Heavy Rainfall Episodes Research Articles

Impact of Western Ghats orography on the simulation of extreme precipitation over Kerala, India during 14–17 August 2018

The state of Kerala, located in southwest peninsular India, has experienced a series of extremely heavy rainfall events in the past few years, resulting in severe flooding and landslides. Among these events, an extremely heavy rainfall episode (50 to 480 mm/day) occurred during 14–17 August 2018 had led to devastating floods along the southwest coast of India. In this study, we have chosen this event as a case study to analyze the role of orography, using a high-resolution (1-km) cloud-resolving WRF model configuration. We conducted four numerical sensitivity experiments to examine the impact of different topographic configurations, ranging from no-mountain to plateau, moderate, and steep mountain terrains, on the simulation of the extreme rainfall event. The results of the mountain sensitivity experiments indicate that as mountain height increases, simulated low-level wind decelerates quickly. This flow blocking is also manifested in parameters such as reduced upper-air wind intensity, increased dynamical convergence, and increase of vertical velocities at the Western Ghat (WG) mountain barriers, which lead to the variations in moist instability and cloud microphysical processes influencing the horizontal and vertical distribution of solid-phase hydrometeors. Furthermore, the results also show that a reduction in the orography of the WGs decreases the vertical extension of low-level jet winds to upper levels, weakens the tropical easterly flow, and decreases the wind shears between the lower and upper troposphere. In addition, the results suggest that large-scale variations in mountain orography in numerical simulations can affect the simulated magnitude and direction of moisture transport, which may have played a role in determining the magnitude and distribution of simulated rainfall over Kerala.

Qualitative Evaluation of the High Resolution Satellite Precipitation Products with Dense Surface Rain Gauge Observations in Odisha Over a Time Period

The study aims to the Hydro-Estimator Method (HEM) has been used as the noble approach for analysing the heavy rainfall episodes over entire Odisha using the INSAT-3D satellite- derived rainfall estimates. The findings demonstrate that, in terms of the frequency of rainfall occurrences, INSAT-3D satellite rainfall products clearly illustrated both the spatial and temporal variability in rainfall pattern of Odisha. The performance statistics with IMERG and daily merged satellite retrieved rainfall show that both the dataset corelated well with the HEM with a small deviation. For heavy rainfall events, HEM shows good skill and correlation in detecting heavy rainfall with an accuracy of 20 mm and good pattern matching with actual rainfall. Entire Odisha is considered as study area, which is located in the eastern part of India. It comprises of 30 districts and of 314 blocks spreading over an area of 155707 km2. The state has 30 districts, which are further divided into 314 revenue blocks. The rainfall data (1 year; 2016) for all the blocks of Odisha has been obtained from Special Relief Commissioner (SRC), Government of Odisha and subjected to further analysis process. The satellite derived rainfall estimates viz., HEM, were evaluated with rain gauge based gridded data viz., IMD-GRIDDED Dataset for the year 2016 over the Odisha region at the summer monsoon period. The satellite derived rainfall estimates HE have exhibited some good results with the IMD-GRIDDED Dataset its average R2 on a daily basis for different blocks is 0.34 and on a monthly basis it is 0.44. RMSE has also been determined to different block for JJAS month. The average RMSE on daily basis is 17.7 and on monthly basis is 94.6 as shown in bias maps.

Impacts of Water and Stress Transfers from Ground Surface on the Shallow Earthquake of 11 November 2019 at Le Teil (France)

The 4.9 Mw earthquake of 11 November 2019 at Le Teil (France) occurred at a very shallow depth (about 1 km), inducing the surface rupture of La Rouvière fault. The question was raised shortly after about the potential impact of a nearby surface quarry. Thanks to satellite differential interferometry, here, we revealed the existence of a secondary surface rupture of the quasi-parallel Bayne Rocherenard fault. A newly processed seismic cross-section allowed us to shape the three-dimensional geometry of the local three-fault system. Assuming that the earthquake was triggered by the impact of meteoric water recharge, our numerical simulations show that the hydraulic pressure gradient at depth was at a maximum during the period of 2010–2019, just before the seismic event. The estimated overpressure at the intersection of the two faults, which is the most probable place of the hypocenter, was close to 1 MPa. This hydraulic effect is about two and a half times larger than the cumulative effect of mechanical stress release due to the mass removal from the surface quarry over the two past centuries. This work suggests a rapid hydraulic triggering mechanism on a network of faults at a shallow depth after a heavy rainfall episode.

Diatom responses to warming, heavy rains and human impact in a Mediterranean lake since the preindustrial period

In the Mediterranean region, annual mean air temperature will continue to increase during the 21st century, while seasonal precipitation is expected to decrease and extreme events to be more frequent. Human-induced climate change will severely impact aquatic ecosystems. A subdecadal stratigraphic diatom record of Lake Montcortès (central Pyrenees) was investigated, focusing on the potential responses of diatoms to anthropogenic warming and catchment alteration. The study includes the end of the Little Ice Age (LIA), the transition to the industrial and postindustrial eras, and the recent global warming and its current acceleration. Sediment samples were treated and diatoms taxonomically identified. Relationships between diatom taxa abundances and climatic (temperature and precipitation) and environmental (land use, soil erosion, and eutrophication) variables were investigated using multivariate statistical methods. The results indicate that, from ca. 1716 to 1971 CE, the diatom community was dominated by Cyclotella cyclopuncta and showed small perturbations, despite the pressure of important stressors such as strong cooling episodes, droughts and an intense use of the lake for hemp retting during the 18th and 19th centuries. However, during the 20th century, other centric species gained relevance, and from the 1970s on, Cyclotella ocellata competed with C. cyclopuncta for dominance. These changes coincided with pulse-like disturbances in the form of extreme rainfall events along with the gradual 20th century increase in global temperature. These perturbations affected the planktonic diatom community and led to instability dynamics. The benthic diatom community did not reflect any comparable shifts under the effect of the same climatic and environmental variables. Because heavy rainfall episodes are likely to intensify with current climate change in the Mediterranean region, their importance as stressors of planktonic primary producers should be taken into account as potential disrupters of biogeochemical cycles and trophic networks of lakes and ponds.

Comparative analysis of Sub division wise rainfall INSAT-3D vs Ground based observations

Rainfall monitoring during south west monsoon season both are very important ad crucial activity. It is important mainly because it is a boon for agriculture, a mirror for future for both social and economic activities and crucial for its measurements (ground as well as remote). In this current works authors made an attempt to know the performance of recently Space Application Centre (SAC), ISRO developed INSAT-3D improved rainfall algorithms (Hydro Estimator and corrected IMSARA) with actual ground based rainfall data by calculating the bias (Actual –Satellite) for each sub-division. The analysis is done for the southwest monsoon season -2021 in by calculating weekly, monthly and seasonal bias for each subdivisions of Indian domain. It is seen that both the algorithms behave similar fashion (both show increase or decrease, simultaneously) with actual data and mostly satellite overestimate with actual data ranges from ~ 20-40 mm. In some subdivisions bias reached within the range 40 -70 mm (except Konkan & Goa ). Almost 40 % of the subdivisions have bias within 0 to 20 mm range, however the variation on weekly, monthly or seasonal differs subdivision and magnitude-wise. Overall, both the algorithms captures and performance well the trends in weekly, monthly and seasonal accumulated rainfall values. Corrected IMSRA (IMC) algorithm perform slightly better (15-20 %) except heavy rainfall episodes during the monsoon season -2021. In both the heavy and very heavy rainfall cases Hydro Estimators pick up well and performs better (~ 10 -12 %) than IMC algorithm especially over orographic areas. In extremely heavy rainfall cases both the algorithms behave in the same manner and captures the events although it is differing magnitude wise. Seasonal analysis of monsoon 2021 rainfall shows that 8 subdivisions have negative biases in the range of 50-60 mm) and 24 subdivisions have negative biases in the range of 0-20 mm, except Konkan Goa, Coastal Karnataka & A & N Islands have positive biases. Therefore, there is need to strengthen the actual observation rainfall measuring network and re-examine the performance of algorithms with larger data sets so that current algorithms retuned as per changing scenario.

Synoptic Features of August Heavy Rainfall Episodes Accompanied By a Quasi-Stationary Front Over the Korean Peninsula and Its Relationship With the Western Pacific Subtropical High

In this study, we investigated the synoptic features of the August 26–27, 2018 heavy rainfall episode, which was accompanied by a quasi-stationary front over the Korean peninsula, as well as its relationship with the climatological characteristics of the Western Pacific Subtropical High (WPSH), using reanalysis and observational data. Through a case study, we analyzed the synoptic environment and frontal structure of the heavy rainfall event by comparing it with a heavy rainfall event associated with a quasi-stationary front that occurred on June 26–27, 2018 (during the Changma period). The case study indicates that the environment and structure of the quasi-stationary fronts in both events exhibited common characteristic features: an extended WPSH and strong low-level winds along the western or northwestern edge of the WPSH and a northward tilted frontal structure. Although differences in the moisture transport path were observed (southwesterly for the Changma event and southerly for the August event), their contributions to maintaining the quasi-stationary fronts were comparable around the Korean peninsula. We further investigated the climatological characteristics of these two heavy rainfall episodes for a 30 year period (1990–2019). We identified heavy rainfall days similar to those of the case study using pattern correlations of the 850 hPa geopotential height anomaly. The occurrence frequencies for each period indicate that the environmental features of the Changma event can be regarded as the typical heavy rainfall environment during the Changma period, whereas the environmental features of the August event were not typical for heavy rainfall during August. The main difference between similar and different cases to the August event is the expansion of the WPSH. Analysis of the relationship between annual variations in the WPSH indices and the occurrence frequency of heavy rainfall days during each August period also indicates that heavy rainfall with a quasi-stationary front similar to the August event is closely related to WPSH expansion.

The sensitivity of the WRF-4DVar data assimilation system to the control variables: A study on heavy rainfall events over India

The impact of different formulations of background error covariances (BECs) is examined for three heavy rainfall episodes over north India with a regional 4-dimensional variational (4DVar) data assimilation (DA) system. Three BEC formulations are analyzed, in which two of them employ stream function and velocity potential (ψ and χ) and the third one uses zonal and meridional velocity components (v and v) as momentum control variables. The uv-based formulation is completely univariate whereas, the correlations among the control variables are taken into account in the ψχ-based formulations through linear regression relations. Among the two ψχ-based BECs, one uses univariate relation and the other one uses multivariate relations for the moisture field. The multivariate relationship allows for impacting the moisture analysis through the assimilation of temperature or wind observations. Three experiments are carried out for each case with cyclic 4DVar assimilation. The conventional surface and upper-air observations are assimilated in combination with atmospheric motion vectors (AMVs) and ocean surface winds. Free forecast for 48 h is performed from respective final analysis fields for all the experiments. The results indicate that the uv-based analysis fields are closer to the observations. A comparative analysis of the 4DVar experiments with the 3DVar DA system provided a critical insight on the role of the 4DVar DA system on implicitly accounting for the multivariate correlations. The precipitation forecasts confirm the improved performance of the ψχ-based experiment, when multivariate nature of the humidity is incorporated. The time evolution of the intense rainfall episodes over the location of maximum rainfall are relatively well reproduced in the uv-based experiment. The results indicate that the inclusion of multivariate humidity variable in the BEC formulation does have a significant impact on suppressing the excessive overestimation in rainfall intensity.

Observations of heavy short-term rainfall hotspots associated with warm-sector episodes over coastal South China

Coastal South China is frequently exposed to substantial rainfall within fronts-free environments during the presummer rainy season, which recurrently leads to severe disasters due particularly to the heavy short-term rainfall (HSR). The present study is motivated to identify the HSR hotspots over coastal South China through 10 notorious episodes of warm-sector heavy rainfall, with emphasis on the mesoscale features linking with the HSR hotspots. These episodes suggest complex rainfall features in the occurrence frequency and intensity. HSR mainly occurs rather over the coastal areas than the windward piedmont farther inland, and contributes over 80% to the rainfall accumulation in the regions of Yangjiang and Shanwei. Mesoscale topographies in both regions play an important role in the presence of HSR hotspots, but in different ways. Convergence perturbation line related to the inland mountains migrates southward, and enhances the preexisting convection along the coast resulted from the differential surface friction between land and ocean as well as small hills, which is the primary cause for the high frequency of HSR in coastal Yangjiang. While concave terrain drives cyclone-like perturbation, modulating the convection activity prior to the presence of HSR over Shanwei region. A cold dome induced by the previous convection dominates the mesovalley, furthering the subsequently convective enhancement at coastal zone. Collectively, both inland mountains and ocean-to-land friction regulate the mesoscale surface processes by governing the convergent wind perturbations and upscale convective growth, responsible for the HSR hotspots over the low-altitude coastal areas.

Multiscale Processes of Heavy Rainfall over East Asia in Summer 2020: Diurnal Cycle in Response to Synoptic Disturbances

Abstract Multiscale processes from synoptic disturbances to diurnal cycles during the record-breaking heavy rainfall in summer 2020 were examined in this study. The heavy rainfall consisted of eight episodes, each lasting about 5 days, and were associated with two types of synoptic disturbances. The Type-1 episodes featured a northwestward extending western Pacific subtropical high (WPSH), while the Type-2 episodes had approaching midlatitude troughs with southward retreat in the WPSH. Each heavy rainfall episode had 2–3 occurrences of nocturnal low-level jets (NLLJs), in close association with intense rainfall in the early morning. The NLLJs formed partly due to the geostrophic wind by increased pressure gradients under both types of synoptic disturbances. The NLLJs were also driven by the ageostrophic wind that veered to maximum southerlies at late night due to the boundary-layer inertial oscillation. The diurnal amplitudes of low-level southerlies increased remarkably after the onset of Type-1 episodes, in which the extending WPSH provided strong daytime heating from solar radiation. By contrast, the wind diurnal amplitudes were less changed after the onset of Type-2 episodes. The NLLJs strengthened the mesoscale mean ascent, net moisture flux convergence, and convective instability in elevated warm moist air, which led to the upscale growth of MCSs at the northern terminus of the LLJ after midnight. The MCSs-induced Meiyu rainband was re-established in Central China during the Type-1 episodes with the increased diurnal variations. The findings highlight that the regional diurnal cycles of low-level winds in response to synoptic disturbances can strongly regulate mesoscale convective activities in a downscaling manner, and thus produce heavy rainfall.

Patterns of atmospheric circulation in Western Europe linked to heavy rainfall in Germany: preliminary analysis into the 2021 heavy rainfall episode

The July 2021 heavy rainfall episode in parts of Western Europe caused devastating floods, specifically in Germany. This study examines circulation types (CTs) linked to extreme precipitation in Germany. It was investigated if the classified CTs can highlight the anomaly in synoptic patterns that contributed to the unusual July 2021 heavy rainfall in Germany. The North Atlantic Oscillation was found to be the major climatic mode related to the seasonal and inter-annual variations of most of the classified CTs. On average, wet (dry) conditions in large parts of Germany can be linked to westerly (northerly) moisture fluxes. During spring and summer seasons, the mid-latitude cyclone when located over the North Sea disrupts onshore moisture transport from the North Atlantic Ocean by westerlies driven by the North Atlantic subtropical anticyclone. The CT found to have the highest probability of being associated with above-average rainfall in large part of Germany features (i) enhancement and northward track of the cyclonic system over the Mediterranean; (ii) northward track of the North Atlantic anticyclone, further displacing poleward, the mid-latitude cyclone over the North Sea, enabling band of westerly moisture fluxes to penetrate Germany; (iii) cyclonic system over the Baltic Sea coupled with northeast fluxes of moisture to Germany; (iv) and unstable atmospheric conditions over Germany. In 2021, a spike was detected in the amplitude and frequency of occurrence of the aforementioned wet CT suggesting that in addition to the nearly stationary cut-off low over central Europe, during the July flood episode, anomalies in the CT contributed to the heavy rainfall event.

HEAVY PRECIPITATION OCCURRENCE OVER KHERSON WEATHER STATION ACCORDING TO METEOROLOGICAL OBSERVATIONS AND ERA5 REANALYSIS

The paper presents the results of a study of heavy precipitation in the form of rain (> 30 mm/12 h) using data from the meteorological observations and atmospheric reanalysis ERA5 at the Kherson weather station in 2005-2021.Detected that at the Kherson there were only 19 cases of heavy rainfall, which occurred only in the warm half of the year with a maximum recurrence in July. Compared to 1961-1990, the number of heavy rains of 2005-2021 increased in July and June, and decreased in August.Determined that most of the real cases of increased precipitation in Kherson are in good agreement with the results of the ERA5 reanalysis, but in almost a third of the simulation episodes did not show heavy precipitation at the Kherson coordinates or their center was shifted.Heavy rains in Kherson were formed in a field of low atmospheric pressure, with a weak northwest wind and accompanied by thunderstorms.Clarified that most episodes of heavy rainfall in Kherson in 2005-2021 are associated with the movement of southern cyclones, others formed on the southern periphery of the anticyclone in the southwestern direction of the jet stream in the troposphere.

The Results of Applying Different Methodologies to 10 Years of Quantitative Precipitation Estimation in Catalonia Using Weather Radar

The single polarization C-Band weather radar network of the Meteorological Service of Catalonia covers the entire region (32,000 km2), which allows it to apply a series of corrections that improve preliminary estimations of the rainfall field (hourly and daily). In addition, an automatic re-processing using automatic weather stations helps to incorporate ground-based information. The last process of the quantitative precipitation estimation (QPE) is running the end-product again eight days later, when the data have been reviewed and corrected in the case of detecting anomalies in the radar or gauge data. These corrections are applied operationally, with the fields generated and stored automatically. The QPE fields are generated in the GeoTIFF format, allowing easy use with multiple applications and simplifying processes such as quality control. In this way, the analysis of a 10 year period of GeoTIFF QPE daily data compared with ground rainfall values is introduced. The results help to understand different points regarding the functioning of the network such as the dependance on the type of precipitation and the seasonality. In addition, the description of a heavy rainfall episode (22 October 2019) shows the variations and improvements in the different products. The main conclusions refer to how using GeoTIFF combined with point data (rain gauges), it is possible to ensure simple but effective quality control of an operational radar network.

Role of PBL and Microphysical Parameterizations During WRF Simulated Monsoonal Heavy Rainfall Episodes Over Mumbai

Role of PBL and Microphysical Parameterizations During WRF Simulated Monsoonal Heavy Rainfall Episodes Over Mumbai

Classifying compound coastal storm and heavy rainfall events in the north-western Spanish Mediterranean

Abstract. The north-west (NW) Mediterranean coastal zone is a populous and well-developed area in which the impact of natural hazards like flash floods and coastal storms can result in frequent and significant damages. Although the occurrence and impacts of such hazards have been widely covered, few studies have considered their combined impact on the region, which would result in more damage. Within this context, this study analyses the occurrence and characteristics of compound extreme events of heavy rainfall episodes (as a proxy for flash floods) and coastal storms (using the maximum significant wave height) along the Catalan coast as a paradigm of the NW Mediterranean. Two different types of events are considered: multivariate, in which the two hazards occur at the same location, and spatially compounding, in which they occur within the same limited time window, and their impacts accumulate at distinct and separate locations. The analysis is regionally performed along a coastline extension of about 600 km by considering seven coastal sectors and their corresponding river catchment basins. Once the compound events are analysed, the synoptic atmospheric pressure fields are analysed to determine the prevailing weather conditions that generated them. Finally, a Bayesian network is used to fully characterize these events over the territory. The obtained results show that the NW Mediterranean, represented by the Catalan coast, has a high probability of experiencing compound extreme events. Despite the relatively small size of the study area, there are significant variations in the event characteristics along the territory, with the most frequent type being spatially compound, except in the northernmost sectors where multivariate events dominate. These northern sectors also present the highest correlation in the intensity of both hazards. Three representative synoptic situations have been identified as dominant for the occurrence of these events, with different relative importance levels of the compounding drivers (rainfall and waves) and different distributions of impacts across coastal basins. Overall, results obtained from specific events indicated that heavy rainfall is related to the most significant impacts despite having a larger spatial reach.

IMDAA: High Resolution Satellite-era Reanalysis for the Indian Monsoon Region

AbstractA high resolution regional reanalysis of the Indian Monsoon Data Assimilation and Analysis (IMDAA) project is made available to researchers for deeper understanding of the Indian monsoon and its variability. This 12 km resolution reanalysis covering the satellite-era from 1979 to 2018 using 4D-Var data assimilation method and the UK Met Unified Model is presently the highest resolution atmospheric reanalysis carried out for the Indian monsoon region. Conventional and satellite observations from different sources are used, including Indian surface and upper air observations, of which some were not used in any previous reanalyses. Various aspects of this reanalysis, like quality control and bias correction of observations, data assimilation system, land surface analysis, and verification of reanalysis products, are presented in this paper. Representation of important weather phenomena of each season over India in the IMDAA reanalysis verifies reasonably well against India Meteorological Department (IMD) observations and compares closely with ERA5. Salient features of the Indian summer monsoon are found to be well represented in the IMDAA reanalysis. Characteristics of major semi-permanent summer monsoon features (e.g., Low-level Jet and Tropical Easterly Jet) in IMDAA reanalysis are consistent with ERA5. The IMDAA reanalysis has captured the mean, inter-annual, and intra-seasonal variability of summer monsoon rainfall fairly well. IMDAA produces a slightly cooler winter and a hotter summer than the observations; the reverse for ERA5. IMDAA captured the fine-scale features associated with a notable heavy rainfall episode over complex terrain. In this study, the fine grid spacing nature of IMDAA is compromised due to the lack of comparable resolution observations for verification.

Observing a severe flooding over southern part of India in monsoon season of 2019

Kerala is one of the most flood prone states of India due to its geographical location and topography. In recent decades, the frequency and intensity of flood has significantly increased in Kerala. Floods that occurred in the year 2007, 2009, 2014 and 2018 resulted in heavy damage in the form of lives and properties. This research focuses on exploring a recent flood event of Kerala in July–August 2019 using observations from space. Enhanced convective activities over Kerala were resulted due to movement of a low-pressure system westwards from Bay of Bengal towards coastal Arabian Sea under favourable conditions. Results report that excess cumulative rainfall resulting from multi-day extreme precipitation events due to enhanced convection during July and August resulted in catastrophic flood events over various parts of Kerala. Kannur, Wayanad, Kozhikode and Palakkad districts of north Kerala were affected more as compared to other region. Kannur district received a cumulative rainfall of about 1300 mm from multiple rainy spells during July and August of 2019. Peak rainfall was recorded on August 08, 2019. A peak hourly rainfall of about 60 mm/h was recorded at 1230 UTC on August 08 over Kannur district. These multiple heavy to very heavy rainfall episodes led to severe flooding over Kerala resulting in huge damage. Present research emphasizes on the importance of space-borne satellite remote sensing in monitoring of flood events in order to envisage preparedness and mitigation in flood scenarios.

Proportional Trends of Continuous Rainfall in Indian Summer Monsoon

A comprehensive study on the Indian summer monsoonal rainfall (ISMR) is performed in the light of decadal changes in the continuous rainfall events and the number of rainy days using 68 years (1951–2018) of gridded rain gauge data. Non-parametric Mann–Kendall’s test is applied on total rainfall amount, the number of rainy days, number of continuous rainfall events, and rainfall magnitude to find trends over different climatic zones of India for the two periods, 1951–1984 and 1985–2018. Our results found a decreasing trend for more than 4-days of continuous rainfall events during the recent 34 years (1985–2018) compared to 1951–1984. The rate of increase/decrease in extreme/continuous rainfall events does not follow a similar trend in number of continuous rainfall events and magnitude. Moreover, the rainfall is shifted towards a lesser number of continuous rainfall days with higher magnitudes during 1985–2018. During the crop’s sow season (i.e., the first 45 days from the onset date of Indian monsoon), the total number of rainy days decreased by a half day during the last 34 years. Over the Central and North East regions of India, the number of rainfall days decreased by ~0.1 days/yr and ~0.3 days/yr, respectively, during 1985–2018. Overall, the decreasing trends in continuous rainfall days may escalate water scarcity and lead to lower soil moisture over rain-fed irrigated land. Additionally, an upsurge in heavy rainfall episodes will lead to an unexpected floods. On a daily scale, rainfall correlates with soil moisture and evaporation up to 0.87 over various land cover and land use regions of India. Continuous light-moderate rainfall seems to be a controlling factor for replenishing soil moisture in upper levels. A change in rainfall characteristics may force the monsoon-fed rice cultivation period to adopt changing rainfall patterns.

Flood Hazard Mapping in Rural Area: Case of Ephemeral Watercourses in SidiBoulenouar Zone

The eastern region of Morocco is characterized by an arid to semi-arid climate. It is often confronted with heavy rainfall episodes that can generate floods that can cause adverse human and property damage. This work studies hydrological risk in the SidiBoulenouar area (Oujda province) to model floods and map risk areas. The method used is to determine the watersheds and their watercourses, then to calculate the flows with the mathematical formulas. Topographic data were extracted from a 12.5-m resolution DEM derived from the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer). GDEM (Global DEM). The DEM was used to delimit the hydrographic network with ArcMap software. The use of HEC RAS 1D was necessary to delimit the flooding area. The results of the 1D hydraulic modeling of the centennial flood showed that four ephemeral watercourses landlock the rural area of SidiBoulenouar at the time of the floods.

Spatial-temporal analysis of precipitation characteristics in Artvin, Turkey

The region of Artvin, located in the northeast of Turkey, usually experiences high-intensity precipitation events that occur within a short-time period. Along with other environmental impacts, these events also lead to flash floods in this region. The purpose of this study was to evaluate the changing spatial and temporal characteristics of precipitation on August 24, 2015 and November 11 to 12, 2015 that triggered flash floods and landslides in Artvin. We apply spatiotemporal (ST) kriging as a tool to investigate these ST patterns. The average hourly precipitation data were used, taking episodes of heavy rainfall into account. Our results show that precipitation reached the highest values of 30–50 mm between 8:00 and 9:00 pm in the Hopa district on August 24, 2015. On November 11, 2015, rainfall values reached ≥ 15 mm at 4:00 PM in the Borcka district. During both events occurred on November 12, 2015, it rained for 7 h continuously with precipitation values ranging between 5 and 10 mm. The duration of the precipitation lasted for 8 h. In addition, flood events also occurred in the districts of Arhavi and Murgul. This highlights that these districts are vulnerable in the Artvin region and paves the way for decision-makers to implement measures against flash floods in these at-risk districts. In conclusion, the analysis of spatiotemporal characteristics of heavy rainfall events represents an indispensable basis to ensure that necessary precautions regarding flash flood events in the city are taken.

GNSS Meteorology for Disastrous Rainfalls in 2017–2019 Summer in SW Japan: A New Approach Utilizing Atmospheric Delay Gradients

We studied disastrous heavy rainfall episodes in 2017-2019 summer in SW Japan, especially in the Kyushu region using tropospheric delay data from the dense Global Satellite Navigation System network GEONET (GNSS Earth Observation Network). This region often suffers from extremely heavy rains associated with stationary fronts during summer. In this study, we first analyze behaviors of water vapor on July 6, 2018, using tropospheric parameters obtained from the database at University of Nevada Reno. The data set includes tropospheric delay gradient vectors (G), as well as zenith tropospheric delays, estimated every 5 minutes. At first, we interpolated G to obtain those at grid points and calculated their convergence, similar to the quantity proposed by Shoji (2013) as water vapor concentration index. We obtained zenith wet delay from ZTD by removing zenith hydrostatic delay. The raw ZWD values do not really reflect the wetness of the atmosphere above the GNSS station because they largely depend on the station altitudes. To study the dynamics of water vapor before heavy rains, we estimated ZWD converted to the values at sea-level. In the inversion scheme, we used G at all GEONET stations and ZWD data at low-altitude ( 50 mm/hour) events occurred, i.e., July 5, 2017, July 6, 2018, and August 27, 2019. Next, we performed high time resolution analysis (every 5 minutes) on the days of heavy rain. The results suggest that both WVC and sea-level ZWD go up prior to the onset of the rain, and ZWD decreases rapidly once the heavy rain started.