Coupling model uncertainty for coupled rainfall/runoff and surface water quality models in river problems

Coupled hydrology and water quality models are an important tool today, used in the understanding and management of surface water and watershed areas. Such problems are generally subject to substantial uncertainty in parameters, process understanding, and data. Component models, drawing on different data, concepts, and structures, are affected differently by each of these uncertain elements. This paper proposes a framework wherein the response of component models to their respective uncertain elements can be quantified and assessed, using a hydrological model and water quality model as two exemplars. The resulting assessments can be used to identify model coupling strategies that permit more appropriate use and calibration of individual models, and a better overall coupled model response. One key finding was that an approximate balance of water quality and hydrological model responses can be obtained using both the QUAL2E and Mike11 water quality models. The balance point, however, does not support a particularly narrow surface response (or stringent calibration criteria) with respect to the water quality calibration data, at least in the case examined here. Additionally, it is clear from the results presented that the structural source of uncertainty is at least as significant as parameter-based uncertainties in areal models. © 2012 John Wiley & Sons, Ltd.

Model structure and uncertainty for stochastic non-point source modelling applications

The uncertainty associated with a rainfall-runoff and non-point source loading (NPS) model can be attributed to both the parameterization and model structure. An interesting implication of the areal nature of NPS models is the direct relationship between model structure (i.e. sub-watershed size) and sample size for the parameterization of spatial data. The approach of this research is to find structural limitations in scale for the use of the conceptual NPS model, then examine the scales at which suitable stochastic depictions of key parameter sets can be generated. The overlapping regions are optimal (and possibly the only suitable regions) for conducting meaningful stochastic analysis with a given NPS model. Previous work has sought to find optimal scales for deterministic analysis (where, in fact, calibration can be adjusted to compensate for sub-optimal scale selection); however, analysis of stochastic suitability and uncertainty associated with both the conceptual model and the parameter set, as presented here, is novel; as is the strategy of delineating a watershed based on the uncertainty distribution. The results of this paper demonstrate a narrow range of acceptable model structure for stochastic analysis in the chosen NPS model. In the case examined, the uncertainties associated with parameterization and parameter sensitivity are shown to be outweighed in significance by those resulting from structural and conceptual decisions. © 2011 Copyright IAHS Press.

Model development & application for inland navigational canals

Several agencies in the United Kingdom have interest in the water quality of old navigational canals that have fallen into disuse after the decline of commercial canal transportation. The interested agencies desired a model to predict the water quantity and quality of inland navigational canals in order to evaluate management options to address the issues in the natural streams to which they discharge. Inland navigational canals have unique drivers of their hydrology and water quality compared to either natural streams, irrigation canals, or larger navigational canals connected to seas or oceans. Water in an inland canal is typically sourced from a reservoir and artificially pumped to a summit reach; its movement downhill is controlled by the activity of boats and overflow weirs. Stagnant impoundments between locks, which might normally be expected to result in a decrease in the concentration of sediment-associated pollutants, actually have surprisingly high levels of sediment due to boat traffic. Algal growth in the stagnant reach can be high. This paper describes a canal model developed to simulate hydrology and water quality in inland navigational canals. This model was successfully applied to the Kennet and Avon Canal to predict hydrology, sediment generation and transport, and algal growth and transport. The model is responsive to external influences such as sunlight, temperature, nutrient concentrations, boat traffic, and runoff from the contributing catchment area.