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Validation of lakefetch Calculations

Source: vignettes/validation.Rmd
validation.Rmd

Overview

The lakefetch package has been validated through three complementary approaches:

  1. Analytical validation - Testing against synthetic lakes with known geometry
  2. Literature validation - Comparing results to lakes with published morphometry
  3. Edge case validation - Testing challenging geometries (islands, complex shorelines)

All validation scripts are included in the package under inst/validation/.

Analytical Validation

Analytical validation uses synthetic lake geometries where the expected fetch values can be calculated mathematically. This provides the most rigorous test of algorithm correctness.

Test Cases

Test Geometry Expected Result
Circular lake center r=1000m, point at center 1000m all directions PASS (0% error)
Circular lake edge r=1000m, point 800m from center Min: 200m, Max: 1800m PASS (0% error)
Rectangular lake N/S 2000x1000m, center point 500m PASS (0% error)
Rectangular lake E/W 2000x1000m, center point 1000m PASS (0% error)
Effective fetch Circular center, top 3 mean 1000m PASS (0% error)

Running Analytical Validation 

source(system.file("validation", "validate_fetch.R", package = "lakefetch"))

Literature Validation

Literature validation compares fetch calculations against real lakes with published morphometry data from the World Lake Database (ILEC) and state limnology surveys.

Test Lakes

Lake State Published Area Calculated Area Result
Lake Sunapee NH 16.7 km² 16.85 km² PASS
Cayuga Lake NY 172 km² 173.87 km² PASS
Green Lake WI 29.6 km² 32.66 km² PASS

Validation Approach

For each lake:

  1. Download boundary from OpenStreetMap
  2. Calculate fetch at the lake centroid
  3. Compare max fetch to half the published maximum length
  4. Compare mean fetch to expected range based on lake shape

Cayuga Lake (a Finger Lake) correctly hit the 50 km fetch cap, demonstrating proper handling of very elongated lakes.

Running Literature Validation 

source(system.file("validation", "validate_literature.R", package = "lakefetch"))

Edge Case Validation

Edge case validation tests challenging geometries that could cause algorithm failures.

Test Cases

Test Geometry Key Finding Result
Central island Island at lake center Rays correctly stop at island PASS
Offset island Island 800m north of center North rays blocked at 500m PASS
Complex shoreline Sinusoidal variation ±300m Fetch varies 1119-1881m PASS
Multiple islands 3 islands at different positions Each blocks rays independently PASS
Very large lake Lake Erie OSM limitation* SKIPPED

*Great Lakes require pre-downloaded shapefiles due to OSM bounding box limitations.

Key Validations

  • Islands work correctly: Fetch rays stop at island boundaries, not pass through
  • Complex shorelines handled: Bays and peninsulas produce expected directional variation
  • Multiple islands supported: Each island independently blocks rays in its direction

Running Edge Case Validation 

source(system.file("validation", "validate_edge_cases.R", package = "lakefetch"))

Methodology Alignment

The lakefetch package implements fetch calculation following established standards:

Shore Protection Manual (USACE, 1984)

The Shore Protection Manual defines effective fetch using radial measurements weighted by direction. lakefetch uses a similar ray-casting approach with configurable angular resolution (default 5°). ### Mason et al. (2018)

Mason et al. used a comparable ray-casting approach to create effective fetch maps for the Great Lakes at 30m resolution. Their methodology was validated against USACE Wave Information Studies (R² = 0.635).

Effective Fetch Calculation

lakefetch calculates effective fetch as the mean of the top 3 directional fetch values. This provides a robust exposure metric independent of specific wind direction, suitable for ecological applications where wind patterns may vary.

Unit Tests

In addition to validation scripts, the package includes 79 formal unit tests using the testthat framework:

Test File Tests Coverage
test-fetch_core.R 18 Core algorithm, analytical validation
test-data_loading.R 25 Input handling, column detection
test-options.R 24 Configuration management
test-visualization.R 12 Plotting functions

Run tests with:

devtools::test()

R CMD Check Status

The package passes R CMD check with:

  • 0 errors
  • 0 warnings
  • 1 note (system time check - acceptable for CRAN)

Summary

The validation suite demonstrates that lakefetch:

  1. Correctly calculates fetch - 0% error against analytical solutions
  2. Handles real-world lakes - Results match published morphometry
  3. Manages complex geometries - Islands and irregular shorelines handled correctly
  4. Follows established methods - Consistent with SPM and published literature

References

  • Mason, L.A., Riseng, C.M., Layman, A.J., Jensen, R. (2018). Effective fetch and relative exposure index maps for the Laurentian Great Lakes. Scientific Data 5:180295. doi:10.1038/sdata.2018.295

  • U.S. Army Corps of Engineers (1984). Shore Protection Manual, 4th ed.

  • Håkanson, L.A. (1981). A Manual of Lake Morphometry. Springer-Verlag.