Redistribution of landslide debris through episodic heavy rainfall events as revealed by multi-period Lidar DEMs

Author(s):  
Yu-Chang Chan ◽  
Yu-Chung Hsieh ◽  
Kou-Jen Chang

<p>Landslides are commonly triggered by heavy rainfall events, but how the loose landslide debris is redistributed through time and how fast the landslide scars are healed by vegetation are not well and precisely documented. Due to recent advances in airborne Lidar-derived digital elevation models, we are able to obtain precise DEMs at different time periods and analyze the redistribution of landslide debris that was once difficult to measure because of relatively minor elevation changes. Three periods of Lidar-derived DEMs were used to analyze a drainage basin that was affected by a heavy rainfall event and generated several landslide deposits and scars within the drainage basin in Taiwan. We selected a single drainage basin to better constrain the source of landslide debris for subsequent observations of landslide debris removal. How the landslide debris is transported and redistributed remains an important topic for understanding debris removal and evaluating post-landslide hazards in downstream areas. The multi-period high-resolution Lidar DEMs give the necessary accuracy to calculate small but significant volume changes that were not easily detectable from previous measuring techniques. Our results show that the landslide debris redistributed most effectively during later large rainfall events, and the landslide materials are minimally redistributed during small rainfall events. Areas without existing landslides were also insignificantly affected in terms of volume change even during large rainfall events. The standard deviation of elevations in the drainage basin is used to show how the topography was changed due to heavy rainfall events within the drainage basin. The concept of surface roughness may be useful to characterize the dissipation of landslide debris because the roughness values become lower during the debris redistribution process. The redistribution of landslide debris over the observed years suggests that the dissipation of landslide debris is mainly affected by by episodic heavy rainfall events and the landslide scars recover relatively quickly for smaller affected landslide regions.</p>

RBRH ◽  
2016 ◽  
Vol 21 (4) ◽  
pp. 653-665
Author(s):  
Rubia Girardi ◽  
Adilson Pinheiro ◽  
Edson Torres ◽  
Vander Kaufmann ◽  
Luis Hamilton Pospissil Garbossa

ABSTRACT Studies carried out over short time intervals assist in understanding the biogeochemical processes occurring relatively fast in natural waters. High frequency monitoring shows a greater variability in the water quality during and immediately after heavy rainfall events. This paper presents an assessment of the surface water quality parameters in the Atlantic Forest biome, caused by heavy rainfall events. The work was developed in two fluviometric sections of the Concordia River watershed, located in the state of Santa Catarina, southern Brazil. The spatial distribution of land use shows the predominance of Atlantic Forest in fluviometric section 1 (FS1) and pasture, forestry, agriculture, and Atlantic Forest in fluviometric section 2 (FS2). In each selected heavy rainfall event, the evolution rainfall height, the water level, and physicochemical parameters of water were analyzed. In all events, the water quality changed due to the heavy rainfall. After the events, an increase in water level and turbidity in both fluviometric sections were detected. In addition, the ammonium ion concentration increased in the river, and the pH value and nitrate concentration decreased. The electrical conductivity presented different behavior in each section. The dissolved oxygen concentration increased in 19 of 27 events. The principal component (PC1) correlated with the turbidity in FS1, and it correlated with level, turbidity, and pH in FS2.


2020 ◽  
Vol 148 (10) ◽  
pp. 4117-4141
Author(s):  
Feng Hsiao ◽  
Yi-Leng Chen ◽  
David Eugene Hitzl

AbstractShort-lived afternoon heavy rainfall events may form over central Oahu during seasonal transition periods (June and October) under favorable large-scale settings. These include a deep moist layer with relatively high precipitable water (>40 mm), blocking pattern in midlatitudes with a northeast–southwest moist tongue from low latitudes ahead of an upper-level trough, absence of a trade wind inversion, and weak (<3 m s−1) low-level winds. Our high-resolution (1.5 km) model results show that immediately before the storm initiation, daytime land surface heating deepens the mixed layer over central Oahu and the top of the mixed layer reaches the lifting condensation level. Meanwhile, the development of onshore/sea-breeze flows, driven by land–sea thermal contrast, brings in moist maritime air over the island interior. Finally, convergence of onshore flows over central Oahu provides the localized lifting required for the release of instability. Based on synoptic and observational analyses, nowcasting with a lead time of 2–3 h ahead of this type of event is possible. In the absence of orographic effects after removing model topography, processes that lead to heavy rainfall are largely unchanged, and subsequent development of heavy showers over central Oahu are still simulated. However, when surface heat and moisture fluxes are turned off, convective cells are not simulated in the area. These results indicate that daytime heating is crucial for the development of this type of heavy rainfall event under favorable large-scale settings.


2021 ◽  
Vol 13 (13) ◽  
pp. 2500
Author(s):  
Douglas Miller ◽  
Malarvizhi Arulraj ◽  
Ralph Ferraro ◽  
Christopher Grassotti ◽  
Bob Kuligowski ◽  
...  

Two heavy rainfall events occurring in early 2020 brought flooding, flash flooding, strong winds, and tornadoes to the southern Appalachian Mountains. Part I of the study examined large-scale atmospheric contributions to the atmospheric river-influenced events and subsequent societal impacts. Contrary to expectations based on previous work in this region, the event having a lower event accumulation and shorter duration resulted in a greater number of triggered landslides and prolonged downstream flooding outside of the mountains. One purpose of this study (Part II) is to examine the local atmospheric conditions contributing to the rather unusual surface response to the shorter duration heavy rainfall event of 12–13 April 2020. A second purpose of this study is to investigate the utility of several spaced-based QPE and vertical atmospheric profile methods in illuminating some of the atmospheric conditions unique to the April event. The embedded mesoscale convective elements in the warm sector of the April event were larger and of longer duration than of the other event in February 2020, leading to sustained periods of convective rain rates. The environment of the April event was convectively unstable, and the resulting available potential energy was sustained by relatively dry airstreams at the 700 hPa level, continuously overriding the moist air stream at low levels attributed to an atmospheric river.


Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1122
Author(s):  
Monica Ionita ◽  
Viorica Nagavciuc

The role of the large-scale atmospheric circulation in producing heavy rainfall events and floods in the eastern part of Europe, with a special focus on the Siret and Prut catchment areas (Romania), is analyzed in this study. Moreover, a detailed analysis of the socio-economic impacts of the most extreme flood events (e.g., July 2008, June–July 2010, and June 2020) is given. Analysis of the largest flood events indicates that the flood peaks have been preceded up to 6 days in advance by intrusions of high Potential Vorticity (PV) anomalies toward the southeastern part of Europe, persistent cut-off lows over the analyzed region, and increased water vapor transport over the catchment areas of Siret and Prut Rivers. The vertically integrated water vapor transport prior to the flood peak exceeds 300 kg m−1 s−1, leading to heavy rainfall events. We also show that the implementation of the Flood Management Plan in Romania had positive results during the 2020 flood event compared with the other flood events, when the authorities took several precaution measurements that mitigated in a better way the socio-economic impact and risks of the flood event. The results presented in this study offer new insights regarding the importance of large-scale atmospheric circulation and water vapor transport as drivers of extreme flooding in the eastern part of Europe and could lead to a better flood forecast and flood risk management.


2012 ◽  
Vol 69 (2) ◽  
pp. 521-537 ◽  
Author(s):  
Christopher A. Davis ◽  
Wen-Chau Lee

Abstract The authors analyze the mesoscale structure accompanying two multiday periods of heavy rainfall during the Southwest Monsoon Experiment and the Terrain-Induced Mesoscale Rainfall Experiment conducted over and near Taiwan during May and June 2008. Each period is about 5–6 days long with episodic heavy rainfall events within. These events are shown to correspond primarily to periods when well-defined frontal boundaries are established near the coast. The boundaries are typically 1 km deep or less and feature contrasts of virtual temperature of only 2°–3°C. Yet, owing to the extremely moist condition of the upstream conditionally unstable air, these boundaries appear to exert a profound influence on convection initiation or intensification near the coast. Furthermore, the boundaries, once established, are long lived, possibly reinforced through cool downdrafts and prolonged by the absence of diurnal heating over land in generally cloudy conditions. These boundaries are linked phenomenologically with coastal fronts that occur at higher latitudes.


Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 875
Author(s):  
Li Zhou ◽  
Lin Xu ◽  
Mingcai Lan ◽  
Jingjing Chen

Heavy rainfall events often cause great societal and economic impacts. The prediction ability of traditional extrapolation techniques decreases rapidly with the increase in the lead time. Moreover, deficiencies of high-resolution numerical models and high-frequency data assimilation will increase the prediction uncertainty. To address these shortcomings, based on the hourly precipitation prediction of Global/Regional Assimilation and Prediction System-Cycle of Hourly Assimilation and Forecast (GRAPES-CHAF) and Shanghai Meteorological Service-WRF ADAS Rapid Refresh System (SMS-WARR), we present an improved weighting method of time-lag-ensemble averaging for hourly precipitation forecast which gives more weight to heavy rainfall and can quickly select the optimal ensemble members for forecasting. In addition, by using the cross-magnitude weight (CMW) method, mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (CC), the verification results of hourly precipitation forecast for next six hours in Hunan Province during the 2019 typhoon Bailu case and heavy rainfall events from April to September in 2020 show that the revised forecast method can more accurately capture the characteristics of the hourly short-range precipitation forecast and improve the forecast accuracy and the probability of detection of heavy rainfall.


Author(s):  
Chanil Park ◽  
Seok-Woo Son ◽  
Joowan Kim ◽  
Eun-Chul Chang ◽  
Jung-Hoon Kim ◽  
...  

AbstractThis study identifies diverse synoptic weather patterns of warm-season heavy rainfall events (HREs) in South Korea. The HREs not directly connected to tropical cyclones (TCs) (81.1%) are typically associated with a midlatitude cyclone from eastern China, the expanded North Pacific high and strong southwesterly moisture transport in between. They are frequent both in the first (early summer) and second rainy periods (late summer) with impacts on the south coast and west of the mountainous region. In contrast, the HREs resulting from TCs (18.9%) are caused by the synergetic interaction between the TC and meandering midlatitude flow, especially in the second rainy period. The strong south-southeasterly moisture transport makes the southern and eastern coastal regions prone to the TC-driven HREs. By applying a self-organizing map algorithm to the non-TC HREs, their surface weather patterns are further classified into six clusters. Clusters 1 and 3 exhibit frontal boundary between the low and high with differing relative strengths. Clusters 2 and 5 feature an extratropical cyclone migrating from eastern China under different background sea-level pressure patterns. Cluster 4 is characterized by the expanded North Pacific high with no organized negative sea-level pressure anomaly, and cluster 6 displays a development of a moisture pathway between the continental and oceanic highs. Each cluster exhibits a distinct spatio-temporal occurrence distribution. The result provides useful guidance for predicting the HREs by depicting important factors to be differently considered depending on their synoptic categorization.


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