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Peer review report 1 On “Mapping daily evapotranspiration at field scales over rainfed and irrigated agricultural areas using remote sensing data fusion”
Agricultural and Forest Meteorology 201S (2015) 301
Contents lists available at ScienceDirect
Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet
Peer review report
Peer review report 1 On “Mapping daily evapotranspiration at field scales over rainfed and irrigated agricultural areas using remote sensing data fusion”
Original Submission Recommendation Minor Revision Comments to Author The authors report remotely sensed ET modeling results over two US agricultural sites. The new contribution is implementing and testing an existing data fusion approach using MODIS and Landsat data. The study does not develop a new approach, nor does it refine existing approaches, but it does provide important and useful evidence for the utility of fusing remote sensing data of different kinds to obtain more frequent and better spatial resolution estimates of ET than would otherwise be obtained from a single satellite The manuscript lacks support for parameterization of crop light interception and net radiation computation. How do we know you didn’t custom tune in a non-general and non-physical way? It would help if you provide readers more specifics on all parameters The manuscript is generally well written but there are several instances of spelling errors and peculiar use of English. I suggest a careful review and edit by all authors to correct the problems Abstract Findings are mostly described but missing was mention and notable feature of the underlying data fusion approach, namely STARFM. Certainly testing the approach and verifying its accuracy for two rainfed & irrigated sites, but the overriding importance of the work is the implementation of a particular data fusion methodology. It is the methodology and its potential generality that will have lasting importance. Summary and Conclusions The liberal use of subjective evaluations such as ‘satisfactory agreement’ is inappropriate unless you can provide some measures of ‘satisfaction’. Address this lack of measures would help this section and the paper overall since you can the say something about the current state of art and how your work is advancing the science of ET with remote sensing.
DOI of original article: http://dx.doi.org/10.1016/j.agrformet.2013.11.001. 0168-1923/$ – see front matter http://dx.doi.org/10.1016/j.agrformet.2015.08.121
I can accept the general remark about monitoring water use over large agricultural areas—it is widely used in the literature—but it too could be refined. One of the big questions that you might think is beyond this paper’s scope is who would be the potential monitors? Certainly if you asked individual farmers they would almost surely say that they are not at all keen to have their water use data available to authorities. You cant address that particular issue in this paper, but you could cite regions of the world where water management is tightly regulated by governments or (for example) irrigation districts. Doing so will more precisely motivate your work. L 24: suggest you drop the first ‘A’: Continuous monitoring of daily ET. . .. L 45: sporadic contributions. . . L 162: the Campbell and Norman 1998 transport model is highly parameterized and requires knowledge of canopy density, leaf angle distribution and clumping. None of this part of the model is described here. L 179: this iteration means that the energy balance is not well constrained since the iteration a priori assumes LE > = 0, thus you just have a lower bound but not an upper one and Eq. 3 is weakly constrained since you cannot solve it without PT assumption. L 232 meteorological forcing L 425 what is your measure for ‘reasonable’? L 439-444: these are key points (small field sizes under irrigation) that are buried in you results/discussion section and otherwise couched in equivocal terms, such as in the abstract where you say’ accuracy was . . . somewhat lower. . .. One cannot expect data fusion to ever solve these kinds of problems, meaning that better\ remote sensing satellites are needed if you wish to monitor these water use areas. Data fusion fits a niche for medium to large size fields, but for the future we will need finer resolution sensors. Anonymous Available online 6 August 2015
Contents lists available at ScienceDirect
Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet
Peer review report
Peer review report 1 On “Mapping daily evapotranspiration at field scales over rainfed and irrigated agricultural areas using remote sensing data fusion”
Original Submission Recommendation Minor Revision Comments to Author The authors report remotely sensed ET modeling results over two US agricultural sites. The new contribution is implementing and testing an existing data fusion approach using MODIS and Landsat data. The study does not develop a new approach, nor does it refine existing approaches, but it does provide important and useful evidence for the utility of fusing remote sensing data of different kinds to obtain more frequent and better spatial resolution estimates of ET than would otherwise be obtained from a single satellite The manuscript lacks support for parameterization of crop light interception and net radiation computation. How do we know you didn’t custom tune in a non-general and non-physical way? It would help if you provide readers more specifics on all parameters The manuscript is generally well written but there are several instances of spelling errors and peculiar use of English. I suggest a careful review and edit by all authors to correct the problems Abstract Findings are mostly described but missing was mention and notable feature of the underlying data fusion approach, namely STARFM. Certainly testing the approach and verifying its accuracy for two rainfed & irrigated sites, but the overriding importance of the work is the implementation of a particular data fusion methodology. It is the methodology and its potential generality that will have lasting importance. Summary and Conclusions The liberal use of subjective evaluations such as ‘satisfactory agreement’ is inappropriate unless you can provide some measures of ‘satisfaction’. Address this lack of measures would help this section and the paper overall since you can the say something about the current state of art and how your work is advancing the science of ET with remote sensing.
DOI of original article: http://dx.doi.org/10.1016/j.agrformet.2013.11.001. 0168-1923/$ – see front matter http://dx.doi.org/10.1016/j.agrformet.2015.08.121
I can accept the general remark about monitoring water use over large agricultural areas—it is widely used in the literature—but it too could be refined. One of the big questions that you might think is beyond this paper’s scope is who would be the potential monitors? Certainly if you asked individual farmers they would almost surely say that they are not at all keen to have their water use data available to authorities. You cant address that particular issue in this paper, but you could cite regions of the world where water management is tightly regulated by governments or (for example) irrigation districts. Doing so will more precisely motivate your work. L 24: suggest you drop the first ‘A’: Continuous monitoring of daily ET. . .. L 45: sporadic contributions. . . L 162: the Campbell and Norman 1998 transport model is highly parameterized and requires knowledge of canopy density, leaf angle distribution and clumping. None of this part of the model is described here. L 179: this iteration means that the energy balance is not well constrained since the iteration a priori assumes LE > = 0, thus you just have a lower bound but not an upper one and Eq. 3 is weakly constrained since you cannot solve it without PT assumption. L 232 meteorological forcing L 425 what is your measure for ‘reasonable’? L 439-444: these are key points (small field sizes under irrigation) that are buried in you results/discussion section and otherwise couched in equivocal terms, such as in the abstract where you say’ accuracy was . . . somewhat lower. . .. One cannot expect data fusion to ever solve these kinds of problems, meaning that better\ remote sensing satellites are needed if you wish to monitor these water use areas. Data fusion fits a niche for medium to large size fields, but for the future we will need finer resolution sensors. Anonymous Available online 6 August 2015