ASSESSMENT OF SEWERAGE NETWORK COLLECTORS AT HEAVY RAINFALL OCCURRENCE IN URBAN CATCHMENT

2020 ◽  
Author(s):  
Reka Wittmanova ◽  
Stefan Stanko ◽  
Ivana Marko ◽  
Marek Sutus
Keyword(s):  
Heavy Rainfall ◽  
Urban Catchment ◽  
Rainfall Occurrence ◽  
Sewerage Network

scholarly journals Cause Analysis on Eastward Movement of Southwest China Vortex and Its Induced Heavy Rainfall in South China

2015 ◽  
Vol 2015 ◽  
pp. 1-22 ◽  
Author(s):  
Yongren Chen ◽  
Yueqing Li ◽  
Tianliang Zhao
Keyword(s):  
South China ◽  
Heavy Rainfall ◽  
Southwest China ◽  
Dominant Role ◽  
Vertical Wind Shear ◽  
Heavy Rain ◽  
Convective Systems ◽  
Rainfall Occurrence ◽  
Positive Vorticity ◽  
Upper Level Jet

The movement of southwest China vortex (SWV) and its heavy rainfall process in South China had been investigated during June 11–14, 2008. The results show that under the steering of upper-level jet (ULJ) and mid-level westerly trough, SWV moved eastward from southern Sichuan Plateau, across eastern Yunnan-Guizhou Plateau to South China, forming an obvious heavy rain belt. SWV developed in the large storm-relative helicity (SRH) environment, as environmental wind field continuously transferred positive vorticity to it to support its development. The thermodynamic structures of distinctive warm (cold) advections in front (rear) of the SWV movement are also important factors for the SWV evolutions with a southwest low-level jet (LLJ) and vertical wind shear. SWV development was associated with the distributions of negative MPV1 (the barotropic item of moist potential vorticity) and positive MPV2 (the baroclinic item of it). The MPV1 and MPV2 played the dominant role in the formation and the evolution of SWV, respectively. The mesoscale convective systems (MCSs) frequently occurred and persisted in water vapor convergence areas causing the severe heavy rainfall. The areas of high moist helicity divergence and heavy rainfall are consistent, and the moist helicity divergence could be a good indicator for heavy rainfall occurrence.

scholarly journals Simulation of Severe Local Storm by Mesoscale Model MM5 and Validation Using Data from Different Platforms

2015 ◽  
Vol 2015 ◽  
pp. 1-23 ◽  
Author(s):  
Prosenjit Chatterjee ◽  
Utpal Kumar De ◽  
Devendra Pradhan
Keyword(s):  
Heavy Rainfall ◽  
West Bengal ◽  
Mesoscale Model ◽  
Temperature Drop ◽  
Pressure Rise ◽  
Convective Cloud ◽  
Rainfall Simulation ◽  
Temporal Shift ◽  
Rainfall Occurrence ◽  
Using Data

During premonsoon season (March to May) convective developments in various forms are common phenomena over the Gangetic West Bengal, India. In the present work, simulation of wind squall on three different dates has been attempted with the help of mesoscale model MM5. The combination of various physical schemes in MM5 is taken as that found in a previous work done to simulate severe local storms over the Gangetic West Bengal. In the present study the model successfully simulates wind squall showing pressure rise, wind shift, wind surge, temperature drop, and heavy rainfall, in all cases. Convective cloud development and rainfall simulation by the model has been validated by the corresponding product from Doppler Weather Radar located at Kolkata and TRMM satellite product 3B42 (V6), respectively. It is found that the model is capable of capturing heavy rainfall pattern with up to three-hour time gap existing between simulation and observation of peak rainfall occurrence. In all simulations there is spatial as well as temporal shift from observation.

Extended-Range Forecasts of Areal-Averaged Rainfall over Saudi Arabia

2015 ◽  
Vol 30 (4) ◽  
pp. 1090-1105 ◽  
Author(s):  
Michael K. Tippett ◽  
Mansour Almazroui ◽  
In-Sik Kang
Keyword(s):  
Saudi Arabia ◽  
Heavy Rainfall ◽  
Mean Value ◽  
Forecast Skill ◽  
Global Ocean ◽  
Heavy Rainfall Event ◽  
Wet Season ◽  
Rainfall Occurrence ◽  
Extended Range ◽  
Clear Relation

Abstract The climate of Saudi Arabia is arid–semiarid with infrequent but sometimes intense rainfall, which can cause flooding. Interannual and intraseasonal precipitation variability in the region is related to ENSO and MJO tropical convection. The predictability of these tropical signals gives some expectation of skillful extended-range rainfall forecasts in the region. Here, the extent to which this predictability is realizable in the Climate Forecast System (CFS), version 2, a state-of-the-art coupled global ocean–atmosphere model, is assessed. While there are deficiencies in the forecast climatology likely related to orography and resolution, as well as lead-dependent biases, CFS represents the climatology of the region reasonably well. Forecasts of the areal average of rainfall over Saudi Arabia show that the CFS captures some features of a spring 2013 heavy rainfall event up to 10 days in advance and a transition from dry to wet conditions up to 20 days in advance. Analysis of a 12-yr (1999–2010) reforecast dataset shows that the CFS can skillfully predict the rainfall amount, the number of days exceeding a threshold, and the probability of heavy rainfall occurrence for forecast windows ranging from 1 to 30 days. While the probability forecasts show good discrimination, they are overconfident. Logistic regression based on the ensemble mean value improves forecast skill and reliability. Forecast probabilities have a clear relation with the MJO phase in the wet season, providing a physical basis for the observed forecast skill.

scholarly journals Using Weather Pattern Recognition to Classify and Predict Summertime Heavy Rainfall Occurrence over the Upper Nan River Basin, Northwestern Thailand

2019 ◽  
Vol 34 (2) ◽  
pp. 345-360 ◽  
Author(s):  
Dzung Nguyen-Le ◽  
Tomohito J. Yamada
Keyword(s):  
River Basin ◽  
Summer Monsoon ◽  
Heavy Rainfall ◽  
Japan Meteorological Agency ◽  
False Alarms ◽  
Self Organizing Maps ◽  
Global Spectral Model ◽  
Weather Patterns ◽  
Rainfall Occurrence ◽  
Northwestern Thailand

Abstract In this study, self-organizing maps in combination with K-means clustering are used to objectively classify the anomalous weather patterns (WPs) associated with the summertime [May–June (MJ) and July–August–September (JAS)] heavy rainfall days during 1979–2007 over the Upper Nan River basin, northwestern Thailand. The results show that in MJ, intensive rains are mainly brought by the remarkable enhancement of the westerly summer monsoon. Meanwhile, westward-propagating tropical disturbances including tropical cyclones are the primary factors that reproduce heavy rainfall over the Upper Nan in JAS. These results also suggest that the occurrence time of local heavy rainfall is strongly related to the seasonal transition of the summer monsoon over the Indochina Peninsula. The classification results are then implemented with the perfect prognosis and analog method to predict the occurrence (yes/no) of heavy rainfall days over the studied basin in summer 2008–17 using prognostic WPs from the operational Japan Meteorological Agency Global Spectral Model (GSM). In general, the forecast skill of this approach up to 3-day lead times is significantly improved, in which the method not only outperforms GSM with the same forecast ranges, but also its 3-day forecast is better than the 1–2-day forecasts from GSM. However, the false alarms ratio is still high, particularly in JAS. Nevertheless, it is expected that the new approach will provide warning and useful guidance for decision-making by forecasters or end-users engaging in water management and disaster prevention activities.

scholarly journals Prediction of Moderate and Heavy Rainfall in New Zealand Using Data Assimilation and Ensemble

2015 ◽  
Vol 2015 ◽  
pp. 1-14
Author(s):  
Yang Yang ◽  
Phillip Andrews ◽  
Trevor Carey-Smith ◽  
Michael Uddstrom ◽  
Mike Revell
Keyword(s):  
New Zealand ◽  
Data Assimilation ◽  
Heavy Rainfall ◽  
Weather Prediction ◽  
Forecast Accuracy ◽  
Model Verification ◽  
Ensemble Prediction ◽  
Limited Area ◽  
The North ◽  
Rainfall Occurrence

This numerical weather prediction study investigates the effects of data assimilation and ensemble prediction on the forecast accuracy of moderate and heavy rainfall over New Zealand. In order to ascertain the optimal implementation of state-of-the-art 3Dvar and 4Dvar data assimilation techniques, 12 different experiments have been conducted for the period from 13 September to 18 October 2010 using the New Zealand limited area model. Verification has shown that an ensemble based on these experiments outperforms all of the individual members using a variety of metrics. In addition, the rainfall occurrence probability derived from the ensemble is a good predictor of heavy rainfall. Mountains significantly affect the performance of this ensemble which provides better forecasts of heavy rainfall over the South Island than over the North Island. Analysis suggests that underestimation of orographic lifting due to the relatively low resolution of the model (~12 km) is a factor leading to this variability in heavy rainfall forecast skill. This study indicates that regional ensemble prediction with a suitably fine model resolution (≤5 km) would be a useful tool for forecasting heavy rainfall over New Zealand.

Present Condition Analysis and Design of Sewer Collector Recovery

2020 ◽  
Vol 15 (3) ◽  
pp. 184-195
Author(s):  
Réka Csicsaiová ◽  
Ivana Marko ◽  
Jaroslav Hrudka ◽  
Ivona Škultétyová ◽  
Štefan Stanko
Keyword(s):  
Catchment Area ◽  
Present Condition ◽  
Urban Catchment ◽  
Analysis And Design ◽  
Current State ◽  
Sewer Network

The aim of the study is to assess the hydraulic capacity of the sewer network and sewer collector recovery in the urban catchment area of Trnava.The analysis focuses on the evaluation of situations with different precipitation frequencies. Elaboration consists of modeling the current state of the assessed sewer collector B and subsequent loading of this collector by several block rainfalls. Based on the results of the analysis, the recovery of the sewer network proposed.

High Resolution Measurements of Pollution Wash-Off from an Asphalt Surface

1992 ◽  
Vol 23 (4) ◽  
pp. 245-256 ◽  
Author(s):  
Å. Spångberg ◽  
J. Niemczynowicz
Keyword(s):  
Water Quality ◽  
High Resolution ◽  
Time Resolution ◽  
Quality Data ◽  
Rainfall Runoff ◽  
Water Quality Data ◽  
Urban Catchment ◽  
Complex Process ◽  
Surface Measurements ◽  
Fine Time

The paper describes a measurement project aiming at delivering water quality data with the very fine time resolution necessary to discover deterministic elements of the complex process of pollution wash-off from an urban surface. Measurements of rainfall, runoff, turbidity, pH, conductivity and temperature with 10 sec time resolution were performed on a simple urban catchment, i.e. a single impermeable 270 m2 surface drained by one inlet. The paper presents data collection and some preliminary results.

Enteric viruses in drinking water supplies

2002 ◽  
Vol 2 (3) ◽  
pp. 17-22
Author(s):  
A.P. Wyn-Jones ◽  
J. Watkins ◽  
C. Francis ◽  
M. Laverick ◽  
J. Sellwood
Keyword(s):  
Drinking Water ◽  
Heavy Rainfall ◽  
Liquid Culture ◽  
Plaque Assay ◽  
Enteric Viruses ◽  
Enteric Virus ◽  
The Other ◽  
Raw Water ◽  
Rt Pcr ◽  
Water Supplies

Two rural spring drinking water supplies were studied for their enteric virus levels. In one, serving about 30 dwellings, the water was chlorinated before distribution; in the other, which served a dairy and six dwellings the water was not treated. Samples of treated (40 l) and untreated (20 l) water were taken under normal and heavy rainfall conditions over a six weeks period and concentrated by adsorption/elution and organic flocculation. Infectious enterovirus in concentrates was detected in liquid culture and enumerated by plaque assay, both in BGM cells, and concentrates were also analysed by RT-PCR. Viruses were found in both raw water supplies. Rural supplies need to be analysed for viruses as well as bacterial and protozoan pathogens if the full microbial hazard is to be determined.

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