Surface energy balance algorithm for land-based consumption water use of different land use-cover types in arid-semiarid regions

2016 ◽  
Vol 16 (6) ◽  
pp. 1497-1513
Author(s):  
Shereif H. Mahmoud ◽  
A. A. Alazba
Keyword(s):  
Land Use ◽  
Energy Balance ◽  
Surface Energy ◽  
Water Use ◽  
Water Consumption ◽  
Surface Energy Balance ◽  
Agricultural Land ◽  
Eastern Province ◽  
Very High ◽  
Coastal Lowlands

Spatiotemporal distributions of water consumption for various land use-cover types over the Eastern province of Saudi Arabia were estimated using Surface Energy Balance Algorithm. Water consumption of various land use and cover classes shows similar seasonal dynamic trends. The spatial distribution of annual actual evapotranspiration (AET) shows low values in the Empty Quarter (231–438 mm/yr), and moderate values in the Eastern Province borders (439–731 mm/yr). Very high AET values were observed in irrigated croplands in the Northern plains, Hafar Al-Batin, the central coastal lowlands, and the southern coastal lowlands, where annual AET ranged from 732 to 1,790 mm/yr, representing the majority of the study area agricultural land. Evaporative behavior of land use-cover types indicated that irrigated cropland, which occupies 0.37% of the study area, has an average daily AET ranging from 9.2 mm/day in January to a maximum value in April (30 mm/day). Average annual water use by irrigated cropland is relatively very high and it is roughly 1,786.9 mm/yr, while water bodies, which cover 0.023% (121.2 km2) of the study area, also had relatively high mean AET (660.8 mm/yr). Overall, AET rates for irrigated cropland are much higher than for other land uses.

scholarly journals SURFACE ENERGY BALANCE SYSTEM (SEBS) AND SATELLITE DATA FOR MONITORING WATER CONSUMPTION OF IRRIGATED SUGARCANE

2016 ◽  
Vol 36 (6) ◽  
pp. 1176-1185 ◽  
Author(s):  
Elizabeth Ferreira ◽  
Christiaan M. Mannaerts ◽  
Antonio A. Dantas ◽  
Bernardus H. Maathuis
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Water Consumption ◽  
Satellite Data ◽  
Surface Energy Balance ◽  
Balance System

Investigating the relationship between soil moisture and evapotranspiration at different surfaces. Do we improve fluxes just improving the land use in models?

2020 ◽  
Author(s):  
Carlos Román-Cascón ◽  
Marie Lothon ◽  
Fabienne Lohou ◽  
Aurore Brut ◽  
Oscar Hartogensis ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Moisture ◽  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Physiological State ◽  
Sensible Heat Flux ◽  
Surface Fluxes ◽  
Wave Radiation ◽  
The South

<p>A correct spatial representation of the surface energy balance is still a challenge. In a first step, and assuming a correct knowledge of the incoming short-wave radiation, it is the land cover that mostly controls the albedo and the long-wave radiation emitted to the atmosphere, influencing significantly the net radiation available at the surface and the surface temperature. In a second step, the partitioning of this energy into evapotranspiration and sensible heat flux is, in part, controlled by the availability of soil moisture but also by the type, characteristics and physiological state of the vegetation covering the surface, since plants provide a pathway for soil moisture to the atmosphere through transpiration.</p><p>Hence, to correctly model the surface energy balance, we face three main challenges: an appropriate representation of the land use, soil moisture and a correct modelling of how plants regulate their stomatal behaviour under different soil-moisture limited conditions.</p><p>In this work, by using <em>in situ</em> data we explore the relations between soil moisture and evapotranspiration from several vegetation types at different soil-moisture limited regions: a wetter area in the south of France and a drier one in the south of Spain. For this, we try to distinguish different periods and vegetation states. Since significant differences are observed for the various plant types, we investigate whether using a more realistic and higher-resolution land-use database in the Weather Research and Forecasting (WRF) model improves the simulation of soil moisture and surface fluxes.</p>

scholarly journals Warming Effort and Energy Budget Difference of Various Human Land Use Intensity: Case Study of Beijing, China

Land ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 280
Author(s):  
Shenghui Zhou ◽  
Ke Wang ◽  
Shiqi Yang ◽  
Wenli Li ◽  
Yuxuan Zhang ◽  
...  
Keyword(s):  
Land Use ◽  
Energy Balance ◽  
Surface Energy ◽  
Energy Budget ◽  
Human Activities ◽  
Radiative Forcing ◽  
Surface Energy Balance ◽  
Land Use Intensity ◽  
Human Land Use ◽  
Land Use Types

Human land use intensity affects the surface energy balance by changing the biogeophysical parameters. This study used Moderate Resolution Imaging Spectroradiometer remote sensing data and surface energy balance algorithms to quantify changes in surface energy budgets corresponding to changes in land use in Beijing from 2000 to 2015. Land use was reclassified by considering land use intensity. The difference in the latent heat flux (LE) and net radiation (Rn) (LE−Rn) expressed the warming or cooling effect. The results showed that: (i) The increasing trend of net longwave radiation in Beijing offset the decreasing trend of net shortwave radiation. The Rn changed slightly, while the LE and LE−Rn showed a significant increase of 0.55 and 0.56 W/(m²∙year), respectively. The findings indicated that considering only radiative forcing, or even Rn, was not enough to measure the impacts of land use change on the energy budget. (ii) The order of Rn, LE, and LE−Rn values from high to low were natural and seminatural areas, cropland, mixed pixel areas, urban expansion areas, and old urban areas. Compared with natural and seminatural areas, the changing LE−Rn trend in the other four land use types decreased with the increase in human impact intensity, indicating that human activities weakened the positive change trend of LE−Rn and increased the warming effect. (iii) Although the temporal trend of LE increased in Beijing from 2000 to 2015, the effect of Rn on LE−Rn was greater than that of LE, especially in the four land use types affected by human activities. The results for surface temperature in various land use types confirmed this point. This study highlights the energy budget differences of various land use types affected by human activities. It makes an important contribution to understanding the urban heat island effect from a biogeophysical perspective.

scholarly journals The Role of CO2 and Dynamic Vegetation on the Impact of Temperate Land-Use Change in the HadCM3 Coupled Climate Model

2016 ◽  
Vol 20 (10) ◽  
pp. 1-20 ◽  
Author(s):  
Edward Armstrong ◽  
Paul Valdes ◽  
Jo House ◽  
Joy Singarayer
Keyword(s):  
Land Use ◽  
Energy Balance ◽  
Land Use Change ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Climate Model ◽  
Atmospheric Co2 ◽  
Vegetation Distribution ◽  
Coupled Climate Model ◽  
The Impact

Abstract Human-induced land-use change (LUC) alters the biogeophysical characteristics of the land surface influencing the surface energy balance. The level of atmospheric CO2 is expected to increase in the coming century and beyond, modifying temperature and precipitation patterns and altering the distribution and physiology of natural vegetation. It is important to constrain how CO2-induced climate and vegetation change may influence the regional extent to which LUC alters climate. This sensitivity study uses the HadCM3 coupled climate model under a range of equilibrium forcings to show that the impact of LUC declines under increasing atmospheric CO2, specifically in temperate and boreal regions. A surface energy balance analysis is used to diagnose how these changes occur. In Northern Hemisphere winter this pattern is attributed in part to the decline in winter snow cover and in the summer due to a reduction in latent cooling with higher levels of CO2. The CO2-induced change in natural vegetation distribution is also shown to play a significant role. Simulations run at elevated CO2, yet present-day vegetation show a significantly increased sensitivity to LUC, driven in part by an increase in latent cooling. This study shows that modeling the impact of LUC needs to accurately simulate CO2-driven changes in precipitation and snowfall and incorporate accurate, dynamic vegetation distribution.

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