Calibration and validation of a phenomenological influent pollutant disturbance scenario generator using full-scale data.
The objective of this paper is to demonstrate the full-scale feasibility of the phenomenological dynamic influent pollutant disturbance scenario generator (DIPDSG) that was originally used to create the influent data of the International Water Association (IWA) Benchmark Simulation Model No. 2 (BSM2). In this study, the influent characteristics of two large Scandinavian treatment facilities are studied for a period of two years. A step-wise procedure based on adjusting the most sensitive parameters at different time scales is followed to calibrate/validate the DIPDSG model blocks for: 1) flow rate; 2) pollutants (carbon, nitrogen); 3) temperature; and, 4) transport. Simulation results show that the model successfully describes daily/weekly and seasonal variations and the effect of rainfall and snow melting on the influent flow rate, pollutant concentrations and temperature profiles. Furthermore, additional phenomena such as size and accumulation/flush of particulates of/in the upstream catchment and sewer system are incorporated in the simulated time series. Finally, this study is complemented with: 1) the generation of additional future scenarios showing the effects of different rainfall patterns (climate change) or influent biodegradability (process uncertainty) on the generated time series; 2) a demonstration of how to reduce the cost/workload of measuring campaigns by filling the gaps due to missing data in the influent profiles; and, 3) a critical discussion of the presented results balancing model structure/calibration procedure complexity and prediction capabilities.
Division of Industrial Electrical Engineering and Automation (IEA), Department of Measurement Technology and Industrial Electrical Engineering (MIE), Lund University, Box 118, SE-221 00 Lund, Sweden; Center for Process Engineering and Technology (PROCESS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 229, DK-2800 Kgs. Lyngby, Denmark. Electronic address: xavier.flores@iea.lth.se.
Xavier
X
Flores-Alsina
Division of Industrial Electrical Engineering and Automation (IEA), Department of Measurement Technology and Industrial Electrical Engineering (MIE), Lund University, Box 118, SE-221 00 Lund, Sweden. Electronic address: ramesh.saagi@iea.lth.se.
Ramesh
R
Saagi
Division of Industrial Electrical Engineering and Automation (IEA), Department of Measurement Technology and Industrial Electrical Engineering (MIE), Lund University, Box 118, SE-221 00 Lund, Sweden; Sweco Environment AB, Gjörwellsgatan 22, Box 34044, SE-100 26 Stockholm, Sweden. Electronic address: erik.lindblom@iea.lth.se.
Erik
E
Lindblom
Copenhagen Wastewater Innovation, Lynettefælleskabet IS, Refshalevej 250, DK-1432 København K, Denmark. Electronic address: ct@lyn-is.dk.
Carsten
C
Thirsing
Copenhagen Wastewater Innovation, Lynettefælleskabet IS, Refshalevej 250, DK-1432 København K, Denmark. Electronic address: dt@spvand.dk.
Dines
D
Thornberg
Center for Process Engineering and Technology (PROCESS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 229, DK-2800 Kgs. Lyngby, Denmark. Electronic address: kvg@kt.dtu.dk.
Krist V
KV
Gernaey
Division of Industrial Electrical Engineering and Automation (IEA), Department of Measurement Technology and Industrial Electrical Engineering (MIE), Lund University, Box 118, SE-221 00 Lund, Sweden. Electronic address: ulf.jeppsson@iea.lth.se.
Ulf
U
Jeppsson
D057919:Biological Oxygen Demand Analysis; D003198:Computer Simulation; D008956:Models, Chemical; D012621:Seasons; D013696:Temperature; D014865:Waste Disposal, Fluid / Q000379:methods*; D014872:Water Movements; D014874:Water Pollutants, Chemical / Q000032:analysis; D014876:Water Pollution / Q000032:analysis*; D018508:Water Purification / Q000379:methods*
D014874:Water Pollutants, Chemical
Catchment modelling; Flow prediction; Influent modelling; Load prediction; Scenario analysis