Rainfall variability estimation

The present study is mainly concerned with the changing trend of rainfall in a district of Odisha. We have given an effort to analyse one of the most important climatic variable, i.e., precipitation, for analysing the rainfall trend in the area. Daily rainfall data of 102 years from 1901 to 2002 has been processed in the study to find out the monthly variability of rainfall for which the Mann-Kendall (MK) test has been used together with the Sen‟s Slope Estimator for the determination of trend and slope magnitude.

11p angicungduoc6 22-07-2020 10 2   Download

The present study intended to determine potential trends in monthly, seasonal and annual rainfall in the Brahmaputra valley of Assam during 1986-2015, based on observed daily rainfall data from 10 locations. The magnitude of the trends was estimated using TheilSen’s slope method, while statistical significance of the trends was tested using MannKendall rank statistics. Analysis revealed that mean annual rainfall varied from 1653.5 mm in Golaghat to 3676.9 mm in Gossaigaon, with variability in order of 13-32 per cent at different locations.

11p gaocaolon5 14-06-2020 5 2   Download

The present research investigation was undertaken to work out the rainfall variability analysis of western districts of Rajasthan. The coefficient of variation and standard deviation for weekly, monthly and annual rainfall were computed for all the districts. The normal onset of monsoon over different western districts of Rajasthan is between June to October. It was found that the annual rainfall is higher at Sikar district followed by Jalor and Pali. The mean annual rainfall is lowest at Jaisalmer.

5p trinhthamhodang5 16-05-2020 12 0   Download

Present study examines the effect of climatic factor e.g. Temperature (Maximum and Minimum), Relative humidity (Morning and Evening), Evaporation and Rainfall variation on the yield of different stages of wheat in Samastipur district of Bihar by using Box plot method. The data of wheat yield of 29 Years (1984-2013) was taken from Department of Agricultural Economics, RAU, Pusa and Weather Variables (1984-2013) was taken from Agro-metrology Unit, RAU, Pusa. Box plot will used to estimate the effect of climate variables on the stages of wheat yield.

8p angicungduoc4 04-05-2020 12 1   Download

The long term behaviour of rainfall is necessary to study over space with different time series viz. annual, seasonal, monthly and weekly as it is one of the most significant climatic variable. Rainfall trend is an important tool which assesses the impact of climate change and provides direction to cope up with its adverse effects on the agriculture.

9p nguaconbaynhay4 22-03-2020 26 2   Download

This work has presented yearly dry and wet seasons in the analysis of 28 years daily recorded temperature, relative humidity and rainfall data from 1988 to 2015 in Rajshahi division, Bangladesh using Hilbert frequency analysis. Analysis has estimated the seasonal boundaries in time according to the instantaneous frequency in cycles/day and the estimations are verified with studying power spectrum of the time series. Two boundaries are obtained in each analysis over the average of yearly analysis of four years.

14p 12120609 22-03-2020 19 2   Download

Hydrological modelling is a powerful technique of hydrologic system investigation for both the research hydrologists and the practicing water resources engineers involved in the planning and development of integrated approach for management of water resources. In present study, the observed rainfall and runoff data of 2010, 2011, 2013 and 2014years were used as input data. In ANN, input data was divided in 70 per cent, 15 per cent and 15 per cent for training, testing and validation purpose, respectively.

7p nguathienthan2 19-12-2019 23 0   Download

Precipitation records often suffer from missing data values for certain time periods due to various reasons, one of them being the malfunctioning of rain gauges. This is an important issue in practical hydrology as it affects the continuity of rainfall data. The missing data values ultimately influence the results of hydrologic studies that use rainfall data as one of the input variables. Therefore, it is crucial to estimate the missing rainfall data for qualitative hydrologic assessment.

9p nguaconbaynhay1 04-12-2019 22 2   Download

Greenhouse gases are accumulating in Earth’s atmosphere as a result of human activities, causing surface air temperatures and subsurface ocean temperatures to rise. Temperatures are, in fact, rising. The changes observed over the last several decades are likely mostly due to human activities, but we cannot rule out that some significant part of these changes is also a reflection of natural variability. Human-induced warming and associated sea level rises are expected to continue through the 21st century.

42p tom_123 14-11-2012 56 3   Download