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Journal ArticleDOI

Parsimonious hydrological modeling of urban sewer and river catchments

TL;DR: In this paper, a parsimonious model of flow capable of simulating flow in natural/engineered catchments and at WWTP (Wastewater Treatment Plant) inlets was developed.
About: This article is published in Journal of Hydrology.The article was published on 2012-09-25 and is currently open access. It has received 36 citations till now. The article focuses on the topics: Impervious surface & Combined sewer.

Summary (4 min read)

1. Introduction

  • Catchment modeling is a mature discipline, and much research and modeling has been carried out on natural catchments.
  • Such models are valuable for many purposes, of course.
  • Aquatic Science and Technolerland. , Swiss Federal Institute of m/, last accessed December and Woolhiser (2002) for a review).
  • The model integrates the main physical processes in urban catchments (i.e., precipitation, infiltration, soil moisture, runoff, streamflow and groundwater flow), but without consideration of the detailed pipe drainage network.
  • In urban systems, these two endpoints drain overlapping basins.

2. Design and mathematical description of the model

  • The basin is modeled as a set of three storages (one surface and two subsurface), each characterized by a state variable representing the water stored within it (Fig. 1).
  • The two meteorological forcings considered are precipitation and air temperature, T, both assumed uniform over the basin.
  • The subterranean layer is represented as composed of two reservoirs: the upper soil (or root zone) region and the groundwater region with, respectively, storages of Su and Sg (Botter et al., 2010).

2.1. Modeling of surface processes

  • This water bypasses the subsurface flow, and is treated as a separate component in the lumped model.
  • When falling on the pervious fraction of the basin, the rain can either infiltrate or produce overland flow.
  • This storage also receives the precipitation flux falling on any impervious surfaces, jAi.
  • The output, Q sup, from this storage produces the fast component of the total streamflow.

2.2. Modeling of subsurface processes

  • Surface infiltration enters the root zone storage, the total volume of which is: Su ¼ ZhAp; ð3Þ with Z [L] the depth of the active soil layer.
  • Two types of outputs from this region are considered: evapotranspiration, ET, and deep percolation, Je.

ET ¼ ApETmaxf ðhÞ; ð4Þ

  • A fraction jAi of the rainfall enters this apotranspires or percolates to the subsurface linear reservoir (Sg ).
  • Note that same ulate flow at the WWTP entrance, the subsurface reservoir discharges into the pipe to artificial inputs from water use (see Section 2.4).
  • The maximum evapotranspiration is computed through a modified version of the Blaney–Criddle equation (e.g., Doorenbos and Pruitt, 1975): ETmax ¼ aþ b½pð0:46Tþ 8:13Þ ; ð6Þ where a and b are fitting parameters and p is the mean annual percentage of daytime hours, which varies only with latitude (Allen et al., 1998).
  • This formulation of subterranean flow, based on Botter et al. (2010), is easily extendible to account for interflow (or subsurface runoff) through shallow soil layers.

2.3. Consideration of CSOs

  • A characteristic feature of hybrid sewer networks are CSOs.
  • In the drainage network, CSOs divert flows above a certain level directly to receiving waters, rather than to the WWTP (Butler and Davies, 2010; Lee and Bang, 2000; Wisner et al., 1981).
  • The authors consider in this study that a single, representative flow delimiter is sufficient to model the effect of all CSOs of the system in a lumped fashion manner.
  • This representative CSO is modeled using a diversion law that follows a linear threshold-limited function (in Fig. 2).

2.4. Dynamics of wastewater production

  • During dry weather, discharges arriving at the WWTP inlet are determined mainly by two phenomena: (i) infiltration of groundwater into the pipe network (see Section 2.2 and Dupont et al. (2006); Göbel et al. (2004)) and, (ii) water use and consequent wastewater production.
  • This ‘artificial’ water input, which is not present in a natural catchment, is modeled based on statistical analysis presented by Jordan (2010).
  • Monthly, daily and hourly flow coefficients are extrapolated from temporal series analysis and considered as characteristic of the system.
  • This includes direct water consumption in households, and all parasitic clear water (fountains, street washing, industrial uses, etc).

3. Optimization of hydrological quality index

  • Model calibration was performed based on the two objective functions in Table 1, since this combination has been found to yield better overall fits (Hingray et al., 2009; Perrin et al., 2001).
  • The list of fitting criteria and the range of prior values given before calibration process can be found in Table 2.
  • Similarly to Fenicia et al. (2006) and Seibert (2000), the calibration approach adopted here is based on a Monte Carlo algorithm designed to optimize the model performance, using the Nash–Sutcliffe (NS) and the Normalized Bias (NB) criteria (Table 1).
  • The former places an emphasis on the model’s ability to estimate large magnitudes (i.e., peak discharge), while the latter weights more the deviation between simulated and observed water balance, as follows: Minfð1 NSÞþ j NB jg: ð10Þ 4 http://www.meteosuisse.ch, last accessed January 2012.

4.1. Application of the model to an urban basin: Modeling of flow at the river outlet and WWTP entrance

  • The same modeling framework is employed to model both the dynamics of flows at an urban river outlet and inlet of a local WWTP.
  • The application area is the city of Lausanne in Switzerland, which has a population of about 200,000 and is characterized by a steep average gradient towards nearby Lake Geneva.
  • A feature of Lausanne is that the WWTP catchment and the river catchment overlap over a fraction of the city (Fig. 3).
  • The model is calibrated twice on the same time period, once to model the WWTP input, and once to model the river output to the adjacent Lake Geneva, which is the receiving water body for both river and WWTP discharges.

4.2. Application to the WWTP basin

  • The WWTP catchment under study is the Lausanne hybrid (partially-separate) sewer system, drains to the Vidy Bay WWTP.
  • A large part of the water is in consequence diverted through drainage out of the WWTP basin.
  • The flow rate at the WWTP entrance during significant storm events is attenuated by the presence of CSOs; this behavior is captured by the simulator.
  • The modeling results in Fig. 4 do not capture perfectly the measured data.

4.3. Application to the river basin

  • The modeled river, called the Vuachère, is located in the eastern part of the city of Lausanne (Fig. 3).
  • The flow rate was measured at the outlet of the river basin, just before discharge into Lake Geneva.
  • The calibration and validation periods were taken the same as for the WWTP basin modeling.
  • Different factors in the model drive the simulated flow dynamics in the river.

5. Sensitivity analysis

  • A sensitivity analysis was conducted to estimate the influence of the model parameters (Table 2).
  • Each parameter was varied within the prior range of acceptable values for this parameter, and the two fitting criteria (Nash–Sutcliff and Normal Bias) computed.
  • The authors see from Fig. 7 that two parameters mainly govern the overall performance of the model.
  • These are the discharge constants of the surface impervious reservoir (ksup) and the subsurface reservoir (ksub).
  • On the other hand, changes in the ksub value degrade the ability of the model to reproduce the base flow, and thus move the Normal Bias criterion away from its optimal value of 0, in addition to affecting the Nash–Sutcliff criterion.

6. Discussion

  • The lumped modeling approach was designed to predict, with an identical framework, both flow at the WWTP inlet and at the outlet of the river basin overlapping the WWTP catchment.
  • Saturation excess could be easily implemented but at cost of additional calibration parameter.
  • Another key assumption is the way CSOs are represented.
  • For the river, CSOs provide additional water as excess water in the pipe network is diverted to prevent overloading the WWTP.
  • In agreement with Leon et al. (2010), the study presented here presents a physically consistent model that, despite its simplifications, allows prediction of water flow dynamics in two structurally different basins.

7. Conclusion

  • A hierarchical physically based storage and transmission model was designed as an alternative means for simulating continuous flow dynamics in complex engineered urban basins.
  • The model ignores the complexity of the drainage network, while reproducing efficiently the flow dynamics at the different end-points.
  • Two important modeling assumptions are: (i) the pipe network is replaced by an underground impervious area and thus overland flow and pipe discharge can be together modeled as a fast discharge linear reservoir, and (ii) the water diverted out of the sewer system through the different CSOs can be combined together through the hydraulic discharge function of a representative CSO.
  • Therefore, their approach is ideal for repetitive tasks such as model calibration and optimization.
  • In addition, the model can serve as the flow part of more complex models assessing complex diffuse pollution production and transfer processes.

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Citations
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Journal ArticleDOI
TL;DR: The method consists of formulating alternative models with increasing detail and flexibility and describing their systematic deviations by an autoregressive bias process, and shows that a single bias description produces reliable predictions for all models.
Abstract: Oversimplified models and erroneous inputs play a significant role in impairing environmental predictions. To assess the contribution of these errors to model uncertainties is still challenging. Our objective is to understand the effect of model complexity on systematic modeling errors. Our method consists of formulating alternative models with increasing detail and flexibility and describing their systematic deviations by an autoregressive bias process. We test the approach in an urban catchment with five drainage models. Our results show that a single bias description produces reliable predictions for all models. The bias decreases with increasing model complexity and then stabilizes. The bias decline can be associated with reduced structural deficits, while the remaining bias is probably dominated by input errors. Combining a bias description with a multimodel comparison is an effective way to assess the influence of structural and rainfall errors on flow forecasts. We investigate how a random bias process behaves as a function of model complexity.We analyze 5 model structures to simulate a stormwater system.The reduction of systematic deviations is associated with decreasing structural deficits.In this study the remaining bias is likely to be dominated by input errors.The method provides sound probabilistic predictions in a relatively efficient way.

37 citations


Cites background or methods from "Parsimonious hydrological modeling ..."

  • ...These alternative hypotheses with increasing detail aim to represent the typical levels of complexity used in urban hydrological modeling (Coutu et al., 2012; Leitao et al., 2010)....

    [...]

  • ...These parsimonious simulators (i.e. deterministic models) usually can be very rapidly calibrated, have easily identifiable parameters and can reproduce the hydrologic response of a simple system well (Coutu et al., 2012)....

    [...]

  • ...deterministic models) usually can be very rapidly calibrated, have easily identifiable parameters and can reproduce the hydrologic response of a simple system well (Coutu et al., 2012)....

    [...]

  • ...We selected a completely lumped approach as the simplest model, M1 (Coutu et al., 2012), a fullydetailed network modeling as the two most complex structures, M4 and M5, and two simplified network structures in between (Leitao et al., 2010)....

    [...]

  • ...We selected a completely lumped approach as the simplest model, M1 (Coutu et al., 2012), a fullydetailed network modeling as the two most complex structures, M4 and M5, and two simplified network structures in between (Leitao et al....

    [...]

Journal ArticleDOI
TL;DR: In this paper, a statistical description of systematic model errors was used to generate reliable predictions for TSS in a small ungauged catchment, and the reliability of TSS predictions increased when streamflow data were additionally used in model calibration.

33 citations

Journal ArticleDOI
18 Mar 2017-Water
TL;DR: In this paper, a generalised framework for assessing and mitigating the impacts of intense rainfall on sanitary sewer networks is presented, which involves a detailed hydraulic modelling to evaluate the performance of the sewer network.
Abstract: Short duration intense rainfall causes an increase in rainfall derived infiltration and inflow (RDII) into aging sewer networks, which leads to Sanitary Sewer Overflows (SSOs). This study presents a generalised framework for assessing and mitigating the impacts of intense rainfall on sanitary sewer networks. The first part of the proposed framework involves a detailed hydraulic modelling to evaluate the performance of the sewer network. The second part deals with the development of SSO mitigation strategies based on Water Sensitive Urban Design (WSUD) approaches. This paper also demonstrates the application of the first part of the proposed framework for a case study catchment in Melbourne, Australia. The hydraulic performance of the case study sewer network during a wet and a dry year is presented. The analysis found that for the wet year, 11 manholes had sewer overflows, whereas 53 of 57 manholes in the network of 3.2 km had surcharges. Such a study will benefit the water authorities to develop mitigation strategies for controlling SSOs in their sewer systems.

29 citations


Additional excerpts

  • ...The ENS is suitable for reflecting the trends and overall fit of a flow hydrograph [52]....

    [...]

Journal ArticleDOI
TL;DR: In this paper, the performance of three simplified and a full hydrodynamic (FH) model for two catchments are compared based on the correct determination of CSO event occurrences and of the total discharged volumes to the surface water.

27 citations


Cites background from "Parsimonious hydrological modeling ..."

  • ...Simplified models consist in many representations, see e.g. 57 (Coutu et al., 2012; Mannina and Viviani, 2010; Motiee et al., 1997; Vaes and Berlamont, 1999; 58 Wolfs and Willems, 2014), but all aim to compress the complexity of the real system in only a 59 few characteristics and/or relationships....

    [...]

  • ...Simplified models consist in many representations, see e.g. 57 (Coutu et al., 2012; Mannina and Viviani, 2010; Motiee et al., 1997; Vaes et al., 1999; Wolfs 58 and Willems, 2014), but all aim to compress the complexity of the real system in only a few 59 characteristics and/or relationships....

    [...]

  • ...57 (Coutu et al., 2012; Mannina and Viviani, 2010; Motiee et al., 1997; Vaes et al., 1999; Wolfs 58 and Willems, 2014), but all aim to compress the complexity of the real system in only a few 59 characteristics and/or relationships....

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Journal ArticleDOI
TL;DR: In this paper, the influence of urban growth on stream flow in 14 urban basins was investigated using flow duration curves (FDCs) determined using a stochastic model.

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References
More filters
Book
01 Jan 1998
TL;DR: In this paper, an updated procedure for calculating reference and crop evapotranspiration from meteorological data and crop coefficients is presented, based on the FAO Penman-Monteith method.
Abstract: (First edition: 1998, this reprint: 2004). This publication presents an updated procedure for calculating reference and crop evapotranspiration from meteorological data and crop coefficients. The procedure, first presented in FAO Irrigation and Drainage Paper No. 24, Crop water requirements, in 1977, allows estimation of the amount of water used by a crop, taking into account the effect of the climate and the crop characteristics. The publication incorporates advances in research and more accurate procedures for determining crop water use as recommended by a panel of high-level experts organised by FAO in May 1990. The first part of the guidelines includes procedures for determining reference crop evapotranspiration according to the FAO Penman-Monteith method. These are followed by updated procedures for estimating the evapotranspiration of different crops for different growth stages and ecological conditions.

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"Parsimonious hydrological modeling ..." refers background or methods in this paper

  • ...…is computed through a modified version of the Blaney–Criddle equation (e.g., Doorenbos and Pruitt, 1975): ETmax ¼ aþ b½pð0:46Tþ 8:13Þ ; ð6Þ where a and b are fitting parameters and p is the mean annual percentage of daytime hours, which varies only with latitude (Allen et al., 1998)....

    [...]

  • ...where a and b are fitting parameters and p is the mean annual percentage of daytime hours, which varies only with latitude (Allen et al., 1998)....

    [...]

Journal ArticleDOI
TL;DR: In this article, the principles governing the application of the conceptual model technique to river flow forecasting are discussed and the necessity for a systematic approach to the development and testing of the model is explained and some preliminary ideas suggested.

19,601 citations

01 Jan 1979
TL;DR: In this paper, a hydrological forecasting model is presented that attempts to combine the important distributed effects of channel network topology and dynamic contributing areas with the advantages of simple lumped parameter basin models.
Abstract: A hydrological forecasting model is presented that attempts to combine the important distributed effects of channel network topology and dynamic contributing areas with the advantages of simple lumped parameter basin models. Quick response flow is predicted from a storage/contributing area relationship derived analytically from the topographic structure of a unit within a basin. Average soil water response is represented by a constant leakage infiltration store and an exponential subsurface water store. A simple non-linear routing procedure related to the link frequency distribution of the channel network completes the model and allows distinct basin sub-units, such as headwater and sideslope areas to be modelled separately. The model parameters are physically based in the sense that they may be determined directly by measurement and the model may be used at ungauged sites. Procedures for applying the model and tests with data from the Crimple Beck basin are described. Using only measured and estimated parameter values, without optimization, the model makes satisfactory predictions of basin response. The modular form of the model structure should allow application over a range of small and medium sized basins while retaining the possibility of including more complex model components when suitable data are available.

6,158 citations

Journal ArticleDOI
TL;DR: In this paper, a hydrological forecasting model is presented that combines the important distributed effects of channel network topology and dynamic contributing areas with the advantages of simple luminescence.
Abstract: A hydrological forecasting model is presented that attempts to combine the important distributed effects of channel network topology and dynamic contributing areas with the advantages of simple lum...

4,668 citations

Journal Article

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Frequently Asked Questions (11)
Q1. What are the main physical processes driving the discharge at the two basin end-points in this?

The dominant physical processes driving water discharge at the two basin end-points in this study are Hortonian runoff, evapotranspiration, and gravity-driven percolation to groundwater. 

Two important modeling assumptions are: (i) the pipe network is replaced by an underground impervious area and thus overland flow and pipe discharge can be together modeled as a fast discharge linear reservoir, and (ii) the water diverted out of the sewer system through the different CSOs can be combined together through the hydraulic discharge function of a representative CSO. 

Most popular urban hydrological models used in research and engineering (e.g., MOUSE (Hernebring et al., 2002), SWMM3) are spatially distributed with link-node drainage networks. 

In this study, a hierarchical physically based storage and transmission model was designed as an alternative means for simulating continuous flow dynamics in complex engineered urban basins. 

In addition, the hydrological model integrates functions that aim to reproduce characteristic daily variations of dry weather flow to the WWTP. 

Detailed modeling of drainage systems is often deemed necessary because of the complexity of flow paths in urban catchments (Cantone and Schmid, 2011; Gironás et al., 2009). 

The type of precipitation is determined based on a temperature threshold (DeWalle and Rango, 2008; Schaefli et al., 2005): when T is above the threshold Tcr , precipitation occurs as rain, otherwise precipitation is frozen. 

This CSO, the closest CSO to the WWTP, is responsible for more than a third of all CSO discharge, and is typically the first to become operational in storms (e-dric.ch, 2008). 

During dry weather, discharges arriving at the WWTP inlet are determined mainly by two phenomena: (i) infiltration of groundwater into the pipe network (see Section 2.2 and Dupont et al. (2006); Göbel et al. (2004)) and, (ii) water use and consequent wastewater production. 

It is a typical urban catchment, where much water comes from toilets, washing, industry and other uses, rather than directly from natural sources. 

Saturation excess was not implemented in their modeling scheme as the authors considered an unlimited reservoir height – i.e., the reservoir is never full – and this could lead to underestimation of surface runoff (Buda et al., 2009; MartínezMena et al., 1998; Nachabe et al., 1997).