Estimation of Land Surface Heat Fluxes Based on Landsat 7 ETM+ Data and Field Measurements over the Northern Tibetan Plateau

Gao, Nan; Zhong, Lei; Ma, Yaoming; Cheng, Mingming; Wang, Xian; Zou, Minmin; Huang, Zhengyi

doi:10.3390/rs11242899

Cited by 10 publications

(4 citation statements)

References 41 publications

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“…where H c and H s are sensible heat fluxes for the canopy and soil (W•m −2 ), respectively, ρ a is the air density at constant pressure (Kg.m −3 ), C p is the specific heat of the air at constant pressure (1004 J•kg −1 •K −1 ), LST is the land surface temperature (K), T a is the air temperature (K), r a,s is the aerodynamic resistance for the soil (s•m −1 ), and r a,c is the aerodynamic resistance for the canopy (s•m −1 ). ρ a [81], f c [327] and r a [71] are obtained from Equations (A18), (A19) and (A20), respectively:…”

Section: Appendix a Acronymsmentioning

confidence: 99%

Energy-Based Approaches in Estimating Actual Evapotranspiration Focusing on Land Surface Temperature: A Review of Methods, Concepts, and Challenges

et al. 2022

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The surface energy balance (SEB) model is a physically based approach in which aerodynamic principles and bulk transfer theory are used to estimate actual evapotranspiration. A wide range of different methods have been developed to parameterize the SEB equation; however, few studies addressed solutions to the SEB considering the land surface temperature (LST). Therefore, in the current review, a clear and comprehensive classification is provided for energy-based approaches considering the key role of LST in solving the energy budget. In this regard, three general approaches are presented using LSTs derived by climate and land surface models (LSMs), satellite-based data, and energy balance closure. In addition, this review surveys the concepts, required inputs, and assumptions of energy-based LSMs and SEB algorithms in detail. The limitations and challenges of aforementioned approaches including land surface temperature, surface energy imbalance, and calculation of surface and aerodynamic resistance network are also assessed. According to the results, since the accuracy of resulting LSTs are affected by weather conditions, surface energy closure, and use of vegetation/meteorological information, all approaches are faced with uncertainties in determining ET. In addition, for further study, an interactive evaluation of water and energy conservation laws is recommended to improve the ET estimation accuracy.

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Section: Appendix a Acronymsmentioning

confidence: 99%

Energy-Based Approaches in Estimating Actual Evapotranspiration Focusing on Land Surface Temperature: A Review of Methods, Concepts, and Challenges

et al. 2022

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“…Readers can refer to CAMP/Tibet in Table 1 for detailed information about the location, time range and depths for each CAMP/Tibet station. CAMP/Tibet observations have already been widely used in many scientific studies [70,71].…”

Section: Datamentioning

confidence: 99%

Long-Term Characteristics of Surface Soil Moisture over the Tibetan Plateau and Its Response to Climate Change

Zhu,

Li,

Hagan

et al. 2023

Remote Sensing

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Soil moisture over the Tibetan Plateau (TP) can affect hydrological cycles on local and remote scales through land–atmosphere interactions. However, TP long-term surface soil moisture characteristics and their response to climate change are still unclear. In this study, we firstly evaluate two satellite-based products—SSM/I (the Special Sensor Microwave Imagers) and ECV COMBINED (the Essential Climate Variable combined)—and three reanalysis products—ERA5-Land (the fifth generation of the land component of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis), MERRA2 (the second version of Modern-Era Retrospective Analysis for Research and Applications), and GLDAS Noah (the Noah land surface model driven by Global Land Data Assimilation System)—against two in situ observation networks. SSM/I and GLDAS Noah outperform the other soil moisture products, followed by MERRA2 and ECV COMBINED, and ERA5-Land has a certain degree of uncertainty in evaluating TP surface soil moisture. Analysis of long-term soil moisture characteristics during 1988–2008 shows that annual and seasonal mean soil moisture have similar spatial distributions of soil moisture decreasing from southeast to northwest. Additionally, a significant increasing trend of soil moisture is found in most of the TP region. With a non-linear machine learning method, we quantify the contribution of each climatic variable to warm-season soil moisture. It indicates that precipitation dominates soil moisture changes rather than air temperature. Pixel-wise partial correlation coefficients further show that there are significant positive correlations between precipitation and soil moisture over most of the TP region. The results of this study will help to understand the role of TP soil moisture in land–atmosphere coupling and hydrological cycles under climate change.

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“…Feng et al [61] used an optimized two-source energy balance (TSEB) model to estimate LE for maize farmland in the Heihe River Basin, with an RMSE = 85 W/m 2 . Ge et al [62] used the SEBS model to estimate the energy balance components of alpine and subalpine meadow on the northern Tibetan Plateau (RMSE H = 68.2 W/m 2 and RMSE LE = 54.9 W/m 2 ).…”

Section: Inversion Accuracy Of Energy Fluxesmentioning

confidence: 99%

Comparison of Differences in Actual Cropland Evapotranspiration under Two Irrigation Methods Using Satellite-Based Model

Liu,

Ortega-Farías,

Fan

et al. 2023

Remote Sensing

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Remote sensing technology is widely used to obtain evapotranspiration (ETa), but whether it can distinguish the differences in farmland energy balance components and ETa under different irrigation methods has not been studied. We used Landsat 8 data as the primary dataset to drive the METRIC model and inverted the surface parameters and ETa of the Shiyang River Basin from 2014 to 2018. After improving the METRIC model using Ta obtained by the regression method instead of interpolation to calculate the net radiation flux (Rn), R2 was improved from 0.45 to 0.53, and the RMSE was reduced from 61 W/m2 to 51 W/m2. The ETa estimation results on satellite overpass days performed well, with R2 equal to 0.93 and RMSE equal to 0.48 mm when compared with the Eddy covariance method (EC) observations. Subsequently, the different growth stages and daily average ETa estimates of maize were compared with three observations (water balance, WB; Bowen ratio and energy balance method, BREB; and EC). The daily estimates of ETa correlate well with the observations of BREB (R2BI = 0.82, R2DI = 0.92; RMSEBI = 0.46 mm/day, RMSEDI = 0.32 mm/day) and EC (R2BI = 0.85, R2DI = 0.92; RMSEBI = 0.45 mm/day, RMSEDI = 0.34 mm/day), and the estimation for drip irrigation was found to be better than for border irrigation. The total accuracy of the ETa estimation on the five-year overpass day of maize farmland reached R2 = 0.93 and RMSE = 0.48 mm. With sufficient remote sensing data, the 4-year average ETa of maize was 31 mm lower for DI than for BI, and the mean value of ETa obtained from the three observation methods was 40 mm. The METRIC model can be used to distinguish ETa differences between the two irrigation methods in maize farmlands.

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Estimation of Land Surface Heat Fluxes Based on Landsat 7 ETM+ Data and Field Measurements over the Northern Tibetan Plateau

Cited by 10 publications

References 41 publications

Energy-Based Approaches in Estimating Actual Evapotranspiration Focusing on Land Surface Temperature: A Review of Methods, Concepts, and Challenges

Energy-Based Approaches in Estimating Actual Evapotranspiration Focusing on Land Surface Temperature: A Review of Methods, Concepts, and Challenges

Long-Term Characteristics of Surface Soil Moisture over the Tibetan Plateau and Its Response to Climate Change

Comparison of Differences in Actual Cropland Evapotranspiration under Two Irrigation Methods Using Satellite-Based Model

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