Performance of one-dimensional hydrodynamic lake models during short-term extreme weather events

J.P Mesman,A.I Ayala,R Adrian,E De Eyto,M.A Frassl,S Goyette,J Kasparian,M Perroud,J.A.A Stelzer,D.C Pierson,B.W Ibelings

doi:10.1016/j.envsoft.2020.104852

Abstract

Numerical lake models are useful tools to study hydrodynamics in lakes, and are increasingly applied to extreme weather events. However, little is known about the accuracy of such models during these short-term events. We used high-frequency data from three lakes to test the performance of three one-dimensional (1D) hydrodynamic models (Simstrat, GOTM, GLM) during storms and heatwaves. Models reproduced the overall direction and magnitude of changes during the extreme events, with accurate timing and little bias. Changes in volume-averaged and surface temperatures and Schmidt stability were simulated more accurately than changes in bottom temperature, maximum buoyancy frequency, or mixed layer depth. However, in most cases the model error was higher (30–100%) during extreme events compared to reference periods. As a consequence, while 1D lake models can be used to study effects of extreme weather events, the increased uncertainty in the simulations should be taken into account when interpreting results.

Highlights

Over the last few years, limnologists have devoted increased atten tion to extreme weather events (e.g. Bertani et al, 2016; Kasprzak et al, 2017; Andersen et al, 2020; Chen et al, 2020)
Extreme weather events are projected to increase in magnitude and frequency and can have large and diverse effects on lake ecosystems
One-dimensional hydrodynamic lake models could help in elucidating their impacts on lakes, but so far no studies have investigated how well these models perform during such events

Summary

Introduction

Over the last few years, limnologists have devoted increased atten tion to extreme weather events (e.g. Bertani et al, 2016; Kasprzak et al, 2017; Andersen et al, 2020; Chen et al, 2020). Bertani et al, 2016; Kasprzak et al, 2017; Andersen et al, 2020; Chen et al, 2020) These are predicted to become more frequent and intense with climate change (IPCC, 2014; Bailey and Pol, 2016), and can have profound effects on lake ecosystems. Extreme weather events, such as storms and heatwaves, have a direct effect on lake physics. Short-term mixing events can be a major factor affecting the transport of nutrients, stimulating phytoplankton growth (Soranno et al, 1997; Crockford et al, 2015)

Methods

Discussion

Conclusion