Drainage water management effects on energy flux partitioning, evapotranspiration, and crop coefficients of corn

Niaghi, Ali Rashid; Jia, Xinhua; Steele, Dean D.; Scherer, Thomas F.

doi:10.1016/j.agwat.2019.105760

Cited by 13 publications

(18 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Data which did not satisfy the assumptions of the EC methods [60] or with low turbulent conditions [61] were filtered from the dataset. Since TSEB forces the closure of energy balance (via Equation (3)), energy balance closure of the EC flux measurements was ensured by allocating the residuals to the observed LE, assuming that errors in LE are larger than H due to issues related to the instrumentation (i.e., Foken et al [62]), as in previous studies (e.g., Guzinski et al [63]; Kustas et al [64]; Twine et al [65]; Niaghi et al [66]). Measurements from 2015 of the CT tower were selected as the 'main' simulation site/period and used to perform the SA (Section 2.4.2) and the main model runs (Section 2.4).…”

Section: Eddy Covariance and Bio-meteorological Measurementsmentioning

confidence: 99%

Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass Ecosystem

et al. 2020

View full text Add to dashboard Cite

The thermal-based two-source energy balance (TSEB) model has accurately simulated energy fluxes in a wide range of landscapes with both remote and proximal sensing data. However, tree-grass ecosystems (TGE) have notably complex heterogeneous vegetation mixtures and dynamic phenological characteristics presenting clear challenges to earth observation and modeling methods. Particularly, the TSEB modeling structure assumes a single vegetation source, making it difficult to represent the multiple vegetation layers present in TGEs (i.e., trees and grasses) which have different phenological and structural characteristics. This study evaluates the implementation of TSEB in a TGE located in central Spain and proposes a new strategy to consider the spatial and temporal complexities observed. This was based on sensitivity analyses (SA) conducted on both primary remote sensing inputs (local SA) and model parameters (global SA). The model was subsequently modified considering phenological dynamics in semi-arid TGEs and assuming a dominant vegetation structure and cover (i.e., either grassland or broadleaved trees) for different seasons (TSEB-2S). The adaptation was compared against the default model and evaluated against eddy covariance (EC) flux measurements and lysimeters over the experimental site. TSEB-2S vastly improved over the default TSEB performance decreasing the mean bias and root-mean-square-deviation (RMSD) of latent heat (LE) from 40 and 82 W m−2 to −4 and 59 W m−2, respectively during 2015. TSEB-2S was further validated for two other EC towers and for different years (2015, 2016 and 2017) obtaining similar error statistics with RMSD of LE ranging between 57 and 63 W m−2. The results presented here demonstrate a relatively simple strategy to improve water and energy flux monitoring over a complex and vulnerable landscape, which are often poorly represented through remote sensing models.

show abstract

Section: Eddy Covariance and Bio-meteorological Measurementsmentioning

confidence: 99%

Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass Ecosystem

et al. 2020

View full text Add to dashboard Cite

show abstract

“…The location receives a mean annual precipitation between 533 and 635 mm, with 428 mm rainfall during the growing season in 2018. The study site is on 54 ha field with less than 1% slope where a subsurface drainage system had been installed in 2011 [23]. On May 14, 2018 corn was planted in the east west direction with a 76.5 cm row spacing.…”

Section: Study Site Climate and Soil Propertiesmentioning

confidence: 99%

“…Soils in the field are predominantly classified as poorly drained with parts having a Bearden silt loam (50% of the total area), an Overly silty clay loam (27% of the area), and a Colvin silty clay loam (23% of the area), with an impermeable layer at about 3 m depth [23]. The soil properties for the different soil layers near the EC and BREB towers were measured by the cylindrical core method [24] by the end of the soil release curve measurement at saturation condition.…”

Section: Study Site Climate and Soil Propertiesmentioning

confidence: 99%

“…Details about the EC system, associated meteorological measurements, soil water and water table depth monitoring, and data processing were previously described by Niaghi et al [23,26]. The The study site is on 54 ha field with less than 1% slope where a subsurface drainage system had been installed in 2011 [23]. On 14 May 2018 corn was planted in the east west direction with a 76.5 cm row spacing.…”

Section: Study Site Climate and Soil Propertiesmentioning

confidence: 99%

“…The results are shown in Table 1. [23,26]. The EC was installed in the middle of the field with fetch over 150 m in all directions.…”

Section: Study Site Climate and Soil Propertiesmentioning

confidence: 99%

See 2 more Smart Citations

New Approach to Improve the Soil Water Balance Method for Evapotranspiration Estimation

Niaghi

Jia

2019

Water

Self Cite

View full text Add to dashboard Cite

As an important component of the water budget, quantifying actual crop evapotranspiration (ET) will enable better planning, management, and allocation of the water resources. However, accurate ET measurement has always been a challenging task in agricultural water management. In the upper Midwest, where subsurface drainage is a common practice due to the shallow ground water depth and heavy clayey soil, ET measurement using traditional ground-based methods is more difficult. In this study, ET was measured using the eddy covariance (EC), Bowen ratio-energy balance (BREB), and soil water balance (SWB) methods during the 2018 corn growing season, and the results of the three methods were compared. To close the energy balance for the EC system, the residual method was used. For the SWB method, capillary rise was included in the ET estimation and was calculated using the measured soil water potential. The change of soil water content for ET estimation using the SWB method was calculated in four different ways, including daily average, 24:00–2:00 average, 24:00–4:00 average, and 4:00 measurement. Through the growing season, six observation periods (OPs) with no rainfall or minimal rainfall events were selected for comparisons among the three methods. The estimated latent heat flux (LE) by the EC system using the residual method showed a 29% overestimation compared to LE determined by the BREB system for the entire growing season. After excluding data taken in May and October, LE determined by the EC system was only 10% higher, indicating that the main difference between the two systems occurred during the early and late of the growing season. By considering all six OPs, a 6%–22% LE difference between the EC and the BREB systems was observed. Except during the early growing and late harvest seasons, both systems agreed well in LE estimation. The SWB method using the average soil water contents between 24:00 and 2:00 time period to calculate the daily capillary rise produced the best statistical fit when compared to the ET estimated by the BREB, with a root-mean-square error of 1.15. Therefore, measuring ET using the capillary rise from a shallow water table between 24:00 and 2:00 could improve the performance of the SWB methodology for ET measurement.

show abstract

Corn yield response to subsurface drainage water recycling in the midwestern United States

et al. 2021

Self Cite

View full text Add to dashboard Cite

Drainage water recycling (DWR) involves capture, storage, and reuse of surface and subsurface drainage water as irrigation to enhance crop production during critical times of the growing season. Our objectives were to synthesize 53 site-years of data from 1996 to 2017 in the midwestern United States to determine the effect of DWR using primarily subirrigation on corn (Zea mays L.) grain yield and yield variability and to identify precipitation factors at key stages of corn development (V1-V8, V9-VT, R1-R2, R3-R4, and R5-R6) that correlated to an increase in yield with DWR. A generalized additive model was used to quantify and characterize the relationship between precipitation and corn grain yield during corn development stages and to determine if that relationship differed between DWR and free drainage (FD). Corn yield response to precipitation was generally similar between DWR and FD, except during the critical period of V9-R2, in which DWR was more resilient to precipitation extremes than FD. Drainage water recycling was generally more responsive than FD in years with low and normal precipitation (<181 mm). When precipitation was low (27-85 mm) from V9 to R2, DWR had higher yields (77% of the site-years evaluated), with an average yield increase of 3.6 Mg ha −1 (1.2-7.5 Mg ha −1 ). Overall, FD had 28% greater yield variability than DWR. Additional research is needed on DWR impacts on different soils and locations throughout this region to improve the stability of corn yields and to develop automated DWR systems for enhancing efficiency of water management with increasing climate variability.

show abstract

Drainage water management effects on energy flux partitioning, evapotranspiration, and crop coefficients of corn

Cited by 13 publications

References 34 publications

Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass Ecosystem

Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass Ecosystem

New Approach to Improve the Soil Water Balance Method for Evapotranspiration Estimation

Corn yield response to subsurface drainage water recycling in the midwestern United States

Contact Info

Product

Resources

About