scholarly journals RAINFALL TREND ANALYSIS OF KOLLI HILL, TAMIL NADU, INDIA

MAUSAM ◽  
2021 ◽  
Vol 66 (1) ◽  
pp. 151-154
Author(s):  
K. REMYA ◽  
A. RAMACHANDRAN ◽  
DIVYASUBASH KUMAR ◽  
P. RADHAPRIYA ◽  
P MALINI ◽  
...  
Keyword(s):  
Trend Analysis ◽  
Tamil Nadu ◽  
Rainfall Trend

scholarly journals Rainfall Trend Analysis by ANN Method

2020 ◽  
Vol 9 (6) ◽  
pp. 1437-1447
Author(s):  
Bhupendra Dhankar ◽  
Gunja Dhruw
Keyword(s):  
Trend Analysis ◽  
Rainfall Trend

scholarly journals Monitoring and mapping of seasonal vegetation trend in Tamil Nadu using NDVI and NDWI imagery

2019 ◽  
Vol 11 (1) ◽  
pp. 54-61 ◽  
Author(s):  
P.J. Prajesh ◽  
Balaji Kannan ◽  
S. Pazhanivelan ◽  
K.P. Ragunath
Keyword(s):  
Trend Analysis ◽  
Tamil Nadu ◽  
Vegetation Index ◽  
Regional Scale ◽  
Negative Trend ◽  
Positive Trend ◽  
Vegetation Growth ◽  
Kharif Season ◽  
Regression Slope ◽  
Land Covers

In order to monitor vegetation growth and development over the districts and land covers of Tamil Nadu, India during the crop growing season viz., Khairf and Rabi of 2017, Moderate Resolution Imaging Spectroradiometer (MODIS) derived surface reflectance product (MOD09A1) which is available at 500 m resolution and 8-day temporal period was used to derive a time series based Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) for monitoring and mapping terrestrial vegetation trend analysis which showed areas in Tamil Nadu having vegetation greening and vegetation browning. The regression slope values derived from the trend analysis was utilized and the NDVI and NDWI seasonal trend showed majority of area in Tamil Nadu falling under positive trend during the Kharif season (86.52 per cent for NDVI and 90.29 per cent for NDWI). While irrespective of land cover classes, NDVI and NDWI during Kharif season showed a greater positive trend (greening) with least negative trend (browning) for vegetation growth over the land covers whereas during Rabi season it was observed to have a mix of positive trend and negative trend over the land covers. This study was carried out to show that a systematic study can be done for understanding changes over the landscape through the use of high spatial resolution satellite dataset such as MODIS, which provides detailed spatial and temporal description at regional scale. While a trend analysis using regression slope values can be considered for demonstrating the spatial and temporal consistency on land and vegetation dynamics.

scholarly journals Comparison of Statistical Methods to Graphical Methods in Rainfall Trend Analysis: Case Studies from Tropical Catchments

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Upaka Rathnayake
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Climatic Factors ◽  
Data Series ◽  
Graphical Methods ◽  
Rainfall Trend ◽  
Comparison Analysis ◽  
Analysis Techniques ◽  
Rainfall Trends ◽  
Time Series Analyses

Time series analyses for climatic factors are important in climate predictions. Rainfall is being one of the most important climatic factors in today’s concern for future predictions; thus, many researchers analyze the data series for identifying potential rainfall trends. The literature shows several methods in identifying rainfall trends. However, statistical trend analysis using Mann–Kendall equation and graphical trend analysis are the two widely used and simplest tests in trend analysis. Nevertheless, there are few studies in comparing various methods in the trend analysis to suggest the simplest methods in analyzing rainfall trends. Therefore, this paper presents a comparison analysis of statistical and graphical trend analysis techniques for two tropical catchments in Sri Lanka. Results reveal that, in general, both trend analysis techniques produce comparable results in identifying rainfall trends for different time steps including annual, seasonal, and monthly rainfalls.

scholarly journals Advanced Rainfall Trend Analysis of 117 Years over West Coast Plain and Hill Agro-Climatic Region of India

Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1225
Author(s):  
Atul Saini ◽  
Netrananda Sahu ◽  
Pankaj Kumar ◽  
Sridhara Nayak ◽  
Weili Duan ◽  
...  
Keyword(s):  
Trend Analysis ◽  
West Coast ◽  
Winter Season ◽  
Recurrence Interval ◽  
Annual Rainfall ◽  
Rainfall Trend ◽  
Climatic Region ◽  
Monotonic Trend ◽  
Slope Test ◽  
The Impact

In this paper, the rainfall trend of the West Coast Plain and Hill Agro-Climatic Region is analyzed for 117 years (1901–2017). This region is a globally recognized biodiversity hotspot and known for one of the highest rainfall receiving regions in India. Rainfall grid dataset is used for the analysis of rainfall trends on monthly, seasonal, and decadal time scales. Modified Mann–Kendall’s test, Linear Regression, Innovative Trend Analysis, Sen’s Slope test, Weibull’s Recurrence Interval, Pearson’s Coefficient of Skewness, Consecutive Disparity Index, Kurtosis, and some other important statistical techniques are employed for trend analysis. Results indicate that the rainfall trend is significant in January, July, August, September as well as the Winter season. Among all the significant trends, January and July showed a decreasing rainfall trend. July has the highest contribution (30%) among all the obtained monotonic trend to annual rainfall and coincidentally has the highest trend magnitude. August and September months with a combined contribution of 30% to annual rainfall, show an increasing monotonic trend with high magnitude whereas Winter season shows a monotonic decreasing rainfall trend with comparatively low magnitudes. Decadal analysis along with the study of recurrence interval of excess and deficit years helps to understand the decadal rhythm of trend and the magnitude of extreme monthly and seasonal events. Skewness reveals that rainfall dataset of all the periodic results is right-skewed and the recurrence interval also supports the skewness results. Sharply decreasing rainfall in July and rising rainfall in August and September is predictive of the impact on agriculture, biodiversity and indicates the rainfall regime shift in the region.

scholarly journals Evaluation of wind energy potential of the state of Tamil Nadu, India based on trend analysis

2021 ◽  
Vol 49 (1) ◽  
pp. 244-251
Author(s):  
Narayanan Natarajan ◽  
S. Rehman ◽  
Nandhini Shiva ◽  
M. Vasudevan
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Trend Analysis ◽  
Tamil Nadu ◽  
Wind Farm ◽  
Linear Trend ◽  
Energy Output ◽  
Energy Yield ◽  
Energy Potential ◽  
Increasing Trend

An accurate estimate of wind resource assessment is essential for the identification of potential site for wind farm development. The hourly average wind speed measured at 50 m above ground level over a period of 39 years (1980-2018) from 25 locations in Tamil Nadu, India have been used in this study. The annual and seasonal wind speed trends are analyzed using linear and Mann-Kendall statistical methods. The annual energy yield, and net capacity factor are obtained for the chosen wind turbine with 2 Mega Watt rated power. As per the linear trend analysis, Chennai and Kanchipuram possess a significantly decreasing trend, while Nagercoil, Thoothukudi, and Tirunelveli show an increasing trend. Mann-Kendall trend analysis shows that cities located in the southern peninsula and in the vicinity of the coastal regions have significant potential for wind energy development. Moreover, a majority of the cities show an increasing trend in the autumn season due to the influence of the retreating monsoons which is accompanied with heavy winds. The mean wind follows an oscillating pattern throughout the year at all the locations. Based on the net annual energy output, Nagercoil, Thoothukudi and Nagapattinam are found to be the most suitable locations for wind power deployment in Tamil Nadu, followed by Cuddalore, Kumbakonam, Thanjavur and Tirunelveli.

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