Premium
Influence of Spatially Variable Soil Hydraulic Properties on Predictions of Water Stress
Author(s) -
Anderson S. H.,
Cassel D. K.,
Skaggs R. W.
Publication year - 1987
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj1987.03615995005100010004x
Subject(s) - drainage , hydraulic conductivity , loam , environmental science , soil water , pedotransfer function , soil science , infiltration (hvac) , hydrology (agriculture) , crop yield , agronomy , geology , geotechnical engineering , geography , ecology , biology , meteorology
Models are often used to predict drainage system effects on crop production. Variability of soil hydraulic properties on predictions made by many models have not been evaluated. This study evaluated several methods for predicting water transport properties and corn ( Zea mays L.) stress as influenced by variable soil hydraulic properties in a field of Portsmouth sandy loam (Typic Umbraquults). Upflux, drainage volume, and infiltration parameters as functions of water table depth were predicted using hydraulic conductivity and soil water retention functions for three soil horizons measured at 150 locations in a field. Crop stress due to both deficient and excess soil water conditions and relative crop yield were estimated using DRAINMOD, a water management simulation model, for three selected methods of averaging soil property inputs. Small differences existed among the three approaches for the 30‐yr average relative corn yield. Large differences in relative corn yield occurred in dry years indicating that the variability of the soil properties was important to consider in predicting crop stress during relatively dry years. More information for the field soil‐drainage response was obtained using the individual locations method which allowed soil property inputs to vary from location to location at each of the 150 points in the field. However, the field averages approach is more practical because fewer data are required to perform the necessary computations and only a 3% difference in the 30‐yr relative yield resulted between the individual location and field average methods.