandu Valley, it is apparent that decreasing rainfall will have (and is already having) an adverse impact on domestic, industrial, and agricultural water supplies, and the livelihoods of people.

scholarly journals Decadal Study of Changing Frequency and Intensity of Rainfall for Selected Locations of Tamil Nadu

2021 ◽  
Vol 16 (3) ◽  
pp. 898-907
Author(s):  
S. KOKILAVANI S. KOKILAVANI ◽  
SP. Ramanathan SP. Ramanathan ◽  
GA. Dheebakaran ◽  
N.K. Sathyamoorthy ◽  
B. Arthirani B. Arthirani ◽  
...  
Keyword(s):  
Tamil Nadu ◽  
Rainfall Intensity ◽  
Rainfall Variability ◽  
Daily Rainfall ◽  
Heavy Rain ◽  
Rainfall Data ◽  
Climatic Extremes ◽  
Increasing Trend ◽  
Research Centres ◽  
Rainy Days

Understanding the pattern of regional climatic extremes is essential for creating an important adaptation measure to safeguard farmers from monsoon tantrums. This paper focuses on the rainfall variability and intensity for spatially different locations of Tamil Nadu. The daily rainfall data over a period of 30 years (1990-2019) for the study locations were collected from the constituent research centres of TNAU. The results indicated that an increasing trend in SWM rainfall was observed in Coimbatore (209.3 to 300.6mm), Ooty (681.4 to 703.1mm), Aduthurai (227.8 to 320.6mm), Kovilpatti (132.8 to 141.3 mm) while the decreasing trend was observed in rest of the places. A decreasing trend was reported in general for all the places during NEM. The decreasing trend in the number of rainy days was registered in Kovilpatti, Virudhunagar and Killikulam that exhibits an alert in modifying the crop planning programme in those areas. The frequency of rainfall intensity revealed that except Ooty, the number of Heavy Rain (HR) to VHR(VHR) was found to be meagre to absent in most of the study locations.

scholarly journals Fitting of a Markov chain model for daily rainfall data at Calcutta

MAUSAM ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 67-74
Author(s):  
A. N. BASU
Keyword(s):  
Markov Chain ◽  
Geometric Distribution ◽  
Markov Chain Model ◽  
Probability Model ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Actual Data ◽  
Chain Model ◽  
Daily Rainfall Data ◽  
Rainy Days

A Markov chain probability model has been fitted to the daily rainfall data recorded at Calcutta. The 'wet spell' and 'weather cycles' are found to obey geometric distribution, The distribution of the number of rainy days per week has been calculated and compared with the actual data.

scholarly journals Characterization of Monsoonal Rainfall in the Sudano-Sahelian Zone of Northwestern Nigeria

2021 ◽  
Vol 1 (2) ◽  
pp. 123-135
Author(s):  
Abdullahi Umar ◽  
Saadu Umar Wali ◽  
Ibrahim Mustapha Dankani
Keyword(s):  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Daily Rainfall ◽  
Kendall Test ◽  
Morlet Wavelet ◽  
Rainfall Data ◽  
Seasonal Rainfall ◽  
Rainfall Characteristics ◽  
Sahelian Zone

Wavelet transform has been underutilized in characterization of rainfall (Real Onset Dates and Real Cessation Dates) in the study area. This study aims at the characterization of monsoonal rainfall. Daily rainfall data of four stations for the period 1981-2018 were collected from Nigerian Meteorological Agency. The Intra-seasonal Rainfall Monitoring Index (IRMI) was generated and used in determining the RODs and RCDs. The Mann–Kendall test was used to detect trends of the rainfall characteristics. Wavelet transform was used in modelling RODs and RCDs. Findings revealed that RODs vary between stations. There is low (0.3 Spearman’s Rank r) correlation between latitudes and Early Cessations (ECs) of rains. The Morlet wavelet analysis revealed that from 1999 to 2018, there were more of EOs and NOs especially in Kano station. We conclude that from 1981 to 2018 there has been a minimal increase in the retreat dates of rainfall in the study area.

scholarly journals Rainfall erosivity estimation based on rainfall data collected over a range of temporal resolutions

2015 ◽  
Vol 12 (5) ◽  
pp. 4965-4996 ◽  
Author(s):  
S. Yin ◽  
Y. Xie ◽  
B. Liu ◽  
M. A. Nearing
Keyword(s):  
Daily Rainfall ◽  
Rainfall Amount ◽  
Rainfall Data ◽  
Data Availability ◽  
Rainfall Erosivity ◽  
Data Prediction ◽  
Yearly Average ◽  
Model Efficiency ◽  
Erosivity Index ◽  
Better Than

Abstract. Rainfall erosivity is the power of rainfall to cause soil erosion by water. The rainfall erosivity index for a rainfall event, EI30, is calculated from the total kinetic energy and maximum 30 min intensity of individual events. However, these data are often unavailable in many areas of the world. The purpose of this study was to develop models that relate more commonly available rainfall data resolutions, such as daily or monthly totals, to rainfall erosivity. Eleven stations with one-minute temporal resolution rainfall data collected from 1961 through 2000 in the eastern water-erosion areas of China were used to develop and calibrate 21 models. Seven independent stations, also with one-minute data, were utilized to validate those models, together with 20 previously published equations. Results showed that models in this study performed better or similar to models from previous research to estimate rainfall erosivity for these data. Prediction capabilities, as determined using symmetric mean absolute percentage errors and Nash–Sutcliffe model efficiency coefficients, were demonstrated for the 41 models including those for estimating erosivity at event, daily, monthly, yearly, average monthly and average annual time scales. Prediction capabilities were generally better using higher resolution rainfall data as inputs. For example, models with rainfall amount and maximum 60 min rainfall amount as inputs performed better than models with rainfall amount and maximum daily rainfall amount, which performed better than those with only rainfall amount. Recommendations are made for choosing the appropriate estimation equation, which depend on objectives and data availability.

scholarly journals Some aspects of daily rainfall distribution over a high range river basin in central Kerala

MAUSAM ◽  
2021 ◽  
Vol 48 (1) ◽  
pp. 71-76
Author(s):  
V. JAYASREE ◽  
K.G. ANIL KUMAR
Keyword(s):  
River Basin ◽  
Frequency Distribution ◽  
Coefficient Of Variation ◽  
Daily Rainfall ◽  
Seasonal Rainfall ◽  
Total Rainfall ◽  
Rainfall Distribution ◽  
Low Intensity ◽  
Rainy Days ◽  
High Range

ABSTRACT. The daily rainfall distribution of twelve stations in the Chalakudy river basin of central Kerala is studied. Normalised rainfall curve (NRC) is constructed and various parameters of the daily rainfall distribution are derived. The number of rainy days and mean rain intensities at each 10% rain amounts are calculated from the NRC. It has been found that the coefficient of variation (CY) is the most important parameter of the daily rainfall distribution which determines the shape of NRC. Frequency distribution of CY values reveals that the CY is highest in the range of 100-120%. Rainfall contributions by non-rainy days and significant rainfall days are calculated. About half of the seasonal rainfall which contributes 80% of the total rainfall are of low intensity. However, the remaining 20% due to higher intensity rainfall are of considerable significance for floods, erosion, etc.    

scholarly journals COMPARISON OF SCS UH AND CLARK METHODS FOR RAINFALL–RUNOFF MODEL IN DELUWANG WATERSHED

2018 ◽  
Vol 2 (01) ◽  
pp. 77
Author(s):  
Muhammad Arifin ◽  
Entin Hidayah ◽  
Wiwik Yunarni Widiarti
Keyword(s):  
Hydrological Modeling ◽  
Daily Rainfall ◽  
Water Source ◽  
Rainfall Data ◽  
Rainfall Runoff ◽  
Unit Hydrograph ◽  
Direct Runoff ◽  
Daily Rainfall Data ◽  
Rainfall Runoff Model ◽  
Better Than

Deluwang River water source is widely used for the needs of irrigation, plantation, and the fulfillment of domestic life. Given the importance of the role of water in Deluwang watershed, then he had to do the management of watershed. The proper management of watershed hydrological modeling requires accurate. Rainfall-runoff using HEC-HMS applications. This research aims tocomparison 2 methods in direct runoff. Therefore this study uses two methods, namely SCS Unit Hydrograph method and method of Clark Unit Hydrograph. On the calibration process using daily rainfall data and daily debit year 2006, whereas in the validation process using daily rainfall data and daily debit years 2007 to 2012. The results of the calibration using Clark Unit Hydrograph method better than using SCS Unit Hydrograph method with Nash's value 0,700 than 0,539. While the results of the validation of modeling using Clark Unit Hydrograph method is better than using SCSUnit Hydrograph method with a value of Nash 0,541 than 0,368. Sungai Deluwang sumber airnya banyak dimanfaatkan untuk kebutuhan irigasi, perkebunan, serta pemenuhan kehidupan rumah tangga. Mengingat pentingnya peranan air pada DAS Deluwang, maka perlu  dilakukannya pengelolaan DAS. Pengelolaan DAS yang tepat membutuhkan pemodelan  hidrologi yang akurat. Pemodelan hujan aliran menggunakan aplikasi HEC-HMS. Penelitian ini bertujuan membandingkan 2 metode yang terdapat pada direct runoff. Oleh karena itu penelitian ini menggunakan dua metode, yaitu metode SCS Unit Hydrograph dan metode Clark Unit Hydrograph. Pada proses kalibrasi menggunakan data curah hujan harian dan debit harian tahun 2006, sedangkan pada proses validasi menggunakan data curah hujan harian dan debit harian tahun 2007 sampai 2012. Hasil kalibrasi menggunakan  metode Clark Unit Hydrograph lebih bagus dibandingkan menggunakan metode SCS Unit Hydrograph dengan nilai Nash 0,700 berbanding 0,539. Sedangkan hasil validasi pemodelan menggunakan  metode Clark Unit Hydrograph lebih bagus dibandingkan menggunakan metode SCS Unit Hydrograph dengan nilai Nash 0,541 berbanding 0,368.

scholarly journals Comparison of Normal Ratio Method and Distance Power Method for Estimating Missing Rainfall Data with Three Neighboring Stations

2021 ◽  
pp. 1-9
Author(s):  
Celeste A. De Asis
Keyword(s):  
Correlation Coefficient ◽  
Daily Rainfall ◽  
T Test ◽  
Monthly Rainfall ◽  
Rainfall Data ◽  
Ratio Method ◽  
Power Method ◽  
Daily Rainfall Data ◽  
Normal Ratio ◽  
Better Than

This study compared the performances of Normal Ratio Method and Distance Power Method as a tool for estimating missing rainfall data. The data utilized are the rainfall data of the three neighboring station of Catarman, Northern Samar, Philippines. These stations are Catbalogan Station (Samar Province), Legazpi (Bicol Province) and Masbate (Masbate Province). The observed daily rainfall data for the Catarman (Northern Samar), Catbalogan, Legazpi, and Masbate were obtained from the Philippine Atmospheric Geographical Astronomical Services Administration. The monthly rainfall were computed for the three (3) neighboring stations (Catbalogan, Legazpi, Masbate). The evaluation used the T-test for correlated samples and the Pearson’s Correlation Coefficient for the monthly rainfall data computed of the three neighboring Station of Catarman, Northern Samar with the three neighboring stations. Based from the results, Normal Ratio Method performs better than Distance Power Method as applied to three neighboring stations.

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