Narayan Kumar Shrestha

Assessment of the different sources of uncertainty in a SWAT model of-the River Senne (Belgium)

Although rainfall input uncertainties are widely identified as being a key factor in hydrological models, the rainfall uncertainty is typically not included in the parameter identification and model output uncertainty analysis of complex distributed models such as SWAT and in maritime climate zones. This paper presents a methodology to assess the uncertainty of semi-distributed hydrological models by including, in addition to a list of model parameters, additional unknown factors in the calibration algorithm to account for the rainfall uncertainty (using multiplication factors for each separately identified rainfall event) and for the heteroscedastic nature of the errors of the stream flow. We used the Differential Evolution Adaptive Metropolis algorithm (DREAM(zs)) to infer the parameter posterior distributions and the output uncertainties of a SWAT model of the River Senne (Belgium). Explicitly considering heteroscedasticity and rainfall uncertainty leads to more realistic parameter values, better representation of water balance components and prediction uncertainty intervals. Adapted a method to incorporate rainfall uncertainty in distributed hydrologic models.Considered different sources of uncertainty in semi-distributed hydrologic model.Assessed impacts of different sources of uncertainty on model parameter estimations.Accounting for different sources of uncertainty leads to more realistic parameter values.Explicitly treating different uncertainty sources improves water balance representation.

Integrated Water Quality Modelling of the River Zenne (Belgium) Using OpenMI

The modelling of the different catchment processes is key for integrated water resources management. Constructing a single model for all the catchment processes may not always be a feasible option, and it does not make appropriate use of existing models. The Open Modelling Interface (OpenMI), which allows time-dependent models to exchange data at run-time, might just be useful for such proposes. We used the Soil and Water Assessment Tool (SWAT) and the Storm Water Management Model (SWMM) for simulating rural and urban catchment processes, respectively. We also used SWMM to model the river processes. To link these models in OpenMI, both models were migrated to the OpenMI platform. As the water quality processes in SWAT are based on the QUAL2E process description, a new OpenMI compliant water quality module that is based on the same principles was developed to simulate the water quality processes in the river. The latter model, which uses a river network that is similar to that of the SWMM river model, is then also linked to the SWMM model using OpenMI. We tested this integrated model for the river Zenne in Belgium. The integrated model results show that such integration can be very useful as a decision support tools for integrated river basin management approach.

Development of RWQM1-based integrated water quality model in OpenMI with application to the River Zenne, Belgium

ABSTRACT Descriptions of biochemical conversion processes based on QUAL principles have been used widely. We chose the recently developed IWA RWQM1 principles to model in-stream conversion of water quality components due to its sound physical background. An engine (a simulator) based on the RWQM1 principles was integrated with three other engine components—hydrological (SWAT), hydraulic (SWMM) and stream water temperature—in the OpenMI interface. We applied the integrated model to the River Zenne, Belgium. The results indicate that the integrated model can simulate various water quality components with a wide range of accuracy, from “Unsatisfactory” to “Very Good”. However, we could not validate the model against each of the RWQM1 components as most of the components were not measured in traditional river monitoring programmes.