Studying Unimodal, Bimodal, PDI and Bimodal-PDI Variants of Multiple Soil Water Retention Models: II. Evaluation of Parametric Pedotransfer Functions Against Direct Fits

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Haghverdi A., Orturk H. S., Durner W.

WATER, cilt.12, sa.3, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 12 Sayı: 3
  • Basım Tarihi: 2020
  • Doi Numarası: 10.3390/w12030896
  • Dergi Adı: WATER
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Agricultural & Environmental Science Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Compendex, Environment Index, Geobase, INSPEC, Pollution Abstracts, Veterinary Science Database, Directory of Open Access Journals
  • Anahtar Kelimeler: Turkish soils, HYPROP, water content, soil hydrology, regression, SIMPLIFIED EVAPORATION METHOD, SIMPLE CONSISTENT MODELS, HYDRAULIC CONDUCTIVITY, PRESSURE, RANGE
  • Ankara Üniversitesi Adresli: Evet

Özet

A high-resolution soil water retention data set (81 repacked soil samples with 7729 observations) measured by the HYPROP system was used to develop and evaluate the performance of regression parametric pedotransfer functions (PTFs). A total of sixteen soil hydraulic models were evaluated including five unimodal water retention expressions of Brooks and Corey (BC model), Fredlund and Xing (FX model), Kosugi (K model), van Genuchten with four free parameters (VG model) and van Genuchten with five free parameters (VG(m) model). In addition, eleven bimodal, Peters-Durner-Iden (PDI) and bimodal-PDI variants of the original expressions were studied. Six modeling scenarios (S1 to S6) were examined with different combinations of the following input predictors: soil texture (percentages of sand, silt and clay), soil bulk density, organic matter content, percent of stable aggregates and saturated water content (theta (s)). Although a majority of the model parameters showed low correlations with basic soil properties, most of the parametric PTFs provided reasonable water content estimations. The VG(m) parametric PTF with an RMSE of 0.034 cm(3) cm(-3) was the best PTF when all input predictors were considered. When averaged across modeling scenarios, the PDI variant of the K model with an RMSE of 0.045 cm(3) cm(-3) showed the highest performance. The best performance of all models occurred at S6 when theta s was considered as an additional input predictor. The second-best performance for 11 out of the 16 models belonged to S1 with soil textural components as the only inputs. Our results do not recommend the development of parametric PTFs using bimodal variants because of their poor performance, which is attributed to their high number of free parameters.