THE IMPACT OF METEOROLOGICAL PARAMETERS ON CROP PRODUCTION IN NALGONDA DISTRICT OF ANDHRA PRADESH,INDIA.

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1 African Journal of Geo-Sciences Research, 2014,2(2)09-14 ISSN: Available Online: THE IMPACT OF METEOROLOGICAL PARAMETERS ON CROP PRODUCTION IN NALGONDA DISTRICT OF ANDHRA PRADESH,INDIA. Shashikala.A.V and Mohd. Akhter ali Department of Geography Osmania University Received: 13,Jan,2014. Accepted: 07,Mar,2014. Abstract This study is undertaken to find out the effect of climatic changes on crop production in Nalgonda district of Andhra Pradesh. It is a proven fact that climate change brings about considerable change in temperature and precipitation patterns. Major crops are directly or indirectly affected by high temperatures, a change in the pattern of climatic conditions like floods or droughts. In the present study using regression models, weather variables, fertilizers and labour inputs climate response functions to crop productivity have been ascertained. For 59 mandals of the district data sets were created for a period beginning from 1988 to Four major crops have been selected to study the climates effect on crop productivity and the results indicate 85% of variation. Using the Ordinary Least Square Model, the contribution of agricultural productivity to the Gross Domestic Product (GDP) is also calculated. From the study it becomes clear that the R 2 value varies from 0.22 to 0.54 and 0.72 to 0.78 without and with GDP. Key words: Agro-Climatic Zones, Multiple Regression, Gross Domestic Product (GDP), Ordinary Least Square Model (OLS). INTRODUCTION The human society is affected in a myriad ways due to increase in concentration of atmospheric CO2 and related changes in temperature and precipitation patterns. The agricultural sector is most affected due to climate variability. Though research scientists have concluded that the changes in the temperature and precipitation do have a lot of implications on agricultural productivity, however some studies show that reduction in crop yield due to excessive atmospheric CO2 can be offset by carbon fertilization and increased precipitation. This type of an alternate method of saving the crop yield was suggested by Eastering et al who created a synthesis of 69 model based results that demonstrated the impact of carbon fertilization and temperature on changes in the cereal yield. In the Indian context, it is estimated that without implementing carbon dioxide fertilization there is a lot of rice and wheat yield loss ranging from 32 and 40 % for rice and 41 to 52 % for wheat and a corresponding decrease in GDP by 1.8 to 3.4 %. Predictions made on the impact of climate change on Indian agriculture indicate that an increase of 1 0 C in temperature reduces the yield of several major crops like wheat, soyabean, groundnut etc. And the losses will be much greater if the temperature rises further. Due to a rise in temperature, yields of rice, wheat, legumes and oil seeds will reduce by 10 to 20 % by In India the current food production is 230 million tons. By 2021 it is going to increase by 276 million tons. This is definitely going to affect pricing of food. It is crucial to understand the impact of climate change has on crop production because crops are highly sensitive to climate variations. Agroecological conditions also keep shifting due to alternations in hydrological characteristics, like the setting in during and intensity of the yearly monsoon. The studies carried out so far are region specific and the conservation measures suggested are unique to that particular region. And these suggestions may not be suitable for a particular block or mandal of a particular region. This study is aiming towards understanding the trends of climatic parameters (rainfall and temperature variations) and their influence along with other parameters like fertilizer input, human labor hours etc. on crop output and productivity at the mandal levels of Nalgonda district. STUDY AREA Nalgonda district belongs to the state of Andhra Pradesh and is located between and on the Northern latitudes and on the Eastern longitudes and is 420 Meters above sea level and as shown in the fig (1) is divided into 59 mandals. Each mandal has about 25 to 30 villages and is a separate administrative block. Hot and dry climate keep alternating throughout the year in the district. May, is the hottest month and in this month the maximum temperature touches 41 0 C and the mean daily minimum temperature is about 29 0 C. The coldest month is December when the mean maximum temperature is C and mean of minimum is C. There are rain gauges installed in different areas in the district and the normal rainfall recorded is 752 mm. In Andhra Pradesh the area cropped is classified into nine zones. This classification is based on the agro climatic conditions include range of rainfall received and the topography of the soils. Nalgonda district falls under the agro-climatic regions of North Telengana zone Southern Telengana zone. The soil types found in this region are chalkas, Red sandy soils, Dubbas, Deep red loamy soils and very deep Black soils. Paddy, Sugarcane, Castor, Maize, Sunflower, Groundnut, Turmeric, Pulses and Chilies are the crops that are grown in this region.

2 deviation of rainfall from normal was calculated. Between the years 1988 and 2012 there was a positive deviation of actual rainfall from the normal rainfall and the highest deviation was observed in the year 2005 which nearly was 23 %. The highest negative deviation was found in the year 1999 which was -44 %. In this district the seasonal rainfall is derived mostly from the South West Monsoon (SWM) and the North East Monsoon (NEM) and the seasonal data procured from these monsoons was grouped with the average annual rainfall data analysis for a period of 25 years. The SWM contributes roundabout 80 % of the rainfall. And the NEM which follows the SWM contributes to about 10 % of the rainfall. The trend observed is that there is a decrease in rainfall from around 711 mm in 1988 to 267 mm in the year This sort of a decline in rainfall was observed even in other states of India like Maharashtra, so this changing pattern in rainfall affects agricultural productivity significantly as also the hydrological cycle in general. When we consider the North East Monsoon the actual average rainfall is below its normal 139 mm and all these facts are highlighted in Table 1. Table (1) Months with actual average rainfall below its normal rainfall (mm) of Nalgonda district for period METHODOLOGY To understand the changes in the rainfall patterns and its impact on crop productivity meteorological socio economic and agricultural data were used. This data was collected from the Directorate of Economics and Statistics of the Government of Andhra Pradesh for a period of and was analyzed at the mandals and district level. Using SPSS-20 and micro soft excel a statistical analysis of rainfall, temperature and yield patterns were undertaken to comprehend the relationship between different parameters. Different statistical methods like Pearson Correlation, Multiple Regression analysis were used to understand the parametric relations. Using equation (1) described below the multiple linear regression analysis was done to ascertain the impact of rainfall, temperature, human labor hour and fertilizer input on crop yields. Equation (1) Y = f (F, HL, AR, DFNR, MAX TEMP, MIN TEMP) Y = Yield in kg / hectare F = Fertilizers in kg / hectare HL = Human Labour hour per hectare AR = Actual Rainfall (mm) DFNR = %Deviation from normal Rainfall MAXTEMP = Maximum Temperature in 0 C MINTEMP = Minimum Temperature in 0 C Combinations of various parameters listed above were analyzed to understand how they were dependent on one another and how they affected agricultural productivity.the Ordinary least square model (OLS) was used to analyze agricultural productivity. RESULTS AND DISCUSSION In this study a collection of data related to rainfall and temperature was undertaken for a period of 25 years and an analysis was done at the mandal and district level. The results are presented at the mandal and the district level. At the district level the rate of For a period of 25 years the rainfall pertaining to each mandal was gathered and an analysis of the rainfall pattern was done. Fig 2 shows the percent deviation of rainfall from normal rainfall for all the 59 mandals during the period

3 African Journal of Geo-Sciences Research, 2014,2(2)09-14 Fig 3(a) shows the distribution of the seasonal rainfall during the South West Monsoon for all the mandals of Nalgonda district and from the figure it is vivid that the mandals located in the north and north east boundary have received maximum rainfall and it is decreasing towards southwest. The highest rainfall received by the mandals is 550 mm 631 mm and the least rainfall is between 273 to 267 mm. This is largely because of the topography of the area. Mandals like Kodad (631mm), Suryapet (621.3mm), Tungathurthy (613.8mm) received the highest rainfall. Whereas mandals like Gundlapalli (273.0mm), Gurrampode (274.0mm), Chandampet (280.6mm) are receiving the least rainfall and the mandals that received the least rainfall are located at the southern part of the district. When there is a decline of rainfall in the months of July, September and October there is a corresponding decline in crop yield. Further an analysis of the North East Monsoon as depicted in Fig 3(b) shows that two mandals to the west like Gurampode & NSP and two mandals to the east such as Mothey & Tirumalagiri received very less amount of rainfall. The rainfall is only in the range of 55 66mm, and those mandals that are northerly located such as Bibinagar, Bhongir, Pochampally and Chotuppal received maximum quantum of rainfall that ranged from to mm. From the meteorological station located in Nalgonda mandal of the district, temperature data measurements were taken. It has been observed that the temperature touches the maximum during the months of April and May and from then on it decreases gradually by the time it is October. By using the SWM and NEM temperature data correlation trends were compiled and from this compilation it was inferred that as the temperature increased the rainfall decreased.

4 12 These facts are highlighted in Table (2) Table (2) Correlation between the temperature and rainfall during Southwest Monsoon and the Northwest Monsoon. When the climatic parameters (rainfall and temperature) were analyzed exhaustively it was ascertained that complex changes affected crop productivity in the district. And therefore a crop productivity analysis was carried out for a long duration of 25 years at the district level. Rice and Groundnut which is the major crop of the region were taken into consideration the results indicate that rice and groundnut s annual productivity shows decrease in the productivity for the period , and The decrease in productivity was due to decreased southwest monsoon rainfall in the same period as reported by the rainfall analysis. However, other years have shown an increasing trend in the groundnut productivity. Therefore it was clear that only rainfall cannot be an indicator for the changes in crop productivity. In order to further assess the impact of other parameters like fertilizers, human labour hour on agricultural production in addition to climatic variables of the Nalgonda district; multiple regression equation has been used. The multiple regression equation takes the form y=b1x1 + b2x bnxn + c. The regression values obtained from the 25 years data for the four crops are presented in Table 3. Table(3) Regression values for the four crops from the period at district level. actual rainfall and temperatures are showing a variation of only 10% on the rice productivity. The results for Jowar indicate a 26% of variation in Jowar yield. However unlike rice, actual rainfall, mean maximum temperature, fertilizer use and human labour hour had a negative co efficient while the mean minimum temperature is showing a positive impact on the Jowar yields, the negative impact by the fertilizers may be due to the over application by farmers which could be theoretically incorrect. Similarly the actual average rainfall and temperatures were showing a variation of 9% only on the Jowar yields where as the rainfall and maximum temperatures are showing negative co efficient implying that these values would affect the Jowar productivity negatively. As far as the Chillie crops are concerned a variation of 43.4% was shown on the yields due to variation in the weather parameters and human labor hour. Except for the maximum temperature all other variables were showing negative impact on Chillies crop productivity. As far as the Groundnut crop was concerned there was a variation of 26.6% due to the four variables. (Such as rainfall, temperature, fertilizer and human labour are showing negative impact) However fertilizers and high temperature did not bring about much alteration in crop yield. It is unfortunate that farmers are overusing fertilizers for this crop, as fertilizers have a negative impact on Groundnut crops. Temperature variation does not have a great effect on either Rice or Groundnut yield. Sushila Kaul had undertaken a same sort of study on the overall effect of rainfall maximum and minimum temperatures, fertilizers input and human labor hour on the output of Rice and Jowar crops. She used the multiple regression equations for the year to calculate the yield and its correlation with weather parameters. The study revealed that excessive rains and extreme variation in temperature affected crop productivity negatively and this in turn affected the incomes of farmers in a drastic way. A similar sort of study was carried out by H. Mongi et al. on the vulnerability of rain fed crops to weather change in the semi-arid parts of the Tabora region of Tanzania in the year The meteorological data results showed that during the season from October to April the annual rainfall data had been declining for 35 seasons from to The total rainfall appeared to decrease to a non-significant rate. Act avg = Actual Average Rainfall, Max Tem = Maximum Temperature, Min Tem = Minimum Temperature, % Deviation from Nor RF = Percentage Deviation from Normal Rainfall The results indicate that the variable used in the study showed about 13.1% of variation in the productivity of rice, while the overall crop has a positive coefficient, implying that the variables of average rainfall, temperature (maximum and minimum) and fertilizers has positive impact on productivity. However in comparison between the average and percent deviation of rainfall more accurate results were obtained with the latter data set. The weather parameters It was a marathon task to conduct calculations at the district level and it would give only a representative picture, so an analysis was undertaken at the mandal level. The district has 59 mandals and so the study was restricted to four mandals and was based on the coefficient of variation which was carried out using 25 years of seasonal data. For the analysis, the two seasons Rabi and Kharif were considered. The mandals chosen for the analysis are Kodad, Mothey, Munagala and Nadigudem. The crop yields data was calculated based on the values of the crop cutting and the averages of the dry yields of the villages that were surveyed and are multiplied with the total area of the surveyed villages and finally their ratio is

5 African Journal of Geo-Sciences Research, 2014,2(2)09-14 taken to achieve the yields. Table (4a) to (4d) presents a season wise analysis for rice in Kharif and Rabi seasons Using the variables of actual rainfall, temperatures, fertilizers and human labor hour a variation of 14.4% is observed in rice productivity for Kharif crop and 13.4% for the Rabi crop in Kodad mandal. Minimum temperature, fertilizers and human labour show a positive impact on the yield. However maximum temperature and rainfall show a negative impact for the Kharif crop. As far as the Kharif crop is concerned the percent deviation shows more negative impact while it was positive for the Rabi crop. The variation shown on the rice yields is 2.9% for the Kharif crop while it was 5.0% for the Rabi crop, when only weather parameters were taken and it was negative for the two seasons as far as the maximum temperature was concerned. A same sort of analysis was undertaken for Munagala, Mothey and Nadigudam mandals for Nalgonda district and the results are as shown in tables 4(b), 4(c) and 4(d) respectively. variation of 11.4% and maximum temperatures have a negative impact on the yields in kharif season In the study an analysis was also made to comprehend the loss in the Agricultural Gross District Domestic Product (AGDDP) at the district level. To see the impact on GDP, AGDDP was calculated for the period 1988 to Figure 5 depicts the percent contribution of AGDDP to the total GDP in the state. As far as the Munagala mandal is concerned a variation of 18.4% was found in rice productivity for Kharif crop while it was 16.4% for the Rabi crop. In this mandal, as far as the Kharif crop is concerned the rainfall, fertilizers and human labour show a positive impact while the maximum and minimum temperature show a negative impact on the yield for Kharif crop. For the rice yields the variation shown is 2.9% for the Kharif season and 6.0% for Rabi when only weather parameters ware taken. Maximum temperature has a negative impact on crop productivity both for Kharif and Rabi seasons. To study the impact of climate factors on the Agricultural GDDP and in turn the prices a study was carried out for a 25 year period between 1988 and To estimate the importance of R square values, the Ordinary Least Square Model (OLS) was used for analysis of the major crops and the two data sets (1) Prices, rainfall and production and (2) GDP, prices, rainfall and production were used. Table 5 shows the R-square, multiple-r, T-stat values for Nalgonda district. Preethi Laddha made a similar study on the impact of weather parameters on commodity prices and also measured the degree of weather risk shown on prices of commodities and its linkage to inflation, exchange rates and GDP using ordinary least square and co integration models. The result indicates a high degree of impact of rainfall on production and prices. In an important study made by Raymond Guiteras the economic impact of climate change on Indian agriculture was made and the effect of a random year to year variation in weather on crop output was considered using a 40- year district level panel data conveying nearly 200 Indian districts. Table( 5)Results of Ordinary Least square method (Nalgonda) In terms of rice productivity a variation of 21.9% is observed for the Kharif season and 71.9% for the Rabi crop. In the Mothey mandal except for rainfall, fertilizers and human labour the temperatures have shown a negative impact. The negative impact of maximum temperature is less when compared to the other two mandals. And compared to the other two mandals the percent deviation shows a more positive impact than the actual rainfall. The rice yields show a In this study the regression values differed from 0.57 for Rice to 0.14 for Chillies, when prices, rainfall and production were taken. Whereas with the parameters like GDP, prices, rainfall and production, the R square values varied from 0.73 for rice and 0.64 for chillies. It is urgent to address the issue of crop productivity and how it is adversely affected by drastic climatic changes. Recent trends in

6 14 meteorological parameters should be seriously taken into consideration while carrying on agricultural planning and formulating government policies. CONCLUSION The present study was done in Nalgonda district of Andhra Pradesh. The whole of the district comes under two agro climatic zones North Telangana Zone and South Telangana Zone. An analysis was undertaken for duration of 25 years of the meteorological data related to rainfall and temperature. The Southwest monsoon was studied for a period of 25 years and the tendency is that rainfall has actually decreased. A few mandals like Kodad, Thungathurthy and Suryapet were receiving the maximum rainfall while Gundlapalli and Chandampet mandals had scarce rainfall during the monsoons. And a corresponding analysis of the North East Monsoon indicates that, the two mandals such as Gurampode and NSP located to the West and the mandals on the East like Mothey and Tirumalagiri received the least rainfall and other mandals located in the North of the district received maximum quantum of rainfall. An analysis was also carried out on the impact of meteorological parameters on the four major crops in Nalgonda District- rice, chillies, jowar and groundnut. For rice the percent variation in crop productivity was 13.1%, for jowar 26.0%, for chillies 43.3% and groundnut 26.6%. Analysis was carried out for four mandals such as Kodad, Mothey, Nadigudem and Munagala of the district related to rice crop for the Kharif and Rabi seasons. The results were all positive in Munagala, Mothey and Nadigudem mandals for Kharif seasons and positive only in Mothey mandal for the Rabi season when the meteorological parameters were considered along with the human labor and fertilizer data. AGGDP was also carried out and the regression values varied from 0.73 for rice and 0.64 for chillies.. 1)Abaje, I.B.,Ishaya, S. and Usman, S.U., 2010, An Analysis of Rainfall Trends in Kafanchan, Kaduna state, Nigeria. Research journal of Environmental and Earth Sciences 2(2), )Agarwal, P.K., 2009 Vulnerability of Indian agriculture to climate change: current state of knowledge. Available online at: df (accessed on 5 January 2013). 3)Intergovernmental Panel for Climate change,2007,climate change 2007: synthesis report ( Cambridge,United Kingdom: Cambridge University Press) 4)Intergovernmental Panel on Climate change, 2007, Food fibre and forest products. Climate change 2007: Impacts, Adaptation and vulnerability. Contribution of working group II to the fourth Assessment Report ( Cambridge,United Kingdom: Cambridge University Press) 5)Mongil, H., Majule, A.E. and Lyimo, J.G., 2010, Vulnerability and adaptation of rain fed agriculture to climate change and variability in semi-arid Tanzania, African Journal of Environmental science and Technology 4(6), )Preethi Laddha., Agarwal, S., Kulkarni, P. and Murthy, N.K.A., 2007, Weather Risk, agro commodity prices and Macro Economic Linkages: Evidence form Indian Scenario using CO-Integration Model. Presented at International Conference on Agribusiness and Food Industry in developing countries: Opportunities and Challenges, Indian Institute of Management, Lucknow. 10 th to 12 th August )Raymond Guiteras., 2007, Impact of climate change on Indian agriculture Available on line at /portaldata/imagegallerywww/2050/imagegallery/guiteras%20pape r.pdf (accessed on 4 January 2013). 8)Reddy.V.N. 1978, Growth rates, Economic policy weekly13 (9), )Sushila Kaul., 2007 Bio-Economic Modeling of climate change on crop production in India. Presented at Economic Modeling Conference, Moscow. References