Assessment of Rainfall Data for Wastewater Network

Transcription

1 Assessment of Rainfall Data for Wastewater Network Yogesh Mahajan, Prof. Sagar Gawande Department of Civil and Environmental Engineering, Anantrao Pawar College of Engineering & Research Savitribai Phule, Pune University, Pune, India ABSTRACT: The wastewater network model is of very much importance to gain the much more accurate results when analysed through GIS software tools. This can be done for various survey used for the verification purpose for the wastewater network. Generally those surveys are called as short term flow surveys for the respective catchment. In hydraulic modelling rainfall data plays an important role without which is not possible to verify the waste water network model. This papers overviews the requirement of rainfall data through rain gauge stations, checking of rainfall data and its analysis for application of hydraulic models. KEYWORDS: Rainfall data collection, Rainfall data analysis, Implementation of rainfall data for wastewater network Various factors consideration for rainfall data. I. INTRODUCTION The use of models to support analysis of wastewater collection systems and development of engineering options to address existing and future needs can provide tremendous benefits. These benefits may include significant capital and operational savings, and more importantly an assurance that any solutions implemented will achieve the targeted objectives. Understanding the performance of a wastewater collection system, including identification of problems and the associated cause of each problem, involves many complex processes. Dynamic rainfall runoff simulation models are the most effective way to predict the behaviour of sewer collection networks under various external loads and operating conditions. The models account for various hydrologic processes that produce runoff from urban areas and use hydraulic modelling route runoff, external inflows, and water quality constituents through the sewer network and track runoff quantity and quality, flow rate and depth, and water quality. They can also model the hydrologic performance of specific types of low-impact development controls, such as porous pavement, rain gardens, green roofs, street planters, rain barrels, infiltration trenches, and vegetative swales. Their predictive capabilities make these hydrologic and conveyance system hydraulics models powerful tools for evaluating sewer collection system response as well as the effectiveness of various operational and management alternatives designed to meet specific performance goals. To be effective, however, these models require an accurate, continuously updated view of the collection network. This can be accomplished by synthesizing rain gauges, radar rainfall, and other real-time telemetry data with the network models. The resulting models provide continuous real-time insights about a collection networks performance. A constant data stream and predictive modelling capabilities enable operators to quickly assess events as they occur, identify potential problems before they reach a critical level, respond decisively to operational challenges, reduce overflow volumes, and minimize downstream effects. Copyright to IJIRSET DOI: /IJIRSET

2 II. METHODS FOR COLLECTION OF DATA 1) Collection of Rainfall data:- Rainfall data is generally collected by the use of raingauges or by the use of weather radar. Raingauges measure the temporal variation in rainfall at specific locations where the raingauge is sited. Although there are a number of different types of measurement device available, including tipping bucket gauges, piezoelectric sensor plate drop counters, weighing gauges and weather stations, it is the tipping bucket variety that are most commonly utilised. This is due to their generally low cost and reliability. There is number of daily measuring raingauges also available. A typical tipping bucket raingauge is constructed from a plastic cylinder with a funnel at the top that routes rainfall on to two buckets that rotate over a central pivot. The volume of the buckets is generally sized to correspond to a rainfall depth of 0.2mm over the plan area of the funnel. There are two buckets so that as one fills and tips, the second one takes its position and continues to collect rainfall and vice-versa. Data is recorded electronically for the time of each tip, which allows the temporal variance in intensity to be calculated. Individual Site Location The two main requirements for an individual site are that it is not sheltered from the true rainfall pattern by overhanging trees or nearby structures and is secure from vandals. Flat roofs are often chosen as sites either within schools, at police stations or in industrial complexes with one storey buildings. Where such sites are not available alternatives include locked water company owned compounds (such as pumping station sites and sewage treatment plants) or private gardens. Where such sites are used, however, it is important to ensure that the raingauge is not overlooked. Therefore it is recommended that the distance from neighbouring objects should exceed the heights of the neighbouring structures. The raingauge density is driven by the likelihood of significant changes in rainfall across a catchment due to orographic effects, the potential for localised cells of rainfall in convective rainfall, and to limit the potential for large variations in rainfall in adjacent raingauges. If there is variable topography across a modelled catchment, there may be a need for different raingauge densities in parts of the catchment. There may also be a case for increasing the number of raingauges in summer surveys due to the increased potential for convective rainfall. It is good practice to install a minimum of 3 raingauges regardless of the size of catchment, in order to provide 2 gauges for measurements with the third operating as a backup should failure occur at one of the sites. 2) Radar Rainfall data:- The radar sends out a signal and measures the time and magnitude of a return signal from hydrometeors in the atmosphere. Depending on the frequency at which they radiate, weather radars can be of three main types (from lower to higher frequency): S-band, C-band and X- band. Lower frequency radars require larger dishes to achieve a small radar beam width, which ultimately determines the spatial resolution at which rainfall is measured. As such, S-band radars require the largest dishes and are therefore the biggest and most expensive type of weather radar, whereas X-band radars are the smallest and cheapest. Lower frequency radars are more powerful, and hence they can survey larger areas and are less susceptible to attenuation. Consequently lower frequency S-band radars tend to be used in tropical areas prone to very intense precipitation. C-band radars represent a good balance between power, size and cost, and are widely used in Europe. X-band radars tend to be used to monitor small mountainous and urban areas or for portable applications such as sporting events or research. X-band radars attenuate significantly in heavy rainfall. When using radar data for model verification purposes in short term flow surveys, the following issues should be taken into consideration:- As the data comes from one source, if the local radar is down for any reason all data will be lost. Checks should be made on the potential for any planned routine maintenance of the radar station during the period of the flow survey. As mentioned above, the accuracy of radar rainfall estimates may be poor and inconsistent due to the indirect nature of the estimates. The radar data will have been calibrated against raingauges which may be a considerable distance from the catchment being surveyed. As such it is good practice to include some raingauges in the catchment to be used for checking of the radar data, and as a possible back up if the radar data is lost for any reason. Copyright to IJIRSET DOI: /IJIRSET

3 The Rain Gain project has sought to obtain detailed rainfall data at an urban scale, to use these data to analyse and predict urban flooding and to implement the use of rainfall and flood data in urban water management practice to make cities more resilient to local rainfall induced floods. Radar data has been extensively used in meteorology and fluvial hydrology for decades. However it is only recently that it has been used more extensively in urban drainage modelling. The lack of use has been down to concerns about accuracy of data, issues with the cost of obtaining the data, and historically it has been easier to find suitable raingauge sites than is presently the case. III. RESULTS AND DISCUSSION Where rain gauge data or radar data is being utilized, there is a need to assign the relevant rainfall to individual runoff surfaces (sub-catchments) in the model. Where radar data is being utilized, rainfall data is an average over the grid square of the rainfall. Hence assignment of the rainfall will be to those surfaces in the rainfall grid. Where rain gauge data is used, as these are point locations, there has been no averaging of rainfall values. The simplest method to assign rainfall to a runoff surface (sub-catchment) is to use the data from the gauge at closest proximity to the centroid of that sub-catchment. This is normally calculated by using the Thiessen polygon approach, but some software will do this automatically. However this process does not take into account variations in catchment topography, and spatial variation between the gauges. Hence there may be instances where the rainfall at the closest rain gauge to a subcatchment is unlikely to be representative of the rainfall actually falling at that location. In situations like this, then the allocation of rain gauges should be amended. There are a number of interpolation techniques, such as Kriging or inverse distance weighting, which will lead to improved rainfall distribution. These interpolation techniques enable the creation of a grid of rain gauge-based rainfall estimates, which better represents rainfall variability across the catchment, based upon known values at point locations. Once a spatial grid of gauge-based rainfall estimates is obtained, it can be applied to subcatchments in the same way as radar data. Antecedent Rainfall Information on antecedent rainfall and in some cases soil moisture data is required to ensure that the catchment wetness conditions are correctly modelled. In addition evapotranspiration will need to be included in the modelling. Dependent on the type of runoff model used in the model, antecedent rainfall data will be required for up to 30 days prior to the first rainfall event, to allow initial catchment wetness parameters to be calculated. For short term flow surveys, actual rainfall data will be required for this period. If using raingauges for the rainfall, this can be obtained by the following methods:- Deployment of all raingauges 30 days prior to the commencement of flow monitoring. Use of radar rainfall data to provide rainfall data 30 days prior to commencement of flow monitoring. Deployment of a limited number of raingauges 30 days prior to commencement to gain an understanding of average rainfall. Use of permanent raingauge data if a suitable location is available. If radar data is being used for the flow survey, this should be collected for the 30 day period prior to the flow survey. SMD data is used in the Standard Wallingford Runoff model. The data is available as an average figure for a 40 x 40 km grid, on a daily, weekly or monthly average. The grid is relatively coarse, with average rainfall data being used in the calculations, some of which is an interpolation of rainfall from gauges up to 100km away from the grid. If the SMD is known at the commencement of the survey period, it is possible to calculate the SMD using the site specific rainfall data. However in most instances the use of the standard MORECS data will be sufficient for the verification process. Copyright to IJIRSET DOI: /IJIRSET

4 Figure 1: A sample line graph of measured rainfall using rain gauge. IV. CONCLUSION Rain gauge data used during the storm verification. The selected event should be as per WaPUG criteria. The total depth should be greater than 5 mm. The rainfall intensity should be greater than 6 mm/hour for more than 4 minutes. The period between events should be sufficient for the flow to return to dry weather conditions. For the events from the flow survey, the predicted flows/depths should be compared to the observed flows/depths. The two flow hydrographs should closely follow each other both in shape and in magnitude, until the flow has substantially returned to dry weather flow rates. In addition to the shape, as a general guide, the observed and modelled hydrographs should meet the following criteria in at least two of the three events. In addition, variation between rainfall measured at adjacent rain gauges should not be outside the following limits: The total depth of rainfall should not vary by more than 20%. The should be no more than a 15 minute difference in the time of a peak measured at the different sites. The time interval between successive peaks in an event should not vary by more than 10% at the different sites. REFERENCES [1] Wastewater Planning Users Group, Code Of Practice For The Hydraulic, Modelling Of Sewer Systems Version November 2002 [2] Department of the Environment/National Water Council Standing Technical Committee. The Wallingford Procedure, HR Wallingford [3] WRc, Model contract document for manhole location surveys and production of record maps. 2nd Edition [4] WRc, Stormpac Version 3.0 User Guide. WRc, [5] WaPUG Committee, Runoff equations and catchment data, WaPUG Usernote 21 [6] Armstrong RJ, Modelling Dry Weather Flow, WaPUG Usernote 33 [7] WRc Sewerage Rehabilitation Manual. WRc 4th Edition [8] Chapman R E, The Percentage runoff equation, WaPUG Usernote 9 [9] Osborne M P, A new runoff model. WaPUG Usernote 28 [10] Orman N R, Predicting flooding using hydraulic models, WaPUG Usernote 29 [11] Allitt R C, Overland flow routing, WaPUG Usernote 37 [12] Osborne M P, Selection of tide levels. WaPUG Usernote 22 [13] Chapman R E, Storage Compensation in WASSP, WaPUG Usernote 15 [14] Balmforth D J, Modelling ancillaries and discharge coefficients, WaPUG Usernote 2 [15] Orman N R, Modelling vortex flow control devices, WaPUG Usernote 1 [16] Balmforth D J, Modelling low side weirs, WaPUG Usernote 14 [17] Balmforth D J, Modelling ancillaries: weir coefficients, WaPUG Usernote 27 [18] Allitt R C, Modelling large detention tanks, WaPUG Usernote 38 [19] Eadon A R, Management of above ground data for partially separate systems, WaPUG Copyright to IJIRSET DOI: /IJIRSET

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