scholarly journals Analyzing Trend and Variability of Rainfall in The Tafna Basin (Northwestern Algeria)

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 347 ◽  
Author(s):  
Hanane Bougara ◽  
Kamila Baba Hamed ◽  
Christian Borgemeister ◽  
Bernhard Tischbein ◽  
Navneet Kumar
Keyword(s):  
Time Series ◽  
Water Resource Management ◽  
Statistical Tests ◽  
Trend Detection ◽  
Detection Methods ◽  
Annual Rainfall ◽  
Rainfall Time Series ◽  
Friedman Test ◽  
Upward Trend ◽  
Increasing Trend

Northwest Algeria has experienced fluctuations in rainfall between the two decades 1940s and 1990s from positive to negative anomalies, which reflected a significant decline in rainfall during the mid-1970s. Therefore, further analyzing rainfall in this region is required for improving the strategies on water resource management. In this study, we complement previous studies by dealing with sub basins that were not previously addressed in Tafna basin (our study area located in Northwest Algeria), and by including additional statistical methods (Kruskal–Wallis test, Jonckheere-Terpstra test, and the Friedman test) that were not earlier reported on the large scale (Northwest Algeria). In order to analyse the homogeneity, trends, and stationarity in rainfall time series for nine rainfall stations over the period 1979–2011, we have used several statistical tests. The results showed an increasing trend for annual rainfall after the break detected in 2007 for Djbel Chouachi, Ouled Mimoun, Sidi Benkhala stations using Hubert, Pettitt, and Buishand tests. The Lee and Heghinian test has detected a break at the same year in 2007 for all stations except Sebdou, Beni Bahdel, and Hennaya stations, which have a break date in 1980. We have confirmed this increasing trend for rainfall with other trend detection methods such as Mann Kendall and Sen’s method that highlighted an upward trend for all the stations in the autumn season, which is mainly due to an increase in rainfall in September and October. On a monthly scale, the date of rupture is different from one station to another because the time series are not homogeneous. In addition, we have applied three tests enabling further results: (i) the Jonckheere-Terpstra test has detected an upward trend for two stations (Khemis and Hennaya), (ii) Friedman test has indicated the difference between the mean rank again with Khemis and Hennaya stations and the Merbeh station, (iii) according to the Kruskal-Wallis test, there have been no variance detected between all the rainfall stations. The increasing trend in rainfall may lead to a rise in stream flow and enhance potential floods risks in low-lying regions of the study area.

scholarly journals Trend detection of atmospheric time series

Elem Sci Anth ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Kai-Lan Chang ◽  
Martin G. Schultz ◽  
Xin Lan ◽  
Audra McClure-Begley ◽  
Irina Petropavlovskikh ◽  
...  
Keyword(s):  
Time Series ◽  
Atmospheric Chemistry ◽  
Surface Ozone ◽  
High Surface ◽  
Effective Means ◽  
Environmental Data ◽  
Model Specification ◽  
Trend Detection ◽  
Detection Methods ◽  
Sources Of Uncertainty

This paper is aimed at atmospheric scientists without formal training in statistical theory. Its goal is to (1) provide a critical review of the rationale for trend analysis of the time series typically encountered in the field of atmospheric chemistry, (2) describe a range of trend-detection methods, and (3) demonstrate effective means of conveying the results to a general audience. Trend detections in atmospheric chemical composition data are often challenged by a variety of sources of uncertainty, which often behave differently to other environmental phenomena such as temperature, precipitation rate, or stream flow, and may require specific methods depending on the science questions to be addressed. Some sources of uncertainty can be explicitly included in the model specification, such as autocorrelation and seasonality, but some inherent uncertainties are difficult to quantify, such as data heterogeneity and measurement uncertainty due to the combined effect of short and long term natural variability, instrumental stability, and aggregation of data from sparse sampling frequency. Failure to account for these uncertainties might result in an inappropriate inference of the trends and their estimation errors. On the other hand, the variation in extreme events might be interesting for different scientific questions, for example, the frequency of extremely high surface ozone events and their relevance to human health. In this study we aim to (1) review trend detection methods for addressing different levels of data complexity in different chemical species, (2) demonstrate that the incorporation of scientifically interpretable covariates can outperform pure numerical curve fitting techniques in terms of uncertainty reduction and improved predictability, (3) illustrate the study of trends based on extreme quantiles that can provide insight beyond standard mean or median based trend estimates, and (4) present an advanced method of quantifying regional trends based on the inter-site correlations of multisite data. All demonstrations are based on time series of observed trace gases relevant to atmospheric chemistry, but the methods can be applied to other environmental data sets.

scholarly journals 3D magneto-hydrodynamical simulations of stellar convective noise for improved exoplanet detection

2020 ◽  
Vol 635 ◽  
pp. A146 ◽  
Author(s):  
S. Sulis ◽  
D. Mary ◽  
L. Bigot
Keyword(s):  
Time Series ◽  
Statistical Tests ◽  
Amplitude Distribution ◽  
False Alarm Probability ◽  
Detection Methods ◽  
Reliable Estimate ◽  
Critical Element ◽  
Adaptive Tests ◽  
Mhd Simulations ◽  
Hydrodynamical Simulations

Context. Convective motions at the stellar surface generate a stochastic colored noise source in the radial velocity (RV) data. This noise impedes the detection of small exoplanets. Moreover, the unknown statistics (amplitude, distribution) related to this noise make it difficult to estimate the false alarm probability (FAP) for exoplanet detection tests. Aims. In this paper, we investigate the possibility of using 3D magneto-hydrodynamical (MHD) simulations of stellar convection to design detection methods that can provide both a reliable estimate of the FAP and a high detection power. Methods. We tested the realism of 3D simulations in producing solar RV by comparing them with the observed disk integrated velocities taken by the GOLF instrument on board the SOHO spacecraft. We presented a new detection method based on periodograms standardized by these simulated time series, applying several detection tests to these standarized periodograms. Results. The power spectral density of the 3D synthetic convective noise is consistent with solar RV observations for short periods. For regularly sampled observations, the analytic expressions of FAP derived for several statistical tests applied to the periodogram standardized by 3D simulation noise are accurate. The adaptive tests considered in this work (Higher-Criticism, Berk-Jones), which are new in the exoplanet field, may offer better detection performance than classical tests (based on the highest periodogram value) in the case of multi-planetary systems and planets with eccentric orbits. Conclusions. 3D MHD simulations are now mature enough to produce reliable synthetic time series of the convective noise affecting RV data. These series can be used to access to the statistics of this noise and derive accurate FAP of tests that are a critical element in the detection of exoplanets down to the cm s−1 level.

scholarly journals Rainfall Trends over the Past Century for Tropical Climatic Region in Western India

10.29007/szsv ◽  
2018 ◽  
Author(s):  
Priyank Sharma ◽  
Prem Lal Patel
Keyword(s):  
Rainfall Intensity ◽  
Trend Detection ◽  
Annual Rainfall ◽  
Past Century ◽  
Western India ◽  
Study Region ◽  
Maximum Rainfall ◽  
Increasing Trend ◽  
Lower Tapi Basin ◽  
Tapi Basin

Present study examines the applications of different trend detection methodologies for investigation of trend in long-term rainfall over Lower Tapi basin, India using daily gridded rainfall data for the period 1901 – 2013 at 0.25  0.25 resolution. The trends in rainfall indices, viz. total annual rainfall (TAR), annual maximum rainfall (AMR) and average annual rainfall intensity (AAI) have been detected using non-parametric and graphical methods. The results show increasing trends in TAR across all the 9 grids in the study region, with significant increasing trend over Grids-8 and 9. Further, AMR exhibited increasing trend over 7 out of 9 grids, with significant increasing trend over Grid-8 (ZMMK = 2.478;  = 0.356 mm/year) and Grid-9 (ZMMK = 2.278;  = 0.257 mm/year). The Innovative Trend Analysis plots reveal overall increasing trend in AMR across all the grids. The AAI exhibited significant increasing trend over 5 grids including Grids-8 and 9. The Grids 8 and 9 encompass the urban areas of the Surat city, located in the Lower Tapi basin. The urbanization in the Surat city and proximity to the Arabian Sea areas may be the possible reasons for significant increase in the extreme rainfall and rainfall intensity over Grids-8 and 9.

scholarly journals Trend analysis of rainfall using Mann-Kendall, Sen’s slope, moving average and least square techniques for Ahmednagar district of Maharashtra

2021 ◽  
Vol 17 (1) ◽  
pp. 19-25
Author(s):  
Virendra N. Barai ◽  
Rohini M. Kalunge
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Moving Average ◽  
Rainfall Variability ◽  
Least Square ◽  
Annual Rainfall ◽  
Series Data ◽  
Sen’S Slope ◽  
Increasing Trend ◽  
The Impact

The long-term behaviour of rainfall is necessary to study over space with different time series viz., annual, monthly and weekly as it is one of the most significant climatic variables. Rainfall trend is an important tool which assesses the impact of climate change and provides direction to cope up with its adverse effects on the agriculture. Several studies have been performed to establish the pattern of rainfall over various time periods for different areas that can be used for better agricultural planning, water supply management, etc. Consequently, the present report, entitled “Trend analysis of rainfall in Ahmednagar district of Maharashtra,” was carried out. 13 tahsils of the district of Ahmednagar were selected to carry out trend analysis. The daily rainfall data of 33 years (1980- 2012) of all stations has been processed out study the rainfall variability. The Mann Kendall (MK) Test, Sen’s slope method, moving average method and least square method were used for analysis. The statistical analysis of whole reference time series data highlighted that July and August month contributes highest amount of rainfall at all tahsils. Regarding trend in annual rainfall, these four methods showed increasing trend at most of the tahsils whereas a decreasing trend only at Shrigonda tahsil. For monthly trend analysis, Kopargaon, Newasa, Shevgaon and Shrirampur tahsils showed an increasing trend during July. During August and September month, most of the tahsils i.e. Kopargaon, Nagar, Parner and Sangamner showed increasing trends, whereas in June, only Shrigonda tahsil showed decreasing trend.

scholarly journals Detecting trend on ecological river status – how to deal with short incomplete bioindicator time series? Methodological and operational issues

2018 ◽  
Vol 379 ◽  
pp. 169-174
Author(s):  
Flavie Cernesson ◽  
Marie-George Tournoud ◽  
Nathalie Lalande
Keyword(s):  
Time Series ◽  
Statistical Tests ◽  
Methodological Issue ◽  
Temporal Trends ◽  
Graphical Analysis ◽  
Point Of View ◽  
Trend Detection ◽  
Data Sets ◽  
Monitoring Networks ◽  
Operational Issues

Abstract. Among the various parameters monitored in river monitoring networks, bioindicators provide very informative data. Analysing time variations in bioindicator data is tricky for water managers because the data sets are often short, irregular, and non-normally distributed. It is then a challenging methodological issue for scientists, as it is in Saône basin (30 000 km2, France) where, between 1998 and 2010, among 812 IBGN (French macroinvertebrate bioindicator) monitoring stations, only 71 time series have got more than 10 data values and were studied here. Combining various analytical tools (three parametric and non-parametric statistical tests plus a graphical analysis), 45 IBGN time series were classified as stationary and 26 as non-stationary (only one of which showing a degradation). Series from sampling stations located within the same hydroecoregion showed similar trends, while river size classes seemed to be non-significant to explain temporal trends. So, from a methodological point of view, combining statistical tests and graphical analysis is a relevant option when striving to improve trend detection. Moreover, it was possible to propose a way to summarise series in order to analyse links between ecological river quality indicators and land use stressors.

A framework of abrupt changes and trends detection for rainfall erosivity

2020 ◽  
Author(s):  
Feng Qian ◽  
Bo Hu ◽  
Honghu Liu ◽  
Jingjun Liu
Keyword(s):  
Time Series ◽  
Correlation Coefficient ◽  
Soil Loss ◽  
Abrupt Change ◽  
Test Method ◽  
Trend Detection ◽  
Annual Rainfall ◽  
Climate Index ◽  
Rainfall Erosivity ◽  
Soil And Water

<p>Rainfall erosivity (R factor), in the Universal Soil Loss Equation (USLE) , a climate index, is used worldwide to assess and predict the potential of rainfall to cause erosion. The temporal variation in rainfall erosivity, informs of abrupt change and trend, are critical for soil loss prediction. To find a simple and effective method for accurate detection of abrupt change and trend has implication for soil and water conservation planning. In this paper, a four-step framework is proposed to detect abrupt change and trend in rainfall erosivity time series, i.e., evaluate the significance of variation in rainfall erosivity time series at three levels: no, weak and strong, abrupt change and trend detection for rainfall erosivity,  estimation of correlation coefficient between the variation component and rainfall erosivity series, remove the variation component with the largest correlation coefficient from the rainfall erosivity series, repeat the above steps for the new series until variance coefficient was insignificance. The first step is based on an index of Hurst coefficient. The trend detection is implemented using both Spearman rank and Kendall rank correlation test. For abrupt change ,three kinds of methods (Mann-Kendall, Moving T and Bayesian test) are employed.  This framework is applied to the annual rainfall erosivity series of the Three Gorges Reservoir , China. There was a large uncertainty in detecting variability with a single test method. Application of the proposed framework can reduce uncertainty  associated with soil erosion assessment and achieve more accurate regional soil and water management. </p>

scholarly journals Variability and Trend Analysis of Rainfall Data of Shillong and Agartala Stations of North East India

2020 ◽  
pp. 134-142
Author(s):  
Mirbana Lusick K. Sangma ◽  
Hamtoiti Reang ◽  
G. T. Patle ◽  
P. P. Dabral
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Winter Season ◽  
Summer Season ◽  
Annual Rainfall ◽  
Rainfall Time Series ◽  
North East ◽  
South West ◽  
Total Annual Rainfall ◽  
Sw Monsoon

This paper discusses the variability in rainfall and trend analysis of annual and seasonal rainfall time series of Shillong and Agartala stations located in the north-east region of India. Commonly used non-parametric statistical methods namely Mann-Kendall and Sen’s slope estimator was used to analyse the seasonal and annual rainfall time series. Statistical analysis showed less variation in annual and south-west monsoon rainfall for both Shillong and Agartala stations. In the total annual rainfall, the share of south-west (SW) monsoon, north-east (NE) monsoon, winter season and summer season rainfall was observed 64.60%, 13.22%, 1.40% and 20.80%, respectively for Shillong station of Meghalaya state. However, the contribution of SW monsoon, NE monsoon, winter season and summer season rainfall in the total annual rainfall was 59.59%, 9.55%, 1.14% and 29.72%, respectively for Agartala station of Tripura state. Non-significant increasing trends of rainfall was observed by 4.54 mm/year, 2.80 mm/year and 2.54 mm/year for annual, SW monsoon, and summer season, whereas, non-significant decreasing trends in rainfall for NE monsoon and winter season was observed with a magnitude of 1.83 mm/year and 1.63 mm/year for Shillong, Meghalaya during 1992 to 2017. Results also revealed that rainfall increased by 1.07 mm/year and 0.18 mm/year in SW monsoon and winter season whereas, rainfall decreased by 7.64 mm/year, 2.58 mm/year and 1.29 mm/year during annual, NE monsoon and summer season non-significantly during 1995 to 2019 in case of Agartala. The findings of present study will be useful for water management and crop planning in hill agriculture of Meghalaya and Tripura state of India.

scholarly journals Long Term Homogeneity, Trend and Change-Point Analysis of Rainfall in the Arid District of Ananthapuramu, Andhra Pradesh State, India

2019 ◽  
Author(s):  
Sandeep Kumar Patakamuri ◽  
Krishnaveni Muthiah ◽  
Venkataramana Sridhar
Keyword(s):  
Time Series ◽  
Serial Correlation ◽  
Andhra Pradesh ◽  
Water Resource Management ◽  
Statistical Tests ◽  
Monsoon Season ◽  
Rainfall Data ◽  
Change Points ◽  
South West Monsoon ◽  
Independent Series

Daily rainfall data was collected for the arid district of Ananthapuramu, Andhra Pradesh state, India from 1981 to 2016 at the sub-district level and aggregated to monthly, annual and seasonal rainfall totals and the number of rainy days. The objective of this study is to evaluate the homogeneity, trend, and trend change points in the rainfall data. After quality checks and homogeneity analysis, a total of 27 rain gauge locations were considered for trend analysis. A serial correlation test was applied to all the time series to identify serially independent series. Non-Parametric Mann-Kendall test and Spearman’s rank correlation tests were applied to serially independent series. The magnitude of the trend was calculated using Sen’s slope method. For the data influenced by serial correlation, various modified versions of Mann-Kendall tests (Pre-Whitening, Trend Free Pre-Whitening, Bias Corrected Pre-Whitening and two variants of Variance Correction Approaches) were applied. A significant increasing summer rainfall trend is observed in 6 out of 27 stations. Significant decreasing trends are observed at two stations in the south-west monsoon season and at two stations in the north-east monsoon season. To identify the trend change-points in the time series, distribution-free Cumulative SUM test and sequential Mann-Kendall tests were applied. Two open-source library packages were developed in R language namely, ‘modifiedmk’ and ‘trendchange’ to implement the statistical tests mentioned in this paper. The study will benefit water resource management, drought mitigation, socio-economic development and sustainable agricultural planning in the region.

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