scholarly journals The Thermodynamic Effect of Shallow Groundwater on Temperature and Energy Balance at Bare Land Surface

10.5772/19691 ◽  
2011 ◽  
Author(s):  
F. Alkhaier ◽  
G. N. ◽  
Z. Su
Keyword(s):  
Energy Balance ◽  
Land Surface ◽  
Shallow Groundwater ◽  
Thermodynamic Effect ◽  
Bare Land

scholarly journals Shallow groundwater effect on land surface temperature and surface energy balance under bare soil conditions: modeling and description

2012 ◽  
Vol 16 (7) ◽  
pp. 1817-1831 ◽  
Author(s):  
F. Alkhaier ◽  
G. N. Flerchinger ◽  
Z. Su
Keyword(s):  
Energy Balance ◽  
Surface Temperature ◽  
Land Surface ◽  
Shallow Groundwater ◽  
Bare Soil ◽  
Heat Fluxes ◽  
Shortwave Radiation ◽  
Soil Conditions ◽  
Potential Evaporation ◽  
Available Energy

Abstract. Understanding when and how groundwater affects surface temperature and energy fluxes is significant for utilizing remote sensing in groundwater studies and for integrating aquifers within land surface models. To investigate the shallow groundwater effect under bare soil conditions, we numerically exposed two soil profiles to identical metrological forcing. One of the profiles had shallow groundwater. The different responses that the two profiles manifested were inspected regarding soil moisture, temperature and energy balance at the land surface. The findings showed that the two profiles differed in three aspects: the absorbed and emitted amounts of energy, the portioning out of the available energy and the heat fluency in the soil. We concluded that due to their lower albedo, shallow groundwater areas reflect less shortwave radiation and consequently get a higher magnitude of net radiation. When potential evaporation demand is sufficiently high, a large portion of the energy received by these areas is consumed for evaporation. This increases the latent heat flux and reduces the energy that could have heated the soil. Consequently, lower magnitudes of both sensible and ground heat fluxes are caused to occur. The higher soil thermal conductivity in shallow groundwater areas facilitates heat transfer between the top soil and the subsurface, i.e. soil subsurface is more thermally connected to the atmosphere. For the reliability of remote sensors in detecting shallow groundwater effect, it was concluded that this effect can be sufficiently clear to be detected if at least one of the following conditions occurs: high potential evaporation and high contrast between day and night temperatures. Under these conditions, most day and night hours are suitable for shallow groundwater depth detection.

scholarly journals Reconnoitering the effect of shallow groundwater on land surface temperature and surface energy balance using MODIS and SEBS

2012 ◽  
Vol 16 (7) ◽  
pp. 1833-1844 ◽  
Author(s):  
F. Alkhaier ◽  
Z. Su ◽  
G. N. Flerchinger
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Temperature ◽  
Water Table ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Shallow Groundwater ◽  
Companion Paper ◽  
Daily Evaporation

Abstract. The possibility of observing shallow groundwater depth and areal extent using satellite measurements can support groundwater models and vast irrigation systems management. Moreover, these measurements can help to include the effect of shallow groundwater on surface energy balance within land surface models and climate studies, which broadens the methods that yield more reliable and informative results. To examine the capacity of MODIS in detecting the effect of shallow groundwater on land surface temperature and the surface energy balance in an area within Al-Balikh River basin in northern Syria, we studied the interrelationship between in-situ measured water table depths and land surface temperatures measured by MODIS. We, also, used the Surface Energy Balance System (SEBS) to calculate surface energy fluxes, evaporative fraction and daily evaporation, and inspected their relationships with water table depths. We found out that the daytime temperature increased while the nighttime temperature decreased when the depth of the water table increased. And, when the water table depth increased, net radiation, latent and ground heat fluxes, evaporative fraction and daily evaporation decreased, while sensible heat flux increased. This concords with the findings of a companion paper (Alkhaier et al., 2012). The observed clear relationships were the result of meeting both conditions that were concluded in the companion paper, i.e. high potential evaporation and big contrast in day-night temperature. Moreover, the prevailing conditions in this study area helped SEBS to yield accurate estimates. Under bare soil conditions and under the prevailing weather conditions, we conclude that MODIS is suitable for detecting the effect of shallow groundwater because it has proper imaging times and adequate sensor accuracy; nevertheless, its coarse spatial resolution is disadvantageous.

scholarly journals Reconnoitering the effect of shallow groundwater on land surface temperature and surface energy balance using MODIS and SEBS

2011 ◽  
Vol 8 (5) ◽  
pp. 8671-8700 ◽  
Author(s):  
F. Alkhaier ◽  
Z. Su ◽  
G. N. Flerchinger
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Temperature ◽  
Water Table ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Shallow Groundwater ◽  
Companion Paper ◽  
Daily Evaporation

Abstract. The possibility of observing shallow groundwater depth and areal extent using satellite measurements can support groundwater models and vast irrigation systems management. Besides, these measurements help bringing groundwater effect on surface energy balance within land surface models and climate studies. To inspect the MODIS capacity of detecting shallow groundwater effect on land surface temperature and surface energy balance in an area within Al-Balikh River basin in northern Syria, we investigated the interrelationship between in-situ measured water table depths and land surface temperatures of MODIS. Further, we used the Surface Energy Balance System (SEBS) to calculate surface energy fluxes, evaporative fraction and daily evaporation, and inspected their relationships with water table depths. In agreement with the findings of a companion paper (Alkhaier et al., 2011), we found that daytime temperature increased and nighttime temperature decreased with increasing water table depth. Where water table depth increased, net radiation, latent and ground heat fluxes, evaporative fraction and daily evaporation decreased, while sensible heat flux increased. The clear observed relationships resulted from meeting both conditions concluded in the companion paper, i.e. high potential evaporation and big contrast in air temperature. Moreover, the prevailing conditions in this study area helped SEBS producing accurate estimates. We conclude that MODIS is suitable for shallow groundwater effect detection since it has proper imaging times and appropriate sensor accuracy; nevertheless, its coarse spatial resolution is disadvantageous.

scholarly journals Shallow groundwater effect on land surface temperature and surface energy balance under bare soil conditions: modeling and description

2011 ◽  
Vol 8 (5) ◽  
pp. 8639-8670 ◽  
Author(s):  
F. Alkhaier ◽  
G. N. Flerchinger ◽  
Z. Su
Keyword(s):  
Energy Balance ◽  
Surface Temperature ◽  
Land Surface ◽  
Shallow Groundwater ◽  
Bare Soil ◽  
Heat Fluxes ◽  
Shortwave Radiation ◽  
Soil Conditions ◽  
Potential Evaporation ◽  
Meteorological Forcing

Abstract. Appreciating when and how groundwater affects surface temperature and energy fluxes is important for utilizing remote sensing in groundwater studies and for integrating aquifers within land surface models. To explore the shallow groundwater effect, we numerically exposed two soil profiles – one having shallow groundwater – to the same meteorological forcing, and inspected their different responses regarding surface soil moisture, temperature and energy balance. We found that the two profiles differed in the absorbed and emitted amounts of energy, in portioning out the available energy and in heat fluency within the soil. We conclude that shallow groundwater areas reflect less shortwave radiation due to their lower albedo and therefore they get higher magnitude of net radiation. When potential evaporation demand is high enough, a large portion of the energy received by these areas is spent on evaporation. This makes the latent heat flux predominant, and leaves less energy to heat the soil. Consequently, this induces lower magnitudes of both sensible and ground heat fluxes. The higher soil thermal conductivity in shallow groundwater areas facilitates heat transfer between the top soil and the subsurface, i.e. soil subsurface is more thermally connected to the atmosphere. In view of remote sensors' capability of detecting shallow groundwater effect, we conclude that this effect can be sufficiently clear to be sensed if at least one of two conditions is met: high potential evaporation and big contrast in air temperature between day and night. Under these conditions, most day and night hours are suitable for shallow groundwater depth detection.

Estimation of Evapotranspiration using Remote Sensing and Surface Energy Balance Algorithm for Land (SEBAL) in Canal Command

2021 ◽  
Vol 58 (03) ◽  
pp. 274-285
Author(s):  
H. V. Parmar ◽  
N. K. Gontia
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Surface Energy ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Crop Growth ◽  
Growth Stages ◽  
Landsat 8 ◽  
Surface Temperatures ◽  
Canal Command

Remote sensing based various land surface and bio-physical variables like Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), surface albedo, transmittance and surface emissivity are useful for the estimation of spatio-temporal variations in evapotranspiration (ET) using Surface Energy Balance Algorithm for Land (SEBAL) method. These variables were estimated under the present study for Ozat-II canal command in Junagadh district, Gujarat, India, using Landsat-7 and Landsat-8 images of summer season of years 2014 and 2015. The derived parameters were used in SEBAL to estimate the Actual Evapotranspiration (AET) of groundnut and sesame crops. The lower values NDVI observed during initial (March) and end (May) stages of crop growth indicated low vegetation cover during these periods. With full canopy coverage of the crops, higher value of NDVI (0.90) was observed during the mid-crop growth stage. The remote sensing-based LST was lower for agricultural areas and the area near banks of the canal and Ozat River, while higher surface temperatures were observed for rural settlements, road and areas with exposed dry soil. The maximum surface temperatures in the cropland were observed as 311.0 K during March 25, 2014 and 315.8 K during May 31, 2015. The AET of summer groundnut increased from 3.75 to 7.38 mm.day-1, and then decreased to 3.99 mm.day-1 towards the end stage of crop growth. The daily AET of summer sesame ranged from 1.06 to 7.72 mm.day-1 over different crop growth stages. The seasonal AET of groundnut and sesame worked out to 358.19 mm and 346.31 mm, respectively. The estimated AET would be helpful to schedule irrigation in the large canal command.

scholarly journals Snow specific surface area simulation using the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS)

2013 ◽  
Vol 7 (3) ◽  
pp. 961-975 ◽  
Author(s):  
A. Roy ◽  
A. Royer ◽  
B. Montpetit ◽  
P. A. Bartlett ◽  
A. Langlois
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Liquid Water ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Liquid Water Content ◽  
Canadian Land Surface Scheme ◽  
Snow Model ◽  
Surface Scheme ◽  
The One

Abstract. Snow grain size is a key parameter for modeling microwave snow emission properties and the surface energy balance because of its influence on the snow albedo, thermal conductivity and diffusivity. A model of the specific surface area (SSA) of snow was implemented in the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS) version 3.4. This offline multilayer model (CLASS-SSA) simulates the decrease of SSA based on snow age, snow temperature and the temperature gradient under dry snow conditions, while it considers the liquid water content of the snowpack for wet snow metamorphism. We compare the model with ground-based measurements from several sites (alpine, arctic and subarctic) with different types of snow. The model provides simulated SSA in good agreement with measurements with an overall point-to-point comparison RMSE of 8.0 m2 kg–1, and a root mean square error (RMSE) of 5.1 m2 kg–1 for the snowpack average SSA. The model, however, is limited under wet conditions due to the single-layer nature of the CLASS model, leading to a single liquid water content value for the whole snowpack. The SSA simulations are of great interest for satellite passive microwave brightness temperature assimilations, snow mass balance retrievals and surface energy balance calculations with associated climate feedbacks.

scholarly journals Estimating evaporation with thermal UAV data and two-source energy balance models

2016 ◽  
Vol 20 (2) ◽  
pp. 697-713 ◽  
Author(s):  
H. Hoffmann ◽  
H. Nieto ◽  
R. Jensen ◽  
R. Guzinski ◽  
P. Zarco-Tejada ◽  
...  
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
High Resolution ◽  
Eddy Covariance ◽  
Land Surface ◽  
Weather Conditions ◽  
Heat Fluxes ◽  
Thermal Camera ◽  
Model Input ◽  
Eddy Covariance Measurements

Abstract. Estimating evaporation is important when managing water resources and cultivating crops. Evaporation can be estimated using land surface heat flux models and remotely sensed land surface temperatures (LST), which have recently become obtainable in very high resolution using lightweight thermal cameras and Unmanned Aerial Vehicles (UAVs). In this study a thermal camera was mounted on a UAV and applied into the field of heat fluxes and hydrology by concatenating thermal images into mosaics of LST and using these as input for the two-source energy balance (TSEB) modelling scheme. Thermal images are obtained with a fixed-wing UAV overflying a barley field in western Denmark during the growing season of 2014 and a spatial resolution of 0.20 m is obtained in final LST mosaics. Two models are used: the original TSEB model (TSEB-PT) and a dual-temperature-difference (DTD) model. In contrast to the TSEB-PT model, the DTD model accounts for the bias that is likely present in remotely sensed LST. TSEB-PT and DTD have already been well tested, however only during sunny weather conditions and with satellite images serving as thermal input. The aim of this study is to assess whether a lightweight thermal camera mounted on a UAV is able to provide data of sufficient quality to constitute as model input and thus attain accurate and high spatial and temporal resolution surface energy heat fluxes, with special focus on latent heat flux (evaporation). Furthermore, this study evaluates the performance of the TSEB scheme during cloudy and overcast weather conditions, which is feasible due to the low data retrieval altitude (due to low UAV flying altitude) compared to satellite thermal data that are only available during clear-sky conditions. TSEB-PT and DTD fluxes are compared and validated against eddy covariance measurements and the comparison shows that both TSEB-PT and DTD simulations are in good agreement with eddy covariance measurements, with DTD obtaining the best results. The DTD model provides results comparable to studies estimating evaporation with similar experimental setups, but with LST retrieved from satellites instead of a UAV. Further, systematic irrigation patterns on the barley field provide confidence in the veracity of the spatially distributed evaporation revealed by model output maps. Lastly, this study outlines and discusses the thermal UAV image processing that results in mosaics suited for model input. This study shows that the UAV platform and the lightweight thermal camera provide high spatial and temporal resolution data valid for model input and for other potential applications requiring high-resolution and consistent LST.

scholarly journals An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data

2019 ◽  
Author(s):  
Bouchra Ait Hssaine ◽  
Olivier Merlin ◽  
Jamal Ezzahar ◽  
Nitu Ojha ◽  
Salah Er-raki ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Energy Balance ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Surface Soil ◽  
Surface Soil Moisture ◽  
Wide Range ◽  
The Mean

Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1 km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1 km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014–2018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014–2018). The field was seeded for the 2014–2015 (S1), 2016–2017 (S2) and 2017–2018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015–2016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated αPT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved αPT remains at a mostly constant value (∼ 0.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181 W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62 W/m2 for S1, S2, S3 and B1 respectively.

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