From: A machine learning approach for mapping the very shallow theoretical geothermal potential

Symbol | Unit | Description |
---|---|---|

\(\alpha\) | (\(\text {m}^{2}\,\text {s}^{-1}\)) | Thermal diffusivity |

\(\gamma _{d}\) | (g/\(\text {cm}^{3}\)) | Dry (bulk) density |

\(\gamma _{s}\) | (g/\(\text {cm}^{3}\)) | Particle density |

\(\gamma _{w}\) | (g/\(\text {cm}^{3}\)) | Water density |

\(\lambda\) | (\(\text {W K}^{-1}\,\text {m}^{-1}\)) | Thermal conductivity |

\(\rho\) | (\(\Omega\) m) | Electrical resistivity |

\(\omega\) | (\(\text {s}^{-1}\)) | Angular frequency of one period in Fourier series |

\(a_{n}\) | (–) | First Fourier coefficient for the nth harmonics |

\(b_{n}\) | (–) | Second Fourier coefficient for the nth harmonics |

\(c_{v}\) | (\(\text {J m}^{-3}\,\text {K}^{-1}\)) | Volumetric heat capacity |

D | (m) | Damping depth |

e | (–) | Void ratio |

F | (%) | Percentage sum of sand and gravel fractions in the soil |

\(h_{i}\) | (m) | Width of soil strata i |

\(I_{1},...,I_{10}\) | (–) | Possible fraction intervals for soil texture variables |

\(M_{s}\) | (g) | Mass of solid soil in ground |

\(M_{w}\) | (g) | Mass of water in ground |

n | (–) | Harmonics index in Fourier series |

\(n_{p}\) | (–) | Porosity |

\(R_{n}\) | (–) | Amplitude of nth harmonic of Fourier series solution for T |

Sd, St, Cl | (%) | Sand, silt, and clay fraction percentage in soil |

\(S_{r}\) | (%) | Saturation degree |

t | (s) | Time |

T | (\(^{\circ }\)C) | Shallow ground temperature |

\(T_{0}\) | (\(^{\circ }\)C) | Average ground surface temperature over a year |

\(V_{a}\) | (\(\text {m}^{3}\)) | Volume of air in ground |

\(V_{s}\) | (\(\text {m}^{3}\)) | Volume of solid soil in ground |

\(V_{T}\) | (\(\text {m}^{3}\)) | Total volume of ground |

\(V_{v}\) | (\(\text {m}^{3}\)) | Volume of void in ground |

\(V_{w}\) | (\(\text {m}^{3}\)) | Volume of water in ground |

w | (%) | Gravimetric water content |

z | (m) | Ground depth |