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4.6 INTRODUCING ‘SWAM’ (SOIL WATER ACCOUNTING MODEL)

4.6 INTRODUCING ‘SWAM’ (SOIL WATER ACCOUNTING MODEL). Soil Water Accounting Model (SWAM). Why SWAM? Simulates soil moisture storage under different scenarios (number/ size of water turns) and for different soils

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4.6 INTRODUCING ‘SWAM’ (SOIL WATER ACCOUNTING MODEL)

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  1. 4.6 INTRODUCING ‘SWAM’ (SOIL WATER ACCOUNTING MODEL)

  2. Soil Water Accounting Model (SWAM) Why SWAM? • Simulates soil moisture storage under different scenarios (number/ size of water turns) and for different soils • Tells you how much of the applied water will remain in the soil profile – by calculating the evaporation and the deep percolation losses • Easy to use (spreadsheet) • Similar results as more complex models such as SWAP

  3. SWAM concepts • Running water balance of the root zone. (Application of the water balance equation per time step). • Uniform distribution of moisture content (θ) in the root zone with depth (z), or dθ/dz = 0 • Percolation rate at lower boundary equals the hydraulic conductivity k in the root zone • Darcy’s Law for vertical flow: • Simplified Darcy’s law: • Upward flux is negligible: groundwater table is deep

  4. Computation procedure • Water balance where Δt is the time step (one day), E is the evaporation flux, P is the precipitation flux and I is irrigation flux in cm d-1.

  5. Computation procedure • Saturation deficit Where St is saturation deficit in cm at time t, Dr is the root Zone depth in cm, n is total soil porosity in %

  6. Computation procedure • Initial saturation deficit where So is initial saturation deficit in cm, Dr is root zone depth in cm, n is total soil porosity in %, SMS0 is initial soil moisture storage

  7. Computation procedure • Bare soil evaporation: Equation of Penman for open water evaporation EPen E is bare soil evaporation, α is a reduction factor, which is a function of the matric pressure in the root zone h

  8. Input Data Time invariable • Soil moisture characteristic θ(h) • Hydraulic conductivity relation k(θ) • Depth of the rootzone(maximum range?) • Length of the time step Time variable data • Initial saturation deficit? • Precipitation • Irrigation gift and interval • Potential evapotranspiration

  9. Input data – example silt loam soil

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