On Estimating Wet Canopy Evaporation from Deciduous and Coniferous Forests in the Asian Monsoon Climate

Abstract Continuous and direct measurement of evapotranspiration (ET) by the eddy covariance (EC) technique is still a challenge under monsoon climate because of a considerable amount of missing data during the long rainy periods and the consequential gap-filling process. Under such wet canopy conditions, especially in forests, evaporation of the intercepted precipitation (EWC) contributes significantly to the total ET. To quantify the role of EWC, leaf wetness has been measured at multiple levels in the canopy simultaneously with eddy covariance measurements at the KoFlux Gwangneung deciduous and coniferous forests for the entire year from September 2007 to August 2008. In this study, the measured EWC and the controlling mechanism during the wet canopy conditions have been scrutinized. Based on the evaluation of the four different algorithms of EWC estimation, that of the variable infiltration capacity (VIC) land surface model (LSM) has been adopted. All the missing EWC data are then recalculated by using the algorithm of VIC LSM and compared against the traditionally gap-filled EWC data based on the modified lookup table (MLT) method. The latter consistently underestimated EWC on average by 39% in deciduous forest and by 28% in coniferous forest. Major causes of such differences were due to the failure of considering aerodynamic coupling, advection of sensible heat, and heat storage in the MLT-based gap-filling method. Accordingly, a new gap-filling strategy for EWC is proposed that takes proper controlling mechanisms into account.

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Comparing Evapotranspiration from Eddy Covariance Measurements, Water Budgets, Remote Sensing, and Land Surface Models over Canadaa,b

Journal of Hydrometeorology ◽

10.1175/jhm-d-14-0189.1 ◽

2015 ◽

Vol 16 (4) ◽

pp. 1540-1560 ◽

Cited By ~ 40

Author(s):

Shusen Wang ◽

Ming Pan ◽

Qiaozhen Mu ◽

Xiaoying Shi ◽

Jiafu Mao ◽

...

Keyword(s):

Remote Sensing ◽

Eddy Covariance ◽

Land Surface ◽

Water Budget ◽

Hybrid Approach ◽

Surface Model ◽

Infiltration Capacity ◽

Mountainous Regions ◽

Community Land Model ◽

Spatial Coverage

Abstract This study compares six evapotranspiration ET products for Canada’s landmass, namely, eddy covariance EC measurements; surface water budget ET; remote sensing ET from MODIS; and land surface model (LSM) ET from the Community Land Model (CLM), the Ecological Assimilation of Land and Climate Observations (EALCO) model, and the Variable Infiltration Capacity model (VIC). The ET climatology over the Canadian landmass is characterized and the advantages and limitations of the datasets are discussed. The EC measurements have limited spatial coverage, making it difficult for model validations at the national scale. Water budget ET has the largest uncertainty because of data quality issues with precipitation in mountainous regions and in the north. MODIS ET shows relatively large uncertainty in cold seasons and sparsely vegetated regions. The LSM products cover the entire landmass and exhibit small differences in ET among them. Annual ET from the LSMs ranges from small negative values to over 600 mm across the landmass, with a countrywide average of 256 ± 15 mm. Seasonally, the countrywide average monthly ET varies from a low of about 3 mm in four winter months (November–February) to 67 ± 7 mm in July. The ET uncertainty is scale dependent. Larger regions tend to have smaller uncertainties because of the offset of positive and negative biases within the region. More observation networks and better quality controls are critical to improving ET estimates. Future techniques should also consider a hybrid approach that integrates strengths of the various ET products to help reduce uncertainties in ET estimation.

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Continental Runoff into the Oceans (1950–2008)

Journal of Hydrometeorology ◽

10.1175/jhm-d-14-0183.1 ◽

2015 ◽

Vol 16 (4) ◽

pp. 1502-1520 ◽

Cited By ~ 24

Author(s):

Elizabeth A. Clark ◽

Justin Sheffield ◽

Michelle T. H. van Vliet ◽

Bart Nijssen ◽

Dennis P. Lettenmaier

Keyword(s):

South America ◽

Land Surface ◽

Water Cycle ◽

Land Surface Model ◽

Hydrologic Model ◽

Surface Model ◽

Infiltration Capacity ◽

Continental Scale ◽

Wide Range ◽

Continental Runoff

Abstract A common term in the continental and oceanic components of the global water cycle is freshwater discharge to the oceans. Many estimates of the annual average global discharge have been made over the past 100 yr with a surprisingly wide range. As more observations have become available and continental-scale land surface model simulations of runoff have improved, these past estimates are cast in a somewhat different light. In this paper, a combination of observations from 839 river gauging stations near the outlets of large river basins is used in combination with simulated runoff fields from two implementations of the Variable Infiltration Capacity land surface model to estimate continental runoff into the world’s oceans from 1950 to 2008. The gauges used account for ~58% of continental areas draining to the ocean worldwide, excluding Greenland and Antarctica. This study estimates that flows to the world’s oceans globally are 44 200 (±2660) km3 yr−1 (9% from Africa, 37% from Eurasia, 30% from South America, 16% from North America, and 8% from Australia–Oceania). These estimates are generally higher than previous estimates, with the largest differences in South America and Australia–Oceania. Given that roughly 42% of ocean-draining continental areas are ungauged, it is not surprising that estimates are sensitive to the land surface and hydrologic model (LSM) used, even with a correction applied to adjust for model bias. The results show that more and better in situ streamflow measurements would be most useful in reducing uncertainties, in particular in the southern tip of South America, the islands of Oceania, and central Africa.

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Hydrological functioning of irrigated maize crops in southwest France using Eddy Covariance measurements and a land surface model

10.5194/egusphere-egu21-15262 ◽

2021 ◽

Author(s):

Oluwakemi Dare-Idowu ◽

Lionel Jarlan ◽

Aurore Brut ◽

Valerie Le-Dantec ◽

Vincent Rivalland ◽

...

Keyword(s):

Eddy Covariance ◽

Land Surface ◽

Sap Flow ◽

Heat Fluxes ◽

Added Value ◽

Surface Model ◽

Data Set ◽

Flow Measurements ◽

Ground Heat Flux

This study aims to analyze the main components of the energy and hydric budgets of irrigated maize in southwestern France. To this objective, the ISBA-A-gs (Interactions between Soil, Biosphere, and Atmosphere) is run over six maize growing seasons. As a preliminary step, the ability of the ISBA-A-gs model to predict the different terms of the energy and water budgets is assessed thanks to a large database of in situ measurements by comparing the single budget version of the model with the new Multiple Energy Balance version solving an energy budget separately for the soil and the vegetation. The in situ data set acquired at the Lamasquere site (43.48o N, 1.249o E) includes half-hourly measurements of sensible (H) and latent heat fluxes (LE) estimated by an Eddy Covariance system. Measurements also include net radiation (Rn), ground heat flux (G), plant transpiration with sap flow sensors, meteorological variables, and 15-days measurements of vegetation characteristics. The seasonal dynamics of the turbulent fluxes were properly reproduced by both configurations of the model with an R&#178; ranging from 0.66 to 0.89, and a root mean square error lower than 48 W m-2. Statistical metrics showed that H was better predicted by MEB with R&#178; of 0.80 in comparison to ISBA-Ags (0.73). However, the difference between the RMSE of ISBA-Ags and MEB during the well-developed stage of the plants for both H and LE does not exceed 8 W m-2. This implies that MEB only has a significant added value over ISBA-Ags when the soil and the canopy are not fully coupled, and over a heterogeneous field. Furthermore, this study made a comparison between the sap flow measurements and the transpiration simulated by ISBA-A-gs and MEB. A good dynamics was reproduced by ISBA-A-gs and MEB, although, MEB (R&#178;= 0.91) provided a slightly more realistic estimation of the vegetation transpiration. Consequently, this study investigated the dynamics of the water budget during the growing maize seasons. Results indicated that drainage is almost null on the site, while the observed values of cumulative evapotranspiration that was higher than the water inputs are related to a shallow ground table that provides supplement water to the crop. This work provides insight into the modeling of water and energy exchanges over maize crops and opens perspectives for better water management of the crop in the future.

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Spatio-Temporal Evaluation of Water Storage Trends from Hydrological Models over Australia Using GRACE Mascon Solutions

Remote Sensing ◽

10.3390/rs12213578 ◽

2020 ◽

Vol 12 (21) ◽

pp. 3578

Author(s):

Xinchun Yang ◽

Siyuan Tian ◽

Wei Feng ◽

Jiangjun Ran ◽

Wei You ◽

...

Keyword(s):

Land Surface ◽

Model Development ◽

Water Storage ◽

Validation Dataset ◽

Surface Model ◽

Hydrological Models ◽

Infiltration Capacity ◽

Australian Water ◽

Community Land Model ◽

Spatio Temporal

The Gravity Recovery and Climate Experiment (GRACE) data have been extensively used to evaluate the total terrestrial water storage anomalies (TWSA) from hydrological models. However, which individual water storage components (i.e., soil moisture storage anomalies (SMSA) or groundwater water storage anomalies (GWSA)) cause the discrepancies in TWSA between GRACE and hydrological models have not been thoroughly investigated or quantified. In this study, we applied GRACE mass concentration block (mascon) solutions to evaluate the spatio-temporal TWSA trends (2003–2014) from seven prevailing hydrological models (i.e., Noah-3.6, Catchment Land Surface Model (CLSM-F2.5), Variable Infiltration Capacity macroscale model (VIC-4.1.2), Water—Global Assessment and Prognosis (WaterGAP-2.2d), PCRaster Global Water Balance (PCR-GLOBWB-2), Community Land Model (CLM-4.5), and Australian Water Resources Assessment Landscape model (AWRA-L v6)) in Australia and, more importantly, identified which individual water storage components lead to the differences in TWSA trends between GRACE and hydrological models. The results showed that all of the hydrological models employed in this study, except for CLM-4.5 model, underestimated the GRACE-derived TWSA trends. These underestimations can be divided into three categories: (1) ignoring GWSA, e.g., Noah-3.6 and VIC-4.1.2 models; (2) underrating both SMSA and GWSA, e.g., CLSM-F2.5, WaterGAP-2.2d, and PCR-GLOBWB-2 models; (3) deficiently modeling GWSA, e.g., AWRA-L v6 model. In comparison, CLM-4.5 model yielded the best agreement with GRACE but overstated the GRACE-derived TWSA trends due to the overestimation of GWSA. Our results underscore that GRACE mascon solutions can be used as a valuable and efficient validation dataset to evaluate the spatio-temporal performance of hydrological models. Confirming which individual water storage components result in the discrepancies in TWSA between GRACE and hydrological models can better assist in further hydrological model development.

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Modelling sun-induced fluorescence and photosynthesis with a land surface model at local and regional scales in northern Europe

Biogeosciences ◽

10.5194/bg-14-1969-2017 ◽

2017 ◽

Vol 14 (7) ◽

pp. 1969-1987 ◽

Cited By ~ 23

Author(s):

Tea Thum ◽

Sönke Zaehle ◽

Philipp Köhler ◽

Tuula Aalto ◽

Mika Aurela ◽

...

Keyword(s):

Chlorophyll Fluorescence ◽

Land Surface ◽

Large Scale ◽

Model Simulation ◽

Gross Primary Production ◽

Regional Scale ◽

Coniferous Forest ◽

Flux Measurement ◽

Surface Model ◽

Fluorescence Measurements

Abstract. Recent satellite observations of sun-induced chlorophyll fluorescence (SIF) are thought to provide a large-scale proxy for gross primary production (GPP), thus providing a new way to assess the performance of land surface models (LSMs). In this study, we assessed how well SIF is able to predict GPP in the Fenno-Scandinavian region and what potential limitations for its application exist. We implemented a SIF model into the JSBACH LSM and used active leaf-level chlorophyll fluorescence measurements (Chl F) to evaluate the performance of the SIF module at a coniferous forest at Hyytiälä, Finland. We also compared simulated GPP and SIF at four Finnish micrometeorological flux measurement sites to observed GPP as well as to satellite-observed SIF. Finally, we conducted a regional model simulation for the Fenno-Scandinavian region with JSBACH and compared the results to SIF retrievals from the GOME-2 (Global Ozone Monitoring Experiment-2) space-borne spectrometer and to observation-based regional GPP estimates. Both observations and simulations revealed that SIF can be used to estimate GPP at both site and regional scales. At regional scale the model was able to simulate observed SIF averaged over 5 years with r2 of 0.86. The GOME-2-based SIF was a better proxy for GPP than the remotely sensed fAPAR (fraction of absorbed photosynthetic active radiation by vegetation). The observed SIF captured the seasonality of the photosynthesis at site scale and showed feasibility for use in improving of model seasonality at site and regional scale.

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Comparing Assimilation of Soil Moisture and C-band Backscatter in High Resolution Land Surface Model

10.5194/egusphere-egu2020-10277 ◽

2020 ◽

Author(s):

Leqiang Sun ◽

Stéphane Belair ◽

Marco Carrera ◽

Bernard Bilodeau

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Land Surface Model ◽

Open Loop ◽

In Situ Measurements ◽

Lookup Table ◽

Surface Model ◽

Loop Model ◽

The Impact

Canadian Space Agency (CSA) has recently started receiving and processing the images from the recently launched C-band RADARSAT Constellation Mission (RCM). The backscatter and soil moisture retrievals products from the previously launched RADARSAT-2 agree well with both in-situ measurements and surface soil moisture modeled with land surface model Soil, Vegetation, and Snow (SVS). RCM will provide those products at an even better spatial coverage and temporal resolution. In preparation of the potential operational application of RCM products in Canadian Meteorological Center (CMC), this paper presents the scenarios of assimilating either soil moisture retrieval or outright backscatter signal in a 100-meter resolution version of the Canadian Land Data Assimilation System (CaLDAS) on field scale with time interval of three hours. The soil moisture retrieval map was synthesized by extrapolating the regression relationship between in-situ measurements and open loop model output based on soil texture lookup table. Based on this, the backscatter map was then generated with the surface roughness retrieved from RADARSAT-2 images using a modified Integral Equation Model (IEM) model. Bias correction was applied to the Ensemble Kalman filter (EnKF) to mitigate the impact of nonlinear errors introduced by multi-sourced perturbations. Initial results show that the assimilation of backscatter is as effective as assimilating soil moisture retrievals. Compared to open loop, both can improve the analysis of surface moisture, particularly in terms of reducing bias. &#160;

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Hydrologic Sensitivities of Colorado River Runoff to Changes in Precipitation and Temperature*

Journal of Hydrometeorology ◽

10.1175/jhm-d-11-069.1 ◽

2012 ◽

Vol 13 (3) ◽

pp. 932-949 ◽

Cited By ~ 128

Author(s):

Julie A. Vano ◽

Tapash Das ◽

Dennis P. Lettenmaier

Keyword(s):

Land Surface ◽

Colorado River ◽

Climate Model ◽

Land Surface Model ◽

Annual Runoff ◽

Surface Model ◽

Fractional Change ◽

Infiltration Capacity ◽

Community Land Model ◽

Runoff Change

Abstract The Colorado River is the primary water source for much of the rapidly growing southwestern United States. Recent studies have projected reductions in Colorado River flows from less than 10% to almost 50% by midcentury because of climate change—a range that has clouded potential management responses. These differences in projections are attributable to variations in climate model projections but also to differing land surface model (LSM) sensitivities. This second contribution to uncertainty—specifically, variations in LSM runoff change with respect to precipitation (elasticities) and temperature (sensitivities)—are evaluated here through comparisons of multidecadal simulations from five commonly used LSMs (Catchment, Community Land Model, Noah, Sacramento Soil Moisture Accounting model, and Variable Infiltration Capacity model) all applied over the Colorado River basin at ⅛° latitude by longitude spatial resolution. The annual elasticity of modeled runoff (fractional change in annual runoff divided by fractional change in annual precipitation) at Lees Ferry ranges from two to six for the different LSMs. Elasticities generally are higher in lower precipitation and/or runoff regimes; hence, the highest values are for models biased low in runoff production, and the range of elasticities is reduced to two to three when adjusted to current runoff climatology. Annual temperature sensitivities (percent change in annual runoff per degree change in annual temperature) range from declines of 2% to as much as 9% per degree Celsius increase at Lees Ferry. For some LSMs, small areas, primarily at midelevation, have increasing runoff with increasing temperature; however, on a spatial basis, most sensitivities are negative.

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Past and future scenarios of the effect of carbon dioxide on plant growth and transpiration for three vegetation types of southwestern France

Atmospheric Chemistry and Physics ◽

10.5194/acp-8-397-2008 ◽

2008 ◽

Vol 8 (2) ◽

pp. 397-406 ◽

Cited By ~ 36

Author(s):

J.-C. Calvet ◽

A.-L. Gibelin ◽

J.-L. Roujean ◽

E. Martin ◽

P. Le Moigne ◽

...

Keyword(s):

Land Surface ◽

Coniferous Forest ◽

Land Surface Model ◽

Co2 Concentration ◽

Sensitivity Study ◽

Surface Model ◽

Canopy Conductance ◽

Vegetation Types ◽

Precipitation Regime ◽

Annual Cycles

Abstract. The sensitivity of an operational CO2-responsive land surface model (the ISBA-A-gs model of Météo-France) to the atmospheric CO2 concentration, (CO2), is investigated for 3 vegetation types (winter wheat, irrigated maize, coniferous forest). Past (1960) and future (2050) scenarios of (CO2) corresponding to 320 ppm and 550 ppm, respectively, are explored. The sensitivity study is performed for 4 annual cycles presenting contrasting conditions of precipitation regime and air temperature, based on continuous measurements performed on the SMOSREX site near Toulouse, in southwestern France. A significant CO2-driven reduction of canopy conductance is simulated for the irrigated maize and the coniferous forest. The reduction is particularly large for maize, from 2000 to 2050 (−18%), and triggers a drop in optimum irrigation (−30 mm y−1). In the case of wheat, the response is more complex, with an equal occurrence of enhanced or reduced canopy conductance.

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Correction of real-time satellite precipitation with satellite soil moisture observations

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-12-5749-2015 ◽

2015 ◽

Vol 12 (6) ◽

pp. 5749-5787 ◽

Cited By ~ 1

Author(s):

W. Zhan ◽

M. Pan ◽

N. Wanders ◽

E. F. Wood

Keyword(s):

Soil Moisture ◽

Real Time ◽

Land Surface ◽

Surface Condition ◽

Remote Sensing Data ◽

Surface Model ◽

Normal Surface ◽

Infiltration Capacity ◽

Satellite Precipitation ◽

The Impact

Abstract. Rainfall and soil moisture are two key elements in modeling the interactions between the land surface and the atmosphere. Accurate and high-resolution real-time precipitation is crucial for monitoring and predicting the on-set of floods, and allows for alert and warning before the impact becomes a disaster. Assimilation of remote sensing data into a flood-forecasting model has the potential to improve monitoring accuracy. Space-borne microwave observations are especially interesting because of their sensitivity to surface soil moisture and its change. In this study, we assimilate satellite soil moisture retrievals using the Variable Infiltration Capacity (VIC) land surface model, and a dynamic assimilation technique, a particle filter, to adjust the Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA) real-time precipitation estimates. We compare updated precipitation with real-time precipitation before and after adjustment and with NLDAS gauge-radar observations. Results show that satellite soil moisture retrievals provide additional information by correcting errors in rainfall bias. High accuracy soil moisture retrievals, when merged with precipitation, generally increase both rainfall frequency and intensity, and are most effective in the correction of rainfall under dry to normal surface condition while limited/negative improvement is seen over wet/saturated surfaces. Errors from soil moisture, mixed among the real signal, may generate a false rainfall signal approximately 2 mm day−1 and thus lower the precipitation accuracy after adjustment.

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On the use of the post-closure methods uncertainty band to evaluate the performance of land surface models against eddy covariance flux data

Biogeosciences ◽

10.5194/bg-12-2311-2015 ◽

2015 ◽

Vol 12 (8) ◽

pp. 2311-2326 ◽

Cited By ~ 18

Author(s):

J. Ingwersen ◽

K. Imukova ◽

P. Högy ◽

T. Streck

Keyword(s):

Heat Flux ◽

Energy Balance ◽

Eddy Covariance ◽

Land Surface ◽

Sensible Heat Flux ◽

Land Surface Model ◽

Bowen Ratio ◽

Surface Model ◽

Flux Data ◽

Uncertainty Band

Abstract. The energy balance of eddy covariance (EC) flux data is normally not closed. Therefore, at least if used for modelling, EC flux data are usually post-closed, i.e. the measured turbulent fluxes are adjusted so as to close the energy balance. At the current state of knowledge, however, it is not clear how to partition the missing energy in the right way. Eddy flux data therefore contain some uncertainty due to the unknown nature of the energy balance gap, which should be considered in model evaluation and the interpretation of simulation results. We propose to construct the post-closure methods uncertainty band (PUB), which essentially designates the differences between non-adjusted flux data and flux data adjusted with the three post-closure methods (Bowen ratio, latent heat flux (LE) and sensible heat flux (H) method). To demonstrate this approach, simulations with the NOAH-MP land surface model were evaluated based on EC measurements conducted at a winter wheat stand in southwest Germany in 2011, and the performance of the Jarvis and Ball–Berry stomatal resistance scheme was compared. The width of the PUB of the LE was up to 110 W m−2 (21% of net radiation). Our study shows that it is crucial to account for the uncertainty in EC flux data originating from lacking energy balance closure. Working with only a single post-closing method might result in severe misinterpretations in model–data comparisons.

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