Thumbnail Image

Chaudhary Charan Singh Haryana Agricultural University, Hisar

Chaudhary Charan Singh Haryana Agricultural University popularly known as HAU, is one of Asia's biggest agricultural universities, located at Hisar in the Indian state of Haryana. It is named after India's seventh Prime Minister, Chaudhary Charan Singh. It is a leader in agricultural research in India and contributed significantly to Green Revolution and White Revolution in India in the 1960s and 70s. It has a very large campus and has several research centres throughout the state. It won the Indian Council of Agricultural Research's Award for the Best Institute in 1997. HAU was initially a campus of Punjab Agricultural University, Ludhiana. After the formation of Haryana in 1966, it became an autonomous institution on February 2, 1970 through a Presidential Ordinance, later ratified as Haryana and Punjab Agricultural Universities Act, 1970, passed by the Lok Sabha on March 29, 1970. A. L. Fletcher, the first Vice-Chancellor of the university, was instrumental in its initial growth.

Browse

2016 - 201912020 - 20211
Reset filters
Subject: Statistics × Author: Nain, Mohit × Start date: 2003 ×
Reset filters

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    ThesisItemOpen Access
    Regional Frequency Analysis of Extreme Rainfall Using L-moments and Partial L-moments in Haryana
    (CCSHAU, Hisar, 2021-06) Nain, Mohit; HOODA, B.K.
    Regional frequency analysis (RFA) is of great importance for planning and designing hydraulic structures by policymakers and structural engineers. In this study, we focus on regional frequency analysis of daily and monthly extreme rainfall from 1970–2017 at 27 rain gauge stations of Haryana (India) using L-moments and PL-moments. Based on mean monthly rainfall, these 27 rain gauge stations were grouped into three homogeneous regions (Region-I, Region-II, and Region-III) using Ward‟s method of cluster analysis and homogeneity of each region was tested using heterogeneity measures (H). The best fit regional distribution was selected for each region from the five candidate distributions i.e. GEV, GNO, GLO, GPA, and PE3 using the -statistic and L-and PL-moments ratio diagrams. For maximum monthly rainfall, using L-moments method, it was found that GNO was best-fitted for Region-I and Region-II while PE3 for Region-III. For maximum daily rainfall, for Region-I, Region-II and Region-III; PE3, GEV, and GLO was the best-fitted distribution, respectively. Using PL-moments method, for Region-I, for maximum monthly rainfall, GNO was best fitted. For Region-II, GEV was best fitted and PE3 for Region-III. Quantiles for various return periods were estimated using these best-fitted distributions for each region. The performance of both methods i.e. L-moments and PL-moments in quantiles estimation were studied by Monte Carlo simulations. From these simulations, accuracy measures such as relative RMSE and absolute relative bias were calculated and it was observed that these accuracy measures were smaller in the case of PL-moments as compared to L-moments. Also, quantiles were estimated using the regional and at-site base approach. The performance of regional and at-site based rainfall quantiles was studied in terms of relative RMSE. It was observed that regional analysis provided better estimates of the quantiles compared to the at-site based estimation.
  • Thumbnail Image
    ThesisItemOpen Access
    Spatial and temporal distribution of monthly rainfall in Haryana
    (CCSHAU, 2016) Nain, Mohit; Hooda, B.K.
    The analysis of monthly rainfall pattern of a region over a number of years is very useful for crop planning and irrigations scheduling. The present study focused on the probability distribution of monthly rainfall in various IMD rain gauge stations and identification of homogeneous rainfall regions in Haryana. The spatial and temporal distribution of monthly rainfall for the period 1970-2011, covering 27 rain gauge stations of Haryana has been studied. Probabilities of drought, normal and abnormal events for monthly rainfall were worked out. The results revealed that drought months are more probable than normal months while normal months are more probable than abnormal months. In case of yearly rainfall, normal years are more probable than drought and abnormal years. For examining the monotonic trend direction and magnitude of change over time, the Mann-Kendall test and Sen’s slope estimator tests were used. Increasing as well as decreasing trends were observed at various rain gauge stations. A significant decrease in annual rainfall was noticed at Ballabgarh and Thanesar while significant increasing trend was noticed at Sirsa only. In monsoon rainfall a significant decreasing trend was observed at Thanesar and Narnaul while significant increasing trend at Sirsa. Clustering of rainfall stations for monsoon period was done using Ward’s method applied on the common principal components scores (CPCs). The results indicated that there are 4 clusters of rain gauge stations having similar monsoon rainfall spread over Haryana. Cluster analysis of mean monthly rainfall was also performed using Ward’s method. The two analyses gave the patterns in close agreement.