Great Lakes Runoff Intercomparison Project Phase 3: Lake Erie (GRIP-E).

Hydrologic model intercomparison studies help to evaluate the agility of models to simulate variables such as streamflow, evaporation, and soil moisture. This study is the third in a sequence of the Great Lakes Runoff Intercomparison Projects. The densely populated Lake Erie watershed studied here is an important international lake that has experienced recent flooding and shoreline erosion alongside excessive nutrient loads that have contributed to lake eutrophication. Understanding the sources and pathways of flows is critical to solve the complex issues facing this watershed. Seventeen hydrologic and land-surface models of different complexity are set up over this domain using the same meteorological forcings, and their simulated streamflows at 46 calibration and seven independent validation stations are compared. Results show that: (1) the good performance of Machine Learning models during calibration decreases significantly in validation due to the limited amount of training data; (2) models calibrated at individual stations perform equally well in validation; and (3) most distributed models calibrated over the entire domain have problems in simulating urban areas but outperform the other models in validation.

Microbial kinetics and thermodynamic (MKT) processes for soil organic matter decomposition and dynamic oxidation-reduction potential: Model descriptions and applications to soil N2O emissions.

A conversion of the global terrestrial carbon sink to a source is critically dependent on the microbially mediated decomposition of soil organic matter (SOM). We have developed a detailed, process-based, mechanistic model for simulating SOM decomposition and its associated processes, based on Microbial Kinetics and Thermodynamics, called the MKT model. We formulated the sequential oxidation-reduction potential (ORP) and chemical reactions undergoing at the soil-water zone using dual Michaelis-Menten kinetics. Soil environmental variables, as required in the MKT model, are simulated using one of the most widely used watershed-scale models - the soil water assessment tool (SWAT). The MKT model was calibrated and validated using field-scale data of soil temperature, soil moisture, and N2O emissions from three locations in the province of Saskatchewan, Canada. The model evaluation statistics show good performance of the MKT model for daily soil N2O simulations. The results show that the proposed MKT model can perform better than the more widely used process-based and SWAT-based models for soil N2O simulations. This is because the multiple processes of microbial activities and environmental constraints, which govern the availability of substrates to enzymes were explicitly represented. Most importantly, the MKT model represents a step forward from conceptual carbon pools at varying rates.