Integrated ecological modelling for evidence-based determination of water management interventions in urbanized river basins: Case study in the Cuenca River basin (Ecuador)

Jerves-Cobo, Rubén; Benedetti, Lorenzo; Amerlinck, Youri; Lock, Koen; Mulder, Chaïm De; Butsel, Jana Van; Cisneros, Félipe; Goethals, Peter

doi:10.1016/j.scitotenv.2019.136067

Cited by 17 publications

(15 citation statements)

References 31 publications

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“…above 5 mg NH4 + -N L -1 and 0.7 mg PO4 3--P L -1 . The high concentration of nutrients with the overgrowth of algae were also found in the discharge of Ucubamba WWTP in the previous studies (Ho, 2018;Jerves-Cobo et al, 2020a). This result highlights the concern about the increasing GHG emissions from the WWTPs and the potential impact of its discharge on the GHG emissions from the receiving water bodies (Mannina et al, 2018).…”

Section: Sources Of the Ghg Emissionssupporting

confidence: 67%

Effects of land use and water quality on greenhouse gas emissions from an urban river system

Jerves-Cobo

Barthel

et al. 2020

Preprint

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Abstract. Rivers act as a natural source of greenhouse gases (GHGs) that can be released from the metabolisms of aquatic organisms. Anthropogenic activities can largely alter the chemical composition and microbial communities of rivers, consequently affecting their GHG emissions. To investigate these impacts, we assessed the emissions of CO2, CH4, and N2O from Cuenca urban river system (Ecuador). High variation of the emissions was found among river tributaries that mainly depended on water quality and neighboring landscapes. By using Prati and Oregon Indexes, a clear pattern was observed between water quality and GHG emissions in which the more polluted the sites were, the higher were their emissions. When river water quality deteriorated from acceptable to very heavily polluted, their global warming potential (GWP) increased by ten times. Compared to the average estimated emissions from global streams, rivers with polluted water released almost double the estimated GWP while the proportion increased to ten times for very heavily polluted rivers. Conversely, the GWP of good-water-quality rivers was half of the estimated GWP. Furthermore, surrounding land-use types, i.e. urban, roads, and agriculture, significantly affected the river emissions. The GWP of the sites close to urban areas was four time higher than the GWP of the nature sites while this proportion for the sites close to roads or agricultural areas was triple and double, respectively. Lastly, by applying random forests, we identified dissolved oxygen, ammonium, and flow characteristics as the main important factors to the emissions. Conversely, low impact of organic matter and nitrate concentration suggested a higher role of nitrification than denitrification in producing N2O. These results highlighted the impacts of land-use types on the river emissions via water contamination by sewage discharges and surface runoff. Hence, to estimate of the emissions from global streams, both their quantity and water quality should be included.

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Section: Sources Of the Ghg Emissionssupporting

confidence: 67%

Effects of land use and water quality on greenhouse gas emissions from an urban river system

Jerves-Cobo

Barthel

et al. 2020

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“…SIMBA (IFAK, 2007) or MIKE 11 (DHI, 2017. Those models have been well developed and, for some of them, uncertainty analyses have also been done (Beven and Binley, 1992;Refsgaard, 1997;Beven and Freer, 2001;Vrugt et al, 2003a;Vrugt et al, 2008;Beven et al, 2010;Andrés-Doménech et al, 2010;Beven, 2012;Jerves-Cobo et al, 2020;Yu et al, 2020), but obviously such uncertainty analyses can only be done if the inputs and the uncertainty associated with these inputs to these models are known. One of these inputs is the inlet from CSO.…”

Section: Uncertainty and Water Quality Impactmentioning

confidence: 99%

“…To better assess environmental impacts, numerical models are applied in urban hydrology to simulate CSO emissions into the environment. It is recommended, however, that such modelling approaches consider the inherent uncertainty associated with the system representation and the approximation of the model to the reality (Hutton et al, 2011). Moreover, the model inputs are also not free of errors, and associated uncertainties will also propagate to the model output (Heuvelink, 1998).…”

mentioning

confidence: 99%

“…Although uncertainty propagation analysis has been applied extensively in hydrologic modelling (e.g. Beven and Binley, 1992;Kuczera and Parent, 1998;Hutton et al, 2011;Vrugt et al, 2003a, b;Vrugt and Robinson, 2007;Renard et al, 2010;Datta, 2011), the number of applications of longterm simulations in urban drainage modelling is limited and typically does not consider the influence of the temporal and spatial correlation in the analysis of the propagation of input uncertainty. Temporal correlation occurs in uncertain dynamic variables, such as precipitation and COD of household wastewater, because values of these variables over short time lags will be more similar than over large time lags.…”

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confidence: 99%

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Multivariate autoregressive modelling and conditional simulation for temporal uncertainty analysis of an urban water system in Luxembourg

Torres-Matallana

Leopold

Heuvelink

2021

Hydrol. Earth Syst. Sci.

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Abstract. Uncertainty is often ignored in urban water systems modelling. Commercial software used in engineering practice often ignores the uncertainties of input variables and their propagation because of a lack of user-friendly implementations. This can have serious consequences, such as the wrong dimensioning of urban drainage systems (UDSs) and the inaccurate estimation of pollution released to the environment. This paper introduces an uncertainty analysis in urban drainage modelling, built on existing methods and applied to a case study in the Haute-Sûre catchment in Luxembourg. The case study makes use of the EmiStatR model which simulates the volume and substance flows in UDS using simplified representations of the drainage system and processes. A Monte Carlo uncertainty propagation analysis showed that uncertainties in chemical oxygen demand (COD) and ammonium (NH4) loads and concentrations can be large and have a high temporal variability. Furthermore, a stochastic sensitivity analysis that assesses the uncertainty contributions of input variables to the model output response showed that precipitation has the largest contribution to output uncertainty related with water quantity variables, such as volume in the chamber, overflow volume, and flow. Regarding the water quality variables, the input variable related to COD in wastewater has an important contribution to the uncertainty for the COD load (66 %) and COD concentration (62 %). Similarly, the input variable related to NH4 in wastewater plays an important role in the contribution of total uncertainty for the NH4 load (34 %) and NH4 concentration (35 %). The Monte Carlo (MC) simulation procedure used to propagate input uncertainty showed that, among the water quantity output variables, the overflow flow is the most uncertain output variable, with a coefficient of variation (cv) of 1.59. Among water quality variables, the annual average spill COD concentration and the average spill NH4 concentration were the most uncertain model outputs (coefficients of variation of 0.99 and 0.82, respectively). Also, low standard errors for the coefficient of variation were obtained for all seven outputs. These were never greater than 0.05, which indicates that the selected MC replication size (1500 simulations) was sufficient. We also evaluated how the uncertainty propagation can more comprehensively explain the impact of water quality indicators for the receiving river. While the mean model water quality outputs for COD and NH4 concentrations were slightly above the threshold, the 0.95 quantile was 2.7 times above the mean value for COD concentration and 2.4 times above the mean value for NH4. This implies that there is a considerable probability that these concentrations in the spilled combined sewer overflow (CSO) are substantially larger than the threshold. However, COD and NH4 concentration levels of the river water will likely stay below the water quality threshold, due to rapid dilution after CSO spill enters the river.

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“…The rest of the year is considered the dry season [25]. The average annual rainfall in Cuenca between 1977 and 2011 was approximately 879 mm per year and the yearly average temperature was 16.3 • C [26].…”

Section: Study Areamentioning

confidence: 99%

Analysis of the Behavior of Abstractions in Two Urban Micro-Basins of the City of Cuenca (Ecuador), through an Aggregate Model

2021

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Several cities in developing countries are challenging the permanent process of urbanization. This generates a great disturbance on the hydrological response of the urbanized area during rainfall events, which can cause floods. Among the disturbances that urbanized basins may suffer, it is found that variations in rain losses (hydrological abstractions) can be estimated by the named volumetric runoff coefficient (CVOL) methodology. In the present study, this methodology is used in an attempt to estimate the hydrological abstraction of two nearby urbanized basins, with different degrees of impermeability, located in the city of Cuenca in Ecuador. The data for that analysis were collected between April and May of 2017. The results obtained indicate that the micro-basin with the largest impervious area presents the higher initial hydrological losses, the higher rate of decrease in abstractions, and the higher stormwater runoff flows per unit area. In addition, the abstractions found in the two urban micro-basins show great sensitivity to the maximum rainfall intensity and do not relate to the antecedent soil moisture. These results demonstrate the importance of having higher pervious surfaces in urbanized areas because they lead to reduce negative impacts associated with increased stormwater runoff on impervious surfaces.

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Integrated ecological modelling for evidence-based determination of water management interventions in urbanized river basins: Case study in the Cuenca River basin (Ecuador)

Cited by 17 publications

References 31 publications

Effects of land use and water quality on greenhouse gas emissions from an urban river system

Effects of land use and water quality on greenhouse gas emissions from an urban river system

Multivariate autoregressive modelling and conditional simulation for temporal uncertainty analysis of an urban water system in Luxembourg

Analysis of the Behavior of Abstractions in Two Urban Micro-Basins of the City of Cuenca (Ecuador), through an Aggregate Model

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