This page has only limited features, please log in for full access.

Unclaimed
Christopher M. U. Neale
Daugherty Water for Food Global Institute, University of Nebraska, Lincoln, NE 68588, USA

Basic Info

Basic Info is private.

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 22 April 2021 in Remote Sensing
Reads 0
Downloads 0

Unmanned aerial system (UAS) remote sensing has rapidly expanded in recent years, leading to the development of several multispectral and thermal infrared sensors suitable for UAS integration. Remotely sensed thermal infrared imagery has been used to detect crop water stress and manage irrigation by leveraging the increased thermal signatures of water stressed plants. Thermal infrared cameras suitable for UAS remote sensing are often uncooled microbolometers. This type of thermal camera is subject to inaccuracies not typically present in cooled thermal cameras. In addition, atmospheric interference also may present inaccuracies in measuring surface temperature. In this study, a UAS with integrated FLIR Duo Pro R (FDPR) thermal camera was used to collect thermal imagery over a maize and soybean field that contained twelve infrared thermometers (IRT) that measured surface temperature. Surface temperature measurements from the UAS FDPR thermal imagery and field IRTs corrected for emissivity and atmospheric interference were compared to determine accuracy of the FDPR thermal imagery. The comparison of the atmospheric interference corrected UAS FDPR and IRT surface temperature measurements yielded a RMSE of 2.24 degree Celsius and a R2 of 0.85. Additional approaches for correcting UAS FDPR thermal imagery explored linear, second order polynomial and artificial neural network models. These models simplified the process of correcting UAS FDPR thermal imagery. All three models performed well, with the linear model yielding a RMSE of 1.27 degree Celsius and a R2 of 0.93. Laboratory experiments also were completed to test the measurement stability of the FDPR thermal camera over time. These experiments found that the thermal camera required a warm-up period to achieve stability in thermal measurements, with increased warm-up duration likely improving accuracy of thermal measurements.

ACS Style

Mitchell Maguire; Christopher Neale; Wayne Woldt. Improving Accuracy of Unmanned Aerial System Thermal Infrared Remote Sensing for Use in Energy Balance Models in Agriculture Applications. Remote Sensing 2021, 13, 1635 .

AMA Style

Mitchell Maguire, Christopher Neale, Wayne Woldt. Improving Accuracy of Unmanned Aerial System Thermal Infrared Remote Sensing for Use in Energy Balance Models in Agriculture Applications. Remote Sensing. 2021; 13 (9):1635.

Chicago/Turabian Style

Mitchell Maguire; Christopher Neale; Wayne Woldt. 2021. "Improving Accuracy of Unmanned Aerial System Thermal Infrared Remote Sensing for Use in Energy Balance Models in Agriculture Applications." Remote Sensing 13, no. 9: 1635.

Special issue paper
Published: 03 April 2021 in Hydrological Processes
Reads 0
Downloads 0

Evapotranspiration (ET) is an important parameter in hydrologic processes and modeling. In agricultural watersheds with competing uses of fresh water including irrigated agriculture, estimating crop evapotranspiration (ETc) accurately is critical for improving irrigation system and basin water management. The use of remote sensing based basal crop coefficients is becoming a common method for estimating crop evapotranspiration for multiple crops over large areas. The Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI), based on reflectance in the red and near‐infrared bands, are commonly used for this purpose. In this paper, we examine the effects of row crop orientation and soil background darkening due to shading and soil surface wetness on these two vegetation indices through modeling, coupled with a field experiment where canopy reflectance of a cotton crop at different solar zenith angles, was measured with a portable radiometer. The results show that the NDVI is significantly more affected than the SAVI by background shading and soil surface wetness, especially in north‐south oriented rows at higher latitudes and could lead to a potential overestimation of crop evapotranspiration and irrigation water demand if used for basal crop coefficient estimation. Relationships between the analyzed vegetation indices and canopy biophysical parameters such as crop height, fraction of cover and leaf area index also were developed for both indices.

ACS Style

Christopher M. U. Neale; Maria P. Gonzalez‐Dugo; Angelica Serrano‐Perez; Isidro Campos; Luciano Mateos. Cotton canopy reflectance under variable solar zenith angles: Implications of use in evapotranspiration models. Hydrological Processes 2021, 35, 1 .

AMA Style

Christopher M. U. Neale, Maria P. Gonzalez‐Dugo, Angelica Serrano‐Perez, Isidro Campos, Luciano Mateos. Cotton canopy reflectance under variable solar zenith angles: Implications of use in evapotranspiration models. Hydrological Processes. 2021; 35 (6):1.

Chicago/Turabian Style

Christopher M. U. Neale; Maria P. Gonzalez‐Dugo; Angelica Serrano‐Perez; Isidro Campos; Luciano Mateos. 2021. "Cotton canopy reflectance under variable solar zenith angles: Implications of use in evapotranspiration models." Hydrological Processes 35, no. 6: 1.

Journal article
Published: 28 February 2021 in Remote Sensing
Reads 0
Downloads 0

The lack of measurement of precipitation in large areas using fine-resolution data is a limitation in water management, particularly in developing countries. However, Version 6 of the Integrated Multi-satellitE Retrievals for GPM (IMERG) has provided a new source of precipitation information with high spatial and temporal resolution. In this study, the performance of the GPM products (Final run) in the state of Paraná, located in the southern region of Brazil, from June 2000 to December 2018 was evaluated. The daily and monthly products of IMERG were compared to the gauge data spatially distributed across the study area. Quantitative and qualitative metrics were used to analyze the performance of IMERG products to detect precipitation events and anomalies. In general, the products performed positively in the estimation of monthly rainfall events, both in volume and spatial distribution, and demonstrated limited performance for daily events and anomalies, mainly in mountainous regions (coast and southwest). This may be related to the orographic rainfall in these regions, associating the intensity of the rain, and the topography. IMERG products can be considered as a source of precipitation data, especially on a monthly scale. Product calibrations are suggested for use on a daily scale and for time-series analysis.

ACS Style

Jéssica G. Nascimento; Daniel Althoff; Helizani C. Bazame; Christopher M. U. Neale; Sergio N. Duarte; Anderson L. Ruhoff; Ivo Z. Gonçalves. Evaluating the Latest IMERG Products in a Subtropical Climate: The Case of Paraná State, Brazil. Remote Sensing 2021, 13, 906 .

AMA Style

Jéssica G. Nascimento, Daniel Althoff, Helizani C. Bazame, Christopher M. U. Neale, Sergio N. Duarte, Anderson L. Ruhoff, Ivo Z. Gonçalves. Evaluating the Latest IMERG Products in a Subtropical Climate: The Case of Paraná State, Brazil. Remote Sensing. 2021; 13 (5):906.

Chicago/Turabian Style

Jéssica G. Nascimento; Daniel Althoff; Helizani C. Bazame; Christopher M. U. Neale; Sergio N. Duarte; Anderson L. Ruhoff; Ivo Z. Gonçalves. 2021. "Evaluating the Latest IMERG Products in a Subtropical Climate: The Case of Paraná State, Brazil." Remote Sensing 13, no. 5: 906.

Agricultural engineering
Published: 01 January 2021 in Scientia Agricola
Reads 0
Downloads 0

SAFER (Simple Algorithm for Evapotranspiration Retrieving) is a relatively new algorithm applied successfully to estimate actual crop evapotranspiration (ET) at different spatial scales of different crops in Brazil. However, its use for monitoring irrigated crops is scarce and needs further investigation. This study assessed the performance of SAFER to estimate ET of irrigated corn in a Brazilian semiarid region. The study was conducted in São Desidério, Bahia State, Brazil, in corn-cropped areas in no-tillage systems and irrigated by central pivots. SAFER algorithm with original regression coefficients (a = 1.8 and b = –0.008) was initially tested during the growing seasons of 2014, 2015, and 2016. SAFER performed very poorly for estimating corn ET, with RMSD values greater than 1.18 mm d –1 for 12 fields analyzed and NSE values < 0 in most fields. To improve estimates, SAFER regression coefficients were calibrated (using 2014 and 2015 data) and validated with 2016 data, with the resulting coefficients a and b equal to 0.32 and –0.0013, respectively. SAFER performed well for ET estimation after calibration, with r 2 and NSE values equal to 0.91 and RMSD = 0.469 mm d –1 . SAFER also showed good performance (r 2 = 0.86) after validation, with the lowest RMSD (0.58 mm d –1 ) values for the set of 14 center pivots in this growing season. The results support the use of calibrated SAFER algorithm as a tool for estimating water consumption in irrigated corn fields in semiarid conditions.

ACS Style

Luan Peroni Venancio; Everardo Chartuni Mantovani; Cibele Hummel Do Amaral; Christopher Michael Usher Neale; Roberto Filgueiras; Ivo Zution Gonçalves; Fernando França Da Cunha. Evapotranspiration mapping of commercial corn fields in Brazil using SAFER algorithm. Scientia Agricola 2021, 78, 1 .

AMA Style

Luan Peroni Venancio, Everardo Chartuni Mantovani, Cibele Hummel Do Amaral, Christopher Michael Usher Neale, Roberto Filgueiras, Ivo Zution Gonçalves, Fernando França Da Cunha. Evapotranspiration mapping of commercial corn fields in Brazil using SAFER algorithm. Scientia Agricola. 2021; 78 (4):1.

Chicago/Turabian Style

Luan Peroni Venancio; Everardo Chartuni Mantovani; Cibele Hummel Do Amaral; Christopher Michael Usher Neale; Roberto Filgueiras; Ivo Zution Gonçalves; Fernando França Da Cunha. 2021. "Evapotranspiration mapping of commercial corn fields in Brazil using SAFER algorithm." Scientia Agricola 78, no. 4: 1.

Journal article
Published: 08 April 2020 in Agricultural Water Management
Reads 0
Downloads 0

Crop biomass (Bio) is one of the most important parameters of a crop, and knowledge of it before harvest is essential to help farmers in their decision making. Both green and dry Bio can be estimated from vegetation spectral indices (VIs) because they have a close relationship with accumulated absorbed photosynthetically active radiation (APAR), which is proportional to total Bio. The aims of this study were to analyze the potential capacity of spectral vegetation indices in estimating corn green biomass based on their relationship with the photosynthetic vegetation sub-pixel fraction derived from spectral mixture analysis and to analyze the best interval of VI accumulation (days) for corn grain yield estimation. Field data of center pivots cultivated with corn during the irrigation seasons of 2015 and 2018 and Landsat 8 and Sentinel 2 images were used. The EVI produced the best results; Pearson's correlation coefficient, RMSE and Willmott’s index reached 0.99, 6.5%, and 0.948, respectively. Among the nine potential VIs analyzed, the EVI, SAVI and OSAVI were considered the first, second and third best performing for corn green Bio estimation, respectively, based on their comparison to the photosynthetic vegetation sub-pixel fraction (fPV), and the time intervals that extended until 120 days after sowing showed the best results for corn grain yield estimation.

ACS Style

Luan Peroni Venancio; Everardo Chartuni Mantovani; Cibele Hummel Do Amaral; Christopher Michael Usher Neale; Ivo Zution Gonçalves; Roberto Filgueiras; Fernando Coelho Eugenio. Potential of using spectral vegetation indices for corn green biomass estimation based on their relationship with the photosynthetic vegetation sub-pixel fraction. Agricultural Water Management 2020, 236, 106155 .

AMA Style

Luan Peroni Venancio, Everardo Chartuni Mantovani, Cibele Hummel Do Amaral, Christopher Michael Usher Neale, Ivo Zution Gonçalves, Roberto Filgueiras, Fernando Coelho Eugenio. Potential of using spectral vegetation indices for corn green biomass estimation based on their relationship with the photosynthetic vegetation sub-pixel fraction. Agricultural Water Management. 2020; 236 ():106155.

Chicago/Turabian Style

Luan Peroni Venancio; Everardo Chartuni Mantovani; Cibele Hummel Do Amaral; Christopher Michael Usher Neale; Ivo Zution Gonçalves; Roberto Filgueiras; Fernando Coelho Eugenio. 2020. "Potential of using spectral vegetation indices for corn green biomass estimation based on their relationship with the photosynthetic vegetation sub-pixel fraction." Agricultural Water Management 236, no. : 106155.

Journal article
Published: 31 March 2020 in Remote Sensing
Reads 0
Downloads 0

Evapotranspiration ( E T ) provides a strong connection between surface energy and hydrological cycles. Advancements in remote sensing techniques have increased our understanding of energy and terrestrial water balances as well as the interaction between surface and atmosphere over large areas. In this study, we computed surface energy fluxes using the Surface Energy Balance Algorithm for Land (SEBAL) algorithm and a simplified adaptation of the CIMEC (Calibration using Inverse Modeling at Extreme Conditions) process for automated endmember selection. Our main purpose was to assess and compare the accuracy of the automated calibration of the SEBAL algorithm using two different sources of meteorological input data (ground measurements from an eddy covariance flux tower and reanalysis data from Modern-Era Reanalysis for Research and Applications version 2 (MERRA-2)) to estimate the dry season partitioning of surface energy and water fluxes in a transitional area between tropical rainforest and savanna. The area is located in Brazil and is subject to deforestation and cropland expansion. The SEBAL estimates were validated using eddy covariance measurements (2004 to 2006) from the Large-Scale Biosphere-Atmosphere Experiment in the Amazon (LBA) at the Bananal Javaés (JAV) site. Results indicated a high accuracy for daily ET, using both ground measurements and MERRA-2 reanalysis, suggesting a low sensitivity to meteorological inputs. For daily ET estimates, we found a root mean square error (RMSE) of 0.35 mm day−1 for both observed and reanalysis meteorology using accurate quantiles for endmembers selection, yielding an error lower than 9% (RMSE compared to the average daily ET). Overall, the ET rates in forest areas were 4.2 mm day−1, while in grassland/pasture and agricultural areas we found average rates between 2.0 and 3.2 mm day−1, with significant changes in energy partitioning according to land cover. Thus, results are promising for the use of reanalysis data to estimate regional scale patterns of sensible heat (H) and latent heat (LE) fluxes, especially in areas subject to deforestation.

ACS Style

Leonardo Laipelt; Anderson Luis Ruhoff; Ayan Fleischmann; Rafael Henrique Bloedow Kayser; Elisa De Mello Kich; Humberto Ribeiro Da Rocha; Christopher Michael Usher Neale. Assessment of an Automated Calibration of the SEBAL Algorithm to Estimate Dry-Season Surface-Energy Partitioning in a Forest–Savanna Transition in Brazil. Remote Sensing 2020, 12, 1108 .

AMA Style

Leonardo Laipelt, Anderson Luis Ruhoff, Ayan Fleischmann, Rafael Henrique Bloedow Kayser, Elisa De Mello Kich, Humberto Ribeiro Da Rocha, Christopher Michael Usher Neale. Assessment of an Automated Calibration of the SEBAL Algorithm to Estimate Dry-Season Surface-Energy Partitioning in a Forest–Savanna Transition in Brazil. Remote Sensing. 2020; 12 (7):1108.

Chicago/Turabian Style

Leonardo Laipelt; Anderson Luis Ruhoff; Ayan Fleischmann; Rafael Henrique Bloedow Kayser; Elisa De Mello Kich; Humberto Ribeiro Da Rocha; Christopher Michael Usher Neale. 2020. "Assessment of an Automated Calibration of the SEBAL Algorithm to Estimate Dry-Season Surface-Energy Partitioning in a Forest–Savanna Transition in Brazil." Remote Sensing 12, no. 7: 1108.

Journal article
Published: 24 December 2019 in Water
Reads 0
Downloads 0

Accurate estimates of sensible (H) and latent (LE) heat fluxes and actual evapotranspiration (ET) are required for monitoring vegetation growth and improved agricultural water management. A large aperture scintillometer (LAS) was used to provide these estimates with the objective of quantifying the effects of surface heterogeneity due to soil moisture and vegetation growth variability. The study was conducted over drip-irrigated vineyards located in a semi-arid region in Albacete, Spain during summer 2007. Surface heterogeneity was characterized by integrating eddy covariance (EC) observations of H, LE and ET; land surface temperature (LST) and normalized difference vegetation index (NDVI) data from Landsat and MODIS sensors; LST from an infrared thermometer (IRT); a data fusion model; and a two-source surface energy balance model. The EC observations showed 16% lack of closure during unstable atmospheric conditions and was corrected using the residual method. The comparison between the LAS and EC measurements of H, LE, and ET showed root mean square difference (RMSD) of 25 W m−2, 19 W m−2, and 0.41 mm day−1, respectively. LAS overestimated H and underestimated both LE and ET by 24 W m−2, 34 W m−2, and 0.36 mm day−1, respectively. The effects of soil moisture on LAS measurement of H was evaluated using the Bowen ratio, β. Discrepancies between HLAS and HEC were higher at β ≤ 0.5 but improved at 1 ≥ β > 0.5 and β > 1.0 with R2 of 0.76, 0.78, and 0.82, respectively. Variable vineyard growth affected LAS performance as its footprints saw lower NDVILAS compared to that of the EC (NDVIEC) by ~0.022. Surface heterogeneity increased during wetter periods, as characterized by the LST–NDVI space and temperature vegetation dryness index (TVDI). As TVDI increased (decreased) during drier (wetter) conditions, the discrepancies between HLAS and HEC, as well as LELAS and LEEC Re decreased (increased). Thresholds of TVDI of 0.3, 0.25, and 0.5 were identified, above which better agreements between LAS and EC estimates of H, LE, and ET, respectively, were obtained. These findings highlight the effectiveness and ability of LAS in monitoring vegetation growth over heterogonous areas with variable soil moisture, its potential use in supporting irrigation scheduling and agricultural water management over large regions.

ACS Style

Hatim M. E. Geli; José González-Piqueras; Christopher M. U. Neale; Claudio Balbontín; Isidro Campos; Alfonso Calera. Effects of Surface Heterogeneity Due to Drip Irrigation on Scintillometer Estimates of Sensible, Latent Heat Fluxes and Evapotranspiration over Vineyards. Water 2019, 12, 81 .

AMA Style

Hatim M. E. Geli, José González-Piqueras, Christopher M. U. Neale, Claudio Balbontín, Isidro Campos, Alfonso Calera. Effects of Surface Heterogeneity Due to Drip Irrigation on Scintillometer Estimates of Sensible, Latent Heat Fluxes and Evapotranspiration over Vineyards. Water. 2019; 12 (1):81.

Chicago/Turabian Style

Hatim M. E. Geli; José González-Piqueras; Christopher M. U. Neale; Claudio Balbontín; Isidro Campos; Alfonso Calera. 2019. "Effects of Surface Heterogeneity Due to Drip Irrigation on Scintillometer Estimates of Sensible, Latent Heat Fluxes and Evapotranspiration over Vineyards." Water 12, no. 1: 81.

Article
Published: 20 December 2019 in Precision Agriculture
Reads 0
Downloads 0

Unmanned aerial systems (UAS) for collecting multispectral imagery of agricultural fields are becoming more affordable and accessible. However, there is need to validate calibration of sensors on these systems when using them for quantitative analyses such as evapotranspiration, and other modeling for agricultural applications. The results of laboratory testing of a MicaSense (Seattle, WA, USA) RedEdge™ 3 multispectral camera and MicaSense Downwelling Light Sensor (irradiance sensor) system using a calibrated integrating sphere were presented. Responses of the camera and irradiance sensor were linear over many light levels and became non-linear at light levels below expected real-world, field conditions. Simple linear corrections should suffice for most light conditions encountered during the growing season. Using an irradiance sensor or similar system may not properly account for light variability in cloudy or partly cloudy conditions as also identified by others. A simple stand for aiding in reference panel imaging was also described, which may facilitate repetitive, consistent reference panel imaging.

ACS Style

J. Burdette Barker; Wayne E. Woldt; Brian D. Wardlow; Christopher M. U. Neale; Mitchell S. Maguire; Bryan C. Leavitt; Derek M. Heeren. Calibration of a common shortwave multispectral camera system for quantitative agricultural applications. Precision Agriculture 2019, 21, 922 -935.

AMA Style

J. Burdette Barker, Wayne E. Woldt, Brian D. Wardlow, Christopher M. U. Neale, Mitchell S. Maguire, Bryan C. Leavitt, Derek M. Heeren. Calibration of a common shortwave multispectral camera system for quantitative agricultural applications. Precision Agriculture. 2019; 21 (4):922-935.

Chicago/Turabian Style

J. Burdette Barker; Wayne E. Woldt; Brian D. Wardlow; Christopher M. U. Neale; Mitchell S. Maguire; Bryan C. Leavitt; Derek M. Heeren. 2019. "Calibration of a common shortwave multispectral camera system for quantitative agricultural applications." Precision Agriculture 21, no. 4: 922-935.

Journal article
Published: 04 December 2019 in Earth and Space Science
Reads 0
Downloads 0

Estimation of turbulent heat fluxes via variational data assimilation (VDA) approaches has been the subject of several studies. The VDA approaches need an adjoint model that is difficult to derive. In this study, remotely sensed land surface temperature (LST) data from Moderate Resolution Imaging Spectroradiometer (MODIS) are assimilated into the heat diffusion equation within an ensemble Kalman smoother (EnKS) approach to estimate turbulent heat fluxes. The EnKS approach is tested in the Heihe River Basin (HRB) in northwest China. The results show that the EnKS approach can estimate turbulent heat fluxes by assimilating low temporal resolution LST data from MODIS. The findings indicate that the EnKS approach perform fairly well in various hydrological and vegetative conditions. The estimated sensible (H) and latent (LE) heat fluxes are compared with the corresponding observations from large aperture scintillometer systems (LAS) at three sites (namely, Arou, Daman, and Sidaoqiao) in the HRB. The turbulent heat flux estimates from EnKS agree reasonably well with the observations, and are comparable to those of the VDA approach. The EnKS approach also provides statistical information on the H and LE estimates. It is found that the uncertainties of H and LE estimates are higher over wet and/or densely vegetated areas (grassland and forest) compared to the dry and/or slightly vegetated areas (cropland, shrubland, and barren land).

ACS Style

Xinlei He; Tongren Xu; Sayed M. Bateni; Christopher M.U. Neale; Shaomin Liu; Thomas Auligne; Kaicun Wang; Shoudong Zhu. Mapping Regional Turbulent Heat Fluxes via Assimilation of MODIS Land Surface Temperature Data into an Ensemble Kalman Smoother Framework. Earth and Space Science 2019, 6, 2423 -2442.

AMA Style

Xinlei He, Tongren Xu, Sayed M. Bateni, Christopher M.U. Neale, Shaomin Liu, Thomas Auligne, Kaicun Wang, Shoudong Zhu. Mapping Regional Turbulent Heat Fluxes via Assimilation of MODIS Land Surface Temperature Data into an Ensemble Kalman Smoother Framework. Earth and Space Science. 2019; 6 (12):2423-2442.

Chicago/Turabian Style

Xinlei He; Tongren Xu; Sayed M. Bateni; Christopher M.U. Neale; Shaomin Liu; Thomas Auligne; Kaicun Wang; Shoudong Zhu. 2019. "Mapping Regional Turbulent Heat Fluxes via Assimilation of MODIS Land Surface Temperature Data into an Ensemble Kalman Smoother Framework." Earth and Space Science 6, no. 12: 2423-2442.

Journal article
Published: 22 November 2019 in Agricultural Water Management
Reads 0
Downloads 0

The increasing pressure on water resources in Nebraska-US and other agricultural areas requires the implementation of innovative tools and solutions for the governance of water resources and the analysis of water use efficiency. In this vein, this paper presents the application of a remote sensing based soil water balance for the study of water use in agricultural areas. The specific objectives were the identification of the temporal and spatial behavior of the irrigation water use based on the quantification of the water use deviation (irrigation water applied minus irrigation water requirements), as the main indicator and the comparative analysis of the irrigation productivity (crop yield under irrigated field minus crop yield under rainfed condition per volume of water applied by irrigation), WPi, water productivity (harvestable grain per total volume of water applied considering precipitation plus irrigation), WP, and finally water productivity based on evapotranspiration (harvested grain per total volume of water evapotranspired), WPET, in the various management zones analyzed. Additionally, we examined the impact of soil types, local weather and irrigation system (center pivot and furrow irrigation) on these indicators. The study was carried out in three Natural Resources District (Tri-Basin, Central Platte and Lower Niobrara) across Central Nebraska for the period 2004–2012 and comprised over 2000 irrigated corn fields per year. Crop water requirements were estimated using the reflectance-based crop coefficient approach developed in previous research (see Campos et al., 2017) and the field data were reported for each field monitored through cropland data layer by National Agricultural Statistics Service of USDA. The difference between modeled irrigation water requirements and field level irrigation application was significant (p < 0.001) being the water use deviation in generally positive (over irrigation). These results were consistently higher for furrow irrigated fields during the whole analyzed period, reaching up to three times more water applied compared to the required amount. This was expected as surface irrigation systems typically require a higher application depth. This trend changed for the central pivot irrigated fields depending on the climatic conditions, especially in dry years. The analysis of the water use deviation with respect to soil types and weather conditions revealed that the water use deviation is not justified by the biophysical conditions alone. The estimated values of WP and WPi for furrow system was lower compared to center pivot in both NRD’s reaching the maximum value of 1.37 kg m-3 and 3.06 kg m-3 for WP and WPi in Tri-basin respectively for center pivot. In general, the results suggested potential to improve water management in these NRDs in Central Nebraska and reduce pumping potentially saving groundwater resources for drought years and other uses monitoring soil type, weather data and switching to sprinklers system.

ACS Style

Ivo Zution Gonçalves; Mesfin Mekonnen; Christopher M.U. Neale; Isidro Campos; Michael R. Neale. Temporal and spatial variations of irrigation water use for commercial corn fields in Central Nebraska. Agricultural Water Management 2019, 228, 105924 .

AMA Style

Ivo Zution Gonçalves, Mesfin Mekonnen, Christopher M.U. Neale, Isidro Campos, Michael R. Neale. Temporal and spatial variations of irrigation water use for commercial corn fields in Central Nebraska. Agricultural Water Management. 2019; 228 ():105924.

Chicago/Turabian Style

Ivo Zution Gonçalves; Mesfin Mekonnen; Christopher M.U. Neale; Isidro Campos; Michael R. Neale. 2019. "Temporal and spatial variations of irrigation water use for commercial corn fields in Central Nebraska." Agricultural Water Management 228, no. : 105924.

Journal article
Published: 23 August 2019 in Geoderma
Reads 0
Downloads 0

It is known that the soil type and its characteristics are very important to the agriculture and to maintain the health of a forest. Thus, the objective of this work was to verify, through multivariate statistical analysis techniques, the variations of evapotranspiration values as a function of the soil type in three different vegetation cover areas: sugarcane, planted forest and native forest. For this, an area of 2231.926 km2 was chosen, using monthly Landsat 8 satellite imagery with Orbit/Path 220 and Point/Row 75, between latitudes 20°43′55.2″S and 22°36′28.8″S and longitudes 46°37′48,0″W and 48°50′16,8″W, in the region of Corumbataí, northeast of the State of São Paulo, Brazil, collected over 24 months between April 2013 and March 2015. The evapotranspiration evaluation was obtained by satellite imagery using a hybrid model of the Two Source Energy Balance (TSEB), with a proposed adjustment methodology to convert hourly ET to monthly and annually data. The multivariate statistical analysis of monthly ET patterns across soil type classified three evapotranspiration groups in the three studied land cover areas. In the areas with sugarcane, evapotranspiration separated statistical groups in the areas of the Cerrado biome with Ferralsol (LVA) and Lithic Leptosol (RL), another group in the areas with Ferralsol (LV) and Ferralic Arenosol (RQ), and a third group of Acrisol (PVA) in an Atlantic Forest biome area. In the areas with planted forest and native forest, evapotranspiration separated a first group with soils LVA, RQ, PVA, Dystric Gleysol (GX) and RL in areas of Cerrado, a second group with LV in Atlantic Forest area and a third group just with Fibric Histosol (OY).

ACS Style

Raoni W.D. Bosquilia; Christopher M.U. Neale; Sergio N. Duarte; Solon J. Longhi; Silvio F. De B. Ferraz; Frank E. Muller-Karger. Evaluation of evapotranspiration variations according to soil type using multivariate statistical analysis. Geoderma 2019, 355, 113906 .

AMA Style

Raoni W.D. Bosquilia, Christopher M.U. Neale, Sergio N. Duarte, Solon J. Longhi, Silvio F. De B. Ferraz, Frank E. Muller-Karger. Evaluation of evapotranspiration variations according to soil type using multivariate statistical analysis. Geoderma. 2019; 355 ():113906.

Chicago/Turabian Style

Raoni W.D. Bosquilia; Christopher M.U. Neale; Sergio N. Duarte; Solon J. Longhi; Silvio F. De B. Ferraz; Frank E. Muller-Karger. 2019. "Evaluation of evapotranspiration variations according to soil type using multivariate statistical analysis." Geoderma 355, no. : 113906.

Journal article
Published: 09 December 2018 in Remote Sensing
Reads 0
Downloads 0

A number of studies have estimated turbulent heat fluxes by assimilating sequences of land surface temperature (LST) observations into the strong constraint-variational data assimilation (SC-VDA) approaches. The SC-VDA approaches do not account for the structural model errors and uncertainties in the micrometeorological variables. In contrast to the SC-VDA approaches, the WC-VDA approach (the so-called weak constraint-VDA) accounts for the effects of structural and model errors by adding a model error term. In this study, the WC-VDA approach is tested at six study sites with different climatic and vegetative conditions. Its performance is also compared with that of SC-VDA at the six study sites. The results show that the WC-VDA produces 10.16% and 10.15% lower root mean square errors (RMSEs) for sensible and latent heat flux estimates compared with the SC-VDA approach. The model error term can capture errors in the turbulent heat flux estimates due to errors in LST and micrometeorological measurements, as well as structural model errors, and does not allow those errors to adversely affect the turbulent heat flux estimates. The findings also indicate that the estimated model error term varies reasonably well, so as to capture the misfit between predicted and observed net radiation in different hydrological and vegetative conditions. Finally, synthetically generated positive (negative) noises are added to the hydrological input variables (e.g., LST, air temperature, air humidity, incoming solar radiation, and wind speed) to examine whether the WC-VDA approach can capture those errors. It was found that the WC-VDA approach accounts for the errors in the input data and reduces their effect on the turbulent heat flux estimates.

ACS Style

Xinlei He; Tongren Xu; Sayed M. Bateni; Christopher M. U. Neale; Thomas Auligne; Shaomin Liu; Kaicun Wang; Kebiao Mao; Yunjun Yao. Evaluation of the Weak Constraint Data Assimilation Approach for Estimating Turbulent Heat Fluxes at Six Sites. Remote Sensing 2018, 10, 1994 .

AMA Style

Xinlei He, Tongren Xu, Sayed M. Bateni, Christopher M. U. Neale, Thomas Auligne, Shaomin Liu, Kaicun Wang, Kebiao Mao, Yunjun Yao. Evaluation of the Weak Constraint Data Assimilation Approach for Estimating Turbulent Heat Fluxes at Six Sites. Remote Sensing. 2018; 10 (12):1994.

Chicago/Turabian Style

Xinlei He; Tongren Xu; Sayed M. Bateni; Christopher M. U. Neale; Thomas Auligne; Shaomin Liu; Kaicun Wang; Kebiao Mao; Yunjun Yao. 2018. "Evaluation of the Weak Constraint Data Assimilation Approach for Estimating Turbulent Heat Fluxes at Six Sites." Remote Sensing 10, no. 12: 1994.

Journal article
Published: 27 November 2018 in Ecohydrology & Hydrobiology
Reads 0
Downloads 0

Knowing the variation of the water consumption of a crop or vegetation can help to avoid damages caused by the lack of water, besides allowing a better knowledge of the environment around. Thus, variations in evapotranspiration in sugarcane, planted forest, and native forest were examined as a function of relief variations and terrain exposure in the northeast sector of the State of São Paulo, Brazil (20°43′55.2″S–22°36′28.8″S, 46°37′48.0″W–48°50′16.8″W). These areas, covering a total of 2232 km2, were studied using monthly Landsat 8 satellite data (Path 220 and Row 75) collected over 24 months from April 2013 to March 2015. Thus, this study aimed to use a hybrid Two Source Energy Balance (TSEB), adjusted to convert hourly ET to monthly and annually data, in obtaining ET for two years to areas with sugarcane, planted and native forests and evaluate how this evapotranspiration behaves spatially for some parameters, as altitude, slope, exposure faces of the terrain and biomes, using multivariate analysis. The results identified three evapotranspiration groups: highest evapotranspiration in the highest altitudes and topographic slope; medium evapotranspiration in medium altitudes and slopes; and low evapotranspiration at low altitudes and slopes. The highest rates of evaporation occurred in summer and fall, when temperatures were highest.

ACS Style

Raoni W.D. Bosquilia; Christopher M.U. Neale; Sergio N. Duarte; Solon J. Longhi; Silvio F. De B. Ferraz; Frank E. Muller-Karger; Matthew J. McCarthy. Evaluation of evapotranspiration variations as a function of relief and terrain exposure through multivariate statistical analysis. Ecohydrology & Hydrobiology 2018, 19, 307 -315.

AMA Style

Raoni W.D. Bosquilia, Christopher M.U. Neale, Sergio N. Duarte, Solon J. Longhi, Silvio F. De B. Ferraz, Frank E. Muller-Karger, Matthew J. McCarthy. Evaluation of evapotranspiration variations as a function of relief and terrain exposure through multivariate statistical analysis. Ecohydrology & Hydrobiology. 2018; 19 (2):307-315.

Chicago/Turabian Style

Raoni W.D. Bosquilia; Christopher M.U. Neale; Sergio N. Duarte; Solon J. Longhi; Silvio F. De B. Ferraz; Frank E. Muller-Karger; Matthew J. McCarthy. 2018. "Evaluation of evapotranspiration variations as a function of relief and terrain exposure through multivariate statistical analysis." Ecohydrology & Hydrobiology 19, no. 2: 307-315.

Accepted manuscript
Published: 21 November 2018 in Environmental Research Letters
Reads 0
Downloads 0

Understanding how irrigation is used across agricultural landscapes is essential to support efforts to grow more food while reducing pressures on limited freshwater resources. However, to date, few studies have analyzed the underlying spatial and temporal variability in farmers' individual water use decisions at a landscape scale. We compare estimates of irrigation water requirements derived using state-of-the-art remote sensing models with metered abstraction records for 1,400 fields over a 13-year period in the U.S. state of Nebraska, one of the world's most intensively irrigated agricultural regions. We show that farmers' observed water use decisions often diverge significantly from biophysical estimates of crop irrigation requirements. In particular, our findings are consistent with widespread use of water conservation practices by farmers in drought years as an adaptive response to rising irrigation costs and regulatory water supply constraints in these years. We also demonstrate that, in any individual year, farmers' observed water use exhibits large field-to-field variability, which cannot be explained fully by differences in weather, soil type, crop choice, or technology. Our results highlight the value of using both in-situ monitoring and remote sensing to evaluate farmers' individual water use behavior and understand likely responses to future changes in climate or water policy. Moreover, our findings also demonstrate potential challenges for current efforts in developed and developing countries to apply model-based approaches for field-level water use accounting and enforcement of irrigation water rights.

ACS Style

Timothy Foster; Ivo Zution Gonçalves; Isidro Campos; Christopher M.U Neale; Nicholas Brozovic. Assessing landscape scale heterogeneity in irrigation water use with remote sensing and in situ monitoring. Environmental Research Letters 2018, 14, 024004 .

AMA Style

Timothy Foster, Ivo Zution Gonçalves, Isidro Campos, Christopher M.U Neale, Nicholas Brozovic. Assessing landscape scale heterogeneity in irrigation water use with remote sensing and in situ monitoring. Environmental Research Letters. 2018; 14 (2):024004.

Chicago/Turabian Style

Timothy Foster; Ivo Zution Gonçalves; Isidro Campos; Christopher M.U Neale; Nicholas Brozovic. 2018. "Assessing landscape scale heterogeneity in irrigation water use with remote sensing and in situ monitoring." Environmental Research Letters 14, no. 2: 024004.

Journal article
Published: 01 August 2018 in Computers and Electronics in Agriculture
Reads 0
Downloads 0

It is known that vegetation needs a certain amount of water to grow and develop. However, it can be difficult to know the actual water requirement of a specific crop. To quantify the hydric balance in hydrographic basins, detailed knowledge of the components of the hydrological cycle is necessary, especially regarding evapotranspiration (ET). Knowledge of ET of crops and forests, in general, is important at all stages of production management of the vegetation cover. Many studies have been developed with the aim of obtaining these values spatially, but temporal variability remains largely uncertain. Thus, the present study had the objective of utilizing a hybrid Two-Source Energy Balance (TSEB), adjusted to integrate hourly, monthly and yearly ET data, aiming at obtaining ET for two years of study, for areas with sugar cane, planted forest and native forest. How evapotranspiration behaves temporally could then be evaluated. Therefore, after analyzing monthly, seasonal and annual results it could be concluded that sugar cane consumes less water than planted forest and native forest with the same rainfall and environment for all uses.

ACS Style

Raoni W.D. Bosquilia; Christopher M.U. Neale; Sérgio N. Duarte; Solon J. Longhi; Silvio F. De B. Ferraz; Frank E. Muller-Karger; Matthew J. McCarthy. Temporal evaluation of evapotranspiration for sugar cane, planted forest and native forest using landsat 8 images and a two-source energy balance. Computers and Electronics in Agriculture 2018, 151, 70 -76.

AMA Style

Raoni W.D. Bosquilia, Christopher M.U. Neale, Sérgio N. Duarte, Solon J. Longhi, Silvio F. De B. Ferraz, Frank E. Muller-Karger, Matthew J. McCarthy. Temporal evaluation of evapotranspiration for sugar cane, planted forest and native forest using landsat 8 images and a two-source energy balance. Computers and Electronics in Agriculture. 2018; 151 ():70-76.

Chicago/Turabian Style

Raoni W.D. Bosquilia; Christopher M.U. Neale; Sérgio N. Duarte; Solon J. Longhi; Silvio F. De B. Ferraz; Frank E. Muller-Karger; Matthew J. McCarthy. 2018. "Temporal evaluation of evapotranspiration for sugar cane, planted forest and native forest using landsat 8 images and a two-source energy balance." Computers and Electronics in Agriculture 151, no. : 70-76.

Journal article
Published: 01 April 2018 in Agricultural Water Management
Reads 0
Downloads 0

Improvements in soil water balance modeling can be beneficial for optimizing irrigation management to account for spatial variability in soil properties and evapotranspiration (ET). A remote-sensing-based ET and water balance model was tested for irrigation management in an experiment at two University of Nebraska-Lincoln research sites located near Mead and Brule, Nebraska. Both fields included a center pivot equipped with variable rate irrigation (VRI). The study included maize in 2015 and 2016 and soybean in 2016 at Mead, and maize in 2016 at Brule, for a total of 210 plot-years. Four irrigation treatments were applied at Mead, including: VRI based on a remote sensing model (VRI-RS); VRI based on neutron probe soil water content measurement (VRI-NP); uniform irrigation based on neutron probe measurement; and rainfed. Only the VRI-RS and uniform treatments were applied at Brule. Landsat 7 and 8 imagery were used for model input. In 2015, the remote sensing model included reflectance-based crop coefficients for ET estimation in the water balance. In 2016, a hybrid component of the model was activated, which included energy-balance-modeled ET as input. Both 2015 and 2016 had above-average precipitation at Mead; subsequently, irrigation amounts were relatively low. Seasonal irrigation was greatest for the VRI-RS treatment in all cases because of drift in the water balance model. This was likely caused by excessive soil evaporation estimates. Irrigation application for the VRI-NP at Mead was about 0 to 12 mm less than for the uniform treatment. Irrigation for the VRI-RS was about 40 to 98 mm greater than uniform at Mead and about 18 mm greater at Brule. For maize at Mead, treatment effects were primarily limited to hydrologic responses (e.g., ET), with differences in yield generally attributed to random error. Rainfed soybean yields were greater than VRI-RS yields, which may have been related to yield loss from lodging, perhaps due to over-irrigation. Regarding the magnitude of spatial variability in the fields, soil available water capacity generally ranked above ET, precipitation, and yield. Future research should include increased cloud-free imagery frequency, incorporation of soil water content measurements into the model, and improved wet soil evaporation and drainage estimates.

ACS Style

J. Burdette Barker; Derek M. Heeren; Christopher M.U. Neale; Daran R. Rudnick. Evaluation of variable rate irrigation using a remote-sensing-based model. Agricultural Water Management 2018, 203, 63 -74.

AMA Style

J. Burdette Barker, Derek M. Heeren, Christopher M.U. Neale, Daran R. Rudnick. Evaluation of variable rate irrigation using a remote-sensing-based model. Agricultural Water Management. 2018; 203 ():63-74.

Chicago/Turabian Style

J. Burdette Barker; Derek M. Heeren; Christopher M.U. Neale; Daran R. Rudnick. 2018. "Evaluation of variable rate irrigation using a remote-sensing-based model." Agricultural Water Management 203, no. : 63-74.

Journal article
Published: 01 January 2018 in Transactions of the ASABE
Reads 0
Downloads 0

Accurate generation of spatial soil water maps is useful for many types of irrigation management. A hybrid remote sensing evapotranspiration (ET) model combining reflectance-based basal crop coefficients (Kcbrf) and a two-source energy balance (TSEB) model was modified and validated for use in real-time irrigation management. We modeled spatial ET for maize and soybean fields in eastern Nebraska for the 2011-2013 growing seasons. We used Landsat 5, 7, and 8 imagery as remote sensing inputs. In the TSEB, we used the Priestly-Taylor (PT) approximation for canopy latent heat flux, as in the original model formulations. We also used the Penman-Monteith (PM) approximation for comparison. We compared energy balance fluxes and computed ET with measurements from three eddy covariance systems within the study area. Net radiation was underestimated by the model when data from a local weather station were used as input, with mean bias error (MBE) of -33.8 to -40.9 W m-2. The measured incident solar radiation appeared to be biased low. The net radiation model performed more satisfactorily when data from the eddy covariance flux towers were input into the model, with MBE of 5.3 to 11.2 W m-2. We removed bias in the daily energy balance ET using a dimensionless multiplier that ranged from 0.89 to 0.99. The bias-corrected TSEB ET, using weather data from a local weather station and with local ground data in thermal infrared imagery corrections, had MBE = 0.09 mm d-1 (RMSE = 1.49 mm d-1) for PM and MBE = 0.04 mm d-1 (RMSE = 1.18 mm d-1) for PT. The hybrid model used statistical interpolation to combine the two ET estimates. We computed weighting factors for statistical interpolation to be 0.37 to 0.50 for the PM method and 0.56 to 0.64 for the PT method. Provisions were added to the model, including a real-time crop coefficient methodology, which allowed seasonal crop coefficients to be computed with relatively few remote sensing images. This methodology performed well when compared to basal crop coefficients computed using a full season of input imagery. Water balance ET compared favorably with the eddy covariance data after incorporating the TSEB ET. For a validation dataset, the magnitude of MBE decreased from -0.86 mm d-1 (RMSE = 1.37 mm d-1) for the Kcbrf alone to -0.45 mm d-1 (RMSE = 0.98 mm d-1) and -0.39 mm d-1 (RMSE = 0.95 mm d-1) with incorporation of the TSEB ET using the PM and PT methods, respectively. However, the magnitudes of MBE and RMSE were increased for a running average of daily computations in the full May-October periods. The hybrid model did not necessarily result in improved model performance. However, the water balance model is adaptable for real-time irrigation scheduling and may be combined with forecasted reference ET, although the low temporal frequency of satellite imagery is expected to be a challenge in real-time irrigation management. Keywords: Center-pivot irrigation, ET estimation methods, Evapotranspiration, Irrigation scheduling, Irrigation water balance, Model validation, Variable-rate irrigation.

ACS Style

J. Burdette Barker; Christopher M. U. Neale; Derek M. Heeren; Andrew E. Suyker. Evaluation of a Hybrid Reflectance-Based Crop Coefficient and Energy Balance Evapotranspiration Model for Irrigation Management. Transactions of the ASABE 2018, 61, 533 -548.

AMA Style

J. Burdette Barker, Christopher M. U. Neale, Derek M. Heeren, Andrew E. Suyker. Evaluation of a Hybrid Reflectance-Based Crop Coefficient and Energy Balance Evapotranspiration Model for Irrigation Management. Transactions of the ASABE. 2018; 61 (2):533-548.

Chicago/Turabian Style

J. Burdette Barker; Christopher M. U. Neale; Derek M. Heeren; Andrew E. Suyker. 2018. "Evaluation of a Hybrid Reflectance-Based Crop Coefficient and Energy Balance Evapotranspiration Model for Irrigation Management." Transactions of the ASABE 61, no. 2: 533-548.

Journal article
Published: 01 July 2017 in Agricultural Water Management
Reads 0
Downloads 0
ACS Style

J. Burdette Barker; Trenton E. Franz; Derek M. Heeren; Christopher M.U. Neale; Joe D. Luck. Soil water content monitoring for irrigation management: A geostatistical analysis. Agricultural Water Management 2017, 188, 36 -49.

AMA Style

J. Burdette Barker, Trenton E. Franz, Derek M. Heeren, Christopher M.U. Neale, Joe D. Luck. Soil water content monitoring for irrigation management: A geostatistical analysis. Agricultural Water Management. 2017; 188 ():36-49.

Chicago/Turabian Style

J. Burdette Barker; Trenton E. Franz; Derek M. Heeren; Christopher M.U. Neale; Joe D. Luck. 2017. "Soil water content monitoring for irrigation management: A geostatistical analysis." Agricultural Water Management 188, no. : 36-49.

Journal article
Published: 01 June 2017 in Agricultural Water Management
Reads 0
Downloads 0
ACS Style

Isidro Campos; Christopher M.U. Neale; Andrew E. Suyker; Timothy J. Arkebauer; Ivo Z. Gonçalves. Reflectance-based crop coefficients REDUX: For operational evapotranspiration estimates in the age of high producing hybrid varieties. Agricultural Water Management 2017, 187, 140 -153.

AMA Style

Isidro Campos, Christopher M.U. Neale, Andrew E. Suyker, Timothy J. Arkebauer, Ivo Z. Gonçalves. Reflectance-based crop coefficients REDUX: For operational evapotranspiration estimates in the age of high producing hybrid varieties. Agricultural Water Management. 2017; 187 ():140-153.

Chicago/Turabian Style

Isidro Campos; Christopher M.U. Neale; Andrew E. Suyker; Timothy J. Arkebauer; Ivo Z. Gonçalves. 2017. "Reflectance-based crop coefficients REDUX: For operational evapotranspiration estimates in the age of high producing hybrid varieties." Agricultural Water Management 187, no. : 140-153.

Journal article
Published: 01 October 2016 in Remote Sensing of Environment
Reads 0
Downloads 0

This paper describes the image acquisition and processing methodology, including surface emissivity and atmospheric corrections, for generating surface temperatures of two active hydrothermal systems in Yellowstone National Park. Airborne thermal infrared (8–12 μm) images were obtained annually from 2007 to 2012 using a FLIR SC640 thermal infrared camera system. Thermal infrared image acquisitions occurred under clear-sky conditions after sunset to meet the objective of providing high-spatial resolution, georectified imagery for hydrothermal monitoring. Comparisons of corrected radiative temperature maps with measured ground and water kinetic temperatures at flight times provided an assessment of temperature accuracy. A repeatable, time-sequence of images for Hot Spring Basin (2007–2012) and Norris Geyser Basin (2008–2012) documented fracture-related changes in temperature and fluid flow for both hydrothermal systems, highlighting the utility of methods for synoptic monitoring of Yellowstone National Park's hydrothermal systems.

ACS Style

C.M.U. Neale; C. Jaworowski; H. Heasler; Saravanan Sivarajan; A. Masih. Hydrothermal monitoring in Yellowstone National Park using airborne thermal infrared remote sensing. Remote Sensing of Environment 2016, 184, 628 -644.

AMA Style

C.M.U. Neale, C. Jaworowski, H. Heasler, Saravanan Sivarajan, A. Masih. Hydrothermal monitoring in Yellowstone National Park using airborne thermal infrared remote sensing. Remote Sensing of Environment. 2016; 184 ():628-644.

Chicago/Turabian Style

C.M.U. Neale; C. Jaworowski; H. Heasler; Saravanan Sivarajan; A. Masih. 2016. "Hydrothermal monitoring in Yellowstone National Park using airborne thermal infrared remote sensing." Remote Sensing of Environment 184, no. : 628-644.