Measuring H2O and CO2 fluxes at field scales with scintillometry: Part I – Introduction and validation of four methods

Kesteren, A.J.H. van; Hartogensis, Oscar; Dinther, D. van; Moene, Arnold F.; Bruin, H.A.R. de

doi:10.1016/j.agrformet.2012.09.013

Cited by 17 publications

(10 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, due to edge effects flux observations close to the start or end of a dataset can contain spectral artefacts. Using alternative techniques such as empirical mode decomposition (Barnhart et al, 2012a, b) or structure-parameter methods (Van Kesteren et al, 2013) might help to further improve the results.…”

Section: Discussionmentioning

confidence: 99%

Spatially explicit regionalization of airborne flux measurements using environmental response functions

et al. 2013

View full text Add to dashboard Cite

Abstract. The goal of this study is to characterize the sensible (H) and latent (LE) heat exchange for different land covers in the heterogeneous steppe landscape of the Xilin River catchment, Inner Mongolia, China. Eddy-covariance flux measurements at 50–100 m above ground were conducted in July 2009 using a weight-shift microlight aircraft. Wavelet decomposition of the turbulence data enables a spatial discretization of 90 m of the flux measurements. For a total of 8446 flux observations during 12 flights, MODIS land surface temperature (LST) and enhanced vegetation index (EVI) in each flux footprint are determined. Boosted regression trees are then used to infer an environmental response function (ERF) between all flux observations (H, LE) and biophysical (LST, EVI) and meteorological drivers. Numerical tests show that ERF predictions covering the entire Xilin River catchment (&approx;3670 km2) are accurate to ≤18% (1 σ). The predictions are then summarized for each land cover type, providing individual estimates of source strength (36 W m−2 < H < 364 W m−2, 46 W m−2 < LE < 425 W m−2) and spatial variability (11 W m−2 < σH < 169 W m−2, 14 W m−2 < σLE < 152 W m−2) to a precision of ≤5%. Lastly, ERF predictions of land cover specific Bowen ratios are compared between subsequent flights at different locations in the Xilin River catchment. Agreement of the land cover specific Bowen ratios to within 12 &pm; 9% emphasizes the robustness of the presented approach. This study indicates the potential of ERFs for (i) extending airborne flux measurements to the catchment scale, (ii) assessing the spatial representativeness of long-term tower flux measurements, and (iii) designing, constraining and evaluating flux algorithms for remote sensing and numerical modelling applications.

show abstract

Section: Discussionmentioning

confidence: 99%

Spatially explicit regionalization of airborne flux measurements using environmental response functions

et al. 2013

View full text Add to dashboard Cite

show abstract

“…Taking into account the difficulties encountered with the vegetation variation over the long term, the results provide valuable information for future hydrological modelling at the catchment scale. Kesteren et al (2013aKesteren et al ( , 2013b combined scintillometer measurements with point-sampling measurements of scalar quantities to estimate ET. They used four methods including the Bowen-variance, flux-variance, structure-parameter and energy-balance methods to test the sensitivity to the variables.…”

Section: Introductionmentioning

confidence: 99%

Remote sensing techniques for predicting evapotranspiration from mixed vegetated surfaces

Nouri

Beecham

Anderson

et al. 2014

Urban Water Journal

View full text Add to dashboard Cite

Evapotranspiration (ET) is a key component of the hydrological cycle however it is also the most difficult factor to quantify. In recent decades, estimating ET has been improved by advances in remote sensing, particularly in agricultural studies. However, quantifying ET from mixed vegetation environs, particularly urban parklands, is still challenging due to the heterogeneity of plant species, canopy covers, microclimates, and because of costly methodological requirements. Several studies have recently been conducted in agriculture and forestry which may be useful for mixed landscape vegetation studies with some modifications. This review describes general remote sensing-based approaches to estimate ET and describes their advantages and disadvantages. Most of these approaches need extensive time investment, medium to high skill levels and are quite expensive. However, in addition to the reviewed methods, the authors recommend combining remotely sensed vegetation indices and ground-based techniques for ET estimation of mixed landscape vegetation such as urban parklands.

show abstract

“…Reviews on the measurements, modeling and RS of land actual evapotranspiration have been conducted many times in the past. Different measurement methods of E or λE have been reviewed by Shuttleworth, 4 Verstraeten et al, 6 Baldocchi, 7 Moene et al, 8 and Van Kesteren et al 9 The modeling of E or λE in regional and global models has been summarized by Parlange et al, 10 Sellers et al, 11 and Brutsaert. 12 The use of remotely sensed data, especially land surface temperature data, to estimate E started from 1980s.…”

Section: Introductionmentioning

confidence: 99%

A review of remote sensing based actual evapotranspiration estimation

2016

View full text Add to dashboard Cite

Evapotranspiration is a major component of the global water cycle and provides a critical nexus between terrestrial water, carbon and surface energy exchanges. Evapotranspiration is inherently difficult to measure and predict especially at large spatial scales. Remote sensing provides a cost-effective method to estimate evapotranspiration at regional to global scales. In the past three decades a large number of studies on remote sensing based evapotranspiration estimation have emerged. This review summarizes the basic theories underpinning current remote sensing based evapotranspiration estimation methods. It also lays out the development history of these methods and compares their advantages and limitations. Several key directions for further study are identified and discussed, including identification of uncertainty sources in remote sensing evapotranspiration models, merging of different remote sensing methods, application of data assimilation and fusion techniques in producing robust evapotranspiration estimates, and utilization of multi-source remote sensing data and latest sensor technologies. Further advances in the remote sensing of evapotranspiration will enhance capabilities for monitoring of the global water and energy cycles, including water availability and ecosystem responses and feedbacks to climate change and human impacts. FIGURE 5 | (a) Latitudinal distribution of mean E from six RS E products, (b) mean seasonal cycle of the six E products, (c) time series of annual global land E anomalies from the MTE model and nine other models, and (d) time series of annual global land E anomalies from five RS E model ((a) and (b) Reprinted with permission from Ref 118.

show abstract

Measuring H2O and CO2 fluxes at field scales with scintillometry: Part I – Introduction and validation of four methods

Cited by 17 publications

References 58 publications

Spatially explicit regionalization of airborne flux measurements using environmental response functions

Spatially explicit regionalization of airborne flux measurements using environmental response functions

Remote sensing techniques for predicting evapotranspiration from mixed vegetated surfaces

A review of remote sensing based actual evapotranspiration estimation

Contact Info

Product

Resources

About