Dry spell analysis for effective water management planning

Transcription

1 by the authors Licensee IJASER- Under Creative Commons License 3.0 Research article ISSN Dry spell analysis for effective water management planning Kandasamy P, Chellamuthu M. Post graduate student, Tamilnadu Agricultural University, Tamilnadu doi: /ijaser Abstract: Knowing the dry and wet periods with rainy seasons is essential for successful water management planning in any particular area. With this view, this study analyzed the thirty years ( ) monthly rainfall data of Udumalpet station located in Parambikulam Aliyar sub basin (Tamilnadu) on annual, seasonal and monthly basis for planning a suitable water conservation management system. Sixty two per cent of the total rainfall is received from North East Monsoon and seventeen per cent from South-West Monsoon. In the study period, four years were found to be wet, four years were found to be dry and the remaining twenty two years were found to be normal years. The analysis showed that the annual and seasonal rainfall data did not clearly indicate the problem of drought in the region; whereas the monthly rainfall data indicated serious concerns to deal with drought particularly during the winter and summer months. It also revealed that the winter months were the most susceptible to severe drought conditions. Out of 30 years of study, January and February were found to be the dry months which normally facilitate for the good harvest of the kharif sown long duration crops. There is a need to adopt adequate moisture conservation measures like mulching etc. to mitigate the effect of drought spells during critical periods of crop growth, and to construct water harvesting ponds/tanks for application of pre-sowing irrigation to Rabi (winter) crops, and supplemental irrigation during periods of water scarcity. Keywords: Dry spell, wet spell, monthly rainfall analysis, water management and probability analysis. 1. Introduction Rainfall is considered as principle source of water. The success or failure of crops particularly under rainfed conditions is closely linked with the rainfall patterns. The important characteristics of rainfall influencing production from rainfed farming are the duration of wet spells and durations of intervening dry spells. Rainfall during the monsoon is not uniform. Frequent dry spells are common phenomena during the monsoon season. In rainfed agriculture, the adequacy of rainfall to meet the water requirements of crops and other consumptive and non-consumptive water needs is a basic requirement. The annual and seasonal analysis of rainfall will give general idea about the rainfall pattern of the region, whereas the monthly analysis of rainfall will be of much use as far agricultural planning is concerned. The spatial and temporal variability of rainfall and its uneven and inadequate distribution determines the failure of crops especially in drought prone areas. Knowledge of the distribution of dry spells during the monsoon period is essential for successful rainfed farming. It is also important to know the chances of occurrence of dry spells during the critical stages of the crops for deciding the sowing date, cropping pattern and planning for protective irrigation and intercultural operations. With this view in mind, dry spell analysis was done for Udumalpet station and presented in this special problem report. Tiwari et al. (1988) analyzed the rainfall data of Bundelkhand region for estimation of drought and concluded that water harvesting through the embankment cum- dugout pond on ephemeral streams would 127 *Corresponding author ( kandasamy004@gmail.com) Received on, Jan 2012; Accepted on Feb. 16, 2012; Published on Feb. 24,2012

2 be needed to solve the problem of drought in the region. Tomar et al. (2001) presented the analysis of drought, dry and wet spells at Chhindwara in Madhya pradesh, and suggested sowing of short duration varieties in kharif season for enhancing production. Taley,S.M, Dalvi,V.B., presented the dry - spell analysis for studying the sustainability of rain - fed agriculture in the Vidarbha region of Maharashtra. Anil Kumar., investigated the occurrence of meteorological drought for sustenance of agricultural productivity in Hilly areas of Uttarakhand. Sahoo D.C., presented the rainfall probability analysis for efficient water harvesting and crop planning for Nilgiris and concluded that water harvesting structures need to be adopted in monsoon season. 2. Materials and Methods The Udumalpet station in located at an elevation of 120 m above mean sea level in the PAP basin lies between ' 00" N latitude and ' 00" E longitude in Tamilnadu. The climate of this station is sub-tropical to sub-temperate with a mean maximum temperature of 39 C and mean minimum temperature of 15 C. Station receives most of the precipitation during north-east monsoon. The mean annual precipitation at Udumalpet station is mm. Major crops cultivated in this area are coconut, tomato, maize, onion, etc. Monthly rainfall data ( ) recorded at Udumalpet rain gauge station was taken for this study. The data were then calculated on seasonal and annual basis. The monthly events of thirty years were then classified as drought, normal and wet events depending upon the following criteria (Sharma and Ram,1978; Singh et al.2002 and Pandey et al.2002). If N is the normal monthly rainfall, then a month receiving rainfall less than half of N is termed as drought month. On the other hand, a month receiving rainfall more than 2N is termed as wet month. Also, if P is the mean annual rainfall and Q is the standard deviation then a year is said to be drought, normal and wet if it receives rainfall less than P-Q, in the interval [P-Q,P+Q] and more than P+Q, respectively (Bora et al., 2008). Standard deviation was calculated by using the formula below. Where n is the number of observations, ì is the mean, and x i the i th value Classification of annual, seasonal, monthly and weekly rainfall The annual, seasonal and monthly rainfall values were determined to determine drought occurrences during each period. Based on the following criteria given by Sharma et al. (1987), annual, seasonal and monthly rainfall events were classified as dry, normal and wet. 1 A year receiving rainfall less than or equal to average annual rainfall minus standard deviation is called a drought year; a year receiving rainfall more than or equal to average annual rainfall plus standard deviation is called a wet year; and a year receiving rainfall between the limits of annual rainfall corresponding to drought and wet year is called a normal year. 2 A season receiving rainfall less than or equal to average seasonal rainfall minus standard deviation is called a drought season; a season receiving rainfall more than or equal to average seasonal rainfall plus standard deviation is called a wet season; and a season receiving rainfall between the limits of seasonal rainfall corresponding to drought and wet seasons is called a Kandasamy P, Chellamuthu M 128

3 normal season. 3 A month receiving rainfall less than or equal to 50% of average monthly rainfall is called a drought month; a month receiving rainfall more than or equal to 200% of average monthly rainfall is called a wet month; and a month receiving rainfall between 50% and 200% of average monthly rainfall is called a normal month Drought classification based on IMD criteria Meteorological droughts were classified following India Meteorological Department (IMD) criteria as "moderate", "severe" and "extreme" droughts based on the departure of actual rainfall of duration from the normal or mean rainfall value of the available data. If the departure ranges between 25 and 50% of the normal value, it is called moderate drought; if the departure ranges between 50 and 75%, it is called severe drought; and if the departure exceeds 75% of normal value, it is termed as extreme drought Probability analysis of rainfall Weibull s formula was used to determine the probability of exceedence at various levels, such 20%, 40%, 60%, 80% and 90% for all months, seasons and years, as given below: P = m / (N+1) Where, P is probability of exceedence; m is rank of rainfall magnitude arranged in descending order, and N is Total number of rainfall data. The probability level of 80% is considered as dependable without risk; where 50% level is associated with 50% risk and 20% is very risk from the crop point of view (Anil Kumar., 2009). 3. Result and Discussion The annual, seasonal, and monthly rainfall patterns have been numerically categorized as drought, normal and wet. The moderate, severe and extreme meteorological drought conditions have also been analyzed based on IMD criteria Analysis of annual rainfall pattern The variations in the annual rainfall pattern are shown in the Figure 1. The analysis of annual rainfall indicated that the mean annual rainfall of Udumalpet station is mm. The standard deviation was found to be 88.6, which is shown in Table 1. Kandasamy P, Chellamuthu M 129

4 Figure 1: Variations in the annual rainfall ( ) Hence, the years receiving rainfall less than mm can be termed as drought years and the years receiving rainfall more than mm can be termed as wet years. Out of 30 years ( ), Udumalpet encountered 4 drought years, 4 wet years during the period and the remaining period received normal rainfall. Table 2 shows that during the study period the station experienced 22 normal years, 4 drought years and 4 wet years. The variation in annual total rainfall is shown in Fig. 1. The worst drought year was experienced during the year 1975 with mm rainfall and the wettest was experienced during the year 1993 with 1238 mm rainfall. Out of 30 years seven years were found to be under moderate drought and two years under severe drought. Table 1: Monthly mean rainfall (N), standard deviation (SD), normal (N), dry (D), and wet (W) in the study period Month Mean PN, PW, PD, SD N/2 2N Normal Wet Dry (N) % % % January February March April May June July August September October November December Analysis of seasonal rainfall pattern Variations in the average seasonal rainfall for study period are shown in Fig 2. The mean for winter, summer, South-West and North-East monsoon are mm, mm mm and ; standard deviations 56.55, 70.48, and mm ; and coefficients of variation %,62.22%, and 46.13%, respectively. The winter season receives the lowest rainfall followed by summer and monsoon seasons (Fig. 2). As is evident from Table 3, the contribution of mean seasonal to mean annual rainfall is 4.06, 15.77, 17.2, and 62.9 percent for winter, summer, South-West and North-East monsoon seasons, respectively. On an average, the occurrence of drought, normal and wet seasons was 20, and percent, respectively. This indicates that seasonal distribution of rainfall pattern is generally normal, and the possibility of seasonal drought is the least. This indicates more dependence on assured irrigation during winter season. The possibility of monsoon drought is the least; and the chances of winter and summer droughts are twice and thrice as great as those of monsoon drought, respectively. Therefore, on seasonal basis, better moisture conservation measures should be adopted for summer crops as compared to Kandasamy P, Chellamuthu M 130

5 winter crops. Figure 2: Variations in the average seasonal rainfall ( ) This indicates that assured irrigation should be applied to raise pre-monsoon crops successfully. Table 2: Monthly, seasonal and annual rainfall analysis for Udumalpet station Month/ Number of month/season/year season predicted as Drought Normal Wet January February March April May June July August September October November December Winter Summer South west North east Annual As evident from the Table 2, the number of drought events is more than that of wet events for all the months. The drought events are more than normal for January, February, March and August months, which indicate that there, are more chances of drought during winter and summer seasons. On an average, the occurrence of drought months receives no rainfall at all. Therefore, occurrence of drought becomes more apparent when analyzing the monthly rainfall data as compared to long-term (seasonal or annual) data. Precautionary measures of moisture conservation should be adopted during winter season experiencing the Kandasamy P, Chellamuthu M 131

6 most drought events Analysis of Monthly rainfall pattern Figure 3: Variations in the average monthly rainfall ( ) Table 3: Total rainfall in different seasons ( ) Year S.W N.E Winter Summer Kandasamy P, Chellamuthu M 132

7 Mean SD CV Mean and standard deviation of monthly rainfall for the period of 30 years are Presented in Table-1, where PD: % of dry month, PN: % of normal month, PW: % of wet month. From the data it is evident that October and November received highest rainfall followed by December. For the entire 30 years period maximum dry months were recorded from January to March and August. Table 4: Identification of months falling under moderate and severe meteorological droughts Month Moderate drought Severe drought Extreme drought No Year No Year No Year 1975, 1976, 1977, 1978, 1979, 1981, 1982, 1986, January , , , 1988, 1990, 1991, 1992, 1993, 1998, 2001, 2002, 2003, 2004 February , , 1976, 1977, 1979, 1980, 1981, 1982, 1984, 1986, 1987, 1988, 1989, 1990, 1991, 1993, 1994, 1996, 1997, 1998, 2000, 2001, 2002, 2003, , 1976, 1977, 1979, 1981, 1982, 1984, 1986, March , 1990, 1991, 1992,1993, 1995, 1997, 1998, 1999, 2003 April , 1989, 1990, 1977, 1981, 1982, 1983, , 1978, , 1999, , 1991, 1992, 2001 May , 1989, 1997, 1977, 1985, 1990, , , , 1983, 1984, 1998 June , 1986, 1989, 1978, 1980, 1982, 1977, 1985, 1990, 1995, July , 1985, 1986, 1976, 1977, 1978, 1980, 1992, 1995, 2001, , 1993, , 1987, Kandasamy P, Chellamuthu M 133

8 August , , 1978, 1980, 1981, 1977, 1979, 1986, , 1984, 1985, 1987, , 1990, 1994, , 1978, 1983, 1990, September , , 1999, , 1993, 1995, 1998, 2003 October , 1991, , 1983, 1985, , 1989, , 1992, 1998, , 1984, 1986, November , 1990, , 1988, 1996, , December , 1982, 1985, 1976, 1977, 1979, 1980, , , 1991, , 1994, 1995, 2004 March received the lowest rainfall 11.5 mm) followed by August 13.7 mm). February, January months were also drought months for about 76 and 73%. In the entire study period the month April was normal month for about 40%. The station experienced 152 normal months (42.2%) while 43 months (21.28%) were affected by moderate drought, 40 months (19.8%) under severe drought, and 119 months (58.91 %) under extreme drought. The chances of crop failure are more than 50% in the region, thus proper moisture conservation and water harvesting measures should be adopted. It was also observed that October and November months were the most susceptible to extreme droughts followed by December, March, April and January months. Table 5: Identification of season and year falling under moderate and severe meteorological droughts Month/Season Moderate drought Severe drought Extreme drought No Year No Year No Year South west , 1980, 1983, 1982, 1999, 1985, 1987, 1993, , 1990, 1995 North east , 1985, 1989, 1988, 1991, , 200, , 1976, 1977, 1979, 1980, 1981, 1982, 1986, 1987, Winter , , 1990, 1991, 1993, 1997, 1998, 2000, 2002, 2003, , 1878, Summer , 1996, 2000, , 1984, , , 1991 Kandasamy P, Chellamuthu M 134

9 Annual , 1985, 1988, 1990, 1995, 2002, , Table 5 indicates that the station experienced one moderate drought, 2 severe droughts and 19 extreme droughts during winter season. Therefore, it is evident that winter season is the most likely to be hit by severe drought in this region. There was no occurrence of extreme drought (Table 5). Hence, on annual basis, drought is not a serious problem, but from crop production and water management point of view, seasonal and monthly analyses may be more important deciding factors Probability analysis of rainfall From the table 6, the monthly rainfall in the South-West monsoon season ranges between 0 and 8.5 mm at 80% probability level. Similarly, for the North-East monsoon season, expected rainfall ranges from 13.6 to 82 mm. In the winter season, the chance of occurrence of rainfall at 80% level is 0. Table 6: Expected rainfall (mm) at different probability levels Period Probability (percent) January February March April May June July August September October November December S.W N.E Winter Summer Annual The expected rainfall at the 80% probability level in the south-west, north-east monsoon and winter season are 58, and 0 respectively. So, winter season need much attention on water conservation to take care of water deficit problem. From the crop production point of view, high risk is associated with the winter Kandasamy P, Chellamuthu M 135

10 and south-west monsoon seasons. Also, 50% risk is occurred in the winter season. 4. Water Management Planning From the analysis of annual rainfall pattern, Drought: Normal: Wet = 4: 4: 22. So, on annual basis, Drought is not a serious problem. From the analysis of seasonal rainfall pattern, Percentage of contribution of rainfall for winter: Summer: Monsoons = 0.7: 33.16: In winter, dry: wet: normal = 12: 7: 11. In summer: Dry: wet: normal = 4: 4: 22. Better moisture conservation measures should be adopted for winter crops as compared to summer crops. From the analysis of monthly rainfall pattern, Number of drought events is less than the Number of wet events (for all years) and the Number of drought events are higher than the Number of normal events (January, February, March and August). In overall, Drought: Normal: Wet = 160: 152: 48; Extreme drought: Severe drought: Moderate drought = 119: 40: 43. Precautionary measures of moisture conservation should be adopted during winter. 5. Conclusion Based on the study, winter seasons were found to be the most susceptible to severe drought conditions. There is a need to adopt moisture conservation measures like mulching etc. to mitigate the effect of dry spells during crop growth. Therefore, the excess water can be harvested through water harvesting structures in the monsoon seasons and it can be used for winter season to supply irrigation water to crops. Light irrigation during the month of December will help yield improvement. 6. References 1. Anil Kumar., Investigating meteorological drought for sustenance of agricultural productivity in hilly areas of Uttarakhand, Indian Journal of Soil Conservation, 37 (1) : Bharathi S., Madhavi G. Bindu, Reddy A. Subba Rami Rainfall Analysis for Drought Investigation In Krishna Zone of Andhra Pradesh, Agricultural Science Digest, 31(2), Bora P.K., Karmakar.R.M, Kurmi.K and Debnath.M.C Rainfall analysis for drought investigation in Central Brahmaputra Valley of Assam, Journal of Agro meteorology (Special issue-part2), Dracup JA, Lee K.S. and Paulson, On the definition of droughts, Water Resources Research, 16(2), Gupta V.K., and Duckstein L, A stochastic analysis of extreme droughts, Water Resources Research, 11(2), Kumar A., Prediction of annual maximum rainfall of Ranichauri (Tehri Garhwal) based on probability analysis, Indian Journal of Soil Conservation, 28(2), Machiwal D., and Sharma A, Rainfall analysis for drought occurrences in Udaipur region (Rajasthan), Indian Journal Soil Conservation, 32(1), Panday S.C. et al., 2002, Indian Journal Soil Conservation, 30(2): Ritzema H.P., Drainage principles and applications, ILRI publication 16, second edition, Saeid eslamian S., Maximum Monthly Rainfall Analysis Using L-Moments for an Arid Region in Isfahan Province (Iran), Journal of Applied Meteorology and Climatology, 46(4), Sahoo D.C., Rainfall probability analysis for efficient water harvesting and crop planning in nilgiris, presented in international conference, Kandasamy P, Chellamuthu M 136

11 12. Sharma H.C., and Ram S, Journal of Agriculture Engineering, 17(3): Singh R. et al., Indian Journal of Soil Conservation, 30 (2): Taley SM., and Dalvi VB, 1991, Dry-spell analysis for studying the sustainability of rainfed agriculture in India The case study of the Vidarbha region of Maharashtra state, Large Farm Development Project. 15. Tiwari AK, Sharma.V.K, Bhatt.V.K. Srivatsava Drought Estimation through Rainfall Analysis for Bundelkhand Region, Indian Journal of Soil Conservation, 26 (3), Tomar AS, Ranade.D.H, ParadkarV.K, Jain.L.K. and S.K. Vishwakarma, Analysis of Drought, Dry and Wet Spells at Chhindwara in Madhya Pradesh, Indian Journal of Soil Conservation, 29(3), Kandasamy P, Chellamuthu M 137