A surface energy balance method for partitioning evapotranspiration data into plant and soil components for a surface with partial canopy cover

1992 ◽  
Vol 28 (6) ◽  
pp. 1723-1732 ◽  
Author(s):  
W. J. Massman
2009 ◽  
Vol 28 (1) ◽  
pp. 51-64 ◽  
Author(s):  
Luis Octavio Lagos ◽  
Derrel L. Martin ◽  
Shashi B. Verma ◽  
Andrew Suyker ◽  
Suat Irmak

Agromet ◽  
2007 ◽  
Vol 21 (2) ◽  
pp. 27 ◽  
Author(s):  
I. Risdiyanto ◽  
R. Setiawan

<p>Leaf area index (LAI) is a variable showing relation between leaf area leaf and area closed over it. The conventionally technique to determine LAI value conducted by measure and accumulate wide of amount of leaf in one selected area and divided broadly area. The other technique, LAI also can be measured by using measuring instrument of solar radiation like attached tube solarimeter parallelly above and below/under plant canopy. Both of the approaches have limitation of spatial which developed new method with remote sensing technique. Determination of LAI with remote sensing technique exploits the nature of spectral of surface both from short wave (sun radiation) and long wave (surface radiation). One of the method able to be developed is surface energy balance approach with Beer-Lambert law. Result of this research indicate that value of LAI for the vegetation area by surface energy balance method and equation of Beer-Lambert law got value of mean LAI for natural forest equal to 3.05 with the range value 2.85 - 3.50 and R2 is 0.91, for the rubber agroforest equal to 3.01 with range value 2.79 - 3.40 and R2 is 0.69, while value of mean LAI for the plantation of monoculture of rubber equal to 2.96 with range value 2.74 - 3.28 and and R2 is 0.82. This method can be used for vegetation area especially for homogeneously like natural forest and monoculture.</p><p>---------------------------------------------------------------------</p><p>Indeks luas daun (ILD) merupakan suatu peubah yang menunjukkan hubungan antara luas daun dan luas bidang yang tertutupi. Secara konvensional penentuan nilai LAI dilakukan dengan mengukur dan mengakumulasikan jumlah luas daun dalam satu bidang tertentu dan dibagi dengan luas bidang tersebut. ILD juga dapat diukur menggunakan alat ukur radiasi surya seperti tube solari meter yang dipasang paralel di atas dan di bawah tajuk tumbuhan. Kedua pendekatan tersebut mempunyai keterbatasan spasial, sehingga dicoba mengembangkan metode baru dengan teknik penginderaan jauh. Pendugaan ILD dengan teknik ini memanfaatkan sifat spektral dari permukaan baik yang bersumber dari radiasi gelombang pendek dari matahari maupun radiasi gelombang panjang dari permukaan. Salah satu metode yang dapat dikembangkan adalah pendekatan neraca energi untuk menghasilkan peubah-peubah penduga ILD menggunakan hukum Beer-Lambert. Hasil penelitian ini menunjukkan bahwa nilai rata-rata ILD untuk lahan bervegetasi menggunakan metode neraca energi dan persamaan hukum Beer-Lambert untuk hutan alam sebesar 3.05 dengan nilai kisaran selang 2.85- 3.50 dan R2 validasi dengan ILD lapangan sebesar 0.91. Nilai rata-rata LAI pendugaan untuk agroforest karet sebesar 3.01 dengan selang 2.79–3.40 dan nilai R2 validasi sebesar 0.69, sedangkan nilai rata-rata ILD untuk perkebunan karet monokultur sebesar 2.96 dengan selang 2.74–3.28 dan nilai R2 validasi sebesar 0.82. Metode pendugaan ILD ini dapat digunakan untuk lahan bervegetasi terutama untuk pertanaman homogen seperti hutan alam dan monokultur.</p>


2021 ◽  
pp. 1-19
Author(s):  
Rebecca L. Stewart ◽  
Matthew Westoby ◽  
Francesca Pellicciotti ◽  
Ann Rowan ◽  
Darrel Swift ◽  
...  

Abstract Surface energy-balance models are commonly used in conjunction with satellite thermal imagery to estimate supraglacial debris thickness. Removing the need for local meteorological data in the debris thickness estimation workflow could improve the versatility and spatiotemporal application of debris thickness estimation. We evaluate the use of regional reanalysis data to derive debris thickness for two mountain glaciers using a surface energy-balance model. Results forced using ERA-5 agree with AWS-derived estimates to within 0.01 ± 0.05 m for Miage Glacier, Italy, and 0.01 ± 0.02 m for Khumbu Glacier, Nepal. ERA-5 data were then used to estimate spatiotemporal changes in debris thickness over a ~20-year period for Miage Glacier, Khumbu Glacier and Haut Glacier d'Arolla, Switzerland. We observe significant increases in debris thickness at the terminus for Haut Glacier d'Arolla and at the margins of the expanding debris cover at all glaciers. While simulated debris thickness was underestimated compared to point measurements in areas of thick debris, our approach can reconstruct glacier-scale debris thickness distribution and its temporal evolution over multiple decades. We find significant changes in debris thickness over areas of thin debris, areas susceptible to high ablation rates, where current knowledge of debris evolution is limited.


2020 ◽  
pp. 1-16
Author(s):  
Tim Hill ◽  
Christine F. Dow ◽  
Eleanor A. Bash ◽  
Luke Copland

Abstract Glacier surficial melt rates are commonly modelled using surface energy balance (SEB) models, with outputs applied to extend point-based mass-balance measurements to regional scales, assess water resource availability, examine supraglacial hydrology and to investigate the relationship between surface melt and ice dynamics. We present an improved SEB model that addresses the primary limitations of existing models by: (1) deriving high-resolution (30 m) surface albedo from Landsat 8 imagery, (2) calculating shadows cast onto the glacier surface by high-relief topography to model incident shortwave radiation, (3) developing an algorithm to map debris sufficiently thick to insulate the glacier surface and (4) presenting a formulation of the SEB model coupled to a subsurface heat conduction model. We drive the model with 6 years of in situ meteorological data from Kaskawulsh Glacier and Nàłùdäy (Lowell) Glacier in the St. Elias Mountains, Yukon, Canada, and validate outputs against in situ measurements. Modelled seasonal melt agrees with observations within 9% across a range of elevations on both glaciers in years with high-quality in situ observations. We recommend applying the model to investigate the impacts of surface melt for individual glaciers when sufficient input data are available.


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