Irsute

Séguin, Bernard; Becker, F.; Phulpin, T.; Gu, Xiaojing; Guyot, G.; Kerr, Yann H.; King, Christine; Lagouarde, Jean‐Pierre; Ottlé, Catherine; Stoll, M. P.; Tabbagh, Alain; Vidal, Alain

doi:10.1016/s0034-4257(98)00122-9

Cited by 60 publications

(7 citation statements)

References 52 publications

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“…Relative errors reduce to 18%, 14%, and 8% at weekly, monthly, and yearly timescales, respectively, due to time averaging of random errors. This performance is close to the target of 0.8 mm day −1 error suggested by Seguin [57] for actionable ET information in agroecology. The data fusion approach also supports the high temporal (near daily) and spatial (sub 100-m) requirements specified in that study.…”

Section: Model-measurement Comparisons and Tower Representativitysupporting

confidence: 86%

Field-Scale Assessment of Land and Water Use Change over the California Delta Using Remote Sensing

et al. 2018

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Abstract:The ability to accurately monitor and anticipate changes in consumptive water use associated with changing land use and land management is critical to developing sustainable water management strategies in water-limited climatic regions. In this paper, we present an application of a remote sensing data fusion technique for developing high spatiotemporal resolution maps of evapotranspiration (ET) at scales that can be associated with changes in land use. The fusion approach combines ET map timeseries developed using an multi-scale energy balance algorithm applied to thermal data from Earth observation platforms with high spatial but low temporal resolution (e.g., Landsat) and with moderate resolution but frequent temporal coverage (e.g., MODIS (Moderate Resolution Imaging Spectroradiometer)). The approach is applied over the Sacramento-San Joaquin Delta region in California-an area critical to both agricultural production and drinking water supply within the state that has recently experienced stresses on water resources due to a multi-year (2012-2017) extreme drought. ET "datacubes" with 30-m resolution and daily timesteps were constructed for the 2015-2016 water years and related to detailed maps of land use developed at the same spatial scale. The ET retrievals are evaluated at flux sites over multiple land covers to establish a metric of accuracy in the annual water use estimates, yielding root-mean-square errors of 1.0, 0.8, and 0.3 mm day −1 at daily, monthly, and yearly timesteps, respectively, for all sites combined. Annual ET averaged over the Delta changed only 3 mm year −1 between water years, from 822 to 819 mm year −1 , translating to an area-integrated total change in consumptive water use of seven thousand acre-feet (TAF). Changes were largest in areas with recorded land-use change between water years-most significantly, fallowing of crop land presumably in response to reductions in water availability and allocations due to the drought. Moreover, the time evolution in water use associated with wetland restoration-an effort aimed at reducing subsidence and carbon emissions within the inner Delta-is assessed using a sample wetland chronosequence. Region-specific matrices of consumptive water use associated with land use changes may be an effective tool for policymakers and farmers to understand how land use conversion could impact consumptive use and demand.

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Section: Model-measurement Comparisons and Tower Representativitysupporting

confidence: 86%

Field-Scale Assessment of Land and Water Use Change over the California Delta Using Remote Sensing

et al. 2018

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“…It is also noted that part of the errors encountered are associated with uncertainty in the eddy covariance method. The accuracy achieved with this simple regression method is comparable if not better than that achieved with far more complex methods described elsewhere in this paper and certainly meets the required E retrieval accuracy of about 50 Wm -2 suggested by Seguin et al (1999).…”

Section: Empirical Vegetation Index Methodssupporting

confidence: 76%

“…There are also errors in estimating the available energy (R n -G) and other ground based meteorological observations, as well as errors due to various model assumptions. This paper reports on several approaches which are aimed at reducing the impact of those uncertainties; (vii) Seguin et al (1999) found that the majority of published remote sensing methods for estimating E had an accuracy of ±80-90 W m -2 or 1.5 mm day -1 . They noted that more precise evaluation was needed at various scales and suggested that E flux retrieval accuracy for many agricultural and hydrological applications should have an accuracy of *50 W m -2 or 0.8 mm day -1 at the field scale, although this will vary with individual applications; (viii) the present paper lists some 30 validations of remote sensing approaches for estimating E which report on average an RMSE of just over 50 W m -2 .…”

Section: Discussionmentioning

confidence: 99%

Estimating Land Surface Evaporation: A Review of Methods Using Remotely Sensed Surface Temperature Data

2008

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This paper reviews methods for estimating evaporation from landscapes, regions and larger geographic extents, with remotely sensed surface temperatures, and highlights uncertainties and limitations associated with those estimation methods. Particular attention is given to the validation of such approaches against ground based flux measurements. An assessment of some 30 published validations shows an average root mean squared error value of about 50 W m -2 and relative errors of 15-30%. The comparison also shows that more complex physical and analytical methods are not necessarily more accurate than empirical and statistical approaches. While some of the methods were developed for specific land covers (e.g. irrigation areas only) we also review methods developed for other disciplines, such as hydrology and meteorology, where continuous estimates in space and in time are needed, thereby focusing on physical and analytical methods as empirical methods are usually limited by in situ training data. This review also provides a discussion of temporal and spatial scaling issues associated with the use of thermal remote sensing for estimating evaporation. Improved temporal scaling procedures are required to extrapolate instantaneous estimates to daily and longer time periods and gap-filling procedures are needed when temporal scaling is affected by intermittent satellite coverage. It is also noted that analysis of multi-resolution data from different satellite/sensor systems (i.e. data fusion) will assist in the development of spatial scaling and aggregation approaches, and that several biological processes need to be better characterized in many current land surface models. Nomenclature B Coefficient in Eq. 3 (-) C BNBulk turbulent transfer coefficient (-) C p Specific heat of air at constant pressure (J kg -1 K -1 ) D Zero plane displacement height (m) E, E a Actual evaporation rate (mm day -1 ) E n Normalised actual evaporation (mm day -1 ) E p Potential evaporation rate (mm day -1 ) E PT Priestley-Taylor evaporation rate (mm day -1 ) E w Equilibrium evaporation rate (mm day -1 ) e a Actual vapour pressure of the air (Pa) e a * Saturated vapour pressure of the air (Pa) e s * Saturated vapour pressure at T s (Pa) e u * Saturated vapour pressure at T u (Pa) f c Fractional vegetation cover (-) G Soil heat flux (W m -2 ) G s Surface conductance (m s -1 ) g bBulk leaf boundary layer conductance (m s -1 ) H Sensible heat flux (W m -2 ) H c Sensible heat flux to/from canopy (W m -2 ) H s Sensible heat flux to/from soil (W m -2 ) K;Downwelling shortwave radiation flux (W m -2 ) K:Upwelling shortwave radiation flux (W m -2 ) k Von Karman's constant (0.4) kB -1 Dimensionless ratio used to calculate r ex L Monin-Obukhov length (m) L;Downwelling longwave radiation flux (W m -2 ) L:Upwelling longwave radiation flux (W m -2 ) n Exponent in Eq. 3 r a Aerodynamic resistance (s m -1 ) r c Canopy resistance (s m -1 ) r cp Canopy resistance at potential transpiration (s m -1 ) r ex Excess (supplementary, extra) resistance (s m -1 ) R n N...

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“…Daily MAE values range from 0.61 to 0.85 mm day −1 for ET a -retro and 0.71 to 0.82 mm day −1 for ET a -OP. These errors are on par with the target error of 0.80 mm day −1 suggested by Reference [56] for operational ET use. These errors also align with [39,40], where results from a baseline (retrospective) version of the ET fusion model were compared to flux tower estimates within a vineyard approximately 200 km north of the current study area.…”

Section: Comparisons With Tower Observationsmentioning

confidence: 50%

“…Percent error values were less than 20% at all blocks, despite the greater than 4-day thermal image update cycle as recommended by Reference [23,58]. Daily MAE values were also on par with the target error of 0.80 mm day −1 suggested by Reference [56] for operational ET uses. Estimates of crop water requirements (ET c ) developed from a modified NDVI-based FAO method were unable to capture the rapid decline in vineyard ET a over blocks 1 and 2 during the stress event that took place in late July.…”

Section: Discussionmentioning

confidence: 62%

Using High-Spatiotemporal Thermal Satellite ET Retrievals for Operational Water Use and Stress Monitoring in a California Vineyard

et al. 2019

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In viticulture, deficit irrigation strategies are often implemented to control vine canopy growth and to impose stress at critical stages of vine growth to improve wine grape quality. To support deficit irrigation scheduling, remote sensing technologies can be employed in the mapping of evapotranspiration (ET) at the field to sub-field scales, quantifying time-varying vineyard water requirements and actual water use. In the current study, we investigate the utility of ET maps derived from thermal infrared satellite imagery over a vineyard in the Central Valley of California equipped with a variable rate drip irrigation (VRDI) system which enables differential water applications at the 30 × 30 m scale. To support irrigation management at that scale, we utilized a thermal-based multi-sensor data fusion approach to generate weekly total actual ET (ETa) estimates at 30 m spatial resolution, coinciding with the resolution of the Landsat reflectance bands. Crop water requirements (ETc) were defined with a vegetative index (VI)-based approach. To test capacity to capture stress signals, the vineyard was sub-divided into four blocks with different irrigation management strategies and goals, inducing varying degrees of stress during the growing season. Results indicate derived weekly total ET from the thermal-based data fusion approach match well with observations. The thermal-based method was also able to capture the spatial heterogeneity in ET over the vineyard due to a water stress event imposed on two of the four vineyard blocks. This transient stress event was not reflected in the VI-based ETc estimate, highlighting the value of thermal band imaging. While the data fusion system provided valuable information, latency in current satellite data availability, particularly from Landsat, impacts operational applications over the course of a growing season.

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Irsute

Cited by 60 publications

References 52 publications

Field-Scale Assessment of Land and Water Use Change over the California Delta Using Remote Sensing

Field-Scale Assessment of Land and Water Use Change over the California Delta Using Remote Sensing

Estimating Land Surface Evaporation: A Review of Methods Using Remotely Sensed Surface Temperature Data

Using High-Spatiotemporal Thermal Satellite ET Retrievals for Operational Water Use and Stress Monitoring in a California Vineyard

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