Variability and Trend Analysis of the Rainfall of the Past 119 (1901-2019) Years using Statistical Techniques: A Case Study of Uttar Dinajpur, India

2021 ◽  
Vol 7 (2) ◽  
pp. 49-61
Author(s):  
Ajit Sarkar ◽  
Sunil Saha ◽  
Debabrata Sarkar ◽  
Prolay Mondal
Keyword(s):  
Monsoon Season ◽  
Winter Season ◽  
Monthly Rainfall ◽  
Statistical Techniques ◽  
Study Region ◽  
Maximum Rainfall ◽  
Sen’S Slope ◽  
Average Monthly Rainfall ◽  
June July ◽  
The Impact

The present study aims to identify and measure the impact of climate change on rainfall patterns in the Uttar Dinajpur district of West Bengal. The hydro-meteorological time series rainfall data was collected from the IMD and CHRS data portals and subsequently analysed using various statistical methods. Agriculture in this district is the main economic activity, but the rainfall propensity is very unpredictable and sporadic that has a significant impact on agriculture. The rainfall results (1901-2019) were examined and assessed using statistical techniques for Mann-Kendall’s Z-statistic and Sen’s slope estimators. From the estimation, it is understood that the pre-monsoon, monsoon, and winter seasons have positive trends in rainfall, whereas the post-monsoon rainfall shows a negative trend and both Mann-Kendall and Sen’s slope projections depict the same. Likewise, January, February, April, May, June, July, August, and December reflect upward positive change, while a downward trend (decline trend) was recorded in March, September, and October. The winter Kharif crops are more impacted by this negative or decreasing pattern of seasonal rainfall than other crops. The maximum average monthly rainfall in July (892.1 mm) and January showed the lowest average monthly rainfall of 63.3 mm. The results revealed that during the monsoon season the maximum rainfall (75.2%) occurred and the coefficient of variance value is 20.4%. In the winter season, the minimal rainfall (2.87%) with a coefficient of variance (CV) is 72.9%. The rainfall forecast using SMOreg and linear regression methods has been calculated. This research contributes greatly to adopting different strategies by the planners, researchers, numerous government institutions, and NGOs for the overall development of the study area. This study may also be effective in the management of water resources in the study region.

scholarly journals Analysis of rainfall by using Mann-Kendall trend, Sen’s slope and variability at five districts of south Gujarat, India

MAUSAM ◽  
2021 ◽  
Vol 68 (2) ◽  
pp. 205-222 ◽  
Author(s):  
NEERAJ KUMAR ◽  
C. C. PANCHAL ◽  
S. K. CHANDRAWANSHI ◽  
J. D. THANKI
Keyword(s):  
Standard Deviation ◽  
Monsoon Rainfall ◽  
Monsoon Season ◽  
Rainfall Variability ◽  
Winter Season ◽  
Annual Rainfall ◽  
Present Contribution ◽  
Sen’S Slope ◽  
Post Monsoon ◽  
Data Points

On the basis of past 115 years (1901-2015) rainfall data of five districts of south Gujarat, the Mann-Kendall trend, Sen’s slope and regression slope showed that annual and monsoon rainfall at Valsad, Dang and Surat shows the increasing trend while, that of Navsari and Bharuch districts are declining. The monsoon season (summer monsoon) rainfall variability of Valsad, Dang, Surat, Navsari and Bharuch districts was recorded is 30.1%, 30.9%, 35.9%. 33.3% and 38.6%. The high coefficient of variation (CV) denoted that the variability of rainfall is not equally distributed and the amount of rainfall is lowest. The Bharuch district the annual and monsoon CV per cent denoted that the variability of rainfall in both seasons are very high. Valsad was recorded lowest CV with highest rainfall while the data are represent that variability of rainfall which can varies Bharuch to Dang in different districts of south Gujarat. The data shows that Dang district comes under high rainfall and Bharuch under low rainfall on south Gujarat. A low standard deviation indicates that the data points tend to be close to the mean of the set, while a high standard deviation indicates that the data points are spread out over a wider range of values. Similarly high SD is reported at Dang district because of high range of rainfall and lowest SD is found at Bharuch district because of low rainfall variability. The rainfall distribution different season viz., pre monsoon, monsoon post monsoon and winter season, the highest present contribution of rainfall is observed during monsoon season followed by post monsoon in all the five districts of south Gujarat. Rainfall contribution during remaining months was less than one per cent. While month wise analysis shows during monsoon season highest rainfall per cent contribution to annual rainfall is in July followed by August and June months at all the five districts of south Gujarat.

scholarly journals A Study of Change in Rainfall Pattern in Anand (middle Gujarat) in the last 60 years (1958-2017)

2019 ◽  
Vol 14 (1) ◽  
pp. 128-133
Author(s):  
Kapil Mandloi ◽  
G.J. Kamani ◽  
S.S. Chinchorkar
Keyword(s):  
Rainfall Intensity ◽  
Monthly Rainfall ◽  
Rainfall Pattern ◽  
Annual Data ◽  
Maximum Rainfall ◽  
Rainfall Analysis ◽  
Rainfall Variation ◽  
Average Monthly Rainfall ◽  
Term Data

The analysis of rainfall records for long period provides information about rainfall pattern and variability. The long term monthly rainfall data for the period 1958-2017 (60 years) was studied. And also rainfall studies are the utmost utility for understanding the nature and behaviour of climate change. In this study, trends in rainfall, maximum rainfall intensity and rainy day for 1958-2017 were examined. Long term data analysed for 60 years (1958-2017) annual data suggest that there is a significant change in rainfall over the last decade. It observed that total mean rainfall June to October but in by 50.04mm last 60 years and annual rainy days decreased by 0.017 mm per year. From the average monthly rainfall analysis, it is observed that rainfall variation for first 20 years (1958-1978) and second 20 years (1979-1999) are similar rainfall pattern whereas it differs for last decade (2000-2017) because of the change in magnitude however the overall trend is similar. Average monthly rainfall analysis indicates there is maximum rainfall in the month of June and minimum rainfall in the month of October.

scholarly journals Using Markov Analysis to Study the Impact of Temperature in Bangladesh

2019 ◽  
Vol 6 (2) ◽  
pp. 69-76
Author(s):  
Janardan Mahanta ◽  
Soumen Kishor Nath ◽  
Md. Haronur Rashid
Keyword(s):  
Historical Data ◽  
Monsoon Season ◽  
Winter Season ◽  
Surface Air Temperature ◽  
Markov Analysis ◽  
Average Temperature ◽  
Chain Analysis ◽  
The Impact ◽  
Stationary Probabilities

In this paper has been studied the temperature trend in Bangladesh. Long-term changes of surface air temperature over Bangladesh have been studied using the available historical data collected by the Bangladesh meteorological Department (BMD). Daily temperature data is collected from BMD in Dhaka and Chittagong. Then month have been divided according to season and their descriptive statistics are computed. Maximum average temperature in pre-monsoon season and minimum average temperature in winter season have been shown in the paper. This study also reveals that temperature has increased over the time. Markov chain analysis has been applied for these data so as to find the stationary probability. After 26 and 13 days stationary probabilities in Dhaka and Chittagong stations respectively have observed.

scholarly journals Pemetaan Curah Hujan Dalam Upaya Mengurangi Resiko Bencana Hidrometeorologi Dengan Sistem Informasi Geografis (SIG) Untuk Wilayah Kalimantan Utara

2020 ◽  
Vol 3 (2) ◽  
pp. 129-142
Author(s):  
Rachel Zandra Singal ◽  
Noptri Jumario
Keyword(s):  
Monthly Rainfall ◽  
Rainfall Data ◽  
Maximum Rainfall ◽  
Rainfall Analysis ◽  
High Rainfall ◽  
The North ◽  
Spatial Analyst ◽  
Average Monthly Rainfall ◽  
Rainfall Map ◽  
Source Of Information

North Kalimantan is one of the regions in Indonesia which is prone to hydrometeorological disasters. The purpose of this study was to determine the rainfall analysis of the North Kalimantan Region as a basis in finding rainfall levels in areas that do not have climatological stations, knowing the rainfall maps of the North Kalimantan Region and knowing the conditions of high rainfall causing flood prone in the North Kalimantan region. Rainfall data collection locations are climatology stations Tanjung Harapan, Juwata, Tuvai Semaring, Kalimarau and R.A. Bessing. Rainfall data is taken from OGIMET for 10 years. The result of rainfall analysis is the average monthly rainfall, which is from January to December. The method used to determine the monthly rainfall value in the North Kalimantan region is the Spatial Analyst Interpolation -Kriging method. The results are in the form of monthly rainfall maps, from January to December. Monthly rainfall map is a source of information on the value of rainfall in the region in North Kalimantan. Maximum rainfall is found in the areas of Tanjung Selor and Tarakan, namely January 313,368 mm, May 366,238 mm, July 358,868 mm and December 324,513 mm. Map of monthly rainfall in January, May, July and December is a parameter to see the condition of high rainfall causing hydrometeorological disasters. Through this research it is expected to anticipate the risk of disasters caused by the weather.

PREVALENCE OF PSEUDOINVERTA ORAIENSIS IN FRESH WATER FISH, CLARIAS BATRACHUS

2019 ◽  
Vol 25 (1) ◽  
Author(s):  
ADITYA NARAYAN
Keyword(s):  
Fresh Water ◽  
Monsoon Season ◽  
Winter Season ◽  
Uttar Pradesh ◽  
Summer Season ◽  
Clarias Batrachus ◽  
Fresh Water Fish ◽  
Water Fish

The present investigation deals with the prevalence of infection of cestode, Pseudoinverta oraiensis19 parasitizing Clarias batrachus from Bundelkhand Region (U.P.) India. The studies were recorded from different sampling stations of Bundelkhand region of Uttar Pradesh. For this study 360 fresh water fish, Clarias batrachus were examined. The incidence of infection, monsoon season (17.50%) followed by winter season (20.00%) whereas high in summer season (30.00%).

1033 REDUCING NITROGEN FERTILIZER APPLICATIONS BY BALANCING THE NITROGEN SULFUR RATIO

HortScience ◽  
1994 ◽  
Vol 29 (5) ◽  
pp. 576d-576
Author(s):  
Ellen T. Paparozzi
Keyword(s):  
Groundwater Contamination ◽  
Nitrogen Fertilizer ◽  
Nutrient Balance ◽  
Ornamental Plants ◽  
Consumer Perceptions ◽  
Consumer Acceptance ◽  
Statistical Techniques ◽  
Physiological Processes ◽  
The Impact ◽  
Future Plans

Fertilizer particularly nitrogen is part of the concern about groundwater contamination. Many floricultural and ornamental plants do not need the high rates of nitrogen that are typically recommended. However, whenever one alters the quantity of a given nutrient the overall nutrient balance, as well as other physiological processes, changes. A brief overview of our research on poinsettias, roses, and chrysanthemums will be presented. Suggested ratios, critical S levels and nutrient problems associated with incorrect balances will be shared. Limitations due to statistical methods and the impact nutrient balance has on certain plant processes such as flowering and coloring and thus, consumer acceptance will be summarized. Future plans in this area may focus on the need for new statistical techniques, nutrient acquisition by roots and consumer perceptions of plant quality.

scholarly journals India’s Commitments to Increase Tree and Forest Cover: Consequences for Water Supply and Agriculture Production within the Central Indian Highlands

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 959
Author(s):  
Benjamin Clark ◽  
Ruth DeFries ◽  
Jagdish Krishnaswamy
Keyword(s):  
Groundwater Recharge ◽  
Forest Cover ◽  
Hydrological Modeling ◽  
Monsoon Season ◽  
Forest Policy ◽  
Central India ◽  
Field Measurements ◽  
Tree Cover ◽  
Policy Goals ◽  
The Impact

As part of its nationally determined contributions as well as national forest policy goals, India plans to boost tree cover to 33% of its land area. Land currently under other uses will require tree-plantations or reforestation to achieve this goal. This paper examines the effects of converting cropland to tree or forest cover in the Central India Highlands (CIH). The paper examines the impact of increased forest cover on groundwater infiltration and recharge, which are essential for sustainable Rabi (winter, non-monsoon) season irrigation and agricultural production. Field measurements of saturated hydraulic conductivity (Kfs) linked to hydrological modeling estimate increased forest cover impact on the CIH hydrology. Kfs tests in 118 sites demonstrate a significant land cover effect, with forest cover having a higher Kfs of 20.2 mm hr−1 than croplands (6.7mm hr−1). The spatial processes in hydrology (SPHY) model simulated forest cover from 2% to 75% and showed that each basin reacts differently, depending on the amount of agriculture under paddy. Paddy agriculture can compensate for low infiltration through increased depression storage, allowing for continuous infiltration and groundwater recharge. Expanding forest cover to 33% in the CIH would reduce groundwater recharge by 7.94 mm (−1%) when converting the average cropland and increase it by 15.38 mm (3%) if reforestation is conducted on non-paddy agriculture. Intermediate forest cover shows however shows potential for increase in net benefits.

scholarly journals Vertical to Horizontal UHS Ratios for Low to Medium Seismicity Regions with Deep Soil atop Deep Geological Sediments—An Example of the City of Osijek, Croatia

2021 ◽  
Vol 11 (15) ◽  
pp. 6782
Author(s):  
Borko Đ. Bulajić ◽  
Marijana Hadzima-Nyarko ◽  
Gordana Pavić
Keyword(s):  
Ground Motions ◽  
Spectral Amplitude ◽  
Eurocode 8 ◽  
Uniform Hazard Spectra ◽  
Study Region ◽  
Spectral Estimates ◽  
Local Soil ◽  
The Impact ◽  
Deep Soils ◽  
The City

The severity of vertical seismic ground motions is often factored into design regulations as a component of their horizontal counterparts. Furthermore, most design codes, including Eurocode 8, ignore the impact of local soil on vertical spectra. This paper investigates vertical pseudo-absolute acceleration spectral estimates, as well as the ratios of spectral estimates for strong motion in vertical and horizontal directions, for low to medium seismicity regions with deep local soil and deep geological sediments beneath the local soil. The case study region encompasses the city of Osijek in Croatia. New regional frequency-dependent empirical scaling equations are derived for the vertical spectra. According to these equations, for a 0.3 s spectral amplitude at deep soils atop deep geological sediments compared to the rock sites, the maximum amplification is 1.48 times. The spectra of vertical components of various real strong motions recorded in the surrounding region are compared to the empirical vertical response spectra. The new empirical equations are used to construct a Uniform Hazard Spectra for Osijek. The ratios of vertical to horizontal Uniform Hazard Spectra are generated, examined, and compared to Eurocode 8 recommendations. All the results show that local soil and deep geology conditions have a significant impact on vertical ground motions. The results also show that for deep soils atop deep geological strata, Eurocode 8 can underestimate the vertical to horizontal spectral ratios by a factor of three for Type 2 spectra while overestimating them by a factor of two for Type 1 spectra.

scholarly journals Biodiversity of butterflies in endosulfan-affected areas of Kerala, India

2020 ◽  
Vol 81 (1) ◽  
Author(s):  
K. N. Raghavendra ◽  
Kumar Arvind ◽  
G. K. Anushree ◽  
Tony Grace
Keyword(s):  
Monsoon Season ◽  
Winter Season ◽  
Wiener Index ◽  
Long Term Effects ◽  
Affected Area ◽  
Butterfly Assemblages ◽  
Abundance And Diversity ◽  
The One ◽  
One Way Anova

Abstract Background Butterflies are considered as bio-indicators of a healthy and diversified ecosystem. Endosulfan was sprayed indiscriminately in large plantations of Kasaragod district, Kerala which had caused serious threats to the ecosystem. In this study, we surveyed the butterflies for their abundance and diversity in three differentially endosulfan-affected areas viz., Enmakaje—highly affected area, Periye—moderately affected area, Padanakkad—unaffected area, carried out between the end of the monsoon season and the start of the winter season, lasting approximately 100 days. Seven variables viz., butterfly abundance (N), species richness (S), Simpson’s reciprocal index (D), the Shannon–Wiener index (H′), the exponential of the Shannon–Wiener index (expH′), Pielou’s evenness (J) and species evenness (D/S), related to species diversity were estimated, followed by the one-way ANOVA (F = 25.01, p < 0.001) and the Kruskal-Wallis test (H = 22.59, p < 0.001). Results A population of three different butterfly assemblages comprised of 2300 butterflies which represented 61 species were encountered. Our results showed that Enmakaje displayed significantly lower butterfly diversity and abundance, compared to the other two communities. Conclusion So far, this is the first study concerning the effect of endosulfan on the biodiversity of butterfly in the affected areas of Kasaragod, Kerala, India. This study may present an indirect assessment of the persisting effects of endosulfan in the affected areas, suggesting its long-term effects on the ecosystem.

scholarly journals Seasonal Rainfall Forecasts for the Yangtze River Basin in the Extreme Summer of 2020

2021 ◽  
Author(s):  
Philip E. Bett ◽  
Gill M. Martin ◽  
Nick Dunstone ◽  
Adam A. Scaife ◽  
Hazel E. Thornton ◽  
...  
Keyword(s):  
Linear Regression ◽  
River Basin ◽  
Yangtze River ◽  
Asian Summer Monsoon ◽  
Yangtze River Basin ◽  
Early Summer ◽  
Lead Times ◽  
Seasonal Forecasts ◽  
June July ◽  
The Impact

AbstractSeasonal forecasts for Yangtze River basin rainfall in June, May–June–July (MJJ), and June–July–August (JJA) 2020 are presented, based on the Met Office GloSea5 system. The three-month forecasts are based on dynamical predictions of an East Asian Summer Monsoon (EASM) index, which is transformed into regional-mean rainfall through linear regression. The June rainfall forecasts for the middle/lower Yangtze River basin are based on linear regression of precipitation. The forecasts verify well in terms of giving strong, consistent predictions of above-average rainfall at lead times of at least three months. However, the Yangtze region was subject to exceptionally heavy rainfall throughout the summer period, leading to observed values that lie outside the 95% prediction intervals of the three-month forecasts. The forecasts presented here are consistent with other studies of the 2020 EASM rainfall, whereby the enhanced mei-yu front in early summer is skillfully forecast, but the impact of midlatitude drivers enhancing the rainfall in later summer is not captured. This case study demonstrates both the utility of probabilistic seasonal forecasts for the Yangtze region and the potential limitations in anticipating complex extreme events driven by a combination of coincident factors.

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