Precipitation trends in the Kalu Ganga basin in Sri Lanka

Ampitiyawatta, A. D.

doi:10.4038/jas.v4i1.1641

Cited by 44 publications

(34 citation statements)

References 11 publications

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“…Although the general pattern of rainfall reported by different studies appears to agree to a large extent, still there are some contradictions. For example, Ampitiyawatta and Guo (2009) using monthly and annual data for the period 1965-2004 claimed that rainfall in the whole of the Kalu Ganga Basin has declined, and the decline at the low elevations is more severe than that at the high altitude locations. The entire Kalu Ganga Basin is situated in the highest rainfall region of the Wet Zone.…”

Section: Introductionmentioning

confidence: 98%

Spatial and temporal variation of rainfall trends of Sri Lanka

Wickramagamage

2015

Theor Appl Climatol

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This study was based on daily rainfall data of 48 stations distributed over the entire island covering a 30-year period from 1981 to 2010. Data analysis was done to identify the spatial pattern of rainfall trends. The methods employed in data analysis are linear regression and interpolation by Universal Kriging and Radial Basis function. The slope of linear regression curves of 48 stations was used in interpolation. The regression coefficients show spatially and seasonally variable positive and negative trends of annual and seasonal rainfall. About half of the mean annual pentad series show negative trends, while the rest shows positive trends. By contrast, the rainfall trends of the Southwest Monsoon (SWM) season are predominantly negative throughout the country. The first phase of the Northeast Monsoon (NEM1) displays downward trends everywhere, with the exception of the Southeastern coastal area. The strongest negative trends were found in the Northeast and in the Central Highlands. The second phase (NEM2) is mostly positive, except in the Northeast. The Inter-Monsoon (IM) periods have predominantly upward trends almost everywhere, but still the trends in some parts of the Highlands and Northeast are negative. The long-term data at Watawala Nuwara Eliya and Sandringham show a consistent decline in the rainfall over the last 100 years, particularly during the SWM. There seems to be a faster decline in the rainfall in the last 3 decades. These trends are consistent with the observations in India. It is generally accepted that there has been changes in the circulation pattern. Weakening of the SWM circulation parameters caused by global warming appears to be the main causes of recent changes. Effect of the Asian Brown Cloud may also play a role in these changes.

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Section: Introductionmentioning

confidence: 98%

Spatial and temporal variation of rainfall trends of Sri Lanka

Wickramagamage

2015

Theor Appl Climatol

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“…It helps improve water management strategies, save resources and plan accurate agricultural production activities [10]. Investigation of rainfall trends is vital to the anticipation and management of the potential climate change implications to water resources [11].…”

Section: Introductionmentioning

confidence: 99%

“…Different studies have examined the variability of rainfall over time and space using statistical methods, such as principal component analysis, kriging, and standardized precipitation index (SPI) [10][11][12][13][14]. However, statistical methods have several limitations due to the complexity of the In this context, this paper examines the temporal variability of precipitation in Gabes Basin (south-east of Tunisia), which stands as a representative instance of the arid Mediterranean climate.…”

Section: Introductionmentioning

confidence: 99%

Variability of Precipitation in Arid Climates Using the Wavelet Approach: Case Study of Watershed of Gabes in South-East Tunisia

2017

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This study examines the variability of precipitation in the south-east of Tunisia through the analysis of data about annual and monthly precipitation at five stations in the Watershed of Gabes, from 1977 to 2015. Standardized precipitation ratio, wavelet and coherence wavelet analyses were applied to examine the temporal variability of monthly and annual precipitation and to determine the effect of climatic fluctuations on rainfall variability. Results of wavelet analysis showed varied energy bands at the studied stations at annual and inter-annual scales. The depicted bands spread according to intervals of 1-, 2-to 4-, 4-to 8-and 8-to 12-year cycles, obviously influenced by regional factors including altitude, proximity to the Mediterranean Sea and global fluctuations. Eventually, an analysis of wavelet coherence showed a strong correlation between precipitation and Mediterranean Oscillation (MO) in Gabes Watershed at different temporal scales. Contribution of the MO ranged between 51% and 93% of fluctuations (8-12 years) in the different examined rainfall stations.

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“…For instance, the authors of [31] concluded that hydroclimatic variables have a strong correlation with the change in climate. These variables can indicate a change in climate with time, and can be used to analyze the change patterns at different temporal scales [32,33]. In addition, changes in oceanic and atmospheric conditions (i.e., temperature and pressure fluctuations) were found to influence the change patterns observed in the hydrologic cycle [2,34,35].…”

Section: Introductionmentioning

confidence: 99%

Identification of Streamflow Changes across the Continental United States Using Variable Record Lengths

2016

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Abstract:The study focused on investigating the presence of change patterns in 600 unimpaired streamflow stations across the continental U.S. at different time intervals to understand the change patterns that can provide significant insight regarding climate variability and change. Each station had continuous streamflow data of at least 30 years (the entire dataset covered a range of 109 years). Presence of trends and shifts were detected in water year and the four seasons (fall, winter, spring, and summer) analyzing the water year and seasonal mean flows. Two non-parametric tests, namely, the Mann-Kendall test and the Pettitt's test were used to identify the trends and the shifts, respectively. The results showed an increasing trend in the northeast and upper-mid regions, whereas southeast and northwest regions underwent a decrease. Shifts followed similar patterns as trends with higher number of stations with significant change. Fall and spring showed the highest number of stations with increasing and decreasing change, respectively, in the seasonal analyses. Results of this study may assist water managers to understand the streamflow change patterns across the continental U.S., especially at the regional scale since this study covers a long range of years with a large number of stations in each region.

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Precipitation trends in the Kalu Ganga basin in Sri Lanka

Cited by 44 publications

References 11 publications

Spatial and temporal variation of rainfall trends of Sri Lanka

Spatial and temporal variation of rainfall trends of Sri Lanka

Variability of Precipitation in Arid Climates Using the Wavelet Approach: Case Study of Watershed of Gabes in South-East Tunisia

Identification of Streamflow Changes across the Continental United States Using Variable Record Lengths

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