scholarly journals Rainfall Trend Analysis in Uma Oya Basin, Sri Lanka, and Future Water Scarcity Problems in Perspective of Climate Variability

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Bhabishya Khaniya ◽  
Isuru Jayanayaka ◽  
Pradeep Jayasanka ◽  
Upaka Rathnayake
Keyword(s):  
Sri Lanka ◽  
Climate Variability ◽  
Trend Analysis ◽  
Water Scarcity ◽  
Global Climate ◽  
Development Project ◽  
Intermediate Period ◽  
Rainfall Trends ◽  
Dry Zone ◽  
Slope Estimator

The effect of climate variability on the rainfall pattern is canvassed on the Uma Oya river basin, Sri Lanka, consisting of 5 rainfall gauging stations. The Uma Oya basin (720 km2) is given utmost precedence due to environmental concerns seen in the ongoing Uma Oya multipurpose development project (529 million USD worth) which is expected to divert water to the southeast dry zone of the country while adding 231 GWh/year electricity to the national grid. The rainfall data for a period of 26 years (1992–2017) were analysed using Mann–Kendall’s test and Sen’s slope estimator test to identify the rainfall trends. Both of these trend analysis test results depict only one negative trend for Hilpankandura Estate for the month of June; however, the seasonal trend analysis and annual trend analysis do not support this observation. Nevertheless, Mann–Kendall’s test showed potential positive trends for the 3 rainfall gauging stations Kirklees Estate, Ledgerwatte Estate, and Welimada Group only in the 1st intermediate period (March-April), and this is well supported by the monthly trend analysis. Other than these trends, the results do not show any significant negative trends in the Uma Oya catchment. Therefore, the results vividly explain that there is no threat of water scarcity to the catchment area being resistant to changing global climate for the past 26 years.

scholarly journals Comparison of Different Analyzing Techniques in Identifying Rainfall Trends for Colombo, Sri Lanka

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Anushka Perera ◽  
Thilini Ranasinghe ◽  
Miyuru Gunathilake ◽  
Upaka Rathnayake
Keyword(s):  
Sri Lanka ◽  
Trend Analysis ◽  
Water Distribution ◽  
Graphical Method ◽  
Sustainable Use ◽  
Distribution Networks ◽  
Rainfall Trends ◽  
Slope Estimator ◽  
Trend Identification ◽  
Annual Scale

Identifying rainfall trends in highly urbanized area is extremely important for various planning and implementation activities, including designing, maintaining and controlling of water distribution networks and sewer networks and mitigating flood damages. However, different available methods in trend analysis may produce comparable and contrasting results. Therefore, this paper presents an attempt in comparing some of the trend analysis methods using one of the highly urbanized areas in Sri Lanka, Colombo. Recorded rainfall data for 10 gauging stations for 30 years were tested using the MannKendall test, Sen’s slope estimator, Spearman’s rho test, and innovative graphical method. Results showcased comparable findings among three trend identification methods. Even though the graphical method is easier, it is advised to use it with a proper statistical method due to its identification difficulties when the data scatter has some outliers. Nevertheless, it was found herein that Colombo is under a downward rainfall trend in the month of July where the area receives its major rainfall events. In addition, the area has several upward rainfall trends over the minor seasons and in the annual scale. Therefore, the water management activities in the area have to be revisited for a sustainable use of water resources.

scholarly journals Adaptation to climate variability in Sri Lanka: a case study of the Huruluwewa Irrigation System in the Dry Zone

2021 ◽  
Author(s):  
U. A. Amarasinghe ◽  
G. Amarnath ◽  
N. Alahacoon ◽  
M. Aheeyar ◽  
K. Chandrasekharan ◽  
...  
Keyword(s):  
Sri Lanka ◽  
Climate Variability ◽  
Irrigation System ◽  
Dry Zone

scholarly journals Comparison of Statistical, Graphical, and Wavelet Transform Analyses for Rainfall Trends and Patterns in Badulu Oya Catchment, Sri Lanka

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Ashika M. Ruwangika ◽  
Anushka Perera ◽  
Upaka Rathnayake
Keyword(s):  
Climate Change ◽  
Sri Lanka ◽  
Trend Analysis ◽  
Wavelet Transforms ◽  
Kendall Test ◽  
Discrete Wavelet ◽  
Rainfall Trend ◽  
Analysis Methods ◽  
Rainfall Trends ◽  
Mann Kendall Test

Climate change has adversely influenced many activities. It has increased the intensified precipitation events in some places and decreased the precipitation in some other places. In addition, some research studies revealed that the climate change has moved seasons in the temporal scale. Therefore, the changes can be seen in both spatial and temporal scales. Thus, analyzing climate change in the localized environments is highly essential. Rainfall trend analysis in a localized catchment can improve many aspects of water resource management not only to the catchment itself but also to some of the related other catchments. This research is carried to identify the rainfall trends in Badulu Oya catchment, Sri Lanka. The catchment is important as it is in the intermediate climate zone and rich in agricultural productions. Four rain gauges (namely, Badulla, Kandekatiya, Lower Spring Valley, and Ledgerwatte Estate) were used to analyze the rainfalls in the resolutions of monthly, seasonally, and annually. 30-year monthly cumulative rainfall data for the above four gauging stations are analyzed using various standard tests. Nonparametric tests including Mann–Kendall test and sequential Mann–Kendall test and innovative trend analysis methods are used to identify the potential rainfall trends in Badulu Oya catchment. In addition, continuous wavelet transforms and discrete wavelet transforms tests are carried out to check the patterns on rainfall to the catchment. The trend analysis methods are compared against each other to identify the better technique. The results reveal that the nonparametric Mann–Kendall test is powerful to produce the statistically significant rainfall trends in qualitative and quantitative manner. Mann–Kendall analysis shows a positive trend to Ledgerwatte Estate in monthly (3.7 mm in February and 7.4 mm in October), seasonal (6.9 mm in the 2ndintermonsoon), and annual (3 mm annually) scales. However, the analysis records one decreasing rainfall trend to Kandekatiya (8.1 mm in December) only in monthly scale. Nevertheless, it was found that the graphical method can be easily used in qualitative analysis, while discrete wavelet transformations are efficient in identifying the rainfall patterns effectively.

scholarly journals Development of an Interface in MATLAB for Trend Analysis of Hydro-Meteorological Data

2019 ◽  
Author(s):  
J. P. Patil ◽  
A. Sarangi ◽  
D. K. Singh
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Statistical Methods ◽  
Meteorological Data ◽  
Rainfed Agriculture ◽  
Analysis Process ◽  
Mk Test ◽  
Rainfall Trends ◽  
Change Trend ◽  
Slope Estimator

This study presents an interface, ‘Climate Change Trend Analysis (CCTA)’, developed in MATLAB® environment to analyze the trends using non-parametric statistical methods, Mann-Kendall (MK) test and modified Mann-Kendall (MMK) test with Sen’s slope estimator. The interface was used to determine trend in annual and seasonal (kharif) rainfall depths in Pune district acquired from 13 observatories. The developed interface automates the trend analysis process, which can further use for detecting variability and trends in the meteorological as well as other hydrological and agricultural parameters. The observed rainfall trends during monsoon would play a significant role for rainfed agriculture in Pune district.

scholarly journals RAINFALL TRENDS ANALYSIS IN TÂRGU MUREȘ CITY, ROMÂNIA

2021 ◽  
Vol 31 (1) ◽  
pp. 45-56
Author(s):  
Ion BUGLEA ◽  
Keyword(s):  
Standard Deviation ◽  
Trend Analysis ◽  
Coefficient Of Variation ◽  
Kendall Test ◽  
Precipitation Data ◽  
Monthly Average ◽  
Maximum Value ◽  
Rainfall Trends ◽  
Trends Analysis ◽  
Slope Estimator

The aim of this study is the detection of trends of precipitation from (1986-2020) over Târgu Mureș city. Precipitation data for 35 years were processed with MS Excel spreadsheets to find monthly, seasonal and annual variability of rainfall. The Mann-Kendall test was used for trend analysis of precipitation and the Sen’s slope estimator was used for the magnitude of variation. The calculations of the two methods were performed using the MAKESENS program. The standard deviation and the coefficient of variation were used to highlight the dispersion. Results show that all three scales (annual, seasonal and monthly show a tendency to increase rainfall. The highest monthly average of precipitation is 227.70 mm (August, 2005), and the lowest monthly average of precipitation is 0.80 mm (November, 2011). The maximum value of annual precipitation is 852.60 mm and was registered in 2005, and the minimum value was 408.70 mm registered in 2000.

Review of the genus Cnemaspis Strauch, 1887 (Sauria: Gekkonidae) in Sri Lanka with the description of five new species

Zootaxa ◽  
2007 ◽  
Vol 1490 (1) ◽  
pp. 1-63 ◽  
Author(s):  
L. J.MENDIS WICKRAMASINGHE ◽  
D. A.I. MUNINDRADASA
Keyword(s):  
New Species ◽  
Sri Lanka ◽  
Morphometric Analysis ◽  
Mountain Region ◽  
Geographical Isolation ◽  
Morphological Comparison ◽  
Type Series ◽  
Dry Zone ◽  
High Degree ◽  
Wet Zone

Five new species of geckos are described from Sri Lanka by morphological comparison and morphometric analysis leading to review the genus Cnemaspis in the country. The type series of these species were identified from following localities: C. alwisi and C. kumarasinghei from the intermediate zone, C. retigalensis from the dry zone, C. molligodai from the lowland wet zone and C. samanalensis from the mountain region of the wet zone in the country. The high degree of endemicity (90%) shown by Cnemaspis in Sri Lanka could be attributed to geographical isolation. In addition, the taxonomic issue of C. jerdonii scalpensis is discussed and the species C. scalpensis is errected.

scholarly journals Simulation Skills of the SST-Forced Global Climate Variability of the NCEP–MRF9 and the Scripps–MPI ECHAM3 Models

2000 ◽  
Vol 13 (20) ◽  
pp. 3657-3679 ◽  
Author(s):  
Peitao Peng ◽  
Arun Kumar ◽  
Anthony G. Barnston ◽  
Lisa Goddard
Keyword(s):  
Climate Variability ◽  
Global Climate

scholarly journals Techniques for analyses of trends in GRUAN data

2015 ◽  
Vol 8 (4) ◽  
pp. 1673-1684 ◽  
Author(s):  
G. E. Bodeker ◽  
S. Kremser
Keyword(s):  
Measurement Uncertainty ◽  
Trend Analysis ◽  
Global Climate ◽  
Regional Climate ◽  
Added Value ◽  
Least Squares Regression ◽  
Target Uncertainty ◽  
Reference Quality ◽  
Measurement Uncertainties

Abstract. The Global Climate Observing System (GCOS) Reference Upper Air Network (GRUAN) provides reference quality RS92 radiosonde measurements of temperature, pressure and humidity. A key attribute of reference quality measurements, and hence GRUAN data, is that each datum has a well characterized and traceable estimate of the measurement uncertainty. The long-term homogeneity of the measurement records, and their well characterized uncertainties, make these data suitable for reliably detecting changes in global and regional climate on decadal time scales. Considerable effort is invested in GRUAN operations to (i) describe and analyse all sources of measurement uncertainty to the extent possible, (ii) quantify and synthesize the contribution of each source of uncertainty to the total measurement uncertainty, and (iii) verify that the evaluated net uncertainty is within the required target uncertainty. However, if the climate science community is not sufficiently well informed on how to capitalize on this added value, the significant investment in estimating meaningful measurement uncertainties is largely wasted. This paper presents and discusses the techniques that will need to be employed to reliably quantify long-term trends in GRUAN data records. A pedagogical approach is taken whereby numerical recipes for key parts of the trend analysis process are explored. The paper discusses the construction of linear least squares regression models for trend analysis, boot-strapping approaches to determine uncertainties in trends, dealing with the combined effects of autocorrelation in the data and measurement uncertainties in calculating the uncertainty on trends, best practice for determining seasonality in trends, how to deal with co-linear basis functions, and interpreting derived trends. Synthetic data sets are used to demonstrate these concepts which are then applied to a first analysis of temperature trends in RS92 radiosonde upper air soundings at the GRUAN site at Lindenberg, Germany (52.21° N, 14.12° E).

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