HAPEX—MOBILHY: A Hydrologic Atmospheric Experiment the Study of Water Budget and Evaporation Flux at the Climatic Scale

1986 ◽  
Vol 67 (2) ◽  
pp. 138-144 ◽  
Author(s):  
Jean-Claude André ◽  
Jean-Paul Goutorbe ◽  
Alain Perrier
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Land Surface ◽  
Water Budget ◽  
General Circulation ◽  
Circulation Model ◽  
Surface Energy Budget ◽  
Surface Hydrology ◽  
Land Surface Water ◽  
Evaporation Flux

The HAPEX-MOBILHY program is aimed at studying the hydrological budget and evaporation flux at the scale of a GCM (general circulation model) grid square, i.e., 104 km2. Different surface and subsurface networks will be operated during the year 1986, to measure and monitor soil moisture, surface-energy budget and surface hydrology, as well as atmospheric properties. A two-and-a-half-month special observing period will allow for detailed measurements of atmospheric fluxes and for intensive remote sensing of surface properties using well-instrumented aircraft. The main objective of the program, for which guest investigations are strongly encouraged, is to provide a data base against which parameterization schemes for the land-surface water budget will be tested and developed.

Remote sensing: hydrology

2009 ◽  
Vol 33 (4) ◽  
pp. 490-509 ◽  
Author(s):  
Qiuhong Tang ◽  
Huilin Gao ◽  
Hui Lu ◽  
Dennis P. Lettenmaier
Keyword(s):  
Remote Sensing ◽  
Surface Water ◽  
Land Surface ◽  
Water Budget ◽  
Current Status ◽  
State Variables ◽  
Surface Hydrology ◽  
Earth Observing System ◽  
Land Surface Water ◽  
Terrestrial Water

Satellite remote sensing is a viable source of observations of land surface hydrologic fluxes and state variables, particularly in regions where in situ networks are sparse. Over the last 10 years, the study of land surface hydrology using remote sensing techniques has advanced greatly with the launch of NASA’s Earth Observing System (EOS) and other research satellite platforms, and with the development of more sophisticated retrieval algorithms. Most of the constituent variables in the land surface water balance (eg, precipitation, evapotranspiration, snow and ice, soil moisture, and terrestrial water storage variations) are now observable at varying spatial and temporal resolutions and accuracy via remote sensing. We evaluate the current status of estimates of each of these variables, as well as river discharge, the direct estimation of which is not yet possible. Although most of the constituent variables are observable by remote sensing, attempts to close the surface water budget from remote sensing alone have generally been unsuccessful, suggesting that current generation sensors and platforms are not yet able to provide hydrologically consistent observations of the land surface water budget at any spatial scale.

scholarly journals Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balances

2012 ◽  
Vol 16 (8) ◽  
pp. 2547-2565 ◽  
Author(s):  
G. Tang ◽  
P. J. Bartlein
Keyword(s):  
Soil Moisture ◽  
Surface Water ◽  
Surface Runoff ◽  
Land Surface ◽  
Surface Hydrology ◽  
Large Spatial Scale ◽  
Land Surface Water ◽  
Land Surface Hydrology ◽  
Water Balances ◽  
Global Vegetation

Abstract. Satellite-based data, such as vegetation type and fractional vegetation cover, are widely used in hydrologic models to prescribe the vegetation state in a study region. Dynamic global vegetation models (DGVM) simulate land surface hydrology. Incorporation of satellite-based data into a DGVM may enhance a model's ability to simulate land surface hydrology by reducing the task of model parameterization and providing distributed information on land characteristics. The objectives of this study are to (i) modify a DGVM for simulating land surface water balances; (ii) evaluate the modified model in simulating actual evapotranspiration (ET), soil moisture, and surface runoff at regional or watershed scales; and (iii) gain insight into the ability of both the original and modified model to simulate large spatial scale land surface hydrology. To achieve these objectives, we introduce the "LPJ-hydrology" (LH) model which incorporates satellite-based data into the Lund-Potsdam-Jena (LPJ) DGVM. To evaluate the model we ran LH using historical (1981–2006) climate data and satellite-based land covers at 2.5 arc-min grid cells for the conterminous US and for the entire world using coarser climate and land cover data. We evaluated the simulated ET, soil moisture, and surface runoff using a set of observed or simulated data at different spatial scales. Our results demonstrate that spatial patterns of LH-simulated annual ET and surface runoff are in accordance with previously published data for the US; LH-modeled monthly stream flow for 12 major rivers in the US was consistent with observed values respectively during the years 1981–2006 (R2 > 0.46, p < 0.01; Nash-Sutcliffe Coefficient > 0.52). The modeled mean annual discharges for 10 major rivers worldwide also agreed well (differences < 15%) with observed values for these rivers. Compared to a degree-day method for snowmelt computation, the addition of the solar radiation effect on snowmelt enabled LH to better simulate monthly stream flow in winter and early spring for rivers located at mid-to-high latitudes. In addition, LH-modeled monthly soil moisture for the state of Illinois (US) agreed well (R2 = 0.79, p < 0.01) with observed data for the years 1984–2001. Overall, this study justifies both the feasibility of incorporating satellite-based land covers into a DGVM and the reliability of LH to simulate land-surface water balances. To better estimate surface/river runoff at mid-to-high latitudes, we recommended that LPJ-DGVM considers the effects of solar radiation on snowmelt.

scholarly journals Impacts of soil-aquifer heat and water fluxes on simulated global climate

2013 ◽  
Vol 10 (1) ◽  
pp. 1185-1212 ◽  
Author(s):  
N. Y. Krakauer ◽  
M. J. Puma ◽  
B. I. Cook
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
General Circulation ◽  
Soil Column ◽  
Circulation Model ◽  
The Arctic ◽  
Water Fluxes ◽  
Limited Impact ◽  
Mean Climate ◽  
The Impact

Abstract. Climate models have traditionally only represented heat and water fluxes within relatively shallow soil layers, but there is increasing interest in the possible role of heat and water exchanges with the deeper subsurface. Here, we integrate an idealized 50 m deep aquifer into the land surface module of the GISS ModelE general circulation model to test the influence of aquifer-soil moisture and heat exchanges on climate variables. We evaluate the impact on the modeled climate of aquifer-soil heat and water fluxes separately, as well as in combination. The addition of the aquifer to ModelE has limited impact on annual-mean climate, with little change in global mean land temperature, precipitation, or evaporation. The seasonal amplitude of deep soil temperature is strongly damped by the soil-aquifer heat flux. This not only improves the model representation of permafrost area but propagates to the surface, resulting in an increase in the seasonal amplitude of surface air temperature of >1 K in the Arctic. The soil-aquifer water and heat fluxes both slightly decrease interannual variability in soil moisture and land-surface temperature, and decrease the soil moisture memory of the land surface on annual timescales. The results of this experiment suggest that deepening the modeled land surface, compared to modeling only a shallower soil column with a no-flux bottom boundary condition, has limited impact on mean climate but does affect seasonality and interannual persistence.

Revealing the impact of deforestation on hydrology using remote sensing and land surface modeling

2020 ◽  
Author(s):  
Michiel Maertens ◽  
Gabrielle De Lannoy ◽  
Sebastian Apers ◽  
Sujay Kumar
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Land Cover ◽  
Land Surface ◽  
Water Budget ◽  
Land Surface Modeling ◽  
Operational Level ◽  
Vegetation Parameters ◽  
The Impact ◽  
Level 2

&lt;p&gt;This study aims at better understanding the impact of deforestation on the local hydrology over the Argentinian Chaco, using land surface modeling and remote sensing data. The Chaco is an ecoregion characterized by unprecedented deforestation since the 1980s, mainly for cattle ranging and soybean production. More specifically, default climatological vegetation parameters (LAI, GVF) and static land cover in state-of-the-art land surface models (LSM), grouped within the NASA Land Information System (LIS), are updated using satellite-based dynamic vegetation parameters and yearly land use maps to feed the models with deforestation.&lt;/p&gt;&lt;p&gt;The presentation will show a spatio-temporal analysis of long-term water budget simulations using a range of LSMs (Noah, CLM, CLSM) in which dynamically updated vegetation and land cover parameters are included. Our simulations indicate that different LSMs result in a different partitioning of the total water budget, but all indicate an increase in soil moisture and percolation over the deforested areas. &amp;#160;Model output is evaluated using in situ soil moisture data, and various soil moisture retrieval products from SMOS (operational Level 2 and SMOS-IC) and SMAP (operational Level 2) and evapotranspiration data from GLEAM.&lt;/p&gt;

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