scholarly journals Trend and variability analysis of rainfall and temperature in the Tana basin region, Ethiopia

2018 ◽  
Vol 9 (3) ◽  
pp. 555-569 ◽  
Author(s):  
Hailu Birara ◽  
R. P. Pandey ◽  
S. K. Mishra
Keyword(s):  
Climate Variability ◽  
Kendall Test ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Positive Trend ◽  
Distance Weighted ◽  
Slope Estimator ◽  
Basin Region ◽  
Annual Maximum Temperature ◽  
Inverse Distance

Abstract Global warming and climate variability are emerging as the foremost environmental problems in the 21st century, particularly in developing countries. Ethiopia is one of the countries located in the sub-Sahara region and climate variability has a significant impact on the economy of the country. The aim of this study is to characterize annual and seasonal rainfall and annual temperature variability, and to measure trends on both the spatial and the temporal scale for ten selected stations in the Tana basin region, Ethiopia. The Mann–Kendall test and Sen's slope estimator were used to assess trends and variability of rainfall and temperature. The spatial distribution of rainfall and temperature was determined using the inverse distance weighted technique. Results indicated that the amount of rainfall decreased for the majority of the stations. The annual rainfall showed significant decreasing trends with a magnitude ranging from −5.92 mm/year at Injibara to −9.74 mm/year in Wegera. However, a positive trend of annual rainfall was observed at Addis Zemen (1.81 mm/year). The minimum, maximum and mean temperatures have increased significantly for most of the stations. An increasing trend of annual maximum temperature was obtained between 1980 and 2015; an increase of 1.08°C was observed.

scholarly journals Spatiotemporal Trend Analysis of the Mean Annual Rainfall in Senegal

2016 ◽  
Vol 12 (12) ◽  
pp. 231 ◽  
Author(s):  
Lamine Diop ◽  
Ansoumana Bodian ◽  
Dior Diallo
Keyword(s):  
Kendall Test ◽  
Annual Rainfall ◽  
Positive Trend ◽  
Sen’S Slope Estimator ◽  
Small Areas ◽  
Sen’S Slope ◽  
Trend Magnitude ◽  
North East ◽  
Spatiotemporal Trends ◽  
Slope Estimator

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.

scholarly journals Rainfall trend and variability over Opak River basin, Yogyakarta, Indonesia

2020 ◽  
Vol 1000 (1000) ◽  
Author(s):  
Wakhidatik Nurfaida ◽  
Hendra Ramdhani ◽  
Takenori Shimozono ◽  
Indri Triawati ◽  
Muhammad Sulaiman
Keyword(s):  
River Basin ◽  
Water Resource ◽  
Rainfall Intensity ◽  
Kendall Test ◽  
Rainfall Data ◽  
Positive Trend ◽  
Sen’S Slope Estimator ◽  
Sen’S Slope ◽  
Slope Estimator

Rainfall intensity seems to be increasing nowadays due to climate change as presented in many studies of both global and regional scale. Consequently, cities worldwide are now more vulnerable to flooding. In Indonesia, increasing frequency of floods was reported for the past decades by The National Agency for Disaster Countermeasure (BNPB). To understand the rainfall changes, long-term trend evaluation over a specific area is then crucial due to the large variability of spatial and temporal rainfall distribution. This study investigates the homogeneity and trend of rainfall data from 20 stations over the Opak River basin, Yogyakarta, Indonesia. A long-term ground observation rainfall data whose period varies from 1979 to 2019 were analyzed. Non-parametric Mann – Kendall test was applied to assess the trend, while the magnitude was calculated using the Sen’s slope estimator. An increasing annual maximum of daily rainfall intensity was observed at four stations on a 0.95 confidence level based on the Mann – Kendall test, while the Sen’s slope estimator shows a positive trend at almost all stations. The trend of heavy rainfall frequency was also found to be significantly increased, with only one station showed a decreasing trend. Furthermore, this paper also described the spatial and temporal rainfall variability. Positive trend was mostly found during the rainy season, while the negative trend occurred during the dry season. This could pose a challenge for water resource management engineering and design, such as water supply systems or reservoir management. Understanding this phenomena will benefit hydrologists in preparing future water resource engineering and management.

Homogeneity Evaluation of Historical Rainfall and Temperature Series in Mato Grosso

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.

Effects of inter-annual climate variability on grape harvest timing in rainfed hilly vineyards of Piedmont (NW Italy)

2020 ◽  
Author(s):  
Danilo Rabino ◽  
Marcella Biddoccu ◽  
Giorgia Bagagiolo ◽  
Guido Nigrelli ◽  
Luca Mercalli ◽  
...  
Keyword(s):  
Climate Variability ◽  
Weather Data ◽  
Maximum Temperature ◽  
Data Series ◽  
Positive Trend ◽  
Climate Variables ◽  
Climate Data ◽  
Historical Series ◽  
Nw Italy ◽  
Level Of Significance

<p>Historical weather data represent an extremely precious resource for agro-meteorology for studying evolutionary dynamics and for predictive purposes, to address agronomical and management choices, that have economic, social and environmental effect. The study of climatic variability and its consequences starts from the observation of variations over time and the identification of the causes, on the basis of historical series of meteorological observations. The availability of long-lasting, complete and accurate datasets is a fundamental requirement to predict and react to climate variability. Inter-annual climate changes deeply affect grapevine productive cycle determining direct impact on the onset and duration of phenological stages and, ultimately, on the grape harvest and yield. Indeed, climate variables, such as air temperature and precipitation, affect evapotranspiration rates, plant water requirements, and also the vine physiology. In this respect, the observed increase in the number of warm days poses a threat to grape quality as it creates a situation of imbalance at maturity, with respect to sugar content, acidity and phenolic and aromatic ripeness.</p><p>A study was conducted to investigate the relationships between climate variables and harvest onset dates to assess the responses of grapevine under a global warming scenario. The study was carried out in the “Monferrato” area, a rainfed hillslope vine-growing area of NW Italy. In particular, the onset dates of harvest of different local wine grape varieties grown in the Vezzolano Experimental Farm (CNR-IMAMOTER) and in surrounding vineyards (affiliated to the Terre dei Santi Cellars) were recorded from 1962 to 2019 and then related to historical series of climate data by means of regression analysis. The linear regression was performed based on the averages of maximum and minimum daily temperatures and sum of precipitation (1962–2019) calculated for growing and ripening season, together with a bioclimatic heat index for vineyards, the Huglin index. The climate data were obtained from two data series collected in the Experimental farm by a mechanical weather station (1962-2002) and a second series recorded (2002-2019) by an electro-mechanical station included in Piedmont Regional Agro-meteorological Network. Finally, a third long-term continuous series covering the period from 1962 to 2019, provided by Italian Meteorological Society was considered in the analysis.</p><p>The results of the study highlighted that inter-annual climate variability, with a general positive trend of temperature, significantly affects the ripening of grapes with a progressive anticipation of the harvest onset dates. In particular, all the considered variables excepted precipitation, resulted negatively correlated with the harvest onset date reaching a high level of significance (up to P< 0.001). Best results have been obtained for maximum temperature and Huglin index, especially by using the most complete dataset. The change ratios obtained using datasets including last 15 years were greater (in absolute terms) than results limited to the period 1962-2002, and also correlations have greater level of significance. The results indicated clearly the relationships between the temperature trend and the gradual anticipation of harvest and the importance of having long and continuous historical weather data series available.</p>

TREND ANALYSIS OF RAINFALL, TEMPERATURE AND RUNOFF DATA: A CASE STUDY OF RANGOON WATERSHED IN NEPAL

2017 ◽  
Vol 5 (3) ◽  
pp. 21-38 ◽  
Author(s):  
Amar Bahadur Pal ◽  
Deepak Khare ◽  
Prabhash Kumar Mishra ◽  
Lakhwinder Singh
Keyword(s):  
Trend Analysis ◽  
Research Work ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Original Research ◽  
Positive Trend ◽  
Sen’S Slope ◽  
Z Value ◽  
Trend Direction

Purpose: The study has been carried out to investigate and assess the significance of the potential trend of three variables viz. rainfall, temperature and runoff over the Rangoon watershed in Dadeldhura district of Nepal.Methodology: In this study, trend analysis has been carried out on monthly, seasonal and annual basis using the data period between 1979 to 2010 for rainfall and temperature and 1967 to 1996 for runoff. 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.Main findings: The most important findings are, i) There is warming trends over the Rangoon watershed as Mann-Kendall statistic (Z-value) for most of the maximum temperature values are positive, ii) Rainfall and runoff affected by fluctuations every year though the annual rainfall showing a rising trend whereas runoff showing a falling trend. The rainfall seasonal trend analysis indicates that monsoon and post-monsoon period showed a positive rainfall trend with z statistics of +1.93, and +1.12 respectively, whereas pre-monsoon and winter seasons showed a negative trend with z statistics of -1.02, and -0.54 respectively. However, the annual rainfall in the Rangoon watershed showed a positive trend with a z value of +1.70.Importance of this study: This case study has been undertaken to investigate the trends of important climatic variables viz. rainfall, temperature which have a direct impact on the agriculture of the region.Originality / Novelty of study: This is an original research work undertaken under the M. Tech programme during 2016-17 at IIT Roorkee by the scholar Er. Amar Bahadur Pal from Nepal. 

scholarly journals Cuantificación e interpolación de tendencias locales de temperatura y precipitación en zonas alto andinas de Cundinamarca y Boyacá (Colombia)

2010 ◽  
Vol 11 (2) ◽  
pp. 173 ◽  
Author(s):  
Edwin Rojas ◽  
Blanca Arce ◽  
Andrés Peña ◽  
Francisco Boshell ◽  
Miguel Ayarza
Keyword(s):  
Production Systems ◽  
Hydrological Cycle ◽  
Kendall Test ◽  
Maximum Temperature ◽  
Positive Trend ◽  
Weighted Interpolation ◽  
Weather Patterns ◽  
Statistical Confidence ◽  
Temperature And Precipitation ◽  
Inverse Distance Weighted Interpolation

<p>El cambio en el patrón climático global no sólo afecta la temperatura, sino el ciclo hidrológico con mayores variaciones en los ambientales locales. Con el fin de cuantificar las tendencias de temperatura máxima, mínima y precipitación media, se realizó un análisis no-paramétrico de las series de tiempo de 31 estaciones meteorológicas ubicadas en zonas alto andinas de Cundinamarca y Boyacá, con registros de 1985 a 2008. Se calcularon las tendencias de cambio de las variables climáticas para cada una de las estaciones mediante el método de estimación de pendiente de Sen y se utilizó la prueba de Mann- Kendall para determinar el nivel de confianza de dichas tendencias. La temperatura máxima mostró tendencias positivas con niveles de confianza significativa (&gt;90%) en la mayoría de estaciones climáticas. Para la temperatura mínima, la tendencia positiva fue detectada en menor número de estaciones pero con mayores niveles de confianza estadística (12 estaciones superaron el 95%). La precipitación mostró tendencias significativas (&gt;90%) sólo en siete de las 31 estaciones analizadas (seis de ellas fueron positivas y una negativa). Se utilizó el método de interpolación de distancia inversa ponderada (IDW) para generar los mapas de la distribución espacial de las tendencias. Mediante validación cruzada se encontró que el IDW tiene un mejor ajuste para la precipitación que para la temperatura. Se concluye que el cambio climático tiene manifestaciones muy locales en términos del comportamiento de las temperaturas y la precipitación para la zona de estudio, lo que podría generar impactos específicos sobre los sistemas productivos de la región.</p><p> </p><p><strong>Quantization and interpolation of local trends in temperature and precipitation in the high Andean areas of Cundinamarca and Boyaca (Colombia)</strong></p><p>Change in global weather patterns affects not only temperature, but also the hydrological cycle with greater variations in local environments. In order to quantify trends in maximum temperature and minimum and average precipitation, we performed a nonparametric analysis of time series of 31 meteorological stations located in the high Andes of Cundinamarca and Boyaca, with records from 1985 to 2008. We calculated the changing trends of climatic variables for each of the stations with the Sen slope estimator and we used the Mann-Kendall test to determine the confidence level of such trends. The maximum temperature showed positive trends with significant confidence levels (&gt; 90%) in most seasons. For the lowest temperature, the positive trend was detected in fewer stations but with higher levels of statistical confidence (12 stations exceeded 95%). Rainfall showed significant trends (&gt; 90%) in only seven of the 31 stations analyzed (six of them were positive and one negative). We used the method of inverse distance weighted interpolation (IDW) to generate maps of the spatial distribution of the trends. Cross validation found that IDW has a better fit for precipitation than for temperature. We conclude that climate change manifests very local expressions in terms of the behavior of temperatures and precipitation for the study area, which could lead to specific impacts on production systems in the region.</p>

scholarly journals Rainfall trend analysis

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.

scholarly journals Rainfall Variability across the Agro-Climatic Zones of a Tropical Highland: The Case of the Jema Watershed, Northwestern Ethiopia

Environments ◽  
2019 ◽  
Vol 6 (11) ◽  
pp. 118 ◽  
Author(s):  
Taye ◽  
Simane ◽  
Zaitchik ◽  
Selassie ◽  
Setegn
Keyword(s):  
Climate Variability ◽  
Coefficient Of Variation ◽  
Rainfall Variability ◽  
Arithmetic Functions ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Climatic Zones ◽  
Climate Indicators

The objective of the study was to analyze the variability of various climate indicators across the agro-climatic zones (ACZs) of the Jema watershed. The variability was analyzed considering mean annual rainfall (MARF, mm), mean daily minimum temperature (MDMinT, °C), and mean daily maximum temperature (MDMaxT, °C). A one-way analysis of variance (ANOVA) was employed to test whether group mean differences exist in the values of the indicated climatic indicators among the ACZs of the watershed. The coefficient of variation was computed to analyze the degree of climate variability among the ACZs. Rainfall and temperature data sets from 1983 to 2017 were obtained from nearby meteorological stations. The effect of climate variability in the farming system was assessed with reference to local farmers’ experience. Ultimately, the values of the stated indicators of exposure to climate variability were indexed (standardized) in order to run arithmetic functions. The MARF decreases towards sub-alpine ACZs. Based on the result of the ANOVA, the two-tailed p-value (≤ 0.04) was less than 0.05; that is, there was a significant variation in MARF, MDMaxT (°C), and MDMinT (°C) among the ACZs. The coefficient of variation showed the presence of variations of 0.18–0.88 for MARF, 0.18 to 0.85 for MDMaxT, and 0.02–0.95 for MDMinT across the ACZs. In all of the indicators of exposure to climate variability, the lowest and highest indexed values of coefficient of variation were observed in the moist–cool and sub-alpine ACZs, respectively. Overall, the aggregate indexed values of exposure to various climate indicators ranged from 0.13–0.89 across the ACZs. The level of exposure to climate variability increased when moving from moist–cool to sub-alpine ACZs. The overall crop diversity declined across the ACZs of the watershed. Nevertheless, mainly because of the rise in temperature, the climate became suitable for cultivating maize and tef even at higher elevations. In order to adapt to the inter-annual variability of the rainy season, the process of adapting early-maturing crops and the use of improved seeds needs to be enhanced in the watershed, especially in the higher-elevation zones. It is also essential to revise traditional crop calendars and crop zones across the ACSz.

scholarly journals A Gridded Database for the Spatiotemporal Analysis of Rainfall in Southern Italy (Calabria Region)

2020 ◽  
Vol 2 (1) ◽  
pp. 6
Author(s):  
Tommaso Caloiero ◽  
Roberto Coscarelli ◽  
Gaetano Pellicone
Keyword(s):  
Southern Italy ◽  
Interpolation Method ◽  
Grid Point ◽  
Spatiotemporal Analysis ◽  
Annual Rainfall ◽  
Inverse Distance Weighted ◽  
Calabria Region ◽  
Increasing Trend ◽  
Distance Weighted ◽  
Inverse Distance

In this work, a gridded database was obtained from a rainfall dataset of 129 monthly series collected for the period 1951–2016 in the Calabria region (southern Italy). The Inverse Distance Weighted (IDW) interpolation method was applied to build 603 rainfall grid series with a spatial resolution of 5 km × 5 km. In order to detect possible trends, for each grid point, the seasonal and annual rainfall series were analyzed with the Mann–Kendall non-parametric test and the Theil–Sen estimator. Results showed a decreasing trend for the annual and winter–autumn rainfall and an increasing trend for the summer one.

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