scholarly journals Evaluation of Lake Simcoe watershed rainfall characterisics

2021 ◽  
Author(s):  
Rabi C. Gautam
Keyword(s):  
Winter Season ◽  
Daily Rainfall ◽  
Summer Season ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Initial Analysis ◽  
Daily Rainfall Data ◽  
Average Annual Rainfall ◽  
Increasing Trend ◽  
Lake Simcoe

Lake Simcoe Region Conservation Authority is monitoring the phosphorous loading in Lake Simcoe and to understand the changes in phosphorous loading due to runoff, it is prudent to characterize the rainfall data of the watershed contributing to Lake Simcoe. In this project, hourly and daily rainfall data from 13 different raingage statistics surrounding Lake Simcoe was analyzed to identify event, monthly, seasonal and annual statistics and their trend and thereby to identify the driest and wettest and average annual rainfall. After initial analysis, daily rainfall data from only 4 stations with consistent data for an approximate period of 20 years were chosen for further analysis. The results showed that hydrological year 1995-1996 was the wettest and hydrologic year 1991-1992 was the driest year. Similarly summer season and the month of June were the wettest and winter season and month of February were the driest for the watershed. No significant trend was observed in the yearly and monthly rainfall data while an increasing trend was observed at 3 stations for the winter season.

scholarly journals Evaluation of Lake Simcoe watershed rainfall characterisics

2021 ◽  
Author(s):  
Rabi C. Gautam
Keyword(s):  
Winter Season ◽  
Daily Rainfall ◽  
Summer Season ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Initial Analysis ◽  
Daily Rainfall Data ◽  
Average Annual Rainfall ◽  
Increasing Trend ◽  
Lake Simcoe

Lake Simcoe Region Conservation Authority is monitoring the phosphorous loading in Lake Simcoe and to understand the changes in phosphorous loading due to runoff, it is prudent to characterize the rainfall data of the watershed contributing to Lake Simcoe. In this project, hourly and daily rainfall data from 13 different raingage statistics surrounding Lake Simcoe was analyzed to identify event, monthly, seasonal and annual statistics and their trend and thereby to identify the driest and wettest and average annual rainfall. After initial analysis, daily rainfall data from only 4 stations with consistent data for an approximate period of 20 years were chosen for further analysis. The results showed that hydrological year 1995-1996 was the wettest and hydrologic year 1991-1992 was the driest year. Similarly summer season and the month of June were the wettest and winter season and month of February were the driest for the watershed. No significant trend was observed in the yearly and monthly rainfall data while an increasing trend was observed at 3 stations for the winter season.

scholarly journals Variabilitas Spasial Hujan Tahunan di Wilayah UPT PSDA di Pasuruan, Jawa Timur : Analisis Histogram dan Normal QQ-Plot

2018 ◽  
Vol 11 (1) ◽  
pp. 35-49
Author(s):  
Askin Askin ◽  
Indarto Indarto ◽  
Dimas Ghufron Ash-Shiddiq ◽  
Sri Wahyuningsih
Keyword(s):  
Spatial Variability ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Thematic Map ◽  
Daily Rainfall Data ◽  
Average Annual Rainfall ◽  
Administrative Area ◽  
Main Input

Abstrak. Penelitian ini bertujuan untuk menganalisis variabilitas spasial hujan di wilayah UPT PSDA di Pasuruan. Wilayah studi mencakup kabupaten Probolinggo, kota Probolinggo, Kabupaten Pasuruan dan Kota Pasuruan di Jawa Timur. Data hujan tahunan rerata (Hthn_rrt) dan hujan tahunan maksimal (HthnMaks) dihitung dari kumulatif data hujan harian pada 93 stasiun dan dijadikan sebagai input utama untuk analisis. Panjang periode rekaman data yang digunakan dari tahun 1980 sampai dengan 2015 (35 tahun). Tahap penelitian mencakup: (1) pra-pengolahan data, (2) analisis pendahuluan, (3) analisis menggunakan tool histogram dan voronoi map, (4) interpolasi data dan pembuatan peta tematik. Pra-pengolahan data dilakukan menggunakan excel. Analisis histogram dan QQ-Plot dilakukan untuk melihat variabilitas spasial lebih detail per sub-wilayah. Selanjutnya, metode interpolasi digunakan untuk membuat peta tematik hujan tahunan. Peta tematik menunjukkan hujan tahunan rerata (Hthn_rrt) yang terjadi di wilayah tersebut selama 35 tahun terakhir berkisar antara 1200 sd 2600 mm/tahun. Hujan tahunan maksimal yang terjadi berkisar antara 2100 sd 4500 mm/tahun. Penelitian juga menunjukkan adanya korelasi positif antara lokasi stasiun hujan (elevasi) dengan jumlah hujan tahunan yang diterima. Spatial Variability of Annual Rainfall in The Administrative Area of UPT PSDA at Pasuruan, East Java : Analysis Using Histogram and QQ-Plot Abstract. This research aims to analyze the spatial variability of annual rainfall. Daily rainfall data from 93 rain gauge in the administrative area of UPT PSDA Pasuruan were used as the main input. The average annual rainfall and the maximum annual rainfall obtained from the daily rainfall data. Histograms, and QQ-Plot were used to describe the spatial variability in each sub-regions. Next, interpolation methods is used to create a thematic map of the annual rainfall. The results shows that local spatial variability of rainfall can be visualized more detail for each sub-region by means of histogram and QQ-Plot. The thematic map showed that the distribution of average annual rainfall in the region range from 1,200 mm/year up to 2,600 mm/year. Maximum annual rainfall range between 2,100 mm/year up to 4,500 mm/year. The result also show the positif correlation between the altitude of the rain gauge and local annual rainfall received.

scholarly journals Rainfall Trend Analysis in Tehsils of Palghar District, Maharashtra State, India

2021 ◽  
Vol 9 (11) ◽  
pp. 238-253
Author(s):  
Dr. Sumit M. Dhak
Keyword(s):  
Trend Analysis ◽  
Linear Trend ◽  
Daily Rainfall ◽  
Kendall Test ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Rainfall Trend ◽  
Department Of Agriculture ◽  
Increasing Trend ◽  
Slope Estimator

Abstract: A detailed trend analysis of monthly and annual rainfall for Tehsils of Palghar district were carried out using 22 years (1998-2019) daily rainfall data taken from Department of Agriculture, Maharashtra State. In this study, to analyse the trend, the non-parametric test (Mann-Kendall test) and Sen’s slope estimator were used. For developing a functional relationship between variables, a linear trend of rainfall data for the studied area evaluated using the linear regression. The results showed that the trend analysis of monthly rainfall has a varied trend of rainfall in the rainy months in tehsil of Palghar District. The month of July significant increasing trend was observed at Jawhar (42.91 mm/year), Vikramgad (29.90 mm/year), Wada (24.06 mm/year), Talasari (31.36 mm/year), Palghar (25.299 mm/year), Mokhada (29.96 mm/year) and Dahanu (38.14 mm/year), whereas non-significant increasing trend 2.76 mm/year was observed at Vasai tehsil of Palghar District during 1998-2019. The month of June, August, September and October rainfall did not show any significant trend in tehsil of Palghar District and non significant decreasing as well as non significant increasing trend was observed in tehsil of Palghar District during 1998 – 2019. The result concluded that annual rainfall trend was increased in Jawhar, Vikramgad, Wada, Talasari, Palghar, Mokhada and Dahanu; whereas Vasai tehsil rainfall trend was decreased in tehsil of Palghar District during 1998 -2019. Keywords: Rainfall, Trend Analysis, Mann Kendall’s Test, Sen Slopes, Regression

scholarly journals Taluka Wise Study of Rainfall Pattern in Nanded District of Marthwada Region (Maharashtra) Using Rainfall Data

2021 ◽  
Vol 10 (9) ◽  
pp. 333-350
Author(s):  
Ramesh Bethala B. V. Asewar ◽  
M. S. Peneke K. K. Dakhore ◽  
M. G. Jadhav A. M. Khobragade
Keyword(s):  
Crop Production ◽  
Rainfall Variability ◽  
Winter Season ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Monsoon Period ◽  
Annual Basis ◽  
Rainy Days ◽  
Onset Of Monsoon

About 60 per cent of the total cultivable area of the country is rainfed. However, prolonged dry periods affect the final crop production. Monsoon is an important season for water supplies, from surface reservoir. Uneven distribution of rainfall, affect the agricultural production remarkably. The daily rainfall data was collected for each taluka of Nanded district for the period of 20 years (1998-2017) and it was to be summed up on meteorological weekly, monthly, seasonally, annual basis for each taluka of Nanded district basis for the study of rainfall characterization. The results indicated that weekly mean annual basis total rainfall was ranged between 720.0 mm in Deglur and 1009.9 mm in Mahur. The weekly highest rainfall on annual basis was recorded in Himayat Nagar (53.7 mm) in the 30th MW amongst all the taluka considering monsoon period (23 to 42 MW). The monthly mean rainfall indicated that the lowest and highest monthly mean rainfall amongst all the taluka was observed in Nanded, Kandhar, Loha, Hadgaon, Bhokar, Kinwat, Mahur, Dharmabad, Ardhapur, Naigaon talukas (0.0 mm) in the December month and in the Mahur taluka (283.1 mm) in July month. The seasonal distribution of Nanded district was obtained in winter season (6.1 mm), in summer (15.5 mm), in monsoon (578.3 mm), in post monsoon (216.6 mm). The annual rainfall data is statistical analyzed for Nanded district and within the year and taluka to taluka ranged C.V. (%) were between 25.0 to 46.9 %. The data of taluka-wise annual normal of weather parameter (i.e. rainfall and rainy days) calculated. Here, the results indicated that the onset of monsoon was observed in 23th MW and withdrawal in 43rd MW in Nanded district. It showed that average rainfall of Nanded district is 816.4 mm with 45.0 rainy days per year. The results clearly indicated the onset of monsoon in 23th MW and withdrawal of monsoon in 43rd MW for the Nanded district should be considered. The statistical analysis for rainfall variability was worked out and it was intra-annual as well as intra-taluka variation in Nanded district. It was ranged between 19.0 to 51.0 per cent with annual mean 45.0 rainy days per year.

scholarly journals Trend analysis of rainfall data Rangpur, Bangladesh

2020 ◽  
Vol 8 (1) ◽  
pp. 81
Author(s):  
Sudip Saha
Keyword(s):  
Monsoon Rainfall ◽  
Pearson Correlation ◽  
Daily Rainfall ◽  
Monthly Rainfall ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Increasing Trend ◽  
The Mean ◽  
June July ◽  
The Right

The study area lies in Bangladesh that is in the tropical area. The analysis of rainfall data reveals that the average annual rainfall in Rangpur was 2099.25 mm that varies from 427 mm to 3748 mm within the investigated period of time. The highest amount of annual rainfall was recorded in 1984. Heavy rainfall occurs in the month of July of the year. The highest amount of total monthly rainfall was recorded in July, 1987 and measured as 1314 mm. The rainfall trend can be expressed as monsoon rainfall > pre-monsoon rainfall> post monsoon rainfall. The total amount of annual rainfall is strongly significantly positively correlated with the total monthly rainfall of the months of June, July August, September and October and significantly positively correlated with the total monthly rainfall of the month April. The analysis shows that it rained in every year in the month of June as the minimum monthly value for June is greater than zero. Pearson correlation index shows that the mean daily temperature is significantly negatively correlated with daily rainfall which implies that fall of daily mean temperature with the daily rainfall. The increasing trend of annual rainfall suggests the climate change in Rangpur within the investigated period of time. In Rangpur, the value of skewness for all rainfall data are positive that indicate the data are skewed to the right. The positive values of kurtosis indicate that the distribution is not normal. 

scholarly journals Performance of TRMM TMPA 3B42 V7 in Replicating Daily Rainfall and Regional Rainfall Regimes in the Amazon Basin (1998–2013)

2018 ◽  
Vol 10 (12) ◽  
pp. 1879 ◽  
Author(s):  
Véronique Michot ◽  
Daniel Vila ◽  
Damien Arvor ◽  
Thomas Corpetti ◽  
Josyane Ronchail ◽  
...  
Keyword(s):  
Amazon Basin ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Spatial Coverage ◽  
Rainfall Regimes ◽  
Trmm 3B42 ◽  
Good Agreement

Knowledge and studies on precipitation in the Amazon Basin (AB) are determinant for environmental aspects such as hydrology, ecology, as well as for social aspects like agriculture, food security, or health issues. Availability of rainfall data at high spatio-temporal resolution is thus crucial for these purposes. Remote sensing techniques provide extensive spatial coverage compared to ground-based rainfall data but it is imperative to assess the quality of the estimates. Previous studies underline at regional scale in the AB, and for some years, the efficiency of the Tropical Rainfall Measurement Mission (TRMM) 3B42 Version 7 (V7) (hereafter 3B42) daily product data, to provide a good view of the rainfall time variability which is important to understand the impacts of El Nino Southern Oscilation. Then our study aims to enhance the knowledge about the quality of this product on the entire AB and provide a useful understanding about his capacity to reproduce the annual rainfall regimes. For that purpose we compared 3B42 against 205 quality-controlled rain gauge measurements for the period from March 1998 to July 2013, with the aim to know whether 3B42 is reliable for climate studies. Analysis of quantitative (Bias, Relative RMSE) and categorical statistics (POD, FAR) for the whole period show a more accurate spatial distribution of mean daily rainfall estimations in the lowlands than in the Andean regions. In the latter, the location of a rain gauge and its exposure seem to be more relevant to explain mismatches with 3B42 rather than its elevation. In general, a good agreement is observed between rain gauge derived regimes and those from 3B42; however, performance is better in the rainy period. Finally, an original way to validate the estimations is by taking into account the interannual variability of rainfall regimes (i.e., the presence of sub-regimes): four sub-regimes in the northeast AB defined from rain gauges and 3B42 were found to be in good agreement. Furthermore, this work examined whether TRMM 3B42 V7 rainfall estimates for all the grid points in the AB, outgoing longwave radiation (OLR) and water vapor flux patterns are consistent in the northeast of AB.

The effect of weather, drainage efficiency and duration of spring cultivations on barley yields in England

1972 ◽  
Vol 7 (2) ◽  
pp. 79-83 ◽  
Author(s):  
L P Smith
Keyword(s):  
Yield Loss ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Work Schedule ◽  
Average Yield ◽  
Daily Rainfall Data ◽  
Arable Farming ◽  
Work Distribution

Daily rainfall data for twenty years in arable farming areas are analysed with respect to four standards of drainage and for three lengths of schedule of spring work. Distribution and frequency in time of available work days are interpreted in terms of lateness of sowing and of barley yield. Formulae are established to calculate average yield loss in terms of drainage standard and work schedule, enabling estimates to be made of the effect of planned improvements.

scholarly journals Bayesian Time Series Modelling of the Italian Daily Rainfall Data using Mixed Distribution

2019 ◽  
Vol 8 (4) ◽  
pp. 2279-2288
Keyword(s):  
Time Series ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Seasonal Effects ◽  
Model Parameters ◽  
Daily Rainfall Data ◽  
Mixed Distribution ◽  
Time Series Modelling ◽  
Bayesian Time Series ◽  
The Ideal

A combination of continuous and discrete elements is referred to as a mixed distribution. For example, daily rainfall data consist of zero and positive values. We aim to develop a Bayesian time series model that captures the evolution of the daily rainfall data in Italy, focussing on directly linking the amount and occurrence of rainfall. Two gamma (G1 and G2) distributions with different parameterisations and lognormal distribution were investigated to identify the ideal distribution representing the amount process. Truncated Fourier series was used to incorporate the seasonal effects which captures the variability in daily rainfall amounts throughout the year. A first-order Markov chain was used to model rainfall occurrence conditional on the presence or absence of rainfall on the previous day. We also built a hierarchical prior structure to represent our subjective beliefs and capture the initial uncertainties of the unknown model parameters for both amount and occurrence processes. The daily rainfall data from Urbino rain gauge station in Italy were then used to demonstrate the applicability of our proposed methods. Residual analysis and posterior predictive checking method were utilised to assess the adequacy of model fit. In conclusion, we clearly found that our proposed method satisfactorily and accurately fits the Italian daily rainfall data. The gamma distribution was found to be the ideal probability density function to represent the amount of daily rainfall.

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