Simulating Soil Water Content, Evapotranspiration, and Yield of Variably Irrigated Grain Sorghum Using AquaCrop

Abstract

Use of models to simulate crop production has become important in optimizing irrigation management in arid and semiarid regions. However, applicability and performance of these models differ across regions, due to differences in environmental and management factors. The AquaCrop model was used to simulate soil water content (SWC), evapotranspiration (ET), and yield for grain sorghum under different irrigation regimes and dryland conditions at two sites in Central and Southern High Plains. Prediction error (Pe), estimated as the difference between simulated and measured divided by measured, for SWC ranged from −17% to 4% in fully irrigated, −3% to −10% in limited irrigated, and −16% to 25% in dryland treatments. The Pe within ±4%, −5%, and −17% to 24% were attained for seasonal ET under fully irrigated, limited irrigated, and dryland conditions, respectively. Pe values for grain yield were within those previously reported and ranged from −10% to 12%, −12% to 7%, and 9% to 17% for fully irrigated, limited irrigated and dryland conditions, respectively. Overall performance of the AquaCrop model showed it could be used as an effective tool for evaluating the impacts of variable crop and irrigation managements on the production of grain sorghum in the study area. Finally, the application of the model in the study area revealed planting date has a significant impact on sorghum yield and irrigation requirements, but the impact of planting density was negligible. Editor's note: This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.

Determination of the Most Efficient Forage Sorghum Irrigation Scheduling Strategies in the U.S. Central High Plains Using the AquaCrop Model and Field Experiments

“…The adequacy and excellent accuracy of the AquaCrop model in simulating forage sorghum biomass in the region have been confirmed in the validation process by the following statistics: RMSE = 0.53 ton/ha, NRMSE = 0.04, R 2 = 0.86, d 2 = 0.95, and MBE = −0.26. Masasi et al [43] have declared similar results for simulating grain sorghum affected by deficit irrigation treatments in the Central and Southern High Plains. The comparison between the model biomass outputs and the measurements is presented in Table 4.…”

Irrigation Scheduling for Agriculture in the United States: The Progress Made and the Path Forward

“…Most of the reported research on the use of crop simulation models for implementing tactical irrigation scheduling and strategic crop water allocation over the past ten years has focused on retrospective evaluation of irrigation scheduling options based on experimental data and long-term weather data (DeJonge et al, 2011;Ma et al, 2012;Mauget et al, 2013;Saseendran et al, 2015;Kisekka et al, 2016Kisekka et al, , 2017aAdhikari et al, 2017;Wibowo et al, 2017;Araya et al, 2018;Foster and Brozović, 2018;Sharda et al, 2019;Masasi et al, 2019bMasasi et al, , 2020. With reference to the advances made, most of the progress over the last ten years has focused on improving modeling of the soil water balance, ETc, and irrigation scheduling, as well as data assimilation, coupling crop models to optimization algorithms (e.g., Nguyen et al, 2017), and development of crop-model based decision support systems.…”

Modelagem de base processual aplicada ao crescimento e produtividade do eucalipto

“…Os modelos de simulação de culturas têm sido amplamente utilizados para avaliar a umidade do solo (Ebrahimi-Mollabashi et al, 2019;Masasi et al, 2019) e a interação soloplanta-atmosfera (Gohain et al, 2022;Zizinga et al, 2022). No entanto, é importante comparar diferentes modelos para entender suas semelhanças e diferenças, a fim de identificar possíveis limitações (Battisti et al, 2018).…”