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1
Vishwakarma, Ankur, Mahendra Kumar Choudhary, and Mrityunjay Singh Chauhan. "Applicability of SPI and RDI for forthcoming drought events: a non-parametric trend and one way ANOVA approach." Journal of Water and Climate Change 11, S1 (July 13, 2020): 18–28. http://dx.doi.org/10.2166/wcc.2020.042.
Повний текст джерелаАнотація:
Abstract Monthly, seasonal and annual trends of rainfall and temperature (both minimum and maximum) have been analyzed using the Mann–Kendall trend test (a non-parametric test) and Sen's slope estimator for Sagar division, India from 1988 to 2018. Sagar division is a drought-prone zone of Madhya Pradesh, India. The same analysis has been performed for two drought indices, the Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI). Both indices were calculated to see the trend in the drought for 35 rain-gauge stations belonging to the study area. The study revealed that the minimum temperature had increased more than the maximum temperature in the last 31 years. The strong similarity in the results of Sen's slope of SPI and RDI were seen for both significant and non-significant trends. Analysis of variance (ANOVA) testing validates the substantial similarity between SPI and RDI based on Sen's slope. It also indicated the suitability of RDI for future projection of drought using the general circulation models (GCMs) or regional climate models (RCMs) in meteorological drought as well as the agricultural drought category. In contrast, the SPI indicated the meteorological drought only. The distribution of trends of temperature and drought indices were presented using the kriging interpolation.
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D. Wale, Vishal, V. A. Sthool, D. Jadhav, and S. K. Upadhye. "Trend Analysis of Rainfall and Rainy Days using Mann Kendall Method and Sen’s Slope Estimator Atpadi Tahsil of Sangli District of Maharashtra." Journal of Agriculture Research and Technology 47, no. 01 (2022): 55–60. http://dx.doi.org/10.56228/jart.2022.47111.
Повний текст джерелаАнотація:
The study has been carried out to investigate and assess the significance of the potential trend of rainfall and rainy days over the Atpadi tahsil of Sangli district of Maharashtra. In this study, trend analysis has been carried out on annual, seasonal, monthly and weekly basis using the data period between 1982 to 2018 for rainfall and rainy days. Mann-Kendall test and Sen's slope estimate test were applied to identify the existing trend direction and Sen's slope estimator test were used to detect the trend direction and magnitude of change over time. The test results showed increasing rainfall and rainy days trend over the Atpadi tahsil for annual, seasonal (winter and southwest monsoon), monthly (June, August and September) and weekly (MW23, MW25, MW27, MW31, MW34-MW37, MW42 and MW46) time series.
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Wale, V. D., J. D. Jadhav, V. A. Sthool, and S. K. Upadhye. "Rainfall and Rainy Days Trend Analysis in Miraj Tahsil of Sangli District." Journal of Agriculture Research and Technology 47, no. 01 (2022): 28–33. http://dx.doi.org/10.56228/jart.2022.47106.
Повний текст джерелаАнотація:
The study has been carried out to investigate and asses the significance of the potential trend on annual, seasonal and monthly basis using the data period between 1982 to 2018 for rainfall and rainy days. MannKendall test and Sen's slope estimate test were applied to identify the existing trend direction and Sen's slope estimator test were used to detect the trend direction and magnitude of change over time. The test results showed increasing annual rainfall and rainy days trend over the tahsil. The seasonal rainfall and rainy days showed decreasing trend for summer season and decreasing trend for northeast monsoon and southwest monsoon seasons. The monthly rainfall and rainy days trend showed increasing trend for July to November months and decreasing days for May month. The weekly rainfall and rainy days trend showed decreasing trend for MW21-MW24, MW30, MW33 and MW43-MW45.
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PANDYA, PA, D. K. DWIVEDI, BIMAL PRACHI, SHIMVAM AHIRWAR, and NAITA KUMARI. "Trend and Seasonal Analysis of Annual One Day Maximum Rainfall." JOURNAL OF AGRISEARCH 9, no. 03 (September 3, 2021): 270–74. http://dx.doi.org/10.21921/jas.v9i03.11014.
Повний текст джерелаАнотація:
Saurashtra region is characterized by high temporal and spatial rainfall fluctuations. The daily maximum rainfall has a direct impact on the agricultural yield. It is thereby necessary to comprehend the trend changes in the annual daily maximum rainfall (ADMR). The daily rainfall data of 40 years (1981 to 2020), for 11 stations in Saurashtra was utilized for trend analysis of ADMRusing Mann Kendall's method and Sen's slope method. It was revealed from the Mann-Kendall test that significant positive trends were exhibited at Dwarka and Surendranagar. Further, Sen's slope and linear regression indicated that the ADMRat Rajkot and Surendranagar were having highest increasing trend. Trend analysis of ADMRcontribution to annual rainfall showed negative trend indicating better temporal distribution of rainfall. It was also revealed that the extreme events of rainfall usually occurred uniformly on certain days of the year from the results of directional statistics.
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Jiménez-Ruano, Adrián, Marcos Rodrigues Mimbrero, and Juan de la Riva Fernández. "Exploring spatial–temporal dynamics of fire regime features in mainland Spain." Natural Hazards and Earth System Sciences 17, no. 10 (October 4, 2017): 1697–711. http://dx.doi.org/10.5194/nhess-17-1697-2017.
Повний текст джерелаАнотація:
Abstract. This paper explores spatial–temporal dynamics in fire regime features, such as fire frequency, burnt area, large fires and natural- and human-caused fires, as an essential part of fire regime characterization. Changes in fire features are analysed at different spatial – regional and provincial/NUTS3 – levels, together with summer and winter temporal scales, using historical fire data from Spain for the period 1974–2013. Temporal shifts in fire features are investigated by means of change point detection procedures – Pettitt test, AMOC (at most one change), PELT (pruned exact linear time) and BinSeg (binary segmentation) – at a regional level to identify changes in the time series of the features. A trend analysis was conducted using the Mann–Kendall and Sen's slope tests at both the regional and NUTS3 level. Finally, we applied a principal component analysis (PCA) and varimax rotation to trend outputs – mainly Sen's slope values – to summarize overall temporal behaviour and to explore potential links in the evolution of fire features. Our results suggest that most fire features show remarkable shifts between the late 1980s and the first half of the 1990s. Mann–Kendall outputs revealed negative trends in the Mediterranean region. Results from Sen's slope suggest high spatial and intra-annual variability across the study area. Fire activity related to human sources seems to be experiencing an overall decrease in the northwestern provinces, particularly pronounced during summer. Similarly, the Hinterland and the Mediterranean coast are gradually becoming less fire affected. Finally, PCA enabled trends to be synthesized into four main components: winter fire frequency (PC1), summer burnt area (PC2), large fires (PC3) and natural fires (PC4).
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KHOSRAVI, YOUNES, HASAN LASHKARI, and HOSEIN ASAKEREH. "Water vapor pressure trends in south and southwest Iran." MAUSAM 68, no. 2 (November 30, 2021): 335–48. http://dx.doi.org/10.54302/mausam.v68i2.636.
Повний текст джерелаАнотація:
Recognitionanddetectionofclimaticparameters inhave animportant role inclimate change monitoring. In this study, the analysis of oneofthe most importantparameters, water vapor pressure (WVP), was investigated. For this purpose, two non-parametric techniques, Mann-Kendall and Sen's Slope Estimator, were used to analyze the WVP trend and to determine the magnitude of the trends, respectively. To analyze these tests, ground station observations [10 stations for period of 44 years (1967-2010)] and gridded data [pixels with the dimension of 9 × 9 km over a 30-year period (1981-2010)] in South and SouthwestofIran were used. By programming in MATLAB software, the monthly, seasonal and annual WVP time series were extracted and MK and Sen's slope estimator tests were done. The results of monthly MK test on ground station observations showed that the significant downward trends are more considerable than significant upward trends. It also showed that the WVP highest frequency was more in warm months, April to September and the highest frequency of significant trends slope was in February and May. The spatial distribution of MK test of monthly gridded WVP time series showed that the upward trends were detected mostly in western zone and near the Persian Gulf in August. On the other hand, the downward trends through months. The maximum and minimum values of positive trends slope occurred in warm months and cold months, respectively. The analysis of the MK test of the annual WVP time series indicated the upward significant trends in the southeast and southwest zones of study area.
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Thakur, Aradhana, Prabhash Kumar Mishra, A. K. Nema, and Souranshu Prasad Sahoo. "Spatiotemporal Pattern Assessment of Precipitation for the Wainganga Sub-Basin." Current World Environment 15, no. 3 (December 30, 2020): 515–25. http://dx.doi.org/10.12944/cwe.15.3.15.
Повний текст джерелаАнотація:
Precipitation is the major component of a hydrologic system, which significantly influences the planning and management of the water resources. The present study is principally concerned with the shifting of precipitation patterns over time. This study attempted to explain the precipitation trend for 65 years (1951-2015) using a Mann-Kendall test (MK test) and trend magnitude by Sen's slope estimator. Daily gridded data procured from India Meteorological Department (IMD) of 0.25º × 0.25º degrees to find the monthly and seasonal variability of precipitation. Eighty-five grids were falling in the basin processed for the periods from 1951 to 2015. The statistical analysis revealed that the average annual precipitation (AAP) and monsoon precipitation following the insignificant downward trend with Z statistics 0.10 and 1.23 and Sen's slope 0.79 and 0.76, respectively, over the basin. The shift analysis shows the AAP and monsoon precipitation increased significantly during 1951-61, whereas during the 1962-2015 rise in precipitation was insignificant. That changes in precipitation over the Wainganga sub-basin (WSB) may occur probably due to a rising trend of temperature. Therefore, nature-based climate solutions are the best way to endure the condition.
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DATTA, DEBARATI, SAON BANERJEE, GOURANGA KAR, SOURAV GHOSH, and SARATHI SAHA. "Spatio-temporal dynamics of temperature and rainfall across jute growing districts of India." MAUSAM 73, no. 2 (March 31, 2022): 373–88. http://dx.doi.org/10.54302/mausam.v73i2.569.
Повний текст джерелаАнотація:
Climate variations in relation to meteorological variables has received global attention and thus study of the spatiotemporal dynamics of temperature, rainfall is the central process to assess climate-induced changes and advocate feasible adaptation strategies. The present study examines changes in rainfall and temperature over 5 important jute growing districts of West Bengal, India. Both rainfall and temperature trend for period of 1980-2019 were analysed using Mann-Kendall test and Sen's slope estimator. Analysis of the data for 39 years revealed that while Howrah and Hooghly district had decreasing rainfall trend, Burdwan and Nadia districts showed increasing trend of rainfall during jute growing period. North-24 Parganas recorded negative rainfall trend. Compared with rainfall, lesser variability of temperature was recorded for all the districts except Burdwan. The positive Sen’s Slope exhibited by Nadia and North-24 Parganas showed an increasing temperature trend. The results herein suggests that jute sowing should be done by March end-April to take advantage of the optimum temperature (25-35 °C) and rainfall due to Norwesters. Thus, studying spatio- temporal dynamics of temperature and rainfall across jute growing states of West Bengal will be helpful for climate change adaptation and successful cropping.
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Mohd Wani, John, V. K. Sarda, and Sanjay K. Jain. "Assessment of Trends and Variability of Rainfall and Temperature for the District of Mandi in Himachal Pradesh, India." Slovak Journal of Civil Engineering 25, no. 3 (September 1, 2017): 15–22. http://dx.doi.org/10.1515/sjce-2017-0014.
Повний текст джерелаАнотація:
Abstract Climate variability, particularly, that of the annual air temperature and precipitation, has received a great deal of attention worldwide. The magnitude of the variability of the factors changes according to the locations. The present study focuses on detecting the trends and variability in the annual temperature and rainfall for the district of Mandi in Himachal Pradesh, India. This study used annual and monsoon time series data for the time period 1981-2010 and modified the Mann-Kendall test and Sen's slope estimator in analyzing the problem. The results of the analysis indicate that the annual maximum temperature (TMX) and annual minimum temperature (TMN) for the period of 30 years have shown an increasing trend, whereas the monsoon’s maximum and minimum temperatures have shown a decreasing trend, although it is statistically not significant. The amount of annual rainfall does not show any significant trend, but the monsoonal rainfall has shown an increasing trend that is also statistically not significant. The resulting Mann-Kendall test statistic (Z) and Sen’s slope estimate (Q) of all the parameters studied indicate that changes are occurring in the magnitude and timing of the precipitation and temperature events at the Mandi station.
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Garba, Haruna, and Udeme Udeme Udokpoh. "Analysis of Trend in Meteorological and Hydrological Time-series using Mann-Kendall and Sen’s Slope Estimator Statistical Test in Akwa Ibom State, Nigeria." International Journal of Environment and Climate Change 13, no. 10 (August 24, 2023): 1017–35. http://dx.doi.org/10.9734/ijecc/2023/v13i102748.
Повний текст джерелаАнотація:
The monthly, seasonal, annual, and decadal trends of seven hydro-meteorological variables were analysed for stations in Akwa Ibom State, Nigeria, controlled by the Nigerian Meteorological Agency (NiMet) and the Cross River Basin Development Authority (CRBDA) from 1972 to 2021. At the 5% statistical significance level, the non-parametric Mann-Kendall and Sen's slope estimator techniques were used to detect if there was a positive or negative trend and the magnitude of the trend in hydro-meteorological data. In the present study, there was a significant statistically increasing (positive) trend in mean seasonal and annual rainfall, maximum temperature, minimum temperature, and runoff. However, there was a significant statistically decreasing (negative) trend in average annual relative humidity, solar radiation, and potential evapotranspiration. The magnitudes of the trends were 19.39mm/year, 0.0314oC/year, 0.013oC/year, -0.104%/year, -8.78MJ/m2/year, -1.440mm/year, and 0.028m3/s/year for annual rainfall, maximum temperature, minimum temperature, relative humidity, solar radiation, PET, and runoff, respectively. The rising trends in precipitation, temperature, and runoff in this research area show that this region is subject to climatic variability. The results of the Mann-Kendall and Sen's slope estimator statistical tests revealed the consistency of performance in the detection of the trend for the hydro-meteorological variables.
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Pacheco, Sâmya Silva, Cynthia Braga, Ariani Impieri de Souza, and José Natal Figueiroa. "Efeito da fortificação alimentar com ácido fólico na prevalência de defeitos do tubo neural." Revista de Saúde Pública 43, no. 4 (August 2009): 565–71. http://dx.doi.org/10.1590/s0034-89102009005000033.
Повний текст джерелаАнотація:
OBJETIVO:Analisar o efeito de alimentos fortificados com ácido fólico na prevalência de defeitos de fechamento do tubo neural entre nascidos vivos. MÉTODOS: Estudo longitudinal de nascidos vivos do município de Recife (PE) entre 2000 e 2006. Os dados pesquisados foram obtidos do Sistema Nacional de Informações de Nascidos Vivos. Os defeitos de fechamento do tubo neural foram definidos de acordo com o Código Internacional de Doenças-10ª Revisão: anencefalia, encefalocele e espinha bífida. Compararam-se as prevalências nos períodos anterior (2000-2004) e posterior (2005-2006) ao período mandatório à fortificação. Analisou-se a tendência temporal das prevalências trimestrais de defeitos do fechamento do tubo neural pelos testes de Mann-Kendall e Sen's Slope. RESULTADOS: Não se identificou tendência de redução na ocorrência do desfecho (Teste de Mann-Kendall; p= 0,270; Sen's Slope =-0,008) no período estudado. Não houve diferença estatisticamente significativa entre as prevalências de defeitos do fechamento do tubo neural nos períodos anterior e posterior à fortificação dos alimentos com acido fólico de acordo com as características maternas. CONCLUSÕES: Embora não tenha sido observada redução dos defeitos do fechamento do tubo neural após o período mandatório de fortificação de alimentos com ácido fólico, os resultados encontrados não permitem descartar o seu benefício na prevenção desta malformação. São necessários estudos avaliando maior período e considerando o nível de consumo dos produtos fortificados pelas mulheres em idade fértil.
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Diop, Lamine, Ansoumana Bodian, and Dior Diallo. "Spatiotemporal Trend Analysis of the Mean Annual Rainfall in Senegal." European Scientific Journal, ESJ 12, no. 12 (April 28, 2016): 231. http://dx.doi.org/10.19044/esj.2016.v12n12p231.
Повний текст джерелаАнотація:
The spatiotemporal trends of annual rainfall in Senegal during 1940 - 2013 were investigated using the Mann–Kendall test and Theil–Sen’s slope estimator. Theil and Sen's slope estimator test was used for finding the magnitude of change over a time period. Inverse Weight Distance (IDW) technique in Arc GIS 10.2 was used to investigate spatial patterns of the trends over the entire country. For the period 1940-2013, the results of the analysis showed negative trends in annual rainfall at the whole country except for the Bakel station which exhibits a positive trend but not significant. While for the period 1984 - 2013, all the stations show a positive trend with 07 out of 22 stations exhibiting a significant trend at the 95% confidence interval. The spatial distribution of trend during the period 1940- 2013 showed a significant negative trend in the whole study of area except small areas located at the extreme South Est and West as well as North East and West. The trend magnitude varies between -4.41mm/year to 1.34 mm for the period 1940-2013 with a maximum negative magnitude at the Tambacounda station. For 1984-2013, the trend magnitude is positive for the whole country with values varying between 2.67 mm/year at Goudiry and 12.2 mm/year at Ziguinchor. Magnitudes are greater than 5 mm/year, for stations with significant positive trend.
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Mehta, Darshan, and S. M. Yadav. "Temporal analysis of rainfall and drought characteristics over Jalore District of S-W Rajasthan." Water Practice and Technology 17, no. 1 (December 3, 2021): 254–67. http://dx.doi.org/10.2166/wpt.2021.114.
Повний текст джерелаАнотація:
Abstract Drought forecasting is being considered an important tool to help understand the rainfall pattern and climate change trend. Drought is a prolonged period of months or years in which an area, whether surface water or groundwater, becomes insufficient in its water supplies. Drought is considered as the most difficult but least known environmental phenomenon, impacting more persons than any other. There are several indices used to classify droughts. For this study, precipitation-based drought indices are considered (i.e., SPI, RAI and Percentage Departure of Rainfall). The objective of the research is to examine and determine the possible rainfall trends over the Jalore district of South-West Rajasthan in Luni river basin. In this research, trend analysis using the rainfall data from the years 1901 to 2021 was carried out on a monthly, seasonal and annual basis. To define the current trend path, the Mann-Kendall test and Sen's slope estimator test were used. In order to detect the trend and its change in magnitude over a particular period of time, Sen's slope estimator was used. During the southwest monsoon, declining rainfall leads to short-term meteorological droughts, which have severe effect on the agriculture sector and Jalore district's water supplies, while rising rainfall during other seasons tends to mitigate the severity of drought. The result of research reveals that there is rise of pre-monsoon and post-monsoon rainfall, but it also depicts a fall in the annual rainfall which reflects in reduced Winter and S-W monsoon rainfall.
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Marsitha Barung, Femmy, Wendel Jan Pattipeilohy, and Robi Muharsyah. "ASSESSMENT OF CLIMATE CHANGE BASED ON ANNUAL TREND AND CHANGE OF TEMPERATURE IN MANOKWARI, WEST PAPUA." Jurnal Analisis Kebijakan Kehutanan 18, no. 1 (May 24, 2021): 45–57. http://dx.doi.org/10.20886/jakk.2021.18.1.45-57.
Повний текст джерелаАнотація:
A simple climate change assessment is carried out on annual air temperatures including average, maximum and minimum temperatures in Rendani, Manokwari for the period of 1993-2019. Parametric linear regression and nonparametric Mann-Kendall trend test (MK), Modified Mann-Kendall (MMK), Sen's Slope Estimator (SSE)are used to analyze trends and index numbers for analyzing the temperature changes. Homogenity test is performed using double mass curve and assumption of normality in the distribution is also investigated to meet the requirements of the linear regression trend test. There as a significant upward trend in the mean and minimum temperature with a slope of 0.029ºC/year and 0.069ºC/year, respectively. Meanwhile, the maximum temperature test shows no trend with a slope of 0.009ºC/year. Analysis of temperature changes using index numbers shows an increase in annual average temperature of 2.8% or 0.7°C, maximum temperature of 1.2% or 0.4°C, and minimum temperature of 3.1% or 0.8°C. The increase in annual air temperature in Manokwari City can generally be caused by several factors such as El Nino phenomenon, urbanization, population growth, and deforestation.
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Jagadeesh, P., and Suyash Agrawal. "Investigation of trends and its magnitude by non-parameteric Mann-Kendall and Sen's slope methods." International Journal of Hydrology Science and Technology 5, no. 1 (2015): 83. http://dx.doi.org/10.1504/ijhst.2015.069281.
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Burić, D., J. Luković, V. Ducić, J. Dragojlović, and M. Doderović. "Recent trends in daily temperature extremes over southern Montenegro (1951–2010)." Natural Hazards and Earth System Sciences Discussions 1, no. 5 (October 1, 2013): 5181–98. http://dx.doi.org/10.5194/nhessd-1-5181-2013.
Повний текст джерелаАнотація:
Abstract. Montenegro so far has been poorly investigated in terms of climate extremes. The aim of this paper was to analyse the extreme ETCCD temperature indices in the Mediterranean region of Montenegro for the period of 1951–2010. Four stations in the coastal area of Montenegro have been analysed: Herceg Novi, Ulcinj, Budva and Bar. Two periods (before 1980 and after 1980) were separately investigated in this study due to a well known climate shift that occurred in the late 1970's. Seven indices of temperature extremes have been chosen. The trend was analysed using a Man–Kendall non parametric test while the slope was estimated using Sen's slope estimator. A negative trend has been calculated for cold nights and cold days at almost all stations. The most significant positive trends were obtained for warm conditions. Two separately investigated periods have shown contrasting temperature trends.
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Burić, D., J. Luković, V. Ducić, J. Dragojlović, and M. Doderović. "Recent trends in daily temperature extremes over southern Montenegro (1951–2010)." Natural Hazards and Earth System Sciences 14, no. 1 (January 8, 2014): 67–72. http://dx.doi.org/10.5194/nhess-14-67-2014.
Повний текст джерелаАнотація:
Abstract. Montenegro so far has been poorly investigated in terms of climate extremes. The aim of this paper was to analyse the extreme ETCCDI (Expert Team on Climate Change Detection and Indices) temperature indices in the Mediterranean region of Montenegro for the period of 1951–2010. Four stations in the coastal area of Montenegro have been analysed: Herceg Novi, Ulcinj, Budva and Bar. Two periods (before 1980 and after 1980) were separately investigated in this study due to a well-known climate shift that occurred in the late 1970s. Seven indices of temperature extremes have been chosen. The trend was analysed using a Mann–Kendall non-parametric test, while the slope was estimated using Sen's slope estimator. A negative trend has been calculated for cold nights and cold days at almost all stations. The most significant positive trends were obtained for warm conditions. The two separately investigated periods have shown contrasting temperature trends.
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Liu, Rong, Jun Wen, Xin Wang, and Zuoliang Wang. "Validation of evapotranspiration and its long-term trends in the Yellow River source region." Journal of Water and Climate Change 8, no. 3 (April 19, 2017): 495–509. http://dx.doi.org/10.2166/wcc.2017.134.
Повний текст джерелаАнотація:
In this paper, the ground observations were compared to the ERA-Interim, NCEP-DOE AMIP-II Reanalysis, MODIS ET product, and emerging offline SEBS ET data sets in the Yellow River source region of the Tibet Plateau. In general, the slopes of linear least squares exhibit differences, with ERA-Interim, NCEP–DOE, MOD16, and SEBS slopes of 0.88 ± 0.05, 0.64 ± 0.07, 0.66 ± 0.17, and 1.24 ± 0.97 respectively. ERA-Interim was found superior with ground observations to others; therefore, it provided a good representation of the study area. Based on the ERA-Interim ET product, the Sen's slope estimator and the Mann–Kendall (MK) test were applied to quantify the significance of the shifts in trends, while the moving t-test and MK test characterized abrupt changes. The results show that the Yellow River source region experienced a statistical increase in evapotranspiration (ET) in the northern part and a decrease in the southern part of the region from 1979 to 2014 at rates of approximately 1.65 and −0.50 mm/yr, respectively. The shift in the annual ET trend was more pronounced, and abrupt changes were detected in the 1980s. Precipitation was the most dominant factor affecting ET variation, whereas surface temperature was the least influential.
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Gocic, Milan, and Slavisa Trajkovic. "Analysis of changes in meteorological variables using Mann-Kendall and Sen's slope estimator statistical tests in Serbia." Global and Planetary Change 100 (January 2013): 172–82. http://dx.doi.org/10.1016/j.gloplacha.2012.10.014.
Повний текст джерела
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Collaud Coen, Martine, Elisabeth Andrews, Alessandro Bigi, Giovanni Martucci, Gonzague Romanens, Frédéric P. A. Vogt, and Laurent Vuilleumier. "Effects of the prewhitening method, the time granularity, and the time segmentation on the Mann–Kendall trend detection and the associated Sen's slope." Atmospheric Measurement Techniques 13, no. 12 (December 21, 2020): 6945–64. http://dx.doi.org/10.5194/amt-13-6945-2020.
Повний текст джерелаАнотація:
Abstract. The Mann–Kendall test associated with the Sen's slope is a very widely used non-parametric method for trend analysis. It requires serially uncorrelated time series, yet most of the atmospheric processes exhibit positive autocorrelation. Several prewhitening methods have therefore been designed to overcome the presence of lag-1 autocorrelation. These include a prewhitening, a detrending and/or a correction of the detrended slope and the original variance of the time series. The choice of which prewhitening method and temporal segmentation to apply has consequences for the statistical significance, the value of the slope and of the confidence limits. Here, the effects of various prewhitening methods are analyzed for seven time series comprising in situ aerosol measurements (scattering coefficient, absorption coefficient, number concentration and aerosol optical depth), Raman lidar water vapor mixing ratio, as well as tropopause and zero-degree temperature levels measured by radio-sounding. These time series are characterized by a broad variety of distributions, ranges and lag-1 autocorrelation values and vary in length between 10 and 60 years. A common way to work around the autocorrelation problem is to decrease it by averaging the data over longer time intervals than in the original time series. Thus, the second focus of this study evaluates the effect of time granularity on long-term trend analysis. Finally, a new algorithm involving three prewhitening methods is proposed in order to maximize the power of the test, to minimize the number of erroneous detected trends in the absence of a real trend and to ensure the best slope estimate for the considered length of the time series.
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Aditya, F., E. Gusmayanti, and J. Sudrajat. "Rainfall trend analysis using Mann-Kendall and Sen’s slope estimator test in West Kalimantan." IOP Conference Series: Earth and Environmental Science 893, no. 1 (November 1, 2021): 012006. http://dx.doi.org/10.1088/1755-1315/893/1/012006.
Повний текст джерелаАнотація:
Abstract Climate change has been a prominent issue in the last decade. Climate change on a global scale does not necessarily have the same effect in different regions. Rainfall is a crucial weather element related to climate change. Rainfall trends analysis is an appropriate step in assessing the impact of climate change on water availability and food security. This study examines rainfall variations and changes at West Kalimantan, focusing on Mempawah and Kubu Raya from 2000-2019. The Mann-Kendall (MK) and Sen's Slope estimator test, which can determine rainfall variability and long-term monotonic trends, were utilized to analyze 12 rainfall stations. The findings revealed that the annual rainfall pattern prevailed in all locations. Mempawah region tends to experience a downward trend, while Kubu Raya had an upward trend. However, a significant trend (at 95% confidence level) was identified in Sungai Kunyit with a slope value of -33.20 mm/year. This trend indicates that Sungai Kunyit will become drier in the future. The results of monthly rainfall analysis showed that significant upward and downward trends were detected in eight locations. Rainfall trends indicate that climate change has occurred in this region.
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Sunny, Fatamatuj, Md Selim Miah, Md Younus Mia, and Ruksana Haque Rimi. "Temporal Variability, Trends of Climatic Variables and Drought Analysis of Rajshahi and Sylhet District, Bangladesh." Journal of the Asiatic Society of Bangladesh, Science 46, no. 2 (June 29, 2021): 133–41. http://dx.doi.org/10.3329/jasbs.v46i2.54409.
Повний текст джерелаАнотація:
The study was conducted to quantify the change of selected climatic variables (rainfall, relative humidity, maximum and minimum temperature) over 50 years at Rajshahi and Sylhet districts in Bangladesh. Annual, seasonal, and monthly climatic data comparisons have been executed between 1968-1992 and 1993-2017 through trend analysis. The Mann-Kendall statistic and Sen's Slope model were used to reveal the trends and estimate the magnitude of change respectively. Prediction of the climatic variable of 10 years (2018-2027) was made based on the ARAR algorithm using MaxStat Pro software. Rainfall data were used to analyze drought by using climatic indices (De Mortone Aridity Index, IdM; Seleaninov Hydrothermic Index, IhS; Donciu Climate Index, IcD). Average rainfall was decreasing dramatically in monsoon season at Rajshahi and in both premonsoon and monsoon seasons at Sylhet. The negative change of average rainfall in the monsoon at Rajshahi from 1968-1992 to 1993-2017 was found 29.17 mm. The maximum temperature was increasing in all seasons in both Rajshahi and Sylhet. Annual Mannkendall trend test and Sen’s slope revealed that relative humidity was decreasing and maximum temperature was increasing significantly at Sylhet for the period 1993-2017. At Rajshahi, during 1968-1992, relative humidity was increasing by 0.247 % per year, and minimum temperature was decreasing 0.049℃ per year. Rainfall was decreasing insignificantly in both time scales. ARAR algorithm predicted that average maximum temperature might become comparatively higher than the previous 50 years. 1992 and 2010 were identified as drought years from all climatic indices, and 1969, 1981, and 1997 as excessive wet years at Rajshahi. No drought events were identified during 1968-2017 at Sylhet and the year 2017 to be an excessively wet year. IhS predicted 2020, 2025, and 2027 as drought years and 2024 as an excessive wet year at Sylhet.
Asiat. Soc. Bangladesh, Sci. 46(2): 133-141, December 2020
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F. Hasan, Ihsan. "TREND DETECTION OF METROLOGICAL DROUGHT IN NORTH OF IRAQ." Journal of Engineering and Sustainable Development 25, no. 3 (May 1, 2021): 60–73. http://dx.doi.org/10.31272/jeasd.25.3.7.
Повний текст джерелаАнотація:
This study presents an analysis of meteorological drought using multi time-scales of Standardized Precipitation Index SPI (6, 9 and 12 month), based on observed 49-year daily mean precipitation data records at 11 stations over the Northern region of Iraq. The detection of drought trends in results of SPI analysis was studied to identify whether there is any increase or decrease in the severity of drought at the selected meteorological Stations; Mann Kendall test and Sen's slope estimator were used to detect statistically significant trends. The results indicate that there is a statistically significant decreasing trend of SPI time series at 5% significant level in most of the selected stations. Based on drought categories the meteorological drought in the study region can be classified as mild drought.
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Latrech, Basma, Hiba Ghazouani, Lasram Asma, Boutheina M. Douh, Mansour Mohsen, and Abdelhamid Boujelben. "Long-term trend analysis of climatic variables and reference evapotranspiration over different urban areas in Tunisia." Brazilian Journal of Biological Sciences 6, no. 12 (2019): 189–201. http://dx.doi.org/10.21472/bjbs.061218.
Повний текст джерелаАнотація:
In this study, the trend analysis of annual climatic variables including Tmax, Tmin, Tmean, RHmean, WS and SR as well as FAO-56 PM ET0 were investigated in three locations in Tunisia during 1984-2007. The Mann-Kendall Test, the Sen's Slope Estimator and linear regression tests were used for the analysis. The obtained results showed a significant increasing trends (a < 0.001) and (a < 0.01) in annual Tmax, Tmin and Tmean at all the considered locations. However, Tmin increase faster than Tmax with a slope of magnitudes ranging between 0.057 to 0.1 oC year-1. For RHmean, a non-significant tendency of decrease was observed in Chott-Mariem station. However, significantly increasing trends were found for Kelibia and Tunis Carthage. Concerning the WS variable, a tendency of decrease is observed during the study period for all the stations. Nevertheless, the statistical analysis of decreasing tendency of wind speed varied from non-significant for Tunis Carthage to highly significant (a <= 0.001) at Chott-Mariem and Kelibia. Despite the highly significant upward trend of temperature, the temporal pattern of mean annual FAO56 PM-ET0, over the different stations, did not exhibit any significant trend except for Kelibia station.
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Singla, Chetan, Rajan Aggarwal, Samanpreet Kaur, and ROHIT SHARMA. "Analysis of meteorological parameter changes using Mann-Kendall statistical tests in Indian Punjab." MAUSAM 74, no. 1 (December 29, 2022): 207–13. http://dx.doi.org/10.54302/mausam.v74i1.1440.
Повний текст джерелаАнотація:
Groundwater in Central Punjab is declining at an alarming rate of one meter annually in last two decades and likely to be exhausted up to 300 meter depth in next 2-3 decades as per recent report published in 2018 based upon exhaustive analysis done till 2017 by the relevant agencies (Anonymous, 2018). All the blocks in this zone are over exploited. Rainfall and temperature are predominant meteorological parameters which influence irrigation demand which in turn influences ground water withdrawal; which ultimately influence groundwater depth in the region. Area under rice is increasing due to high returns. So, the trend analysis of these parameters is of paramount importance for sustainability of agriculture in this region. The aim of the present investigation was to study annual trend of precipitation, maximum and minimum temperature and rainfall for 10 locations in Central Punjab during 1998–2019. The effect of rainfall and rice area on groundwater depth has been also studied. To achieve this non-parametric Mann-Kendall and Sen's applied to the data series of annual rainfalls, annual maximum and minimum temperature of the ten selected stations. The nonparametric statistical tests applied to series of annual Tmax revealed an increasing trend in all of the locations of the study area. According to results by Sen’s slope estimator, the increasing trend in annual precipitation series was detected at the Tarantaran, Kapurthala,Ludhiana, Moga, Barnala and Jalandhar, while other stations had negative or no trends.
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Sudarsan, Gayathri, and A. Lasitha. "Rainfall Trend analysis using Mann-Kendall and Sen’s slope test estimation - A case study." E3S Web of Conferences 405 (2023): 04013. http://dx.doi.org/10.1051/e3sconf/202340504013.
Повний текст джерелаАнотація:
In order to analyze the changing pattern of rainfall in one of the important district in Kerala, this study concentrated on a crucial meteorological variable: precipitation. Agriculture in this region depends on rain, but because it occurs erratically and without warning, it has an adverse impact on the cropping system and the availability of natural water resources. Non-parametric analysis was used to determine the monthly, seasonal, and annual rainfall variability (trend and slope magnitude) from rainfall data spanning 30 years (1989-2018) on a monthly basis. To determine the strength of a trend for time series data, the Mann-Kendall (MK) Test for monotonic analysis of trend and non-parametric Sen's Slope Estimator were utilized. The past 30 years have been used to create monthly, seasonal, and yearly precipitation trends. The 30-year monthly data was used to generate monthly, seasonal, and yearly precipitation trends. The results of the statistical analysis of the entire reference time series data shows that the trend appears to be primarily positive (growing), both on an annual and seasonal scale. There was a decreasing tendency in the spring, pre-monsoon, and post-monsoon seasons. Individually, the seven months of January through February show a growing tendency, whereas the remaining five months of March through December show a declining trend with 99% and 95% confidence levels, respectively, the annual total rainfall and monsoon seasons demonstrated a positive significant increasing trend.
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Paul, Arati, Riddhidipa Bhowmik, V. M. Chowdary, Dibyendu Dutta, U. Sreedhar, and H. Ravi Sankar. "Trend analysis of time series rainfall data using robust statistics." Journal of Water and Climate Change 8, no. 4 (July 12, 2017): 691–700. http://dx.doi.org/10.2166/wcc.2017.141.
Повний текст джерелаАнотація:
Abstract A temporal rainfall analysis was carried out for the study area, Rajahmundry city located in lower Godavari basin, India, during the period 1960–2013. Both the parametric and non-parametric approaches were envisaged for identifying the trends at different temporal scales. Linear and robust regression analysis revealed a negative trend at weekly scale during monsoon months, but failed to signify the slope at 95% confidence level. The magnitude of Sen's slope was observed to be negative during the months of April–September. Results of the Mann–Kendall test ascertained the negative rainfall trends during the monsoon months of June and July with a significant trend at 95% confidence interval. Application of robust statistics for long-term rainfall analysis helped to address the outlier's problem in the dataset. The Mann–Kendall test rejected the null hypothesis for all months except February–May and August after exclusion of outliers. Overall, a negative trend during monsoon season and a positive trend during post-monsoon season were observed using a robust non-parametric approach. Further, good correlation was found between the total rainfall and rainy days during the study period. On average, 21.25% days of a year is considered as rainy, while heavy and extreme rainfall in this region together occupies nearly 15% of the rainy days.
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Bagdatlı, M. Cüneyt, Oğuzhan Arslan, Yiğitcan Ballı, and Arzu Nefise Uğuz. "GIS MODELLING AND EVALUATION OF CLIMATE VARIABILITY IN KIZILIRMAK WATERSHED OF TURKEY." International Journal of Engineering Technologies and Management Research 9, no. 5 (May 26, 2022): 48–54. http://dx.doi.org/10.29121/ijetmr.v9.i5.2022.1153.
Повний текст джерелаАнотація:
This research was carried out within the scope of analyzing the temperature and precipitation values observed in the Kızılırmak watershed of Turkey between 2002 - 2016 and spatial modeling using GIS. In the study, Mann-Kendall, Spearman's Rho and Sen's trend slope method tests were applied to the climate data. Data from 13 meteorological stations in the Kızılırmak watershed were used. The general average of monthly maximum temperatures varied between 23.5 and 26.4 oC for many years. The general average of monthly minimum temperatures for many years is -4.5 - 1.2 oC. The total precipitation average was between 377.5 - 644.8 mm. As a result of the trend analyzes made at the 95% confidence level in the research, it was determined that there was an increasing trend in Kastamonu and Sivas meteorological stations at maximum temperatures, and an increasing trend in Çankırı, Gemerek and Kastamonu stations at minimum temperature changes. It was observed that there was a significant change in total precipitation at Kastamonu and Nevşehir stations.
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Singh, Rohit, Animesh Chandravanshi, Sanjeev Gurjar, B. Saxena, and Kanta Kumar Sahu. "Trend Analysis of Rainfall Patterns in Rajnandgaon District, Chhattisgarh, India." International Journal of Environment and Climate Change 13, no. 9 (August 11, 2023): 3553–61. http://dx.doi.org/10.9734/ijecc/2023/v13i92607.
Повний текст джерелаАнотація:
Climate is a crucial determinant of an area's vegetation, wildlife, and livability, influenced by long-term atmospheric characteristics and fluctuations. Precipitation, particularly rainfall, plays a vital role in the Earth's hydrological cycle, connecting weather, climate, and water resources. This study focuses on Rajnandgaon district in Chhattisgarh, India, with an average annual precipitation of 1274mm. Analyzing trends, we identify changes in certain properties over time. The findings indicate that rainfall variability, measured by the coefficient of variation, is lowest during June to September (CV < 76%). Monsoon rainfall displays the least variability (CV of 30.88%), while pre-monsoon rainfall and winter rainfall exhibit higher variability (CV of 33.83% and 208.48%, respectively). The analysis also reveals a significant decreasing trend in annual, monsoon, and September rainfall. However, May rainfall shows a significant increase at a 5% level of significance. The study utilizes the non-parametric Mann-Kendall and Sen's Slope Estimator tests, employing monthly rainfall data from 1988 to 2018 for Rajnandgaon district, Chhattisgarh.
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Alashan, Sadık. "Can innovative trend analysis identify trend change points?" Brilliant Engineering 1, no. 3 (February 21, 2020): 6–15. http://dx.doi.org/10.36937/ben.2020.003.002.
Повний текст джерелаАнотація:
Trends in temperature series are the main cause of climate change. Because solar energy directs hydro-meteorological events and increasing variations in this resource change the balance between events such as evaporation, wind, and rainfall. There are many methods for calculating trends in a time series such as Mann-Kendall, Sen's slope estimator, Spearman's rho, linear regression and the new Sen innovative trend analysis (ITA). In addition, Mann-Kendall's variant, the sequential Mann Kendall, has been developed to identify trend change points; however, it is sensitive to related data as specified by some researchers. Şen_ITA is a new trend detection method and does not require independent and normally distributed time series, but has never been used to detect trend change points. In the literature, multiple, half-time and multi-durations ITA methods are used to calculate partial trends in a time series without identifying trend change points. In this study, trend change points are detected using the Şen_ITA method and named ITA_TCP. This approach may allow researchers to identify trend change points in a time series. Diyarbakır (Turkey) is selected as a study area, and ITA_TCP has detected trends and trends change points in monthly average temperatures. Although ITA detects only a significant upward trend in August, given the 95% statistical significance level, ITA_TCP shows three upward trends in June, July and August, and a decreasing trend in September. Critical trend slope values are obtained using the bootstrap method, which does not require the normal distribution assumption.
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Alashan, Sadık. "Can innovative trend analysis identify trend change points?" Brilliant Engineering 1, no. 3 (February 21, 2020): 6–15. http://dx.doi.org/10.36937/ben.2020.003.02.
Повний текст джерелаАнотація:
Trends in temperature series are the main cause of climate change. Because solar energy directs hydro-meteorological events and increasing variations in this resource change the balance between events such as evaporation, wind, and rainfall. There are many methods for calculating trends in a time series such as Mann-Kendall, Sen's slope estimator, Spearman's rho, linear regression and the new Sen innovative trend analysis (ITA). In addition, Mann-Kendall's variant, the sequential Mann Kendall, has been developed to identify trend change points; however, it is sensitive to related data as specified by some researchers. Şen_ITA is a new trend detection method and does not require independent and normally distributed time series, but has never been used to detect trend change points. In the literature, multiple, half-time and multi-durations ITA methods are used to calculate partial trends in a time series without identifying trend change points. In this study, trend change points are detected using the Şen_ITA method and named ITA_TCP. This approach may allow researchers to identify trend change points in a time series. Diyarbakır (Turkey) is selected as a study area, and ITA_TCP has detected trends and trends change points in monthly average temperatures. Although ITA detects only a significant upward trend in August, given the 95% statistical significance level, ITA_TCP shows three upward trends in June, July and August, and a decreasing trend in September. Critical trend slope values are obtained using the bootstrap method, which does not require the normal distribution assumption.
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Nayak, G. H. Harish, A. Varalakshmi, M. G. Manjunath, Veershetty, G. Avinash, and Moumita Baishya. "Trend Analysis and Prediction of Rainfall Using Deep Learning Models in Three Sub-Divisions of Karnataka." Journal of Experimental Agriculture International 45, no. 4 (March 20, 2023): 36–48. http://dx.doi.org/10.9734/jeai/2023/v45i42114.
Повний текст джерелаАнотація:
Precise estimation of rainfall is a crucial and challenging task in environmental science. It involves the use of advanced and powerful models to forecast non-linear and dynamic changes in rainfall. Deep learning, a recently developed method for handling vast amounts of data and resolving complex problems, has proven to be an effective tool for rainfall forecasting. In this study, we applied various deep learning models such as Multilayer Perceptron (MLP), Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), Stacked LSTM, Gated Recurrent Units (GRUs), and a traditional model called Autoregressive Integrated Moving Average (ARIMA), to forecast monthly rainfall data (mm) for three regions of Karnataka: Coastal Karnataka, North Interior Karnataka (NIK), and South Interior Karnataka (SIK). Trend analysis was conducted using the Mann-Kendall trend test (MK test) and the Seasonal Mann-Kendall trend test, along with Sen's Slope Estimator, to determine trends and slope magnitudes. The results showed that deep learning models perform better than traditional methods in forecasting rainfall. The performance of different models was evaluated using forecasting evaluation criteria and found that the LSTM model performed best for Coastal Karnataka, with an RMSE value of 149.45, while the Bi-LSTM model performed best for NIK, with an RMSE value of 32.57, and the Stacked LSTM model performed best for SIK, with an RMSE value of 45.33. Therefore, deep learning models can be effectively used to predict rainfall data with greater accuracy.
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Aher, Madhura Chetan, and S. M. Yadav. "Assessment of rainfall trend and variability of semi-arid regions of Upper and Middle Godavari basin, India." Journal of Water and Climate Change 12, no. 8 (October 28, 2021): 3992–4006. http://dx.doi.org/10.2166/wcc.2021.044.
Повний текст джерелаАнотація:
Abstract Study of rainfall pattern and trend in the long term is essential from climatic change and socioeconomic perspectives. In the present study, monthly, seasonal and annual rainfall of semi-arid regions (Madhya Maharashtra, Marahwada and Vidarbha) of the Godavari basin is evaluated for the period of 1871–2016. The innovative trend analysis (ITA), Mann–Kendall test (MK) and Sen's slope estimator methods are used to check gradual change. A significant increasing or decreasing trend is not detected in the seasonal and annual rainfall series for any of the regions. The rainfall variability index indicates Madhya Maharashtra has received normal rainfall for 40% of the time, Marathwada for 36% of the time and Vidarbha region for 41% of the time. Very dry and very wet conditions are experienced by all three regions for 15% of the time. The spatial and temporal variation in the seasonal and annual rainfall is not significant in these regions. The results obtained from the study will be useful for water resource management of the Godavari basin.
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Theng Hue, Hui, Jing Lin Ng, Yuk Feng Huang, and Yi Xun Tan. "Evaluation of temporal variability and stationarity of potential evapotranspiration in Peninsular Malaysia." Water Supply 22, no. 2 (October 8, 2021): 1360–74. http://dx.doi.org/10.2166/ws.2021.343.
Повний текст джерелаАнотація:
Abstract Potential Evapotranspiration (PET) functions as an indicator to estimate the amount of water loss to the atmosphere. Over the years, global climate change has eventually led to a change of PET capacity and this has affected the agricultural sector and water resource management. The objective of this study was to determine the best PET estimation method as well as to carry out a trend analysis and stationarity test of PET in Peninsular Malaysia. The Mann–Kendall (MK) test and Sen's slope estimator were applied for the trend analysis while the Augmented Dickey–Fuller (ADF) test and Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test were applied for the stationarity test. The findings showed that Pulau Langkawi and Kuantan stations exhibited increasing trends while Bayan Lepas station exhibited decreasing trends for the daily, monthly, and annual PET time series. The daily, monthly, and annual PET time series at Bayan Lepas, Ipoh, Subang and Muadzam Shah stations were found to be stationary. Overall, the PET trend was found to be higher in the coastal regions and stationary in the mountainous region.
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Siddharam, J. B. Kambale, and D. Basavaraja. "Assessment of Long Term Spatial-Temporal Variability of Wind Speed of Kalaburgi District, Karnataka, India." International Journal of Environment and Climate Change 13, no. 7 (May 8, 2023): 363–71. http://dx.doi.org/10.9734/ijecc/2023/v13i71888.
Повний текст джерелаАнотація:
Accurate wind power estimates (based on variable wind speeds) are necessary for successful planning and investment in wind power development. In order to inform the development of wind energy, it is essential to acquire a trustworthy quantification and spatiotemporal characteristics of wind speeds. This research used the ArcGIS, Mann-Kendall (MK) test, and Sen's slope to analyze long-term wind speed data from 7 stations in the Kalaburgi District, North Eastern Region of Karnataka State, from 1981 to 2018. The findings of this study contribute to our knowledge of how wind speeds in Kalaburgi District vary and are distributed over long time scales. Over 35 years, there has been a slight and steady rise or decrease in the average wind speed (aveWS). Second, over a span of about 35 years, the annual aweWS varied greatly at various points within the Kalaburgi District. Additionally, the annual aveWS at each station showed a rising tendency. Last but not least, values of wind speeds varied geographically were not very consistent throughout the year, and gradually decreased.
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Gupta, Lov Kumar, and Shruti Verma. "Rainfall and Temperature Trend Analysis Using Mann-Kendall and Sen’s Slope Estimator Test in Kharun Watershed, Chhattisgarh, India." Current Journal of Applied Science and Technology 42, no. 23 (July 28, 2023): 1–9. http://dx.doi.org/10.9734/cjast/2023/v42i234174.
Повний текст джерелаАнотація:
Temperature and rainfall are important meteorological variables in connection with changes in the climate. Analyzing rainfall temperature changes is a necessary first step in determining how climate change will affect us. Evaluating how climate change would affect the accessibility of water and the environment. The main focus of the current study is on the shifting patterns of rainfall and temperature in the Kharun Watershed, Chhattisgarh. The Mann-Kendall (MK) test and Sen's slope (SS) method are used in this study to examine trends in seasonal and yearly rainfall, and minimum and maximum temperatures (Tmin and Tmax). The research area contained five stations measuring temperature and rainfall. Three seasons—kharif, rabi, and zaid were taken into consideration for the seasonal and yearly trend study. The results of the trend test for precipitation showed an overall upward trend for all five stations (Pindrawan, Raipur, Patan, Dhamtari, and Gurur) and every season. The yearly trend of precipitation likewise exhibits an upward trend throughout the year. Except the Kharif season at Pindrawan, Raipur, and Patan stations, the minimum temperature for all five stations indicates declining trends for all seasons. In all five stations, the annual trend of the minimum temperature over the 35 years had exhibited a downward trend. All five stations' maximum temperatures exhibit rising patterns throughout the year. In all five stations, the annual trend of maximum temperature over the 35 years showed an upward trend.
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Marhaento, Hero, Martijn J. Booij, and Arjen Y. Hoekstra. "Attribution of changes in stream flow to land use change and climate change in a mesoscale tropical catchment in Java, Indonesia." Hydrology Research 48, no. 4 (August 30, 2016): 1143–55. http://dx.doi.org/10.2166/nh.2016.110.
Повний текст джерелаАнотація:
Changes in the stream flow of the Samin catchment (277.9 km2) in Java, Indonesia, have been attributed to land use change and climate change. Hydroclimatic data covering the period 1990–2013 and land use data acquired from Landsat satellite imageries for the years 1994 and 2013 were analysed. A quantitative measure is developed to attribute stream flow changes to land use and climate changes based on the changes in the proportion of excess water relative to changes in the proportion of excess energy. The results show that 72% of the increase in stream flow might be attributed to land use change. The results are validated by a land use change analysis and two statistical trend analyses namely the Mann-Kendall trend analysis and Sen's slope estimator for mean annual discharge, rainfall and potential evapotranspiration. The results of the statistical trend analysis are in the same direction as the results of the attribution analysis, where climate change was relatively minor compared to significant land uses change due to deforestation during the period 1994–2013. We conclude that changes in stream flow can be mainly attributed to land use change rather than climate change for the study catchment.
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Bekele, Daniel, Tena Alamirew, Asfaw Kebede, Gete Zeleke, and Assefa M. Melese. "Analysis of rainfall trend and variability for agricultural water management in Awash River Basin, Ethiopia." Journal of Water and Climate Change 8, no. 1 (August 20, 2016): 127–41. http://dx.doi.org/10.2166/wcc.2016.044.
Повний текст джерелаАнотація:
The national economy and food security of many sub-Saharan countries relies on rain-fed agriculture, hence the impact of rainfall variability is highly significant. The intent of this study is to characterize rainfall variability and trend in Awash River Basin for agricultural water management using standard rainfall statistical descriptors. Long-term climate data of 12 stations were analyzed. Onset and cessation dates, length of growing period (LGP) and probability of dry spell occurrences were analysed using INSTAT Plus software. The Mann–Kendall test and the Sen's slope method were used to assess the statistical significance of the trend. The results show high variability of rainfall (38–73%), LGP (30–38 days) and high probability of dry spell occurrence (up to 100%) during the Belg season (the short rainy season from March to May) compared with the Kiremt season (the main rainy season from June to September) in all stations. Belg season showed a non-significant decline trend in most of the stations, whereas the Kiremt season indicated the contrary. The finding also revealed that supplementary irrigation is vital, especially in the Belg season to cover up to 40% of the crop water requirement deficit.
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Chang, Xiaodong, Zongxue Xu, Gang Zhao, Tao Cheng, and Sulin Song. "Spatial and temporal variations of precipitation during 1979–2015 in Jinan City, China." Journal of Water and Climate Change 9, no. 3 (November 11, 2017): 540–54. http://dx.doi.org/10.2166/wcc.2017.029.
Повний текст джерелаАнотація:
Abstract The spatiotemporal variation of precipitation significantly affects regional hydrological processes and the management of water resources worldwide, indirectly contributing to an aggravation in the frequency and intensity of extreme events, especially in urban areas. To analyze the spatiotemporal variation characteristics of precipitation during 1979–2015 in Jinan City, the China Meteorological Forcing Dataset and 12 precipitation-related indices are adopted and analyzed by using Mann–Kendall trend test, Sen's slope estimator and Pettitt test in this study. The results show that: (1) the annual mean precipitation (AMP) shows a gradual increasing trend from the northern plain area to the southern mountainous area; (2) the heaviest summer precipitation occurs in the southern part of downtown with a high frequency, resulting in the drastic amplification of urban rainstorm flood disasters; (3) the spatial distributions of most indices show a gradual increasing trend from the northern plain area to the southern mountainous area, while consecutive dry days show the opposite tendency; and (4) most indices roughly show similar spatiotemporal variation characteristics with AMP, i.e., decreases in southwestern area, but increases in the eastern mountainous region and the north plain area, exhibiting an overall increasing trend at the 1% significance level.
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Phuong, Dang Nguyen Dong, Vu Thuy Linh, Tran Thong Nhat, Ho Minh Dung, and Nguyen Kim Loi. "Spatiotemporal variability of annual and seasonal rainfall time series in Ho Chi Minh city, Vietnam." Journal of Water and Climate Change 10, no. 3 (June 12, 2018): 658–70. http://dx.doi.org/10.2166/wcc.2018.115.
Повний текст джерелаАнотація:
Abstract This study analyzed spatial and temporal patterns of rainfall time series from 14 proportionally distributed stations in Ho Chi Minh City for the period 1980–2016. Both parametric and nonparametric approaches, specifically, linear regression, the Mann–Kendall test and Sen's slope estimator, were applied to detect and estimate the annual and seasonal trends after using original and notched boxplots for the preliminary interpretation. The outcomes showed high domination of positive trends in the annual and seasonal rainfall time series over the 37-year period, but most statistically significant trends were observed in the dry season. The results of trend estimation also indicated higher increasing rates of rainfall in the dry season compared to the rainy season at most stations. Even though the total amount of annual rainfall is mainly contributed by rainfall during the rainy season, the pronounced increment in the dry season can be a determining factor of possible changes in annual rainfall. Additionally, the interpolated results revealed a consistently increasing trend in the southeastern parts of the study area (i.e., Can Gio district), where annual rainfall was by far the lowest intensity compared to other regions.
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Bong, C. H. J., and J. Richard. "Drought and climate change assessment using Standardized Precipitation Index (SPI) for Sarawak River Basin." Journal of Water and Climate Change 11, no. 4 (August 12, 2019): 956–65. http://dx.doi.org/10.2166/wcc.2019.036.
Повний текст джерелаАнотація:
Abstract Severe droughts in the year 1998 and 2014 in Sarawak due to the strong El Niño has impacted the water supply and irrigated agriculture. In this study, the Standardized Precipitation Index (SPI) was used for drought identification and monitoring in Sarawak River Basin. Using monthly precipitation data between the year 1975 and 2016 for 15 rainfall stations in the basin, the drought index values were obtained for the time scale of three, six and nine months. Rainfall trend for the years in study was also assessed using the Mann–Kendall test and Sen's slope estimator and compared with the drought index. Findings showed that generally there was a decreasing trend for the SPI values for the three time scales, indicating a higher tendency of increased drought event throughout the basin. Furthermore, it was observed that there was an increase in the numbers of dry months in the recent decade for most of the rainfall stations as compared to the previous 30 to 40 years, which could be due to climate change. Findings from this study are valuable for the planning and formulating of drought strategies to reduce and mitigate the adverse effects of drought.
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Kavitha, S., and J. Manikandan. "Analysis of Statistical Trends of Future Air Pollutants for Accurate Prediction." Journal of Soft Computing Paradigm 3, no. 4 (December 30, 2021): 260–71. http://dx.doi.org/10.36548/jscp.2021.4.002.
Повний текст джерелаАнотація:
The climate change may be mitigated, and intra air quality assessment and local human well-being can benefit from a decrease in emission of pollutant content in the air. Monitoring the quality of the air around us is one way to do this. However, a location with various emission sources and short-term fluctuations in emissions in both time and space, and changes in winds, temperature, and precipitation creates a complex and variable pollution concentration field in the atmosphere. Therefore, based on the time and location where the sample is obtained, the measurement conducted are reflected in the monitoring results. This study aims to investigate one of India's most polluted cities' air quality measurements by greenhouse gas emissions. Using the Mann-Kendall and Sen's slope estimators, the research piece gives a statistical trend analysis of several air contaminants based on previous pollution data from Mumbai, India's air quality index station. In addition, future levels of air pollution may be correctly forecasted using an autoregressive integrated moving average model. This is followed by comparing different air quality standards and forecasts for future air pollution levels.
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Abbas, Sohail, Safdar Ali Shirazi, Nausheen Mazhar, Kashif Mahmood, and Ashfak Ahmad Khan. "Spatial and Temporal Variations of Temperature in the Punjab Province, Pakistan." International Journal of Economic and Environmental Geology 12, no. 1 (June 8, 2021): 67–75. http://dx.doi.org/10.46660/ijeeg.vol12.iss1.2021.564.
Повний текст джерелаАнотація:
Identifying the temperature change at a regional level is one of the essential parameters to determine the intensity of climate change. The current investigation provides an examination of changing trends of temperature in the Punjab province from 1970 to 2019. Sen's slope estimator method is applied to monthly data of mean temperature (Tmean), maximum temperature (Tmax), and minimum temperature (Tmin) to calculate the rate of temperature change. Statistical methods were used to find out the level of significance in terms of negative or positive trends to examine the variability among various weather observatories. Moreover, predicted values have also been observed for a detailed analysis of temperature variability and trends. Significant and pronounced changes in the mean temperature (T mean) are distinguished all over the Punjab regions with an increasing trend from North to South Punjab. In the case of maximum temperature (Tmax), a faster rate of rising in temperature is observed over the Southern and Western regions of Punjab. In contrast, the minimum temperature (Tmin) shows an increasing trend in Central Punjab. The findings provide detailed insight to policymakers for the planning of mitigating efforts and adaptation strategies in response to climate change.
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Ng, Chun Kang, Jing Lin Ng, Yuk Feng Huang, Yi Xun Tan, and Majid Mirzaei. "Tropical rainfall trend and stationarity analysis." Water Supply 20, no. 7 (July 1, 2020): 2471–83. http://dx.doi.org/10.2166/ws.2020.143.
Повний текст джерелаАнотація:
Abstract Climate change is most likely to cause changes to the temporal and spatial variability of rainfall. A trend analysis to investigate the rainfall pattern can detect changes over temporal and spatial scales for a rainfall series. In this study, trend analysis using the Mann–Kendall test and Sen's slope estimator was conducted in the Kelantan River Basin, Malaysia. The Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test was applied to evaluate the stationarity of the rainfall series. This basin annually faces onslaughts of varying year-end flooding conditions. The trend analysis was applied for monthly, seasonal and yearly rainfall series between 1989 and 2018. The temporal analysis results showed that both increasing and decreasing trends were detected for all rainfall series. The spatial analysis results indicated that the northern region of the Kelantan River Basin showed an increasing trend, whilst the southwest region showed a decreasing trend. It was found that almost all the rainfall series were stationary except at two rainfall stations during the Inter Monsoon 1, Inter Monsoon 2 and yearly rainfall series. Results obtained from this study can be used as reference for water resources planning and climate change assessment.
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Mrad, Dounia, Yassine Djebbar, and Yahia Hammar. "Analysis of trend rainfall: Case of North-Eastern Algeria." Journal of Water and Land Development 36, no. 1 (March 1, 2018): 105–15. http://dx.doi.org/10.2478/jwld-2018-0011.
Повний текст джерелаАнотація:
AbstractThe climatic change is a reality largely recognized today in the scientific community. Nevertheless, its impact on precipitation, especially on annual, monthly and seasonally rainfall in arid and semi-arid regions is not yet certain. Indeed, very few studies have dealt with this matter in Algeria.In this context to examine spatial distribution of annual and seasonal rainfall an attempt has been made using the inverse distance weighting (IDW) method. Trends and magnitude estimate of change in rainfall series were detected by Mann–Kendall tests and Sen's test slope, has been applied to the data registered of 35 stations in the watershed Constantinois Seybouse Mellegue (CSM) North-Eastern Algeria over a period of 43 years (1969–2012).Results from spatial plot of annual rainfall showed that the rainfall increases with altitude, but is higher for the stations exposed to moist winds. It also increases from east to west and conversely decreases as one moves away from the coast to the south. From statistical method showed that there are increase trends at 95% confidence at annual scale in some rainfall stations with high altitude and coastal stations during winter season.
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Zabihi, Omid, Mohammad Gheibi, Reza Aghlmand, and Amir Nejatianc. "Scrutinizing Famine Disaster Based On Rainfall Trend Investigation (A Case Study of Khorasan Razavi Province)." Journal of Water 1, no. 2 (May 19, 2022): 17–26. http://dx.doi.org/10.14302/issn.2769-2264.jw-22-4086.
Повний текст джерелаАнотація:
Rainfall is one of the most important components of the hydrological cycle. The importance of rainfall in arid and semi-arid regions is more apparent. Due to the important role of rainfall trend assessment in the proper management of water resources, in the present study, Khorasan Razavi province, the second-most populous province of Iran located in the northeast of the country, for this purpose was studied. Currently, this region is facing water shortage problems. In this study, the non-parametric Mann-Kendall method was used to evaluate the annual rainfall trend over a thirty-year period from 1989 to 2019. On the other hand, Sen's slope estimator method was used to determine the magnitude of the rainfall trend in the studied synoptic and rain gauge stations. The results showed that the root of water shortage problems is not due to drastic changes in rainfall. Therefore, water shortage problems in Khorasan Razavi province are mainly due to a lack of proper management (i.e., mismanagement). The present study, by examining the rainfall trend using an appropriate framework, tried to take an effective step towards improving the management of water resources in the northeast of Iran.
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Athare, Prakash Goraksha, Dharam Raj Singh, Nalini Ranjan Kumar, Girish Kumar Jha, P. Venkatesh, and Bidisha Chakrabarti. "Spatio-Temporal Analysis of Rainfall and Temperature Trends in Maharashtra State, India (Asia)." International Journal of Environment and Climate Change 13, no. 9 (July 7, 2023): 552–61. http://dx.doi.org/10.9734/ijecc/2023/v13i92270.
Повний текст джерелаАнотація:
Examining the manifestations and effects of climate change is critically dependent on the spatiotemporal analysis of meteorological variables, particularly in areas where agriculture depends on rainfall. The present study analyses the change in temperature and rainfall using Mann-Kendall and Sen's slope estimator and also identifies the variations in rainfall by using Rainfall Anomaly Index (RAI). The main purpose of this study is to assess the variation in climatic variable (temperature and rainfall) across the regions of Maharashtra over 50 years (1968-2017) which might be helpful to identify strategies that can aid in addressing the consequences of extreme climate events in the future and in formulating appropriate region-specific strategies. The trend of rainfall and temperature series for the kharif and rabi season revealed a significant increasing trend for maximum and minimum temperature, however nonsignificant decreasing trend for kharif and rabi rainfall. The RAI value indicates a relatively a greater number of dry periods in Marathwada and Vidarbha region in comparison to the Konkan, Western Maharashtra and Khandesh. The findings of the study can be useful in developing plans to manage water resources effectively and reduce the adverse impacts of droughts basically in the Marathwada and Vidarbha regions.
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Osuch, M., R. J. Romanowicz, D. Lawrence, and W. K. Wong. "Assessment of the influence of bias correction on meteorological drought projections for Poland." Hydrology and Earth System Sciences Discussions 12, no. 10 (October 12, 2015): 10331–77. http://dx.doi.org/10.5194/hessd-12-10331-2015.
Повний текст джерелаАнотація:
Abstract. Possible future climate change effects on drought severity in Poland are estimated for six ENSEMBLE climate projections using the Standard Precipitation Index (SPI). The time series of precipitation represent six different RCM/GCM run under the A1B SRES scenario for the period 1971–2099. Monthly precipitation values were used to estimate the Standard Precipitation Index (SPI) for multiple time scales (1, 3, 6, 12 and 24 months) for a spatial resolution of 25 km × 25 km for the whole country. Trends in SPI were analysed using a Mann–Kendall test with Sen's slope estimator for each 25 km × 25 km grid cell for each RCM/GCM projection and timescale, and results obtained for uncorrected precipitation and bias corrected precipitation were compared. Bias correction was achieved using a distribution-based quantile mapping (QM) method in which the climate model precipitation series were adjusted relative to gridded E-OBS precipitation data for Poland. The results show that the spatial pattern of the trend depends on the climate model, the time scale considered and on the bias correction. The effect of change on the projected trend due to bias correction is small compared to the variability among climate models. We also summarise the mechanisms underlying the influence of bias correction on trends using a simple example of a linear bias correction procedure. In the case of precipitation the bias correction by QM does not change the direction of changes but can change the slope of trend. We also have noticed that the results for the same GCM, with differing RCMs, are characterized by similar pattern of changes, although this behaviour is not seen at all time scales and seasons.
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Magidi, James, and Fethi Ahmed. "Monitoring vegetation phenology using MODIS NDVI 250m in the City of Tshwane, South Africa." South African Journal of Geomatics 11, no. 2 (September 1, 2022): 176–89. http://dx.doi.org/10.4314/sajg.v11i2.1.
Повний текст джерелаАнотація:
The unprecedented influx of people into urban areas has led to the horizontal and vertical growth of urban environments. One of the notable impacts of urbanisation is the encroachment of urban-like environments into non-urban areas. This is common in both developed and developing countries, and South Africa’s City of Tshwane, the administrative capital of the country, has been affected by urbanisation because of migration. One of the parameters or proxies used to quantify urban growth is vegetation cover. There is a consensus that with the increase in the population of urban dwellers, vegetation cover will decrease. To assess and monitor vegetation cover, the Normalised Difference Vegetation Index (NDVI) is commonly used. In this study, MODIS NDVI data with a 250m spatial resolution was used to assess the impact of urban growth on vegetation. A time series analysis of the MODIS NDVI with a spatial resolution of 250m was used to establish the patterns of vegetation cover. Trends in vegetation change were determined in newly developed residential areas, informal settlements, and various vegetated areas. Sen's slope estimator and Mann-Kendall’s statisticwere used to analyse the spatial trends and variations in trends among different land cover classes. The slope of the trends differs significantly but there is a general decline in vegetation cover. The temporal profiles revealed the high and low NDVI values, respectively showing greening (high vegetation) and browning (low vegetation) trends from 2000 to 2016. It is concluded that urban growth has an impact on vegetation cover. However, this does not disturb the seasonal changes in vegetation where high NDVI values prevail in summer and low values in winter.
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Oyerinde, Ganiyu Titilope, Agnide E. Lawin, and Oluwafemi E. Adeyeri. "Multi-variate infilling of missing daily discharge data on the Niger basin." Water Practice and Technology 16, no. 3 (May 28, 2021): 961–79. http://dx.doi.org/10.2166/wpt.2021.048.
Повний текст джерелаАнотація:
Abstract The Niger basin has experienced historical drought episodes and floods in recent times. Reliable hydrological modelling has been hampered by missing values in daily river discharge data. We assessed the potential of using the Multivariate Imputation by Chained Equations (MICE) to estimate both continuous and discontinuous daily missing data across different spatial scales in the Niger basin. The study was conducted on 22 discharge stations that have missing data ranging from 2% to 70%. Four efficiency metrics were used to determine the effectiveness of MICE. The flow duration curves (FDC) of observed and filled data were compared to determine how MICE captured the discharge patterns. Mann-Kendall, Modified Mann-Kendall, Pettit and Sen's Slope were used to assess the complete discharge trends using the gap-filled data. Results shows that MICE near perfectly filled the missing discharge data with Nash-Sutcliffe Efficiency (NSE) range of 0.94–0.99 for the calibration (1992–1994) period. Good fits were obtained between FDC of observed and gap-filled data in all considered stations. All the catchments showed significantly increasing discharge trend since 1990s after gap filling. Consequently, the use of MICE in handling missing data challenges across spatial scales in the Niger basin was proposed.