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The Haihe Plain is the largest component of the agriculturally vital North China Plain, and it is characterized by serious water shortage and frequent droughts, which lead to crop reduction and have adverse effects on agriculture and ecology. We used daily precipitation data from 1955–2017; the region’s spatiotemporal characteristics of drought were analyzed by using the standardized precipitation index (SPI), drought probability, and Mann–Kendall test for seasonal scale including two main crops growth seasons for the region’s main crops. Furthermore, a cloud algorithm model was established to analyze the dispersion and instability of the SPI. The annual drought frequency is 28.57%; the SPI for spring has an increasing tendency, while summer shows a significant decreasing trend (p < 0.05); the Haihe Plain has had a tendency towards drought over the last 63 years. The SPI in northwest is the smallest and increases gradually toward the south; the severity of drought in dry years increased from southeast to northwest. The cloud model shows that the SPI randomness of each site decreased significantly and tended to be stable and uniform. The deterministic and stable SPI of each station is stronger in dry years, and the randomness and instability are stronger in wet years. The inter-annual differences of the characteristic values of the SPI cloud model are bigger than the differences among sites, and the inter-annual randomness and inhomogeneity of the SPI are higher.

Changes in pollutant concentrations in environmental media occur both from pollutant transport in water or air and from local processes, such as adsorption, degradation, precipitation, straining, and so on. The terms "fate and transport" and "transport and fate" reflect the coupling of moving with the carrier media and biogeochemical processes describing local transformations or interactions. The Journal of Environmental Quality (JEQ) was one of the first to publish papers on fate and transport (F&T). This paper is a minireview written to commemorate the 50th anniversary of JEQ and show how the research interests, methodology, and public attention have been reflected in fate and transport publications in JEQ during the last 40 years. We report the statistics showing how the representation of different pollutant groups in papers changed with time. Major focus areas have included the effect of solution composition on F&T and concurrent F&T, the role of organic matter, and the relative role of different F&T pathways. The role of temporal and spatial heterogeneity has been studied at different scales. The value of long-term F&T studies and developments in modeling as the F&T research approach was amply demonstrated. Fate and transport studies have been an essential part of conservation measure evaluation and comparison and ecological risk assessment. For 50 years, JEQ has delivered new insights, methods, and applications related to F&T science. The importance of its service to society is recognized, and we look forward to new generations of F&T researchers presenting their contributions in JEQ.

Soil salinity increases when growers are forced to use higher salinity irrigation waters due to water shortages. It is necessary to estimate the impact of irrigation water on soil properties and conditions for crop growth to manage the effects of salinity on perennial crops. Therefore, in this study, we monitored root zone salinity in five almond and pistachio orchards in eastern and western San Joaquin Valley (SJV), California (CA). Volumetric soil water contents and bulk electrical conductivities were measured at four root-zone depths. Evapotranspiration was measured by eddy covariance along with three other types of data. The first is seasonal precipitation and irrigation patterns, including the temporal distribution of rains, irrigation events, and irrigation water salinity. The second is soil chemistry, including the initial sodium adsorption ratio (SAR) and soil solute electrical conductivity (ECe). The third type is the physical properties, including soil type, hydraulic conductivity, and bulk density. As expected, we found low salinity at the eastern sites and higher salinity at the western sites. The western sites have finer textured soils and lower quality irrigation water, measured actual ET was about 90% of modeled crop ET. Across the three western sites, the annual average apparent leaching fraction ranged from 11 to 28%. At the eastern sites, measured ET almost exactly matched modeled crop ET each year. Apparent leaching fractions in the eastern sites were approximately 20%.

Second generation biofuels, such as perennial grasses, have potential to provide biofuel feedstock while growing on degraded land with minimal inputs. Perennial grasses have been reported to sequester large amounts of soil organic carbon (SOC) in the Midwestern United States (USA). However, there has been little work on biofuel and carbon sequestration potential of perennial grasses in the Southeastern US. Biofuel productivity for dryland Miscanthus × gigantus and irrigated maize in Georgia, USA were quantified using eddy covariance observations of evapotranspiration (ET) and net ecosystem exchange (NEE) of carbon. Miscanthus biomass yield was 15.54 Mg ha−1 in 2015 and 11.80 Mg ha−1 in 2016, while maize produced 30.20 Mg ha−1 of biomass in 2016. Carbon budgets indicated that both miscanthus and maize fields lost carbon over the experiment. The miscanthus field lost 5 Mg C ha−1 in both 2015 and 2016 while the maize field lost 1.37 Mg C ha−1 for the single year of study. Eddy covariance measurement indicated that for 2016 the miscanthus crop evapotranspired 598 mm and harvest water use efficiencies ranged from 6.95 to 13.84 kg C ha−1 mm−1. Maize evapotranspired 659 mm with a harvest water use efficiency of 19.12 kg C ha−1 mm−1. While biomass yields and gross primary production were relatively high, high ecosystem respiration rates resulted in a loss of ecosystem carbon. Relatively low biomass production, low water use efficiency and high respiration for Miscanthus × gigantus in this experiment suggest that this strain of miscanthus may not be well-suited for dryland production under the environmental conditions found in South Georgia USA.

The ECOsystem Space Thermal Radiometer Experiment on the Space Station (ECOSTRESS) was launched to the International Space Station on June 29, 2018 by the National Aeronautics and Space Administration (NASA). The primary scientific focus of ECOSTRESS is on evapotranspiration (ET), which occurs as Level 3 (L3) latent heat flux (LE) data products. This data is generated from the Level 2 Earth Surface Temperature and Emissivity Product (L2_LSTE), along with the atmospheric and ancillary surface data. Here, we provide the first validation (Stage 1, preliminary) of the global product ECOSTRESS clear - sky ET (L3_ET_PT - JPL, Version 6.0) against LE measurements at 82 eddy covariance sites around the world. Overall, the ECOSTRESS ET product performs well against site measurements (instant clear sky / flyover time: r 2 = 0.88; overall bias = 8%; normalized root mean square error, RMSE = 6%) . ET uncertainty was generally constant across climate zones, biome types, and times of day (ECOSTRESS samples the diurnal cycle), although temperate sites are over-represented. ECOSTRESS 70 m high spatial resolution improved correlations by 85% and RMSE by 62%, relative to 1 km pixels. This document serves as a reference for the accuracy of ECOSTRESS L3 ET and the Stage 1 validation status for subsequent science that continues to use this data. Fil: Fisher, Joshua B. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Lee, Brian. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Purdy, Adam J. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Halverson, Gregory H. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Dohlen, Matthew B. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Cawse - Nicholson, Kerry. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Wang, Audrey. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Anderson, Ray G. U.S. Department of Agriculture; Estados Unidos Fil: Aragon, Bruno. King Abdullah University of Science and Technology. Division of Biological and Environmental Science and Engineering. Hydrology, Agriculture and Land Observation Group (HALO); Arabia Saudita Fil: Arain, M. Alfat. McMaster University. School of Geography and Earth Sciences; Canadá Fil: Baldocchi, Dennis D. University of California, Berkeley. Department of Environmental Science, Policy and Management; Estados Unidos Fil: Baker, John M. U.S. Department of Agriculture; Estados Unidos Fil: Barral, Helene. University Montpellier. HydroSciences Montpellier (HSM); Francia Fil: Bernacchi, Carl J. University of Illinois Urbana‐Champaign. Institute for Sustainability, Energy, and Environment and Carl R. Woese Institute for Genomic Biology. Center for Advanced Bioenergy and Bioproducts Innovation; Estados Unidos. U.S. Department of Agriculture, Global Change and Photosynthesis Research Unit; Estados Unidos Fil: Bernhofer, Christian. Technische Universität Dresden, Institute of Hydrology and Meteorology; Alemania Fil: Biraud, Sebastien C. Lawrence Berkeley National Laboratory; Estados Unidos Fil: Bohrer, Gil. Ohio State University. Department of Civil, Environmental and Geodetic Engineering; Estados Unidos Fil: Brunsell, Nathaniel. University of Kansas. Department of Geography and Atmospheric Science; Estados Unidos Fil: Cappelaere, Bernard. University Montpellier. HydroSciences Montpellier (HSM); Francia Fil: Castro - Contreras, Saulo. University of Alberta. Earth and Atmospheric Sciences Department. Centre for Earth Observation Sciences (CEOS); Canadá Fil: Chum, Junghwa. National Institute of Forest Science; Corea del Sur Fil: Conrad, Bryan. University of Kansas. Department of Geography and Atmospheric Science; Estados Unidos Fil: Cremonese, Edoardo. Environmental Protection Agency of Aosta Valley; Italia Fil: Demarty, Jerome. University Montpellier. HydroSciences Montpellier (HSM); Francia Fil: Desai, Ankur R. University of Wisconsin‐Madison. Department of Atmospheric and Oceanic Sciences; Estados Unidos Fil: De Ligne, Anne. University of Liege. TERRA Teaching and Research Centre. Gembloux Agro‐Bio Tech; Bélgica Fil: Foltynova, Lenka. Czech Academy of Sciences. Global Change Research Institute ; República Checa Fil: Goulden, Michael L. University of California Irvine. Department of Earth System Science; Estados Unidos Fil: Griffis, Timothy J. University of Minnesota. Department of Soil, Water, and Climate; Estados Unidos Fil: Grunwald, Thomas. Technische Universität Dresden, Institute of Hydrology and Meteorology; Alemania Fil: Johnson, Mark S. University of British Columbia. Department of Earth, Ocean, and Atmospheric Sciences; Canadá Fil: Kang, Minseok. National Center for AgroMeteorology; Corea del Sur Fil: Kelbe, Dave. Xerra Earth Observation Institute; Nueva Zelanda Fil: Kowalska, Natalia. Czech Academy of Sciences. Global Change Research Institute ; República Checa Fil: Jong - Hwan, Lim. National Institute of Forest Science; Corea del Sur Fil: Mainassara, Ibrahim. University Montpellier. HydroSciences Montpellier (HSM); Francia Fil: McCabe, Matthew F. King Abdullah University of Science and Technology. Division of Biological and Environmental Science and Engineering. Hydrology, Agriculture and Land Observation Group (HALO); Arabia Saudita Fil: Missik, Justine E.C. Washington State University. Department of Civil and Environmental Engineering. Laboratory for Atmospheric Research; Estados Unidos Fil: Mohanty, Binayak P. Texas A&M University. Texas Water Observatory; Estados Unidos Fil: Moore, Caitlin E. University of Illinois Urbana‐Champaign. Institute for Sustainability, Energy, and Environment and Carl R. Woese Institute for Genomic Biology. Center for Advanced Bioenergy and Bioproducts Innovation; Estados Unidos Fil: Morillas, Laura. University of British Columbia. Department of Earth, Ocean, and Atmospheric Sciences; Canadá Fil: Morrison, Ross. Centre for Ecology and Hydrology; Reino Unido Fil: Munger, J. Willians. Harvard University. School of Engineering and Applied Sciences; Estados Unidos Fil: Posse, Gabriela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina Fil: Richardson, Andrew D. Northern Arizona University Center for Ecosystem Science and Society; Estados Unidos Fil: Russell, Eric. S. Washington State University. Department of Civil and Environmental Engineering. Laboratory for Atmospheric Research; Estados Unidos Fil: Ryu, Youngryel. Seoul National University . Department of Landscape Architecture and Rural Systems Engineering; Corea del Sur Fil: Sanchez - Azofeifa, Arturo. University of Alberta. Earth and Atmospheric Sciences Department. Centre for Earth Observation Sciences (CEOS); Canadá Fil: Schmidt, Marius. IInstitute of Bio‐ and Geosciences: Agrosphere (IBG‐3) Forschungszentrum Jülich IBG‐3; Alemania Fil: Schwartz, Efrat. Weizmann Institute of Science. Department of Earth and Planetary Sciences, ; Israel Fil: Sharp, Iain. University of Alberta. Earth and Atmospheric Sciences Department. Centre for Earth Observation Sciences (CEOS); Canadá Fil: Sigut, Ladislav. Czech Academy of Sciences. Global Change Research Institute ; República Checa Fil: Tang, Yao. Georgia Institute of Technology. School of Civil and Environmental Engineering; Estados Unidos Fil: Hulley, Glynn. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Anderson, Martha. U.S. Department of Agriculture‐Agricultural Research Service; Estados Unidos Fil: Hain, Christopher. NASA Marshall Space Flight Center; Estados Unidos Fil: French, Andrew. U.S. Department of Agriculture; Estados Unidos Fil: Wood, Eric. Princeton University. Department of Civil and Environmental Engineering; Estados Unidos Fil: Hook, Simón. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos

Field experiments offer the most acceptable approach to quantifying agricultural fumigant emissions but there is an absence of replicated field data in reported literature. Air concentration profiles of 1,3-dichloropropene (1,3-D) were determined on duplicate masts above the center of a treated field over 14 days. Meteorological parameters were also measured. Three meteorological approaches were then used to determine the total and flux density emissions of 1,3-D. Across the three calculation methods, the averages of the duplicated measurements showed total emission losses of cis 1,3-D ranging from 27% to 36% and of trans 1,3-D ranging from 18% to 24%. The replicate measurements differed by between 1.6 and 7.7 percentage points, which we consider to be excellent replicability. Flux densities over time showed maximum emissions during the first nighttime and early morning of the day following application. A general declining trend in emission fluxes was accompanied by nighttime peaks. Flux density curves during the experiment showed excellent agreement between replicates, with linear regression of the two data sets yielding r2 values of 0.95–0.98 and slopes of 1.01–1.17. To our knowledge, this is the first time that replicated fumigant fluxes have been reported. The high degree of replicability indicates the robustness of the approaches and lends credence to previous non-replicated flux data.

Saline-sodic soils are a major impediment for agricultural production in semi-arid regions. Salinity and sodicity drastically reduce agricultural crop yields, damage farm equipment, jeopardize food security, and render soils unusable for agriculture. However, many farmers in developing semi-arid regions cannot afford expensive amendments to reclaim saline-sodic soils. Furthermore, existing research does not cover soil types (e.g., Luvisols and Lixisols) that are found in many semi-arid regions of South America. Therefore, we used percolation columns to evaluate the effect of inexpensive chemical and organic amendments (gypsum and cow manure) on the reclamation of saline-sodic soils in the northeast of Brazil. Soil samples from two layers (0&ndash, 20 cm and 20&ndash, 40 cm in depth) were collected and placed in percolation columns. Then, we applied gypsum into the columns, with and without cow manure. The experiment followed a complete randomized design with three replications. The chemical amendment treatments included a control and four combinations of gypsum and cow manure. Percolation columns were subjected to a constant flood layer of 55 mm. We evaluated the effectiveness of sodic soil reclamation treatments via changes in soil hydraulic conductivity, chemical composition (cations and anions), electrical conductivity of the saturated soil-paste extract, pH, and the exchangeable sodium percentage. These results suggest that the combined use of gypsum and cow manure is better to reduce soil sodicity, improve soil chemical properties, and increase water infiltration than gypsum alone. Cow manure at 40 ton ha&minus, 1 was better than at 80 ton ha&minus, 1 to reduce the sodium adsorption ratio.

The eddy covariance method is regularly used for measuring gas fluxes over agricultural fields and natural ecosystems. For many applications, it is desirable to partition the measured fluxes into constitutive components: the water vapor flux into transpiration and direct evaporation components, and the carbon dioxide flux into photosynthesis and respiration components. The flux variance similarity (FVS) partitioning method is based on flux variance similarity relationships and correlation analyses of high-frequency eddy covariance data ( Scanlon and Sahu, 2008 , Scanlon and Kustas, 2010 , Scanlon and Kustas, 2012 ). The FVS method is relatively complex computationally, and that complexity has likely been an impediment to greater use and testing of the procedure. In this work, we present a new algebraic solution to the key computational task in the partitioning algorithm, which significantly simplifies the FVS method. We also introduce Fluxpart, a free and open source Python 3 module that implements the FVS partitioning procedure. Example flux partitioning calculations are presented.

California is increasingly experiencing drought conditions that restrict irrigation deliveries to perennial nut crops such as almonds and pistachios. During drought, poorer quality groundwater is often used to maintain these crops, but this use often results in secondary salinization that requires skilled management. Process-based models can help improve management guidelines under these challenging circumstances. The main objective of this work was to assess seasonal soil salinity and root water uptake as a function of irrigation water salinity and annual rain amounts. The manuscript presents a comparison of three-year experimental and numerically simulated root zone salinities in and below the root zone of almond and pistachio drip-irrigated orchards at multiple locations in the San Joaquin Valley (SJV), California, with different meteorological characteristics. The HYDRUS-1D numerical model was calibrated and validated using field measurements of soil water contents and soil solute bulk electrical conductivities at four root zone depths and measured soil hydraulic conductivities. The remaining soil hydraulic parameters were estimated inversely. Observations and simulations showed that the effects of rain on root zone salinity were higher in fields with initially low salinities than in fields with high salinities. The maximum reduction in simulated root water uptake (7%) occurred in response to initially high soil salinity conditions and saline irrigation water. The minimum reduction in simulated water uptake (2.5%) occurred in response to initially low soil salinity conditions and a wet rain year. Simulated water uptake reductions and leaching fractions varied at early and late times of the growing season, depending on irrigation water salinity. Root water uptake reduction was highly correlated with the cumulative effects of using saline waters in prior years, more than salt leaching during a particular season, even when rain was sufficient to leach salts during a wet year.

Accurate parameterization of reference evapotranspiration (ET0) is necessary for optimizing irrigation scheduling and avoiding costs associated with over-irrigation (water expense, loss of water productivity, energy costs, and pollution) or with under-irrigation (crop stress and suboptimal yields or quality). ET0 is often estimated using the FAO-56 method with meteorological data gathered over a reference surface, usually short grass. However, the density of suitable ET0 stations is often low relative to the microclimatic variability of many arid and semi-arid regions, leading to a potentially inaccurate ET0 for irrigation scheduling. In this study, we investigated multiple ET0 products from six meteorological stations, a satellite ET0 product, and integration (merger) of two stations’ data in Southern California, USA. We evaluated ET0 against lysimetric ET observations from two lysimeter systems (weighing and volumetric) and two crops (wine grapes and Jerusalem artichoke) by calculating crop ET (ETc) using crop coefficients for the lysimetric crops with the different ET0. ETc calculated with ET0 products that incorporated field-specific wind speed had closer agreement with lysimetric ET, with RMSE reduced by 36 and 45% for grape and Jerusalem artichoke, respectively, with on-field anemometer data compared to wind data from the nearest station. The results indicate the potential importance of on-site meteorological sensors for ET0 parameterization; particularly where microclimates are highly variable and/or irrigation water is expensive or scarce.

Current approaches to scheduling crop irrigation using reference evapotranspiration (ET 0 ) recommend using a dual-coefficient approach using basal (K cb ) and soil (K e ) coefficients along with a stress coefficient (K s ) to model crop evapotranspiration (ET c ), [e.g. ET c = (K s *K cb + K e )*ET 0 ]. However, determining K s , K cb , and K e from the combined evapotranspiration (ET) is challenging, particularly for K e , and a new method is needed to more rapidly determine crop coefficients for novel cultivars and cultivation practices. In this study, we partition eddy covariance ET observations into evaporation (E) and transpiration (T) components using correlation structure analysis of high frequency (10–20 Hz) observations of carbon dioxide and water vapor (Scanlon and Sahu, 2008) at three irrigated agricultural sites. These include a C4 photosynthetic-pathway species (sugarcane— Sacharum officinarum L.) and a C3 pathway species (peach —Prunus persica ) under sub-surface drip and furrow irrigation, respectively. Both sites showed high overall K c consistent with their height (>4 m). The results showed differences in K e , with the sub-surface drip-irrigated sugarcane having a low K e (0.1). There was no significant relationship (r 2 cb *K s , indicating that there was no stress (K s = 1), while the peach orchard showed mid-season declines in K cb *K s when VWC declined below 0.2. Partitioning of K c into K cb and K e resulted in a better regression (r 2 = 0.43) between the Normalized Differential Vegetation Index (NDVI) and K cb in sugarcane than between NDVI and K c (r 2 = 0.11). The results indicate the potential for correlation structure flux partitioning to improve crop ET coefficient determination by improved use of eddy covariance observations compared to traditional approaches of lysimeters and microlysimeters and sap flow observations to determine K c , K e , K s , and K cb .

Diminishing availability of non-saline water in arid and semiarid regions is of concern to all irrigated agricultural producers, including wine and grape producers. Grapes are not a salt tolerant crop and producers often face the choice of either limiting fresh water application, using alternative saline waters or a combination of both. We examined the salt tolerance and effect of restricted water application on three purported salt tolerant rootstocks grafted to Cabernet Sauvignon scion in a 4-year replicated field experiment. ANOVA indicated significant effects of salinity water stress and rootstock on fruit yields. The 140 Ruggeri scion was the top producer across all treatments including control, followed by Salt Creek, with St. George significantly less productive than 140 Ruggeri across all treatments. In terms of salt tolerance, Salt Creek and 140 Ruggeri were not statistically different but St. George was significantly less tolerant than Salt Creek. In terms of drought tolerance (relative yield), there were no statistical differences among rootstocks. Soil salinity profiles and soil moisture sensors indicated reduced water consumption under high salinity, thus no matric stress under 60% of optimal water application when high salt stress was present. The multiplicative stress model where salt and water stress are individually evaluated did not satisfactorily predict yield under combined salinity and reduced water application, likely due to decreased water consumption under saline conditions. Short term (one year) experiments underestimate salt damage to grape vines as salt tolerance decreased over the 4-year experiment.

Evaporation (E) and transpiration (T) respond differently to ongoing changes in climate, atmospheric composition, and land use. Our ability to partition evapotranspiration (ET) into E and T is limited at the ecosystem scale, which renders the validation of satellite data and land surface models incomplete. Here, we review current progress in partitioning E and T, and provide a prospectus for how to improve theory and observations going forward. Recent advancements in analytical techniques provide additional opportunities for partitioning E and T at the ecosystem scale, but their assumptions have yet to be fully tested. Many approaches to partition E and T rely on the notion that plant canopy conductance and ecosystem water use efficiency (EWUE) exhibit optimal responses to atmospheric vapor pressure deficit (D). We use observations from 240 eddy covariance flux towers to demonstrate that optimal ecosystem response to D is a reasonable assumption, in agreement with recent studies, but the conditions under which this assumption holds require further analysis. Another critical assumption for many ET partitioning approaches is that ET can be approximated as T during ideal transpiring conditions, which has been challenged by observational studies. We demonstrate that T frequently exceeds 95 % of ET from some ecosystems, but other ecosystems do not appear to reach this value, which suggests that this assumption is ecosystem-dependent with implications for partitioning. It is important to further improve approaches for partitioning E and T, yet few multi-method comparisons have been undertaken to date. Advances in our understanding of carbon-water coupling at the stomatal, leaf, and canopy level open new perspectives on how to quantify T via its strong coupling with photosynthesis. Photosynthesis can be constrained at the ecosystem and global scales with emerging data sources including solar-induced fluorescence, carbonyl sulfide flux measurements, thermography, and more. Such comparisons would improve our mechanistic understanding of ecosystem water flux and provide the observations necessary to validate remote sensing algorithms and land surface models to understand the changing global water cycle.

A three-year study was conducted to assess the ability of satellite-based vegetation index (VI) images to track evapotranspiration over wheat. While the ability of using VIs, notably with the Normalized Difference Vegetation Index (NDVI), to track vegetation growth has been well established, the operational capability to accurately estimate the crop coefficient (Kc) and crop evapotranspiration (ETc) at farm-scale from spaceborne platforms has not been widely studied. The study evaluated wheat ET over 7 sites between 2016 and 2019 in Yuma and Maricopa, Arizona, USA estimated by using Sentinel 2 and Venus satellites to map NDVI time-series for entire wheat cropping seasons, December to June. The basal crop coefficient (Kcb) was modeled by the NDVI time-series and the daily FAO56 reference ETo was obtained by near-by weather network stations. Eddy covariance (EC) stations in each field observed ETc during the same seasonal periods, and applied irrigation amounts were logged. The experiment found that remote sensing of NDVI and modeled Kcb accurately estimated Kc and crop ET during mid-season through senescence in most cases. However, NDVI-based estimation performed less well during early season (

Irrigation is a widely used water management practice that is often poorly parameterized in land surface and climate models. Previous studies have addressed this issue via use of irrigation area, applied water inventory data, or soil moisture content. These approaches have a variety of drawbacks including data latency, accurately prescribing irrigation intensity, and a lack of conservation of water volume for models using a prescribed soil moisture approach. In this study, we parameterize irrigation fluxes using satellite observations of evapotranspiration (ET) compared to ET from a suite of land surface models without irrigation. We then incorporate the irrigation flux into the Community Land Model (CLM) and use a systematic trial-and-error procedure to determine the ground- and surface-water withdrawals that are necessary to balance the new irrigation flux. The resulting CLM simulation with irrigation produces ET that matches the magnitude and seasonality of observed satellite ET well, with a mean difference of 6.3 mm month−1 and a correlation of 0.95. Differences between the new CLM ET values and satellite-observed ET values are always less than 30 mm month−1 and the differences show no pattern with respect to seasonality. The results reinforce the importance of accurately parameterizing anthropogenic hydrologic fluxes into land surface and climate models to assess environmental change under current and future climates and land management regimes.

Water availability is a major limiting factor for sustainable production of potential biofuel crops in Maui, Hawaii, USA. It is essential to improve regional, near-real time estimates of crop water use to facilitate optimal water management. Satellite remote-sensing offers multiple methods to estimate water management, however, most approaches assume a spatially homogeneous regional meteorology, which does not apply in Hawaii due to strong orographically-induced variations in climate. Canopy ground cover ( f c ) and spectral reflectance were measured over two sugarcane fields on the satellite Landsat 7 overpass dates. A strong linear relationship between satellite-based Normalized Difference Vegetation Index (NDVI) values and f c was found ( R 2 = 0.97). Canopy ground cover was also found to be highly correlated to crop coefficient ( K c ) which was calculated from reference evapotranspiration (ET 0 ) and sugarcane crop evapotranspiration (ET c ) observations from the Eddy Covariance towers. Spatial ET 0 for the entire sugarcane plantation was determined from an automated weather station network previously installed by the commercial grower of the plantation. Regressions were used to convert the satellite NDVI to K c maps, and then the satellite-based ET c maps were created from the satellite-based K c maps and ET 0 values computed and interpolated from the weather station network. To compare with the satellite-based crop coefficient/reference ET method, ET c and K c were also estimated using a satellite-based surface energy balance technique, the METRIC model. These two satellite-based methods were correlated fairly well ( R 2 = 0.84 for K c and 0.81 for ET c ). Compared to the METRIC model, the satellite-based crop coefficient/reference ET method may be more practicable for estimating crop water use in Maui, where ground-based ET 0 measurements are available through the on-site automated weather station network with right choice of reference ET equation.

Published in Agron. J. 107:1310–1320 (2015) doi:10.2134/agronj14.0588 Copyright © 2015 by the American Society of Agronomy, 5585 Guilford Road, Madison, WI 53711. All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. ABSTRACT The renewed interest in the use of sugarcane (Saccharin officinarum L.) for biofuel could provide a viable market for potential Hawaiian sugarcane feedstock producers. In Hawaii, sugarcane is grown as an irrigated 2-yr cycle crop. There is however little information on crop parameter attributes of 2-yr cycle sugarcane. This field study on Maui, Hawaii, analyzed the relationship between sugarcane biomass accumulation and specific crop parameters. Overall, the high dry biomass yield (80.20 Mg ha–1) was the result of a high leaf area index (LAI, 7.50) and radiation use efficiency (RUE, 2.06 g MJ–1. The crop growth rate was highly correlated to LAI (R2, 0.86), and a light extinction coefficient (k) of 0.53 was estimated. Stalk density was estimated at 18 stalks m–2, with a maximum plant height of 3.6 m, and a rooting depth exceeding 2.0 m. When the crop parameters were incorporated into a biological model of Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) the model accurately simulated sugarcane yields across seven different soil types and multiple management scenarios of applied irrigation water, N and P fertilizer inputs and various planting and harvest dates. The mean simulation percent (%) errors ranged from –6.4% to 1.8%, while the calculated Fisher’s paired t test of 1.41 with 39 degrees of freedom, showed no significant differences (P ≥ 0.05) between measured and simulated yields. The ALMANAC model should be useful as a decision support tool for evaluating sugarcane management alternatives that maximize yields while optimizing water, N and P inputs.

Sugarcane has been widely used as a biofuel crop due to its high biological productivity, ease of conversion to ethanol, and its relatively high potential for greenhouse gas reduction and lower environmental impacts relative to other derived biofuels from traditional agronomic crops. In this investigation, we studied four sugarcane cultivars (H-65-7052, H-78-3567, H-86-3792 and H-87-4319) grown on a Hawaiian commercial sugarcane plantation to determine their ability to store and accumulate soil carbon (C) and nitrogen (N) across a 24-month growth cycle on contrasting soil types. The main study objective establish baseline parameters for biofuel production life cycle analyses, sub-objectives included (1) determining which of four main sugarcane cultivars sequestered the most soil C and (2) assessing how soil C sequestration varies among two common Hawaiian soil series (Pulehu-sandy clay loam and Molokai-clay). Soil samples were collected at 20 cm increments to depths of up to 120 cm using hand augers at the three main growth stages (tillering, grand growth, and maturity) from two experimental plots at to observe total carbon (TC), total nitrogen (TN), dissolved organic carbon (DOC) and nitrates (NO−3) using laboratory flash combustion for TC and TN and solution filtering and analysis for DOC and NO−3. Aboveground plant biomass was collected and subsampled to determine lignin and C and N content. This study determined that there was an increase of TC with the advancement of growing stages in the studied four sugarcane cultivars at both soil types (increase in TC of 15–35 kg·m2). Nitrogen accumulation was more variable, and NO−3 (&lt, 5 ppm) were insignificant. The C and N accumulation varies in the whole profile based on the ability of the sugarcane cultivar’s roots to explore and grow in the different soil types. For the purpose of storing C in the soil, cultivar H-65-7052 (TC accumulation of ~30 kg·m−2) and H-86-3792 (25 kg·m−2) rather H-78-3567 (15 kg·m−2) and H-87-4319 (20 kg·m−2) appeared to produce more accumulated carbon in both soil types.

Standardized reference evapotranspiration (ET) and ecosystem-specific vegetation coefficients are frequently used to estimate actual ET. However, equations for calculating reference ET have not been well validated in tropical environments. We measured ET (ETEC) using eddy covariance (EC) towers at two irrigated sugarcane fields on the leeward (dry) side of Maui, Hawaii, USA in contrasting climates. We calculated reference ET at the fields using the short (ET0) and tall (ETr) vegetation versions of the American Society for Civil Engineers (ASCE) equation. The ASCE equations were compared to the Priestley–Taylor ET (ETPT) and ETEC. Reference ET from the ASCE approaches exceeded ETEC during the mid-period (when vegetation coefficients suggest ETEC should exceed reference ET). At the windier tower site, cumulative ETr exceeded ETEC by 854 mm over the course of the mid-period (267 days). At the less windy site, mid-period ETr still exceeded ETEC, but the difference was smaller (443 mm). At both sites, ETPT approximated mid-period ETEC more closely than the ASCE equations ((ETPT-ETEC) < 170 mm). Analysis of applied water and precipitation, soil moisture, leaf stomatal resistance, and canopy cover suggest that the lower observed ETEC was not the result of water stress or reduced vegetation cover. Use of a custom-calibrated bulk canopy resistance improved the reference ET estimate and reduced seasonal ET discrepancy relative to ETPT and ETEC in the less windy field and had mixed performance in the windier field. These divergences suggest that modifications to reference ET equations may be warranted in some tropical regions.

Sugarcane has been a major agronomic crop in Hawaii with an unique, high-yield, two-year production system. However, parameters relevant to advanced, cellulosic biofuel production, such as net ecosystem productivity (NEP) and radiation use efficiency (RUE), have not been evaluated in Hawaii under commercial production. Recent demand potential has rekindled interest in Hawaiian grown biofuels; as such, there is a need to understand productivity under changing climate and agronomic practices. To this end, we established two eddy covariance towers in commercial sugarcane fields in Maui, Hawaii to evaluate the carbon balance and RUE of sugarcane under contrasting elevations and soil types. We combined the tower observations with biometric and satellite data to assess RUE in terms of net biomass accumulation and daily gross primary production. High, sustained net NEP was found in both fields (cumulative NEP 4.23–5.37 × 10 3 g C m −2 over the course of the measurement period). Biomass RUE was statistically similar for both fields (1.15–1.24 g above ground biomass per MJ intercepted solar irradiance). Carbon accumulated in both fields at nearly the same rate with differences in cumulative biomass due to differing crop cycle lengths; cumulative gross primary productivity and ecosystem respiration were higher in the lower elevation field. Contrary to previous studies in Hawaiian sugarcane, we did not see a large decrease in NEP or increase in ecosystem respiration in the 2nd year, which we attributed to suppressed decomposition of dead cane stalks and leaves due to drip irrigation and drought. Biomass RUE also showed little decline in the 2nd year. The results show that Hawaiian sugarcane has a higher productivity than sugarcane grown in other regions of the world and also suggests that a longer (>12 months) growing cycle may be optimal for biomass production.

Due to the diminishing availability of good quality water for irrigation, it is increasingly important that irrigation and salinity management tools be able to target submaximal crop yields and support the use of marginal quality waters. In this work, we present a steady-state irrigated systems modeling framework that accounts for reduced plant water uptake due to root zone salinity. Two explicit, closed-form analytical solutions for the root zone solute concentration profile are obtained, corresponding to two alternative functional forms of the uptake reduction function. The solutions express a general relationship between irrigation water salinity, irrigation rate, crop salt tolerance, crop transpiration, and (using standard approximations) crop yield. Example applications are illustrated, including the calculation of irrigation requirements for obtaining targeted submaximal yields, and the generation of crop-water production functions for varying irrigation waters, irrigation rates, and crops. Model predictions are shown to be mostly consistent with existing models and available experimental data. Yet the new solutions possess advantages over available alternatives, including: (i) the solutions were derived from a complete physical-mathematical description of the system, rather than based on an ad hoc formulation; (ii) the analytical solutions are explicit and can be evaluated without iterative techniques; (iii) the solutions permit consideration of two common functional forms of salinity induced reductions in crop water uptake, rather than being tied to one particular representation; and (iv) the utilized modeling framework is compatible with leading transient-state numerical models.

Soil salinity negatively impacts the productivity and profitability of western San Joaquin Valley (WSJV) farmland. Many factors, including drought, climate change, reduced water allocations, and land-use changes could worsen salinity conditions there, and in other agricultural lands in the state. Mapping soil salinity at regional and state levels is essential for identifying drivers and trends in agricultural soil salinity, and for developing mitigation strategies, but traditional soil sampling for salinity does not allow for accurate large-scale mapping. We tested remote-sensing modeling to map root zone soil salinity for farmland in the WSJV. According to our map, 0.78 million acres are salt affected (i.e., ECe > 4 dS/m), which represents 45% of the mapped farmland; 30% of that acreage is strongly or extremely saline. Independent validations of the remote-sensing estimations indicated acceptable to excellent correspondences, except in areas of low salinity and high soil heterogeneity. Remote sensing is a viable tool for helping landowners make decisions about land use and also for helping water districts and state agencies develop salinity mitigation strategies.

The lack of energy closure has been a longstanding issue with Eddy Covariance (EC). Multiple mechanisms have been proposed to explain the discrepancies in energy balance including diurnal energy storage changes, advection of energy, and larger scale turbulent processes that cannot be resolved by field EC. To investigate the energy balance issue, we used a year of data from paired EC towers in irrigated sugarcane in Maui, Hawai’i, USA. The towers were in identical crops and cultivation practices and had similar climate with the notable exception of wind. One tower was in a location where nearby orographic features funneled Trade Winds, resulting in sustained, continuous turbulence. The other was in a leeward location with less turbulence, particularly at night (u*). We found significantly improved closure (8.5–10%) at both sites using daily sums of Available Energy in closure regressions as opposed to 30 min data, illustrating the importance of storage terms. The energy budget closed for both fields when only days with continuous turbulence (all 30 min u* > critical u*) were considered, with significantly larger uncertainty in the leeward field (±13%) due to the small number of days (n = 13) with this condition. Significant energy imbalance appeared in both fields with even 30 min of subcritical turbulence in a day, and each field had different turbulence-closure patterns. Closure with continuous turbulence was sensitive to choice of critical u*; an arbitrary u* of 0.1 m s−1 resulted in non-closure. The results show the value of paired EC towers in contrasting turbulence conditions to assess energy budget closure.

We evaluate a new approach to estimate regional evapotranspiration (ET) across a montane, Mediterranean climate gradient in the San Jacinto and Santa Rosa Mountains of Southern California. Spatially distributed evaporative fraction (EF) measurements were made monthly from October 2008 to September 2009 at 54 locations across an elevational gradient using a mobile measurement platform, called the Regional Evaporative Fraction Energy Balance (REFEB) method. We used these measurements and the Enhanced Vegetation Index (EVI) from MODerate resolution Imaging Spectroradiometer (MODIS) observations to derive EF at a regional scale. We converted EF to monthly ET using remote-sensing based observations of available energy. We compared the REFEB ET estimates, along with modified Priestly–Taylor (PT) ET estimates driven by MODIS data against four eddy covariance (EC) towers and eight gauged catchments. Both of the satellite-based ET estimates were highly correlated with tower ET observations (r 2 = 0.66 for REFEB and 0.95 for PT). The PT MODIS approach overestimated ET compared to precipitation estimates and stream gauge measurements, while REFEB ET was moderately lower than PT ET. The annual regional REFEB ET (193 mm) was 87 mm less than precipitation (280 mm). REFEB ET underestimated EC tower ET (regression slope = 0.78, p

Soil salinity undermines global agriculture by reducing crop yield and impairing soil quality. Irrigation management can help control salinity levels within the soil root-zone. To best manage water and soil resources, accurate regional-scale inventories of soil salinity are needed. The past decade has seen several successful applications of soil salinity remote sensing. Two salinity remote sensing approaches exist: direct assessment based on analysis of surface soil reflectance (the most popular approach), and indirect assessment of root-zone (e.g., 0-1 m) soil salinity based on analysis of crop canopy reflectance. In this perspective paper, we call on researchers and funding agencies to pay greater attention to the indirect approach because it is better suited for surveying agriculturally important lands. A joint effort between agricultural producers, irrigation specialists, environmental scientists, and policy makers is needed to better manage saline agricultural soils, especially because of projected future water scarcity in arid and semi-arid irrigated areas. The remote sensing community should focus on providing the best tools for mapping and monitoring salinity in such areas, which are of vital relevance to global food production.

Near-ground soil sensing improves interpolation of soil properties.Parallel (clustered) transect sampling is generally used on soil-sensor surveys.Unbiased interpolation quality assessment can be achieved using h-block resampling. Near-ground geophysical soil sensors provide valuable information for precision agriculture applications. Indeed, their readings can be used as proxy for many soil parameters. On-the-go soil sensor surveys are, typically, carried out intensively (e.g., every 2m) over many parallel transects. Two types of soil sensors measurements are considered in this paper: apparent electrical conductivity (4 fields in California, USA) and reflectance (1 field in Italy). Two types of spatial interpolations are carried out, universal kriging (model-based) and inverse distance weighting (deterministic). Interpolation quality assessment is usually carried out using leave-one-out (loo) resampling. We show that loo resampling on transect sampling datasets returns overly-optimistic, low interpolation errors, because the left-out data point has values very close to that of its neighbors in the training dataset. This bias in the map quality assessment can be reduced by removing the closest neighbors of the validation observation from the training dataset, in a (spatial) h-block (SHB) fashion. The results indicate that, for soil sensor data acquired along parallel transects: (i) the SHB resampling is a useful tool to test the performance of interpolation techniques and (ii) the optimal (i.e., rendering the same errors of un-sampled locations between transects) SHB threshold distance (h.dist) for neighbor-exclusion is proportional to the semi-variogram range and partial sill. This procedure provides research scientists with an improved means of understanding the error of soil maps made by interpolating soil sensor measurements.

Regional estimates of evapotranspiration (ET) are needed for environmental analysis and management purposes, yet can be difficult to obtain. Current methods for determining regional ET have spatial, temporal, methodological, and/or logistical limitations that affect their usefulness. To address these gaps, we developed a surface mobile measurement technique, the Regional Evaporative Fraction Energy Balance platform (REFEB), which measures evaporative fraction (EF) and water use efficiency (WUE) using a truck operating on a public right of way. REFEB can measure EF and WUE at 25 or more locations per day, which allows for rapid, dense, and spatially distributed sampling of fields across a region. We assessed the accuracy of the field measurements of EF and WUE with REFEB by comparing them to an Eddy covariance (EC) and Bowen ratio energy balance (BREB) tower. This site validation showed that REFEB has error and uncertainty similar to previous BREB approaches. We then used empirical relationships between field measurements and remote sensing vegetation indices to derive regional maps of EF. We combined these EF maps with satellite observations of net radiation to derive monthly and annual calculations of ET at a 250 m resolution during calendar year 2004 in the Imperial Valley, California, a major agricultural region that is dependent upon irrigation and which has a well constrained water budget. We then summed ET for the Imperial Valley and compared the result to a surface water budget based on irrigation and drainage measurements, which showed good annual and seasonal agreement. These results indicate REFEB produces accurate field measurements of EF and WUE, which can be scaled to estimate regional ET at time scales ranging from less than a week to annual sums.

Urban vegetation provides many highly valued ecosystem services but also requires extensive urban water resources. Increasingly, cities are experiencing water limitations and managing outdoor urban water use is an important concern. Quantifying the water lost via evapotranspiration (ET) is critical for urban water management and conservation, especially in arid or semi-arid regions. In this study, we deployed a mobile energy balance platform to measure evaporative fraction throughout Riverside, California, a warm, semi-arid, city. We observed the relationship between evaporative fraction and satellite derived vegetation index across 29 sites, which was then used to map whole-city ET for a representative mid-summer period. Resulting ET distributions were strongly associated with both neighborhood population density and income. By comparing 2014 and 2015 summer-period water uses, our results show 7.8% reductions in evapotranspiration, which were also correlated with neighborhood demographic characteristics. Our findings suggest a mobile energy balance measurement platform coupled with satellite imagery could serve as an effective tool in assessing the outdoor water use at neighborhood to whole city scales.

Standardized reference evapotranspiration (ET) and ecosystem-specific vegetation coefficients are frequently used to estimate actual ET. However, equations for calculating reference ET have not been well validated in tropical environments. We measured ET (ETEC) using Eddy Covariance (EC) towers at two irrigated sugarcane fields on the leeward (dry) side of Maui, Hawaii, USA in contrasting climates. We calculated reference ET at the fields using the short (ET0) and tall (ETr) vegetation versions of the American Society for Civil Engineers (ASCE) equation. The ASCE equations were compared to the Priestley–Taylor ET (ETPT) and ETEC. Reference ET from the ASCE approaches exceeded ETEC during the mid-period (when vegetation coefficients suggest ETEC should exceed reference ET). At the windier tower site, cumulative ETr exceeded ETEC by 854 mm over the course of the mid-period (267 days). At the less windy site, mid-period ETr still exceeded ETEC, but the difference was smaller (443 mm). At both sites, ETPT approximated mid-period ETEC more closely than the ASCE equations ((ETPT–ETEC) < 170 mm). Analysis of applied water and precipitation, soil moisture, leaf stomatal resistance, and canopy cover suggest that the lower observed ETEC was not the result of water stress or reduced vegetation cover. Use of a custom calibrated bulk canopy resistance improved the reference ET estimate and reduced seasonal ET discrepancy relative to ETPT and ETEC for the less windy field and had mixed performance at the windier field. These divergences suggest that modifications to reference ET equations may be warranted in some tropical regions.

We combined observations from four eddy covariance towers with remote sensing to better understand the altitudinal patterns of climate, plant phenology, Gross Ecosystem CO2Uptake, and Evapotranspiration (ET) around the Upper Kings River basin in the southern Sierra Nevada Mountains. Precipitation (P) increased with elevation to ∼500 m, and more gradually at higher elevations, while vegetation graded from savanna at 405 m to evergreen oak and pine forest to mid-montane forest to subalpine forest at 2700 m. CO2uptake and transpiration at 405 m peaked in spring (March to May) and declined in summer; gas exchange at 1160 and 2015 m continued year-round; gas exchange at 2700 m peaked in summer and ceased in winter. A phenological threshold occurred between 2015 and 2700 m, associated with the development of winter dormancy. Annual ET and Gross Primary Production were greatest at 1160 and 2015 m and reduced at 405 m coincident with less P, and at 2700 m coincident with colder temperatures. The large decline in ET above 2015 m raises the possibility that an upslope redistribution of vegetation with climate change could cause a large increase in upper elevation ET. We extrapolated ET to the entire basin using remote sensing. The 2003–11 P for the entire Upper Kings River basin was 984 mm y−1 and the ET was 429 mm y−1, yielding a P-ET of 554 mm y−1, which agrees well with the observed Kings River flow of 563 mm y−1. ET averaged across the entire basin was nearly constant from year to year.

Estimates of consumptive use of surface water by agriculture are vital for assessing food security, managing water rights, and evaluating anthropogenic impacts on regional hydrology. However, reliable, current, and public data on consumptive use can be difficult to obtain, particularly in international and less developed basins. We combine remotely-sensed precipitation and satellite observations of evapotranspiration and groundwater depletion to estimate surface water consumption by irrigated agriculture in California's Central Valley for the 2004–09 water years. We validated our technique against measured consumption data determined from streamflow observations and water export data in the Central Valley. Mean satellite-derived surface water consumption was 291.0 ± 32.4 mm/year while measured surface water consumption was 308.1 ± 6.5 mm/year. The results show the potential for remotely-sensed hydrologic data to independently observe irrigated agriculture's surface water consumption in contested or unmonitored basins. Improvements in the precision and spatial resolution of satellite precipitation, evapotranspiration and gravimetric groundwater observations are needed to reduce the uncertainty in this method and to allow its use on smaller basins and at shorter time scales.

International audience; Forestry – including afforestation (the planting of trees on land where they have not recently existed), reforestation, avoided deforestation, and forest management – can lead to increased sequestration of atmospheric carbon dioxide and has therefore been proposed as a strategy to mitigate climate change. However, forestry also influences land-surface properties, including albedo (the fraction of incident sunlight reflected back to space), surface roughness, and evapotranspiration, all of which affect the amount and forms of energy transfer to the atmosphere. In some circumstances, these biophysical feedbacks can result in local climate warming, thereby counteracting the effects of carbon sequestration on global mean temperature and reducing or eliminating the net value of climate-change mitigation projects. Here, we review published and emerging research that suggests ways in which forestry projects can counteract the consequences associated with biophysical interactions, and highlight knowledge gaps in managing forests for climate protection. We also outline several ways in which biophysical effects can be incorporated into frameworks that use the maintenance of forests as a climate protection strategy.

Policies for climate mitigation on land rarely acknowledge biophysical factors, such as reflectivity, evaporation, and surface roughness. Yet such factors can alter temperatures much more than carbon sequestration does, and often in a conflicting way. We outline a framework for examining biophysical factors in mitigation policies and provide some best-practice recommendations based on that framework. Tropical projects—avoided deforestation, forest restoration, and afforestation—provide the greatest climate value, because carbon storage and biophysics align to cool the Earth. In contrast, the climate benefits of carbon storage are often counteracted in boreal and other snow-covered regions, where darker trees trap more heat than snow does. Managers can increase the climate benefit of some forest projects by using more reflective and deciduous species and through urban forestry projects that reduce energy use. Ignoring biophysical interactions could result in millions of dollars being invested in some mitigation projects that provide little climate benefit or, worse, are counter-productive.