Statistical Analysis and Stochastic Modelling of Hydrological Extremes

Tabari, Hossein

doi:10.3390/w11091861

Cited by 21 publications

(9 citation statements)

References 67 publications

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“…Our results suggest wetter winters and drier summers for Belgium, consistent with the results obtained from the CMIP5 GCMs (Tabari et al, 2015). An increase in the length of extreme dry spells (Breinl et al, 2020) and in aridity conditions (Tabari, 2020) was also found for western Europe. The same methodology is followed to assess the significance of the results after downscaling.…”

Section: Significance Of Climate Change Signalssupporting

confidence: 90%

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Comparison of statistical downscaling methods for climate change impact analysis on precipitation-driven drought

Tabari

Paz

Buekenhout

et al. 2021

Hydrol. Earth Syst. Sci.

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Abstract. General circulation models (GCMs) are the primary tools for evaluating the possible impacts of climate change; however, their results are coarse in temporal and spatial dimensions. In addition, they often show systematic biases compared to observations. Downscaling and bias correction of climate model outputs is thus required for local applications. Apart from the computationally intensive strategy of dynamical downscaling, statistical downscaling offers a relatively straightforward solution by establishing relationships between small- and large-scale variables. This study compares four statistical downscaling methods of bias correction (BC), the change factor of mean (CFM), quantile perturbation (QP) and an event-based weather generator (WG) to assess climate change impact on drought by the end of the 21st century (2071–2100) relative to a baseline period of 1971–2000 for the weather station of Uccle located in Belgium. A set of drought-related aspects is analysed, i.e. dry day frequency, dry spell duration and total precipitation. The downscaling is applied to a 28-member ensemble of Coupled Model Intercomparison Project Phase 6 (CMIP6) GCMs, each forced by four future scenarios of SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5. A 25-member ensemble of CanESM5 GCM is also used to assess the significance of the climate change signals in comparison to the internal variability in the climate. A performance comparison of the downscaling methods reveals that the QP method outperforms the others in reproducing the magnitude and monthly pattern of the observed indicators. While all methods show a good agreement on downscaling total precipitation, their results differ quite largely for the frequency and length of dry spells. Using the downscaling methods, dry day frequency is projected to increase significantly in the summer months, with a relative change of up to 19 % for SSP5–8.5. At the same time, total precipitation is projected to decrease significantly by up to 33 % in these months. Total precipitation also significantly increases in winter, as it is driven by a significant intensification of extreme precipitation rather than a dry day frequency change. Lastly, extreme dry spells are projected to increase in length by up to 9 %.

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Section: Significance Of Climate Change Signalssupporting

confidence: 90%

“…convective precipitation). These processes are therefore simplified by means of parameterisation, leading to significant bias and uncertainty in the model (Tabari, 2019). In order to work with these results on finer scales, which is usually required for hydrological impact studies, a downscaling approach can be applied.…”

Section: Introductionmentioning

confidence: 99%

Comparison of statistical downscaling methods for climate change impact analysis on precipitation-driven drought

Tabari

Paz

Buekenhout

et al. 2021

Hydrol. Earth Syst. Sci.

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“…Mann-Kendall test. The Mann-Kendall statistical test has been frequently utilized to quantify the significance of trends in hydro-meteorological time series (Tabari, 2019;Silva et al, 2015;Duhan and Pandey 2013). The Mann-Kendall (Mann 1945;Kendall 1957) is calculated as:…”

Section: 25mentioning

confidence: 99%

Lake water volume calculation using time series LANDSAT satellite data: a geospatial analysis of Deepor Beel Lake, Guwahati

Ahmed

Shahfahad

Baig

et al. 2021

FEBE

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PurposeDeepor Beel is one of the Ramsar Site and a wetland of great biodiversity, situated in the south-western part of Guwahati, Assam. With urban development at its forefront city of Guwahati, Deepor Beel is under constant threat. The study aims to calculate the lake water volume from the water surface area and the underwater terrain data using a triangulated irregular network (TIN) volume model.Design/methodology/approachThe lake water surface boundaries for each year were combined with field-observed water level data to generate a description of the underwater terrain. Time series LANDSAT images of 2001, 2011 and 2019 were used to extract the modified normalized difference water index (MNDWI) in GIS domain.FindingsThe MNDWI was 0.462 in 2001 which reduced to 0.240 in 2019. This shows that the lake water storage capacity shrank in the last 2 decades. This leads to a major problem, i.e. the storage capacity of the lake has been declining gradually from 20.95 million m3 in 2001 to 16.73 million m3 in 2011 and further declined to 15.35 million m3 in 2019. The fast decline in lake water volume is a serious concern in the age of rapid urbanization of big cities like Guwahati.Originality/valueNone of the studies have been done previously to analyze the decline in the volume of Deepor Beel lake. Therefore, this study will provide useful insights in the water resource management and the conservation of Deepor Beel lake.

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“…To this end, various statistical methods have been developed and used over time. The classical methods, however, rely on many assumptions on the time series to be examined such as normality, temporal and special independency and the temporal constancy of the data distribution [14]. The Mann-Kendall (MK) test is well-known to be non-parametric and therefore not affected by the non-normality of data [15,16] and also because of its low sensitivity to abrupt breaks in inhomogeneous series [17].…”

Section: Introductionmentioning

confidence: 99%

Combined Use of Graphical and Statistical Approaches for Analyzing Historical Precipitation Changes in the Black Sea Region of Turkey

Cengiz

Tabari

Onyutha

et al. 2020

Water

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Many statistical methods have been developed and used over time to analyze historical changes in hydrological time series, given the socioeconomic consequences of the changes in the water cycle components. The classical statistical methods, however, rely on many assumptions on the time series to be examined such as the normality, temporal and spatial independency and the constancy of the data distribution over time. When the assumptions are not fulfilled by the data, test results are not reliable. One way to relax these cumbersome assumptions and credibilize the results of statistical approaches is to make a combined use of graphical and statistical methods. To this end, two graphical methods of the refined cumulative sum of the difference between exceedance and non-exceedance counts of data points (CSD) and innovative trend analyses (ITA)-change boxes alongside the classical statistical Mann–Kendall (MK) method are used to analyze historical precipitation changes at 16 stations during 1960–2015 in the Black Sea region of Turkey. The results show a good match between the results of the graphical and statistical methods. The graphical CSD and ITA methods, however, are able to identify the hidden trends in the precipitation time series that cannot be detected using the statistical MK method.

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Statistical Analysis and Stochastic Modelling of Hydrological Extremes

Cited by 21 publications

References 67 publications

Comparison of statistical downscaling methods for climate change impact analysis on precipitation-driven drought

Comparison of statistical downscaling methods for climate change impact analysis on precipitation-driven drought

Lake water volume calculation using time series LANDSAT satellite data: a geospatial analysis of Deepor Beel Lake, Guwahati

Combined Use of Graphical and Statistical Approaches for Analyzing Historical Precipitation Changes in the Black Sea Region of Turkey

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