Assimilating Leaf Area Index Time Series Into a Simple Crop Growth Model To Estimate Soil Water Holding Capacity and Soybean Yield.

Soil water holding capacity (WHC) is the main determinant of soybean yield in rainfed agriculture in the pampas region. Estimating WHC is challenging, and the capacity to measure it over large areas is limited. The main goal of this work is in advancing in methods to estimate WHC based on inverse modeling of crop growth, relying on the assumption that it is the main factor accounting for variations in growth. For that purpose we used a simple model of crop growth and soil water balance developed by Campbell and Diaz (1988). The model was inverted to estimate WHC, using leaf area index time series as input while holding other parameters describing the site and crop fixed (i.e. planting, emergence and maturity dates, dry matter water ratio). The model was also modified to estimate grain yield, assuming linear increase in harvest index and senescence driven by nitrogen remobilization from the above ground biomass. The model was tested with data from sampling points in field conditions, where time series of leaf area, dry matter accumulation and evapotranspiration (measured with Eddy Covariance) were available. One parameter (rooting depth) was calibrated through the assimilation of leaf area index data. It was also validated in field conditions in 2012 and 2013 where leaf area index, dry ground biomass, evapotranspiration and harvest yield were measured. The use of a simple model with few parameters to adjust proved useful in achieving sufficiently reliable and robust estimates of final WHC and grain yield.