Temporal and Spatial Analysis of Drought over a Tropical Wet Station of India in the Recent Decades Using the SPI Method Keerthi Sasikumar 1 and Dr. Venu G.Nair 2 1 Department of Atmospheric Sciences, Cochin University of Science & Technology, Kerala, India, 2 Centre for Earth Research and Environment Management, Kochi- 36, India Abstract We have carried out the drought analysis over Kerala, a tropical wet station, using the Standardized Precipitation Index for a period of 30 s (011).Monthly precipitation data of 9 districts were taken into consideration for drought study and also to create drought severity maps using GIS. From the analysis we have found that homogenous drought conditions are not prevailing over Kerala whether it is agriculture drought or hydrologic drought. It is observed that the frequency of occurrence of mild drought is more than severe and extreme droughts except in the northern and southern most tips of Kerala. Short term and long term analysis shows that more droughts are prevailing after onwards in the region, which can be interpreted in different ways for the better planning of water and agriculture management. Keywords: SPI, Meteorological Drought, Hydrological Drought, Agriculture Drought I. INTRODUCTION A drought is a natural phenomenon that has significant social, economic and environmental impacts. It is difficult to give a precise definition of drought due to its varying characteristics region by region. Drought can be considered as a prolonged period of water scarcity in a given region. It develops slowly and its impact may remain for s after termination of the event. It is difficult to predict drought prior to its onset. Usually drought occurs due to deficiency of precipitation resulting in water shortages. Drought impacts are first seen in agriculture and then slowly move towards water resources. The Indian national commission on agriculture (1978) has categorized drought into three types, which are as under: A. Meteorological drought B. Hydrological drought C. Agricultural drought Kerala is a state in the southern Peninsular India, which receives copious rainfall from both Southwest and Northeast Monsoon events extending from June to December in any. Due to the strong intra-seasonal as well as low frequency variability exhibited by the Indian monsoon, the availability of this rainwater varies widely across the region thus eventually putting the agricultural activity in a havoc condition especially the coconut and other plantation crops of the Western Ghats region. In this context a detailed analysis of the distribution of drought in the spatial and temporal domain over the region with the help of a widely used method of Standard Precipitation Index (SPI) is an essential exercise to map the drought affected areas of the study region. McKee et al. () developed the Standardized Precipitation Index (SPI) for the purpose of defining and monitoring droughts.spi is calculated from the long term record of precipitation in each @IJAPSA016, All rights Reserved Page 12
International Journal of Applied and Pure Science and Agriculture (IJAPSA) location (at least 30 s). Technically, the SPI is the number of standard deviations that the observed value would deviate from the long-term mean, for a normally distributed random variable. The SPI was designed to quantify the precipitation deficit for multiple time scales. (McKee et al., ) originally calculated the SPI for 3, 6, 12, 24, and 48 month time scales. The short term time scales which is 3 and 6 months SPI s have great impact on Meteorological and agricultural droughts. The long term time scale which are 12-month SPI or more are associated with hydrological droughts which have an impact on stream flow and reservoir levels. The short term durations are important for agricultural planning while long terms are important for water supply management interest. The 3-month SPI provides a comparison of the precipitation over a specific 3-month period with the precipitation totals from the same 3-month period for all the s included in the historical record For instance, a 3-month SPI for June uses the precipitation total of April, May and June in that particular. A 3-month SPI reflects short and medium-term soil moisture conditions and provides a seasonal estimation of precipitation. Since it gives an account of agriculture drought, it will help in better planning in crop planting. What could be a drought condition for the cultivation of rice could well be a suitable condition for wheat and a condition of excess soil moisture for dry crops like bajra or jowar. Similarly the 6, 12 and more time scales compares the precipitation for that period with the same 6, 12 or more period over the historical record. The 6-month SPI can be effective in showing the variation of precipitation s over various seasons. The 12 month SPI reflect long-term precipitation patterns and is associated with hydrological droughts probably related to water reservoirs, stream flows, groundwater levels. 2.1 Study area II. MATERIALS AND METHODS Kerala (10.8505 o N, 76.2711 o E, 38,863 km 2, 1.18% of India s landmass) is situated at the southern tip of Deccan plateau which lies across Arabian Sea to the west and Western Ghats to the east. Kerala is having a coastline of about 700 km in length, while the state itself varies between 3520 km in width in the east-west direction between sea and mountain. For the study, we have taken the monthly precipitation data of these 9 districts of Kerala. Figure 1. Map of the Study Area @IJAPSA016, All rights Reserved Page 13
International Journal of Applied and Pure Science and Agriculture (IJAPSA) 2.2 Methods Monthly precipitation data for each station was taken from IMD and KDWR for a period of -. The SPI for 3-month, 6-month, 12- month and 24- month time scales were calculated for each station from a period of 011. Obtained SPI values are then classified further according to drought classification given by WMO for drought. (Table 1) Table 1:- SPI and drought classification SPI VALUES CLASSIFICATION 2+ Extremely wet 1.5 to 1.99 Very wet 1.0 to 1.49 Moderately wet -0.99 to 0.99 Near normal/ mild dry.0 to.49 Moderately dry.5 to.99 Severely dry and less Extremely dry III. RESULTS 3.1 Temporal variation of drought across Kerala Since Kerala is under the southwest monsoon activity from the month of June itself, the calculation started from June to December i.e. up to the northeast monsoon period. The value of 3-month SPI up to the month of August and 6-month SPI up to the month of November has been found out. The results are given in the figures below.(fig 2 to Fig 10 ).Blue colour represents 3 month SPI value up to the month of August and red colour represents 6 month SPI up to November starting from the month of June. The northern stations of Kerala (Kannur, Kozhikode, Malappuram, Palghat) show almost similar patterns throughout the period. SPI values.5.5 KANNUR Figure 2. SPI values for Kannur station From the to, there was extreme wet condition prevailed over this station but the next 10 s ( to ) was moderately dry at the same place. Only once during the, the station was under severely dry condition. The same pattern was seen in the adjacent station Kozhikode also. The moderately dry condition was prevailing consistently from the to. @IJAPSA016, All rights Reserved Page 14
International Journal of Applied and Pure Science and Agriculture (IJAPSA).5.5 KOZHIKODE Figure 3. SPI values for Kozhikode station Malappuram is an exception in the northern districts. The dryness during the beginning of this century was absent in the station. More than that, this station shows extremely wet condition during which was notable point. In Palghat of course another phenomena was noticed during the same period. It is found that the moderate drought condition was extending to the end of the first decade of this century ( to ) and the strength also changes from moderately dry to extremely dry condition at the beginning of the second decade of the century ()..5.5 MALAPPURAM Figure 4. SPI values for Malappuram station.5.5 PALGHAT Figure 5. SPI values for Palakkad station When we analyse the central Kerala stations, Ernakulam shows an unusual near normal conditions during the end of 20 th century. Before and after this period a see-saw type variation can be seen in the SPI values. Near normal condition were visible from onwards in the adjacent station Kottayam with an extreme drought condition in. @IJAPSA016, All rights Reserved Page 15
International Journal of Applied and Pure Science and Agriculture (IJAPSA) ERNAKULAM.5.5 Year Figure 6. SPI values for Ernakulam station.5.5 KOTTAYAM Figure 7. SPI values for Kottayam station Alappuzha also follows a sinusoidal pattern, but not with the severity as in the northern Kerala stations. The was extremely dry and was extremely wet over this station. 3 2.5 2 1.5 1 0.5 0-0.5.5.5 ALAPPUZHA Figure 8. SPI values for Alappuzha station @IJAPSA016, All rights Reserved Page 16
International Journal of Applied and Pure Science and Agriculture (IJAPSA).5.5 KOLLAM Year Figure 9. SPI values for Kollam station For Kollam, mostly arid conditions prevailed throughout the study period except a small period of to. The same pattern of variation of Aridity over Palghat can be visible over this station also. But the strength of the drought is not severe as of Palghat. The shows extremely wet over the station in the entire study period..5.5 TRIVANDRUM Year Figure 10. SPI values for Trivandrum station Trivandrum also shows wet and dry conditions randomly during these s. But a notable point is that whenever this station showed a moderate to severe dry conditions during the southwest monsoon period, during the same northeast monsoon is dragging this station to moderate wet conditions. This is quite visible during the s and. 3.2 Importance of temporal variations of 3, 6, 12 and 24 months SPI values To understand the importance of temporal variation of different SPI values in any station, we have analysed 3, 6, 12, 24 months SPI over Ernakulam as a sample. (Fig 11) The most important characteristics of drought is the change in drought frequency as the time scale changes.(fig 11) In shorter time scales, drought becomes more frequent, but lasts for shorter duration while in longer time scales,drought occurs less frequently but it lasts for longer duration. Both cases (more droughts but shorter duration and fewer droughts for longer duration) can be interpreted differently for different water resources. For example, soil moisture at Ernakulum can be sensitive to a 3month drought whereas it may take a longer time scale to see the effect of drought on underground water resources. Similarly a 6month drought for the cultivation of rice can be suitable for the cultivation of wheat, thus helping us to plan accordingly. @IJAPSA016, All rights Reserved Page 17
International Journal of Applied and Pure Science and Agriculture (IJAPSA) 3 month SPI 6month SPI 3 2 1 0 3 2 1 0 12 month SPI Figure 11. Temporal variations of SPI at varying time scales in Ernakulum station 3.3 Short term and long term frequency analysis Results of the short term and long term drought frequency analysis in Kerala are shown in Table 2 and Table 3. From the short term frequency analysis we can see that mild droughts are more recurring in this station (more than 30%). Moderate and severe categories are less frequent and its values go below 10%. By identifying the critical stations, a short term measures can be suggested for those areas to fulfil the agricultural requirements, attaining optimum soil moisture and reducing agricultural drought vulnerabilities. It is good to take proper measures early in response to mild drought which may turn into severe droughts on longer time scales. Thus short term analysis shows that, generally there is a higher probability of occurrence of mild droughts than moderate or severe droughts to occur in majority of the districts of the state. Since short term analysis gives us an account of agriculture drought, we can give advice to the agriculture sector for planning of proper crop management. Table 2:- Short term frequency analysis Types of drought Range of SPI values 3month SPI frequency (%) 6month SPI frequency (%) Mild Drought -0.9 to -0 33.699.89 31.8-33.96 Moderate drought.0 to.49 7.82-8.09 7.01 8.36 Severe drought.5 to.99 3.23 3.50 3.50-4.04 Long term analysis also shows more mild cases of drought persisting over the study area (about 35%). Then moderate droughts with about 8-9% are also seen. The possibility of occurrence of severe drought is meagre in this area. It is observed that there is a probability of hydrological drought.5.5 24 month SPI @IJAPSA016, All rights Reserved Page 18
International Journal of Applied and Pure Science and Agriculture (IJAPSA) and depletion of ground water, stream flow in the critical areas. Thus, there is a prior need to adopt water conservation and management practices in those areas. Table 3:- Long term frequency analysis Types of drought Range of SPI values 12month SPI frequency (%) 24month SPI frequency (%) Mild Drought -0.9 to -0 35.04 49.60 35.04 40.43 Moderate drought.0 to.49 6.74 9.97 8.09 10.24 Severe drought.5 to.99 2.13 2.70 1.62 5.29 3.4 Spatial distribution of drought Over Kerala, the SPI values for 3 months have been analyzed through contour analysis using GIS. (Fig 12) This type of analysis will clearly help to identify the hot spots of drought in the study region. Thus, we have identified Palghat and Alappuzha as the drought hot spots where severely dry conditions are prevailing during the study periods. Kochi is showing sufficient wet conditions while in Kozhikode it is near normal condition. But 6 months SPI indicates a different picture. (Fig 13) Here in the extreme northern and southern Kerala stations (Kannur and Trivandrum) show moderately dry conditions other than the Palakkad and Alappuzha stations. In the 12 month SPI calculation, the result is going towards some extreme value towards wet. (Fig 14)Extremely wet and moderately wet conditions are prevailing over Kochi and Kozhikode in this analysis. This may be attributed to increase of rainfall activity during the non-monsoon months in these stations. But in contrast, north and south Kerala is changing from Moderately Dry conditions to Severely Dry conditions in the 12 month SPI analysis. @IJAPSA016, All rights Reserved Page 19
International Journal of Applied and Pure Science and Agriculture (IJAPSA) Figure 13. SPI Analysis for 6 Months for Kerala during Figure 14. SPI Analysis for 12 Months for Kerala during IV. DISCUSSIONS The study provides a comprehensive knowledge of spatio - temporal extent of droughts over Kerala during the period -. More studies are required to understand the heterogeneous behaviour of drought over the region. The major findings evolved from this study are as follows: A. Even though it is a small state in India, homogeneous drought conditions are not prevailing over Kerala whether it is in the case with Agriculture drought or Hydrological drought as we expected. @IJAPSA016, All rights Reserved Page 20
International Journal of Applied and Pure Science and Agriculture (IJAPSA) B. It is found that only Palghat and Alappuzha stations in Kerala showed severe hydrological drought conditions while agriculture drought is moderate in these stations.palghat has shown moderate to severe drought once in two s. C. From onwards there is an increase of occurrence in Agricultural droughts events in Kerala with exception over Malappuram Station. D. From the frequency analysis, it can be seen that generally mild drought are more prevailing over Kerala than Severe and Extreme droughts with exceptions in the northernmost and southernmost stations. E. Short term analysis shows the loss of soil moisture rapidly over the region and it requires short term measures like good irrigation system, and crop rotation for the critical areas to enhance the agriculture activity. F. Similarly the long term analysis reflects the impacts of droughts on stream flow and other surface water resources. This is a concern in the extreme north and south stations in the study area. Hence proper conservation and management system and also the recharge capacities should be developed in those areas. V. FUTURE SCOPE Thus SPI can be utilized effectively to give advice to many Agricultural and Water Management Authorities. By identifying the drought prone area, we can plan accordingly in the agriculture and water management sector. Thus by studying drought over any region, we can take appropriate steps to avoid the severe impacts of droughts and may forecast the onset of droughts. BIBLIOGRAPHY 1. Domonkos P, () Recent Precipitation Trends in Hungary in the Context of Larger Scale Climatic Changes, Natural Hazards, 29: 255 271. 2. Hayes, M. J., Svoboda, M. D., Wilhite, D. A., and Vanyarkho, O. V, (), Monitoring the drought using the standardized precipitation index, Bull. Amer. Meteorol. Soc. 80, 429 438. 3. Hughes Lloyed, Saunders A., () A Drought climatology for Europe International Journal of climatology, 22: 1571 1592 4. Karavitis A., Alexandris Stavros, Tsesmilis E., Athanasopoulos G() Application of the Standardized Precipitation Index (SPI) in Greece, Water, 3, 787-805 5. Lana X.,Serra C.,Burgueno A. () Patterns of monthly rainfall shortage and excess in terms of the standardized precipitation index for Catalonia ( NE Spain) International Journal of climatology, 21: 1669 1691 6. Min Seung - Ki,Kwon Won-Tae,Park E-Hyung,Choi Youngeun() Spatial and temporal comparisons of drought over Korea with East Asia, Inetrnational Journal of climatology 23: 223 233. 7. Palmer WC (1965), Meteorological drought, Weather Bureau Research Paper, 45,58pp. 8. Rachchh Rahul, Bhatt Neelkhant, (2014) Monitoring of Drought Event by Standard Precipitation Index (SPI) in Rajkot District, Gujarat, India International Journal of Engineering Development and Research,2 : 2321-9939. 9. Seiler R. A, Hayes M, Bressan L, () Using the standardised precipitation index for flood risk monitoring,international Journal of climatology, 22: 1365 1376. 10. Sharma D and N Mundetia (2014) Analysis of rainfall and drought in Rajasthan State, India, Global NEST Journal, Vol 17, No 1, pp 121. @IJAPSA016, All rights Reserved Page 21