| Title: | Winter wheat phenology simulations improve when adding responses to water stress |
| Authors: | McMaster, G.S., D.A. Edmunds, R. Marquez, S. Haley, G. Buchleiter, P. Byrne, T.R. Green, R. Erskine, N. Lighthart, H. Kipka, F. Fox, L. Wagner, J. Tatarko, M. Moragues and J. Ascough II |
| Year: | 2019 |
| Journal: | Agronomy Journal |
| Volume (Issue): | 111(5) |
| Pages: | 2350–2360 |
| Article ID: | |
| DOI: | 10.2134/agronj2018.09.0615 |
| URL (non-DOI journals): | |
| Model: | SWAT |
| Broad Application Category: | crop/plant/tree growth or production |
| Primary Application Category: | crop, forest and/or vegetation growth/yield and/or parameters |
| Secondary Application Category: | model and/or data comparison |
| Watershed Description: | Two research sites located near the cities of Greeley and Fort Collins, which are located respectively in the north central and northeastern semi-arid region of Colorado, U.S. |
| Calibration Summary: | |
| Validation Summary: | |
| General Comments: | |
| Abstract: | Phenology is critical in simulating crop production and hydrology
and must be sufficiently robust to respond to varying
environments, soils, and management practices. Phenological
algorithms typically focus on the air temperature response function
and rarely quantify the phenological responses to varying
water deficits, particularly for versions of the Environmental
Policy Integrated Climate model (EPIC)-based plant growth
component used in many agroecosystem models. Three EPICbased
plant growth components (Soil Water Assessment Tool
[SWAT], Wind Erosion Prediction System [WEPS], and the
Unified Plant Growth Model [UPGM]) have been incorporated
into the spatially distributed Agricultural Ecosystems Services
model [AgES], and only the UPGM includes a phenological
response to varying water deficits. These three plant components
were used to evaluate the phenological responses of winter wheat
(Triticum aestivum L.) to varying water deficits and whether
having a water stress factor in UPGM improves the simulation
of phenology. A 3-yr irrigation study and a 4-yr study across a
rainfed landscape were used in the evaluation. Only the UPGM
simulated all five of the developmental stagesmeasured. The
UPGM was the only component that simulated a phenological
response to variable water deficits, resulting in better prediction
of phenology. For example, the RMSE (days) and relative error
(RE, days) decreased and index of agreement (d) increased in
predicting maturity from SWAT (RMSE = 18.4; RE = 9.2; d =
0.34) to WEPS (RMSE = 6.2; RE = 1.0, d = 0.63) to the UPGM
(RMSE = 6.1; RE = 0.1; d = 0.70). Incorporating phenological
responses to varying water deficits improves the accuracy and
robustness of predicting phenology, which is particularly important
in spatially distributed agroecosystem models. |
| Language: | English |
| Keywords: | |