SlideShare a Scribd company logo
1 of 7
Download to read offline
International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 5, Sep – Oct 2019
Available at www.ijsred.com
ISSN : 2581-7175 ©IJSRED: All Rights are Reserved Page 348
Analysis of 20 Years Rainfall Data from 1999 to
2018 in Badulla District: A Case Study
N. R. A. M. Ruwangika*, C. N. Hettiarachchi**, G. M. L. P. Aponsu***
(*Department of Physical Sciences and Technology, Faculty of Applied Sciences, Sabaragamuwa University of Sri Lanka.
Email: ruwangika.@appsc.sab.ac.lk)
(** Center for Computer Studies, Sabaragamuwa University of Sri Lanka.
Email :chathurani.@appsc.sab.ac.lk)
(***Department of Physical Sciences and Technology, Faculty of Applied Sciences, Sabaragamuwa University of Sri Lanka.
Email: aponsul@appsc.sab.ac.lk)
----------------------------------------************************----------------------------------
Abstract:
The Climate in Sri Lanka is tropical and consists of very characteristic in dry and wet seasons. As
compared with the land area of Sri Lanka, Badulla district covers 4.4 %. Badulla district is a capital city of
Uva province and it consists of 15 AGA divisions and 1960 villages. Badulla district is an agricultural
district where vegetables, tea, fruits, and paddy are cultivated. The district has been separated into two
portions as Upper region and Lower region considering the climatic and geographical features. The upper
region of the district is eminent for tea plantation and vegetable cultivation while the lower region is
famous for paddy agriculture. Changing climate is an uncountable cause of worry for all over the world
especially rain-fed developing country. The fluctuated rainfall pattern harmfully affects their crops. The
attempt was made to study the variation of monthly, seasonal and annual rainfall over Badulla district of
Sri Lanka during twenty years’ period from 1999 to 2018. Annual rainfall trends over the Badulla District
showed the increasing trends of about 15.8 mm/Year. Near about 12 years (60 %) shows annual rainfall
less than that of mean annual rainfall and 08 years (40 %) show annual rainfall more that of mean annual
rainfall. First Inter-Monsoon Season (March-April), Southwest-monsoon Season (May-September) and
Second Inter-Monsoon Season (October-November) rainfall trends show the decreasing rainfall trends
while Northeast-Monsoon Season (December-February) rainfall trends shows the increasing rainfall trend.
Keywords —Rainfall, Annual, Seasonal, Monthly, Rainfall trends
----------------------------------------************************----------------------------------
I. INTRODUCTION
Water is one of the most important substances on
the Earth. It is vigorous for life process of while it
is a basis of power for living being. There is no
substitute for it. Beyond above, water serves many
other useful purposes for domestic consumption,
agriculture, industry and so on. The main vital
source of water in World is the rain which has a
dramatic consequence mainly on agriculture.
Vegetations get their water supply from natural
sources as well as through the irrigation. The yield
of crops in rainfed areas depends mainly on the
rainfall pattern. The studying of these patterns is
very important. It makes significant to predict the
probability of amount of rainfall based on the past
records of hydrological data using statistical
analysis. By appropriating a frequency distribution
to the set of rainfall data, the probability of
incidences of random parameter can be calculated.
RESEARCH ARTICLE OPEN ACCESS
International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 5, Sep – Oct 2019
Available at www.ijsred.com
ISSN : 2581-7175 ©IJSRED: All Rights are Reserved Page 349
II. STUDY AREA
The present study is carried out at Badulla district
(Fig.1) located in Uva province. The region has a
latitude and longitude of 6.9934° N and 81.0550° E,
respectively and Elevation is 670 m. Agriculture is
the main occupation in this area and almost
encircled by the BaduluOya River. This area is
surrounded by tea plantations and also includes
paddy, rubber, banana and vegetables. In Badulla
district, it receives rainfall from Inter, northeast and
southwest Monsoons. The daily rainfall data is
collected from the Meteorological Department of
Sri Lanka, for a period of 20 years from 1999 to
2018. These data is used for the Annual, Monthly
and Seasonal Rainfall data analysis.
Fig. 1Location map of the study area
III. DATA AND METHODOLOGY
The daily rainfall measured in millimetre (mm) of
Badulla district for a period of twenty years from
1999 to 2018 was collected from Metrological
Department of Sri Lanka because this study was
performed separately for annual, seasonal and
monthly rainfall. The monthly rainfall was
calculated by taking the total of daily rainfall of the
particular month while seasonal and annual rainfall
were calculated by taking the total of monthly
rainfalls of the particular season and seasonal
rainfalls for the particular year, respectively. And
finally, average values of each three parameters for
the said period were calculated. First Inter-
Monsoon Season (March-April), Southwest-
Monsoon Season (May-September), Second Inter-
Monsoon Season (October-November) and
Northeast-Monsoon Season (December-February)
time series of all parameters under study rainfall are
prepared and analyzing of data were done using
Minitab software.
The Mean, Standard Deviation (St. Dev),
Variance, Coefficient of Variation (Coef. Var),
Minimum, Maximum, Mean of the Squared
Successive Differences (MSSD) of the monthly,
seasonal and annual rainfall contributed for the
entire period of study (1969-2010) is computed.
IV. RAINFALL FEATURES
Rainfall characteristics of Badulla district are
shown in table 1. Annual rainfall over Badulla
district from 1999 to 2018 is 1823.9 mm with a
standard deviation 385.5 mm. The coefficient of
variation of annual rainfall for Badulla is 21.13%.
The seasonal rainfall for First Inter-Monsoon
Season (March-April), Southwest-Monsoon Season
(May- September), Second Inter-Monsoon Season
(October-November), and Northeast-Monsoon
Season (December-February) are 313.7mm, 378.0
mm, 544.7 mm, and 583.2 mm, respectively.
Maximum rainfall was observed in Northeast-
Monsoon Season which contributes near about
32.22%. First Inter-Monsoon Season, Southwest-
Monsoon Season, Second Inter-Monsoon Season
contribute nearly 17.2 %, 20.73 % and 29.86 %
respectively to annual rainfall.
The Maximum coefficient of variation was
observed in February and it is 101.64 % which
mean rainfall is more variable in February. The
Minimum coefficient of variation is observed in
November and it is 34.59% which means that
rainfall is more November. Maximum monthly
rainfall was observed in November, December,
October, January, and April are 286.00 mm,
269.85mm, 258.66 mm, 201.34 mm and 201.21 mm
respectively. November contributes highest in
monthly rainfall and it is 15.68% to the annual
rainfall. Rainfall in July (47.46 mm) is least and
contributes only 2.60 % to the annual rainfall.
International Journal of Scientific Research and Engineering Development
©IJSRED: All Rights are Reserved
TABLE I
RAINFALL CHARACTERISTICS IN MILLIMETERS (
BADULLA DISTRICT
A. Analysis of Annual Rainfall Trends
Annual rainfall trends over the Badulla District
showed the increasing trends of about 15.8
mm/Year. Near about 12 years (60 %) shows
annual rainfall less than that of mean annual
and 08 years (40 %) show annual rainfall more that
of mean annual rainfall. The maximum rainfall was
observed in 2001 and it is 2525.1 mm. The
minimum rainfall was observed in 2010 and it was
1034.7 mm. As considered with the departure of
annual rainfall from normal over Badulla,
maximum negative departure was shown in 2016
which was -789.225 mm/year. The maximum
positive departure was shown in 2011 and it was
701.175 mm/year. The minimum departure was
3.975 mm/year and it was shown in 2018. Annual
rainfall shows 21.13 mm/year coefficient of
variation from 1999 to 2018.
Variable Mean
St.D
ev
Varia
nce
Coef.
Var
Minim
um
January 201.3
132.
5
17562.
3 65.82 24.7
February 116.3
117.
5
13800.
3 100.97 17.4
March 112.5 84.8 7182.9 75.32 3.4
April 201.2
103.
1
10633.
3 51.25 35.7
May 114.4 86 7395.9 75.2 0.4
June 47.6 47.9 2295.6 100.61 2.7
July 47.46
35.6
8
1273.1
8 75.18 10.3
August 69.9 49.1 2408.3 70.24 3
September 98.7 60.7 3690.3 61.55 0.5
October 258.7
142.
5
20310.
2 55.1 60.1
November 286 98.9 9786.3 34.59 137.1
December 269.9
144.
4 20861 53.52 65
First Inter-
Monsoon Se
ason 555.9
178.
4 31825 32.09 241.7
Southwest -
monsoon Se
ason 1748 472
22239
7 26.97 1048
Second
Inter-
Monsoon Se
ason 2304 642
41176
9 27.85 1290
Northeast -
Monsoon Se
ason 4608 1283
16470
75 27.85 2579
Annual 1823.9
385.
5
14859
0.9 21.13 1034.7
International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 5, Sep
Available at www.ijsred.com
©IJSRED: All Rights are Reserved
ACTERISTICS IN MILLIMETERS (mm) OF
Annual rainfall trends over the Badulla District
showed the increasing trends of about 15.8
mm/Year. Near about 12 years (60 %) shows
annual rainfall less than that of mean annual rainfall
and 08 years (40 %) show annual rainfall more that
of mean annual rainfall. The maximum rainfall was
observed in 2001 and it is 2525.1 mm. The
minimum rainfall was observed in 2010 and it was
1034.7 mm. As considered with the departure of
ainfall from normal over Badulla,
maximum negative departure was shown in 2016
789.225 mm/year. The maximum
positive departure was shown in 2011 and it was
701.175 mm/year. The minimum departure was
3.975 mm/year and it was shown in 2018. Annual
rainfall shows 21.13 mm/year coefficient of
Fig. 2 Annual Rainfall Trend
Fig. 3 Departure of Annual Rainfall from normal
B. Seasonal Rainfall Trends
During the past 20 years, seasonal rainfall has
been considerably changed. Considering with
coefficient of variation in seasons First Inter
Monsoon season, it shows the highest variation as
32.09 mm/year and Southwest
Second Inter-Monsoon Season, Northeast
Monsoon Season shows 26.97 mm/year, 27.85
mm/year, 27.85 mm/year coefficient of variation
respectively.
First Inter-Monsoon season rainfall shows a small
increasing trend of 0.15 mm/year. The minimum
First Inter-Monsoon seasonal rainfall
2014 and maximum First Inter
rainfall was shown in 2016. The respective values
are 241.7 mm/year and 947.9 mm/year. In May to
September (Southwest-monsoon Season) shows a
comparatively high increasing trend of 14.8
mm/year. 1047.9 mm/year and 2815.3 mm/year
were shown as a minimum and maximum
202012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
2600
2400
2200
2000
1800
1600
1400
1200
1000
Year
Rainfall(mm)
Annual Rainf
Linear Trend Mo
Yt = 1658 + 15.Maxim
um
MSS
D
579.7
20812
.2
538
14747
.7
355.1
7503.
9
406.4 10843
309.4
6703.
9
188.8
3022.
3
162.6
1750.
72
186.7
2401.
6
229.6
4272.
9
508.5
20433
.6
470
11867
.1
669.5
25388
.2
947.9
34845
.7
2815
23506
5
3763
44387
2
7526
17754
89
2525.1
17687
7.5
Volume 2 Issue 5, Sep – Oct 2019
www.ijsred.com
Page 350
Rainfall Trend
Departure of Annual Rainfall from normal
During the past 20 years, seasonal rainfall has
been considerably changed. Considering with
coefficient of variation in seasons First Inter-
Monsoon season, it shows the highest variation as
32.09 mm/year and Southwest-Monsoon Season,
eason, Northeast -
Monsoon Season shows 26.97 mm/year, 27.85
mm/year, 27.85 mm/year coefficient of variation
Monsoon season rainfall shows a small
increasing trend of 0.15 mm/year. The minimum
Monsoon seasonal rainfall was shown in
2014 and maximum First Inter-Monsoon seasonal
rainfall was shown in 2016. The respective values
are 241.7 mm/year and 947.9 mm/year. In May to
monsoon Season) shows a
comparatively high increasing trend of 14.8
047.9 mm/year and 2815.3 mm/year
were shown as a minimum and maximum
2018
2017
2016
2015
2014
201312
MAPE 17
MAD 288
MSD 132904
Accuracy Measures
Actual
Fits
Variable
fall
odel
.8×t
International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 5, Sep – Oct 2019
Available at www.ijsred.com
ISSN : 2581-7175 ©IJSRED: All Rights are Reserved Page 351
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
3000
2500
2000
1500
1000
MAPE 21
MAD 353
MSD 203982
Accuracy Measures
Year
Southwest-monsoonSeason
Actual
Fits
Variable
Southwest -monsoon Season
Linear Trend Model
Yt = 1593 + 14.8×t
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1000
900
800
700
600
500
400
300
200
MAPE 29.5
MAD 135.3
MSD 30233.1
Accuracy Measures
Year
FirstInter-monsoonSeason
Actual
Fits
Variable
First Inter-monsoon Season
Linear Trend Model
Yt = 554.3 + 0.15×t
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
4500
4000
3500
3000
2500
2000
1500
1000
MAPE 32
MAD 617
MSD 623962
Accuracy Measures
Year
SecondInter-monsoonSeason
Actual
Fits
Variable
Second Inter-monsoon Season
Linear Trend Model
Yt = 2146 + 15.1×t
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
10000
9000
8000
7000
6000
5000
4000
3000
2000
1000
MAPE 48
MAD 1586
MSD 4113854
Accuracy Measures
Year
Northeast-monsoonSeason
Actual
Fits
Variable
Northeast -monsoon Season
Linear Trend Model
Yt = 4136 + 45.0×t
Southwest -Monsoon Seasonal rainfalls in the year
2016 and year 2014 respectively. Long term Second
Inter-Monsoon Seasonal rainfall shows 15.1
mm/year increasing trend with a maximum in 2014
and minimum in 1016 as 4155.25 mm/year and
947.44 mm/year respectively. Northeast -Monsoon
Season in December to February shows a
comparatively very high increasing trend with 45.0
mm/year rainfall. The maximum Northeast -
Monsoon Seasonal rainfall was shown in 2014 as
9377.43 mm/ year and the minimum was shown in
2016 as 1250.42 mm/year.
Fig. 4 FirstInter-Monsoon Season Rainfall Trend
Fig. 5 Southwest -Monsoon Season Rainfalls
Fig. 6 Second Inter-Monsoon Season Rainfall
Fig. 7 Northeast -Monsoon Season Rainfall Trend
C. Monthly Rainfall Trends
Characteristics of monthly rainfall over Badulla
have been calculated for individual months by
fitting them to the linear trends. Maximum monthly
rainfall was observed for November, December and
October and they were 5173.1 mm, 5397 mm and
5720.1 mm respectively. The minimum monthly
rainfall was observed in July, June and August and
they were 949.2 mm, 952.4 mm and 1397.3 mm
correspondingly.
Analysing the fitted linear trends, four months
(33.33%) shows the decreasing monthly rainfall
trend and eight months (66.66%) shows the
increasing monthly rainfall trends. The negative
maximum monthly rainfall trends were shown in
International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 5, Sep – Oct 2019
Available at www.ijsred.com
ISSN : 2581-7175 ©IJSRED: All Rights are Reserved Page 352
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
600
500
400
300
200
100
0
MAPE 81.6
MAD 86.7
MSD 15300.9
Accuracy Measures
Year
january
Actual
Fits
Variable
january
Linear Trend Model
Yt = 269.1 - 6.45×t
January and November. The minimum negative
rainfall trend was shown in September and it was -
0.66. Within the other Eight months May and
October shows maximum positive monthly rainfall
trends, respectively given by 8.15 mm and 6.35 mm.
For monthly rainfall, maximum coefficient of
variation was observed for February and June and
they were 100.97 % and 100.61 % respectively and
minimum coefficient of variation was observed for
November and it was 34.59 %. This means that
monthly rainfall was more variable in February and
June it is more stable in November.
Fig. 8 January Rainfall Trend
Fig. 9 February Rainfall Trend
Fig. 10MarchRainfall Trend
Fig. 11AprilRainfall Trend
Fig. 12 MayRainfall Trend
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
400
300
200
100
0
MAPE 202.84
MAD 58.86
MSD 6372.59
Accuracy Measures
Year
march
Actual
Fits
Variable
March
Linear Trend Model
Yt = 73.8 + 3.68×t
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
400
300
200
100
0
MAPE 80.24
MAD 78.74
MSD 9952.04
Accuracy Measures
Year
April
Actual
Fits
Variable
April
Linear Trend Model
Yt = 178.9 + 2.12×t
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
350
300
250
200
150
100
50
0
MAPE 1841.75
MAD 58.48
MSD 4815.90
Accuracy Measures
Year
May
Actual
Fits
Variable
May
Linear Trend Model
Yt = 28.8 + 8.15×t
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
600
500
400
300
200
100
0
MAPE 109.5
MAD 76.9
MSD 13009.7
Accuracy Measures
Year
february
Actual
Fits
Variable
february
Linear Trend Model
Yt = 98.1 + 1.74×t
International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 5, Sep – Oct 2019
Available at www.ijsred.com
©IJSRED: All Rights are Reserved Page 353
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
200
150
100
50
0
MAPE 269.95
MAD 34.54
MSD 2149.22
Accuracy Measures
Year
August
Actual
Fits
Variable
August
Linear Trend Model
Yt = 91.3 - 2.04×t
Fig. 13 JuneRainfall Trend
Fig. 14 JulyRainfall Trend
Fig. 15 AugustRainfall Trend
Fig. 16September Rainfall Trend
Fig. 17October Rainfall Trend
Fig. 18 November Rainfall Trend
Fig. 19 DecemberRainfall Trend
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
200
150
100
50
0
MAPE 261.94
MAD 35.10
MSD 2113.54
Accuracy Measures
Year
June
Actual
Fits
Variable
June
Linear Trend Model
Yt = 32.7 + 1.42×t
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
180
160
140
120
100
80
60
40
20
0
MAPE 93.75
MAD 27.93
MSD 1153.60
Accuracy Measures
Year
July
Actual
Fits
Variable
July
Linear Trend Model
Yt = 33.8 + 1.30×t
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
250
200
150
100
50
0
MAPE 1032.19
MAD 47.11
MSD 3491.20
Accuracy Measures
Year
september
Actual
Fits
Variable
September Rainfall Trend
Linear Trend Model
Yt = 105.7 - 0.66×t
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
500
400
300
200
100
0
MAPE 69.9
MAD 107.5
MSD 17954.0
Accuracy Measures
Year
October
Actual
Fits
Variable
October
Linear Trend Model
Yt = 192.0 + 6.35×t
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
500
400
300
200
100
MAPE 30.45
MAD 78.69
MSD 8916.59
Accuracy Measures
Year
November
Actual
Fits
Variable
November
Linear Trend Model
Yt = 321.5 - 3.38×t
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
700
600
500
400
300
200
100
0
MAPE 63.0
MAD 106.9
MSD 19403.7
Accuracy Measures
Year
December
Actual
Fits
Variable
December
Linear Trend Model
Yt = 232.8 + 3.53×t
Fig. 15 AugustRainfall Trend
International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 5, Sep – Oct 2019
Available at www.ijsred.com
ISSN : 2581-7175 ©IJSRED: All Rights are Reserved Page 354
V. CONCLUSIONS
The aim of the present study was to identify rainfall
trends for the period of 1999 to 2018 over Badulla
district. Annual rainfall trends showed a
significantly increasing trend of about 15.8
mm/Year. Near about 12 years (60 %) shows
annual rainfall less than that of mean annual rainfall
and 08 years (40 %) show annual rainfall more that
of mean annual rainfall. The maximum rainfall was
observed in 2001 and it is 2525.1 mm and
minimum rainfall was observed in 2010 and it was
1034.7 mm.
The minimum First Inter-Monsoon seasonal rainfall
was shown in 2014 and maximum First Inter-
Monsoon seasonal rainfall was shown in 2016. The
respective values are 241.7 mm/year and 947.9
mm/year.
In May to September (Southwest-Monsoon season)
shows a comparatively high increasing trend of
14.8 mm/year. 1047.9 mm/year and 2815.3mm/year
were shown as minimum and maximum Southwest-
monsoon seasonal rainfalls in the year 2016 and
year 2014 respectively.
Long term Second Inter-Monsoon seasonal rainfall
shows 15.1 mm/year increasing trend with a
maximum in 2014 and minimum in 1016 as
4155.25 mm/year and 947.44 mm/year respectively.
Northeast-Monsoon Season in December to
February shows a comparatively very high
increasing trend with 45.0 mm/year rainfall. The
maximum Northeast-Monsoon seasonal rainfall was
shown in 2014 as 9377.43 mm/ year and the
minimum was shown in 2016 as 1250.42 mm/year.
Characteristics of monthly rainfall over Badulla
have been calculated for individual months by
fitting them to the linear trends. Maximum monthly
rainfall was observed for November, December and
October and they were 5173.1 mm, 5397 mm and
5720.1 mm respectively. The minimum monthly
rainfall was observed in July, June and August and
they were 949.2 mm, 952.4 mm and 1397.3 mm
correspondingly.
Analyzing the fitted linear trends, four months
(33.33%) shows the decreasing monthly rainfall
trend and eight Months (66.66%) shows the
increasing monthly rainfall trends. The negative
maximum monthly rainfall trends were shown in
January and November. The minimum negative
rainfall trend was shown in September and it was -
0.66. Within the other, eight months May and
October shows maximum positive monthly rainfall
trends, respectively given by 8.15 mm and 6.35
mm.
REFERENCES
[1] Adger WN, Hug S, Brown K, Conway D, Hulme M (2003). Adaptation
to climate change in the developing world. Proc. Dev. Stud., 3(3): 179-
195.
[2] Akinremi, O.O., McGinn, S.M., Cutforth, H.W., 2001. Seasonal and
spatial patterns of rainfall trends on the Canadian prairies. Journal of
Climate 14 (9), 2177– 2182.
[3] Anser Khan, SoumenduChatterjee, DipakBisai and NilayKanti
Barman (2014) Analysis of change point in surface temperature time
series using cumulative sum chart and bootstrapping for Asansol
weather observation station, west Bengal, India American journal on
climate change Vol. 3 pp. 83-94.
[4] Dr. Avinash Kadam, Kailas Karnewar (2016), Analysis of monthly
and seasonal temperature trends of Nanded., July 2016., Indian stream
research journal vol.6 no.6 pp ;1-9 . Available online at isrj.in
[5] Frich P, Alexander LV, Della-Marta P, Gleason B, Haylock M, Klein
Tank AMG, Peterson T (2002). Observed coherent changes in climatic
extremes during the second half of twentieth century. Clim. Res., 19:
193-212.
[6] Guhathakurta, P., Rajeevan, M., 2007. Trends in the rainfall pattern
over India. International Journal of Climatology 28 (11), 1453–1469.
doi:10.1002/joc.1640.Available from:www.intersciences.wiley.com
(2002) The IEEE website. [Online]. Available: http://www.ieee.org/
[7] Intergovernmental panel on climate change (2007) The physical
science basis: in contribution of working group 1 to the fourth
assessment report of the Intergovernmental panel on climate change
(eds) Soloma. 18.
[8] Jagannathan, P., Bhalme, H.N., 1973. Changes in pattern of
distribution of southwest monsoon rainfall over India associated with
sunspots. Monthly Weather Review 101, 691–700.
[9] Jayawardene HKWI, Sonnadara DUJ, Jayewardene DR (2005). Trends
of Rainfall in Sri Lanka over the Last Century. Sri Lankan J. Phys., 6:
7-17
[10] Karnewar Kailas and Avinash Kadam (2015) “a” Study of Temperature
Trends of Nanded, Maharashtra, India. World Rural Observ;7(2):30-35.
[11] Karnewar Kailas and Avinash Kadam (2016) “b” Trends of monthly
and seasonal temperature of Nanded, International Journal of Research
in Social Sciences; 6 (9) :90-102.
[12] koteswaram, P., Alvi, S.M.A.,1969. Secular trends and periodicities in
rainfall at west coast stations in India. Current Science 101, 371–375
[13] Murphy, Bradley F, Timbal, Bertrand, 2007. A review of recent
climate variability and climate change in southeastern Australia.
International Journal of Clima-tology.doi:10.1002/joc.1627 Available
from:www.interscience.wiley.com
[14] Naidu, C.V., Srinivasa Rao, B.R., Bhaskar Rao, D.V., 1999. Climatic
trends and periodicities of annual rainfall over India. Meteorological
Application 6, 395– 404.
[15] Nicholls, Neville, Lavery, Beth, 2006. Australian rainfall trends during
the twentieth century. International Journal of Climatology 12 (2),
153–163. doi:10.1002/ joc.3370120204. Available from:
www.interscience.wiley.com

More Related Content

What's hot

Hydroclimatological assessment of Jawi River Basin, Malaysia
Hydroclimatological assessment of Jawi River Basin, MalaysiaHydroclimatological assessment of Jawi River Basin, Malaysia
Hydroclimatological assessment of Jawi River Basin, Malaysia
ijtsrd
 

What's hot (6)

Hydroclimatological assessment of Jawi River Basin, Malaysia
Hydroclimatological assessment of Jawi River Basin, MalaysiaHydroclimatological assessment of Jawi River Basin, Malaysia
Hydroclimatological assessment of Jawi River Basin, Malaysia
 
Indian Economy Rainfall Project
Indian Economy Rainfall ProjectIndian Economy Rainfall Project
Indian Economy Rainfall Project
 
South american monsoon-time_scale
South american monsoon-time_scaleSouth american monsoon-time_scale
South american monsoon-time_scale
 
North american monsoon_time_scale
North american monsoon_time_scaleNorth american monsoon_time_scale
North american monsoon_time_scale
 
1a.iscale.nl.basic
1a.iscale.nl.basic1a.iscale.nl.basic
1a.iscale.nl.basic
 
Analysis of Monthly Rainfall Trend over the Mahanadi Basin in Kesinga Station
Analysis of Monthly Rainfall Trend over the Mahanadi Basin in Kesinga StationAnalysis of Monthly Rainfall Trend over the Mahanadi Basin in Kesinga Station
Analysis of Monthly Rainfall Trend over the Mahanadi Basin in Kesinga Station
 

Similar to IJSRED-V2I5P27

Understanding the Kerala Floods of 2018: Role of Mixed Rossby-Gravity Waves
Understanding the Kerala Floods of 2018: Role of Mixed Rossby-Gravity WavesUnderstanding the Kerala Floods of 2018: Role of Mixed Rossby-Gravity Waves
Understanding the Kerala Floods of 2018: Role of Mixed Rossby-Gravity Waves
S Kiran
 
29 report spatial_temporal_distribution_of_temperature_crop_agriculture_full
29 report spatial_temporal_distribution_of_temperature_crop_agriculture_full29 report spatial_temporal_distribution_of_temperature_crop_agriculture_full
29 report spatial_temporal_distribution_of_temperature_crop_agriculture_full
caltec
 
Towards Climate Change Resilient of Hail Haor, Sylhet: Reviewing the Role of ...
Towards Climate Change Resilient of Hail Haor, Sylhet: Reviewing the Role of ...Towards Climate Change Resilient of Hail Haor, Sylhet: Reviewing the Role of ...
Towards Climate Change Resilient of Hail Haor, Sylhet: Reviewing the Role of ...
IOSR Journals
 
3 ijsrmss-02686-paid
3 ijsrmss-02686-paid3 ijsrmss-02686-paid
3 ijsrmss-02686-paid
Mohammed Badiuddin Parvez
 
Natural disasters vulnerability assessment of gondia district, maharashtra, i...
Natural disasters vulnerability assessment of gondia district, maharashtra, i...Natural disasters vulnerability assessment of gondia district, maharashtra, i...
Natural disasters vulnerability assessment of gondia district, maharashtra, i...
eSAT Publishing House
 

Similar to IJSRED-V2I5P27 (20)

Analysis of rainfall trends in akwa ibom state, nigeria
Analysis of rainfall trends in akwa ibom state, nigeriaAnalysis of rainfall trends in akwa ibom state, nigeria
Analysis of rainfall trends in akwa ibom state, nigeria
 
Rainfall Trends and Variability in Tamil Nadu (1983 - 2012): Indicator of Cli...
Rainfall Trends and Variability in Tamil Nadu (1983 - 2012): Indicator of Cli...Rainfall Trends and Variability in Tamil Nadu (1983 - 2012): Indicator of Cli...
Rainfall Trends and Variability in Tamil Nadu (1983 - 2012): Indicator of Cli...
 
4 wajes-02828
4 wajes-028284 wajes-02828
4 wajes-02828
 
Climate and Consumption Pattern -Demand and Supply of Water District concessi...
Climate and Consumption Pattern -Demand and Supply of Water District concessi...Climate and Consumption Pattern -Demand and Supply of Water District concessi...
Climate and Consumption Pattern -Demand and Supply of Water District concessi...
 
Understanding the Kerala Floods of 2018: Role of Mixed Rossby-Gravity Waves
Understanding the Kerala Floods of 2018: Role of Mixed Rossby-Gravity WavesUnderstanding the Kerala Floods of 2018: Role of Mixed Rossby-Gravity Waves
Understanding the Kerala Floods of 2018: Role of Mixed Rossby-Gravity Waves
 
29 report spatial_temporal_distribution_of_temperature_crop_agriculture_full
29 report spatial_temporal_distribution_of_temperature_crop_agriculture_full29 report spatial_temporal_distribution_of_temperature_crop_agriculture_full
29 report spatial_temporal_distribution_of_temperature_crop_agriculture_full
 
monther,+5049-Article-Text-15067-1-6-20190816.pdf
monther,+5049-Article-Text-15067-1-6-20190816.pdfmonther,+5049-Article-Text-15067-1-6-20190816.pdf
monther,+5049-Article-Text-15067-1-6-20190816.pdf
 
F2113444
F2113444F2113444
F2113444
 
ANALYSIS ON INTERDEPENDENCE OF WEATHER PARAMETERS USING SPSS SOFTWARE
ANALYSIS ON INTERDEPENDENCE OF WEATHER PARAMETERS USING SPSS SOFTWAREANALYSIS ON INTERDEPENDENCE OF WEATHER PARAMETERS USING SPSS SOFTWARE
ANALYSIS ON INTERDEPENDENCE OF WEATHER PARAMETERS USING SPSS SOFTWARE
 
Sanogo paris2015-poster
Sanogo paris2015-posterSanogo paris2015-poster
Sanogo paris2015-poster
 
Analysis of rainfall intensity of kunigal taluk, tumkur district, karnataka u...
Analysis of rainfall intensity of kunigal taluk, tumkur district, karnataka u...Analysis of rainfall intensity of kunigal taluk, tumkur district, karnataka u...
Analysis of rainfall intensity of kunigal taluk, tumkur district, karnataka u...
 
Generation of intensity_duration_frequency_curves_for manvi taluk raichur dis...
Generation of intensity_duration_frequency_curves_for manvi taluk raichur dis...Generation of intensity_duration_frequency_curves_for manvi taluk raichur dis...
Generation of intensity_duration_frequency_curves_for manvi taluk raichur dis...
 
Towards Climate Change Resilient of Hail Haor, Sylhet: Reviewing the Role of ...
Towards Climate Change Resilient of Hail Haor, Sylhet: Reviewing the Role of ...Towards Climate Change Resilient of Hail Haor, Sylhet: Reviewing the Role of ...
Towards Climate Change Resilient of Hail Haor, Sylhet: Reviewing the Role of ...
 
Heavy rainfall northeast india
Heavy rainfall northeast indiaHeavy rainfall northeast india
Heavy rainfall northeast india
 
3 ijsrmss-02686-paid
3 ijsrmss-02686-paid3 ijsrmss-02686-paid
3 ijsrmss-02686-paid
 
Floods in sri lanka
Floods in sri lankaFloods in sri lanka
Floods in sri lanka
 
Climate Change Events in Myanmar and Future Scenarios mod
Climate Change Events in Myanmar and Future Scenarios  modClimate Change Events in Myanmar and Future Scenarios  mod
Climate Change Events in Myanmar and Future Scenarios mod
 
Predicting Meteorological Drought in Iraq: An Evaluation of Machine Learning ...
Predicting Meteorological Drought in Iraq: An Evaluation of Machine Learning ...Predicting Meteorological Drought in Iraq: An Evaluation of Machine Learning ...
Predicting Meteorological Drought in Iraq: An Evaluation of Machine Learning ...
 
Natural disasters vulnerability assessment of gondia district, maharashtra, i...
Natural disasters vulnerability assessment of gondia district, maharashtra, i...Natural disasters vulnerability assessment of gondia district, maharashtra, i...
Natural disasters vulnerability assessment of gondia district, maharashtra, i...
 
Lesson 2- Traditional Agriculture: agriculture, climate and soil
Lesson 2- Traditional Agriculture: agriculture, climate and soilLesson 2- Traditional Agriculture: agriculture, climate and soil
Lesson 2- Traditional Agriculture: agriculture, climate and soil
 

More from IJSRED

BigBasket encashing the Demonetisation: A big opportunity
BigBasket encashing the Demonetisation: A big opportunityBigBasket encashing the Demonetisation: A big opportunity
BigBasket encashing the Demonetisation: A big opportunity
IJSRED
 
Quantitative and Qualitative Analysis of Plant Leaf Disease
Quantitative and Qualitative Analysis of Plant Leaf DiseaseQuantitative and Qualitative Analysis of Plant Leaf Disease
Quantitative and Qualitative Analysis of Plant Leaf Disease
IJSRED
 
DC Fast Charger and Battery Management System for Electric Vehicles
DC Fast Charger and Battery Management System for Electric VehiclesDC Fast Charger and Battery Management System for Electric Vehicles
DC Fast Charger and Battery Management System for Electric Vehicles
IJSRED
 
Parallelization of Graceful Labeling Using Open MP
Parallelization of Graceful Labeling Using Open MPParallelization of Graceful Labeling Using Open MP
Parallelization of Graceful Labeling Using Open MP
IJSRED
 
Study of Phenotypic Plasticity of Fruits of Luffa Acutangula Var. Amara
Study of Phenotypic Plasticity of  Fruits of Luffa Acutangula Var. AmaraStudy of Phenotypic Plasticity of  Fruits of Luffa Acutangula Var. Amara
Study of Phenotypic Plasticity of Fruits of Luffa Acutangula Var. Amara
IJSRED
 
An Emperical Study of Learning How Soft Skills is Essential for Management St...
An Emperical Study of Learning How Soft Skills is Essential for Management St...An Emperical Study of Learning How Soft Skills is Essential for Management St...
An Emperical Study of Learning How Soft Skills is Essential for Management St...
IJSRED
 
Impacts of a New Spatial Variable on a Black Hole Metric Solution
Impacts of a New Spatial Variable on a Black Hole Metric SolutionImpacts of a New Spatial Variable on a Black Hole Metric Solution
Impacts of a New Spatial Variable on a Black Hole Metric Solution
IJSRED
 
A Study to Assess the Effectiveness of Planned Teaching Programme on Knowledg...
A Study to Assess the Effectiveness of Planned Teaching Programme on Knowledg...A Study to Assess the Effectiveness of Planned Teaching Programme on Knowledg...
A Study to Assess the Effectiveness of Planned Teaching Programme on Knowledg...
IJSRED
 
Functions of Forensic Engineering Investigator in India
Functions of Forensic Engineering Investigator in IndiaFunctions of Forensic Engineering Investigator in India
Functions of Forensic Engineering Investigator in India
IJSRED
 
Participation Politique Feminine En Competition Électorale Au Congo-Kinshasa....
Participation Politique Feminine En Competition Électorale Au Congo-Kinshasa....Participation Politique Feminine En Competition Électorale Au Congo-Kinshasa....
Participation Politique Feminine En Competition Électorale Au Congo-Kinshasa....
IJSRED
 

More from IJSRED (20)

IJSRED-V3I6P13
IJSRED-V3I6P13IJSRED-V3I6P13
IJSRED-V3I6P13
 
School Bus Tracking and Security System
School Bus Tracking and Security SystemSchool Bus Tracking and Security System
School Bus Tracking and Security System
 
BigBasket encashing the Demonetisation: A big opportunity
BigBasket encashing the Demonetisation: A big opportunityBigBasket encashing the Demonetisation: A big opportunity
BigBasket encashing the Demonetisation: A big opportunity
 
Quantitative and Qualitative Analysis of Plant Leaf Disease
Quantitative and Qualitative Analysis of Plant Leaf DiseaseQuantitative and Qualitative Analysis of Plant Leaf Disease
Quantitative and Qualitative Analysis of Plant Leaf Disease
 
DC Fast Charger and Battery Management System for Electric Vehicles
DC Fast Charger and Battery Management System for Electric VehiclesDC Fast Charger and Battery Management System for Electric Vehicles
DC Fast Charger and Battery Management System for Electric Vehicles
 
Growth Path Followed by France
Growth Path Followed by FranceGrowth Path Followed by France
Growth Path Followed by France
 
Acquisition System
Acquisition SystemAcquisition System
Acquisition System
 
Parallelization of Graceful Labeling Using Open MP
Parallelization of Graceful Labeling Using Open MPParallelization of Graceful Labeling Using Open MP
Parallelization of Graceful Labeling Using Open MP
 
Study of Phenotypic Plasticity of Fruits of Luffa Acutangula Var. Amara
Study of Phenotypic Plasticity of  Fruits of Luffa Acutangula Var. AmaraStudy of Phenotypic Plasticity of  Fruits of Luffa Acutangula Var. Amara
Study of Phenotypic Plasticity of Fruits of Luffa Acutangula Var. Amara
 
Understanding Architecture of Internet of Things
Understanding Architecture of Internet of ThingsUnderstanding Architecture of Internet of Things
Understanding Architecture of Internet of Things
 
Smart shopping cart
Smart shopping cartSmart shopping cart
Smart shopping cart
 
An Emperical Study of Learning How Soft Skills is Essential for Management St...
An Emperical Study of Learning How Soft Skills is Essential for Management St...An Emperical Study of Learning How Soft Skills is Essential for Management St...
An Emperical Study of Learning How Soft Skills is Essential for Management St...
 
Smart Canteen Management
Smart Canteen ManagementSmart Canteen Management
Smart Canteen Management
 
Gandhian trusteeship and Economic Ethics
Gandhian trusteeship and Economic EthicsGandhian trusteeship and Economic Ethics
Gandhian trusteeship and Economic Ethics
 
Impacts of a New Spatial Variable on a Black Hole Metric Solution
Impacts of a New Spatial Variable on a Black Hole Metric SolutionImpacts of a New Spatial Variable on a Black Hole Metric Solution
Impacts of a New Spatial Variable on a Black Hole Metric Solution
 
A Study to Assess the Effectiveness of Planned Teaching Programme on Knowledg...
A Study to Assess the Effectiveness of Planned Teaching Programme on Knowledg...A Study to Assess the Effectiveness of Planned Teaching Programme on Knowledg...
A Study to Assess the Effectiveness of Planned Teaching Programme on Knowledg...
 
Inginious Trafalgar Contrivition System
Inginious Trafalgar Contrivition SystemInginious Trafalgar Contrivition System
Inginious Trafalgar Contrivition System
 
Farmer's Analytical assistant
Farmer's Analytical assistantFarmer's Analytical assistant
Farmer's Analytical assistant
 
Functions of Forensic Engineering Investigator in India
Functions of Forensic Engineering Investigator in IndiaFunctions of Forensic Engineering Investigator in India
Functions of Forensic Engineering Investigator in India
 
Participation Politique Feminine En Competition Électorale Au Congo-Kinshasa....
Participation Politique Feminine En Competition Électorale Au Congo-Kinshasa....Participation Politique Feminine En Competition Électorale Au Congo-Kinshasa....
Participation Politique Feminine En Competition Électorale Au Congo-Kinshasa....
 

Recently uploaded

Integrated Test Rig For HTFE-25 - Neometrix
Integrated Test Rig For HTFE-25 - NeometrixIntegrated Test Rig For HTFE-25 - Neometrix
Integrated Test Rig For HTFE-25 - Neometrix
Neometrix_Engineering_Pvt_Ltd
 
Call Now ≽ 9953056974 ≼🔝 Call Girls In New Ashok Nagar ≼🔝 Delhi door step de...
Call Now ≽ 9953056974 ≼🔝 Call Girls In New Ashok Nagar  ≼🔝 Delhi door step de...Call Now ≽ 9953056974 ≼🔝 Call Girls In New Ashok Nagar  ≼🔝 Delhi door step de...
Call Now ≽ 9953056974 ≼🔝 Call Girls In New Ashok Nagar ≼🔝 Delhi door step de...
9953056974 Low Rate Call Girls In Saket, Delhi NCR
 
Standard vs Custom Battery Packs - Decoding the Power Play
Standard vs Custom Battery Packs - Decoding the Power PlayStandard vs Custom Battery Packs - Decoding the Power Play
Standard vs Custom Battery Packs - Decoding the Power Play
Epec Engineered Technologies
 
Call Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort Service
Call Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort ServiceCall Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort Service
Call Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort Service
9953056974 Low Rate Call Girls In Saket, Delhi NCR
 
Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil
Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak HamilCara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil
Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil
Cara Menggugurkan Kandungan 087776558899
 

Recently uploaded (20)

Integrated Test Rig For HTFE-25 - Neometrix
Integrated Test Rig For HTFE-25 - NeometrixIntegrated Test Rig For HTFE-25 - Neometrix
Integrated Test Rig For HTFE-25 - Neometrix
 
Block diagram reduction techniques in control systems.ppt
Block diagram reduction techniques in control systems.pptBlock diagram reduction techniques in control systems.ppt
Block diagram reduction techniques in control systems.ppt
 
(INDIRA) Call Girl Bhosari Call Now 8617697112 Bhosari Escorts 24x7
(INDIRA) Call Girl Bhosari Call Now 8617697112 Bhosari Escorts 24x7(INDIRA) Call Girl Bhosari Call Now 8617697112 Bhosari Escorts 24x7
(INDIRA) Call Girl Bhosari Call Now 8617697112 Bhosari Escorts 24x7
 
Hazard Identification (HAZID) vs. Hazard and Operability (HAZOP): A Comparati...
Hazard Identification (HAZID) vs. Hazard and Operability (HAZOP): A Comparati...Hazard Identification (HAZID) vs. Hazard and Operability (HAZOP): A Comparati...
Hazard Identification (HAZID) vs. Hazard and Operability (HAZOP): A Comparati...
 
Water Industry Process Automation & Control Monthly - April 2024
Water Industry Process Automation & Control Monthly - April 2024Water Industry Process Automation & Control Monthly - April 2024
Water Industry Process Automation & Control Monthly - April 2024
 
Call Now ≽ 9953056974 ≼🔝 Call Girls In New Ashok Nagar ≼🔝 Delhi door step de...
Call Now ≽ 9953056974 ≼🔝 Call Girls In New Ashok Nagar  ≼🔝 Delhi door step de...Call Now ≽ 9953056974 ≼🔝 Call Girls In New Ashok Nagar  ≼🔝 Delhi door step de...
Call Now ≽ 9953056974 ≼🔝 Call Girls In New Ashok Nagar ≼🔝 Delhi door step de...
 
Standard vs Custom Battery Packs - Decoding the Power Play
Standard vs Custom Battery Packs - Decoding the Power PlayStandard vs Custom Battery Packs - Decoding the Power Play
Standard vs Custom Battery Packs - Decoding the Power Play
 
Thermal Engineering-R & A / C - unit - V
Thermal Engineering-R & A / C - unit - VThermal Engineering-R & A / C - unit - V
Thermal Engineering-R & A / C - unit - V
 
Call Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort Service
Call Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort ServiceCall Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort Service
Call Girls in Ramesh Nagar Delhi 💯 Call Us 🔝9953056974 🔝 Escort Service
 
Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil
Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak HamilCara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil
Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil
 
FEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced Loads
FEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced LoadsFEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced Loads
FEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced Loads
 
chapter 5.pptx: drainage and irrigation engineering
chapter 5.pptx: drainage and irrigation engineeringchapter 5.pptx: drainage and irrigation engineering
chapter 5.pptx: drainage and irrigation engineering
 
(INDIRA) Call Girl Aurangabad Call Now 8617697112 Aurangabad Escorts 24x7
(INDIRA) Call Girl Aurangabad Call Now 8617697112 Aurangabad Escorts 24x7(INDIRA) Call Girl Aurangabad Call Now 8617697112 Aurangabad Escorts 24x7
(INDIRA) Call Girl Aurangabad Call Now 8617697112 Aurangabad Escorts 24x7
 
Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...
Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...
Call Girls Pimpri Chinchwad Call Me 7737669865 Budget Friendly No Advance Boo...
 
Work-Permit-Receiver-in-Saudi-Aramco.pptx
Work-Permit-Receiver-in-Saudi-Aramco.pptxWork-Permit-Receiver-in-Saudi-Aramco.pptx
Work-Permit-Receiver-in-Saudi-Aramco.pptx
 
Hostel management system project report..pdf
Hostel management system project report..pdfHostel management system project report..pdf
Hostel management system project report..pdf
 
University management System project report..pdf
University management System project report..pdfUniversity management System project report..pdf
University management System project report..pdf
 
Unit 2- Effective stress & Permeability.pdf
Unit 2- Effective stress & Permeability.pdfUnit 2- Effective stress & Permeability.pdf
Unit 2- Effective stress & Permeability.pdf
 
ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf
ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdfONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf
ONLINE FOOD ORDER SYSTEM PROJECT REPORT.pdf
 
Unleashing the Power of the SORA AI lastest leap
Unleashing the Power of the SORA AI lastest leapUnleashing the Power of the SORA AI lastest leap
Unleashing the Power of the SORA AI lastest leap
 

IJSRED-V2I5P27

  • 1. International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 5, Sep – Oct 2019 Available at www.ijsred.com ISSN : 2581-7175 ©IJSRED: All Rights are Reserved Page 348 Analysis of 20 Years Rainfall Data from 1999 to 2018 in Badulla District: A Case Study N. R. A. M. Ruwangika*, C. N. Hettiarachchi**, G. M. L. P. Aponsu*** (*Department of Physical Sciences and Technology, Faculty of Applied Sciences, Sabaragamuwa University of Sri Lanka. Email: ruwangika.@appsc.sab.ac.lk) (** Center for Computer Studies, Sabaragamuwa University of Sri Lanka. Email :chathurani.@appsc.sab.ac.lk) (***Department of Physical Sciences and Technology, Faculty of Applied Sciences, Sabaragamuwa University of Sri Lanka. Email: aponsul@appsc.sab.ac.lk) ----------------------------------------************************---------------------------------- Abstract: The Climate in Sri Lanka is tropical and consists of very characteristic in dry and wet seasons. As compared with the land area of Sri Lanka, Badulla district covers 4.4 %. Badulla district is a capital city of Uva province and it consists of 15 AGA divisions and 1960 villages. Badulla district is an agricultural district where vegetables, tea, fruits, and paddy are cultivated. The district has been separated into two portions as Upper region and Lower region considering the climatic and geographical features. The upper region of the district is eminent for tea plantation and vegetable cultivation while the lower region is famous for paddy agriculture. Changing climate is an uncountable cause of worry for all over the world especially rain-fed developing country. The fluctuated rainfall pattern harmfully affects their crops. The attempt was made to study the variation of monthly, seasonal and annual rainfall over Badulla district of Sri Lanka during twenty years’ period from 1999 to 2018. Annual rainfall trends over the Badulla District showed the increasing trends of about 15.8 mm/Year. Near about 12 years (60 %) shows annual rainfall less than that of mean annual rainfall and 08 years (40 %) show annual rainfall more that of mean annual rainfall. First Inter-Monsoon Season (March-April), Southwest-monsoon Season (May-September) and Second Inter-Monsoon Season (October-November) rainfall trends show the decreasing rainfall trends while Northeast-Monsoon Season (December-February) rainfall trends shows the increasing rainfall trend. Keywords —Rainfall, Annual, Seasonal, Monthly, Rainfall trends ----------------------------------------************************---------------------------------- I. INTRODUCTION Water is one of the most important substances on the Earth. It is vigorous for life process of while it is a basis of power for living being. There is no substitute for it. Beyond above, water serves many other useful purposes for domestic consumption, agriculture, industry and so on. The main vital source of water in World is the rain which has a dramatic consequence mainly on agriculture. Vegetations get their water supply from natural sources as well as through the irrigation. The yield of crops in rainfed areas depends mainly on the rainfall pattern. The studying of these patterns is very important. It makes significant to predict the probability of amount of rainfall based on the past records of hydrological data using statistical analysis. By appropriating a frequency distribution to the set of rainfall data, the probability of incidences of random parameter can be calculated. RESEARCH ARTICLE OPEN ACCESS
  • 2. International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 5, Sep – Oct 2019 Available at www.ijsred.com ISSN : 2581-7175 ©IJSRED: All Rights are Reserved Page 349 II. STUDY AREA The present study is carried out at Badulla district (Fig.1) located in Uva province. The region has a latitude and longitude of 6.9934° N and 81.0550° E, respectively and Elevation is 670 m. Agriculture is the main occupation in this area and almost encircled by the BaduluOya River. This area is surrounded by tea plantations and also includes paddy, rubber, banana and vegetables. In Badulla district, it receives rainfall from Inter, northeast and southwest Monsoons. The daily rainfall data is collected from the Meteorological Department of Sri Lanka, for a period of 20 years from 1999 to 2018. These data is used for the Annual, Monthly and Seasonal Rainfall data analysis. Fig. 1Location map of the study area III. DATA AND METHODOLOGY The daily rainfall measured in millimetre (mm) of Badulla district for a period of twenty years from 1999 to 2018 was collected from Metrological Department of Sri Lanka because this study was performed separately for annual, seasonal and monthly rainfall. The monthly rainfall was calculated by taking the total of daily rainfall of the particular month while seasonal and annual rainfall were calculated by taking the total of monthly rainfalls of the particular season and seasonal rainfalls for the particular year, respectively. And finally, average values of each three parameters for the said period were calculated. First Inter- Monsoon Season (March-April), Southwest- Monsoon Season (May-September), Second Inter- Monsoon Season (October-November) and Northeast-Monsoon Season (December-February) time series of all parameters under study rainfall are prepared and analyzing of data were done using Minitab software. The Mean, Standard Deviation (St. Dev), Variance, Coefficient of Variation (Coef. Var), Minimum, Maximum, Mean of the Squared Successive Differences (MSSD) of the monthly, seasonal and annual rainfall contributed for the entire period of study (1969-2010) is computed. IV. RAINFALL FEATURES Rainfall characteristics of Badulla district are shown in table 1. Annual rainfall over Badulla district from 1999 to 2018 is 1823.9 mm with a standard deviation 385.5 mm. The coefficient of variation of annual rainfall for Badulla is 21.13%. The seasonal rainfall for First Inter-Monsoon Season (March-April), Southwest-Monsoon Season (May- September), Second Inter-Monsoon Season (October-November), and Northeast-Monsoon Season (December-February) are 313.7mm, 378.0 mm, 544.7 mm, and 583.2 mm, respectively. Maximum rainfall was observed in Northeast- Monsoon Season which contributes near about 32.22%. First Inter-Monsoon Season, Southwest- Monsoon Season, Second Inter-Monsoon Season contribute nearly 17.2 %, 20.73 % and 29.86 % respectively to annual rainfall. The Maximum coefficient of variation was observed in February and it is 101.64 % which mean rainfall is more variable in February. The Minimum coefficient of variation is observed in November and it is 34.59% which means that rainfall is more November. Maximum monthly rainfall was observed in November, December, October, January, and April are 286.00 mm, 269.85mm, 258.66 mm, 201.34 mm and 201.21 mm respectively. November contributes highest in monthly rainfall and it is 15.68% to the annual rainfall. Rainfall in July (47.46 mm) is least and contributes only 2.60 % to the annual rainfall.
  • 3. International Journal of Scientific Research and Engineering Development ©IJSRED: All Rights are Reserved TABLE I RAINFALL CHARACTERISTICS IN MILLIMETERS ( BADULLA DISTRICT A. Analysis of Annual Rainfall Trends Annual rainfall trends over the Badulla District showed the increasing trends of about 15.8 mm/Year. Near about 12 years (60 %) shows annual rainfall less than that of mean annual and 08 years (40 %) show annual rainfall more that of mean annual rainfall. The maximum rainfall was observed in 2001 and it is 2525.1 mm. The minimum rainfall was observed in 2010 and it was 1034.7 mm. As considered with the departure of annual rainfall from normal over Badulla, maximum negative departure was shown in 2016 which was -789.225 mm/year. The maximum positive departure was shown in 2011 and it was 701.175 mm/year. The minimum departure was 3.975 mm/year and it was shown in 2018. Annual rainfall shows 21.13 mm/year coefficient of variation from 1999 to 2018. Variable Mean St.D ev Varia nce Coef. Var Minim um January 201.3 132. 5 17562. 3 65.82 24.7 February 116.3 117. 5 13800. 3 100.97 17.4 March 112.5 84.8 7182.9 75.32 3.4 April 201.2 103. 1 10633. 3 51.25 35.7 May 114.4 86 7395.9 75.2 0.4 June 47.6 47.9 2295.6 100.61 2.7 July 47.46 35.6 8 1273.1 8 75.18 10.3 August 69.9 49.1 2408.3 70.24 3 September 98.7 60.7 3690.3 61.55 0.5 October 258.7 142. 5 20310. 2 55.1 60.1 November 286 98.9 9786.3 34.59 137.1 December 269.9 144. 4 20861 53.52 65 First Inter- Monsoon Se ason 555.9 178. 4 31825 32.09 241.7 Southwest - monsoon Se ason 1748 472 22239 7 26.97 1048 Second Inter- Monsoon Se ason 2304 642 41176 9 27.85 1290 Northeast - Monsoon Se ason 4608 1283 16470 75 27.85 2579 Annual 1823.9 385. 5 14859 0.9 21.13 1034.7 International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 5, Sep Available at www.ijsred.com ©IJSRED: All Rights are Reserved ACTERISTICS IN MILLIMETERS (mm) OF Annual rainfall trends over the Badulla District showed the increasing trends of about 15.8 mm/Year. Near about 12 years (60 %) shows annual rainfall less than that of mean annual rainfall and 08 years (40 %) show annual rainfall more that of mean annual rainfall. The maximum rainfall was observed in 2001 and it is 2525.1 mm. The minimum rainfall was observed in 2010 and it was 1034.7 mm. As considered with the departure of ainfall from normal over Badulla, maximum negative departure was shown in 2016 789.225 mm/year. The maximum positive departure was shown in 2011 and it was 701.175 mm/year. The minimum departure was 3.975 mm/year and it was shown in 2018. Annual rainfall shows 21.13 mm/year coefficient of Fig. 2 Annual Rainfall Trend Fig. 3 Departure of Annual Rainfall from normal B. Seasonal Rainfall Trends During the past 20 years, seasonal rainfall has been considerably changed. Considering with coefficient of variation in seasons First Inter Monsoon season, it shows the highest variation as 32.09 mm/year and Southwest Second Inter-Monsoon Season, Northeast Monsoon Season shows 26.97 mm/year, 27.85 mm/year, 27.85 mm/year coefficient of variation respectively. First Inter-Monsoon season rainfall shows a small increasing trend of 0.15 mm/year. The minimum First Inter-Monsoon seasonal rainfall 2014 and maximum First Inter rainfall was shown in 2016. The respective values are 241.7 mm/year and 947.9 mm/year. In May to September (Southwest-monsoon Season) shows a comparatively high increasing trend of 14.8 mm/year. 1047.9 mm/year and 2815.3 mm/year were shown as a minimum and maximum 202012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 2600 2400 2200 2000 1800 1600 1400 1200 1000 Year Rainfall(mm) Annual Rainf Linear Trend Mo Yt = 1658 + 15.Maxim um MSS D 579.7 20812 .2 538 14747 .7 355.1 7503. 9 406.4 10843 309.4 6703. 9 188.8 3022. 3 162.6 1750. 72 186.7 2401. 6 229.6 4272. 9 508.5 20433 .6 470 11867 .1 669.5 25388 .2 947.9 34845 .7 2815 23506 5 3763 44387 2 7526 17754 89 2525.1 17687 7.5 Volume 2 Issue 5, Sep – Oct 2019 www.ijsred.com Page 350 Rainfall Trend Departure of Annual Rainfall from normal During the past 20 years, seasonal rainfall has been considerably changed. Considering with coefficient of variation in seasons First Inter- Monsoon season, it shows the highest variation as 32.09 mm/year and Southwest-Monsoon Season, eason, Northeast - Monsoon Season shows 26.97 mm/year, 27.85 mm/year, 27.85 mm/year coefficient of variation Monsoon season rainfall shows a small increasing trend of 0.15 mm/year. The minimum Monsoon seasonal rainfall was shown in 2014 and maximum First Inter-Monsoon seasonal rainfall was shown in 2016. The respective values are 241.7 mm/year and 947.9 mm/year. In May to monsoon Season) shows a comparatively high increasing trend of 14.8 047.9 mm/year and 2815.3 mm/year were shown as a minimum and maximum 2018 2017 2016 2015 2014 201312 MAPE 17 MAD 288 MSD 132904 Accuracy Measures Actual Fits Variable fall odel .8×t
  • 4. International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 5, Sep – Oct 2019 Available at www.ijsred.com ISSN : 2581-7175 ©IJSRED: All Rights are Reserved Page 351 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 3000 2500 2000 1500 1000 MAPE 21 MAD 353 MSD 203982 Accuracy Measures Year Southwest-monsoonSeason Actual Fits Variable Southwest -monsoon Season Linear Trend Model Yt = 1593 + 14.8×t 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1000 900 800 700 600 500 400 300 200 MAPE 29.5 MAD 135.3 MSD 30233.1 Accuracy Measures Year FirstInter-monsoonSeason Actual Fits Variable First Inter-monsoon Season Linear Trend Model Yt = 554.3 + 0.15×t 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 4500 4000 3500 3000 2500 2000 1500 1000 MAPE 32 MAD 617 MSD 623962 Accuracy Measures Year SecondInter-monsoonSeason Actual Fits Variable Second Inter-monsoon Season Linear Trend Model Yt = 2146 + 15.1×t 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 10000 9000 8000 7000 6000 5000 4000 3000 2000 1000 MAPE 48 MAD 1586 MSD 4113854 Accuracy Measures Year Northeast-monsoonSeason Actual Fits Variable Northeast -monsoon Season Linear Trend Model Yt = 4136 + 45.0×t Southwest -Monsoon Seasonal rainfalls in the year 2016 and year 2014 respectively. Long term Second Inter-Monsoon Seasonal rainfall shows 15.1 mm/year increasing trend with a maximum in 2014 and minimum in 1016 as 4155.25 mm/year and 947.44 mm/year respectively. Northeast -Monsoon Season in December to February shows a comparatively very high increasing trend with 45.0 mm/year rainfall. The maximum Northeast - Monsoon Seasonal rainfall was shown in 2014 as 9377.43 mm/ year and the minimum was shown in 2016 as 1250.42 mm/year. Fig. 4 FirstInter-Monsoon Season Rainfall Trend Fig. 5 Southwest -Monsoon Season Rainfalls Fig. 6 Second Inter-Monsoon Season Rainfall Fig. 7 Northeast -Monsoon Season Rainfall Trend C. Monthly Rainfall Trends Characteristics of monthly rainfall over Badulla have been calculated for individual months by fitting them to the linear trends. Maximum monthly rainfall was observed for November, December and October and they were 5173.1 mm, 5397 mm and 5720.1 mm respectively. The minimum monthly rainfall was observed in July, June and August and they were 949.2 mm, 952.4 mm and 1397.3 mm correspondingly. Analysing the fitted linear trends, four months (33.33%) shows the decreasing monthly rainfall trend and eight months (66.66%) shows the increasing monthly rainfall trends. The negative maximum monthly rainfall trends were shown in
  • 5. International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 5, Sep – Oct 2019 Available at www.ijsred.com ISSN : 2581-7175 ©IJSRED: All Rights are Reserved Page 352 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 600 500 400 300 200 100 0 MAPE 81.6 MAD 86.7 MSD 15300.9 Accuracy Measures Year january Actual Fits Variable january Linear Trend Model Yt = 269.1 - 6.45×t January and November. The minimum negative rainfall trend was shown in September and it was - 0.66. Within the other Eight months May and October shows maximum positive monthly rainfall trends, respectively given by 8.15 mm and 6.35 mm. For monthly rainfall, maximum coefficient of variation was observed for February and June and they were 100.97 % and 100.61 % respectively and minimum coefficient of variation was observed for November and it was 34.59 %. This means that monthly rainfall was more variable in February and June it is more stable in November. Fig. 8 January Rainfall Trend Fig. 9 February Rainfall Trend Fig. 10MarchRainfall Trend Fig. 11AprilRainfall Trend Fig. 12 MayRainfall Trend 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 400 300 200 100 0 MAPE 202.84 MAD 58.86 MSD 6372.59 Accuracy Measures Year march Actual Fits Variable March Linear Trend Model Yt = 73.8 + 3.68×t 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 400 300 200 100 0 MAPE 80.24 MAD 78.74 MSD 9952.04 Accuracy Measures Year April Actual Fits Variable April Linear Trend Model Yt = 178.9 + 2.12×t 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 350 300 250 200 150 100 50 0 MAPE 1841.75 MAD 58.48 MSD 4815.90 Accuracy Measures Year May Actual Fits Variable May Linear Trend Model Yt = 28.8 + 8.15×t 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 600 500 400 300 200 100 0 MAPE 109.5 MAD 76.9 MSD 13009.7 Accuracy Measures Year february Actual Fits Variable february Linear Trend Model Yt = 98.1 + 1.74×t
  • 6. International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 5, Sep – Oct 2019 Available at www.ijsred.com ©IJSRED: All Rights are Reserved Page 353 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 200 150 100 50 0 MAPE 269.95 MAD 34.54 MSD 2149.22 Accuracy Measures Year August Actual Fits Variable August Linear Trend Model Yt = 91.3 - 2.04×t Fig. 13 JuneRainfall Trend Fig. 14 JulyRainfall Trend Fig. 15 AugustRainfall Trend Fig. 16September Rainfall Trend Fig. 17October Rainfall Trend Fig. 18 November Rainfall Trend Fig. 19 DecemberRainfall Trend 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 200 150 100 50 0 MAPE 261.94 MAD 35.10 MSD 2113.54 Accuracy Measures Year June Actual Fits Variable June Linear Trend Model Yt = 32.7 + 1.42×t 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 180 160 140 120 100 80 60 40 20 0 MAPE 93.75 MAD 27.93 MSD 1153.60 Accuracy Measures Year July Actual Fits Variable July Linear Trend Model Yt = 33.8 + 1.30×t 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 250 200 150 100 50 0 MAPE 1032.19 MAD 47.11 MSD 3491.20 Accuracy Measures Year september Actual Fits Variable September Rainfall Trend Linear Trend Model Yt = 105.7 - 0.66×t 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 500 400 300 200 100 0 MAPE 69.9 MAD 107.5 MSD 17954.0 Accuracy Measures Year October Actual Fits Variable October Linear Trend Model Yt = 192.0 + 6.35×t 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 500 400 300 200 100 MAPE 30.45 MAD 78.69 MSD 8916.59 Accuracy Measures Year November Actual Fits Variable November Linear Trend Model Yt = 321.5 - 3.38×t 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 700 600 500 400 300 200 100 0 MAPE 63.0 MAD 106.9 MSD 19403.7 Accuracy Measures Year December Actual Fits Variable December Linear Trend Model Yt = 232.8 + 3.53×t Fig. 15 AugustRainfall Trend
  • 7. International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 5, Sep – Oct 2019 Available at www.ijsred.com ISSN : 2581-7175 ©IJSRED: All Rights are Reserved Page 354 V. CONCLUSIONS The aim of the present study was to identify rainfall trends for the period of 1999 to 2018 over Badulla district. Annual rainfall trends showed a significantly increasing trend of about 15.8 mm/Year. Near about 12 years (60 %) shows annual rainfall less than that of mean annual rainfall and 08 years (40 %) show annual rainfall more that of mean annual rainfall. The maximum rainfall was observed in 2001 and it is 2525.1 mm and minimum rainfall was observed in 2010 and it was 1034.7 mm. The minimum First Inter-Monsoon seasonal rainfall was shown in 2014 and maximum First Inter- Monsoon seasonal rainfall was shown in 2016. The respective values are 241.7 mm/year and 947.9 mm/year. In May to September (Southwest-Monsoon season) shows a comparatively high increasing trend of 14.8 mm/year. 1047.9 mm/year and 2815.3mm/year were shown as minimum and maximum Southwest- monsoon seasonal rainfalls in the year 2016 and year 2014 respectively. Long term Second Inter-Monsoon seasonal rainfall shows 15.1 mm/year increasing trend with a maximum in 2014 and minimum in 1016 as 4155.25 mm/year and 947.44 mm/year respectively. Northeast-Monsoon Season in December to February shows a comparatively very high increasing trend with 45.0 mm/year rainfall. The maximum Northeast-Monsoon seasonal rainfall was shown in 2014 as 9377.43 mm/ year and the minimum was shown in 2016 as 1250.42 mm/year. Characteristics of monthly rainfall over Badulla have been calculated for individual months by fitting them to the linear trends. Maximum monthly rainfall was observed for November, December and October and they were 5173.1 mm, 5397 mm and 5720.1 mm respectively. The minimum monthly rainfall was observed in July, June and August and they were 949.2 mm, 952.4 mm and 1397.3 mm correspondingly. Analyzing the fitted linear trends, four months (33.33%) shows the decreasing monthly rainfall trend and eight Months (66.66%) shows the increasing monthly rainfall trends. The negative maximum monthly rainfall trends were shown in January and November. The minimum negative rainfall trend was shown in September and it was - 0.66. Within the other, eight months May and October shows maximum positive monthly rainfall trends, respectively given by 8.15 mm and 6.35 mm. REFERENCES [1] Adger WN, Hug S, Brown K, Conway D, Hulme M (2003). Adaptation to climate change in the developing world. Proc. Dev. Stud., 3(3): 179- 195. [2] Akinremi, O.O., McGinn, S.M., Cutforth, H.W., 2001. Seasonal and spatial patterns of rainfall trends on the Canadian prairies. Journal of Climate 14 (9), 2177– 2182. [3] Anser Khan, SoumenduChatterjee, DipakBisai and NilayKanti Barman (2014) Analysis of change point in surface temperature time series using cumulative sum chart and bootstrapping for Asansol weather observation station, west Bengal, India American journal on climate change Vol. 3 pp. 83-94. [4] Dr. Avinash Kadam, Kailas Karnewar (2016), Analysis of monthly and seasonal temperature trends of Nanded., July 2016., Indian stream research journal vol.6 no.6 pp ;1-9 . Available online at isrj.in [5] Frich P, Alexander LV, Della-Marta P, Gleason B, Haylock M, Klein Tank AMG, Peterson T (2002). Observed coherent changes in climatic extremes during the second half of twentieth century. Clim. Res., 19: 193-212. [6] Guhathakurta, P., Rajeevan, M., 2007. Trends in the rainfall pattern over India. International Journal of Climatology 28 (11), 1453–1469. doi:10.1002/joc.1640.Available from:www.intersciences.wiley.com (2002) The IEEE website. [Online]. Available: http://www.ieee.org/ [7] Intergovernmental panel on climate change (2007) The physical science basis: in contribution of working group 1 to the fourth assessment report of the Intergovernmental panel on climate change (eds) Soloma. 18. [8] Jagannathan, P., Bhalme, H.N., 1973. Changes in pattern of distribution of southwest monsoon rainfall over India associated with sunspots. Monthly Weather Review 101, 691–700. [9] Jayawardene HKWI, Sonnadara DUJ, Jayewardene DR (2005). Trends of Rainfall in Sri Lanka over the Last Century. Sri Lankan J. Phys., 6: 7-17 [10] Karnewar Kailas and Avinash Kadam (2015) “a” Study of Temperature Trends of Nanded, Maharashtra, India. World Rural Observ;7(2):30-35. [11] Karnewar Kailas and Avinash Kadam (2016) “b” Trends of monthly and seasonal temperature of Nanded, International Journal of Research in Social Sciences; 6 (9) :90-102. [12] koteswaram, P., Alvi, S.M.A.,1969. Secular trends and periodicities in rainfall at west coast stations in India. Current Science 101, 371–375 [13] Murphy, Bradley F, Timbal, Bertrand, 2007. A review of recent climate variability and climate change in southeastern Australia. International Journal of Clima-tology.doi:10.1002/joc.1627 Available from:www.interscience.wiley.com [14] Naidu, C.V., Srinivasa Rao, B.R., Bhaskar Rao, D.V., 1999. Climatic trends and periodicities of annual rainfall over India. Meteorological Application 6, 395– 404. [15] Nicholls, Neville, Lavery, Beth, 2006. Australian rainfall trends during the twentieth century. International Journal of Climatology 12 (2), 153–163. doi:10.1002/ joc.3370120204. Available from: www.interscience.wiley.com