Rainfall Trend Analysis and Adaptation Strategies to Manage Climate-Induced Crisis in Coastal Zone of Karnataka, India

2017 ◽  
Vol 13 (5) ◽  
pp. 1-11
Author(s):  
H Kumar ◽  
M Shivamurthy ◽  
M Lunagaria
2019 ◽  
pp. 77-104 ◽  
Author(s):  
Karla Diana Infante Ramírez ◽  
Ana Minerva Arce Ibarra

The main objective of this study was to analyze local perceptions of climate variability and the different adaptation strategies of four communities in the southern Yucatán Peninsula, using the Social-Ecological System (SES) approach. Four SESs were considered: two in the coastal zone and two in the tropical forest zone. Data were collected using different qualitative methodological tools (interviews, participant observation, and focal groups) and the information collected from each site was triangulated. In all four sites, changes in climate variability were perceived as “less rain and more heat”. In the tropical forest (or Maya) zone, an ancestral indigenous weather forecasting system, known as “Xook k’íin” (or “las cabañuelas”), was recorded and the main activity affected by climate variability was found to be slash-and burn farming or the milpa. In the coastal zone, the main activities affected are fishing and tourism. In all the cases analyzed, local climate change adaptation strategies include undertaking alternative work, and changing the calendar of daily, seasonal and annual labor and seasonal migration. The population of all four SESs displayed concern and uncertainty as regards dealing with these changes and possible changes in the future.


Author(s):  
Bhupendra Dhankar ◽  
Gunja Dhruw

Author(s):  
Sushanta Sarkar Birendra Kumar ◽  
Sanjay Kumar

2009 ◽  
Author(s):  
S. Shrestha ◽  
S. Riley ◽  
L. Thomas

2018 ◽  
Vol 1 (1) ◽  
pp. 62-75
Author(s):  
Pradip Raj Poudel ◽  
Narayan Raj Joshi ◽  
Shanta Pokhrel

A study on effects of climate change on rice (Oryza sativa) production in Tharu communities of Dang district of Nepal was conducted in 2018A.D to investigate the perception and major adaptation strategies followed by Tharu farmers. The study areas were selected purposively. Cross-sectional data was collected using a household survey of 120 households by applying simple random sampling technique with lottery method for sample selection. Primary data were collected using semi-structured and pretested interview schedule, focus group discussion and key informants interview whereas monthly and annual time series data on temperature and precipitation over 21years (1996-2016) were collected from Department of Hydrology and Meteorology, Kathmandu as secondary data. Descriptive statistics and trend analysis were used to analyze the data. The ratio of male and female was found to be equal with higher literacy rate at study area than district. Most of the farmers depended on agriculture only for their livelihood where there was large variation in land distribution. Farmers had better access to FM/radio for agricultural extension information sources. The study resulted that Tharu farmers of Dang perceived all parameters of climate. Temperature and rainfall were the most changing component of climate perceived by farmers. The trend analysis of temperature data of Dang over 21 years showed that maximum, minimum and average temperature were increasing at the rate of 0.031°C, 0.021°C and 0.072°C per year respectively which supports the farmers perception whereas trend of rainfall was decreased with 7.56mm per year. The yearly maximum rainfall amount was increased by 1.15mm. The production of local indigenous rice varieties were decreasing while hybrid and improved rice varieties were increasing. The district rice production trend was increasing which support the farmer’s perception. The study revealed that there were climate change effects on paddy production and using various adaptation strategies to cope in Dang district.


2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Upaka Rathnayake

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.


Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1225
Author(s):  
Atul Saini ◽  
Netrananda Sahu ◽  
Pankaj Kumar ◽  
Sridhara Nayak ◽  
Weili Duan ◽  
...  

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.


2020 ◽  
Vol 8 (2) ◽  
pp. 201
Author(s):  
Sadikul Islam ◽  
P.R. Ojasvi ◽  
Pankaj Srivastava ◽  
Anand Kumar Gupta ◽  
R.S. Yadav

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