Runoff regime after heavy rainfall events in view of changing climate in a beech stand at the LTER-CWN site “Klausenleopoldsdorf”

2021 ◽  
Author(s):  
Gollobich Günther ◽  
Gartner Karl ◽  
Riedel Sebastian
Keyword(s):  
Electrical Conductivity ◽  
Water Level ◽  
Time Resolution ◽  
Extreme Events ◽  
Heavy Rainfall ◽  
Research Infrastructure ◽  
Precipitation Event ◽  
Rainfall Events ◽  
Runoff Regime ◽  
Heavy Rainfall Events

<p>The Austrian Research Infrastructure LTER-CWN (Long-Term Ecosystem Research Infrastructure for Carbon, Water and Nitrogen) aims for measuring extreme events in high temporal resolution. Within the framework of this project a measuring weir was installed near Klausen-Leopoldsdorf (Lower Austria) in order to collect high-resolution data of stream-water quantity and quality. The measuring weir is located in the western part of the „Wienerwald“, the north-eastern edge of the Alps, at about 475m a.s.l. Especially in the year 2020 this area showed humid weather conditions with an annual precipitation of 904mm. The observed catchment has an area of about 46 hectares. The dominating soil types in the catchment are Planosoils and Stagnosols. The observations at the weir with a time resolution of 5 minutes started in February 2019. The plot was set up for recordings of carbon (C), nitrogen (N) and water fluxes theparameters TOC-N, DOC-N, NO<sub>3,</sub> water level, water temperature, electrical conductivity, turbidity and organic matter values being measured. To answer one of the main research issues - the impact of heavy rainfall events on the runoff regime of a catchment within a dense beech forest in relation to the soil, specific time, the influence of interception and corresponding water level in the observed river - a water level sensor (OTT) and a multifunction spectrolyzer (S:CAN) were installed at the weir. During the measuring period 2019/2020 11 heavy rainfall events (corresponding to more than 20mm daily precipitation sum) were recorded. Due to the small catchment area the average time interval between heavy rainfall events and the corresponding increase of the water level at the measuring weir is about 2 hours. The time and intensity of the rainfall event together with the level of soil moisture before the precipitation event are the key factors for the amount of runoff. Additionally, other measured parameters like the turbidity or the electrical conductivity of the water correspond very well with the amount of runoff. Data with such a high time resolution will help to get a better understanding of extreme events and the consequences of these events in respect to climate change.</p>

scholarly journals Brief communication "Climatic covariates for the frequency analysis of heavy rainfall in the Mediterranean region"

2011 ◽  
Vol 11 (9) ◽  
pp. 2463-2468 ◽  
Author(s):  
Y. Tramblay ◽  
L. Neppel ◽  
J. Carreau
Keyword(s):  
Extreme Events ◽  
Heavy Rainfall ◽  
Climate Models ◽  
Extreme Event ◽  
Generalized Pareto Distribution ◽  
Climatic Conditions ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
The Future ◽  
Heavy Rainfall Events

Abstract. In Mediterranean regions, climate studies indicate for the future a possible increase in the extreme rainfall events occurrence and intensity. To evaluate the future changes in the extreme event distribution, there is a need to provide non-stationary models taking into account the non-stationarity of climate. In this study, several climatic covariates are tested in a non-stationary peaks-over-threshold modeling approach for heavy rainfall events in Southern France. Results indicate that the introduction of climatic covariates could improve the statistical modeling of extreme events. In the case study, the frequency of southern synoptic circulation patterns is found to improve the occurrence process of extreme events modeled via a Poisson distribution, whereas for the magnitude of the events, the air temperature and sea level pressure appear as valid covariates for the Generalized Pareto distribution scale parameter. Covariates describing the humidity fluxes at monthly and seasonal time scales also provide significant model improvements for the occurrence and the magnitude of heavy rainfall events. With such models including climatic covariates, it becomes possible to asses the risk of extreme events given certain climatic conditions at monthly or seasonal timescales. The future changes in the heavy rainfall distribution can also be evaluated using covariates computed by climate models.

scholarly journals Evolution of physicochemical species concentration in streams based on heavy rainfall event data obtained for high-frequency monitoring

RBRH ◽  
2016 ◽  
Vol 21 (4) ◽  
pp. 653-665
Author(s):  
Rubia Girardi ◽  
Adilson Pinheiro ◽  
Edson Torres ◽  
Vander Kaufmann ◽  
Luis Hamilton Pospissil Garbossa
Keyword(s):  
Water Quality ◽  
Water Level ◽  
Atlantic Forest ◽  
High Frequency ◽  
Heavy Rainfall ◽  
Rainfall Event ◽  
Heavy Rainfall Event ◽  
Rainfall Events ◽  
Frequency Monitoring ◽  
Heavy Rainfall Events

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.

scholarly journals Extreme Floods in the Eastern Part of Europe: Large-Scale Drivers and Associated Impacts

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1122
Author(s):  
Monica Ionita ◽  
Viorica Nagavciuc
Keyword(s):  
Water Vapor ◽  
Heavy Rainfall ◽  
Large Scale ◽  
Vapor Transport ◽  
Water Vapor Transport ◽  
Flood Events ◽  
Rainfall Events ◽  
Catchment Areas ◽  
Large Scale Atmospheric Circulation ◽  
Heavy Rainfall Events

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.

scholarly journals Mesoscale Analysis of Heavy Rainfall Episodes from SoWMEX/TiMREX

2012 ◽  
Vol 69 (2) ◽  
pp. 521-537 ◽  
Author(s):  
Christopher A. Davis ◽  
Wen-Chau Lee
Keyword(s):  
Heavy Rainfall ◽  
Southwest Monsoon ◽  
Rainfall Events ◽  
Mesoscale Analysis ◽  
Mesoscale Structure ◽  
Profound Influence ◽  
Moist Condition ◽  
Virtual Temperature ◽  
Convection Initiation ◽  
Heavy Rainfall Events

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.

scholarly journals An Improved Weighting Method of Time-Lag-Ensemble Averaging for Hourly Precipitation Forecasts and Its Application in a Typhoon-Induced Heavy Rainfall Event

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 875
Author(s):  
Li Zhou ◽  
Lin Xu ◽  
Mingcai Lan ◽  
Jingjing Chen
Keyword(s):  
Heavy Rainfall ◽  
Time Lag ◽  
Probability Of Detection ◽  
Precipitation Forecast ◽  
Ensemble Averaging ◽  
Weighting Method ◽  
Prediction Ability ◽  
Rainfall Events ◽  
Hourly Precipitation ◽  
Heavy Rainfall Events

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.

Diverse synoptic weather patterns of warm-season heavy rainfall events in South Korea

2021 ◽  
Author(s):  
Chanil Park ◽  
Seok-Woo Son ◽  
Joowan Kim ◽  
Eun-Chul Chang ◽  
Jung-Hoon Kim ◽  
...  
Keyword(s):  
North Pacific ◽  
Moisture Transport ◽  
Heavy Rainfall ◽  
Eastern China ◽  
Warm Season ◽  
Sea Level Pressure ◽  
Rainfall Events ◽  
Weather Patterns ◽  
Synoptic Weather ◽  
Heavy Rainfall Events

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.

scholarly journals Spatiotemporal patterns of synchronous heavy rainfall events in East Asia during the Baiu season

2021 ◽  
Author(s):  
Frederik Wolf ◽  
Ugur Ozturk ◽  
Kevin Cheung ◽  
Reik V. Donner
Keyword(s):  
System Dynamics ◽  
East Asia ◽  
Heavy Rainfall ◽  
Spatial Organization ◽  
Monsoon Season ◽  
Spatiotemporal Patterns ◽  
Extreme Weather Events ◽  
Earth System ◽  
Rainfall Events ◽  
Heavy Rainfall Events

<p>Investigating the synchrony and interdependency of heavy rainfall occurrences is crucial to understand the underlying physical mechanisms and reduce physical and economic damages by improved forecasting strategies. In this context, studies utilizing functional network representations have recently contributed to significant advances in the understanding and prediction of extreme weather events.</p><p>To thoroughly expand on previous works employing the latter framework to the East Asian Summer Monsoon (EASM) system, we focus here on changes in the spatial organization of synchronous heavy precipitation events across the monsoon season (April to August) by studying the temporal evolution of corresponding network characteristics in terms of a sliding window approach. Specifically, we utilize functional climate networks together with event coincidence analysis for identifying and characterizing synchronous activity from daily rainfall estimates with <span>a spatial resolution of 0.25° </span>between 1998 and 2018. Our results demonstrate that the formation of the Baiu front as a main feature of the EASM is reflected by a double-band structure of synchronous heavy rainfall with two centers north and south of the front. Although the two separated bands are strongly related to either low- or high-level winds which are commonly assumed to be independent, we provide evidence that it is rather their mutual interconnectivity that changes during the different phases of the EASM season in a characteristic way.</p><p>Our findings shed some new light on the interplay between tropical and extratropical factors controlling the EASM intraseasonal evolution, which could potentially help improving future forecasts of the Baiu onset in different regions of East Asia.</p><p> </p><p>Further details: F. Wolf, U. Ozturk, K. Cheung, R.V. Donner: Spatiotemporal patterns of synchronous heavy rainfall events in East Asia during the Baiu season. Earth System Dynamics (in review). Discussion Paper: Earth System Dynamics Discussions, (2020)</p>

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