2 edition of Rainfall probability estimates for selected locations of semi-arid India found in the catalog.
Rainfall probability estimates for selected locations of semi-arid India
S. M. Virmani
by International Crops Research Institute for the Semi-arid Tropics in Patancheru, India
Written in English
Bibliography: p. 166-167.
|Statement||S.M. Virmani, M.V.K. Siva Kumar, and S.J. Reddy.|
|Series||Research bulletin ;, no. 1, Research bulletin (International Crops Research Institute for the Semi-arid Tropics) ;, no. 1.|
|Contributions||Siva Kumar, M. V. K., Reddy, S. J.|
|LC Classifications||QC925.5.I47 V57 1982|
|The Physical Object|
|Pagination||ix, 170 p. :|
|Number of Pages||170|
|LC Control Number||85902043|
After the best‐fitted probability distribution for the considered rainfall data is defined, it can be easily used to estimate rainfall quantiles for different return periods (e.g. 10, 20, 50, , and years). These estimates can be performed at point or regional scale. checked before design rainfall depths are estimated. 2. Probability of exceedance and return period Rainfall depths expected for specific probability (X P) Estimates of rainfall depths (X P) or intensities that can be expected for a specific probability during a specific reference period (hour, day, week, day, month, year) are.
Basin‐wide Comparison  In this analysis, we used two GIS interpolation techniques to generate continuous surfaces of precipitation over the entire basin. First, the ° × ° gridded TMPA products were interpolated to °‐resolution data sets for the Laohahe basin using a simple cropping approach [Hossain and Huffman, ]. The climate of India comprises a wide range of weather conditions across a vast geographic scale and varied topography, making generalizations difficult. Climate in south India is generally hotter than north India. Most parts of the nation don't experience temperatures below 10 °C (50 °F) in winter, and the temperature usually tends to exceed 40 °C ( °F) during summer.
ABSTRACT: Monthly rainfall data for 40 years () were collected from 27stations of NER. Four of the commonly used hydrological time series probability distribution were selected viz. Normal, Log Normal, Log Pearson Type III and Extreme Value Type I (Gumbel distribution) to find the best probability distribution of rainfall of NER India. To model strictly positive non-symmetric rainfall totals, Gamma, Log-logistic, Generalized Extreme Value, Log-Pearson type III and Generalized Gamma distributions have been utilised [19,20,21,22,23].However, monthly or seasonal rainfall data in arid or semi-arid regions are of mixed type (continuous rainfall amounts with presence of dry months/seasons).
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RAINFALL PROBABILITY ESTIMATES FOR SELECTED LOCATIONS OF SEMI-ARID INDIA RESEARCH BULLETIN NO. 1 2nd Edition - Enlarged S. VIRMANI M. SIVA KUMAR AND S.
REDDY ICRISAT International Crops Research Institute for the Semi-Arid Tropics ICRISAT Patancheru P.O. Andhra PradeshIndia Virmani, S M and Sivakumar, M V K and Reddy, S J () Rainfall probability estimates for selected locations of semi-arid India.
Research Bulletin No. Monograph. International Crops Research Institute for the Semi-Arid Tropics, Patancheru, Andhra Pradesh, India. PDF | On Jan 1,S M Virmani and others published Rainfall probability estimates for selected locations of semi-arid India.
Research Bulletin. Rainfall probability estimates for selected locations of semi-arid India. Research Bulletin No.
1Author: S M Virmani, M V K Sivakumar and S J Reddy. S.M. Virmani, M.V.K. Sivakumar, S.J. ReddyRainfall Probability Estimates for Selected Locations of Semi-Arid India (2nd edition), Research Bulletin No.
1, International Crops Research Institute for the Semi-Arid Tropics, Patancheru ()Cited by: Rainfall probability estimates for selected locations of semi-arid India. Research BulletinNo.1, 2nd Edit. enlarge., International Crops Research Institute for the Semi-Arid (ICRISAT). Weerasinghe.
Virmani SM, Sivakumar MVK, Reddy SJ () Rainfall probability estimates for selected locations of semi-arid India. International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Andhra Pradesh, India (Research Bulletin 1) Google Scholar.
The rainfall received during the winter, summer, southwest and northeast monsoon seasons were,mm, respectively. Rainfall frequency analysis done by Weibull’s method revealed that the annual average rainfall of mm can be expected to occur once in years at a probability of 40 %.
The awareness of rainfall pattern, in terms of probability, helps in the planning of crops, different irrigation schemes and watershed management. Keeping it in view, the rainfall data of 22 years, from towere collected from the Dry Farming Research Station; Solapur were analyzed and discussed in this paper.
Incomplete gamma distribution of rainfall for sustainable crop production strategies at Palampur, Himach60 (1): Subbulakshmi, S., Selvaraju, R. and Manickasundaram, S. Rainfall probability analysis for crop planning in selected locations of Tamil Nadu. Madras Agric.
J., 92(): As estimated by Log Pearson-III, the seasonal rainfall of mm can be expected in years with 1% probability and in every 2 year return periods, the magnitude of rainfall of is expected with 50% probability.
Rainfall Probability Estimates for Selected Location of Semi-arid India, Research Bulletin No. 1 Evaluation of two land configurations in production of pearl millet and castorbean on shallow red soils of semi-arid tropics.
Andhra Pradesh, India, International Agrophysics 2: – Rainfall Probability Estimates for Selected Location. IDENTIFICATION OF RAINFALL PROBABILITY DISTRIBUTION FOR JUNAGADH D. K Junagadh Agricultural University, Gujarat, India ABSTRACT Rainfall data of 30 years () was analysed to obtain its descriptive statistics i.e.
the mean, standard identified best fit probability distribution model for peak daily rainfall of selected cities in. Trend and climate change were studied in annual rainfall data for the period of 62 years () of Sagar and 65 years () of Damoh districts of Bundelkhand region of central India.
The analysis of weekly rainfall probability was also carried out at both the locations for field operations and crop planning in rainfed agricultural system for improving the farmer’s. Gupta et al. () suggested cropping systems for Doon Valley during rainy and winter crop seasons on the basis of expected amount of rainfall at 80% probability level.
Stern and Coe () analyzed daily rainfall data for crop planning in semi-arid tropics. S.M. Virmani's 50 research works with citations and 1, reads, including: Agricultural performance in semi-arid tropics of India. The pink color in the inset map of India shows Madhya Maharashtra Subdivision.
K = Karha, Y = Yerala, M = Man, A = Agrani, and S = Sina river basins. Projected rainfall and temperature data were collected for the area demarcated by the red dashed square.
(b) Distribution of the selected rainfall stations over the study area. Predicting monthly and seasonal rainfall, An estimate of the probability of an event can be made directly from its relative frequency of occurrence, or alternatively a distribution (such as the normal) can be fitted.
Rainfall Probability Estimates for Selected Locations of Semi-arid India. Research Report 1, Hyderabad, India. Rainfall-runoff modelling is a useful tool for water resources management.
This study presents a simple daily rainfall-runoff model, based on the water balance equation, which we apply to km2 Lesser Zab catchment in northeast Iraq. The model was forced by either observed daily rain gauge data from four stations in the catchment or satellite-derived rainfall estimates.
The first step is to obtain annual rainfall totals for the cropping season from the area of concern. In locations where rainfall records do not exist, figures from stations nearby may be used with caution.
It is important to obtain long-term records. As explained in sectionthe variability of rainfall in arid and semi-arid areas is. The average rainfall in India is cm according to annual data from the Meteorological Department.
The following is the distribution of rainfall in India: Extreme Precipitation regions: Northeastern regions and the windward side of the Western ghats experience an average of cm of annual rainfall.AbstractThis study was designed to find the best-fit probability distribution of annual maximum rainfall based on a twenty-four-hour sample in the northern regions of Pakistan using four probability distributions: normal, log-normal, log-Pearson type-III and Gumbel max.
Based on the scores of goodness of fit tests, the normal distribution was found to be the best-fit probability .Mean monthly rainfall provides a general idea about the available supply. Hargreaves () indicated that 75% probability of rainfall occurrence is a much more reliable indication of moisture available for crop production than mean precipitation.
With this idea, we are listing the dependable precipitation (DP) amounts for all the locations.