Abstract
Metrics describing the shape and size of lakes, known as lake morphometry metrics, are important for any limnological study. In cases where a lake has long been the subject of study these data are often already collected and are openly available. Many other lakes have these data collected, but access is challenging as it is often stored on individual computers (or worse, in filing cabinets) and is available only to the primary investigators. The vast majority of lakes fall into a third category in which the data are not available. This makes broad scale modelling of lake ecology a challenge as some of the key information about in-lake processes are unavailable. While this valuable in situ information may be difficult to obtain, several national datasets exist that may be used to model and estimate lake morphometry. In particular, digital elevation models and hydrography have been shown to be predictive of several lake morphometry metrics. The R package lakemorpho has been developed to utilize these data and estimate the following morphometry metrics: surface area, shoreline length, major axis length, minor axis length, major and minor axis length ratio, shoreline development, maximum depth, mean depth, volume, maximum lake length, mean lake width, maximum lake width, and fetch. In this software tool article we describe the motivation behind developing lakemorpho, discuss the implementation in R, and describe the use of lakemorpho with an example of a typical use case.
Highlights
The study and quantification of lake shape is one of the foundations of limnology, and for students of limnology, some of the first lessons are centered around a typical suite of metrics and how to calculate them1
The widely used Vollenweider input-output models that are used to estimate nutrient concentrations rely on hydraulic residence time and sometimes mean depth, both of which are derived from total lake volume2,3
In an effort to reach a broader audience, the tools were converted to R, expanded to include a more complete suite of lake morphometry metrics and compiled into an R Package
Summary
The study and quantification of lake shape (i.e. lake morphology and morphometry) is one of the foundations of limnology, and for students of limnology, some of the first lessons are centered around a typical suite of metrics and how to calculate them. Detailed bathymetry is a requirement for the calculation of most lake morphometry metrics, but is generally only available for a relatively small number of lakes. Soranno et al found that for some water quality datasets lake depth, in spite of its importance, was not always available10 In cases such as these, alternative approaches for estimating lake morphometry are required. Maximum depth and lake volume may be predicted using the lake polygon and surrounding topography provided by the National Hydrography Dataset Plus and the National Elevation Dataset, respectively. Maximum depth and lake volume may be predicted using the lake polygon and surrounding topography provided by the National Hydrography Dataset Plus and the National Elevation Dataset, respectively14,15 These methods were initially developed with proprietary tools, limiting their accessibility. In an effort to reach a broader audience, the tools were converted to R, expanded to include a more complete suite of lake morphometry metrics and compiled into an R Package
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