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MAUSAM ◽  
2022 ◽  
Vol 46 (2) ◽  
pp. 175-180
Author(s):  
S. A. SASEENDRAN ◽  
K. K. SINGH ◽  
J. BAHADUR ◽  
O. N. DHAR

 The daily rainfall data for 80 years from 98 stations in Kerala region have been analysed to arrive at the Probable Maximum Precipitation (PMP) estimates for rainfall durations or 1 to 10 days. Hershfield's statistical technique has been adopted for the estimation of PMP from annual maximum data. The study will be useful in the estimation of extreme precipitation for computation of design floods, required for design of spillways of dams and other major hydraulic structures in the Kerala state.    


2021 ◽  
Vol 12 (23) ◽  
pp. 61-71
Author(s):  
Mykola Pashynskyi ◽  
◽  
Victor Pashynskyi ◽  
Evgeniy Klymenko ◽  
◽  
...  

The aim of this work is to improve a method for determining the characteristic values of climatic loads according to a probabilistic model of the annual maxima sequence, by choosing a rational type of generalized extreme value distribution law. An analysis is provided regarding the suitability of using four types of distributions for describing a data collection of maximum values of climatic loads. Using example data from the meteorological stations of Ukraine, it is found that for coefficients of variation smaller than 0.85–1.0, it is advisable to use the double exponential Gumbel distribution (generalized extreme value distribution type-I), and at higher values of the coefficient of variation, it is advisable to use the Weibull distribution (generalized extreme value distribution type-III). Recommendations are provided for considering the accuracy in the estimations of the characteristic values of loads according to the probabilistic model for the annual maximum value series.


2021 ◽  
Author(s):  
Na Li ◽  
Shenglian Guo ◽  
Feng Xiong ◽  
Jun Wang ◽  
Yuzuo Xie

Abstract The coincidence of floods in the mainstream and its tributaries may lead to a large flooding in the downstream confluence area, and the flood coincidence risk analysis is very important for flood prevention and disaster reduction. In this study, the multiple regression model was used to establish the functional relationship among flood magnitudes in the mainstream and its tributaries. The mixed von Mises distribution and Pearson Type III distribution were selected to fit the probability distribution of the annual maximum flood occurrence dates and magnitudes, respectively. The joint distributions of the annual maximum flood occurrence dates and magnitudes were established using copula function, respectively. Fuhe River in the Poyang Lake region was selected as a study case. The joint probability, co-occurrence probability and conditional probability of flood magnitudes were quantitatively estimated and compared with the predicted flood coincidence risks. The results show that the selected marginal and joint distributions can fit observed flood dataset very well. The coincidence probabilities of flood occurrence dates in the upper mainstream and its tributaries mainly occur from May to early July. It is found that the conditional probability is the most consistent with the predicted flood coincidence risks in the mainstream and its tributaries, and is more reliable and rational in practice.


2021 ◽  
Author(s):  
Angelo Avino ◽  
Salvatore Manfreda ◽  
Luigi Cimorelli ◽  
Domenico Pianese

MAUSAM ◽  
2021 ◽  
Vol 68 (1) ◽  
pp. 161-168
Author(s):  
VIVEKANAND SINGH ◽  
ANSHUMAN SINGH

In this paper, the variation of temperature and rainfall at Patna are analysed using simple non-parametric tests. The trends in the annual maximum and minimum daily temperatures, annual rainfall, annual maximum daily rainfall, number of rainy days in a year, the annual average rainfall per rainy day and the ratio of maximum to average rainfall per rainy day at Patna have been examined. Tends in total monthly rainfall, Highest daily rainfall in a month and number of rainy days in a month have also been determined for every month in a year. The monthly trends of data using simple Mann-Kendall test indicated statistically significant changes in rainfall pattern for the city.


Author(s):  
Subhankar Biswas ◽  
Ajay Verma ◽  
R. Sendhil ◽  
AK Dixit ◽  
Ajmer Singh ◽  
...  

The cause and effect relationship of climatic variables on milk production of indigenous cattle and buffalo had been carried in West Bengal state during 2019-2020. Regression analysis indicated the indigenous cow milk production was directly responsive to annual minimum temperature, while crossbred cow milk production was indirectly responsive to annual maximum temperature and relative humidity. The buffalo milk production was inversely related to annual maximum temperature and relative humidity. More than half of surveyed farmers had a medium level of experience in farming. Majority of farmers were perceived climate variability in general like increase in temperature during the summer season, late onset of monsoon and early withdrawal of monsoon season. For crop farming, crop diversification was the most preferred adaptation strategy among the farmers followed by changing crop variety. For dairy farming, provide proper shed and shelter was most preferred adaptation strategy followed by provide additional fresh drinking water in summer.


Water ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 3264
Author(s):  
Renato Morbidelli ◽  
Carla Saltalippi ◽  
Jacopo Dari ◽  
Alessia Flammini

The main challenge of this paper is to demonstrate that one of the most frequently conducted analyses in the climate change field could be affected by significant errors, due to the use of rainfall data characterized by coarse time-resolution. In fact, in the scientific literature, there are many studies to verify the possible impacts of climate change on extreme rainfall, and particularly on annual maximum rainfall depths, Hd, characterized by duration d equal to 24 h, due to the significant length of the corresponding series. Typically, these studies do not specify the temporal aggregation, ta, of the rainfall data on which maxima rely, although it is well known that the use of rainfall data with coarse ta can lead to significant underestimates of Hd. The effect of ta on the estimation of trends in annual maximum depths with d = 24 h, Hd=24 h, over the last 100 years is examined. We have used a published series of Hd=24 h derived by long-term historical rainfall observations with various temporal aggregations, due to the progress of recording systems through time, at 39 representative meteorological stations located in an inland region of Central Italy. Then, by using a recently developed mathematical relation between average underestimation error and the ratio ta/d, each Hd=24 h value has been corrected. Successively, commonly used climatic trend tests based on different approaches, including least-squares linear trend analysis, Mann–Kendall, and Sen’s method, have been applied to the “uncorrected” and “corrected” series. The results show that the underestimation of Hd=24 h values with coarse ta plays a significant role in the analysis of the effects of climatic change on extreme rainfalls. Specifically, the correction of the Hd=24 h values can change the sign of the trend from positive to negative. Furthermore, it has been observed that the innovative Sen’s method (based on a graphical approach) is less sensitive to corrections of the Hd values than the least-squares linear trend and the Mann–Kendall method. In any case, the analysis of Hd series containing potentially underestimated values, especially when d = 24 h, can lead to misleading results. Therefore, before conducting any trend analysis, Hd values determined from rainfall data characterized by coarse temporal resolution should always be corrected.


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