Abstract
Estimating water balance is the foundation of improving water productivity (WP) and managing crop production efficiently in fields with significant spatial variability of soil properties. Agricultural system models are useful tools to simulate crop yield, WP, and water balance; however, they are rarely focused on geostatistical characteristics on the spatial scale. If agricultural system models are used spatially, it is important to consider whether the geostatistical characteristics of the simulations are similar to those based on measured data. In this study, two process-based models, the widely-used Agricultural Production Systems sIMulator (APSIM) and the newly-developed soil Water Heat Carbon Nitrogen Simulator (WHCNS), were used to simulate crop yield, water balance, and WP in a 54-ha field with spatially variable soil properties. Performance of the simulations was good for both models; however, the simulation accuracy of WHCNS was higher than for APSIM. Geostatistical characteristics of measured maize yield and final soil water storage (SWSf) were different from the simulated data. The fitted semivariogram models of simulated yield and SWSf had a higher semivariogram range and lower random variation than that of measured data. The fitted semivariogram models and geostatistical characteristics of simulated water balance also varied between the two models. Although the agricultural system models simulated the spatial distribution of variables efficiently, their spatial structure was changed in comparison with the spatial structure of measured data. This would affect the interpolation precision of spatial distribution maps. More work is required on the robustness and prediction accuracy of both models for their implementation in a spatial way.
Original language | English |
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Article number | 107174 |
Journal | Agricultural Water Management |
ISSN | 0378-3774 |
Publication status | Published - 2021 |
Keywords
- APSIM
- Geostatistics
- Spatial variability
- WHCNS
- Water balance