Agronomy (May 2023)

Strategy for Deriving Sacramento Model Parameters Using Soil Properties to Improve Its Runoff Simulation Performances

  • Bin Wang,
  • Hao Sun,
  • Shuaishuai Guo,
  • Jinbai Huang,
  • Zhongbo Wang,
  • Xuefeng Bai,
  • Xinglong Gong,
  • Xiaoli Jin

DOI
https://doi.org/10.3390/agronomy13061473
Journal volume & issue
Vol. 13, no. 6
p. 1473

Abstract

Read online

Physically-based parameter estimations are essential to improve the simulation performance of a hydrologic model and to produce physically reasonable parameters with spatial consistency. This study proposed a parameter derivation strategy to improve the Sacramento Soil Moisture Accounting (SAC-SMA) model simulation performance based on the publicly accessible Harmonized World Soil Database (HWSD). The HWSD soil properties were used to estimate the soil moisture characteristics, and the HWSD soil texture classifications and International Geosphere-Biosphere Programme (IGBP) land cover types were used to identify the Soil Conservation Service (SCS) runoff curve number (CN). After the soil moisture characteristics and CNs were identified, the major parameters of the SAC-SMA model were derived. The simulation results were evaluated using the Nash efficiency coefficient (NSEC), and Free Search (FS) algorithm was used to further adjust and calibrate the parameters. Compared with the simulation accuracy (NSEC = 0.66~0.88) and parameter transferability (NSEC = 0.22~0.83) obtained for the SAC-SMA model using directly calibrated parameters, the HWSD data-derived parameters allowed the SAC-SMA model to achieve a similar simulation accuracy (NSEC = 0.65~0.86) and a better transferability (NSEC = 0.61~0.85).

Keywords