scholarly journals ECOSTRESS and CIMIS: A Comparison of Potential and Reference Evapotranspiration in Riverside County, California

2020 ◽  
Vol 12 (24) ◽  
pp. 4126
Author(s):  
Gurjot Kohli ◽  
Christine M. Lee ◽  
Joshua B. Fisher ◽  
Gregory Halverson ◽  
Evan Variano ◽  
...  
Keyword(s):  
Reference Evapotranspiration ◽  
Potential Evapotranspiration ◽  
Spatial Scales ◽  
Irrigation Management ◽  
Space Station ◽  
Careful Examination ◽  
Diurnal Variability ◽  
Riverside County ◽  
Spatial Coverage ◽  
Water District

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) provides remotely-sensed estimates of evapotranspiration at 70 m spatial resolution every 1–5 days, sampling across the diurnal cycle. This study, in partnership with an operational water management organization, the Eastern Municipal Water District (EMWD) in Southern California, was conducted to evaluate estimates of evapotranspiration under ideal conditions where water is not limited. EMWD regularly uses a ground-based network of reference evapotranspiration (ETo) from the California Irrigation Management Information System (CIMIS); yet, there are gaps in spatial coverage and questions of spatial representativeness and consistency. Space-based potential evapotranspiration (PET) estimates, such as those from ECOSTRESS, provide consistent spatial coverage. We compared ECOSTRESS ETo (estimated from PET) to CIMIS ETo at five CIMIS sites in Riverside County, California from July 2018–June 2020. We found strong correlations between CIMIS ETo and ECOSTRESS ETo across all five sites (R2 = 0.89, root mean square error (RMSE) = 0.11 mm hr−1). Both CIMIS and ECOSTRESS ETo captured similar seasonal patterns through the study period as well as diurnal variability. There were site-specific differences in the relationship between ECOSTRESS AND CIMIS, in part due to spatial heterogeneity around the station site. Consequently, careful examination of landscapes surrounding CIMIS sites must be considered in future comparisons. These results indicate that ECOSTRESS successfully retrieves PET that is comparable to ground-based reference ET, highlighting the potential for providing observation-driven guidance for irrigation management across spatial scales.

scholarly journals Reference evapotranspiration of Brazil modeled with machine learning techniques and remote sensing

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0245834
Author(s):  
Santos Henrique Brant Dias ◽  
Roberto Filgueiras ◽  
Elpídio Inácio Fernandes Filho ◽  
Gemima Santos Arcanjo ◽  
Gustavo Henrique da Silva ◽  
...  
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Reference Evapotranspiration ◽  
Potential Evapotranspiration ◽  
Irrigation Management ◽  
Machine Learning Algorithms ◽  
Machine Learning Techniques ◽  
Fundamental Parameter ◽  
Free Products ◽  
Climatic Regions

Reference evapotranspiration (ETo) is a fundamental parameter for hydrological studies and irrigation management. The Penman-Monteith method is the standard to estimate ETo and requires several meteorological elements. In developing countries, the number of weather stations is insufficient. Thus, free products of remote sensing with evapotranspiration information must be used for this purpose. In this context, the objective of this study was to estimate monthly ETo from potential evapotranspiration (PET) made available by MOD16 product. In this study, the monthly ETo estimated by Penman-Monteith method was considered as the standard. For this, data from 265 weather station of the National Institute of Meteorology (INMET), spread all over the Brazilian territory, were acquired for the period from 2000 to 2014 (15 years). For these months, monthly PET values from MOD16 product for all Brazil were also downloaded. By using machine learning algorithms and information from WorldClim as covariates, ETo was estimated through images from the MOD16 product. To perform the modeling of ETo, eight regression algorithms were tested: multiple linear regression; random forest; cubist; partial least squares; principal components regression; adaptive forward-backward greedy; generalized boosted regression and generalized linear model by likelihood-based boosting. Data from 2000 to 2012 (13 years) were used for training and data of 2013 and 2014 (2 years) were used to test the models. The PET made available by the MOD16 product showed higher values than those of ETo for different periods and climatic regions of Brazil. However, the MOD16 product showed good correlation with ETo, indicating that it can be used in ETo estimation. All models of machine learning were effective in improving the performance of the metrics evaluated. Cubist was the model that presented the best metrics for r2 (0.91), NSE (0.90) and nRMSE (8.54%) and should be preferred for ETo prediction. MOD16 product is recommended to be used to predict monthly ETo, which opens possibilities for its use in several other studies.

scholarly journals The diurnal cycle of cloud profiles over land and ocean between 51° S and 51° N, seen by the CATS spaceborne lidar from the International Space Station

2018 ◽  
Vol 18 (13) ◽  
pp. 9457-9473 ◽  
Author(s):  
Vincent Noel ◽  
Hélène Chepfer ◽  
Marjolaine Chiriaco ◽  
John Yorks
Keyword(s):  
High Altitude ◽  
International Space Station ◽  
Diurnal Cycle ◽  
Space Station ◽  
Cloud Fraction ◽  
Vertical Profiles ◽  
Diurnal Variability ◽  
International Space ◽  
Low Level ◽  
Diurnal Cycles

Abstract. We document, for the first time, how detailed vertical profiles of cloud fraction (CF) change diurnally between 51∘ S and 51∘ N, by taking advantage of 15 months of measurements from the Cloud-Aerosol Transport System (CATS) lidar on the non-sun-synchronous International Space Station (ISS). Over the tropical ocean in summer, we find few high clouds during daytime. At night they become frequent over a large altitude range (11–16 km between 22:00 and 04:00 LT). Over the summer tropical continents, but not over ocean, CATS observations reveal mid-level clouds (4–8 km above sea level or a.s.l.) persisting all day long, with a weak diurnal cycle (minimum at noon). Over the Southern Ocean, diurnal cycles appear for the omnipresent low-level clouds (minimum between noon and 15:00) and high-altitude clouds (minimum between 08:00 and 14:00). Both cycles are time shifted, with high-altitude clouds following the changes in low-altitude clouds by several hours. Over all continents at all latitudes during summer, the low-level clouds develop upwards and reach a maximum occurrence at about 2.5 km a.s.l. in the early afternoon (around 14:00). Our work also shows that (1) the diurnal cycles of vertical profiles derived from CATS are consistent with those from ground-based active sensors on a local scale, (2) the cloud profiles derived from CATS measurements at local times of 01:30 and 13:30 are consistent with those observed from CALIPSO at similar times, and (3) the diurnal cycles of low and high cloud amounts (CAs) derived from CATS are in general in phase with those derived from geostationary imagery but less pronounced. Finally, the diurnal variability of cloud profiles revealed by CATS strongly suggests that CALIPSO measurements at 01:30 and 13:30 document the daily extremes of the cloud fraction profiles over ocean and are more representative of daily averages over land, except at altitudes above 10 km where they capture part of the diurnal variability. These findings are applicable to other instruments with local overpass times similar to CALIPSO's, such as all the other A-Train instruments and the future EarthCARE mission.

scholarly journals Productive characteristics of banana genotypes submitted to different irrigation water depths under Cerrado conditions

2017 ◽  
Vol 38 (4Supl1) ◽  
pp. 2351
Author(s):  
Luciana Borges e Silva ◽  
Jorge Luís do Nascimento ◽  
Ronaldo Veloso Naves ◽  
Juracy Rocha Braga Filho ◽  
Wilian Henrique Diniz Buso ◽  
...  
Keyword(s):  
Water Depth ◽  
Irrigation Water ◽  
Potential Evapotranspiration ◽  
Block Design ◽  
Irrigation Management ◽  
Fruit Production ◽  
Production Cycle ◽  
Fruit Length ◽  
Water Depths ◽  
Fruit Diameter

Irrigation management associated with other banana agricultural practices can provide an increased productivity and improved fruit quality. This study assessed the productive characteristics of banana genotypes under different irrigation water depths. The experiment was conducted at the experimental area of the School of Agronomy (EA/UFG) in Goiânia, GO, Brazil. The experimental design was a split-plot randomized block design, in which four irrigation water depths (30, 65, 100, and 135% of crop potential evapotranspiration, ETpc) composed the plots and three genotypes (‘FHIA 18’, ‘Grande-Naine’, and ‘Prata’) the subplots, with a spacing of 2.5 × 1.6 m. During the experimental period (first production cycle), the total precipitation was 1719.20 mm. Characterization of genotype development and yield was performed with the following assessments: bunch mass (kg), number of hands, stalk mass (kg), fruit diameter of the second hand (mm), fruit length of the second hand (cm), mass of the second hand (kg), number of fruits of the second hand, total number of fruits, and number of damaged fruits. The cultivar ‘FHIA 18’, differently from the others, showed a significant response to irrigation water depths on productivity. In the genotypes ‘Grande-Naine’ and ‘Prata’, an influence of irrigation was observed only on external and visual characteristics of fruit (diameter, length, and number of damaged fruits). In the genotype ‘Prata’, the irrigation water depth of 965 mm allowed fruit production with a larger diameter. Fruit length in the genotype ‘Prata’ increased linearly as water depth increased. The use of irrigation promoted a reduction in the number of damaged fruits in the genotypes ‘FHIA 18’ and ‘Grande-Naine’.

scholarly journals Spatial resolution of tropical terrestrial CO<sub>2</sub> fluxes inferred using space-borne column CO<sub>2</sub> sampled in different earth orbits: the role of spatial error correlations

2011 ◽  
Vol 4 (9) ◽  
pp. 1995-2006 ◽  
Author(s):  
P. I. Palmer ◽  
L. Feng ◽  
H. Bösch
Keyword(s):  
Spatial Resolution ◽  
Spatial Scales ◽  
Space Station ◽  
Co2 Flux ◽  
Model Errors ◽  
Spatial Error ◽  
Clear Sky ◽  
Free Data ◽  
Combining Data ◽  
Infrared Measurements

Abstract. We use realistic numerical experiments to assess the sensitivity of 8-day CO2 flux estimates, inferred from space-borne short-wave infrared measurements of column-averaged CO2 dry air mixing ratio XCO2, to the choice of Earth observing orbit. We focus on three orbits: (1) a low-inclination circular orbit used by the NASA Tropical Rainfall Measuring Mission (TRMM); (2) a sun-synchronous orbit used by the Japanese Greenhouse Gases Observing SATellite (GOSAT) and proposed for the NASA Orbiting Carbon Observatory (OCO-2) instrument; and (3) a precessing orbit used by the International Space Station (ISS). For each orbit, we assume an instrument based on the specification of the OCO-2; for GOSAT we use the relevant instrument specification. Sun-synchronous orbits offer near global coverage within a few days but have implications for the density of clear-sky measurements. The TRMM and ISS orbits intensively sample tropical latitudes, with sun-lit clear-sky measurements evenly distributed between a.m./p.m. For a specified spatial resolution for inferred fluxes, we show there is a critical number of measurements beyond which there is a disproportionately small decrease in flux uncertainty. We also show that including spatial correlations for measurements and model errors (of length 300 km) reduces the effectiveness of high measurement density for flux estimation, as expected, and so should be considered when deciding sampling strategies. We show that cloud-free data from the TRMM orbit generally can improve the spatial resolution of CO2 fluxes achieved by OCO-2 over tropical South America, for example, from 950 km to 630 km, and that combining data from these low-inclination and sun-synchronous orbits have the potential to reduce this spatial length further. Decreasing the length of the error correlations to 50 km, reflecting anticipated future improvements to transport models, results in CO2 flux estimates on spatial scales that approach those observed by regional aircraft.

scholarly journals Spatiotemporal variability of NO<sub>2</sub> and PM<sub>2.5</sub> over Eastern China: observational and model analyses with a novel statistical method

2018 ◽  
Vol 18 (17) ◽  
pp. 12933-12952 ◽  
Author(s):  
Mengyao Liu ◽  
Jintai Lin ◽  
Yuchen Wang ◽  
Yang Sun ◽  
Bo Zheng ◽  
...  
Keyword(s):  
Spatial Scales ◽  
Eastern China ◽  
Ground Level ◽  
Vertical Gradient ◽  
Spatiotemporal Variability ◽  
Model Errors ◽  
Diurnal Variability ◽  
Near Surface ◽  
Synchronous Mode ◽  
The North

Abstract. Eastern China (27–41∘ N, 110–123∘ E) is heavily polluted by nitrogen dioxide (NO2), particulate matter with aerodynamic diameter below 2.5 µm (PM2.5), and other air pollutants. These pollutants vary on a variety of temporal and spatial scales, with many temporal scales that are nonperiodic and nonstationary, challenging proper quantitative characterization and visualization. This study uses a newly compiled EOF–EEMD analysis visualization package to evaluate the spatiotemporal variability of ground-level NO2, PM2.5, and their associations with meteorological processes over Eastern China in fall–winter 2013. Applying the package to observed hourly pollutant data reveals a primary spatial pattern representing Eastern China synchronous variation in time, which is dominated by diurnal variability with a much weaker day-to-day signal. A secondary spatial mode, representing north–south opposing changes in time with no constant period, is characterized by wind-related dilution or a buildup of pollutants from one day to another. We further evaluate simulations of nested GEOS-Chem v9-02 and WRF/CMAQ v5.0.1 in capturing the spatiotemporal variability of pollutants. GEOS-Chem underestimates NO2 by about 17 µg m−3 and PM2.5 by 35 µg m−3 on average over fall–winter 2013. It reproduces the diurnal variability for both pollutants. For the day-to-day variation, GEOS-Chem reproduces the observed north–south contrasting mode for both pollutants but not the Eastern China synchronous mode (especially for NO2). The model errors are due to a first model layer too thick (about 130 m) to capture the near-surface vertical gradient, deficiencies in the nighttime nitrogen chemistry in the first layer, and missing secondary organic aerosols and anthropogenic dust. CMAQ overestimates the diurnal cycle of pollutants due to too-weak boundary layer mixing, especially in the nighttime, and overestimates NO2 by about 30 µg m−3 and PM2.5 by 60 µg m−3. For the day-to-day variability, CMAQ reproduces the observed Eastern China synchronous mode but not the north–south opposing mode of NO2. Both models capture the day-to-day variability of PM2.5 better than that of NO2. These results shed light on model improvement. The EOF–EEMD package is freely available for noncommercial uses.

scholarly journals Performance of methods for estimation of table beet water requirement in Alagoas

2018 ◽  
Vol 22 (3) ◽  
pp. 189-193 ◽  
Author(s):  
Daniella P. dos Santos ◽  
Célia S. dos Santos ◽  
Leiliane M. da Silva ◽  
Márcio A. L. dos Santos ◽  
Cícero G. dos Santos
Keyword(s):  
Water Use ◽  
Standard Method ◽  
Water Scarcity ◽  
Performance Index ◽  
Reference Evapotranspiration ◽  
Irrigation Management ◽  
Crop Evapotranspiration ◽  
Abstract Optimization ◽  
Crop Coefficients ◽  
Drainage Lysimeter

ABSTRACT Optimization of water use in agriculture is fundamental, particularly in regions where water scarcity is intense, requiring the adoption of technologies that promote increased irrigation efficiency. The objective of this study was to evaluate evapotranspiration models and to estimate the crop coefficients of beet grown in a drainage lysimeter in the Agreste region of Alagoas. The experiment was conducted at the Campus of the Federal University of Alagoas - UFAL, in the municipality of Arapiraca, AL, between March and April 2014. Crop evapotranspiration (ETc) was estimated in drainage lysimeters and reference evapotranspiration (ETo) by Penman-Monteith-FAO 56 and Hargreaves-Samani methods. The Hargreaves-Samani method presented a good performance index for ETo estimation compared with the Penman-Monteith-FAO method, indicating that it is adequate for the study area. Beet ETc showed a cumulative demand of 202.11 mm for a cumulative reference evapotranspiration of 152.00 mm. Kc values determined using the Penman-Monteith-FAO 56 and Hargreaves-Samani methods were overestimated, in comparison to the Kc values of the FAO-56 standard method. With the obtained results, it is possible to correct the equations of the methods for the region, allowing for adequate irrigation management.

scholarly journals Evaluation and Bias Correction in WRF Model Forecasting of Precipitation and Potential Evapotranspiration

2019 ◽  
Vol 20 (5) ◽  
pp. 965-983 ◽  
Author(s):  
Theodor Bughici ◽  
Naftali Lazarovitch ◽  
Erick Fredj ◽  
Eran Tas
Keyword(s):  
Bias Correction ◽  
Potential Evapotranspiration ◽  
Irrigation Management ◽  
Hybrid Approach ◽  
Wrf Model ◽  
Irrigation Scheduling ◽  
Weather Research And Forecasting ◽  
Forecast Bias ◽  
Synoptic Conditions ◽  
High Bias

Abstract A reliable forecast of potential evapotranspiration (ET0) is key to precise irrigation scheduling toward reducing water and agrochemical use while optimizing crop yield. In this study, we examine the benefits of using the Weather Research and Forecasting (WRF) Model for ET0 and precipitation forecasts with simulations at a 3-km grid spatial resolution and an hourly temporal resolution output over Israel. The simulated parameters needed to calculate ET0 using the Penman–Monteith (PM) approach, as well as calculated ET0 and precipitation, were compared to observations from a network of meteorological stations. WRF forecasts of all PM meteorological parameters, except wind speed Ws, were significantly sensitive to seasonality and synoptic conditions, whereas forecasts of Ws consistently showed high bias associated with strong local effects, leading to high bias in the evaluated PM–ET0. Local Ws bias correction using observations on days preceding the forecast and interpolation of the resulting PM–ET0 to other locations led to significant improvement in ET0 forecasts over the investigated area. By using this hybrid forecast approach (WRFBC) that combines WRF numerical simulations with statistical bias corrections, daily ET0 forecast bias was reduced from an annual mean of 13% with WRF to 3% with WRFBC, while maintaining a high model–observation correlation. WRF was successful in predicting precipitation events on a daily event basis for all four forecast lead days. Considering the benefit of the hybrid approach for forecasting ET0, the WRF Model was found to be a high-potential tool for improving crop irrigation management.

scholarly journals Evaluation of Multi-Reanalysis Solar Radiation Products Using Global Surface Observations

Atmosphere ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 42 ◽  
Author(s):  
Xiaomin Peng ◽  
Jiangfeng She ◽  
Shuhua Zhang ◽  
Junzhong Tan ◽  
Yang Li
Keyword(s):  
Solar Radiation ◽  
Large Scale ◽  
Spatial Scales ◽  
Global Solar Radiation ◽  
Hydrological Process ◽  
China Meteorological Administration ◽  
Surface Solar Radiation ◽  
Climate Zones ◽  
Tropical Regions ◽  
Spatial Coverage

Solar radiation incident at the Earth’s surface is an essential driver of the energy exchange between the atmosphere and the surface and is also an important input variable in the research on the surface eco-hydrological process. The reanalysis solar radiation dataset is characterized by a long time series and wide spatial coverage and is used in the research of large-scale eco-hydrological processes. Due to certain errors in their production process of the reanalysis of solar radiation products, reanalysis products should be evaluated before application. In this study, three global solar-radiation reanalysis products (ERA-Interim; JRA-55; and NCEP-DOE) in different temporal scales and climate zones were evaluated using surface solar-radiation observations from the National Meteorological Information Center of the China Meteorological Administration (CMA, Beijing, China) and the Global Energy Balance Archive (GEBA, Zürich, Switzerland) from 2000 to 2009. All reanalysis products (ERA-Interim; JRA-55; and NCEP-DOE) overestimated with an annual bias of 14.86 W/m2, 22.61 W/m2, and 31.85 W/m2; monthly bias of 15.17 W/m2, 21.29 W/m2, and 36.91 W/m2; and seasonal bias of 15.08 W/m2, 21.21 W/m2, and 36.69 W/m2, respectively. In different Köppen climate zones, the annual solar radiation of ERA-Interim performed best in cold regions with a bias of 10.30 W/m2 and absolute relative error (ARE) of 8.98%. However, JRA-55 and NCEP-DOE showed the best performance in tropical regions with a bias of 20.08 W/m2 and −0.12 W/m2, and ARE of 11.00% and 9.68%, respectively. Overall, through the evaluations across different temporal and spatial scales, the rank of the three reanalysis products in order was the ERA-Interim, JRA-55, and NCEP-DOE. In addition, based on the evaluation, we analyzed the relationship between the error (ARE) of the reanalysis products and cloud cover, aerosol, and water vapor, which significantly influences solar radiation and we found that cloud was the main cause for errors in the three solar radiation reanalysis products. The above can provide a reference for the application and downscaling of the three solar radiation reanalysis products.

scholarly journals Comparative evaluation of 24 reference evapotranspiration equations applied on an evergreen-broadleaved forest

2017 ◽  
Vol 49 (4) ◽  
pp. 1028-1041 ◽  
Author(s):  
Athanassios Bourletsikas ◽  
Ioannis Argyrokastritis ◽  
Nikolaos Proutsos
Keyword(s):  
Goodness Of Fit ◽  
Hydrological Cycle ◽  
Reference Evapotranspiration ◽  
Potential Evapotranspiration ◽  
Efficiency Index ◽  
Daily Basis ◽  
Forest Environment ◽  
Statistical Parameters ◽  
Model Efficiency

Abstract Reference evapotranspiration (ET0) is a major component of the hydrological cycle. Its use is essential both for the hydrological rainfall–runoff assessment models and determination of water requirements in agricultural and forest ecosystems. This study investigates the performance of 24 different methods, which produce ET0 or potential evapotranspiration estimates above a grass-covered ground in a Mediterranean forest environment in Greece and compares the derived results with those of the presumed most accurate and scientifically acceptable Penman–Monteith method (ETP-M). Their performance was evaluated on a daily basis for a period of 17 years, using 17 different statistical parameters of goodness of fit. The results showed that some empirical methods could serve as suitable alternatives. More specifically, Copais (ETCOP), Hargreaves original (ETHAR), and Valiantzas2 (ETVA2) methods, exhibited very good values of the model efficiency index, EF (0.934, 0.932, and 0.917, respectively) and the index of agreement, d (0.984, 0.982, and 0.977, respectively). Additionally, the differences of the estimated mean daily value against the respective ETP-M value (rt index) for all methods had a range of −27.8% (Penman – ETPEN) to +59.5% (Romanenko – ETROM), while Copais (ETCOP), Hargreaves–Samani modified1 (ETHS1), and STU (ETSTU) yielded the best values (−0.06%, +0.06%, and 0.22%, respectively).

Comparison between forecasts of reference evapotranspiration and ETo values calculated using data from different climatic conditions

2020 ◽  
Author(s):  
Ghaieth Ben Hamouda ◽  
Francesca Ventura ◽  
Daniele Zaccaria ◽  
Khaled M. Bali ◽  
Richard L. Snyder
Keyword(s):  
Reference Evapotranspiration ◽  
Irrigation Management ◽  
Climatic Conditions ◽  
Physical Models ◽  
Dew Point ◽  
Water Losses ◽  
Plant Canopies ◽  
Crucial Component ◽  
And Performance ◽  
Using Data

&lt;p&gt;Evapotranspiration is the transfer of water from the earth's surface to the atmosphere. It comprises the sum of water losses to atmosphere due to the processes of evaporation of moisture from soil, water bodies and wet plant canopies, and the transpiration of water from plants. Forecasts of this crucial component of the hydrologic cycle can be very valuable for growers, farm managers, irrigation practitioners, water resource planners and managers, and reservoir operators for their planning, allocation, delivery and scheduling decisions, as well as to hydrologic scientists for research purposes. Verifying the reliability of models&amp;#8217; forecasts is among the critical tasks for development and performance evaluation of physical models. In fact, the verification allows understanding the models&amp;#8217; behavior, and evaluating their applicability and dependability. The US National Weather Service (NWS) has released a product that provides forecasts of reference evapotranspiration (FRET) at 2.5-km grid resolution for the entire continental US. In this study, a comparison is made between ETo estimates from FRET and ETo values calculated by the California Irrigation Management Information System (CIMIS) for 68 days during summer 2019. Both the FRET forecasts and ETo values were obtained from NWS and CIMIS, respectively, on the basis of 15 CIMIS locations that are representative of different climatic conditions in California. In addition, air temperature, dew point temperature, relative humidity, wind speed, and vapor pressure deficit (VPD) data were also collected/calculated from the NWS and CIMIS websites to analyze the sensitivity of FRET forecasts to predictions of these parameters. All FRET forecasts were performed with timescales of 1, 3, 5 and 7 days. Statistical indices were calculated to assess the dependability of FRET values. They showed a good correlation of the FRET model outputs with CIMIS ETo data, with some differences depending on the climatic characteristics of selected weather stations&amp;#8217; locations, suggesting that FRET data could be valuable for anticipating near-future water demand and improve irrigation management in California.&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document