Water and surface energy balance model with a multilayer canopy representation for remote sensing purposes

1989 ◽  
Vol 25 (5) ◽  
pp. 949-971 ◽  
Author(s):  
A. A. van de Griend ◽  
J. H. van Boxel
2009 ◽  
Vol 28 (1) ◽  
pp. 51-64 ◽  
Author(s):  
Luis Octavio Lagos ◽  
Derrel L. Martin ◽  
Shashi B. Verma ◽  
Andrew Suyker ◽  
Suat Irmak

2009 ◽  
Vol 48 (4) ◽  
pp. 693-715 ◽  
Author(s):  
Toru Kawai ◽  
Mohammad Kholid Ridwan ◽  
Manabu Kanda

Abstract The authors’ objective was to apply the Simple Urban Energy Balance Model for Mesoscale Simulation (SUMM) to cities. Data were selected from 1-yr flux observations conducted at three sites in two cities: one site in Kugahara, Japan (Ku), and two sites in Basel, Switzerland (U1 and U2). A simple vegetation scheme was implemented in SUMM to apply the model to vegetated cities, and the surface energy balance and radiative temperature TR were evaluated. SUMM generally reproduced seasonal and diurnal trends of surface energy balance and TR at Ku and U2, whereas relatively large errors were obtained for the daytime results of sensible heat flux QH and heat storage ΔQS at U1. Overall, daytime underestimations of QH and overestimations of ΔQS and TR were common. These errors were partly induced by the poor parameterization of the natural logarithm of the ratio of roughness length for momentum to heat (κB−1); that is, the observed κB−1 values at vegetated cities were smaller than the simulated values. The authors proposed a new equation for predicting this coefficient. This equation accounts for the existence of vegetation and improves the common errors described above. With the modified formula for κB−1, simulated net all-wave radiation and TR agreed well with observed values, regardless of site and season. However, at U1, simulated QH and ΔQS were still overestimated and underestimated, respectively, relative to observed values.


Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1747 ◽  
Author(s):  
Camilo Souto ◽  
Octavio Lagos ◽  
Eduardo Holzapfel ◽  
Mahesh Lal Maskey ◽  
Lynn Wunderlich ◽  
...  

A surface energy balance model was conceived to estimate crop transpiration and soil evaporation in orchards and vineyards where the floor is partially wetted by micro-irrigation systems. The proposed surface energy balance model for partial wetting (SEB-PW) builds upon previous multiple-layer modelling approaches to estimate the latent, sensible, and soil heat fluxes, while partitioning the total evapotranspiration ( E T ) into dry and wet soil evaporation ( λ E s o i l ) and crop transpiration ( T ). The model estimates the energy balance and flux resistances for the evaporation from dry and wet soil areas below the canopy, evaporation from dry and wet soil areas between plant rows, crop transpiration, and total crop E T . This article describes the model development, sensitivity analysis and a preliminary model evaluation. The evaluation shows that simulated hourly E T values have a good correlation with field measurements conducted with the surface renewal method and micro-lysimeter measurements in a micro-irrigated winegrape vineyard of Northern California for a range of fractional crop canopy cover conditions. Evaluation showed that hourly L E estimates had root mean square error ( R M S E ) of 58.6 W m−2, mean absolute error ( M A E ) of 35.6 W m−2, Nash-Sutcliffe coefficient ( C N S ) of 0.85, and index of agreement ( d a ) of 0.94. Daily soil evaporation ( E s ) estimations had R M S E of 0.30 mm d−1, M A E of 0.24 mm d−1, C N S of 0.87, and d a of 0.94. E s estimation had a coefficient of determination ( r 2 ) of 0.95, when compared with the micro-lysimeter measurements, which showed that E s can reach values from 28% to 46% of the total E T after an irrigation event. The proposed SEB-PW model can be used to estimate the effect and significance of soil evaporation from wet and dry soil areas on the total E T , and to inform water balance studies for optimizing irrigation management. Further evaluation is needed to test the model in other partially wetted orchards and to test the model performance during all growing seasons and for different environmental conditions.


2017 ◽  
Vol 21 (3) ◽  
pp. 1339-1358 ◽  
Author(s):  
Jordi Cristóbal ◽  
Anupma Prakash ◽  
Martha C. Anderson ◽  
William P. Kustas ◽  
Eugénie S. Euskirchen ◽  
...  

Abstract. The Arctic has become generally a warmer place over the past decades leading to earlier snow melt, permafrost degradation and changing plant communities. Increases in precipitation and local evaporation in the Arctic, known as the acceleration components of the hydrologic cycle, coupled with land cover changes, have resulted in significant changes in the regional surface energy budget. Quantifying spatiotemporal trends in surface energy flux partitioning is key to forecasting ecological responses to changing climate conditions in the Arctic. An extensive local evaluation of the Two-Source Energy Balance model (TSEB) – a remote-sensing-based model using thermal infrared retrievals of land surface temperature – was performed using tower measurements collected over different tundra types in Alaska in all sky conditions over the full growing season from 2008 to 2012. Based on comparisons with flux tower observations, refinements in the original TSEB net radiation, soil heat flux and canopy transpiration parameterizations were identified for Arctic tundra. In particular, a revised method for estimating soil heat flux based on relationships with soil temperature was developed, resulting in significantly improved performance. These refinements result in mean turbulent flux errors generally less than 50 W m−2 at half-hourly time steps, similar to errors typically reported in surface energy balance modeling studies conducted in more temperate climatic regimes. The MODIS leaf area index (LAI) remote sensing product proved to be useful for estimating energy fluxes in Arctic tundra in the absence of field data on the local biomass amount. Model refinements found in this work at the local scale build toward a regional implementation of the TSEB model over Arctic tundra ecosystems, using thermal satellite remote sensing to assess response of surface fluxes to changing vegetation and climate conditions.


2016 ◽  
Author(s):  
Jordi Cristóbal ◽  
Anupma Prakash ◽  
Martha C. Anderson ◽  
William P. Kustas ◽  
Eugénie S. Euskirchen ◽  
...  

Abstract. The Arctic has become generally a warmer place over the past decades leading to earlier snow melt, permafrost degradation and changing plant communities. Increases in precipitation and local evaporation in the Arctic, known as one of the acceleration components of the hydrologic cycle, coupled with land cover changes, have resulted in significant changes in the regional surface energy budget. Quantifying spatiotemporal trends in surface energy flux partitioning is a key to forecasting ecological responses to changing climate conditions in the Arctic regions. An extensive evaluation of the two-source energy balance model (TSEB) – a remote sensing-based model using thermal infrared retrievals of land–surface temperature – was performed using tower measurements collected over different tundra types in Alaska in all sky conditions over the full growing season from 2008 to 2012. Based on comparisons with flux tower observations, refinements in the original TSEB net radiation, soil heat flux and canopy transpiration parameterizations were identified for the unique Arctic tundra conditions. In particular, a revised method for estimating soil heat flux based on relationships with soil temperature was developed, resulting in significantly improved performance. These refinements result in mean flux errors around 50 W m−2 at half-hourly timesteps similar to errors typically reported in surface energy balance modeling studies conducted in more temperate climatic regimes. MODIS LAI remote sensing product proved to be useful for estimating energy fluxes in Arctic tundra in the absence of field data. This work builds toward a regional implementation of the TSEB model over Arctic tundra ecosystems, using thermal satellite remote sensing to assess response of surface fluxes to changing vegetation and climate conditions.


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