Trend analysis and ARIMA modelling of pre-monsoon rainfall data for western India

2013 ◽  
Vol 345 (1) ◽  
pp. 22-27 ◽  
Author(s):  
Priya Narayanan ◽  
Ashoke Basistha ◽  
Sumana Sarkar ◽  
Sachdeva Kamna
Keyword(s):  
Trend Analysis ◽  
Monsoon Rainfall ◽  
Rainfall Data ◽  
Western India

scholarly journals Water–food–energy nexus with changing agricultural scenarios in India during recent decades

2017 ◽  
Vol 21 (6) ◽  
pp. 3041-3060 ◽  
Author(s):  
Beas Barik ◽  
Subimal Ghosh ◽  
A. Saheer Sahana ◽  
Amey Pathak ◽  
Muddu Sekhar
Keyword(s):  
Food Production ◽  
Monsoon Rainfall ◽  
Central India ◽  
Recent Decade ◽  
High Energy ◽  
Western India ◽  
Groundwater Storage ◽  
Ganga Basin ◽  
Strong Negative Correlation ◽  
Food Energy

Abstract. Meeting the growing water and food demands in a densely populated country like India is a major challenge. It requires an extensive investigation into the changing patterns of the checks and balances behind the maintenance of food security at the expense of depleting groundwater, along with high energy consumption. Here we present a comprehensive set of analyses which assess the present status of the water–food–energy nexus in India, along with its changing pattern, in the last few decades. We find that with the growth of population and consequent increase in the food demands, the food production has also increased, and this has been made possible with the intensification of irrigation. However, during the recent decade (after 1996), the increase in food production has not been sufficient to meet its growing demands, precipitating a decline in the per-capita food availability. We also find a statistically significant declining trend of groundwater storage in India during the last decade, as derived from the Gravity Recovery and Climate Experiment (GRACE) satellite datasets. Regional studies reveal contrasting trends between northern and western–central India. North-western India and the middle Ganga basin show a decrease in the groundwater storage as opposed to an increasing storage over western–central India. Comparison with well data reveals that the highest consistency of GRACE-derived storage data with available well measurements is in the middle Ganga basin. After analysing the data for the last 2 decades, we further showcase that, after a drought, the groundwater storage drops but is unable to recover to its original condition even after good monsoon years. The groundwater storage reveals a very strong negative correlation with the electricity consumption for agricultural usage, which may also be considered as a proxy for groundwater pumped for irrigation in a region. The electricity usage for agricultural purposes has an increasing trend and, interestingly, it does not have any correlation with the monsoon rainfall as computed with the original or de-trended variables. This reveals an important finding that the irrigation has been intensified irrespective of rainfall. This also resulted in a decreasing correlation between the food production and monsoon rainfall, revealing the increasing dependency of agricultural activities on irrigation. We conclude that irrigation has now become essential for agriculture to meet the food demand; however, it should be judiciously regulated and controlled, based on the water availability from monsoon rainfall, specifically after the drought years, as it is essential to recover from the deficits suffered previously.

Genetic improvement trend analysis for end-use quality characteristics among wheat cultivars of North-Western India

2016 ◽  
Vol 76 (2) ◽  
pp. 137 ◽  
Author(s):  
Soma Gupta ◽  
Rajbir Yadav ◽  
Kiran Gaikwad ◽  
Ashutosh Kushwah ◽  
Anju M. Singh ◽  
...  
Keyword(s):  
Trend Analysis ◽  
Genetic Improvement ◽  
Quality Characteristics ◽  
Western India ◽  
Wheat Cultivars ◽  
End Use ◽  
North Western

scholarly journals DYNAMICS PATTERNS OF INFLOW IN THE RESERVOIR THAT OPERATED FOR TWO DECADES

2021 ◽  
Vol 56 (4) ◽  
pp. 92-103
Author(s):  
Heriantono Waluyadi ◽  
Pitojo Tri Juwono ◽  
Widandi Soetopo ◽  
Rispiningtati ◽  
Lily Montarcih Limantara ◽  
...  
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Rainfall Data ◽  
Operation Pattern ◽  
The Pacific ◽  
Ocean Region ◽  
Reservoir Watershed ◽  
June July

Climate change in the past 20 years brings significant alteration in the earth surface. It affects extremely anomaly temperature, such as the ENSO, IOD, and SOI phenomena. The Pacific Ocean Region, the Indian Ocean Region, and the Darwin – Tahiti Region undergo an increase and a decrease in the sea surface temperatures (SST); thus, it can lead to seasonal change in Indonesia. Due to ENSO, IOD, and SOI, climate change also highly affects the operation pattern of reservoirs, food production, and other commodities. This research used SST data (Nino 1.2, Nino 3, Nino 3.4, Nino 4, IOD West, IOD East, and SOI) from National Oceanic and Atmospheric Administration (NOAA) and rainfall data from 1998 to 2018 of nine stations at Wonogiri Reservoir watershed. Trend analysis of the SST index indicated an increase in trend SST index. Trend analysis of monthly rainfall average at Wonogiri Watershed area indicated a decrease in January, March, April, May, June, July, August, and October, while it increased in February, September, November, and December. Multiple linear regression analysis with the stepwise regression method indicated that during the rainy season, the rainfall at Wonogiri Watershed and Inflow at Wonogiri reservoir were influenced by the SST index (Nino 1.2, Nino 3, Nino 3.4, Nino 4). Meanwhile, during the dry season, the rainfall at Wonogiri Watershed and the Inflow at Wonogiri reservoir were influenced by the SST index (IOD West, IOD East, and SOI). With monthly correlations between SST and rainfall data that have a dynamic characteristic, it can be used to calculate the inflow probability distribution in optimizing reservoir operation patterns.

scholarly journals Long term rainfall variability and trend analysis in lower Shivaliks of Punjab, India

MAUSAM ◽  
2021 ◽  
Vol 72 (3) ◽  
pp. 571-582
Author(s):  
NAVNEET KAUR ◽  
ABRAR YOUSUF ◽  
M. J. SINGH
Keyword(s):  
Trend Analysis ◽  
Monsoon Rainfall ◽  
Rainfall Variability ◽  
Kendall Test ◽  
Annual Rainfall ◽  
Entire Study ◽  
Seasonal Basis ◽  
Normal Rainfall ◽  
Rainy Days

The trend analysis of historical rainfall data on monthly, annual and seasonal basis for three locations in lower Shivaliks of Punjab, viz., Patiala-ki-Rao (1982-2015), Ballowal Saunkhri (1987-2015) and Saleran (1984-2017) has been done in the present study using linear regression model, Mann Kendall test and Sen’s slope. Further, the data for annual and seasonal rainfall and rainy days has also been analyzed on quindecennial basis, i.e., for the period of 1986-2000 and 2001-2015. The analysis of data showed that annual rainfall in the region ranged from 1000 to 1150 mm. The trend analysis of the data shows that the monthly rainfall is decreasing at Patiala-ki-Rao and Saleran, however, the trend was significant for May at Patiala-ki-Rao; and in March and November at Saleran. At Ballowal Saunkhri, the decreasing trend is observed from May to October, however, the trend is significant only in August. The decrease in annual and monsoon rainfall is about 13 to 17 mm and 12 to 13 mm per year respectively at three locations in lower Shivaliks of Punjab. The highest annual (1600-2000 mm) and monsoon (1500-1800 mm) rainfall during the entire study period was recorded in the year 1988 at three locations. The decadal analysis of the data shows below normal rainfall during April to October. The analysis of the rainfall and rainy days on monthly, annual and seasonal averages of 15 year basis showed that both rainfall and rainy days have decreased during the 2001-2015 as compared to 1986-2000 during all the seasons of the year.

Trend Analysis of Rainfall Data in Divisional Meteorological Stations of Bangladesh

2020 ◽  
Vol 23 (1) ◽  
pp. 49-61
Author(s):  
M Noorunnahar ◽  
MA Hossain
Keyword(s):  
Trend Analysis ◽  
Statistical Tests ◽  
Statistical Significance ◽  
Kendall Test ◽  
Monthly Rainfall ◽  
Rainfall Data ◽  
Total Rainfall ◽  
Annual Total ◽  
Level Of Significance ◽  
Non Parametric

Sixty four years, 1952-2016, rainfall data (monthly rainfall and annual total rainfall) were analyzed using non-parametric methods like Mann-Kendall and Sen’s T test to detect the recent trends in rainfall pattern over seven divisions of Bangladesh. Sen’s non-parametric estimator of slope was frequently used to estimate the magnitude of trend, whose statistical significance was assessed by the Mann–Kendall test. Station basis trend analysis was performed for rainfall data. For rainfall of Bangladesh most of the stations, viz. Dhaka, Sylhet, Rangpur, Khulna showed significant upward trend. There were rising rates of rainfall in some months such as April in Rangpur and September in Khulna and a decreasing trend in some other months as in January in Sylhet were obtained by these statistical tests suggested overall significant changes in rainfall trend in these areas. Monthly rainfall and annual total rainfall were found to decrease at the rates of 4.94 mm/year and 16.11 mm/year, respectively, where the downward trend of monthly total rainfall was insignificant but the trend of annual total rainfall was significant with 5% level of significance. Ann. Bangladesh Agric. (2019) 23(1) : 49-61

scholarly journals Insights from a joint analysis of Indian and Chinese monsoon rainfall data

2011 ◽  
Vol 15 (8) ◽  
pp. 2709-2715 ◽  
Author(s):  
M. Zhou ◽  
F. Tian ◽  
U. Lall ◽  
H. Hu
Keyword(s):  
Large Scale ◽  
Monsoon Rainfall ◽  
Indian Monsoon ◽  
Southern China ◽  
Principal Component ◽  
Northern China ◽  
Rainfall Data ◽  
Joint Analysis ◽  
Climate Indices ◽  
The Common

Abstract. Monsoon rainfall is of great importance for agricultural production in both China and India. Understanding the features of the Indian and Chinese monsoon rainfall and its long term predictability is a challenge for research. In this paper Principal Component Analysis (PCA) method was adopted to analyze Indian monsoon and Chinese monsoon separately as well as jointly during the period 1951 to 2003. The common structure of Indian monsoon and Chinese monsoon rainfall data was explored, and its correlation with large scale climate indices and thus the possibility of prediction were analyzed. The joint PCA results gives a clearer correlation map between Chinese monsoon rainfall and Indian monsoon rainfall. The common rainfall structure presents a significant teleconnection to Sea Surface Temperature anomaly (SSTa), moisture transport and other climate indices. Specifically, our result shows that Northern China would garner less rainfall when whole Indian rainfall is below normal, and with cold SSTa over the Indonesia region more rainfall would be distributed over India and Southern China. The result also shows that SSTa in the previous winter months could be a good indicator for the summer monsoon rainfall in China.

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