Simulation of River Discharges in Major Watersheds of Northwestern Java From 1901 To 2006

This study is intended to simulate the river discharges in major watersheds of northwestern Java, Indonesia. The five largest watersheds are considered: Ciujung, Cisadane, Ciliwung, Citarum, and Cimanuk. The simulation period covers the 20th century and early 21st century, from January 1901 to June 2006, at a monthly time step. Discharge simulation was carried out using STREAM (Spatial Tools for River Basins and Environmental and Analysis of Management Option). The input data for the simulation are climate (precipitation and temperature), land cover and topographic data. Setup and analysis of input data are also part of this study. The Mann-Kendall test and linear regression were used to detect trends. Temperature datasets show statistically significant increasing trends for all periods and areas. Significant increasing trends of precipitation occurred in the latest 16-year period (1990-2006) in hilly and middle areas. A positive trend of simulated discharge is seen in all watersheds and periods. They are only significant for Ciujung (periods of 1950-2006 and 1975-2006), Cisadane (periods of 1950-2006 and 1990-2006), and Ciliwung (periods of 1950-2006, 1975-2006, and 1990- 2006). The most noteworthy trend is seen in the 1990-2006 period. Over the course of the 20th and early decade of the 21st century, monthly discharges have increased by 3% to 9%.

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

Atmosphere ◽

10.3390/atmos11040332 ◽

2020 ◽

Vol 11 (4) ◽

pp. 332 ◽

Cited By ~ 10

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.

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Homogeneity Evaluation of Historical Rainfall and Temperature Series in Mato Grosso

Journal of Experimental Agriculture International ◽

10.9734/jeai/2019/v35i330205 ◽

2019 ◽

pp. 1-7

Author(s):

Elizangela Selma da Silva ◽

José Holanda Campelo Júnior ◽

Francisco De Almeida Lobo ◽

Ricardo Santos Silva Amorim

Keyword(s):

Trend Analysis ◽

Minimum Temperature ◽

Statistical Tests ◽

Kendall Test ◽

Maximum Temperature ◽

Data Series ◽

Positive Trend ◽

Mato Grosso ◽

Temperature Climate ◽

Precipitation And Temperature

The homogeneity investigation of a series can be performed through several nonparametric statistical tests, which serve to detect artificial changes or non-homogeneities in climatic variables. The objective of this work was to evaluate two methodologies to verify the homogeneity of the historical climatological series of precipitation and temperature in Mato Grosso state. The series homogeneity evaluation was performed using the following non-parametric tests: Wald-Wolfowitz (for series with one or no interruption), Kruskal-Wallis (for series with two or more interruptions), and Mann-Kendall (for time series trend analysis). The results of the precipitation series homogeneity analysis from the National Waters Agency stations, analyzed by the Kruskal-Wallis and Wald-Wolfowitz tests, presented 61.54% of homogeneous stations, being well distributed throughout Mato Grosso state, whereas those of the trend analysis allowed to identify that 87.57% of the rainfall-gauging stations showed a concentrated positive trend, mainly in the rainy season. Out of the conventional stations of the National Institute of Meteorology of Mato Grosso, seven were homogeneous for the precipitation variable, five for maximum temperature and four stations were homogeneous for minimum temperature. For the trend analysis in the 11 stations, positive trends of random nature were observed, suggesting increasing alterations in the analyzed variables. Therefore, the trend analysis performed by the Mann-Kendall test in the precipitation, and maximum and minimum temperature climate series, indicated that several data series showed increasing trends, suggesting a possible increase in precipitation and temperature values over the years. The results of the Kruskal-Wallis and Wald-Wolfowitz tests for homogeneity presented more than 87% of homogeneous stations.

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Rainfall trend analysis

INTERNATIONAL JOURNAL OF AGRICULTURAL SCIENCES ◽

10.15740/has/ijas/17.1/121-125 ◽

2021 ◽

Vol 17 (1) ◽

pp. 121-125

Author(s):

Virendra N. Barai ◽

Rohini M. Kalunge

Keyword(s):

Trend Analysis ◽

Kendall Test ◽

River Basins ◽

Annual Rainfall ◽

Positive Trend ◽

Rainfall Trend ◽

Trend Magnitude ◽

Increasing Trends ◽

Multiple Units ◽

Rainy Days

This article aims to review studies pertaining to trends in rainfall, rainy days over India. Non-parametric tests such as Sen’s Slope were used as estimator of trend magnitude which was supported by Mann-Kendall test. The findings of various studies indicate variance with respect to the rainfall rate, which contributes to an uncertain picture of the rainfall trend. In the study of monsoon of different locations in India some places showed increasing trends however, there is signifying decrease in trend all over India. It was also mentioned that analysis can vary from for a location if done using different source or types of collection of data. Spatial units range from station results and sub-division to sub-basin/river basins for trend analysis. The outcomes of the different experiments vary and a simple and reliable picture of the trend of rainfall has not appeared. While there can be a non-zero slope value for the multiple units (sub-basins or sub-divisions), few values are statistically important. In a basin-wise trend analysis report, some basins had a declining annual rainfall trend; at a 95 per cent confidence stage, only one basin showed a strong decreasing trend. Out of the six basins exhibiting a rising trend saw a major positive trend in one basin. Many of the basins have the same pattern direction on the annual and seasonal scale for rainfall and rainy days.

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Spatial and temporal characterization of climate at regional scale using homogeneous monthly precipitation and air temperature data: an application in Calabria (southern Italy)

Hydrology Research ◽

10.2166/nh.2014.022 ◽

2014 ◽

Vol 46 (4) ◽

pp. 629-646 ◽

Cited By ~ 31

Author(s):

T. Caloiero ◽

G. Buttafuoco ◽

R. Coscarelli ◽

E. Ferrari

Keyword(s):

Regional Scale ◽

Kendall Test ◽

Temperature Data ◽

Winter Period ◽

Positive Trend ◽

Monthly Precipitation ◽

Average Temperature ◽

Increasing Trend ◽

Precipitation And Temperature

In the present study, an approach for a climate characterization based on a statistical analysis of monthly precipitation and temperature data is presented. First, the original database (1916–2010) was homogenized and a geostatistical analysis was carried out to characterize the monthly mean distribution of the two variables in the study area. Then, temporal change of precipitation and temperature were evaluated through the Mann–Kendall test. Finally, to better assess the climate patterns in Calabria, a climatic characterization was carried out by means of the Péguy climograph. Results have shown a decreasing trend for autumn–winter rainfall and an increasing trend in summer. With respect to the average temperature, the analyses revealed a positive trend in late spring and summer, mainly due to the increase in the minimum values, and a negative trend in the autumn–winter period, mainly due to a decrease in the maximum values. The analysis of the Péguy climographs allowed the dataset to be divided into three groups, depending on the different elevation of the gauges. Moreover, different temporal behaviours were detected by analysing the climographs in three sub-periods.

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