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Pedotransfer functions and their impact on water dynamics simulation and yield prediction
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The dynamics of water availability for plant growth is particularly important for crop productivity simulation. Critical for the prediction of crop growth and development is the accurate simulation of soil moisture variation time. Soil capacity-based models assume that the vertical movement of water in the soil is mostly controlled by the intrinsic soil water retention capacities (WRCs), mainly field capacity (FC) and wilting point (WP). However, FC and WP are difficult to measure directly. Pedotransfer functions (PTFs) have been developed to determine these parameters from basic, more readily available soil attributes such as texture and soil organic carbon content. Functional evaluation, a procedure to assess the appropriateness of a PTF, entails testing the sensitivity of the different PTFs to model’s target simulation outcomes. This study constitutes an attempt to quantify and understand the impact of different PTFs on crop yield in a soil capacity-based model.Six PTFs were used in the crop model HERMES to test their ability to simulate soil water dynamics and to determine their effect on yield simulation. This study, carried out in Germany, included three sandy soil sites in Brandenburg and a silty soil site in Bavaria. Five lysimeters at a site in Brandenburg provided a complete record for assessing the performance of PTFs. Measured soil texture and organic carbon were used as inputs in HERMES, which by applying the PTFs under study, produced the corresponding estimates of WRPs used for soil water dynamic simulations and yield predictions. Soil water records were statistically compared with model outputs to assess the accuracy of each PTF-based simulation. Differences in yield predictions were measured to estimate the sensitivity of the crop model to the PTFs tested.Not a single PTF performed best in all sites. PTFs by Batjes and Rosetta were the best performers at the three Brandenburg sites. At Duernast, Bavaria, all PTFs resulted in higher errors than at the other sites. At this site, the measured soil water content maxima during the rainy months appeared very variable from year to year, which was unexpected if assumed that the maxima should stay around FC and be fairly constant. In general, HERMES simulations followed the trends in measured soil water dynamics regardless of the PTF applied, whereas differences between PTFs appear on the magnitude of the water maxima during the winter months. This shows that the accuracy of PTFs largely depended on their ability to correctly estimate FC. The highest variability in yield prediction for the different PTFs was observed in the three Brandenburg sites, which also corresponded with higher differences in FC estimation. A closer look at the sandy sites, and simulations with a synthetic soil database showed that differences in yield simulation between PTFs increased proportionally with soil sand percent. This points out at the empirical nature of PTFs and the care that needs to be taken when applied in new situations.
Copernicus GmbH
Title: Pedotransfer functions and their impact on water dynamics simulation and yield prediction
Description:
The dynamics of water availability for plant growth is particularly important for crop productivity simulation.
Critical for the prediction of crop growth and development is the accurate simulation of soil moisture variation time.
Soil capacity-based models assume that the vertical movement of water in the soil is mostly controlled by the intrinsic soil water retention capacities (WRCs), mainly field capacity (FC) and wilting point (WP).
However, FC and WP are difficult to measure directly.
Pedotransfer functions (PTFs) have been developed to determine these parameters from basic, more readily available soil attributes such as texture and soil organic carbon content.
Functional evaluation, a procedure to assess the appropriateness of a PTF, entails testing the sensitivity of the different PTFs to model’s target simulation outcomes.
This study constitutes an attempt to quantify and understand the impact of different PTFs on crop yield in a soil capacity-based model.
Six PTFs were used in the crop model HERMES to test their ability to simulate soil water dynamics and to determine their effect on yield simulation.
This study, carried out in Germany, included three sandy soil sites in Brandenburg and a silty soil site in Bavaria.
Five lysimeters at a site in Brandenburg provided a complete record for assessing the performance of PTFs.
Measured soil texture and organic carbon were used as inputs in HERMES, which by applying the PTFs under study, produced the corresponding estimates of WRPs used for soil water dynamic simulations and yield predictions.
Soil water records were statistically compared with model outputs to assess the accuracy of each PTF-based simulation.
Differences in yield predictions were measured to estimate the sensitivity of the crop model to the PTFs tested.
Not a single PTF performed best in all sites.
PTFs by Batjes and Rosetta were the best performers at the three Brandenburg sites.
At Duernast, Bavaria, all PTFs resulted in higher errors than at the other sites.
At this site, the measured soil water content maxima during the rainy months appeared very variable from year to year, which was unexpected if assumed that the maxima should stay around FC and be fairly constant.
In general, HERMES simulations followed the trends in measured soil water dynamics regardless of the PTF applied, whereas differences between PTFs appear on the magnitude of the water maxima during the winter months.
This shows that the accuracy of PTFs largely depended on their ability to correctly estimate FC.
The highest variability in yield prediction for the different PTFs was observed in the three Brandenburg sites, which also corresponded with higher differences in FC estimation.
A closer look at the sandy sites, and simulations with a synthetic soil database showed that differences in yield simulation between PTFs increased proportionally with soil sand percent.
This points out at the empirical nature of PTFs and the care that needs to be taken when applied in new situations.
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