Time Scales of Land Surface Hydrology

2006 ◽  
Vol 7 (5) ◽  
pp. 868-879 ◽  
Author(s):  
Aihui Wang ◽  
Xubin Zeng ◽  
Samuel S. P. Shen ◽  
Qing-Cun Zeng ◽  
Robert E. Dickinson
Keyword(s):  
Soil Moisture ◽  
Time Scales ◽  
Time Scale ◽  
Land Surface ◽  
Vertical Structure ◽  
Root Zone ◽  
Layer Model ◽  
Surface Hydrology ◽  
Soil System ◽  
Land Surface Hydrology

Abstract This paper intends to investigate the time scales of land surface hydrology and enhance the understanding of the hydrological cycle between the atmosphere, vegetation, and soil. A three-layer model for land surface hydrology is developed to study the temporal variation and vertical structure of water reservoirs in the vegetation–soil system in response to precipitation forcing. The model is an extension of the existing one-layer bucket model. A new time scale is derived, and it better represents the response time scale of soil moisture in the root zone than the previously derived inherent time scale (i.e., the ratio of the field capacity to the potential evaporation). It is found that different water reservoirs of the vegetation–soil system have different time scales. Precipitation forcing is mainly concentrated on short time scales with small low-frequency components, but it can cause long time-scale disturbances in the soil moisture of root zone. This time scale increases with soil depth, but it can be reduced significantly under wetter conditions. Although the time scale of total water content in the vertical column in the three-layer model is similar to that of the one-layer bucket model, the time scale of evapotranspiration is very different. This suggests the need to consider the vertical structure in land surface hydrology reservoirs and in climate study.

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 Variability of phenology and fluxes of water and carbon with observed and simulated soil moisture in the Ent Terrestrial Biosphere Model (Ent TBM version 1.0.1.0.0)

2015 ◽  
Vol 8 (12) ◽  
pp. 3837-3865 ◽  
Author(s):  
Y. Kim ◽  
P. R. Moorcroft ◽  
I. Aleinov ◽  
M. J. Puma ◽  
N. Y. Kiang
Keyword(s):  
Soil Moisture ◽  
Leaf Area ◽  
Land Surface ◽  
Surface Hydrology ◽  
Terrestrial Biosphere ◽  
Dynamic Global Vegetation Model ◽  
Area Index ◽  
Frost Hardening ◽  
Land Surface Hydrology ◽  
Biosphere Model

Abstract. The Ent Terrestrial Biosphere Model (Ent TBM) is a mixed-canopy dynamic global vegetation model developed specifically for coupling with land surface hydrology and general circulation models (GCMs). This study describes the leaf phenology submodel implemented in the Ent TBM version 1.0.1.0.0 coupled to the carbon allocation scheme of the Ecosystem Demography (ED) model. The phenology submodel adopts a combination of responses to temperature (growing degree days and frost hardening), soil moisture (linearity of stress with relative saturation) and radiation (light length). Growth of leaves, sapwood, fine roots, stem wood and coarse roots is updated on a daily basis. We evaluate the performance in reproducing observed leaf seasonal growth as well as water and carbon fluxes for four plant functional types at five Fluxnet sites, with both observed and prognostic hydrology, and observed and prognostic seasonal leaf area index. The phenology submodel is able to capture the timing and magnitude of leaf-out and senescence for temperate broadleaf deciduous forest (Harvard Forest and Morgan–Monroe State Forest, US), C3 annual grassland (Vaira Ranch, US) and California oak savanna (Tonzi Ranch, US). For evergreen needleleaf forest (Hyytiäla, Finland), the phenology submodel captures the effect of frost hardening of photosynthetic capacity on seasonal fluxes and leaf area. We address the importance of customizing parameter sets of vegetation soil moisture stress response to the particular land surface hydrology scheme. We identify model deficiencies that reveal important dynamics and parameter needs.

scholarly journals Variability of phenology and fluxes of water and carbon with observed and simulated soil moisture in the Ent Terrestrial Biosphere Model (Ent TBM version 1.0.1.0.0)

2015 ◽  
Vol 8 (7) ◽  
pp. 5809-5871 ◽  
Author(s):  
Y. Kim ◽  
P. R. Moorcroft ◽  
I. Aleinov ◽  
M. J. Puma ◽  
N. Y. Kiang
Keyword(s):  
Soil Moisture ◽  
Leaf Area ◽  
Land Surface ◽  
Surface Hydrology ◽  
Terrestrial Biosphere ◽  
Dynamic Global Vegetation Model ◽  
Area Index ◽  
Frost Hardening ◽  
Land Surface Hydrology ◽  
Biosphere Model

Abstract. The Ent Terrestrial Biosphere Model (Ent TBM) is a mixed-canopy dynamic global vegetation model developed specifically for coupling with land surface hydrology and general circulation models (GCMs). This study describes the leaf phenology submodel implemented in the Ent TBM version 1.0.1.0.0, coupled to the carbon allocation scheme of the Ecosystem Demography (ED) model. The phenology submodel adopts a combination of responses to temperature (growing degree days and frost-hardening), soil moisture (linearity of stress with relative saturation), and radiation (light length). Growth of leaves, sapwood, fine roots, stem wood, and coarse roots is updated on a daily basis. We evaluate the performance in reproducing observed leaf seasonal growth as well as water and carbon fluxes for four plant functional types at five Fluxnet sites, with both observed and prognostic hydrology, and observed and prognostic seasonal leaf area index. The phenology submodel is able to capture the timing and magnitude of leafout and senescence for temperate broadleaf deciduous forest (Harvard Forest and Morgan–Monroe State Forest, US), C3 annual grassland (Vaira Ranch, US), and California oak savanna (Tonzi Ranch, US). For evergreen needleleaf forest (Hyytiäla, Finland), the phenology submodel captures the effect of frost-hardening of photosynthetic capacity on seasonal fluxes and leaf area. We address the importance of customizing parameter sets of vegetation soil moisture stress response to the particular land surface hydrology scheme. We identify model deficiencies that reveal important dynamics and parameter needs.

scholarly journals Assessment and Enhancement of MERRA Land Surface Hydrology Estimates

2011 ◽  
Vol 24 (24) ◽  
pp. 6322-6338 ◽  
Author(s):  
Rolf H. Reichle ◽  
Randal D. Koster ◽  
Gabriëlle J. M. De Lannoy ◽  
Barton A. Forman ◽  
Qing Liu ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Snow Water Equivalent ◽  
Root Zone ◽  
State Of The Art ◽  
Global Precipitation Climatology Project ◽  
Surface Hydrology ◽  
Independent Analysis ◽  
Hydrological Fields

Abstract The Modern-Era Retrospective Analysis for Research and Applications (MERRA) is a state-of-the-art reanalysis that provides, in addition to atmospheric fields, global estimates of soil moisture, latent heat flux, snow, and runoff for 1979–present. This study introduces a supplemental and improved set of land surface hydrological fields (“MERRA-Land”) generated by rerunning a revised version of the land component of the MERRA system. Specifically, the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameter values in the rainfall interception model, changes that effectively correct for known limitations in the MERRA surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ECMWF Re-Analysis-Interim (ERA-I). MERRA-Land and ERA-I root zone soil moisture skills (against in situ observations at 85 U.S. stations) are comparable and significantly greater than that of MERRA. Throughout the Northern Hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 18 U.S. basins) of MERRA and MERRA-Land is typically higher than that of ERA-I. With a few exceptions, the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using MERRA output for land surface hydrological studies.

Exploring the effects of the land surface on tropical precipitation

2021 ◽  
Author(s):  
Marianne Pietschnig ◽  
Abigail L. S. Swann ◽  
Ruth Geen ◽  
F. Hugo Lambert ◽  
Geoffrey K. Vallis
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Amazon Basin ◽  
Earth System ◽  
Maritime Continent ◽  
Surface Hydrology ◽  
System Models ◽  
Tropical Precipitation ◽  
Land Surface Hydrology ◽  
Earth System Models

&lt;p&gt;Projected precipitation changes over tropical land tend to be enhanced by vegetation responses to CO&lt;sub&gt;2&lt;/sub&gt; forcing in Earth System Models. Projected decreases in rainfall over the Amazon basin and increases over the Maritime Continent are both stronger when plant physiological changes are modelled than if these changes are neglected, but the reasons for this amplification remain unclear. The responses of vegetation to increasing CO&lt;sub&gt;2 &lt;/sub&gt;levels are complex and uncertain, but changes in stomatal conductance likely dominate the evapotranspiration response in Earth System Models.&lt;/p&gt;&lt;p&gt;We investigate why vegetation changes cause precipitation to increase more strongly over the Maritime Continent while decreasing more strongly over the Amazon basin. We employ an idealized Atmospheric General Circulation Model with a simplified vegetation scheme that captures CO&lt;sub&gt;2&lt;/sub&gt;-driven stomatal closure.&lt;/p&gt;&lt;p&gt;We find that &amp;#8211; counter-intuitively &amp;#8211; rainfall is enhanced over a narrow rectangular island when terrestrial evaporation falls to zero with high CO&lt;sub&gt;2&lt;/sub&gt;. Strong heating and ascent over the island trigger moisture advection from the surrounding ocean. In contrast, over larger continents rainfall depends on continental moisture recycling.&lt;/p&gt;&lt;p&gt;Simulations with two large rectangular continents representing South America and Africa reveal that the stronger decrease in rainfall over the Amazon basin is due to a combination of local and remote effects:&lt;/p&gt;&lt;p&gt;Finally, we investigate the impact of land-surface hydrology on continental rainfall on seasonal timescales. Using our idealized model and realistic continents, we study the strength of the South East Asian monsoon for different continental evaporation schemes. Surprisingly, when terrestrial evapotranspiration is unlimited (i.e. does not depend on soil moisture availability), monsoon precipitation is much weaker than when terrestrial evapotranspiration is limited by soil moisture. In order to explain this behavior, we compare the atmospheric energy budgets and circulation between the simulations.&lt;/p&gt;&lt;p&gt;Our results show that the land-surface hydrology plays an important role in modifying tropical precipitation and atmospheric dynamics on seasonal timescales and in the long-term under climate change, and that further investigation into the topic is called for.&lt;/p&gt;

scholarly journals Multilevel and multiscale drought reanalysis over France with the Safran-Isba-Modcou hydrometeorological suite

2010 ◽  
Vol 14 (3) ◽  
pp. 459-478 ◽  
Author(s):  
J.-P. Vidal ◽  
E. Martin ◽  
L. Franchistéguy ◽  
F. Habets ◽  
J.-M. Soubeyroux ◽  
...  
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Time Scales ◽  
Time Scale ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Multiple Time Scales ◽  
Flow Index ◽  
Severe Drought ◽  
Hydrological Droughts

Abstract. Physically-based droughts can be defined as a water deficit in at least one component of the land surface hydrological cycle. The reliance of different activity domains (water supply, irrigation, hydropower, etc.) on specific components of this cycle requires drought monitoring to be based on indices related to meteorological, agricultural, and hydrological droughts. This paper describes a high-resolution retrospective analysis of such droughts in France over the last fifty years, based on the Safran-Isba-Modcou (SIM) hydrometeorological suite. The high-resolution 1958–2008 Safran atmospheric reanalysis was used to force the Isba land surface scheme and the hydrogeological model Modcou. Meteorological droughts are characterized with the Standardized Precipitation Index (SPI) at time scales varying from 1 to 24 months. Similar standardizing methods were applied to soil moisture and streamflow for identifying multiscale agricultural droughts – through the Standardized Soil Wetness Index (SSWI) – and multiscale hydrological droughts, through the Standardized Flow Index (SFI). Based on a common threshold level for all indices, drought event statistics over the 50-yr period – number of events, duration, severity and magnitude – have been derived locally in order to highlight regional differences at multiple time scales and at multiple levels of the hydrological cycle (precipitation, soil moisture, streamflow). Results show a substantial variety of temporal drought patterns over the country that are highly dependent on both the variable and time scale considered. Independent spatio-temporal drought events have then been identified and described by combining local characteristics with the evolution of area under drought. Summary statistics have finally been used to compare past severe drought events, from multi-year precipitation deficits (1989–1990) to short hot and dry periods (2003). Results show that the ranking of drought events depends highly on both the time scale and the variable considered. This multilevel and multiscale drought climatology will serve as a basis for assessing the impacts of climate change on droughts in France.

scholarly journals Assessment of MERRA-2 Land Surface Hydrology Estimates

2017 ◽  
Vol 30 (8) ◽  
pp. 2937-2960 ◽  
Author(s):  
Rolf H. Reichle ◽  
Clara S. Draper ◽  
Q. Liu ◽  
Manuela Girotto ◽  
Sarith P. P. Mahanama ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Root Zone ◽  
The United States ◽  
Probability Of Detection ◽  
Satellite Observations ◽  
Surface Hydrology ◽  
Depletion Curve ◽  
Terrestrial Water ◽  
Land Hydrology

The MERRA-2 atmospheric reanalysis product provides global, 1-hourly estimates of land surface conditions for 1980–present at ~50-km resolution. MERRA-2 uses observations-based precipitation to force the land (unlike its predecessor, MERRA). This paper evaluates MERRA-2 and MERRA land hydrology estimates, along with those of the land-only MERRA-Land and ERA-Interim/Land products, which also use observations-based precipitation. Overall, MERRA-2 land hydrology estimates are better than those of MERRA-Land and MERRA. A comparison against GRACE satellite observations of terrestrial water storage demonstrates clear improvements in MERRA-2 over MERRA in South America and Africa but also reflects known errors in the observations used to correct the MERRA-2 precipitation. Validation against in situ measurements from 220–320 stations in North America, Europe, and Australia shows that MERRA-2 and MERRA-Land have the highest surface and root zone soil moisture skill, slightly higher than that of ERA-Interim/Land and higher than that of MERRA (significantly for surface soil moisture). Snow amounts from MERRA-2 have lower bias and correlate better against reference data from the Canadian Meteorological Centre than do those of MERRA-Land and MERRA, with MERRA-2 skill roughly matching that of ERA-Interim/Land. Validation with MODIS satellite observations shows that MERRA-2 has a lower snow cover probability of detection and probability of false detection than MERRA, owing partly to MERRA-2’s lower midwinter, midlatitude snow amounts and partly to MERRA-2’s revised snow depletion curve parameter compared to MERRA. Finally, seasonal anomaly R values against naturalized streamflow measurements in the United States are, on balance, highest for MERRA-2 and ERA-Interim/Land, somewhat lower for MERRA-Land, and lower still for MERRA (significantly in four basins).

scholarly journals On the utility of land surface models for agricultural drought monitoring

2012 ◽  
Vol 16 (9) ◽  
pp. 3451-3460 ◽  
Author(s):  
W. T. Crow ◽  
S. V. Kumar ◽  
J. D. Bolten
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Cross Correlation ◽  
Root Zone ◽  
Vegetation Indices ◽  
Agricultural Drought ◽  
Drought Monitoring ◽  
Global Evaluation ◽  
Land Surface Models ◽  
Surface Models

Abstract. The lagged rank cross-correlation between model-derived root-zone soil moisture estimates and remotely sensed vegetation indices (VI) is examined between January 2000 and December 2010 to quantify the skill of various soil moisture models for agricultural drought monitoring. Examined modeling strategies range from a simple antecedent precipitation index to the application of modern land surface models (LSMs) based on complex water and energy balance formulations. A quasi-global evaluation of lagged VI/soil moisture cross-correlation suggests, when globally averaged across the entire annual cycle, soil moisture estimates obtained from complex LSMs provide little added skill (< 5% in relative terms) in anticipating variations in vegetation condition relative to a simplified water accounting procedure based solely on observed precipitation. However, larger amounts of added skill (5–15% in relative terms) can be identified when focusing exclusively on the extra-tropical growing season and/or utilizing soil moisture values acquired by averaging across a multi-model ensemble.

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