Extension of an Existing Model for Soil Water Evaporation and Redistribution under High Water Content Conditions

Abstract

Most crop, hydrology, and water quality models require the simulation of evaporation from the soil surface. A model developed by J.T. Ritchie in 1972 provides useful algorithms for estimating soil evaporation, but it does not calculate the soil water redistribution resulting from evaporation. A physically‐based model using diffusion theory, described previously by Suleiman and Ritchie in 2003, provides efficient algorithms for soil water redistribution and soil evaporation. However, the model is appropriate only for second stage drying when the soil in the entire profile being simulated is below the drained upper limit (θDUL) and no more drainage occurs due to gravity. This paper extends the Suleiman–Ritchie model for soil water contents higher than θDUL where soil evaporation rates are usually higher than second stage drying. New algorithms were developed for these wetter conditions that are functions of soil depth and the wetness of the near‐surface soil. New model parameters were calibrated with data measured in laboratory soil column studies. The resulting model was integrated into DSSAT‐CSM (Decision Support System for Agrotechnology Transfer Cropping Systems Model). Simulated soil evaporation rates and soil water contents obtained using the Suleiman–Ritchie model with the developed extensions and the previous DSSAT soil evaporation model were compared and evaluated with field measurements of soil water content during several drying cycles for parts of 3 yr in North Central Florida. Computed soil water contents from the model agreed well with the measured soil water contents near the surface, and provided more accurate estimations than the original DSSAT soil evaporation model, especially for the 5‐cm surface layer.

Implementing Standardized Reference Evapotranspiration and Dual Crop Coefficient Approach in the DSSAT Cropping System Model

“…The model calculates ET partitioning in the following order: (1) ES o via equation 4, (2) actual E from one of two algorithms (Ritchie, 1972;Ritchie et al, 2009), (3) EP o as the minimum of equation 3 and E0 minus actual E, and (4) actual T as the minimum of EP o and available water supplied by the soil through the simulated root profile. The ES o calculation in equation 4 is implemented for the CSM-CERESMaize model and several other crop models.…”

“…The Ritchie (1972) algorithm evaporates water using a two-stage drying process based on the water content of the upper soil layer only, commonly specified with a depth of 5 cm. The Ritchie et al (2009) method adds an upward flux calculation for all soil layers based on diffusion theory, and actual evaporation is the minimum of the surface soil layer upflux and ES o . Soil-limited plant (root) water uptake (EP r ) is calculated based on simulated root growth and available water supply in each user-defined soil layer (Ritchie, 1998).…”

“…First, within the FAO-56 water balance approach, K cbmin is used to account for upflow from deep soil layers (Richard Allen, personal communication). However, the evaporation routine in DSSAT-CSM already accounts for this (Ritchie et al, 2009). Second, DSSAT-CSM is often used for sequential simulations of crop rotations, including fallow periods when transpiration simulations should be zero.…”

“…Thus, the K r term in the DSSAT-CSM implementation of FAO-56 was fixed at 1.0 in the calculation of K e (eq. A5), and the native DSSAT-CSM soil evaporation routines, e.g., the Suleiman-Ritchie (Ritchie et al, 2009) approach for maize and the Ritchie (1972) approach for cotton, were used to reduce actual evaporation from potential evaporation as the soil profile dried. Similarly, FAO-56 uses K s (eq.…”

A Remote-Sensing Driven Tool for Estimating Crop Stress and Yields

“…Potential ET can be computed using either the Priestley-Taylor approximation [27] or the full Penman-Monteith combination method [56] depending on the availability of data. Soil limited evaporation is then computed using a diffusivity approach with an empirical transfer coefficient [57].…”