IMPROVING NUTRIENT TRANSPORT SIMULATION IN SWAT BY DEVELOPING A REACH-SCALE WATER QUALITY MODEL
Ecohydrological models are extensively used to evaluate land use, land management and climate change impacts on hydrology and in-stream water quality conditions. The scale at which these models operate influences the complexity of processes incorporated within the models. For instance, a large scale hydrological model such as Soil and Water Assessment Tool (SWAT) that runs on a daily scale may ignore the sub-daily scale in-stream processes. The key processes affecting in-stream solute transport such as advection, dispersion and transient storage (dead zone) exchange can have considerable effect on the predicted stream solute concentrations, especially for localized studies. To represent realistic field conditions, it is therefore required to modify the in-stream water quality algorithms of SWAT by including these additional processes. Existing reach-scale solute transport models like OTIS (One-dimensional Transport with Inflow and Storage) considers these processes but excludes the actual biochemical reactions occurring in the stream and models nutrient uptake using an empirical first-order decay equation. Alternatively, comprehensive stream water quality models like QUAL2E (The Enhanced Stream Water Quality Model) incorporates actual biochemical reactions but neglects the transient storage exchange component which is crucial is predicting the peak and timing of solute concentrations. In this study, these two popular models (OTIS and QUAL2E) are merged to integrate all essential solute transport processes into a single in-stream water quality model known as ‘Enhanced OTIS model’. A generalized model with an improved graphical user interface was developed on MATLAB platform that performed reasonably well for both experimental data and previously published data (R2=0.76). To incorporate this model into large-scale hydrological models, it was necessary to find an alternative to estimate transient storage parameters, which are otherwise derived through calibration using experimental tracer tests. Through a meta-analysis approach, simple regression models were therefore developed for dispersion coefficient (D), storage zone area (As) and storage exchange coefficient (α) by relating them to easily obtainable hydraulic characteristics such as discharge, velocity, flow width and flow depth. For experimental data from two study sites, breakthrough curves and storage potential of conservative tracers were predicted with good accuracy (R2>0.5) by using the new regression equations. These equations were hence recommended as a tool for obtaining preliminary and approximate estimates of D, As and α when reach-specific calibration is unfeasible.
The existing water quality module in SWAT was replaced with the newly developed ‘Enhanced OTIS model’ along with the regression equations for storage parameters. Water quality predictions using the modified SWAT model (Mir-SWAT) for a study catchment in Germany showed that the improvements in process representation yields better results for dissolved oxygen (DO), phosphate and Chlorophyll-a. While the existing model simulated extreme low values of DO, Mir-SWAT improved these values with a 0.11 increase in R2 value between modeled and measured values. No major improvement was observed for nitrate loads but modeled phosphate peak loads were reduced to be much closer to measured values with Mir-SWAT model. A qualitative analysis on Chl-a concentrations also indicated that average and maximum monthly Chl-a values were better predicted with Mir-SWAT when compared to SWAT model, especially for winter months. The newly developed in-stream water quality model is expected to act as a stand alone model or coupled with larger models to improve the representation of solute transport processes and nutrient uptake in these models. The improvements made to SWAT model will increase the model confidence and widen its extent of applicability to short-term and localized studies that require understanding of fine-scale solute transport dynamics.