Showing papers in "Mausam in 2016"

Managing impact of extreme weather events in sugarcane in different agro-climatic zones of Uttar Pradesh

Abstract: Sugarcane is a cash crop in Uttar Pradesh; economic condition of the farmers is highly dependent on sugarcane production. However, average yield of the state has gone up from 39.5 t/ha (1950-51) to 59.2 t/ha (2009-10), was observed associated with fluctuating weather conditions, whereas other major sugar producing area in India have average yield of 70 t/ha. The result of the above study showed that there was an average rising trend in the annual minimum temperature (0.03° Cyr-1) over all the agro-climatic zones of the state. Out of nine agro-climatic zones, four zones namely South Western Zone, Central Plain Zone, Western Plain Zone and Eastern Plain zone, which were marked by decreasing annual rainfall trend. However, Vindhyan Zone, Mid Western Zone and Bhabhar and Tarai Zone show rising trend. To explain better relation between cane yield and weather parameters this study also show that maximum, minimum temperature and moisture plays the most important role during germination, tillering, grand growth and ripening phases of the sugarcane. Considering extreme weather, we found that temperature below 25 °C, above 35 °C and 40 °C are slowing down the growth and finally reducing the final yield. It is also noticed that temperature and rainfall extremes had high possibility of governing sugarcane yields but there were also quite a number of instances wherein the extremes couldn’t be reasoned directly for the yield fluctuations. Therefore, to sustain the productivity, this study recommends the improvements of the adoptive responses of varieties, management of the risk associated with extreme weather events by providing weather linked value-added advisory services to the farmers and crop insurance agencies.

Assessment and quantification of meteorological data for implementation of weather radar in mountainous regions

Abstract: The scope of this paper is to improve observation and detection of hydro-meteorological hazard over the Grenoble region which is characterised by significant changes of terrain in altitude and geomorphology. The city of Grenoble is located at a height between 200 up to 500 m, installing the weather radar in this range of elevation leads to better quality measurements, but visibility and as well coverage capability will be reduced at the other sites of the affected region. Two locations are shortlisted for the implementation of the future weather radar in Grenoble; (i) Moucherotte (1920 m a.s.l.) and (ii) Saint Eynard (1365 m a.s.l.). Several simulation and data analysis are performed to get the clear picture about precipitation variability by considering meteorological data from individual ground stations and radio sounding data as well. Compared to previous work, in this study is considered climatology of the vertical structure of the rainfall. In this context, several statistical computations are done regarding 0°C isotherm altitude. Concerning rainfall error estimation, ground clutter and screening effect, statistical calculations by using VISHYDRO code, are performed by for different quintiles for several elevation angles in both shortlisted sites. The results obtained from calculations carried out on two locations are almost similar. Also, significant under and over-estimation of rainfall error due to screening and ground clutter effect are detected. To achieve more accurate results, other sites need to be tested for further simulation. On the other hand since ground clutter, and screening effect at the Moucherotte is not too high compare with Saint Eynard, this site may be considered for implementing the future weather radar for observation of the meteorological processes over the Grenoble region.

Managing impact of climatic vagaries on the productivity of wheat and mustard in India

Abstract: Wheat and mustard crop is highly vulnerable, particularly in the semi-arid and arid regions of India. The climate is warming through the processes such as CO2 and changed pattern of temperature and precipitation resulting in heat and drought stresses, respectively. The effect of increasing temperature during grain filling stage of wheat causes substantial reduction in grain yield. The effect of low temperature (frost) during podding and seed development stage in mustard causes freezing injury in seeds and sizable reduction in seed yield. In this review paper response of wheat and mustard crop to weather extremes and management practices such as time of sowing, selection of resistance cultivars, mulching, seed priming, foliar spray of salts, use of extra irrigation water, foliar spray of micronutrients, sprinkler, wind barrier etc. to mitigate the temperature and moisture stress effect on the productivity of wheat and mustard crop have been discussed. Above ground dry weight of wheat and its rate decreased with increasing water stress at each stage. The averaged values of damage threshold temperatures compiled from the literature were 31 °C for flowering and 35 °C for grain filling of wheat. Changes in average daily maximum temperature during flowering and grain filling had a negative effect on grain yield of 518 kg/ha and 1140 kg/ha, respectively for every 1 degree increase in average maximum temperature in South Australia. Temperature rise would be most harmful for the crop in eastern region, followed by central and northern India, where winter season temperature is comparatively higher than northern region. Rainfed mustard was less vulnerable to temperature rise in northern India as compared to other two central and eastern India. Rise in atmospheric temperature reduced leaf area index, grain number as well as weight of grains which was in turn reflected in yield of mustard crop. Seed yield reduction occurred by low water availability during stem elongation, flowering and pod development in mustard. Priming with moringa water extract and ascorbate substantially improved the tissue water status, membrane stability, gas exchange, water productivity of the plant. Late sown wheat crop faces high temperature stress during ripening phase. Delayed sowing reduces the tillering period and hot weather during critical period of grain filling lead to forced maturity thereby reduces the grain yield. Application of mulches in wheat produced higher grain yield over without much wheat. Organic mulches provided better soil water status and improved plant canopy in terms of biomass, root growth, leaf area index and grain yield as compared to inorganic mulch. The foliar spray of KNO3 (0.5%) at 50 per cent flowering stage, 1.0 per cent KNO3 during anthesis stage, 2.5 mM of arginine, spray of zinc, extra irrigation water during grain filling stage increased the productivity of wheat under high temperature stress. Light irrigation in mustard crop one day before frost occurrence protects from frost damage by improving heat transfer and heat capacity. Plastic mulch raises the surface temperature of the soil nearly 10 °C over bare soil. Smoke particles are usually less than 1 µm in size, reflect visible radiation but trap the long wave radiation and so are effective in preventing rapid cooling of surface near ground. Mixing air and liquid materials in the right proportion to create many small bubbles is the secret to generate foam with low thermal conductivity. Organic mulches (straw and saw dust) provided better soil water status over ash mulch.

Monsoon rainfall variability and rainfed agriculture in the water-scarce Karha Basin, western India

Abstract: Recent climate projection models indicate that the semi-arid regions of the world are most vulnerable to the impact of climate change. Hence, the understanding of rainfall variability and availability of water resources in water-scarce regions is crucial for planners to formulate annual plan for judicious utilization and distribution of water. In the present study, an attempt is made to evaluate the hydro-meteorological characteristics of the Karha Basin, located in the rain shadow zone of the Western Ghat. Trends in monsoon rainfall, dam storage and the area under some principal crops were analyzed to ascertain their interrelationship. The analyses indicate high inter-annual variability in monsoon rainfall and distinct episodes of above - and below-average monsoon rainfall. There is enough evidence for enhanced monsoon variability during the recent decades and a tendency for weaker monsoons to be associated with El Nino events. The study also provides evidence of changes in the area under major crops with the multi-year fluctuations in monsoon rainfall and dam water storage. The relationship, however, is not as strong as expected and the pattern gets more erratic and confusing in the most recent decades, partly on account of increasing dependence on irrigation. The Karha Basin is already suffering from severe water scarcity. Increasing monsoon variability, seasonality and dependence on groundwater is likely to threaten agriculture and food security. Climate change related impacts are likely to further add to already difficult water management challenges in the basin. It is therefore necessary to plan for new challenges under climate change scenarios.

Trends in surface temperature variability over Mumbai and Ratnagiri cities of coastal Maharashtra, India

Abstract: Increasing urbanization and expansion of cities has led to intensification of the urban heat island (UHI). High consumption of fossil fuels and trapping of radiated heat leads to increase in surface temperature in and around city. Present research paper focuses on temperature variability over Mumbai and Ratnagiri cities, which are located in the same coastal climatic region and almost at same altitude. Trends in maximum and minimum temperature were investigated at annual and seasonal scale. The occurrences of temperature extremes were also analysed. In general, increasing trends were observed over both the stations, with high rate of increase in maximum temperature than the minimum temperatures statistically significant at 95% confidence level. Mumbai experienced significant warming with higher rates than Ratnagiri. Warm extremes have also increased significantly over Mumbai. Ratnagiri showed decrease in hot days during monsoon and hot nights during remaining seasons significant in summer.

Real time implementation of agricultural contingency plans to cope with weather aberrations in Indian agriculture

Abstract: Weather aberrations impact agriculture and allied sectors in one or other parts of the India round the year. Seasonal droughts and extreme weather events in 21st century have caused alarming losses not only in agricultural production but also horticulture, livestock, poultry and fisheries. ICAR-CRIDA, SAUs and DAC, MoA, GoI, prepared more than 580 district level agriculture plans within formation on contingency measures for sustaining higher agriculture production and to cope with extreme events. Real-time contingency planning (RTCP) is being conceptualized and implemented at micro level in farmers’ fields in this country. RTCP implementation during delayed onset of monsoon, seasonal droughts and floods resulted in better crop performance, higher agricultural production, better incomes and overall stability in house-hold livelihoods. In this paper, the real-contingency measures to cope with extreme events for management of horticultural crops, livestock, poultry and fisheries are proposed. Further, the preparedness for RTCP implementation with policy initiatives is also suggested.

The regional features of precipitation variation trends over Sichuan in China by the ESMD method

Abstract: Based on a precipitation time series from 49 meteorological stations in Sichuan Province during the period from 1961 to 2011, the multi-scale characteristics of precipitation variability are analyzed using the extreme-point symmetric mode decomposition method (ESMD). Regional differences in variation trends and change-points were also preliminarily discussed. The results indicated that in the last 50+ years, the overall precipitation in Sichuan Province has exhibited a significant non-linear downward trend, and its changes have clearly exhibited an inter-annual scale (quasi-3 and quasi-8-year) and interdecadal scale (quasi-13-year). The variance contribution rates of each component demonstrated that the inter-annual change had a strong influence on the overall precipitation change in Sichuan Province, and the reconstructed inter-annual variation trend could describe the fluctuation state of the original precipitation during the study period. The reconstructed interdecadal variability revealed that the climate mode in Sichuan Province had divided into three distinct variation periods with 1973 and 1998 as the boundaries. Furthermore, there were regional differences in the non-linear changes and change-points of precipitation. In addition, in order to study the relations between the changing more or less of rising or decrease and meteorological station’s geographical position (latitude, longitude and elevation) i.e., the Cokriging interpolation technique is applied directly to precipitation variation trend components through ESMD decomposition. At the same time, the results also suggested that the ESMD method can effectively reveal variations in long-term precipitation sequences at different time scales and can be used for the complex diagnosis of non-linear and non-stationary signal changes.

Thermal indices in relation to crop phenology and seed yield of pigeon pea (Cajanus cajan L. Millsp.) grown in the north bank plains zone of Assam

Abstract: Two varieties of pigeon pea viz., BC (local) and ICPL 88039 were grown on the sandy loam soils of AICRPDA research farm of B. N. College of Agriculture, AAU in two consecutive kharif seasons of 2012-13 to 2013-14. Both the cultivars were sown on three different dates at ten days interval starting from 3rd June to 23rd June. GDD accumulation for attaining different phenological events viz., emergence, initiation of 1st flower bud and flower appearance, 50 per cent flowering, 1st pod formation, 1st seed formation and physiological maturity were worked out. The cumulative GDD accumulations up to physiological maturity were relatively higher in BC (local) which varied from 3395.6 to 3593.5 °C day, whereas, in ICPL 88039, it varied from 2945.0 to 3296.7 °C day in different sowings and seasons. A decreasing trend in accumulated GDD for attaining any Phenological event was observed with successive delay in sowings in both the cultivars in the two seasons. In both the crop seasons, Pheno-Thermal Index (PTI) varied from 16.67 to 18.18 °C day growth day-1, in BC (local) and 18.31 to 19.11 °C day growthday-1 in ICPL 88039 during the vegetative growth period under all the sowing dates while, in the reproductive growth stage, it was comparatively lower and ranged from 7.96 to 8.23 °C day growthday-1 in BC (local) and 10.28 to 11.87 °C day growthday-1 in ICPL 88039. Seed yield heat use efficiency (HUE) in BC (local) varied from 0.207 to 0.296 kg ha-1 °Cday-1, whereas, in ICPL 88039 it varied from 0.201 to 0.312 kg ha-1°Cday-1 under different sowing dates in both crop seasons. Seed yield heat use efficiency was relatively higher in 2013-14 followed by 2012-13 in both the cultivars which indicated the significant differences in using the heat, available to the plants.

Establishing an operational system for assessment and forecasting the impact of extreme weather events on crop production

Abstract: Crop production forecasting is essential for various economic policy and decision making. There is a very successful operational programme in the country, called FASAL, which uses multiple approaches for pre-harvest production forecasting. With the increase in the frequency of extreme events and their large-scale impact on agriculture, there is a strong need to use remote sensing technology for assessing the impact. Various works have been done in this direction. This article provides three such case studies, where remote sensing along with other data have been used for assessment of flood inundation of rice crop post Phailin cyclone, period operational district/sub-district level drought assessment and understanding the impact of recent hailstorm/unseasonal rainfall on wheat crop. The case studies highlight the great scope of remote sensing data for assessment of the impact of extreme weather events on crop production.

Variability and trends in extreme rainfall over India

Abstract: This study has been attempted to investigate the seasonal and annual trends and variations in the occurrence of extreme rainfall over different Indian region and India as a whole. Trends and variations are examined on the basis of following parameters (i) frequency and magnitude of extreme rainfall intensity (ERI) and its contribution in total rainfall (ii) highest rainfall events (iii) frequency of extreme rainfall events and days (iv) frequency of rainfall events and days with daily rainfall above 100 mm and 200 mm in a grid box (1° × 1°) over different Indian regions and India as a whole. Daily gridded rainfall data from India Meteorological Department (IMD) available at 1° × 1° resolution has been used to examine trends and variations associated with extreme rainfall events. Based on the long term 95 and 99 percentile values of daily total /maximum rainfall as a threshold for extreme rainfall intensity/events of category 1 and category 2 respectively, the trends and variations in above mentioned parameters are analyzed for the periods 1951-2007, 1951-1980 and 1981-2007. The magnitude of highest intensity rainfall is increased over country as a whole and over peninsular India; it is found to be increased by 1% during 1981-2007 as compared to period 1951-1980. The frequency of extreme rainfall intensity (ERI) days of category 1 is found to be significant increasing (0.4 days/decade) over north central region and significant decreasing trend is found over north east region (0.5 days/decade) during the pre-monsoon season. The magnitude of 24 hours highest rainfall in a grid box is found to be significant increasing over all regions under consideration except over north east and south peninsular regions. Over the last ten years period of the present study, most of the 24 hours highest rainfall events in a grid box are seen over west peninsular region. Generalized extreme value (GEV) distribution fitted with annual highest rainfall event over the country as a whole and over different Indian region indicates an increase in magnitude of most probable 24 hours highest rainfall in a grid box during second half of the study period over north central region of the country. Analysis also reveals an increase in frequency and severity of extreme rainfall over north west, north central and west peninsular regions during the period of 1981-2007 as compared to 1950-1980. Annual frequency of days and events with extreme rainfall of both categories is increased most significantly over country during the period of present study (1951-2007). Significant increasing trends in frequency of days with extreme rainfall of both categories is noticed only during the monsoon season while extreme rainfall events showed increasing trends during monsoon and winter season over country as a whole. Number of days and events with daily rainfall in any grid box above 100 mm and 200 mm is observed to be significantly increased over the country. Out of six regions, significant increasing trends in annual number of days with rainfall above 100 mm in a grid box is observed over north central and north east regions and for rainfall above 200 mm significant increase is observed over north west and north central regions.

Verification of district level weather forecast

Abstract: IMD started issuing quantitative district level weather forecast upto 5 days on operational basis from 1st June, 2008. The products comprise of quantitative forecasts for seven weather parameters, viz., rainfall, maximum and minimum temperatures, wind speed and direction, relative humidity and cloudiness. The rainfall forecast is generated based on multi model-ensemble techniques (MME). For other parameters, ECMWF forecasts (presently IMDGFS) are used. These forecast products are further value added, by the respective MCs/RMCs and forwarded to 130 Agrometeorological Field Units (AMFUs) for preparation of weather based District Agromet Advisory Service bulletin. This Meteorological Monograph describes the performance skill of the operational district level weather forecasts over different parts of India rainfall during monsoon and temperature during winter and summer from 2012-14. The Monograph also highlights limitations and future scope for further improvement of the MME models. The verification results show weather forecasts are reasonably accurate and value addition has improved the accuracy of model forecast. Though the MME model could predict the weather in hill regions in the North but in other regions having some hilly areas, the same could not come true in respect of temperature. North East region of the country shows very less accuracy due to its predominantly humid sub-tropical climate with hot, humid summers, severe monsoons and mild winter.

Adaptability evaluation of TRMM over the Tianshan Mountains in central Asia

Abstract: Accurate precipitation in mountain area is very important for evaluating the hydrological process and ecological problem. With the satellite data having been widely used in the past few decades, adaptability evaluation becomes the principle problem. The adaptability of TRMM 3B43 in mountain area of Central Asia was analyzed in this study. The TRMM product was compared with the observed data for the period of 2000-2006. Four statistic parameters were introduced based on the statistical analysis theory. The results show that the bias reached -13.93% over the entire regions, and the correlation coefficients over 70% of stations were greater than 0.70. According to the accuracy analysis of TRMM, we found the errors have significant differences in time and space. On the whole, the precision in the warm seasons is much higher than that in the cold seasons. The precision of the southern and eastern areas is higher than the other areas in space. Additionally, the accuracy of TRMM with elevation was acceptable at very significant level. This study indicates that the precipitation from TRMM 3B43 could be applied in the Tianshan Mountains in Central Asia. It could provide reference for the use of new data source in the mountain area.

Conceptualization of a framework of decision support system for agriculture in hilly region

Abstract: Decision support system (DSS) in agriculture helps farming community to take appropriate decision as per the situation to maximize economic return by enhancing productivity and reducing the cost of inputs. The prime most purpose of DSS is to enhance the input use efficiency by applying the input when it is needed most. The requirement of DSS in the hilly states is being felt more as environmental conditions vary greatly in tempo-spatial domain. Climate change associated with increasing probability of extreme weather conditions has further deepened the need of DSS. There have been many attempts in the past to use / develop DSS in the hilly regions. The serious efforts in this direction were initiated by fine tuning the Decision Support System for Agrotechnology Transfer (DSSAT) in Indian conditions. DSSAT helps to take appropriate decisions on selection of cultivar, sowing time, irrigation, fertilization and harvesting of crops. Of late geospatial technology alone and in combination with crop simulation model has also been used to develop DSS. Present paper underlines the efforts of researchers / academicians to develop DSS in hilly states with their usability and limitations. Paper also conceptualizes a framework of DSS for hilly regions by integrating a forewarning system and agriculture expert system.

Use of ordinal logistic regression in crop yield forecasting

Abstract: The performance of ordinal logistic regression and discriminant function analysis has been compared in crop yield forecasting of wheat crop for Kanpur district of Uttar Pradesh. Crop years were divided into two or three groups based on the detrended yield. Crop yield forecast models have been developed using probabilities obtained through ordinal logistic regression along with year as regressors and validated using subsequent years data. In discriminant function approach two types of models were developed, one using scores and another using posterior probabilities. Performance of the models obtained at different weeks was compared using Adj R2, PRESS (Predicted error sum of square), number of misclassifications and forecasts were compared using RMSE (Root Mean Square Error) and MAPE (Mean absolute percentage error) of forecast. Ordinal logistic regression based approach was found to be better than discriminant function analysis approach.

SARIMA modeling of the monthly average maximum and minimum temperatures in the eastern plateau region of India

Abstract: The SARIMA time series model is fitted to the monthly average maximum and minimum temperature data sets collected at Giridih, India for the years 1990-2011. From the time-series plots, we observe that the patterns of both the series are quite different; maximum temperature series contain sharp peaks in almost all the years while it is not true for the minimum temperature series and hence both the series are modeled separately (also for the sake of simplicity). SARIMA models are selected based on observing autocorrelation function (ACF) and partial autocorrelation function (PACF) of the monthly temperature series. The model parameters are obtained by using maximum likelihood method with the help of three tests [i.e., standard error, ACF and PACF of residuals and Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC) and corrected Akaike Information Criteria (AICc)]. Adequacy of the selected models is determined using diagnostic checking with the standardized residuals, ACF of residuals, normal Q-Q plot of the standardized residuals and p-values of the Ljung-Box statistic. The models ARIMA (1; 0; 2) × (0; 1; 1)12 and ARIMA (0; 1; 1) × (1; 1; 1)12 are finally selected for forecasting of monthly average maximum and minimum temperature values respectively for the eastern plateau region of India.

Farming system approach to meet the challenges from extreme weather

Abstract: Location specific and integrated farming system based technological management options reduce the climatic risk and better utilization of available natural resources produce higher agricultural productivity and thereby enhance food and livelihood security of small and marginal farmers of India. The significance of IFS approach is supportive in enhancing productivity to meet the food, feed and fuel for ever increasing human and animal population. It also increases the land productivity, profitability and also generate employment. Since small farms are often vulnerable to natural vagaries like flood, drought and farming remains at risk. Due to industrialization and population growth, the horizontal expansion of agricultural area is not possible. The vertical expansion in small farms is possible by integrating appropriate farming system components requiring less space and time and ensuring periodic income to the farmers. A farming system model was synthesized based on the studies conducted at ICAR-IIFSR located in western plain zone of Uttar Pradesh for a period of six years (2004-2010) revealed that Integrated farming system approach applied on a piece of 1.5 hectare irrigated land, besides fulfilling all the requirement of 7 members household food and fodder demand (animals) inclusive cost of production, could create an additional average annual savings of Rs. 47000/- in four fours of its establishment and more than Rs. 50000/- in subsequent years. the family gets some income round the year and another benefit is if due to any extreme event occurred at any time of the year, the farmer will get some income from any of the enterprises, so that it will cater to the need of the food security. Since each enterprise react differently to extreme weather events; the influence of droughts/floods/ higher temperature will be different to different enterprises and because of the diversification, the farmer will get some income from their enterprises, so that he can sustain under difficult times. This manuscript analyses how farming system approach is different and site specific and also how it will decrease the vulnerability under extreme climatic situations with some examples

Epidemiology and forecasting of insect-pests and diseases for value-added agro-advisory

Abstract: Models are means to capture, condense and organize knowledge. These are expressions, which represent relationship between various components of a system. A well-tested weather-based model can be an effective scientific tool for forewarning insect-pests and diseases in advance so that timely plant protection measures could be taken up. Various types of techniques have been developed for the purpose. The simplest technique forms the class of thumb rules, which are based on experience. Though these do not have much scientific background but are extensively used to provide quick forewarning of the menace. Another tool in practice is regression model that represents relationship between two or more variables so that one variable can be predicted from the other (s). Linear and non-linear regression models have been widely used in studying relationship of insect-pests and diseases with time and weather variables (as such or in some transformed forms). With the advent of computers more sophisticated techniques such as simulation modelling and machine learning approach such as decision tree induction algorithms, genetic algorithms, neural networks, rough sets, etc. have been explored. A number of simulation models have been developed all over the world for quantifying effects of various factors including weather on agriculture. These may provide a good forecast but require detailed data base, which may not be available. Machine learning approach has recently received some attention. As opposed to traditional model-based methods, machine learning approach is self adaptive methods in that there are a few a priori assumptions about the models for problem(s) under study. This technique learns more from examples and captures subtle functional relationships among the data even if the underlying relationships are unknown or hard to describe. This modelling approach with ability to learn from experience is very useful for many practical problems provided enough data are available. Remotely sensed data can provide useful information relating to area under the crop and also the condition thereof. It has certain advantages over land use statistics due to multi-spectral, synoptic and repetitive coverage. An attempt has been made for accurate estimation of area affected by insect-pests and diseases in crops along with accurate assessment of damage due to the same are possible for providing compensation to farmers. In this study, an Integrated Decision Support System (IDSS) for Crop Protection Services is also discussed.

Rice phenology and growth simulation using CERES-Rice model under the agro-climate of upper Brahmaputra valley of Assam

Abstract: Crop growth simulation models, properly validated against experimental data have the potential for facilitating strategic decision making in agriculture. Such validated models can also make use of the information generated for site specific experiments and trials to other sites and for different time durations. For proper calibration and evaluation of crop simulation models, there is a need for collection of a comprehensive minimum set of data on soil, weather and crop management in all agronomic experiments. Keeping this in view, data from seven field experiments conducted at Jorhat (26° 47' N, 94°12' E; 87 m amsl) during 1998-2005 for long duration rice cultivar Ranjit grown under rainfed conditions were collected. Genetic coefficients required for running the CERES-Rice v4.5 model were derived and the performance of the model under the climate of upper Brahmaputra valley was evaluated. These results indicate that the CERES Rice v4.5 model is capable of estimating growth stages and grain yield of rice cultivar Ranjit in the climatic conditions of upper Brahmaputra valley with reasonable accuracy. Hence, the model have the potential for its use as a tool in making various strategic and tactical decisions related to agricultural planning in the state.

Agrometeorological Advisory to assist the farmers in meeting the challenges of extreme weather events

Abstract: In recent past extreme weather events are causing great concern in different sectors contributing to the Indian economy. Among other, agricultural sectors are badly affected by the extreme weather events. Weather and climate information play a great role in minimizing the loss of crops. India Meteorological Department is doing yeomen’s service by providing advance information including monitoring of the extreme weather events along with the proper advisories to the farming community by using state of art instruments & technology through efficient delivering mechanism of the information and ultimately help the farmers from incurring great loss. Satellite information is also used for preparation of the accurate crop and location specific Agromet Advisories. Under Public Private Partnership, today it is possible to send the weather forecast and advisories within short time to large number of farmers in the country before the occurrence of extreme weather events and ultimately possible to improve the economic condition of small and marginal farmers by increasing the productivity of crops.

Crop yield forecasting of paddy and sugarcane through modified Hendrick and Scholl technique for south Gujarat

Abstract: Regression models by modified Hendrick and Scholl technique were developed on paddy and sugarcane for six districts of south Gujarat. The data on the yield and weather parameters were analyzed for 27 years. The 25 year data was used for development of the model. The validation of model was done using data set of 2010 and 2011. The stepwise regression analysis was executed by trial and error method to obtain the finest combination of predictors, significant at 5% level. The multiple regression techniques was used for fitting of the model and decided best by highest R2 and lowest percent error. All crop yield forecasting models gave good estimates and produced error percent within acceptable range. Analysis revealed that the model error percent of paddy and sugarcane for respective crop growing districts were -10.0 to 8.1% and -12.2 to 1.5% respectively. Crop yield forecasting for year 2012 based on validated model was made for the districts of Navsari, Surat, Bharuch, Valsad, Narmada and Tapi.

Agricultural drought monitoring and management at sub district level in Telangana

Abstract: The weather or climate is considered as an important natural resource and basic input for better planning of crop and cropping system in agriculture particularly rainfed environments. Every plant process, related with growth, development and yield of a crop and each of in-season and off-season farm operations depends on weather. Amongst the various weather elements, temperatures, radiation and rainfall play crucial role in deciding the crop growth, development and yield levels. Precipitation is one of the important weather factors being responsible for atmospheric and soil moisture and therefore has more agricultural importance, especially in rainfed agriculture. Rainfed crops like jowar, maize, groundnut, greengram, blackgram and sunflower and one water-intensive crop like rice are mainly affected owing to drought. The drought conditions occur due to failure of South West Monsoon, delay in arrival of SW monsoon, and break monsoon conditions or early cessation of SW monsoon. Rainfed agriculture in India depends on onset of monsoon and the rainfall distribution during crop growth season. The amount of rainfall and the time of onset of monsoon decides the type of the crop to be grown. The timely onset and well distribution of monsoon rain in the month of June and July decides the area coverage of rainfed crops. Any deviation in the onset and distribution of southwest monsoon rainfall causes huge impact on agriculture and its dependent activities. Close monitoring of progress of monsoon and distribution of rainfall and its impact on sowing of rainfed crops is essential at sub district level to suggest time to time crop management strategies thereby to minimize the impact of aberrant seasonal conditions. In this paper a monitoring of drought at national, state and sub district (Mandal) level using indices like MAI, WRSI etc. were presented. Management strategies to reduce the impact of drought like optimum time of sowing, strategic irrigation, crop calendar, contingency crop planning etc. were discussed. Agromet advisories for communication of real time weather information for benefit of farming community were presented.