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.

Precipitation Trend Analysis by Mann-Kendall Test: A Case of Tianchang County Anhui Province, China

2013 ◽  
Vol 864-867 ◽  
pp. 2218-2223 ◽  
Author(s):  
Elsie Akwei ◽  
Bao Hong Lu ◽  
Han Wen Zhang
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Trend Analysis ◽  
Null Hypothesis ◽  
Kendall Test ◽  
Anhui Province ◽  
Significant Trend ◽  
Precipitation Data ◽  
Precipitation Time Series ◽  
Mann Kendall Test

The purpose of this research is to study the temporal variability of precipitation time series of Tianchang County in Anhui Province, China to aid in the understanding of the state of the hydrology of the catchment. Trend analysis of one of the main component of the water balance of a catchment and a climate variable, precipitation was conducted with the aim of detecting a possible trend in the precipitation time series of Tianchang County, the non-parametric Mann-Kendall test was applied to precipitation series from 1951-2010 of Tianchang County. It was performed using Trend (version 1.0.2) to identify the significant positive or negative trends in the precipitation data if any. The 59 years period of precipitation data for the different towns in whole area showed, on the whole, some significant trend at an alpha level of 0.01 and 0.05 when grouped into the four seasons present in the area. The trend analysis revealed an overall upward and significant trend in five towns namely Datong, Xinjie, Shiliang, Qinlan and Tongcheng with downward statistically non-significant trend in the other ten areas .Using hypothesis testing, the null hypothesis states that there is no trend and alternative state there is a trend. From the results we reject the null hypothesis within the level of confidence 0.05 and 0.01. The rising rate of precipitation in some months and decreasing in others signifies an overall random pattern in the time series. This result is a part contribution to the effect of Climate change on hydrology and indicates that there is still room for research on the impact of climate change to ensure sustainable development in future.

scholarly journals Rainfall trend analysis and weather forecast accuracy in selected parts of Khyber Pakhtunkhwa, Pakistan

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Fakhri Alam ◽  
Muhammad Salam ◽  
Nasir Ahmad Khalil ◽  
Owais khan ◽  
Masaud Khan
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Forecast Accuracy ◽  
Weather Forecast ◽  
Kendall Test ◽  
Annual Rainfall ◽  
Rainfall Trend ◽  
Khyber Pakhtunkhwa ◽  
Temperature Records ◽  
Nonparametric Techniques

AbstractClimate change is a multidimensional phenomenon, which has various effects on people's environmental and socioeconomic conditions. In the agricultural economy that is susceptible to natural changes, its impact is more profound. Therefore, climate change directly affects society in different ways, and society must pay a price. Climate change, especially the changes in annual temperature and rainfall, has attracted widespread attention worldwide. The variability of these factors or the magnitude of fluctuations varies according to location. Therefore, in the context of climate change, especially in countries dominated by rainfed agriculture, studying the trend of meteorological variables is essential to assess climate-induced variations and propose feasible adaptation approaches. Focusing on this fact is the main goal of this research study was to determine the rainfall trend and the accuracy of predicted temperature at three particular stations of Khyber Pakhtunkhwa (Kp) Province, Pakistan. For this purpose, rainfall and temperature data were provided by Pakistan Meteorological Department (PMD), Islamabad, for the period 1960–2020. Two types of nonparametric techniques, Sen’s slope estimate and the Mann–Kendall test, were applied to determine a trend in the average monthly and annual rainfall. The results of the annual rainfall trend analysis showed that Peshawar and Dera Ismail Khan stations showed a positive increasing trend, while the monthly rainfall trend showed a negative decreasing trend for all stations. The trend was statistically significant for Peshawar and Saidu Sharif stations. The accuracy of predicted and actual temperature and rainfall indicated that mostly over-forecast occurred at Saidu Sharif and Peshawar. Most of the precipitation and temperature records showed under forecast for Dera Ismail Khan, but some over-prediction has also occurred. Graphical abstract

scholarly journals Statistical analysis of long-term rainfall trends in Cherrapunji, Meghalaya, India

2021 ◽  
Vol 13 (1) ◽  
pp. 170-177
Author(s):  
Surobhi Deka
Keyword(s):  
Trend Analysis ◽  
Water Resource Management ◽  
Kendall Test ◽  
Monthly Rainfall ◽  
Change Scenario ◽  
Rainfall Trend ◽  
Large Variability ◽  
Rainfall Trends ◽  
Test Of Significance ◽  
Level Of Significance

Rainfall is the key climatic variable that governs the regional hydrologic cycle and availability of water resources. Rainfall trend analysis in a localized watershed can improve many aspects of water resource management not only to the catchment itself but also to some of the related other catchments. The trend analysis of monthly rainfall data over Cherrapunji of Meghalaya in India for the period 1872-2007 has been carried out in this work. While the magnitude of the trend in the time series has been determined using Sen's estimator, the significance of the trend in monthly rainfall series has been tested using Mann-Kendall test. During the time span 1872-2007, an increasing trend has been found in the monthly rainfall for the months July, October and November, and a decreasing trend has been found in the monthly rainfall for the months February to June, August and September. On the other hand, it was found that none of Mann-Kendall Z values was significant at 5% level of significance. Therefore, from Mann-Kendall Z test, it can be concluded that there is no trend in any month in monthly rainfall for the station Cherrapunji. For the better assessment of the temporal variation in monthly rainfall trend, whole period was divided into two halves, 1872-1939 and 1940-2007. Then, trend magnitude through Sen's estimator and Mann-Kendall Z for test of significance were determined for these two time periods separately. The analysis of trends of monthly rainfall in these two halves showed large variability in the magnitude and direction of the trend in various months from one half to another. Accurate prediction of trends in monthly rainfall is an important aspect of climate research and we believe that present study could provide a scope to correlate between current rainfall trend and climate change scenario of the study area.

scholarly journals Innovative Trend Analysis of Precipitation in the Lake Issyk-Kul Basin, Kyrgyzstan

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 332 ◽  
Author(s):  
Yilinuer Alifujiang ◽  
Jilili Abuduwaili ◽  
Balati Maihemuti ◽  
Bilal Emin ◽  
Michael Groll
Keyword(s):  
Trend Analysis ◽  
Resource Planning ◽  
Kendall Test ◽  
Trend Test ◽  
Lake Basin ◽  
Positive Trend ◽  
Monthly Precipitation ◽  
Innovative Trend Analysis ◽  
Mann Kendall Test ◽  
Increasing Trends

The analysis of various characteristics and trends of precipitation is an essential task to improve the utilization of water resources. Lake Issyk-Kul basin is an upper alpine catchment, which is more susceptible to the effects of climate variability, and identifying rainfall variations has vital importance for water resource planning and management in the lake basin. The well-known approaches linear regression, Şen’s slope, Spearman’s rho, and Mann-Kendall trend tests are applied frequently to try to identify trend variations, especially in rainfall, in most literature around the world. Recently, a newly developed method of Şen-innovative trend analysis (ITA) provides some advantages of visual-graphical illustrations and the identification of trends, which is one of the main focuses in this article. This study obtained the monthly precipitation data (between 1951 and 2012) from three meteorological stations (Balykchy, Cholpon-Ata, and Kyzyl-Suu) surrounding the Lake Issyk-Kul, and investigated the trends of precipitation variability by applying the ITA method. For comparison purposes, the traditional Mann–Kendall trend test also used the same time series. The main results of this study include the following. (1) According to the Mann-Kendall trend test, the precipitation of all months at the Balykchy station showed a positive trend (except in January (Zc = −0.784) and July (Zc = 0.079)). At the Cholpon-Ata and Kyzyl-Suu stations, monthly precipitation (with the same month of multiple years averaged) indicated a decreasing trend in January, June, August, and November. At the monthly scale, significant increasing trends (Zc > Z0.10 = 1.645) were detected in February and October for three stations. (2) The ITA method indicated that the rising trends were seen in 16 out of 36 months at the three stations, while six months showed decreasing patterns for “high” monthly precipitation. According to the “low” monthly precipitations, 14 months had an increasing trend, and four months showed a decreasing trend. Through the application of the ITA method (January, March, and August at Balykchy; December at Cholpon-Ata; and July and December at Kyzyl-Suu), there were some significant increasing trends, but the Mann-Kendall test found no significant trends. The significant trend occupies 19.4% in the Mann-Kendall test and 36.1% in the ITA method, which indicates that the ITA method displays more positive significant trends than Mann–Kendall Zc. (3) Compared with the classical Mann-Kendall trend results, the ITA method has some advantages. This approach allows more detailed interpretations about trend detection, which has benefits for identifying hidden variation trends of precipitation and the graphical illustration of the trend variability of extreme events, such as “high” and “low” values of monthly precipitation. In contrast, these cannot be discovered by applying traditional methods.

scholarly journals Trend Analysis of Hydroclimatic Variables in the Kamo River Basin, Japan

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1782 ◽  
Author(s):  
Maochuan Hu ◽  
Takahiro Sayama ◽  
Sophal TRY ◽  
Kaoru Takara ◽  
Kenji Tanaka
Keyword(s):  
Trend Analysis ◽  
River Basin ◽  
River Discharge ◽  
Water Resource Management ◽  
Potential Evapotranspiration ◽  
Kendall Test ◽  
Winter Precipitation ◽  
Significant Trend ◽  
Mann Kendall Test ◽  
Proactive Measures

Understanding long-term trends in hydrological and climatic variables is of high significance for sustainable water resource management. This study focuses on the annual and seasonal trends in precipitation, temperature, potential evapotranspiration, and river discharge over the Kamo River basin from the hydrological years 1962 to 2017. Homogeneity was examined by Levene’s test. The Mann–Kendall and a modified Mann–Kendall test as well as Sen’s slope estimator were used to analyze significant trends (p < 0.05) in a time series with and without serial correlation and their magnitudes. The results indicate that potential evapotranspiration calculated by the Penman–Monteith equation was highly related to temperature, and significantly increased in the annual and summer series. Annual river discharge significantly decreased by 0.09 m3/s. No significant trend was found at the seasonal scale. Annual, autumn, and winter precipitation at Kumogahata station significantly increased, while no significant trend was found at Kyoto station. Precipitation was least affected by the modified Mann–Kendall test. Other variables were relatively highly autocorrelated. The modified Mann–Kendall test with a full autocorrelation structure improved the accuracy of trend analysis. Furthermore, this study provides information for decision makers to take proactive measures for sustainable water management.

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.

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