Drought Risk Assessment in Vidarbha Region of

ISSN : 2454-2415 Vol. 6, Issue 10, October, 2018 DOI 11.25835/IJIK-277 www.doie.org

Drought Risk Assessment in Vidarbha Region of Maharashtra, India, Using Standardized Precipitation Index Kumar Daksh1, Varsha Kumari2, Anjani Kumari3 *, Mohit Mayoor4, Harendra Prasad Singh5, Somnath Mahapatra6 1 P. G. Student, Centre for Water Engineering and Management, Central University of Jharkhand Brambe 835205 Ranchi, [email protected] +917070457504 2 P. G. Student, Centre for Water Engineering and Management, Central University of Jharkhand Brambe 835205 Ranchi, [email protected] +917903684686 3 Assistant Professor, Civil Engineering Department, Netaji Subhas Institute of Technology, Bihta, 801118 Patna, [email protected] +918051065073 4 Assistant Professor, Civil Engineering Department, Netaji Subhas Institute of Technology, Bihta, 801118 Patna, [email protected] +917903650061 5 Professor, Centre for Water Engineering and Management, Central University of Jharkhand Brambe 835205 Ranchi, [email protected] +918521937013 6 Scientist-E, Monsoon Mission Phase-II, Indian Institute of Tropical Meteorology, Pune 411008 Maharashtra [email protected] +919860477538 Abstract: Drought is a destructive hazard of nature. It is conceivably the most complex natural hazard. It shows a creeping appearance in nature. The impact of drought varies from region to region. It is difficult to define it in the most generalized way. It originates and crawls due to lack of precipitation over an extended period of time. Worldwide prevalence and duration of drought increases due to climate change and increasing water demands. Thus, the opulence of drought mitigation largely depends upon timely information on drought beginning, operation, and areal extent of drought. These kinds of information are better linked with drought monitoring. Monitoring is performed generally by using various indices. Various drought indices have been developed so far but many of them are region specific and have limitations of applicability in other climatic conditions. Moreover, the presence of multiple time steps in drought indices make it harder to decide the best time step to show the drought conditions. The present study aims to evaluate the Standardized Precipitation index (SPI) at 12 and 24 months timescale using monthly data of precipitation from 1953 to 2002 at eleven districts for monitoring drought years, in the Vidarbha region of Maharashtra, India. The Present study unveils the fact that Vidarbha region is associated with larger number of drought spells. Almost seven to eight numbers of dry periods have been observed in the data set from 1953-2002. Among the 11 districts namely Akola, Amravati, Bhandara, Buldhana, Chandrapur, Gadchiroli, Gondia, Nagpur, Wardha, Washim and Yavatmal, Nagpur is associated with severe drought in most of the years.

Key words: Standardized Precipitation index (SPI), Insidious Hazard, Drought Onset, Monitoring, Drought Spells. I. INTRODUCTION Drought is conceivably the most complex natural hazard or an extreme event as detection of droughts is very much challenging or effortful. It is generally defined as a fugitive meteorological event that stems

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from the lack of precipitation overlong period of time compared with a long-term average precipitation. It creeps slowly with time. The phenomenon is caused due to the uneven rainfall distribution, greater requirement of water than the availability or the combination of both. The drought preparedness and mitigation of drought largely depends on timely information of drought onset, progress of drought and the areal extent of drought. This type of information may be generated through drought monitoring. Monitoring is done through different kinds of drought indices which provide decision makers information on drought severity, frequency and duration which can be used to set-off drought eventuality plan, if they are available. Many drought indices have been developed till date. These include the Palmer Drought Severity Index (PDSI, Palmer, 1965), which is widely used in the United States, the Decile index (Gibbs and Maher, 1967), which is serviceable in Australia, National Metrological Center of China (Wu et al., 2001) uses the China-Z index (CZI), the Surface Water Supply Index (SWSI, Shafer and Dezman, 1982), adopted by several states in the United States and Standardized Precipitation Index (SPI, McKee et al., 1993) etc. SPI has gained worldwide popularity now a days. Most of these indices are calculated using climatic data (mostly rainfall and in some cases temperature such as in (PDSI). A large number of people have affected worldwide due to drought and have caused tremendous economic losses, environmental damage and social hardships. Yet, drought is one of the least understood phenomenon among all other weather phenomena (Obasi 1994). They are onerous to define, monitor and detect (Wilhite 2000). Scientists have developed various indices to monitor droughts.

International Journal of Innovative Knowledge Concepts, 6(10) October, 2018

ISSN : 2454-2415 Vol. 6, Issue 10, October, 2018 DOI 11.25835/IJIK-277 www.doie.org A drought index is said to be useful, only if it provides a simple, clear and quantitative assessment of the major drought characteristics like spatial extent, intensity and duration (Hayes et al. 2000). Standardized Precipitation Index (SPI) is originated by McKee et al. (1993) for assessment of drought in USA, Colorado State. One of the advantages of SPI is that it can monitor dry and wet periods of time scales from 1 to 72 months over a wide spectrum (Edwards and McKee, 1997). By the drought analysis of the southwestern United States and southern plains in the spring of 1996, Hayes et al. (1999) stated that the SPI is a more authentic index of developing drought than the Palmer Drought Severity Index. In India about 330 million people are troubled by drought. Fifty Nine percent of the area in India has received fundamentally less rainfall as estimated by the previous years. In some part of India, the failure of the monsoon results in the water shortage, resulting in below average crop yields. Some of major drought prone regions in India are southern and eastern Maharashtra, northern Karnataka, Andhra Pradesh, Orissa, Gujarat and Rajasthan. It is not possible to predict the onset of drought precisely as it creeps slowly. In addition to it as water requirement varies greatly in different sector it is impossible to state the general drought condition prevailing for the entire sector at once. The definition of drought which is good enough for one field does not help its implementation in another field. However, some broad definitions on different kinds of drought are listed below: Meteorological drought The definition of Meteorological drought is based on the degree of dryness (in comparison to an average amount) and the duration of the dry period. As per Indian Meteorological Department (IMD), the meteorological drought over an area is defined as a condition in which the seasonal rainfall over that area is less than 75 percent of its long term normal. Agricultural drought A situation when soil moisture and rainfall are inadequate during the crop growing season to support healthy crop to maturity, causing crop stress and wilting is termed as Agricultural drought. Hydrological drought The occurrence of Hydrological drought is detectable when the available water in the surface water resources is reduced due to lower than normal precipitation events. Hisdal and Tallaksen, (2003) in

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sighted that the Hydrological droughts are often lagged compared to Meteorological droughts. Socio-economic drought The socio-economic drought is associated with the failure of water resources system to meet the socioeconomic water demands and with the insufficient supply of water and demand for an economic good. Social impacts of drought predominantly involve public safety, health, conflict between water users, reduced quality of life and inequalities in the distribution of disaster relief goods. Vidarbha is a region of the Indian State of Maharashtra. This region of Maharashtra has faced several droughts in the past. Vidarbha is a inland region. As far as the climatology of Vidarbha region is concerned, it is under the influence of southwest monsoon. When southwest monsoon reaches in western coast in the month of June, heavy rainfall occurs in its western coasts but as rainfall decreases from west to east. So, when it reaches Vidarbha region, the average rainfall becomes scanty. Agriculture was worst affected in Vidarbha. It is very painful to observe that food grain output grew very low percent per annum which was far below the growth of population for a long time (Sonawane, 2017). The living condition of farmers in this region is drastic compared to other regions of Maharashtra. Maharashtra has the highest rate of suicide especially in the Vidarbha region, it is one of the most troubled regions of the country and in the recent years there have been reports of numerous agrarian crisis induced suicide in this region (Sonawane, 2017). In India the number of farmers committed suicides during 1995-2015 is 308798 while in Maharashtra 66546 farmers committed suicide for the same period (Sonawane, 2017). In India Maharashtra takes the first place in farmer suicide, while Vidarbha region is at the top in Maharashtra (Sonawane, 2017). The Standardized Precipitation Index (SPI) is very effective and proficient tool for monitoring and it is broadly accepted and used throughout the world by various researchers for investigate and explore operational mode of SPI, because it normalizes both location and time. This standardization allows the SPI to determine the rarity of a current drought event (McKee et al., 1993). At any location SPI is allowed to be computed and at any time steps, depending upon the impacts of interest to the user. So, the present study focused on monitoring the drought event on the basis of rainfall using Standardized Precipitation Index (SPI) in the Vidarbha region of Maharashtra.


ISSN : 2454-2415 Vol. 6, Issue 10, October, 2018 DOI 11.25835/IJIK-277 www.doie.org III. MATERIALS AND METHOLOGY STUDYAREA:

Fig.1 Location Map of Vidarbha region of Maharashtra, India. In Maharashtra Vidarbha is one of the most Drought affected region. Nagpur and Amravati is two of the important divisions of Vidarbha. Border of Vidarbha touches Madhya Pradesh to the north, Telangana to the south, Chhattisgarh to the east and Marathwada and Khandesh region of Maharashtra to the west. The largest city of Vidarbha is Nagpur. Vidarbha Region comprises of an area of 97321km2 and population of 23003179 according to 2011 census of India. Figure 1 shows eleven districts of Vidarbha which include Akola, Amravati, Buldhana, Bhandara, Chandrapur, Gadchiroli, Gondia, Nagpur, Yavatmal, Washim and Wardha. Vidarbha is drought prone region and it is a part of scanty rainfall area of eastern Maharashtra. This region of Maharashtra has faced several droughts in the past. Vidarbha is a inland region. The entire region is drained by Wainganga River along with its tributaries. Most of its tributaries e.g. Wardha, Kanhan and Painganga etc. are not perennial. Its water flows south into the Godavari River. They carry water only during rainy season. As the summer approaches they become dry. Major dams have been constructed in the Vidarbha region e.g. Nand in Nagpur, Pujaritola and Kalisarar in Gondia, Dina in Gadchiroli, Bembla in Yavatmal, Katepurna in Akola and Pentakli in Buldhana. Most of the time these reservoirs get dried up due to less rainfall in the Monsoon. DATA USED: The monthly precipitation data from 1953-2002 has been used as an input parameter for the computation of SPI. The data is taken from India

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Water Portal (IWP). The excel spread sheet has been used for the computations of indices at different timescales and the graph is plotted with the help of Microsoft Excel. RAINFALL DISTRIBUTION: If the rainfall pattern over Vidarbha region is examined precisely, spatial as well as temporal distribution can be visualized. Over the regions like Gondia and Bhandara highest precipitation value is recorded in the year 1995, 1994 approximately as 730mm. In the same way regions like Akola, Amravati, Buldhana, Chandrapur, Gadchiroli, Nagpur, Wardha, Washim and Yavatmal are examined, highest precipitation values are recorded in the year 1970, 1974, 1983, 1994, 1995, 1994, 1972, 1997 and 1959 respectively. Most of the years can be seen over these districts covering Vidarbha region with almost no or scanty rainfall. These years are primarily associated with drought years. Statistical average will not give the correct measure for the amount of precipitation occurring over the Vidarbha regions as these regions are associated with lots of fluctuation as far as rainfall pattern is concerned. This is the main reason behind promoting the use of Index for monitoring extreme events as index like SPI uses normalized precipitation value. Figure (2-7) shows the rainfall variability in Vidarbha region. The distribution of rainfall can be accessed from the figure.



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Standardized Precipitation Index (SPI) Calculation of SPI encompasses the transformation of one frequency distribution to other. The gamma density Probability Function is best fitted for Climatological data like Rainfall (Thom, 1966). So the computation involves fitting a gamma distribution function (Abramowitz and Stegun, 1970) as a probability density function (PDF) of precipitation aggregates for the given station. The PDF is then used to find cumulative probability of observed precipitation for required temporal scales (1, 3, 6, 9, 12, 24, 48 & 72 months). As it is seen earlier, statistically the rainfall distribution hardly follows the normal distribution curve so the data

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needs to be normalized. The procedure of normalization is called Equi-probability transformation (Panofsky and Brier, 1958). Now the cumulative probability according to the distribution and for each value of the precipitation is then transformed to the standard normal random variable Z with a mean of Zero and standard deviation of unity, which gives the value of SPI (McKee et al. 1995 and Kumar et.al., 2009). Table 1 (Source: McKee et al., 1993) shows the different conditions with SPI values. In the Table 1, values greater than zero shows surplus water and less than zero shows water deficit. Table. 1. Values of SPI with description



SPI VALUES 2.0+ 1.5 to 1.99 1.0 to 1.49 -0.99 to 0.99 -1.0 to -1.49 -1.5 to -1.99 -2 and less

CONDITION OF DROUGHT AND FLOOD Extremely wet Very wet Moderately wet Near normal Moderately dry Severely dry Extremely dry

IV. RESULTS AND DISCUSSIONS Droughts are always associated with longer dry spells i.e. droughts are expected to occur in the years which are counted under long dry spell years. The SPI at 24 months time scale shows the long-term precipitation patterns. These longterm SPI’s like SPI-12 & SPI-24 are the associative analysis of the shorter periods that

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may be above or below normal so they mostly tend to produce Zero unless a distinctive wet or dry period is observed. Through the analysis of SPI- 24 longer spell of distinctive dry and wet region is obtained. SPI-12 under takes 12-month precipitation data at once and compares with aggregated 12-month precipitation values recorded for the same month in the past for considered data set. It is also a long-term precipitation record but has higher number of fluctuations recorded as compared to SPI- 24 as it aggregates lesser months. These longer SPI’s are used for the analysis of availability of water in different water resources. Figure 8 to 18 shows the SPI-24 and SPI-12 plot of all the11 districts of Vidarbha region namely Akola, Amravati, Bhandara, Buldhana, Chandrapur, Gadchiroli, Gondia, Nagpur, Wardha, Washim and Yavatmal respectively.



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If figure 8(a) is observed precisely, it can be seen that SPI- 24 plot of Akola district right from 1953 to 2002 asserts six predominant dry cycles out of which two of them are having extremely high negative value greater than -2 (1991-1995 and 20012002). Observed drought spells are 1953-1954,

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1964-1968, 1972-1973, 1987-1989, 1991-1995 and 2001-2002. Spatial distribution or differences can be stated from the fact that there are many differences in the index value of SPI plot for the same period for different regions. This fact can be cleared from the observation of figure 8(a) to 18(a). In the same way


ISSN : 2454-2415 Vol. 6, Issue 10, October, 2018 DOI 11.25835/IJIK-277 www.doie.org Figure 9(a) to 18(a) represents 5, 4, 4, 3, 4, 5, 2, 5, 3 and 4 significant drought spells of Amaravati, Bhandara, Buldhana, Chandrapur, Gadchiroli, Gondia, Nagpur, Wardha, Washim and Yavatmalrespectively with moderate as well as severe drought spells. Period of 1972-1973, 19871989, 1991-1995 and 2001-2002 are drought spell for almost every district of Vidarbha region. By the observation of SPI-12, Fig 8(b) – 18(b) several other drought years have also been observed in addition to those listed in drought spells by SPI24. SPI-12 plot of Amravati Fig. 9(b) shows the extreme drought spells of 1987-1988, 1992-1993 and 2001-2002 and moderate drought years of 19531954, 1966-1967 and 1980-1981. SPI- 12 plot of other districts has almost followed the same trend of drought with other drought years from 1972-1973, Fig18(b) for Yavatmal, 1965-1966 for Washim Fig 17(b). Figure 15(b) shows the SPI-12 plot Nagpur region. As per the analysis Nagpur had Extreme drought event in 1953-1954, 1972-1973 and 19911992. Under these spells index values surpassed the value of -2. The proposed study however does not focus on the Standardized Precipitation Index Value at 9-month time scales, 6 months’ time scale, 3 month time steps

and 1-month time step. As per the analysis of McKee et al. 2003, drought monitoring does not yield better result when analyzed at 1month time step, 3month time step, 6month time step etc. The most possible reason is that drought is a creeping phenomenon. It creeps slowly and stays for longer duration sometime for more than 5 years even. As it is an event of longer spell so it is not suggested to monitor drought using 3 or 6-month time steps. V. CONCLUSIONS SPI is a powerful as well as flexible tool to monitor drought at different time scales precisely. Based upon the present study it was observed that 5 to 6 number of drought years are associated within the 11 districts of Vidarbha region. Akola district has maximum number of dry spells. It has almost seven number of drought spells. Nagpur region has shown severe drought with index value almost equal to -3 in the years 1991-1992, 1971-1972 and 1953-1954. It was concluded that it is better to monitor drought at higher month time steps as drought is a prolonged phenomenon and stays for longer duration. The Present work assesses the drought accurately which will help farmers to take necessary steps well in advance.

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