scholarly journals An Enhanced Innovative Triangular Trend Analysis of Rainfall Based on a Spectral Approach

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 727
Author(s):  
Bilel Zerouali ◽  
Nadhir Al-Ansari ◽  
Mohamed Chettih ◽  
Mesbah Mohamed ◽  
Zaki Abda ◽  
...  
Keyword(s):  
Trend Analysis ◽  
Rainfall Variability ◽  
Extreme Rainfall ◽  
Discrete Wavelet ◽  
Rainfall Time Series ◽  
Extreme Rainfall Event ◽  
Good Efficiency ◽  
High Rainfall ◽  
Trend Identification ◽  
Annual Scale

The world is currently witnessing high rainfall variability at the spatiotemporal level. In this paper, data from three representative rain gauges in northern Algeria, from 1920 to 2011, at an annual scale, were used to assess a relatively new hybrid method, which combines the innovative triangular trend analysis (ITTA) with the orthogonal discrete wavelet transform (DWT) for partial trend identification. The analysis revealed that the period from 1950 to 1975 transported the wettest periods, followed by a long-term dry period beginning in 1973. The analysis also revealed a rainfall increase during the latter decade. The combined method (ITTA–DWT) showed a good efficiency for extreme rainfall event detection. In addition, the analysis indicated the inter- to multiannual phenomena that explained the short to medium processes that dominated the high rainfall variability, masking the partial trend components existing in the rainfall time series and making the identification of such trends a challenging task. The results indicate that the approaches—combining ITTA and selected input combination models resulting from the DWT—are auspicious compared to those found using the original rainfall observations. This analysis revealed that the ITTA–DWT method outperformed the ITTA method for partial trend identification, which proved DWT’s efficiency as a coupling method.

scholarly journals Comparison of Different Analyzing Techniques in Identifying Rainfall Trends for Colombo, Sri Lanka

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Anushka Perera ◽  
Thilini Ranasinghe ◽  
Miyuru Gunathilake ◽  
Upaka Rathnayake
Keyword(s):  
Sri Lanka ◽  
Trend Analysis ◽  
Water Distribution ◽  
Graphical Method ◽  
Sustainable Use ◽  
Distribution Networks ◽  
Rainfall Trends ◽  
Slope Estimator ◽  
Trend Identification ◽  
Annual Scale

Identifying rainfall trends in highly urbanized area is extremely important for various planning and implementation activities, including designing, maintaining and controlling of water distribution networks and sewer networks and mitigating flood damages. However, different available methods in trend analysis may produce comparable and contrasting results. Therefore, this paper presents an attempt in comparing some of the trend analysis methods using one of the highly urbanized areas in Sri Lanka, Colombo. Recorded rainfall data for 10 gauging stations for 30 years were tested using the MannKendall test, Sen’s slope estimator, Spearman’s rho test, and innovative graphical method. Results showcased comparable findings among three trend identification methods. Even though the graphical method is easier, it is advised to use it with a proper statistical method due to its identification difficulties when the data scatter has some outliers. Nevertheless, it was found herein that Colombo is under a downward rainfall trend in the month of July where the area receives its major rainfall events. In addition, the area has several upward rainfall trends over the minor seasons and in the annual scale. Therefore, the water management activities in the area have to be revisited for a sustainable use of water resources.

scholarly journals Characterizing past and future trend and frequency of extreme rainfall in urban catchments: a case study

2020 ◽  
Vol 3 (1) ◽  
pp. 288-305
Author(s):  
Philip Mzava ◽  
Patrick Valimba ◽  
Joel Nobert
Keyword(s):  
Trend Analysis ◽  
Rainfall Variability ◽  
Extreme Rainfall ◽  
Dar Es Salaam ◽  
Extreme Rainfall Events ◽  
Maximum Rainfall ◽  
Rainfall Events ◽  
The Past ◽  
The Future ◽  
Urban Catchments

Abstract Urban communities in developing countries are one of the most vulnerable areas to extreme rainfall events. The availability of local information on extreme rainfall is therefore critical for proper planning and management of urban flooding impacts. This study examined the past and future characteristics of extreme rainfall in the urban catchments of Dar es Salaam, Tanzania. Investigation of trends and frequency of annual, seasonal and extreme rainfall was conducted, with the period 1967–2017 taken as the past scenario and 2018–2050 as the future scenario; using data from four key ground-based weather stations and RCM data respectively. Mann–Kendall trend analysis and Sen's slope estimator were used in studying changes in rainfall variability. Frequencies of extreme rainfall events were modeled using the Generalized Pareto model. Overall, the results of trend analysis provided evidence of a significant increase in annual and seasonal maximum rainfall and intensification of extreme rainfall in the future under the RCP4.5 CO2 concentration scenario. It was determined that extreme rainfall will become more frequent in the future, and their intensities were observed to increase approximately between 20 and 25% relative to the past. The findings of this study may help to develop adaptation strategies for urban flood control in Dar es Salaam.

scholarly journals Effects of Climate Variability on Normalized Difference Vegetation Index (NDVI) in the Gojeb River Catchment, Omo-Gibe Basin, Ethiopia

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Melku Dagnachew ◽  
Asfaw Kebede ◽  
Awdenegest Moges ◽  
Adane Abebe
Keyword(s):  
Climate Variability ◽  
Trend Analysis ◽  
Vegetation Dynamics ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Rainfall Variability ◽  
Time Lag ◽  
Rainfall Time Series ◽  
River Catchment ◽  
Vegetation Degradation

Vegetation dynamics have been visibly influenced by climate variability. The Normalized Difference Vegetation Index (NDVI) has been the most commonly used index in vegetation dynamics. The study was conducted to examine the effects of climatic variability (rainfall) on NDVI for the periods 1982–2015 in the Gojeb River Catchment (GRC), Omo-Gibe Basin, Ethiopia. The spatiotemporal trend in NDVI and rainfall time series was assessed using a Theil–Sen (Sen) slope and Mann–Kendall (MK) statistical significance test at a 95% confidence interval. Moreover, the residual trend analysis (RESTREND) method was used to investigate the effect of rainfall and human induction on vegetation degradation. The Sen’s slope trend analysis and MK significant test indicated that the magnitude of annual NDVI and rainfall showed significant decrement and/or increment in various portions of the GRC. The concurrent decrement and/or increment of annual NDVI and rainfall distributions both spatially and temporarily could be attributed to the significant positive correlation of the monthly (RNDVI-RF = 0.189, P≤0.001) and annual (RNDVI-RF = 0.637, P≤0.001) NDVI with rainfall in almost all portions of the catchment. In the GRC, a strongly negative decrement and strong positive increment of NDVI could be derived by human-induced and rainfall variability, respectively. Accordingly, the significant NDVI decrement in the downstream portion and significant increment in the northern portion of the catchment could be attributed to human-induced vegetation degradation and the variability of rainfall, respectively. The dominance of a decreasing trend in the residuals at the pixel level for the NDVI from 1982, 1984, 2000, 2008 to 2012 indicates vegetation degradation. The strong upward trend in the residuals evident from 1983, 1991, 1998 to 2007 was indicative of vegetation improvements. In the GRC, the residuals may be derived from climatic variations (mainly rainfall) and human activities. The time lag between NDVI and climate factors (rainfall) varied mainly from two to three months. In the study catchment, since vegetation degradations are mainly caused by human induction and rainfall variability, integrated and sustainable landscape management and climate-smart agricultural practices could have paramount importance in reversing the degradation processes.

scholarly journals Building hazard maps of extreme daily rainy events from PDF ensemble, via REA method, on Senegal River Basin

2011 ◽  
Vol 15 (11) ◽  
pp. 3605-3615 ◽  
Author(s):  
J. D. Giraldo Osorio ◽  
S. G. García Galiano
Keyword(s):  
Time Series ◽  
River Basin ◽  
Rainfall Variability ◽  
Quantitative Measure ◽  
Extreme Rainfall ◽  
Rainfall Time Series ◽  
Hazard Maps ◽  
Senegal River ◽  
Mitigation And Adaptation ◽  
Senegal River Basin

Abstract. The Sudano-Sahelian zone of West Africa, one of the poorest of the Earth, is characterized by high rainfall variability and rapid population growth. In this region, heavy storm events frequently cause extensive damage. Nonetheless, the projections for change in extreme rainfall values have shown a great divergence between Regional Climate Models (RCM), increasing the forecast uncertainty. Novel methodologies should be applied, taking into account both the variability provided by different RCMs, as well as the non-stationary nature of time series for the building of hazard maps of extreme rainfall events. The present work focuses on the probability density functions (PDFs)-based evaluation and a simple quantitative measure of how well each RCM considered can capture the observed annual maximum daily rainfall (AMDR) series on the Senegal River basin. Since meaningful trends have been detected in historical rainfall time series for the region, non-stationary probabilistic models were used to fit the PDF parameters to the AMDR time series. In the development of PDF ensemble by bootstrapping techniques, Reliability Ensemble Averaging (REA) maps were applied to score the RCMs. The REA factors were computed using a metric to evaluate the agreement between observed -or best estimated- PDFs, and that simulated with each RCM. The assessment of plausible regional trends associated to the return period, from the hazard maps of AMDR, showed a general rise, owing to an increase in the mean and the variability of extreme precipitation. These spatial-temporal distributions could be considered by Organization for the Development of the Senegal River (Organisation pour la mise en valeur du fleuve Sénégal, OMVS), in such a way as to reach a better balance between mitigation and adaptation.

scholarly journals Long-term trend analysis of rainfall using hybrid Discrete Wavelet Transform (DWT) based Mann-Kendall tests in central Gujarat region, India

MAUSAM ◽  
2021 ◽  
Vol 71 (2) ◽  
pp. 209-224
Author(s):  
RAJANI NIRAV V ◽  
TIWARI MUKESH K ◽  
CHINCHORKAR S S
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Trend Analysis ◽  
Time Scales ◽  
Series Data ◽  
Trend Test ◽  
Discrete Wavelet ◽  
Rainfall Time Series

Trend analysis has become one of the most important issues in hydro-meteorological variables study due to climate change and the focus given to it in the recent past from the scientific community. In this study, long-term trends of rainfall are analyzed in eight stations located in semi-arid central Gujarat region, India by considering time series data of 116 years (1901-2016). Discrete wavelet transform (DWT) as a dyadic arrangement of continuous wavelet transformation combined with the widely applied and acknowledged Mann-Kendall (MK) trend analysis method were applied for analysis of trend and dominant periodicities in rainfall time series at monthly, annual and monsoonal time scales. Initially, rainfall time series applied in this study were decomposed using DWT to generate sub-time series at high and low frequencies, before applying the MK trend test. Further, the Sequential Mann-Kendall (SQMK) test was also applied to find out the trend changing points. The result showed that at the monthly annual and monsoon time scales, the trends in rainfall were significantly decreasing in most of the station. The 4-month and 8-month components were found as dominant at the monthly time series and the 2-year and 4-year component were found as dominant at the monsoon time series, whereas the 2-year components were observed as dominant in the annual time scale.

scholarly journals Building hazard maps of extreme daily rainy events from PDF ensemble, via REA method, on Senegal River Basin

2011 ◽  
Vol 8 (2) ◽  
pp. 3817-3839
Author(s):  
J. D. Giraldo ◽  
S. G. García Galiano
Keyword(s):  
Time Series ◽  
River Basin ◽  
Rainfall Variability ◽  
Quantitative Measure ◽  
Extreme Rainfall ◽  
Rainfall Time Series ◽  
Hazard Maps ◽  
Senegal River ◽  
Mitigation And Adaptation ◽  
Senegal River Basin

Abstract. The Sudano-Sahelian zone of West Africa, one of the poorest of the Earth, is characterized by high rainfall variability and rapid population growth. In this region, heavy storm events frequently cause extensive damage. Nonetheless, the projections for change in extreme rainfall values have shown a great divergence between Regional Climate Models (RCM), increasing the forecast uncertainty. Novel methodologies should be applied, taking into account both the variability provided by different RCMs, as well as the non-stationary nature of time series for the building of hazard maps of extreme rainfall events. The present work focuses in the probability density functions (PDFs)-based evaluation and a simple quantitative measure of how well each RCM considered can capture the observed annual maximum daily rainfall (AMDR) series on the Senegal River basin. Since meaningful trends have been detected in historical rainfall time series for the region, non-stationary probabilistic models were used to fit the PDF parameters to the AMDR time series. In the development of PDF ensemble by bootstrapping techniques, Reliability Ensemble Averaging (REA) maps were applied to score the RCMs. The REA factors were computed using a metric to evaluate the agreement between observed -or best estimated- PDFs, and that simulated with each RCM. The assessment of plausible regional trends associated to the return period, from the hazard maps of AMDR, showed a general rise, owing to an increase in the mean and the variability of extreme precipitation. These spatial-temporal distributions could be considered by local stakeholders in such a way as to reach a better balance between mitigation and adaptation.

scholarly journals Rainfall variability and floods occurrence in the city of Bamenda (Northwest of Cameroon)

2017 ◽  
Vol 11 (1) ◽  
pp. 65-82 ◽  
Author(s):  
Saha Frederic ◽  
Tchindjang Mesmin
Keyword(s):  
Rainfall Variability ◽  
Extreme Rainfall ◽  
Annual Rainfall ◽  
Annual Number ◽  
Extreme Rainfall Event ◽  
Average Profile ◽  
Flood Flows ◽  
Annual Distribution ◽  
Subsistence Activities ◽  
The City

Abstract This study is based on analysis of rainfall data from 1951-2010 collected at the climatic station of Bamenda. We also use the results of a questionnaire survey applied to 172 households in at-risk neighborhoods. The inventory of some cases of flooding that occurred in the city of Bamenda was done through focus groups. The appreciation of the socio-economic and demographic environment is based on surveys among Cameroonian Households by the National Institute of Statistics (NIS) and General Census of Population and Housing. Statistical examination revealed that annual rainfall in the city of Bamenda experienced a break in 1958. This break buckled the wettest decade of the series. After three decades of worsening, rainfall is experiencing rising since early 1990. The average profile of the annual distribution of rainfall shows a concentration of over 53% in 03 months (July, August and September). During these three months, the rivers of the city know their flood flows and populations in the valleys are affected. The analysis of the annual number of rainy days shows a downward trend and an increase of extreme rainfall event frequency (≥50mm in 24h). It is also apparent that more and more years are experiencing erratic distribution of their precipitation. Then, the perception of people is significantly reduced. Subsistence activities are also affected and development is facing new subtleties. In conclusion, the rainfall experienced strong variability in the city of Bamenda. This situation reinforces the risk of flooding by increasing flood water and increasing the vulnerability of populations.

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