Overflow Data of Rainwater Discharge Systems Determined from Run off Simulation of Pluviograph Records

A MASS BALANCE METHOD FOR ESTIMATING COMBINED SEWER RUNOFF AND OVERFLOW QUALITY FROM SEWAGE TREATMENT PLANT DATA

Simulation errors due to insufficient temporal rainfall resolution — Annual combined sewer overflow

The design rainfall value is a critical parameter in flood analysis and water structure design. In general, the design rainfall calculation uses measured rainfall data. However, sometimes it is difficult to find complete rainfall data from evenly distributed rainfall stations and in an extended measurement range. This study aims to test the use of CHIRPS satellite-based rainfall data as an alternative solution for providing data in areas with difficulty with rainfall data. The analysis includes data accuracy and calibration evaluation, followed by design rainfall analysis with frequency analysis and mapping using spatial data processing software. The accuracy test results obtained an average deviation value of the original CHIRPS that did not meet the average NSE value of 0.346. Furthermore, the data was calibrated using the regression method, and corrected data was obtained with an NSE of 0.446 with an interpretation of the meeting. A rainfall analysis was conducted for corrected CHIRPS with ARR (Automatic Rainfall Recorder) measurement as a control. The results obtained the average percentage deviation for design rainfall with a return period of 2, 5, 10, 25, 50, and 100 years using corrected CHIRPS ranging from 18 - 28% lower than design rainfall using ARR. The design rainfall isohyet map using spatial data processing software for the North Lombok Region shows that high design rainfall occurs in the eastern part of North Lombok, namely around the Santong and Sambik Bangkol stations, while design rainfall with low values is in the western part of North Lombok, namely around the Tanjung and Gunungsari stations.

Design flood discharge analysis is required in the planning of water structures in a watershed.The unit hydrograph method is commonly used in designing flood discharge calculations that require rainfall data in the analysis.Current technology makes it possible to use satellite data as an alternative to data from rain gauge stations whose distribution is very limited.The rainfall data used in this study uses measured rainfall data from rain gauge stations and the PERSIANN satellite.The calculation results from both data will then be validated with the river flood discharge recorded at the Tukad Petanu Hulu AWLR Station and see the suitability.This research shows that the amount of design flood discharge in Tukad Petanu watershed analyzed using Nakayasu SUH based on measured rainfall data for 5, 10, 25, 50, and 100-year return periods is 58.16 m 3 /sec, 67.99 m 3 /sec, 82.76 m 3 /sec, 95.88 m 3 /sec, and 110.81 m 3 /sec, while based on PERSIANN satellite rainfall data for the same return period of 77.19 m 3 /sec, 83.64 m 3 /sec, 90.62 m 3 /sec, 94.84 m 3 /sec, and 98.51 m 3 /sec, respectively.The design flood discharge in the Tukad Petanu watershed based on measured discharge data at the Tukad Petanu Hulu AWLR Station for the same return period is 15.75 m 3 /sec, 24.94 m 3 /sec, 42.47 m 3 /sec, 61.28 m 3 /sec, and 86.63 m 3 /sec, respectively.The level of conformity of the design flood discharge generated by the Nakayasu Method using measured rainfall data and the PERSIANN satellite has a higher value than the discharge data at the AWLR Station for all return times.

The rainfall run off modelling is necessary until now days, for fulling data or make data longer. Artificial neural network can made the alternative rainfall run off modelling. The implementation Artificial neural networ for modelling on the water resources which is done by researcher to get an accurate result. Artificial neural networ is one of artificial intelligent that is imitation of representation from brain of human. This model is the black box modelling, so in the implementation were not need complecity of scient among the other aspect in the process of rainfall run off modelling. The case study applied to the river flow on the way Sekampung river in Lampung Province. The data used is rainfall data and stream flow data in the middle of the month on the water level station Pujorahayu, for 19 years from 1983 up to 2001. The rainfall data is input and stream flow is a variable output. Learning method that is used reduced gradient. From the result of this research got correlation coefficient 0,790 or 79 % the tallest. The conclution of this research is the generaly ANN can implementated in the rainfall run off modeling, although the result is not too accurate because of there is still deviation. Keywords: rainfall-runoff, artificial neural network, black box, generalized reduced gradient Permalink: http://ejournal.undip.ac.id/index.php/mkts/article/view/3907 [How to cite: Hadihardaja, I.K. dan Sutikno, S., 2005, Aplikasi Metode Generalized Reduced Gradient dalam Pemodelan Curah Hujan-Limpasan Menggunakan Artificial Neural Network (ANN), Jurnal Media Komunikasi Teknik Sipil , Volume 13, Nomor 2, pp. 37-49]

In the agricultural domain, decision-making is greatly guided by agricultural meteorology, which is the science that applies knowledge of weather and climate to qualitative and quantitative improvement in agricultural efficiency. The study area is challenged with increasing multifaceted agricultural production risks and complex agricultural ecosystems, which require analysis and understanding of local rainfall and temperature patterns. Digital technologies, such as the automatic weather station, play a pivotal role to monitor the physical environment, successively. This study engaged on a thorough analysis and interpretation of long-term rainfall and temperature data. The results would enable farmers and other users to comprehend valuable knowledge for improved productivity. The objectives of this paper were to analyse long-term climate data for Glen automatic weather station. To determine decadal climate patterns and trends, determine seasonal shifts, climate variability and climate change and quantify the frequency of the occurrence of weather extremes and develop suitable adaptation strategies relating to agronomic, phenological and physiological data necessary for crop modelling, operational evaluation and statistical analysis. The applied methods entailed Microsoft Excel and INSTAT Plus statistical software, which used to detect the interactions of environmental factors and suitable agricultural productivity. Understanding of rainfall and temperature patterns is required for agricultural management decisions, on planting date selection, crop suitability, livestock adaptation, ecosystem conservation. Agro meteorological knowledge derived from meteorological parameters, temperature, rainfall, wind and weather extremes, and may enhance agricultural productivity. Analysis of long-term and decadal trends in the time series indorse a sequence of alternately increasing and decreasing in mean annual rainfall and air temperature in Glen Farm.

Assessing the impact of climate change on Combined Sewer Overflows based on small time step future rainfall timeseries and long-term continuous sewer network modelling

A rainfall spatial variation scale to be considered in a runoff simulation will be investigated using meshtype rainfall data and a distributed runoff model. At first, a runoff simulation is conducted by using a mesh-type rainfall data as it is, and the result is regarded as a standard result. As the next step, the rainfall data is averaged in some area and a runoff simulation is conducted by using this averaged rainfall data. If we have little difference between the standard result and the result obtained by using the averaged data, we do not have to explicitly consider the rainfall spatial variability in the area where the data is averaged, and we have only to use the average rainfall data as an input data of the simulation. Conversely, if the difference is large, we have to consider the rainfall variability in the averaging area when conducting a runoff simulation. These numerical experiments indicate that it is important to find out the rainfall spatial variability which affects the results of runoff simulations and the scale changes with basin size.

Frequent flood disasters have caused serious damage to karst areas with insufficient measured rainfall data, and the analysis of the applicability of satellite rainfall data in runoff simulation is helpful to the local water management. Therefore, the purpose of this study is to analyze the accuracy of IMERG satellite rainfall data and apply it to long-term runoff simulations in a karst area—the Xiajia River basin, China. First, R (correlation coefficient) and POD (probability of detection) are applied to analyze the accuracy of the IMERG data, and the SWAT model is used for runoff simulation. The results show that the accuracy of the original IMERG data is poor (R range from 0.412 to 0.884 and POD range from 47.33 to 100), and the simulation results are “Unsatisfactory” (NSE (Nash-Sutcliffe efficiency coefficient) ranged from 0.17 to 0.32 and RSR (root mean square standard deviation ratio) ranged from 0.81 to 0.92). Therefore, the GDA correction method is used to correct the original IMERG data, and then the accuracy analysis and runoff simulation are carried out. The results show that the accuracy of the corrected IMERG data is better than that of the original data (R range from 0.886 to 0.987 and POD range from 94.08 to 100), and the simulation results of the corrected IMERG data are “Satisfactory” (NSE is over 0.55 and RSR is approximately 0.65). Therefore, the corrected data have a certain applicability in long-term continuous runoff simulations.

This study aims to investigate the impact of spatial rainfall distribution scenarios from ground observation stations on runoff simulation using hydrological modeling specific to the Rainfall-Runoff-Inundation (RRI) model. The RRI model was applied with six different spatial distribution scenarios of input rainfall, including Inverse Distance Weight (IDW), Thiessen polygon (TSP), Surface Polynomial (SPL), Simple kriging (SKG), and Ordinary kriging (OKG), to simulate the runoff of a 13,000 km2 watershed, namely the Nan River Basin in Thailand. This study utilized data from the 2014 storm event, incorporating temporal information from 28 rainfall stations to estimate rainfall in the spatial distribution scenarios. The six statistics, Volume Bias, Peak Bias, Root Mean Square Error, Correlation, and Mean Bias, were used to determine the accuracy of the estimated rainfall and runoff. Overall, the Simple kriging (SKG) method outperformed the other scenarios based on the statistical values to validate with measured rainfall data. Similarly, SKG demonstrated the closest match between simulated and observed runoff, achieving the highest correlation (0.803), the lowest Root Mean Square Error (164.48 cms), and high Nash-Sutcliffe Efficiency coefficient (0.499) values. This research underscores the practical significance of spatial interpolation methods, such as SKG, in combination with digital elevation models (DEMs) and landuse/soil type datasets, in delivering reliable runoff simulations considering the RRI model on the river basin scale.

During rain events, rainwater reaches the combined sewer system and causes additional hydraulic and pollutant load. Due to the limited capacity of the sewer system and the wastewater treatment plant, overflow structures are constructed to reduce the discharge and thus create a potential hazard for the environment. For optimal management of these structures, it is necessary to know the runoff and pollutant load of the events and their distribution over time. When these distributions have a significant peak, they are often referred to as a flush, the best-known phenomenon being the first flush at the beginning of a rainfall event. This knowledge can be used for the design of retention facilities and the calibration of sewer models. The flush phenomena are mainly caused by the erosion of contaminants on the surface as well as the remobilisation of sediments in the sewer network.Although many papers have investigated the first flush, no common pattern for the occurrence of these flushes has been identified. While the concentration of the flushes in rainwater sewers can be measured directly, the rain flushes in combined sewers are mixed with more polluted wastewater, which leads to a reduction in signal strength.The sensor site for the used measurement data is located in a combined sewer overflow in the western part of Graz, Austria with a catchment area of 460 ha, consisting mainly of residential areas and with about 19500 inhabitants.This work aims to separate and classify pollution flush signals from rainfall events in combined sewer systems to better understand the relationship between these signals and rainfall event characteristics.For this reason, the continuous hydraulic and pollution data are first analysed to determine the representative dry weather contribution. By subtracting the dry weather contribution from the combined wastewater volume and the mass flux, the stormwater contribution and thus the flushes can be estimated. In addition, automatic event detection of combined sewer events was done.Next, the wet weather events are classified by clustering the stormwater runoff-induced pollutant distribution (flush signals) and the event parameters. For the clustering of the temporal pollutant load distribution of events of different duration, the events are normalised by the mass-volume curves. To obtain the best possible clustering result, the dimension of the mass-volume curves is reduced by a principal component analysis. Different clustering methods, such as partitioning or hierarchical methods, are applied and compared.

An approach on flow duration and flood design estimation on the ungauged catchment with no rainfall and discharge data availability was been being develop with hydrological modelling including rainfall run off model implemented with watershed characteristic dataset. Near real time Rainfall data from multi satellite platform e.g. TRMM can be utilized for regionalization approach on the ungauged catchment. Watershed hydrologically similarity analysis were conducted including all of the major watershed in Borneo which was predicted to be similar with the Nanga Raun Watershed. It was found that a satisfactory hydrological model calibration could be achieved using catchment weighted time series of TRMM daily rainfall data, performed on nearby catchment deemed to be sufficiently similar to Nanga Raun catchment in hydrological terms. Based on this calibration, rainfall runoff parameters were then transferred to a model. Relatively reliable flow duration curve and extreme discharge value estimation were produced with reasonable several limitation. Further approach may be performed in order to deal with the primary limitations inherent in the hydrological and statistical analysis, especially to give prolongation to the availability of the rainfall and climate data with some novel approach like downscaling of global climate model.

Combined sewer systems are designed to transport stormwater surface run off in addition to the dry weather flows up to defined limits. In most European countries, hydraulic loads greater than the design flow are discharged directly into receiving water bodies, with minimal treatment (screening, sedimentation), or with no treatment at all. One feasible solution to prevent receiving waters from strong negative impacts seems to be the application of vertical flow constructed wetlands. In Germany, first attempts to use this ecological technology were recognized in early 1990s. Since then, further development continued until a high level of treatment performance was reached. During recent years the national “state-of-the-art” (defined in 2005) was adapted in other European countries, including France and Italy. Against the background of differing national requirements in combined sewer system design, substantial developmental steps were taken. The use of coarser filter media in combination with alternating loadings of separated filter beds allows direct feedings with untreated combined runoff. Permanent water storage in deep layers of the wetland improves the system’s robustness against extended dry periods, but contains operational risks. Besides similar functions (but different designs and layouts), correct dimensioning of all approaches suffers from uncertainties in long-term rainfall predictions as well as inside sewer system simulation tools.

PT Hasnur Riung Sinergi conducts coal mining using the open pit method, so that mining activities are directly related to outside. The problem is condition of the trench that unable to drain run off, so that makes overflows and inundates the roads and other mining areas. The research aims to design a trench that able to drain the planned run off and calculate the cost of making a trench. The method used is to calculate run off flow to determine the dimensions of the trench, then calculate the productivity of the machine to determine the cost of fuel requirements and the wages of the heavy equipment operator in making the trench. Based on the analysis of rainfall data obtained rainfall intensity of 53.58 mm/hour. There are 7 catchment areas that produce different amounts of run off. Design of a trapezoidal trench for each DTH, the trench on DTH 1, DTH 2, DTH 3, DTH 4 will be made in the pit and useful for flowing run off into the pit leading to the sump, while the trench on DTH 5, DTH 6, DTH 7 will be made outside the pit and useful for flowing run off that is outside the pit to the settling pond. The trench manufacturing work requires 2 PC200 komatsu backhoe machines with excavation time of 11 days. The cost to purchase fuel is Rp.27.846.000 and the cost to pay the operator is Rp.2.970.000. The total cost required for the work of making trenches is Rp.30.456.000. The design was made as a reference for companies in making trenches in the mining area to control run off so as not to interfere with mining activities.

Evaluation and improvement of the CLIGEN model for storm and rainfall erosivity generation in Central Chile