Opportunities and Limits of Using Meteorological Reanalysis Data for Simulating Seasonal to Sub-Daily Water Temperature Dynamics in a Large Shallow Lake

Marieke Frassl,Zhaoliang Peng,Jinge Zhu,Weiping Hu,Bertram Boehrer,Peter Holtermann,Knut Klingbeil,Karsten Rinke

doi:10.3390/w10050594

Abstract

In lakes and reservoirs, physical processes control temperature dynamics and stratification, which are important determinants of water quality. In large lakes, even extensive monitoring programs leave some of the patterns undiscovered and unresolved. Lake models can complement measurements in higher spatial and temporal resolution. These models require a set of driving data, particularly meteorological input data, which are compulsory to the models but at many locations not available at the desired scale or quality. It remains an open question whether these meteorological input data can be acquired in a sufficient quality by employing atmospheric models. In this study, we used the European Centre for Medium-Range Weather Forecasts’ (ECMWF) ERA-Interim atmospheric reanalysis data as meteorological forcing for the three-dimensional hydrodynamic General Estuarine Transport Model (GETM). With this combination, we modelled the spatio-temporal variation in water temperature in the large, shallow Lake Chaohu, China. The model succeeded in reproducing the seasonal patterns of cooling and warming. While the model did predict diurnal patterns, these patterns were not precise enough to correctly estimate the extent of short stratification events. Nevertheless, applying reanalysis data proved useful for simulating general patterns of stratification dynamics and seasonal thermodynamics in a large shallow lake over the year. Utilising reanalysis data together with hydrodynamic models can, therefore, inform about water temperature dynamics in the respective water bodies and, by that, complement local measurements.

Highlights

Shallow lakes are widely distributed across the globe [1], which is reflected in the low global average depths of 3.5 m for lakes in the smallest size class of 0.1–1 km2 and generally low average depths across different continents [2]
The model was driven by ERA-Interim reanalysis data
Diurnal stratification patterns predicted by the model were too regular compared to that observed: stratification occurred more often in the model and, on average, lasted longer compared to observations

Summary

Introduction

Shallow lakes are widely distributed across the globe [1], which is reflected in the low global average depths of 3.5 m for lakes in the smallest size class of 0.1–1 km and generally low average depths across different continents [2] Given their low average water depth, the water column of shallow lakes heats up faster compared to a deeper lake with the same surface area in the same climatic region [3,4]. Surface scums of cyanobacteria are not distributed homogeneously, but are constantly transported by wind and occur at a spatially-variable severity (e.g., [8]) This can result in larger horizontal than vertical gradients in shallow lakes [9,10]. Pronounced spatial patterns have been observed for the occurrence of hypoxic zones, which lead to the dissolution of reduced metals and, water quality deterioration (e.g., [11,12])

Methods

Results

Conclusion