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993
MAUSAM
UDC No. 551.583:551.577.1(540.47)
Rainfall characteristics under changing climate in Sundergarh district of Odisha
MANJARI SINGH* and B. S. RATH#
*Dept. of Agrometeorology, GBPUA&T, Pantnagar, Uttarakhand, - 263 145
*#Dept. of Agricultural Meteorology, OUAT, Bhubaneswar, Odisha, - 751 003
(Received 31 October 2021, Accepted 17 June 2024)
e-mail: manjari07.07@gmail.com
—
, -
-
34 (1988-2022)
- , , -
( ) 95%
. .
1290 ± 314 ,
- (86%) , (6.2%), (5.7%),
(2.1%)
50%
1071 () 1578 ()
, , ,
, ,
: (34% ); ( 7.6%);
( 3.3%); ( 3.2%)
,
ABSTRACT. Most pronounced signal of warming world is the increase in intensity and frequency of extreme
events worldwide. Many researchers have reported the nature of these events in coastal district of Odisha, but for
Sundergarh district which comes under North-western Plateau Agro-Climatic Zone, it still needed to be studied. The
present study was conducted with an objective to study rainfall characteristics - rainfall climatology, rainy days, trend -
their deviation and resulting meteorological drought in Sundergarh district of Odisha at block level using 34 years of
daily rainfall data (1988-2022). IMD classification for rainy days was adopted to determine the frequency of rainy days in
different categories. SPI was computed using Climpact to determine the occurrence and severity of meteorological
drought and identify episodes of dry and wet events during the study period for each block. MK test and Sen’s slope
estimator was used for detecting trend in rainfall (annual and seasonal) and rainy days at 95% significance level. Long
term rainfall analysis reveals that the mean annual rainfall of the district is 1290 ± 314 mm, most of which is received
during SW monsoon (86%) followed by post-monsoon (6.2%), pre-monsoon (5.7%) and least during winter (2.1%).
Rainfall received in the months of July and August together accounts for more than 50% of the total. Spatial distribution
of rainfall indicated that mean annual rainfall varies from 1071 mm (Subdega) to 1578 mm (Bonai). Annually, rainfall is
dependable in most of the blocks. However, during pre-monsoon, post-monsoon and winter, CV is very high, so the
rainfall is not dependable. Bulk of annual rainfall received in the district is contributed by rain events of light to moderate
category. Direction and magnitude of the trend of rainfall amount and rainy days varies a lot in different blocks. SPI
MAUSAM, 75, 4 (October 2024), 993-1008
DOI : https://doi.org/10.54302/mausam.v75i4.3563
Homepage: https://mausamjournal.imd.gov.in/index.php/MAUSAM
MAUSAM, 75, 4 (October 2024)
994
values calculated for the district as a whole shows that frequency of occurrence of these drought events were: mild (34%
of months); moderate (7.6% of months); severe (3.3% of months) and extreme (3.2% of months). The present study
provides pertinent information on the rainfall climatology and its trend under climate change over the Sundergarh district
of Odisha. Finding of the study suggests that there is an urgent need to raise awareness about the climate resilient society,
train personnels about sustainable development approaches and highlight the necessity of water harvesting techniques at
community level.
Key words - Rainfall climatology, Rainy days, Variability, Standard precipitation index, Mann Kendall test.
1. Introduction
The frequency and intensity of extreme heat and
heavy rainfall events since the late 1980s, especially in
mid-latitude regions, have been observed to increase
(Fischer et al., 2015; Lehmann et al., 2015). Arctic near-
surface temperature is rising at a pace two to three times
greater than that observed in the tropics, termed Arctic
amplification (Cohen et al., 2014), becoming even
positive in recent years. Issues mentioned in Arctic Report
2018, like record low sea-ice extent in Barents and Kara
Sea (BKS); decreased old ice-cover in the Arctic, which
has reduced from 16% to less than 1% in 33 years;
Atlantification of fresh Arctic water; heat waves across
central Arctic, have raised questions like how these
changes are going to affect the weather in middle and low
latitudes. Does the influence bring sufferings to the entire
globe or will it be restricted only to Polar Regions? What
effect will these have on the marine and land carbon cycle,
etc.? In recent years, rising ocean temperature in the
tropics has led to increased frequency and intensity of
cyclones as observed globally. Simultaneously, marked
decrease in precipitation levels since 1994 in many
regions of Australia, increased weather variability,
untimely rains, rainy days with heavy downpours and
prolonged dry spells otherwise, have become normal in
many parts of India in the last decade. This has forced the
scientific community to think about the future of Earth.
The Indian subcontinent receives most of its rain
during the south-west monsoon period, i.e., from June to
September. The geography of this region makes it unique
but also susceptible to the above-mentioned changes.
Atmospheric teleconnection existing between the Indian
Ocean, Pacific Ocean & adjoining landmasses translates a
lot of weather-related changes occurring in one part of the
globe to the others. In meteorology, we call it the butterfly
effect. Variation in insolation, movement of air masses,
pressure gradient, flow direction of atmospheric rivers & a
multitude of other meteorological factors, they all act
simultaneously and determine the spatial & temporal
distribution of rainfall in the country. India is such a
diverse country that it is not uncommon to see floods in
one part & water scarcity in another part. In the past
decade, the country has witnessed several flooding events
caused by intense rain spells, also called cloudbursts in
different parts of the country. Simultaneously, the country
has also faced water shortages in megacities, especially
during the summer season.
For the sustenance of a developing country like India
with billions of inhabitants to feed and to ensure a quality
life for all, there is a need to reconsider our approach to
development. The recent report of IPCC titled “Climate
Change 2021: The Physical Science Basis” highlights that
continued global warming is projected to further intensify
the global water cycle, including its variability, global
monsoon precipitation and the severity of wet and dry
events. Also, monsoon precipitation is projected to
increase over South and Southeast Asia. Rainfall
characterization at the block level the lowest
administrative level will help the decision-making bodies
and policy planners to identify the gaps and opportunities
available. Adoption and implementation of any approach
with a view of sustainability at this level will give the
most effective results. Both soil and water are valuable
natural resources which need to be conserved for future
generations. In earlier days, each locality used to have
fallow lowland or small pond-like structure (e.g., Dobha)
where runoff flows, gets stored and subsequently keeps on
recharging the groundwater table. However, in the present
day due to increased population pressure in and near the
cities land is filled and covered with impervious materials
to erect multistory apartments, roads and other buildings.
Even though the rainfall pattern has not changed in a
region, the inhabitants are facing a shortage of water
during summers. This is mainly because in the race of
development, cities have constructed big buildings, roads,
supermarkets, etc., people on the outskirts filled lands to
grow vegetables, and left very little space for water to get
stored and subsequently infiltrate and percolate into the
soil. It would be wise to go for a bottom to top approach
to raise awareness among households about sustainability
and climate resilience. Odisha, an eastern Indian province,
is mainly an agrarian state where about 70% of the
population is engaged in agricultural activities and 50% of
the state’s economy comes from the agricultural sector
(Panigrahi et al., 2010). In Odisha, the current stage of
ground water extraction is 42.18 % as of 2017 (CWC
Abstract on water sector, 2020). The depth of ground
water level varies between 5-10 m during pre-monsoon
and between 2-5 m during the post-monsoon season
(Central Ground Water Board) in Sundergarh district. In
the coastal districts however, depth of water table is
relatively shallow i.e., it varies between 2-5 m
during pre-monsoon and < 2 m during post-monsoon.
In the last two or three decades, frequency of extreme
weather events such as intense rainfall has increased in
many parts of Odisha (Pasupalak et al., 2017).
SINGH and RATH: RAINFALL CHARACTERISTICS UNDER CHANGING CLIMATE IN SUNDERGARH
995
Fig. 1. Location map of study area.
A significantly increasing (decreasing) trend in the
frequency of high-intensity (low-intensity and wet days)
rainfall events over most parts of Odisha is observed for
all the seasons (Nageswararao et al., 2019). Most of these
rainfalls are associated with the low-pressure systems
developing over north and adjoining central Bay of
Bengal. Higher intensity of rainfall breaks the soil
structure, creates temporary surface crust, thus running
water has less retention time over any surface, resulting in
more runoff and diminished groundwater recharge. A
long-term imbalance between the abstraction and recharge
of groundwater results in hydrological drought sooner or
later depending on the soil moisture holding
characteristics and the amount of water present in the
aquifer.
Selection of crops, cropping system and associated
agricultural activities depends a lot on the soil moisture
availability and rainfall characteristics. In order to plan
different adaptation and mitigation strategies against the
changing climate, policy maker or agricultural official
must have a good understanding of the rainfall
characteristics of the area apart from the edaphic,
hydrological and socio-economic characteristics. In view
of the changing climate, extreme rainfall events were
studied by several researchers (Swain et al., 2018; Naika
et al., 2019; Swain et al., 2020) for different districts of
Odisha, especially the coastal districts. Similar study is
needed for the North-western Plateau Agro-Climatic Zone
of Odisha which shows more continental type of climate.
Block wise irrigation status (PMKSY, 2016) indicates that
the blocks are still under rainfed agriculture. Therefore, it
is a dire need to identify the potentials and constraints
associated with rainfall in the district. This enables the end
user (farmer) as well as policy maker to identify potential
regions and time when challenges associated with any
unforeseen event can be avoided and the community can
be made resilient and adapted to such circumstances, if
possible. In this study, an attempt was made to study the
spatial and temporal variability of rainfall and rainy days,
their trend during the study period, frequency of rainfall
events in different categories and their deviation resulting
in different types of meteorological drought. This analysis
provides information at block level which is assumed
homogeneous with respect to weather and thus can be a
great tool for decision makers who can give advisory,
recommend farm operations, choice of crops and cropping
pattern based on the results.
2. Materials and methods
2.1. Study area description
Sundergarh district forms the North-Western border
of Odisha (Fig. 1). Geographically, it extends between 21°
35ʹ N and 22° 32ʹ N latitudes and 83° 32ʹ E and 85° 22ʹ E
longitudes, spanning over an area of 9712 sq.km, out of
which 3130 sq.km area is net sown. Sundergarh comes
under North-western Plateau Agro-climatic zone of the
state (Nayak et al., 2020), one of the unexplored regions
of Odisha, which experience Hot & Moist Sub-humid
climate. The district comprises of 17 blocks and is second
largest in the state in terms of area, accounting for 6.23 %
of the total area. Cropping intensity in the district is very
low (126.8%) compared to that of the state average
(156%). A greater proportion of available land in the
district is still rainfed and only a few blocks have irrigated
MAUSAM, 75, 4 (October 2024)
996
Figs. 2 (a & b). (a) Block wise irrigation status and (b) major crops grown in the district (data source: PMKSY, 2016).
area more than 50% (Fig. 2). Rainfall characterization is
therefore needed to identify potential and limitations of
the district in terms of weather and use the same for
necessary decision making.
TABLE 1
Description of rain-gauge stations in the district including their
geographic position
Block Name
Block_ID*
Latitude
Longitude
Balisankara
1
22.3505
84.0351
Baragaon
2
21.9064
84.6824
Bisra
3
22.2479
84.9981
Bonai
4
21.8256
84.9495
Gurundia
5
21.8468
84.7848
Hemgir
6
21.9495
83.7026
Koida
7
21.9017
85.2464
Kuarmunda
8
22.3029
84.7776
Kutra
9
22.2328
84.456
Lahunipara
10
21.9031
84.9331
Lathikata
11
22.1406
84.8919
Lephripara
12
22.1456
83.8063
Nuagaon
13
22.0221
85.0979
Rajagangapur
14
22.1902
84.5799
Subdega
15
22.2866
84.1058
Sundargarh
16
22.124
84.0432
Tangarpali
17
22.0984
83.9937
* Block id: number corresponding to each block in maps
2.2. Data
Daily rainfall series of 34 years (1988-2022)
recorded at 17 rain-gauge station, one in each block
(administrative unit) were used. The database has been
collected from the Department of Revenue and Disaster
management, Special Relief Commissioner, Government
of Odisha. Table 1 presents the characteristics of rain-
gauge stations, including the geographic position in map
(Block id).
2.3. Methodology
Daily series of rainfall data were used to compute
climatological mean, Interannual variability (IAV) and
Coefficient of variation (CV) at different time scales. The
threshold levels for coefficient of variation (CV) were
taken as <25 %, <50 %, <100 %, <150 % for annual,
seasonal, monthly and weekly rainfall respectively during
interpretation (Manorama et al., 2007). If the CV is within
the threshold limit of variability, it is considered that the
rainfall is highly dependable and vice versa. In addition,
rainfall events in different categories (mean ± standard
deviation; IMD, 2021) and Standardized Precipitation
Index (SPI) on a time scale of 3, 6, 12 and 24 months
(Balram and Fanai, 2020) were also calculated. Based on
the intensity of 24-hour accumulated rainfall, IMD
categorized rainfall events into seven different categories:
very light; light; moderate; heavy; very heavy; extreme
heavy and exceptionally heavy rainfall (Table 2).
Recently, threshold values of rainfall intensity for each
category were modified and therefore have been presented
in Table 2. In addition to the frequency of intense rainfall
events, the frequency of rainy days in different categories
(as per IMD classification); Standard Operation
Procedure-Weather Forecasting and Warning (2021)) i.e.,
dry days and wet days, were also calculated in R. Dry
days are the number of days with “no rain”. Wet days are
SINGH and RATH: RAINFALL CHARACTERISTICS UNDER CHANGING CLIMATE IN SUNDERGARH
997
TABLE 2
Different categories of rainfall events based on the intensity as
classified by the IMD
S. No.
Terminology
Rainfall range (in mm/day)
01
Very light rainfall
(VLR)
Trace – 2.4
02
Light rainfall (LR)
2.5 – 15.5
03
Moderate Rainfall
(MR)
15.6 – 64.4
04
Heavy rainfall (HR)
64.5 – 115.4
05
Very heavy rainfall
(VHR)
115.5 – 204.4
06
Extreme heavy
rainfall (EHR)
≥ 204.5
07
Exceptionally heavy
rainfall (Exc. HR)
When the amount is a value
near about the highest recorded
rainfall at or near the station
for the month or season.
However, this term will be
used only when the actual
rainfall amount exceeds 24 cm.
Source : IMD
the number of days receiving a given amount of rainfall
(equal to or more than 1 mm/day; Pal and Tabbaa, 2011;
Sinha et al., 2013).
SPI is calculated to identify the episodes of dry and
wet periodsat various time scales (McKee et al., 1993).
Short term rainfall anomalies are computed in studies
dealing with soil moisture, whereas long-term anomalies
are used in studies on groundwater, reservoir storage etc.
In order to compute SPI for any location, long term
precipitation data is required (Edwards and McKee, 1997).
In the present study, SPI was computed using Climpact
(https://infoasis.shinyapps.io/climpact/) at 1, 3, 6, 12 and
24 months, over the period of 1988-2022 for different
blocks of Sundergarh. Considering the length of the
article, results were tabulated and presented for all time
scales, however, graphical representation to show the
variation of SPI, was done only for 12-month averaged
SPI and 1-month SPI values during the monsoon months.
Climpact is an R software package that calculates Expert
Team on Sector-specific Climate Indices (ET-SCI) in
which SPI is one of the indices. Positive SPI values
indicate greater than median precipitation whereas
negative values indicate less than median precipitation
(Balram and Fanai, 2020). The identification of wet and
dry periods and classification of drought severity can be
done using the classification system adopted by McKee
et al., 1993 (Table 3).
TABLE 3
SPI classification and their values
Category
SPI range
Extremely wet
2.00 or more
Severely wet
1.50 to 1.99
Moderately wet
1.00 to 1.49
Mildly wet
0 to 0.99
Mildly dry
0 to -0.99
Moderately dry
-1.00 to -1.49
Severely dry
-1.5 to -1.99
Extremely dry
-2.00 or less
(Source: World Meteorological Organization, 2012)
To identify the trends of rainfall, total number of
rainy days and various rainfall events, non-parametric
Mann-Kendall test at 95% significance level was
used (Waghaye et al., 2018; Tiwari et al., 2019). MK test
is not affected by gross data errors and outliers
(Guhathakurta et al., 2011). Sen’s slope estimator is then
computed to capture the magnitude of the trend. MK test
and Sen’s slope was computed in R using “Trend”
package (https://cran.r-project.org/web/packages/trend/
trend.pdf).
3. Results & discussion
In this study, characteristics of rainfall at different
temporal scales (annual, seasonal and monthly) for
Sundergarh district of Odisha have been analyzed using
the observed station dataset and results are presented in
the following subsections.
3.1. Spatial distribution of rainfall
The mean, inter annual variability (IAV) and
coefficient of variation (CV) of rainfall for the seventeen
blocks of Sundergarh district were computed using daily
rainfall data of 34 years (1988-2022). Block wise
distribution of long-term mean rainfall at annual, seasonal,
and monthly time scale are presented in Table 4. The
mean annual rainfall for the district as a whole is 1290 ±
314 mm, which however exhibits great spatial and
temporal heterogeneity at the block level. It varies from
1071 mm in Sub dega to 1578 mm in Bonai. Blocks in the
eastern and north-eastern part of the district receive higher
amount of rainfall. SW monsoon is the main rain bearing
season in Sundergarh district, which alone accounts for
about 86% of the total annual rainfall. The district
receives highest rainfall in the month of August (27.5%
contribution) followed by July (26.6%), September
MAUSAM, 75, 4 (October 2024)
998
Figs. 3(a-o). Spatial distribution of rainfall and its variability (expressed as Interannual variability and Coefficient of variation) in
different blocks of Sundergarh district for the study period (1988-2022).
a-c: mean, Interannual variability (IAV in mm) and Coefficient of variation (CV in %) for annual rainfall;
d-f: same indicators for pre-monsoon rainfall;
g-i: same for SW Monsoon rainfall;
j-l: same indicators for post-monsoon rainfall; and
m-o: same for winter rainfall.
SINGH and RATH: RAINFALL CHARACTERISTICS UNDER CHANGING CLIMATE IN SUNDERGARH
999
Fig 4. SRTM Digital Elevation Map of Sundergarh district & adjoining. Fig. 5. Year-wise variation of the number of rain days at seventeen stations in
the Sundergarh district.
(16.4%) and June (15.5%; Table 4). Rainfall received in
the months of July and August together accounts for more
than 50% of the total annual rainfall. Winter months are
generally dry (receives 2.1% of annual rainfall). Pre-
monsoon and Post-monsoon season receive a few of the
rainfall events that contributes about 5.7 % and 6.2 %
respectively to the annual rainfall. The long-term mean
rainfall for all blocks at different time scale can be seen in
Table 4.
Block wise distribution of mean, IAV and CV of
annual and seasonal rainfall are shown in Fig. 3. CV for
the annual rainfall ranges from 16.8% (Lahunipara block)
to 34.5% (Lephripara). Rainfall is considered dependable
when CV is less than 25% for the annual rainfall and less
than 50% for the seasonal rainfall. Annually, rainfall can
be considered dependable in most of the blocks. Although
Bonai receives highest rainfall in the district, its
coefficient of variation is high (29 %). Other blocks with
high CV are: Bargaon; Bisra; Lephripara and Rajgangpur.
The undulating topography of the district and adjoining
areas (Fig. 4) is an important factor explaining the
heterogeneity observed at block level. The presence of
medium to higher hills in south-eastern part of district
may be ascribed as one of the reasons of concentration of
rainfall in these blocks and rain shadow effect in the
remaining blocks.
The seasonal rainfall during pre-monsoon, post-
monsoon and winter months is not dependable as the CV
during these months is very high. During monsoon
months (June-Sept), however, rainfall can be considered
dependable (CV ranging between 19.6 - 42.1%). The
coefficient of variation varies between 30-40% in
Bargaon, Bisra, Bonai, Kutra, Lephripara and Rajgangpur.
The lowest and highest variability is observed for
Balisankara (19.6%) and Lephripara (42.1%) respectively.
Elsewhere, rainfall variability was found to lie between 20
- 30%. Because rainfall received during monsoon months
contributes about 86% to the annual rainfall, it is the main
cropping season in the district. Rice is the major crop
grown throughout the district. In years with poor SW
monsoon, rainfed crops generally suffer significant loss.
Despite the district receives good amount of annual
rainfall, cropping intensity is only 126.7% (Pasupalak et
al., 2019). This is mainly because: (i) about 40% of the
rainfall received annually (45% during the monsoon
season) is lost as runoff from the undulating topography of
the district; (ii) high variability of rainfall during pre-
monsoon, post-monsoon and winter season; and (iii)
insufficient irrigation facility. This suggests a need of
supple-mental irrigation facility if the farmer is growing a
second crop during rabi or zaid cropping season. Also, it
is to note that there is 75% probability of receiving at least
20 mm of weekly rainfall during SMW 25-38
(Supplementary Table 1), which again exhibits great
spatial variability among the blocks.
3.2. Spatial distribution of rainy days and intense
rainfall events
Number of rainy days (i.e., a day receiving ≥2.5 mm
of rainfall) varies from 64 (in Subdega) to 85 (in
Lahunipara and Koida) annually (Table 4). Fig. 5 shows
the spatial variation of number of rainy days representing
17 blocks in different years during the study period.
During first half of the study period (1988-2003),
spatial variation was high compared to the later half
(2004-2022). This indicates that in the last decade,
number of rainy dayswas found to be relatively
homogenous throughout the district compared to what was
observed before 2003. Fig. 6 shows the contribution of
different categories of rainfall events (based on 24-hours
MAUSAM, 75, 4 (October 2024)
1000
TABLE 4
Mean monthly, seasonal, annual rainfall and rainy days based upon 1988-2022 data over
different block of Sundargarh district
Block name
Balisankara
Bargaon
Bisra
Bonai
Gurundia
Hemgir
Lahunipara
Lathikata
Lephripara
Koida
Kuarmunda
Kutra
Nuagaon
Rajgangpur
Subdega
Sundergarh
Tangarpali
District
Jan
16
13
10
16
12
14
13
17
17
13
12
14
13
7
15
14
12
13.4
Feb
10
12
15
17
15
13
17
16
10
17
10
13
17
12
9
12
13
13.4
Mar
7
12
10
12
14
9
11
15
9
17
11
10
14
10
9
13
10
11.4
Apr
14
17
17
28
16
14
27
23
10
26
18
11
12
15
10
16
10
16.7
May
27
36
53
63
61
33
62
76
33
75
55
41
42
41
20
44
32
46.7
Jun
205
175
185
260
231
208
243
223
191
223
196
188
177
161
162
212
168
200.5
Jul
354
299
307
403
358
369
388
379
335
344
376
318
317
268
301
376
325
342.2
Aug
323
310
324
418
364
386
400
399
363
344
391
337
336
317
308
364
331
353.8
Sep
216
173
193
252
235
248
226
237
221
217
223
182
216
175
178
216
190
211.6
Oct
51
46
54
81
73
55
76
72
54
99
67
49
49
49
45
53
49
60.1
Nov
8
11
7
14
11
10
10
14
11
14
15
13
10
11
8
10
8
10.9
Dec
7
11
9
14
11
10
12
11
9
9
8
10
12
9
6
9
5
9.5
Winter
26
25
25
33
27
27
30
33
27
30
22
27
30
19
24
26
25
26.8
Pre-
monsoon
48
65
80
103
91
56
100
114
52
118
84
62
68
66
39
73
52
74.8
Monsoon
1098
957
1009
1333
1188
1211
1257
1238
1110
1128
1186
1025
1046
921
949
1168
1014
1108.1
Post-
monsoon
66
68
70
109
95
75
98
97
74
122
90
72
71
69
59
72
62
80.5
Annual
1238
1115
1184
1578
1401
1369
1485
1482
1263
1398
1382
1186
1215
1075
1071
1339
1153
1290.2
No. of
Rainy
day
67
76
76
79
75
75
85
71
65
85
78
68
73
70
64
81
69
73.4
Fig. 6. Spatial distribution of the proportion of rainfall events (based on
accumulated 24-hours rainfall) in a given categories to the total rainy
days in Sundergarh.
accumulated rainfall) to the total rainy days in different
blocks. A significant fraction of the rainfall is received as
intense spells. Annually, about 49 ± 2 % rain spells
received are of Moderate category followed by Light rain
(31 ± 3 %) and Very Light (15 ± 3%) category (Table 5).
This suggests that a greater proportion of the rainfall
is received as rainfall events of light to moderate category.
It is apparent that bulk of the annual rainfall at different
stations is contributed by few rainy days, most of which
are associated with heavy downpours. Therefore, there is a
high probability of getting floods after such events and
experiencing prolonged dry spells otherwise. Soils in the
district are coarse-textured and moderately shallow in
depth. Even though the district is receiving good quantum
of rainfall in monsoon months, majority of the farmers are
practicing rainfed farming & they grow single crop. Only
a small fraction of farmers is able to grow another crop
SINGH and RATH: RAINFALL CHARACTERISTICS UNDER CHANGING CLIMATE IN SUNDERGARH
1001
TABLE 5
Mean and Inter annual variability (IAV)of number of rainy days in various categories, dry days and wet days in different blocks of
Sundergarh during the study period (1988-2022).
Block name
Categories of rainy days (Based on 24-hour accumulated rainfall)
Days with or without rainfall
Very LR
Light R
Mod. R
Heavy R
Very HR
Ext. HR
DD
WD
Balisankara
7 ± 4
34 ± 9
23 ± 4
3 ± 2
0 ± 1
0.0 ± 0.2
305 ± 9
60 ± 9
Bargaon
15 ± 7
38 ± 7
21 ± 6
2 ± 2
0 ± 1
0.0 ± 0.2
304 ± 9
61 ± 9
Bisra
14 ± 6
39 ± 10
21 ± 6
2 ± 2
0 ± 1
0.0 ± 0.4
301 ± 9
64 ± 9
Bonai
12 ± 6
36 ± 9
26 ± 7
3 ± 2
1 ± 1
0.1 ± 0.2
298 ± 10
67 ± 10
Gurundia
10 ± 6
36 ± 8
25 ± 5
3 ± 2
1 ± 1
0.0 ± 0.3
301 ± 8
64 ± 8
Hemgir
11 ± 7
37 ± 6
24 ± 5
3 ± 2
1 ± 1
0.1 ± 0.3
301 ± 11
64 ± 12
Koida
12 ± 5
46 ± 8
25 ± 7
2 ± 2
1 ± 1
0.1 ± 0.4
292 ± 10
74 ± 10
Kuarmunda
10 ± 5
34 ± 7
24 ± 5
3 ± 2
1 ± 1
0.1 ± 0.2
304 ± 10
61 ± 10
Kutra
7 ± 4
34 ± 8
21 ± 6
2 ± 2
0 ± 1
0.0 ± 0.2
305 ± 10
59 ± 10
Lahunipara
15 ± 6
41 ± 8
26 ± 5
3 ± 2
1 ± 1
0.1 ± 0.2
294 ± 9
71 ± 9
Lathikata
9 ± 6
39 ± 7
25 ± 5
4 ± 2
1 ± 1
0.1 ± 0.2
298 ± 9
69 ± 9
Lephripara
10 ± 6
32 ± 8
23 ± 8
2 ± 2
1 ± 1
0.1 ± 0.2
305 ± 12
60 ± 12
Nuagaon
13 ± 6
36 ± 9
21 ± 5
3 ± 2
0 ± 1
0.0 ± 0.2
305 ± 9
60 ± 9
Rajgangpur
14 ± 9
34 ± 7
19 ± 7
2 ± 1
0 ± 1
0.0 ± 0.2
309 ± 12
56 ± 10
Subdega
8 ± 5
33 ± 7
20 ± 6
2 ± 2
0 ± 1
0.0 ± 0.3
309 ± 8
55 ± 9
Sundergarh
16 ± 6
38 ± 7
23 ± 5
3 ± 2
1 ± 1
0.1 ± 0.3
301 ± 10
64 ± 10
Tangarpali
10 ± 5
36 ± 9
20 ± 6
2 ± 2
0 ± 1
0.1 ± 0.2
306 ± 10
59 ± 10
VLR = Very light rain, LR =Light rain, MR= Moderate rain, HR = Heavy rain, DD = days with no rainfall, WD =days with rainfall (>0 mm)
TABLE 6
Trend of rainfall (annual and seasonal) and rainy days in different blocks of Sundergarh (1988-2022).
Block name
Annualrainfall
Pre-monsoon
SW Monsoon
Post-monsoon
Winter
No. of Rainydays
Balisankara
-2.84
0.00
-5.30
0.91
0.05
0.10
Bargaon
14.47*
1.96*
10.00*
1.13
0.19
0.36*
Bisra
13.28*
3.10*
5.00
2.43*
0.30
0.32
Bonai
-11.04
-0.25
-10.57
0.42
0.00
0.00
Gurundia
9.50
1.92
4.24
1.69
0.00
0.21
Hemgir
12.95*
1.11
11.00
1.62
0.12
0.00
Koida
-1.42
1.00
-4.45
0.26
0.00
-0.15
Kuarmunda
7.25
2.94*
-1.17
1.25
0.47*
0.50*
Kutra
2.58
0.82
0.71
1.31
0.34
0.44*
Lahunipara
-5.02
-0.47
-7.49
0.82
0.00
-0.83*
Lathikata
-3.58
1.54
-7.57
0.98
0.00
0.00
Lephripara
1.15
0.41
1.95
0.66
0.00
0.00
Nuagaon
0.56
0.38
-3.11
1.00
0.00
0.08
Rajgangpur
17.02*
2.28*
11.18*
2.13*
0.30
0.81*
Subdega
16.40*
0.91*
15.51*
1.00
0.00
0.00
Sundergarh
-3.38
0.76
-7.37
0.93
0.00*
0.07
Tangarpali
14.49*
1.70*
9.88*
0.85
0.55
0.40*
* Indicates values at 95% significance level.
MAUSAM, 75, 4 (October 2024)
1002
using the supplemental irrigation from various sources.
Undulating and rolling terrains at downhill of the district
can be utilized as a valuable and appropriate site for
checkdams and similar structures to collect and store
runoff from the villages.
3.3. Trend of rainfall at different temporal scales
and rainy days
Mean annual rainfall (mm) in different blocks of
Sundergarh showed great variation (Table 6) during the
study period. Rainfall is showing significantly increasing
trend in blocks like Bargaon (14.47 mm/year), Bisra
(13.28 mm/year), Hemgir (12.95 mm/year), Rajgangpur
(17.02 mm/year), Subdega (16.40 mm/year) and
Tangarpali (14.49 mm/year). Increase in rainfall offers
several kinds of opportunities, but, if not managed well, it
can result in natural disasters. This therefore, demands
preparedness against any unforeseen events, especially in
the areas with poor drainage. Keeping in view the soil
characteristics, vegetation & physiography of the region,
runoff must be channelized & stored by adopting different
Managed aquifer recharge (MAR) techniques. This way
water requirement for household activities as well as
agricultural purposes can be met out during prolonged dry
spells. However, in Bonai & Lahunipara, annual rainfall is
showing decreasing trend of magnitude greater than 5
mm/year (Table 6). The decreasing trend again demands
attention. In Bonai, more than two-third of the cultivable
area is rainfed, whereas, in Lahunipara more than half is
rainfed (PMKSY, 2016). Other blocks such as
Balisankara, Lathikata & Sundergarh are also witnessing
reduction in annual rainfall. Therefore, reduction of
rainfall can bring down crop yields & may impact food
security in the region. Taking into consideration the
irrigation status in different blocks, construction of
appropriate water retention & storage structures should be
encouraged at the individual as well as community level.
In the case of seasonal rainfall, magnitude as well as
direction of trend was computed for all four seasons.
Trend direction during the SW monsoon season followed
the trend of annual rainfall in some of the blocks but with
varying magnitude. Mann Kendall trend analysis for SW
monsoon suggests that rainfall is decreasing in about 50%
of the blocks (Table 6), with a magnitude greater than that
observed in the case of annual rainfall. Unlike SW
monsoon season, rainfall is increasing during the pre-
monsoon season (except in Bonai and Lahunipara).
Although magnitude of the Sen’s slope is smaller, rainfall
is showing an increasing trend in all blocks during post-
monsoon season. In winter season, rainfall is showing a
significant increase in Kuarmunda (0.47 mm/year) and no
change in Sundergarh and other blocks.
With regard to the trend of the number of rainy days,
it showed significant increase in some of the blocks,
whereas, a decrease in others (Table 6). A significantly
increasing trend was observed in Bargaon, Kuarmunda,
Kutra, Rajgangpur and Tangarpali, with varying
magnitudes. Opposite trend however, was observed in
three blocks namely, Lahunipara, Koida and Lathikata.
Although result indicated decreasing trend in these blocks,
the trend was significant only in Lahunipara (-0.83 per
year). Special consideration needs to be given to Hemgir
and Subdega where annual rainfall is showing an
increasing trend without any trend in rainy days. This
suggests that frequency of extreme rainfall events has
increased in these blocks without any change in the
number of wet days (>1 mm/day). Interpretation of the
result also suggests that there is rise in the number of
intense rainfall events, thus, leading to (i) submergence of
crops in the lowlands, (ii) increased removal of topsoil
fertile soil (erosion) by the running water on the sloping
surface, (iii) reduced infiltration of water into the soil,
caused by sealing of macro as well as micropores, (iv) less
recharge of groundwater and (v) more loss in the form of
surface runoff.
Information of this kind is of utmost importance to
agriculture officials. They can use it to minimize the
damaging potential of any hazard - resulting from change
in rainfall pattern and transform it into opportunity. It is
necessary to be prepared for the changing climate and
adopt strategies to make the farming climate resilient.
Excess runoff during monsoon months can be stored in
farm ponds, dugout ponds, reservoirs etc. which will
simultaneously recharge the groundwater. MAR
techniques - such as check dam, percolation tank,
recharge well etc. which have been implemented across
the country since 1970s (Dillon et al., 2020) can be
advocated. Field channels can be constructed for smooth
delivery of water into the fields when in need and safe
removal of excess water during and after the rainfall
events. Also, because the district is comprised of uneven
terrains in many blocks, check dams can be constructed
across the course of river (or deep gullies created by
running water) at regular intervals. Checkdams have
traditionally been built to (i) slow down the velocity of
running water, (ii) impeding waterflow increases the
retention period and thus facilitate ground water storage,
and (iii) conserve soil. Implementation of different MAR
techniques ensures the availability of water for longer
period and second crop can be grown without any risk of
failure. Fisheries are another important source of
livelihood which can be promoted in the region when
community is made aware of in-situ and ex-situ water
harvesting techniques. High water requiring crops can
also be grown during monsoon season.
SINGH and RATH: RAINFALL CHARACTERISTICS UNDER CHANGING CLIMATE IN SUNDERGARH
1003
Fig. 7. Variation of SPI (12-month) during the study period for seventeen blocks of Sundergarh.
MAUSAM, 75, 4 (October 2024)
1004
Fig. 8. Variation of SPI (1-month) values in the seventeen blocks of Sundergarh district during the monsoon months.
3.4. Meteorological drought assessment using SPI
Fig. 7 shows the long-term variability of rainfall and
episodes of dry and wet periods during the study period
using 12 month averaged SPI values. Graphical
representation of SPI values (Fig. 7) shows a cyclic
pattern of wet and dry periods, although duration of each
period varies in different blocks. This illustrates the long-
term variability of rainfall in the district over the
seventeen blocks. Result also indicates that the district
experienced almost equal number of dry and wet events in
the past. In most of the blocks, dry periods alternated with
wet periods. Majority of the drought events fall under
mild drought category (68.7 %) followed by Moderate
(17.8 %), severe (8%), and extreme (5.5%) category.
24 month averaged SPI values indicate the occurrence of
Extreme drought conditions during 1990-93 in Hemgir,
during 1998-99 in Balisankara, Bargaon and and Bisra
and during 2009-11 in several blocks (namely, Gurundia,
Koida, Kuarmunda, Kutra, Lahunipara and Nuagaon).
Balisankara, Bonai, Lephripara and Subdega have never
experienced drought in extreme category during the study
period.
Drought of various categories are recurring features
in different blocks of Sundergarh district, which shows
great variation across time and space. In addition to
identifying the episodes of wet and dry periods, another
attempt was made to find out the number of drought years
and its frequency of occurrence. Table 7 shows that the
SINGH and RATH: RAINFALL CHARACTERISTICS UNDER CHANGING CLIMATE IN SUNDERGARH
1005
TABLE 7
Frequency (percentage) of occurrence of droughts in SPI series of 3, 6, 12 and 24 months in different blocks of Sundergarh district.
Blocks
3 month
6 month
12 month
24 month
Mild
Mod
Sev
Ext
Mild
Mod
Sev
Ext
Mild
Mod
Sev
Ext
Mild
Mod
Sev
Ext
Balisankara
32.1
6.9
1.9
1.7
35.7
8.0
2.2
3.2
34.7
9.8
4.6
2.0
29.8
13.1
4.0
0.5
Bargaon
32.1
6.9
1.9
1.7
35.7
8.0
2.2
3.2
34.7
9.8
4.6
2.0
29.8
13.1
4.0
0.5
Bisra
31.1
3.1
3.8
1.2
24.5
8.0
3.2
3.9
20.5
5.6
3.4
8.3
14.6
1.0
10.6
7.1
Bonai
35.9
5.7
2.6
0.7
38.8
6.8
3.6
1.5
43.5
9.3
4.2
0.7
46.5
6.3
5.1
0.0
Gurundia
33.3
6.7
2.6
0.7
31.1
10.2
3.9
1.5
24.2
13.9
4.2
2.7
26.3
5.8
3.5
5.6
Hemgir
33.3
6.5
2.4
0.7
32.3
7.8
6.3
1.5
32.3
9.0
3.7
3.7
28.8
2.0
1.0
9.6
Koida
30.1
9.1
3.3
1.4
34.2
6.3
3.6
3.6
35.0
5.4
1.0
5.6
36.1
5.6
0.8
6.1
Kuarmunda
35.9
6.0
1.7
0.7
36.4
9.2
2.7
1.5
35.0
8.8
3.9
1.5
38.9
9.1
1.8
2.0
Kutra
35.9
6.0
1.7
0.7
36.4
9.2
2.7
1.5
35.0
8.8
3.9
1.5
38.9
9.1
1.8
2.0
Lahunipara
31.3
9.3
1.7
0.5
34.7
10.4
4.1
1.5
38.6
7.3
6.6
0.7
40.4
7.6
0.8
3.0
Lathikata
35.9
5.5
2.4
1.4
34.0
10.2
3.4
1.5
38.1
11.5
3.4
1.0
31.6
9.3
4.5
2.3
Lephripara
35.9
5.7
2.6
0.7
38.8
6.8
3.6
1.5
43.5
9.3
4.2
0.7
46.5
6.3
5.1
0.0
Nuagaon
35.2
5.3
3.1
0.7
34.5
8.5
4.4
1.9
33.0
8.3
5.6
2.4
31.6
10.1
3.5
3.0
Rajgangpur
33.5
4.5
2.6
1.2
34.7
3.4
3.9
2.7
33.5
2.0
4.9
4.2
34.8
4.3
0.3
6.3
Subdega
35.2
7.2
1.9
0.5
35.0
9.7
3.9
0.5
29.1
14.2
3.9
0.2
27.3
14.1
5.1
0.0
Sundergarh
32.8
5.5
2.4
0.7
35.4
8.7
5.1
0.7
32.5
12.2
3.9
0.5
39.6
7.1
4.5
1.0
Tangarpali
33.0
4.8
1.7
1.0
35.4
4.6
2.7
2.4
37.2
4.6
1.0
5.1
36.6
4.8
0.3
5.6
District
33.7
6.2
2.4
1.0
34.6
8.0
3.6
2.0
34.1
8.8
3.9
2.5
34.0
7.6
3.3
3.2
Mild = Mild drought, Mod = Moderate drought, Sev = Severe drought, Ext = Extreme drought
requency of the occurrence of droughts of various
categories varies in different blocks. For different time
scales under analysis, the blocks experienced maximum
number of mild drought events (For example, ranging
from 29.8 to 35.7% for Balisankara) followed by
moderate drought (ranging from 6.9 to 13.1%), severe
drought (ranging from 1.9 to 4.6%) and extreme drought
(0.5 to 3.2%). The frequency of occurrence of severe and
extreme drought is relatively smaller as compared to the
mild and moderate droughts.
SPI values for 24-months analysis period showed
that Bonai and Lephripara have experienced the highest
number of mild drought years (46.5% frequency) followed
by Lahunipara (40.4% frequency), and least in Bisra.
Result also revealed that in addition to the mild droughts,
Bisra has experienced several drought events of severe
to extreme category. Year 1998 - 2002 were largely deficit
years for Bisra. Year 1889-93 were the deficit years for
Hemgir. Other periods of rainfall deficit in different
blocks can be seen in Fig. 7 for 12-months analysis
period. Deficit periods under different categories
identified using 24-month averaged SPI suggests that most
of the discrepancies in receipt of rainfall were observed
during first half of the study period, suggesting below-
normal recharge of groundwater and aquifers and resulting
water shortage for household and agricultural needs. SPI
values for 3-month analysis period indicates the drought
of mild and moderate category is a persisting feature in
the district. This suggests that soil moisture might not be
at the optimal level during rainless periods and so there is
a need of improving irrigation facility in all blocks to
ensure availability of supplemental irrigation. Fig. 8
presents the SPI values at 1-month analysis period focused
on monsoon months (June-September). There is again a
cyclic pattern in the excess or deficit in any given month
MAUSAM, 75, 4 (October 2024)
1006
Supplementary TABLE 1
Expected weekly rainfall at 75% probability levels in different blocks of Sundargarh district during the monsoon season.
Expected rainfall at 75% probability level corresponding to SMW
Block
SMW
22
SMW
23
SMW
24
SMW
25
SMW
26
SMW
27
SMW
28
SMW
29
SMW
30
SMW
31
SMW
32
SMW
33
SMW
34
SMW
35
SMW
36
SMW
37
SMW
38
SMW
39
Balisankara
5.6
8
16.9
30.3
31
40.1
53.7
54.7
45.1
47.4
48.9
52.8
39.4
34.5
33.9
25.4
17.9
7.6
Baramunda
6.6
10.4
21.4
33.7
31.6
38.6
53.3
53
46.1
48.6
47.7
52.9
39.3
35.6
35.3
27.8
21.1
9.4
Bisra
7.7
11
20.6
35.4
35.4
40.3
52.8
50.1
46.5
52.1
49.7
55.1
38.7
34.6
31.7
29.1
23.2
9.9
Bonai
7.6
12.2
24.1
36.3
34.7
39
52.3
51.7
47.8
51.6
49.5
55.2
40.4
36.3
36.4
30.6
23.7
10.9
Gurundia
7.6
12.2
24.1
36.3
34.7
39
52.3
51.7
47.8
51.6
49.5
55.2
40.4
36.3
36.4
30.6
23.7
10.9
Hemgir
5.2
7.8
16.8
28.5
28.4
37
53.5
54.5
44.9
42.6
45.8
51.1
38.7
34.8
34.7
25.6
16.9
7.5
Koida
7.6
12.2
24.1
36.3
34.7
39
52.3
51.7
47.8
51.6
49.5
55.2
40.4
36.3
36.4
30.6
23.7
10.9
Kuarmunda
7.7
11
20.6
35.4
35.4
40.3
52.8
50.1
46.5
52.1
49.7
55.1
38.7
34.6
31.7
29.1
23.2
9.9
Kutra
6.6
10.4
21.4
33.7
31.6
38.6
53.3
53.0
46.1
48.6
47.7
52.9
39.3
35.6
35.3
27.8
21.1
9.4
Lahunipara
7.6
12.2
24.1
36.3
34.7
39
52.3
51.7
47.8
51.6
49.5
55.2
40.4
36.3
36.4
30.6
23.7
10.9
Lathikata
7.6
12.2
24.1
36.3
34.7
39
52.3
51.7
47.8
51.6
49.5
55.2
40.4
36.3
36.4
30.6
23.7
10.9
Lephripara
5.2
7.8
16.8
28.5
28.4
37
53.5
54.5
44.9
42.6
45.8
51.1
38.7
34.8
34.7
25.6
16.9
7.5
Nuagaon
7.7
11
20.6
35.4
35.4
40.3
52.8
50.1
46.5
52.1
49.7
55.1
38.7
34.6
31.7
29.1
23.2
9.9
Rajgangpur
6.6
10.4
21.4
33.7
31.6
38.6
53.3
53
46.1
48.6
47.7
52.9
39.3
35.6
35.3
27.8
21.1
9.4
Subdega
7
9.9
19.3
33.4
33.1
40
54.1
52.1
45.5
50.5
49.2
53.2
38.7
34.4
31.7
26.8
21.2
9
Sundargarh
5.2
7.8
16.8
28.5
28.4
37
53.5
54.5
44.9
42.6
45.8
51.1
38.7
34.8
34.7
25.6
16.9
7.5
Tangarpali
5.2
7.8
16.8
28.5
28.4
37
53.5
54.5
44.9
42.6
45.8
51.1
38.7
34.8
34.7
25.6
16.9
7.5
District
6.72
10.25
20.58
33.32
32.48
38.81
53.04
52.51
46.29
48.73
48.29
53.55
39.35
35.31
34.55
28.14
21.06
9.35
in a given block, however, the interval between two
similar cases and their magnitude varied in different years.
This was the case for all blocks.
4. Conclusion
In the present study, long-term mean, variability,
trend of rainfall and rainy days in different categories for
seventeen blocks of Sundergarh district of Odisha have
been analyzed using observed station dataset of 34 years
(1988-2022). Statistics (mean, IAV and CV) of rainfall
distribution at different temporal scales are important
aspects of rainfall climatology. This is especially of
interest to the local governing bodies which can be used as
a tool in planning and designing runoff harvesting
structures, improving irrigation potential of the small
farmers, prepare contingency crop plans for respective
block and raising cropping intensity of the district.
The main conclusions of the present study are as
follows:
(i) Great spatial variability was observed at the block
level: mean annual rainfall varied from 1087 mm
(Subdega) to 1529 mm (Bonai).
GUPTA et. al. : WEATHER BASED WHEAT YIELD PREDICTION USING MACHINE LEARNING
1007
(ii) Annually, rainfall can be considered dependable for
most of the blocks. However, during pre-monsoon, post-
monsoon and winter, CV is very high, so the rainfall is not
dependable. This suggests a need of supplemental
irrigation facility when the farmer plans to grow a second
crop.
(iii) Bulk of annual rainfall received in the district is
contributed by rain events of light to moderate category.
The number of rainy days is showing a significant
increasing trend (in Bargaon, Kuarmunda, Kutra,
Rajgangapur and Tangarpali) and decreasing (in
Lahunipara) trend.
(iv) During the study period, annual rainfall is showing
an increasing as well as decreasing trend in different
blocks. Significantly increasing trend was observed in
Bargaon (14.47 mm/year), Bisra (13.28 mm/year), Hemgir
(12.95 mm/year), Rajgangpur (17.02 mm/year), Subdega
(16.40 mm/year) and Tangarpali. Decreasing and non-
significant trend was observed in Bonai, Lahunipara,
Lathikata, and Sundergarh. Because most of the high
rainfall events are received during SW monsoon, we need
to prepare ourselves with appropriate drainage systems to
redirect runoffs towards reservoir and rivers.
Simultaneously, in blocks where rainfall is showing a
decreasing trend, there is a need to promote water
harvesting at household and community levels to increase
resilience of the society.
(v) Computation of SPI allowed us to establish the
sequence of dry and wet periods during the study period
for the seventeen blocks of Sundergarh. Results indicated
a clear cyclic pattern of dry and wet periods, especially at
lower time scales (3, 6 and 12 months), alternating with
each other. For the district as a whole, SPI values at
different time scales show that drought events were
generally of mild, moderate, severe to extreme intensity.
For 24-months analysis period, frequency of occurrence of
these events were: mild (34% of months); moderate (7.6%
of months); severe (3.3% of months) and extreme (3.2%
of months). Remaining months showed positive SPI
values, and thus corresponded to the wet events.
Acknowledgements
This work is a part of master’s research at Orrisa
University of Agriculture &Technology (OUAT),
Bhubaneswar, Odisha. I acknowledge the financial
support provided by the ICAR during 2016-18 as ICAR-
JRF scholarship at OUAT, Bhubaneswar.
Disclaimer: The contents and views presented in this
research article/paper are the views of the authors and do
not necessarily reflect the views of the organizations they
belongs to.
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