scholarly journals Analysis of rainfall by using Mann-Kendall trend, Sen’s slope and variability at five districts of south Gujarat, India

MAUSAM ◽  
2021 ◽  
Vol 68 (2) ◽  
pp. 205-222 ◽  
Author(s):  
NEERAJ KUMAR ◽  
C. C. PANCHAL ◽  
S. K. CHANDRAWANSHI ◽  
J. D. THANKI
Keyword(s):  
Standard Deviation ◽  
Monsoon Rainfall ◽  
Monsoon Season ◽  
Rainfall Variability ◽  
Winter Season ◽  
Annual Rainfall ◽  
Present Contribution ◽  
Sen’S Slope ◽  
Post Monsoon ◽  
Data Points

On the basis of past 115 years (1901-2015) rainfall data of five districts of south Gujarat, the Mann-Kendall trend, Sen’s slope and regression slope showed that annual and monsoon rainfall at Valsad, Dang and Surat shows the increasing trend while, that of Navsari and Bharuch districts are declining. The monsoon season (summer monsoon) rainfall variability of Valsad, Dang, Surat, Navsari and Bharuch districts was recorded is 30.1%, 30.9%, 35.9%. 33.3% and 38.6%. The high coefficient of variation (CV) denoted that the variability of rainfall is not equally distributed and the amount of rainfall is lowest. The Bharuch district the annual and monsoon CV per cent denoted that the variability of rainfall in both seasons are very high. Valsad was recorded lowest CV with highest rainfall while the data are represent that variability of rainfall which can varies Bharuch to Dang in different districts of south Gujarat. The data shows that Dang district comes under high rainfall and Bharuch under low rainfall on south Gujarat. A low standard deviation indicates that the data points tend to be close to the mean of the set, while a high standard deviation indicates that the data points are spread out over a wider range of values. Similarly high SD is reported at Dang district because of high range of rainfall and lowest SD is found at Bharuch district because of low rainfall variability. The rainfall distribution different season viz., pre monsoon, monsoon post monsoon and winter season, the highest present contribution of rainfall is observed during monsoon season followed by post monsoon in all the five districts of south Gujarat. Rainfall contribution during remaining months was less than one per cent. While month wise analysis shows during monsoon season highest rainfall per cent contribution to annual rainfall is in July followed by August and June months at all the five districts of south Gujarat.

scholarly journals Rainfall Analysis by Using Mann-Kendall Trend, Sen’s Slope and Variability at Six Stations of Andaman & Nicobar Islands

2021 ◽  
Author(s):  
Sukumar Roy ◽  
Nabajit Chakravarty
Keyword(s):  
Standard Deviation ◽  
Coefficient Of Variation ◽  
Monsoon Rainfall ◽  
Monsoon Season ◽  
Rainfall Variability ◽  
Sen’S Slope ◽  
Post Monsoon ◽  
Wide Range ◽  
Data Points ◽  
Nicobar Islands

Abstract On analysis of thirty five years rainfall data ( 1980-2015 ) of six stations of Andaman & Nicobar islands it was found through Mann-Kendall trend , Sen’s slope and Regression slope , that annual and monsoon rainfall at Mayabandar, LongIsland, PortBlair and Carnicobar showed increasing trend while that of HutBay and Nuncowrie showed decreasing trend. The monsoon season ( summer monsoon ) rainfall variability of 49.78% in Mayabandar, 52.12% in Long Island, 24.09 % in Port Blair, 49.39% in HutBay , 47.26% in Carnicobar and 51.91% in Nuncowrie has been recorded in this time span. The high coefficient of variation ( CV) denoted that the variability of rainfall is not equally distributed. A low standard deviation indicates that the data points tend to be close to the mean of the set, while a high standard deviation indicates that the data points are spread out over a wide range of values. High SD was reported at all the five stations of study in comparison to Port Blair which also had a low coefficient of variation. The rainfall distribution of different season viz. pre monsoon , monsoon , post monsoon and winter , it was observed that the highest present contribution of rainfall was observed during monsoon season followed by post monsoon in all the six stations of Andaman & Nicobar islands . Rainfall contribution during May to November was most in all the six stations studied , while in remaining months it was 5.3% in Mayabandar , 6.4% LongIsland, 10.2% in Port Blair, 12.3% in HutBay , 16.9% in CarNicobar and 21.1 % in Nuncowrie.

scholarly journals Rainfall trend analysis using Mann-Kendall and Sen’s slope estimator test in West Kalimantan

2021 ◽  
Vol 893 (1) ◽  
pp. 012006
Author(s):  
F Aditya ◽  
E Gusmayanti ◽  
J Sudrajat
Keyword(s):  
Climate Change ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Sen’S Slope Estimator ◽  
West Kalimantan ◽  
Rainfall Analysis ◽  
Sen’S Slope ◽  
Rainfall Trends ◽  
Slope Estimator ◽  
The Impact

Abstract Climate change has been a prominent issue in the last decade. Climate change on a global scale does not necessarily have the same effect in different regions. Rainfall is a crucial weather element related to climate change. Rainfall trends analysis is an appropriate step in assessing the impact of climate change on water availability and food security. This study examines rainfall variations and changes at West Kalimantan, focusing on Mempawah and Kubu Raya from 2000-2019. The Mann-Kendall (MK) and Sen's Slope estimator test, which can determine rainfall variability and long-term monotonic trends, were utilized to analyze 12 rainfall stations. The findings revealed that the annual rainfall pattern prevailed in all locations. Mempawah region tends to experience a downward trend, while Kubu Raya had an upward trend. However, a significant trend (at 95% confidence level) was identified in Sungai Kunyit with a slope value of -33.20 mm/year. This trend indicates that Sungai Kunyit will become drier in the future. The results of monthly rainfall analysis showed that significant upward and downward trends were detected in eight locations. Rainfall trends indicate that climate change has occurred in this region.

scholarly journals Analysis of rainfall trends over Tripura

MAUSAM ◽  
2022 ◽  
Vol 73 (1) ◽  
pp. 27-36
Author(s):  
RANJAN PHUKAN ◽  
D. SAHA
Keyword(s):  
Heavy Rainfall ◽  
Monsoon Season ◽  
Rainfall Variability ◽  
Kendall Test ◽  
Annual Rainfall ◽  
The North ◽  
Rainfall Trends ◽  
Annual Scale ◽  
Increasing Trends ◽  
Rainy Days

Rainfall in India has very high temporal and spatial variability. The rainfall variability affects the livelihood and food habits of people from different regions. In this study, the rainfall trends in two stations in the north-eastern state of Tripura, namely Agartala and Kailashahar have been studied for the period 1955-2017. The state experiences an annual mean of more than 2000 mm of rainfall, out of which, about 60% occurs during the monsoon season and about 30% in pre-monsoon. An attempt has been made to analyze the trends in seasonal and annual rainfall, rainy days and heavy rainfall in the two stations, during the same period.Non-parametric Mann-Kendall test has been used to find out the significance of these trends. Both increasing and decreasing trends are observed over the two stations. Increasing trends in rainfall, rainy days and heavy rainfall are found at Agartala during pre-monsoon season and decreasing trends in all other seasons and at annual scale. At Kailashahar, rainfall amount (rainy days & heavy rainfall) is found to be increasing during pre-monsoon and monsoon seasons (pre-monsoon season). At annual scale also, rainfall and rainy days show increasing trends at Kailashahar. The parameters are showing decreasing trends during all other seasons at the station. Rainy days over Agartala show a significantly decreasing trend in monsoon, whereas no other trend is found to be significant over both the stations.  

scholarly journals Annual and monthly rainfall trend in plantation and spice farming Western Ghats districts

1970 ◽  
pp. 45
Author(s):  
K Kandiannan, K S Krishnamurthy, C K Thankamani, S J Ankegowda
Keyword(s):  
Coefficient Of Variation ◽  
Western Ghats ◽  
Monsoon Rainfall ◽  
Southwest Monsoon ◽  
Monthly Rainfall ◽  
Negative Trend ◽  
Annual Rainfall ◽  
Post Monsoon ◽  
The Nilgiris ◽  
Southwest Monsoon Rainfall

Rainfall analysis of important plantation and spices producing districts such as The Nilgiris (Tamil Nadu), Kodagu (Karnataka) Idukki (Kerala) and Wayanad (Kerala) with 100 years data (1901 to 2000) obtained from the India Meteorological Department (IMD), Pune indicated that mean annual rainfall were 1839.7mm, 2715.7mm, 2979.4mm and 3381.0mm with a coefficient of variation (CV) of 16.0%, 17.0%, 25.8% and 19.6%, respectively. The contribution of southwest monsoon(June-September) to the annual rainfall in these districts were 80.3% (Wayanad), 78.9% (Kodagu),  65.2% (Idukki) and 56.3%  (The Nilgiris) with corresponding CV of 24.1%, 20.6%, 32.5%, and 24.6%, respectively. The declining trend in mean annual rainfall was noticed for Idukki, Wayanad and The Nilgiris, whereas, for Kodagu, it was stable. The change was significant in Wayanad and The Nilgiris. Similar trend was also observed for the southwest monsoon rainfall. The maximum decline in annual and southwest monsoon rainfall was noticed in The Nilgiris followed by Wayanad. Pre and post monsoon rainfall receipts were comparatively less with high inter-annual variations. The pre-monsoon (March-May) receipt and its coefficient of variation (CV) was 252.4mm & 20.6% (Kodagu), 360.9mm & 36.5% (Idukki), 251.7mm & 36.6% (The Nilgiris) and 274.2mm & 54.2% (Wayanad). The post monsoon (October-December) rain was maximum in Idukki 548.1mm (CV 27.9%) followed by The Nilgiris 503.4mm(CV 31.3%), Wayanad, 333.1mm(CV 37.8%) and Kodagu 310.5mm (CV 32.7%). In all these districts there was a declining trend in the pre-monsoon rain with maximum decline in The Nilgiris. Similar declining trend was also observed in post-monsoon rain except for The Nilgiris, where the trend has been increasing. Overall, the study gives an indication that there was a spatial and temporal variation in rainfall amounts.  The maximum decline in annual rainfall and the southwest monsoon was observed in The Nilgiris and Wayanad. July was the rainiest month in all the districts studied. Significant negative trend was asscoaited with The Nilgiris for January, May, June, July and August months. Whereas, in Kodagu, no significant trend was observed for mean monthly rainfall, except for August. In Idukki, significant negative changes were noticed for January, March, October and December rainfall. Monthly rainfall of January, March, April and July monthly rainfall were showed significant negative trend in Wayanad,. These negative trends across important plantation and spices producing districts of the Western Ghats would affect not only the agricultural economy of this sector but also water resources.

scholarly journals Long term rainfall variability and trend analysis in lower Shivaliks of Punjab, India

MAUSAM ◽  
2021 ◽  
Vol 72 (3) ◽  
pp. 571-582
Author(s):  
NAVNEET KAUR ◽  
ABRAR YOUSUF ◽  
M. J. SINGH
Keyword(s):  
Trend Analysis ◽  
Monsoon Rainfall ◽  
Rainfall Variability ◽  
Kendall Test ◽  
Annual Rainfall ◽  
Entire Study ◽  
Seasonal Basis ◽  
Normal Rainfall ◽  
Rainy Days

The trend analysis of historical rainfall data on monthly, annual and seasonal basis for three locations in lower Shivaliks of Punjab, viz., Patiala-ki-Rao (1982-2015), Ballowal Saunkhri (1987-2015) and Saleran (1984-2017) has been done in the present study using linear regression model, Mann Kendall test and Sen’s slope. Further, the data for annual and seasonal rainfall and rainy days has also been analyzed on quindecennial basis, i.e., for the period of 1986-2000 and 2001-2015. The analysis of data showed that annual rainfall in the region ranged from 1000 to 1150 mm. The trend analysis of the data shows that the monthly rainfall is decreasing at Patiala-ki-Rao and Saleran, however, the trend was significant for May at Patiala-ki-Rao; and in March and November at Saleran. At Ballowal Saunkhri, the decreasing trend is observed from May to October, however, the trend is significant only in August. The decrease in annual and monsoon rainfall is about 13 to 17 mm and 12 to 13 mm per year respectively at three locations in lower Shivaliks of Punjab. The highest annual (1600-2000 mm) and monsoon (1500-1800 mm) rainfall during the entire study period was recorded in the year 1988 at three locations. The decadal analysis of the data shows below normal rainfall during April to October. The analysis of the rainfall and rainy days on monthly, annual and seasonal averages of 15 year basis showed that both rainfall and rainy days have decreased during the 2001-2015 as compared to 1986-2000 during all the seasons of the year.

scholarly journals Trend analysis of rainfall using Mann-Kendall, Sen’s slope, moving average and least square techniques for Ahmednagar district of Maharashtra

2021 ◽  
Vol 17 (1) ◽  
pp. 19-25
Author(s):  
Virendra N. Barai ◽  
Rohini M. Kalunge
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Moving Average ◽  
Rainfall Variability ◽  
Least Square ◽  
Annual Rainfall ◽  
Series Data ◽  
Sen’S Slope ◽  
Increasing Trend ◽  
The Impact

The long-term behaviour of rainfall is necessary to study over space with different time series viz., annual, monthly and weekly as it is one of the most significant climatic variables. Rainfall trend is an important tool which assesses the impact of climate change and provides direction to cope up with its adverse effects on the agriculture. Several studies have been performed to establish the pattern of rainfall over various time periods for different areas that can be used for better agricultural planning, water supply management, etc. Consequently, the present report, entitled “Trend analysis of rainfall in Ahmednagar district of Maharashtra,” was carried out. 13 tahsils of the district of Ahmednagar were selected to carry out trend analysis. The daily rainfall data of 33 years (1980- 2012) of all stations has been processed out study the rainfall variability. The Mann Kendall (MK) Test, Sen’s slope method, moving average method and least square method were used for analysis. The statistical analysis of whole reference time series data highlighted that July and August month contributes highest amount of rainfall at all tahsils. Regarding trend in annual rainfall, these four methods showed increasing trend at most of the tahsils whereas a decreasing trend only at Shrigonda tahsil. For monthly trend analysis, Kopargaon, Newasa, Shevgaon and Shrirampur tahsils showed an increasing trend during July. During August and September month, most of the tahsils i.e. Kopargaon, Nagar, Parner and Sangamner showed increasing trends, whereas in June, only Shrigonda tahsil showed decreasing trend.

Mortality Pattern of Broiler Rabbits in an Organized Farm in Bihar, India

2020 ◽  
Author(s):  
Asit Chakrabarti
Keyword(s):  
Monsoon Season ◽  
Abdominal Cavity ◽  
Winter Season ◽  
The Other ◽  
Housing System ◽  
Pathological Examination ◽  
Eastern Region ◽  
Mortality Pattern ◽  
Bacterial Diseases ◽  
Post Monsoon

Background: The pre and post-weaning mortality in broiler rabbit limits the production potential and lower the income generation through rabbit farming. Therefore, mortality pattern of animals in a farm is very essential clue for future strategy to combat the incidences of various diseases and prevention. Considering the above fact the present study was undertaken to find out the incidences of various rabbit diseases and mortality in an organized institutional farm.Methods: ICAR Research Complex for Eastern Region, Patna was maintaining a broiler rabbit farm with 364 rabbit comprising Newzealand White (194) and Soviet Chinchilla (170) rabbit breed. During the three years (October, 2011 to September, 2014) study period in total 364 rabbits were under observation. The seasonal variation viz. (pre-monsoon, monsoon, post-monsoon and winter, in regards to mortality, disease incidences, young and adults, sex variation, breed, housing system etc were recorded. The incidences of disease and mortality of rabbits were diagnosed through pathological examination and postmortem findings. The descriptive statistics and ÷2 test were used to explain the statistical significance.Result: During the three years study period out of 364 broiler rabbits (Soviet Chinchilla and Newzealand white) in total 63 rabbits (17.31%) were died due to various diseases. The coccidiosis (3.02%), green slime disease (2.20%), haemorrhagic tracheitis (1.92%), enteritis (1.65%), pneumonia (1.37%) and peritonitis (1.37%) were affected more than the other diseases. Apart from these the other ailments that affected broiler rabbits were ear cancer (0.82%), gastroenteritis (0.82%), stomach infection (0.82%), cardinogenic shock (0.55%), stomach impaction (0.55%), kidney infection (0.55%), limb injury (0.27%), ascites (0.27%), cystitis (0.27%), abscess in abdominal cavity (0.27%), rupture of liver and gall bladder (0.27%) as well as injury of eye and blindness (0.27%). The Soviet Chinchilla rabbits were less (7.14%) affected than the Newzealand white (10.16%). It was observed that mortality of male rabbits (6.04%) were less than the female rabbits (11.26%) and mortality of young were higher (11.54%) than the adult rabbits (5.77%). The seasonal variations in mortality of broiler rabbits were observed in present study. In monsoon season mortality was maximum i.e. 6.32% whereas, in post-monsoon it was 5.49%, pre-monsoon 3.02% and in winter season mortality was only 2.47%. The Soviet Chinchilla rabbits were less susceptible and comparatively better performer in regards to disease resistance. It may be concluded that in broiler rabbit farm coccidiosia is a major concern along with other parasitic and bacterial diseases. However, proper hygiene and sanitation along with periodic treatment with coccidiostat and deworming reduces mortality of rabbits. 

Evapotranspiration Distribution and Variation of Pakistan (1931-2015)

2017 ◽  
Vol 17 (2) ◽  
pp. 184-197 ◽  
Author(s):  
Saifullah Khan ◽  
Mahmood Ul Hasan
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Surface Pressure ◽  
Sunshine Duration ◽  
Monsoon Season ◽  
Winter Season ◽  
Main Element ◽  
Mountainous Region ◽  
Post Monsoon ◽  
Post Monsoon Season

AbstractEvapotranspiration is the main element of aridity and desertification and to balance the natural hydrological processes. Pakistan has a high degree of evapotranspiration, as it is in subtropical belt, with long sunshine duration and low cloudiness in summers. June is the warmest month, when the evapotranspiration exceeds 7mm (0.28inches), whereas, January is the coldest month, when evapotranspiration of the country falls to 1mm (0.04inches). The maximum evapotranspiration has been recorded at the southern latitudes of the country (Hyderabad and Jacobabad), while it decreases towards northwest (mountainous region) and Gilgit-Baltistan (Astore and Skardu). This variation in evapotranspiration is due to fluctuation in temperature, precipitation, sunshine duration, wind speed, relative humidity, physical relief and latitudinal as well as altitudinal extend of the country. The average evapotranspiration of Pakistan is 4.5mm with an increase of 1.0mm during 1931-2015. In winter and summer season, the lower Indus basin, has recorded high evapotranspiration as compared to the northern mountainous region. The average evapotranspiration of Pakistan during winter season is 2.7mm, while in summer it is 6.3mm. This variation is due to the variation in the length of day and night, humidity, precipitation, surface pressure, wind speed, and topography of the land. During cold season the average evapotranspiration of the country is 13.7mm, pre-monsoon season 17.1mm, monsoon season 15.8mm and post monsoon season 8mm. Obviously, the highest evapotranspiration of Pakistan has recorded during pre-monsoon season with extreme temperature, scarce precipitation, long sunshine duration, lowest relative humidity, low pressure, and calm winds and chilly condition. Furthermore, during cold (0.1mm), pre-monsoon (3.5mm), and monsoon season (2.2mm) the evapotranspiration shows an increase, where as it reveals a negative deviation of -5.6mm in post monsoon season due to increase in the precipitation from reversible monsoon lows at the southern latitudes of the country. Generally, the evapotranspiration of Pakistan increases from northwest to southeast and a main agent of delimitation of the arid region of the country. The main factors that cause variation in the evapotranspiration of the country from south towards north are temperature, precipitation, sunshine duration, relative humidity, surface pressure, wind speed, fogs, cloudiness, topography, latitudinal and altitudinal extend of the country that required further research.

scholarly journals Intercomparison review of IPWV retrieved from INSAT-3DR sounder, GNSS and CAMS reanalysis data

2021 ◽  
Vol 14 (7) ◽  
pp. 4857-4877
Author(s):  
Ramashray Yadav ◽  
Ram Kumar Giri ◽  
Virendra Singh
Keyword(s):  
Water Vapor ◽  
Monsoon Season ◽  
Winter Season ◽  
Precipitable Water ◽  
Satellite System ◽  
Reanalysis Data ◽  
Regional Variability ◽  
Post Monsoon ◽  
Post Monsoon Season ◽  
Gnss Data

Abstract. The spatiotemporal variations of integrated precipitable water vapor (IPWV) are very important in understanding the regional variability of water vapor. Traditional in situ measurements of IPWV in the Indian region are limited, and therefore the performance of satellite and Copernicus Atmosphere Meteorological Service (CAMS) retrievals with the Indian Global Navigation Satellite System (GNSS) as reference were analyzed. In this study the CAMS reanalysis data of 1 year (2018) and the Indian GNSS and INSAT-3DR sounder retrieval data for 1.5 years (January 2017 to June 2018) were utilized, and statistics were computed. It is noticed that seasonal correlation coefficient (CC) values between INSAT-3DR and Indian GNSS data mainly lie within the range of 0.50 to 0.98 for all the selected 19 stations except Thiruvananthapuram (0.1), Kanyakumari (0.31) and Karaikal (0.15) during the monsoon season and Panjim (0.2) during the post-monsoon season. The seasonal CC values between CAMS and GNSS IPWV range from 0.73 to .99 except for Jaipur (0.16) and Bhubaneswar (0.29) during the pre-monsoon season, Panjim (0.38) during the monsoon season, Nagpur (0.50) during the post-monsoon season, and Dibrugarh (0.49) Jaipur (0.58) and Bhubaneswar (0.16) during the winter season. The root mean square error (RMSE) values are higher under the wet conditions (pre-monsoon and monsoon season) than under dry conditions (post-monsoon and winter season), and we found differences in magnitude and sign of bias for INSAT-3DR and CAMS with respect to GNSS IPWV from station to station and season to season. This study will help to improve understanding and utilization of CAMS and INSAT-3DR data more effectively along with GNSS data over land, coastal and desert locations in terms of the seasonal flow of IPWV, which is an essential integrated variable in forecasting applications.

scholarly journals Evaluation of TRMM Precipitation Dataset over Himalayan Catchment: The Upper Ganga Basin, India

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 613 ◽  
Author(s):  
Anoop Shukla ◽  
Chandra Ojha ◽  
Rajendra Singh ◽  
Lalit Pal ◽  
Dafang Fu
Keyword(s):  
Spatial Distribution ◽  
Lake Victoria ◽  
Monsoon Season ◽  
Winter Season ◽  
India Meteorological Department ◽  
Statistical Parameters ◽  
Ganga Basin ◽  
Dual Nature ◽  
Post Monsoon ◽  
Trmm Precipitation

Satellite based rainfall estimation techniques have emerged as a potential alternative to ground based rainfall measurements. The Tropical Rainfall Measuring Mission (TRMM) precipitation, in particular, has been used in various climate and hydrology based studies around the world. While having wide possibilities, TRMM rainfall estimates are found to be inconsistent with the ground based rainfall measurements at various locations such as the southwest coast and Himalayan region of India, northeast parts of USA, Lake Victoria in Africa, La Plata basin in South America, etc. In this study, the applicability of TRMM estimates is evaluated over the Upper Ganga Basin (Himalayan catchment) by comparing against gauge-based India Meteorological Department (IMD) gridded precipitation records. Apart from temporal evaluation, the ability of TRMM in capturing spatial distribution is also examined using three statistical parameters namely correlation coefficient (r), mean absolute error (MAE) and relative bias (RBIAS). In the results, the dual nature of bias is evident in TRMM precipitation with rainfall magnitude falling in the range from 100 to 370 mm representing positive bias, whereas, rainfall magnitude above 400 mm, approximately, representing negative bias. The Quantile Mapping (QM) approach has been used to correct the TRMM dataset from these biases. The raw TRMM precipitation is found to be fairly correlated with IMD rainfall for post-monsoon and winter season with R2 values of 0.65 and 0.57, respectively. The R2 value of 0.41 is obtained for the monsoon season, whereas least correlation is found for the pre-monsoon season with an R2 value of 0.24. Moreover, spatial distribution of rainfall during post-monsoon and winter season is captured adequately; however, the limited efficiency of TRMM is reflected for pre-monsoon and monsoon season. Bias correction has satisfactorily enhanced the spatial distribution of rainfall obtained from TRMM for almost all the seasons except for monsoon. Overall, the corrected TRMM precipitation dataset can be used for various climate analyses and hydrological water balance based studies in the Himalayan river basins.

Sign in / Sign up

Export Citation Format

Share Document