Using Eddy Covariance, Soil Water Balance, and Photosynthetically Active Radiation Methods for Corn Evapotranspiration Measurements in the Red River Valley

2013 ◽  
Author(s):  
Kelsey A. Kolars ◽  
Xinhua Jia ◽  
Dean D. Steele ◽  
Thomas F. Scherer ◽  
Thomas M. DeSutter
2015 ◽  
Vol 12 (9) ◽  
pp. 6783-6820 ◽  
Author(s):  
K. Imukova ◽  
J. Ingwersen ◽  
M. Hevart ◽  
T. Streck

Abstract. The energy balance of eddy covariance (EC) flux data is typically not closed. The nature of the gap is usually not known, which hampers using EC data to parameterize and test models. The present study elucidates the nature of the energy gap of EC flux data from winter wheat stands in southwest Germany. During the vegetation periods 2012 and 2013, we continuously measured, in a half-hourly resolution, latent (LE) and sensible (H) heat fluxes using the EC technique. Measured fluxes were adjusted with either the Bowen-ratio (BR), H or LE post-closure method. The adjusted LE fluxes were tested against evapotranspiration data (ETWB) calculated using the soil water balance (WB) method. At sixteen locations within the footprint of an EC station, the soil water storage term was determined by measuring the soil water content down to a soil depth of 1.5 m. In the second year, the volumetric soil water content was also continuously measured in 15 min resolution in 10 cm intervals down to 90 cm depth with sixteen capacitance soil moisture sensors. During the 2012 vegetation period, the H post-closed LE flux data (ETEC = 3.4 ± 0.6 mm day−1) corresponded closest with the result of the WB method (3.3 ± 0.3 mm day−1). ETEC adjusted by the BR (4.1 ± 0.6 mm day−1) or LE (4.9 ± 0.9 mm day−1) post-closure method were higher than the ETWB by 20 and 33%, respectively. In 2013, ETWB was in best agreement with ETEC adjusted with the H post-closure method during the periods with low amount of rain and seepage. During these periods the BR and LE post-closure methods overestimated ET by about 30 and 40%, respectively. During a period with high and frequent rainfalls, ETWB was in-between ETEC adjusted by H and BR post-closure methods. We conclude that, at most vegetation periods on our site, LE is not a~major component of the energy balance gap. Our results indicate that the energy balance gap other energy fluxes and unconsidered or biased energy storage terms.


2011 ◽  
Vol 15 (11) ◽  
pp. 3461-3473 ◽  
Author(s):  
J. A. Breña Naranjo ◽  
M. Weiler ◽  
K. Stahl

Abstract. The hydrology of ecosystem succession gives rise to new challenges for the analysis and modelling of water balance components. Recent large-scale alterations of forest cover across the globe suggest that a significant portion of new biophysical environments will influence the long-term dynamics and limits of water fluxes compared to pre-succession conditions. This study assesses the estimation of summer evapotranspiration along three FLUXNET sites at Campbell River, British Columbia, Canada using a data-driven soil water balance model validated by Eddy Covariance measurements. It explores the sensitivity of the model to different forest succession states, a wide range of computational time steps, rooting depths, and canopy interception capacity values. Uncertainty in the measured EC fluxes resulting in an energy imbalance was consistent with previous studies and does not affect the validation of the model. The agreement between observations and model estimates proves that the usefulness of the method to predict summer AET over mid- and long-term periods is independent of stand age. However, an optimal combination of the parameters rooting depth, time step and interception capacity threshold is needed to avoid an underestimation of AET as seen in past studies. The study suggests that summer AET could be estimated and monitored in many more places than those equipped with Eddy Covariance or sap-flow measurements to advance the understanding of water balance changes in different successional ecosystems.


2018 ◽  
Vol 82 (3) ◽  
pp. 568-577 ◽  
Author(s):  
Debjit Roy ◽  
Xinhua Jia ◽  
Dean D. Steele ◽  
Dongqing Lin

2021 ◽  
Author(s):  
Keshav Parameshwaran Shankara Mahadevan ◽  
Hartmut Holländer ◽  
Paul Bullock ◽  
Steven Frey ◽  
Timi Ojo

<p>Soil moisture is highly variable in space and time. Climate change is expected to increase the variation in precipitation that may cause more frequent extremes in soil moisture. This will have major impacts on agriculture and infrastructure. Hence, forecasting can help mitigate the impacts of soil moisture extremes by providing warning about upcoming extreme events. Accurate soil moisture forecasting will provide policymakers, farmers and other stakeholders more reliable information on crop yield potential and flood risk to improve decision making.  Real-time soil moisture monitoring and forecasting can be accomplished by utilizing a numerical modelling approach that consolidates various sources of weather and hydrological data to simulate soil moisture levels. Soil water movement is difficult to describe numerically for fine-textured soils. Additionally, soil water behaviour during freeze/thaw events are generally weakly described by numerical tools. This study addresses both problems and evaluates how soil moisture can be forecasted under the hydrologically challenging conditions of the Red River Valley using the Brunkild catchment within the Red River basin.  The Brunkild catchment represents a highly variable landscape cross-section that includes heavy clay soils of the Red River Valley through to the coarse-textured soils of the adjacent escarpment. Soil moisture levels were continuously monitored from June – August 2020 using Sentek sensors which were installed at depths of 10 to 90 cm with 10 cm spacing, and with POGO sensors that were used to manually measure surface soil moisture levels at monthly intervals from June to August 2020. Climate variables were obtained from the RISMA (Real-time In-situ Soil Monitoring for Agriculture) stations present inside the catchment.  In addition to soil moisture data, surface water flow and groundwater data will also be used to aid with calibration and validation of a fully-integrated HydroGeoSphere (HGS) surface water – groundwater model of the catchment. Preliminary results using MERRA 2 data as climate forcing showed a strong fit for all observations in sandy soils and a good fit for all observation in clay. The next simulations will use the observed weather data. The model will be recalibrated and then being used to forecast soil moisture in the Brunkild catchment for the coming 14 days for the 2021 growing season.</p>


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