Table 2 - uploaded by Thea Turkington
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ERA-Interim variables used in this study, along with abbreviations used. A brief description of each variable is also given.
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Debris flows and flash floods are often preceded by intense, convective rainfall. The establishment of reliable rainfall thresholds is an important component for quantitative hazard and risk assessment, and for the development of an early warning system. Traditional empirical thresholds based on peak intensity, duration and antecedent rainfall can...
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... study area is approximately half of one grid box, so only the grid box containing the study area and those directly beside it are used (nine in total). The variables chosen (Table 2) contain commonly used predictors for statistical downscaling precip- itation from Global Climate Models at multiple atmospheric pressure levels ( Chen et al., 2010;Jeong et al., 2012). In ad- dition, convective available potential energy (CAPE), deep layer shear (DLS), and soil moisture fields are also included. ...
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... positive CAPE values indicate that the air may be unstable and favourable for convection. A brief description of each of the variables is also given in Table 2. Atmospheric indicators at 850 and 700 hPa represent lower tropospheric conditions, while indicators at 500 and 250 hPa represent the upper troposphere. ...
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... is possible that some of the flash events are in the wrong category. Four of the nine synoptic events had no rainfall recorded in at least half of the stations 1-4, which would not Swl Q850 Q700 Q500 T850 T700 T500 T250 Vo850 Vo700 Vo500 D850 D700 D500 DLS U&V Figure 4. The SI value for each pair of atmospheric indicators in Table 2 for local convection events using daily values. ...
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... of the nine synoptic events had no rainfall recorded in at least half of the stations 1-4, which would not Swl Q850 Q700 Q500 T850 T700 T500 T250 Vo850 Vo700 Vo500 D850 D700 D500 DLS U&V Figure 4. The SI value for each pair of atmospheric indicators in Table 2 for local convection events using daily values. Any value that was not significant at p = 0.05 level was given a value of zero. ...
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... any thresholds were unlikely to be as robust as for the local con- vection and weather stations, as there were fewer events to both calibrate and validate the thresholds. Swl Q850 Q700 Q500 T850 T700 T500 T250 Vo850 Vo700 Vo500 D850 D700 D500 DLS U&V 850 U&V 700 U&V 500 All Vo700 Bottom panel: the SI value for each pair of atmospheric indicators for Sr using (daily value and 8-day average). Any value that was not significant at p = 0.10 level was given a value of zero. ...
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Citations
... To the best of our knowledge only Turkington et al. (2014) studied torrential watersheds of the order of ten square kilometers, by developing atmospheric indicators allowing to isolate the situations generating debris flows and flash floods in the Ubaye region (Southern French Alps). Among all these studies, only the study by Caspary (1995) goes back further than the middle 45 of the twentieth century, to 1926, but for watersheds of the order of a thousand square kilometers. ...
... Among all these studies, only the study by Caspary (1995) goes back further than the middle 45 of the twentieth century, to 1926, but for watersheds of the order of a thousand square kilometers. The study by Turkington et al. (2014) is restricted to the period 1979-2010, during which 64 flash flood events were recorded, corresponding to 6-month return periods. As far as we know, no study applied such an approach at torrential scale before the 1950s, and therefore had a sufficiently large sample of hydrological extremes to study long return periods. ...
... Together with the extremeness of the studied events -the torrential events correspond to return periods of order 2-3 years at the scale of the conurbation -, a benefit of our work in comparison to Turkington et al. (2014) is to study the driving atmospheric conditions with respect to the main types of atmospheric circulation. Finally, by comparing two reanalyses with different spa-55 tial resolution, we study whether the atmospheric signature of torrential events is either local (at the scale of the conurbation) or regional (at the scale of the French Alps). ...
In this article we study the atmospheric conditions at the origin of damaging torrential events in the Northern French Alps over the long run, using a database of reported occurrence of damaging torrential flooding in the Grenoble conurbation since 1851. We consider seven atmospheric variables that describe the nature of the air masses involved and the possible triggers of precipitation. Using both 20CRv2c and ERA5 reanalyses, we try to isolate the variables associated with torrential events, by objectively determining which of them differ particularly from the climatology at the dates of torrential events. This analysis is done conditionally on the main types of generating atmospheric circulation derived from Lamb weather classes, namely the North-West, Southeast-Southwest and Barometric Swamp classes. Furthermore, the atmospheric variables are considered over two spatial scales – a local scale (the Grenoble conurbation) and a regional scale (the French Alps), in order to study the spatial variability of the atmospheric signature. The results show that all atmospheric variables are less discriminant for torrential events before 1950 according to 20CRv2c – this is likely more linked to 20CRv2c limitations over the remote past than a consequence of climate change. For the post-1950 period, similar atmospheric signatures are found both at local and regional scales in the North-West and Southeast-Southwest classes and for both reanalyses. In the North-West class – which is the best discriminated – humidity and particularly humidity transport (IVT) plays the greatest role. In the Southeast-Southwest class, instability potential (CAPE) is mostly at play. In the Barometric Swamp class both humidity (PWAT) and instability (CAPE) are discriminant – and even more at the local scale –, showing more mixed situations generating torrential events in this class. In total, depending on the class, torrential events are 4 to 14 times more likely when the respective discriminant variables are extreme (typically above their 0.95-quantile).
... Understanding the temporal occurrence of GH events is essential for hazard assessment, early warning, and disaster risk reduction strategies (van Westen et al., 2008;Ali et al., 2017;Liu et al., 2018;Guzzetti et al., 2020). Temporal information with an accuracy of a few days is needed to understand the close association between precipitation and the occurrence of GH events (Guzzetti et al., 2008(Guzzetti et al., , 2020Turkington et al., 2014;Marc et al., 2018). For site-specific and local-scale investigation, this accurate information on the timing of GH events can be obtained with field-based approaches such as watershed/hillslope monitoring (Guzzetti et al., 2012) or a network of observers (Jacobs et al., 2019;Sekajugo et al., 2022). ...
... In recent GH detection studies, amplitude products are usually preferred over coherence products (Ge et al., 2019;Jung and Yun, 2020;Mondini et al., 2021), since coherence generally yields less accurate results due to lower resolution (Burrows et al., 2019(Burrows et al., , 2020 and a higher number of false positives (Aimaiti et al., 2019;Jung and Yun, 2020). Despite the increasing use of SAR imagery for GH detection (Martinis et al., 2015;Psomiadis, 2016;Twele et al., 2016;Mondini et al., 2019;Burrows et al., 2020;Jung and Yun, 2020;Tzouvaras et al., 2020;Jacquemart and Tiampo, 2021;Handwerger et al., 2022), to date, only the recent study of Burrows et al. (2022) used SAR to refine the timing of GH inventories. Although located in the tropics and showing accurate results, their study was only applied (1) within a relatively densely vegetated landscape, (2) only on landslides, (3) using pre-processed amplitude imagery with Google Earth Engine (GEE) (Gorelick et al., 2017) and (4) with a priori knowledge on the timing of the event (i.e. the year). ...
Landslides and flash floods are geomorphic hazards (GHs) that often co-occur and interact. They generally occur very quickly, leading to catastrophic socioeconomic impacts. Understanding the temporal patterns of occurrence of GH events is essential for hazard assessment, early warning, and disaster risk reduction strategies. However, temporal information is often poorly constrained, especially in frequently cloud-covered tropical regions, where optical-based satellite data are insufficient. Here we present a regionally applicable methodology to accurately estimate GH event timing that requires no prior knowledge of the GH event timing, using synthetic aperture radar (SAR) remote sensing. SAR can penetrate through clouds and therefore provides an ideal tool for constraining GH event timing. We use the open-access Copernicus Sentinel-1 (S1) SAR satellite that provides global coverage, high spatial resolution (∼10–15 m), and a high repeat time (6–12 d) from 2016 to 2020. We investigate the amplitude, detrended amplitude, spatial amplitude correlation, coherence, and detrended coherence time series in their suitability to constrain GH event timing. We apply the methodology on four recent large GH events located in Uganda, Rwanda, Burundi, and the Democratic Republic of the Congo (DRC) containing a total of about 2500 manually mapped landslides and flash flood features located in several contrasting landscape types. The amplitude and detrended amplitude time series in our methodology do not prove to be effective in accurate GH event timing estimation, with estimated timing accuracies ranging from a 13 to 1000 d difference. A clear increase in accuracy is obtained from spatial amplitude correlation (SAC) with estimated timing accuracies ranging from a 1 to 85 d difference. However, the most accurate results are achieved with coherence and detrended coherence with estimated timing accuracies ranging from a 1 to 47 d difference. The amplitude time series reflect the influence of seasonal dynamics, which cause the timing estimations to be further away from the actual GH event occurrence compared to the other data products. Timing estimations are generally closer to the actual GH event occurrence for GH events within homogenous densely vegetated landscape and further for GH events within complex cultivated heterogenous landscapes. We believe that the complexity of the different contrasting landscapes we study is an added value for the transferability of the methodology, and together with the open-access and global coverage of S1 data it has the potential to be widely applicable.
... Satellite rainfall missions, such as Global Precipitation Measurement (GPM)-Integrated Multi-satellitE Retrievals for GPM (IMERG)-, provide 0.5 hourly rainfall products with global coverage and spatial resolution of 0.1 ∘ (∼15 km), thus offering detailed information to support landslide hazard assessment in regions with scarce ground-based rainfall measurements (Guimarães et al. 2017). Alternatively, the recently released hourly ERA5 climate reanalysis has the same spatial resolution with IMERG featuring several meteorological variables, such as precipitation intensity (Maussion et al. 2014;Turkington et al. 2014). Rainfall products with a spatial resolution of ≈10 km potentially improve our ability to link landslides activity to rainfall and aid in early warning (Nikolopoulos et al. 2017), which otherwise requires either a dense gauge network (<10 km resolution), or a ground-based rainfall radar network. ...
Predicting rainfall-induced landslides hinges on the quality of the rainfall product. Satellite rainfall estimates or rainfall reanalyses aid in studying landslide occurrences especially in ungauged areas, or in the absence of ground-based rainfall radars. Quality of these rainfall estimates is critical; hence, they are commonly crosschecked with their ground-based counterparts. Beyond their temporal precision compared to ground-based observations, we investigate whether these rainfall estimates are adequate for hindcasting landslides, which particularly requires accurate representation of spatial variability of rainfall. We developed a logistic regression model to hindcast rainfall-induced landslides in two sites in Japan. The model contains only a few topographic and geologic predictors to leave room for different rainfall products to improve the model as additional predictors. By changing the input rainfall product, we compared GPM IMERG and ERA5 rainfall estimates with ground radar–based rainfall data. Our findings emphasize that there is a lot of room for improvement of spatiotemporal prediction of landslides, as shown by a strong performance increase of the models with the benchmark radar data attaining 95% diagnostic performance accuracy. Yet, this improvement is not met by global rainfall products which still face challenges in reliably capturing spatiotemporal patterns of precipitation events.
... Flash flood forecast is specially a complex issue due to depending on many factors (e.g., meteorological conditions or river characteristics). As illustrated in lots of studies that meteorological contributions to flash flood are significantly important [20][21][22]. The reason for this is that extreme rainfall events potentially leading to pluvial flash floods closely associates to air moisture like dewpoint temperature, relative humidity or precipitable water. ...
In recent years, losses and damages from flash floods have been steadily increasing worldwide as well as in Vietnam, due to physical factors, human activities, especially under a changing climate. This is a hotspot issue which requires immediate response from scientists and policy-makers to monitor and mitigate the negative impacts of flash floods. This study presents a way to reduce losses through increasing the accuracy of real-time flash flood warning systems in Vietnam, a case study developed for Ha Giang province where the topography is relatively complex with severe flash floods observed. The objective of this paper is to generate the real-time flash flood system based on bankfull discharge threshold. To do this, HEC-HMS model is applied to calibrate and validate observer inflow to the reservoir with nine automatic rain gauges installed. More importantly, on the basic of measured discharge at 35 locations from the fieldtrips, an empirical equation constructed is to identify the bankful discharge values. It bases on the relationship between basin characteristics of river length, basin area and bankfull discharge. The results indicate an effective approach to determine bankfull threshold with the established-empirical equation. On the scale of a small basin, it depicts the consistency of flood status and warning time with the reality. Doi: 10.28991/cej-2021-03091687 Full Text: PDF
... The performance of the upper, intermediate and lower thresholds to identify true or false alarms was evaluated using a binary classifier of the rainfall conditions that do or do not lead to flood and flash flood occurrences (Segoni et al. 2014;Turkington et al. 2014;Zhao et al. 2019). A contingency matrix consisting of four components was used for each threshold, including: (1) true positive (TP), when the threshold is exceeded and the hydrological disaster occurs; (2) false negative (FN), when the threshold is not exceeded and the hydrological disaster occurs; (3) false positive (FP), when the threshold is exceeded and the hydrological disaster does not occur; and (4) true negative (TN), when the threshold is not exceeded and the hydrological disaster does not occur. ...
This paper presents an improved method of using threshold of peak rainfall intensity for robust flood/flash flood evaluation and warnings in the state of São Paulo, Brazil. The improvements involve the use of two tolerance levels and the delineating of an intermediate threshold by incorporating an exponential curve that relates rainfall intensity and Antecedent Precipitation Index (API). The application of the tolerance levels presents an average increase of 14% in the Probability of Detection (POD) of flood and flash flood occurrences above the upper threshold. Moreover, a considerable exclusion (63%) of non-occurrences of floods and flash floods in between the two thresholds significantly reduce the number of false alarms. The intermediate threshold using the exponential curves also exhibits improvements for almost all time steps of both hydrological hazards, with the best results found for floods correlating 8-h peak intensity and 8 days API, with POD and Positive Predictive Value (PPV) values equal to 81% and 82%, respectively. This study provides strong indications that the new proposed rainfall threshold-based approach can help reduce the uncertainties in predicting the occurrences of floods and flash floods.
... In agreement with that, Brunetti et al. (2018), after comparing the derivatives of four satellite products with ground rain gauges data for developing landslide rainfall thresholds in Italy, they concluded that radar-based rainfall is outmatched by ground data and underestimates rainfall, especially when it is of high intensity. Turkington et al. (2014) developed empirical thresholds for rainfalltriggered debris flows and flash floods using atmospheric indicators for the Ubaye Valley, France, to conclude that for their case study the atmospheric indicators performed better than the weather station thresholds. ...
Satellite rainfall products for landslide early warning prediction have been spotlighted by several researchers, in the last couple of decades. This study investigates the use of TRMM and ERA-Interim data, for the determination of rainfall thresholds and the prediction of precipitation, respectively, to be used for landslide early warning purposes at the Bogowonto catchment, Central Java, Indonesia. A landslide inventory of 218 landslides for the period of 2003–2016 was compiled, and rainfall data were retrieved for the landslide locations, as given by 6 ground stations, TRMM, and ERA-Interim data. First, rainfall data from the three different sources was compared in terms of correlation and extreme precipitation indices. Second, a procedure for the calculation of rainfall thresholds for landslide occurrence was followed consisting of four steps: i) the TRMM-based rainfall data was reconstructed for selected dates and locations characterized by landslide occurrence and non-occurrence; ii) the antecedent daily rainfall was calculated for 3, 5, 10, 15, 20 and 30 days for the selected dates and locations; iii) two-parameter daily rainfall-antecedent rainfall thresholds were calculated for the aforementioned dates; after analysis of the curves the optimum number of antecedent rainfall days was selected; and (iv) empirical rainfall thresholds for landslide occurrence were determined. The procedure was repeated for the entire landslide dataset, differentiating between forested and built-up areas, and between landslide occurrence in four temporal periods, in relation to the monsoon. The results indicated that TRMM performs well for the detection of very heavy precipitation and can be used to indicate the extreme rainfall events that trigger landslides. On the contrary, as ERA-Interim failed to detect those events, its applicability for LEWS remains limited. The 15-day antecedent rainfall was indicated to mostly affect the landslide occurrence in the area. The rainfall thresholds vary for forested and built-up areas, as well as for the beginning, middle and end of the rainy season.
... For example, Lehmann and Or (2012), using a shallow landslide model, found an important role of the topography and the rainfall conditions. Turkington et al. (2014) showed how intense locally driven convection is the main meteorological trigger for flash occurrence in the French Alps. Camarasa-Belmonte (2016) showed the important role of rainfall intensity and duration in the shape of the hydrograph, with intense rainfall shortening the response time of the basin and large durations increasing the flood peak. ...
On 18 May 2015, a severe rainfall event triggered a flash flood in the municipality of Salgar, located in the northwestern Colombian Andes. This work aims to reconstruct the main hydrological features of the flash flood to better understand the processes modulating the occurrence of the event. Radar quantitative precipitation estimates (QPEs), satellite information, and post-event field visits are used to reconstruct the Salgar flash flood, in an ungauged basin, addressing the relationship among rainfall spatiotemporal structure, soil moisture, and runoff generation during successive rainfall events by using a conceptual modeling framework including landslide and hydraulic submodels. The hydrological model includes virtual tracers to explore the role of runoff and subsurface flow and the relative importance of convective and stratiform precipitation in flash flood generation. Despite potential shortcomings due to the lack of data, the modeling results allow an assessment of the impact of the interactions between runoff, subsurface flow, and convective–stratiform rainfall on the short-term hydrological mechanisms leading to the flash flood event. The overall methodology reproduces the magnitude and timing of the La Liboriana flash flood peak discharge considerably well, as well as the areas of landslide occurrence and flood spots, with limitations due to the spatial resolution of the available digital elevation model. Simulation results indicate that the flash flood and regional landslide features were strongly influenced by the antecedent rainfall, which was associated with a northeasterly stratiform event. The latter recharged the gravitational and capillary storages within the model, moistening the entire basin before the occurrence of the flash flood event and impacting the subsurface–runoff partitioning during the flash flood event. Evidence suggests that the spatial structure of the rainfall is at least as important as the geomorphological features of the basin in regulating the occurrence of flash flood events.
... Rather, this seems to be a problem to which solutions are either scope-, resolutionor data source-dependent. Recent works exploring observed rawinsonde data [55], atmospheric model forecasts [56,57], and reanalysis [15,58] outputs reached different optimal sets of best descriptors. These results make the use of techniques such as sensitivity analysis for feature selection (e.g., [56,57]), which is almost a mandatory step for each activity related to FF forecasting due to the increasing volume of data and candidates. ...
Recent years have witnessed considerable developments in multiple fields with the potential to enhance our capability of forecasting pluvial flash floods, one of the most costly environmental hazards in terms of both property damage and loss of life. This work provides a summary and description of recent advances related to insights on atmospheric conditions that precede extreme rainfall events, to the development of monitoring systems of relevant hydrometeorological parameters, and to the operational adoption of weather and hydrological models towards the prediction of flash floods. With the exponential increase of available data and computational power, most of the efforts are being directed towards the improvement of multi-source data blending and assimilation techniques, as well as assembling approaches for uncertainty estimation. For urban environments, in which the need for high-resolution simulations demands computationally expensive systems, query-based approaches have been explored for the timely retrieval of pre-simulated flood inundation forecasts. Within the concept of the Internet of Things, the extensive deployment of low-cost sensors opens opportunities from the perspective of denser monitoring capabilities. However, different environmental conditions and uneven distribution of data and resources usually leads to the adoption of site-specific solutions for flash flood forecasting in the context of early warning systems.
... Following their suggestions, multiple atmospheric "ingredients" and combinations of variables, including stability indices, have been used to integrate local meteorology with the hydro-geologic conditions at debris source regions (Toreti et al. 2013). Researchers also investigated the temporal and spatial relationship of CG lightning flashes and intense local rainfall with the potential to produce debris flows (Underwood and Schultz 2004;Turkington et al. 2014;Underwood et al. 2016). Following this approach, the present research aims to evaluate the characteristics of the atmosphere related to convection and assess the value of atmospheric processes to predict and/or warn of hydrogeologic hazards such as DF. ...
Debris flow events, generated by surface runoff, occur with great frequency in the Dolomites (Northeastern Italian Alps) during the summer season. Summer thunderstorms, which are common in the region, can quickly generate runoff at the base of rocky cliffs, which then entrains and propagates downstream the underlying unconsolidated material. In the past, the main atmospheric feature considered in evaluating the initiation of debris flow events was rainfall. Observations led to the development of rainfall intensity–duration thresholds for sediment mobilization, which compared incoming severe rainfalls with the potential for triggering debris flows. This study works toward the examination of another characteristic of the atmosphere, the atmospheric electric field. In particular, the behavior of the electric field prior to convective rainfall is investigated as an indicator of rainfall intensities capable of triggering debris flows, in a basin near Cortina d’Ampezzo (Italy). Results suggest that prior to bursts of intense rainfall, the electric field derivative frequency distribution exhibits a recurrent pattern roughly half the time. When it occurs, the amplitude of derivative frequency distribution intersects the zero axis twice before rainfall reaches maximum intensity. A regression model is designed which considers the amplitude maximum and the difference in time between the crossings of the zero axis. The validation of this model suggests a mild relationship between electric field and rainfall intensity in an alpine environment.
... However, establishing the relationship between rainfall and landslides is very complex (Bai et al. 2014). Regional forecasting of rainfall-induced landslides has attracted considerable attention in recent years (Corominas and Moya 1999;Brunetti et al. 2010;Turkington et al. 2014;Vessia et al. 2014;Zhou and Tang 2014). Regional analysis of landslide probability relies strongly on rainfall levels. ...
Rainfall-induced shallow landslides are common in many mountainous countries. Highly concentrated precipitation triggers landslides and debris flows in worldwide. Every year, several shallow slides and debris flows occur in Busan, South Korea during heavy rainfall. To reduce and prevent associated damage, we developed a matrix-based approach of rainfall threshold and landslide susceptibility. This study collects landslide inventories which consist of information of 260 landslide location, 35 landslide event times, and corresponding rainfall intensities and durations. A rainfall threshold warning levels were established using rainfall intensities and durations associated with 35 historical shallow slides, and categorised as null (< 5%), watch (5–20%), attention (20–50%), and alarm (> 50%). We used a back propagation ANN machine-learning algorithm to explore the effects of 14 causative factors on shallow slide distribution. The area under the curve was used to assess accuracy, and accuracy was found to be 86.12%. The derived rainfall threshold warning levels were assigned in rows and the susceptibility classes were used in columns of the matrix. The combined result represents the shallow slide hazards to rainfall threshold warning levels with a varying likelihood to shallow slide initiation. The results aim to raise awareness towards landslide hazards and to support regional decision for the land-use planning.
