Review of Coupling a three-dimensional subsurface flow and transport model with a land surface model to simulate stream-aquifer land interactions (PFLOTRAN_CLM v1.0)

2017 ◽  
Author(s):  
Anonymous
2022 ◽  
Vol 15 (1) ◽  
pp. 75-104
Author(s):  
Niccolò Tubini ◽  
Riccardo Rigon

Abstract. This paper presents WHETGEO and its 1D deployment: a new physically based model simulating the water and energy budgets in a soil column. The purpose of this contribution is twofold. First, we discuss the mathematical and numerical issues involved in solving the Richardson–Richards equation, conventionally known as the Richards equation, and the heat equation in heterogeneous soils. In particular, for the Richardson–Richards equation (R2) we take advantage of the nested Newton–Casulli–Zanolli (NCZ) algorithm that ensures the convergence of the numerical solution in any condition. Second, starting from numerical and modelling needs, we present the design of software that is intended to be the first building block of a new customizable land-surface model that is integrated with process-based hydrology. WHETGEO is developed as an open-source code, adopting the object-oriented paradigm and a generic programming approach in order to improve its usability and expandability. WHETGEO is fully integrated into the GEOframe/OMS3 system, allowing the use of the many ancillary tools it provides. Finally, the paper presents the 1D deployment of WHETGEO, WHETGEO-1D, which has been tested against the available analytical solutions presented in the Appendix.


2017 ◽  
Author(s):  
Thibaud Thonat ◽  
Marielle Saunois ◽  
Philippe Bousquet ◽  
Isabelle Pison ◽  
Zeli Tan ◽  
...  

Abstract. Understanding the recent evolution of methane emissions in the Arctic is necessary to interpret the global methane cycle. Emissions are affected by significant uncertainties and are sensitive to climate change, leading to potential feedbacks. A polar version of the CHIMERE chemistry-transport model is used to simulate the evolution of tropospheric methane in the Arctic during 2012, including all known regional anthropogenic and natural sources. CHIMERE simulations are compared to atmospheric continuous observations at six measurement sites in the Arctic region. In winter, the Arctic is dominated by anthropogenic emissions; emissions from continental seepages and oceans, including from the East Siberian Arctic Shelf, can contribute significantly in more limited areas. In summer, emissions from wetland and freshwater sources dominate across the whole region. The model is able to reproduce the seasonality and synoptic variations of methane measured at the different sites. We find that all methane sources significantly affect the measurements at all stations at least at the synoptic scale, except for biomass burning; this indicates the relevance of continuous observations to gain a mechanistic understanding of Arctic methane sources. Sensitivity tests reveal that the choice of the land surface model used to prescribe wetland emissions can be critical in correctly representing methane concentrations. Also testing different freshwater emission inventories leads to large differences in modelled methane. Attempts to include methane sinks (OH oxidation and soil uptake) reduced the model bias relative to observed atmospheric CH4. The study illustrates how multiple sources, having different spatiotemporal dynamics and magnitudes, jointly influence the overall Arctic methane budget, and highlights ways towards further improved assessments.


2017 ◽  
Vol 17 (13) ◽  
pp. 8371-8394 ◽  
Author(s):  
Thibaud Thonat ◽  
Marielle Saunois ◽  
Philippe Bousquet ◽  
Isabelle Pison ◽  
Zeli Tan ◽  
...  

Abstract. Understanding the recent evolution of methane emissions in the Arctic is necessary to interpret the global methane cycle. Emissions are affected by significant uncertainties and are sensitive to climate change, leading to potential feedbacks. A polar version of the CHIMERE chemistry-transport model is used to simulate the evolution of tropospheric methane in the Arctic during 2012, including all known regional anthropogenic and natural sources, in particular freshwater emissions which are often overlooked in methane modelling. CHIMERE simulations are compared to atmospheric continuous observations at six measurement sites in the Arctic region. In winter, the Arctic is dominated by anthropogenic emissions; emissions from continental seepages and oceans, including from the East Siberian Arctic Shelf, can contribute significantly in more limited areas. In summer, emissions from wetland and freshwater sources dominate across the whole region. The model is able to reproduce the seasonality and synoptic variations of methane measured at the different sites. We find that all methane sources significantly affect the measurements at all stations at least at the synoptic scale, except for biomass burning. In particular, freshwater systems play a decisive part in summer, representing on average between 11 and 26 % of the simulated Arctic methane signal at the sites. This indicates the relevance of continuous observations to gain a mechanistic understanding of Arctic methane sources. Sensitivity tests reveal that the choice of the land-surface model used to prescribe wetland emissions can be critical in correctly representing methane mixing ratios. The closest agreement with the observations is reached when using the two wetland models which have emissions peaking in August–September, while all others reach their maximum in June–July. Such phasing provides an interesting constraint on wetland models which still have large uncertainties at present. Also testing different freshwater emission inventories leads to large differences in modelled methane. Attempts to include methane sinks (OH oxidation and soil uptake) reduced the model bias relative to observed atmospheric methane. The study illustrates how multiple sources, having different spatiotemporal dynamics and magnitudes, jointly influence the overall Arctic methane budget, and highlights ways towards further improved assessments.


2021 ◽  
Author(s):  
Marine Remaud ◽  
Camille Abadie ◽  
Sauveur Belviso ◽  
Antoine Berchet ◽  
Frédéric Chevallier ◽  
...  

<p>Carbonyle Sulphide, a trace gas exhibiting a striking similarity with CO2 in the biochemical diffusion path of leaves, has been recognized to be a promising surrogate of CO2 for estimating carbon storage in the terrestrial vegetation. Based on the similarity between COS and CO2, an empirical linear model relating both gas concentrations provides constraints on the estimation of the Gross Primary Productivity (GPP), the amount of carbon dioxide that is absorbed by ecosystems. However, large uncertainties on the other components of its atmospheric budget prevent us from directly relating the atmospheric COS measurements to the the GPP at global scale. The largest uncertainty arises from the closure of its atmospheric budget, with a source component missing. We explore here the benefit of assimilating both COS and CO2 measurements into the LMDz atmospheric transport model to gain insight on the COS budget. We develop an analytic inverse system which optimized the biospheric fluxes within the 14 Plant functional Type (PFTs) as defined in the ORCHIDEE land surface model. The vegetation uptake of COS is parameterized as a linear function of GPP and of the leaf relative uptake (LRU), which is the ratio of COS to CO2 deposition velocities in plants. A possible scenario leads to a global biospheric sink between 800-900 GgS/y, with a higher GPP in the high latitudes and higher total oceanic emissions between 400 and 600 GgS/y over the tropics. The COS inter-hemispheric gradient is in better agreement with HIPPO independent aircraft measurements. The comparison against NOAA COS airborne profiles and Solar Induced Fluorescence shed light on a too strong GPP in spring in ORCHIDEE in northern America,  leaving room for improvements. <span>We also show that uncertainty in the location of hot spots in the prior anthropogenic inventory limits the use of atmospheric COS measurements in inverse modeling.</span></p>


2017 ◽  
Vol 10 (12) ◽  
pp. 4539-4562 ◽  
Author(s):  
Gautam Bisht ◽  
Maoyi Huang ◽  
Tian Zhou ◽  
Xingyuan Chen ◽  
Heng Dai ◽  
...  

Abstract. A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively parallel multiphysics reactive transport model (PFLOTRAN). The coupled model, named CP v1.0, is applied to a 400 m × 400 m study domain instrumented with groundwater monitoring wells along the Columbia River shoreline. CP v1.0 simulations are performed at three spatial resolutions (i.e., 2, 10, and 20 m) over a 5-year period to evaluate the impact of hydroclimatic conditions and spatial resolution on simulated variables. Results show that the coupled model is capable of simulating groundwater–river-water interactions driven by river stage variability along managed river reaches, which are of global significance as a result of over 30 000 dams constructed worldwide during the past half-century. Our numerical experiments suggest that the land-surface energy partitioning is strongly modulated by groundwater–river-water interactions through expanding the periodically inundated fraction of the riparian zone, and enhancing moisture availability in the vadose zone via capillary rise in response to the river stage change. Meanwhile, CLM4.5 fails to capture the key hydrologic process (i.e., groundwater–river-water exchange) at the site, and consequently simulates drastically different water and energy budgets. Furthermore, spatial resolution is found to significantly impact the accuracy of estimated the mass exchange rates at the boundaries of the aquifer, and it becomes critical when surface and subsurface become more tightly coupled with groundwater table within 6 to 7 meters below the surface. Inclusion of lateral subsurface flow influenced both the surface energy budget and subsurface transport processes as a result of river-water intrusion into the subsurface in response to an elevated river stage that increased soil moisture for evapotranspiration and suppressed available energy for sensible heat in the warm season. The coupled model developed in this study can be used for improving mechanistic understanding of ecosystem functioning and biogeochemical cycling along river corridors under historical and future hydroclimatic changes. The dataset presented in this study can also serve as a good benchmarking case for testing other integrated models.


2021 ◽  
Author(s):  
Niccolò Tubini ◽  
Riccardo Rigon

Abstract. This paper presents WHETGEO and its 1D deployment, a new, physically based model simulating the water and energy budgets in a soil column. The purpose of this contribution is twofold. First, we discuss the mathematical and numerical issues involved in solving the Richardson-Richards equation, conventionally known as Richards' equation, and the heat equation in heterogeneous soils. In particular, for the Richardson-Richards equation (R2) we take advantage of the nested Newton-Casulli-Zanolli (NCZ) algorithm that ensures the convergence of the numerical solution in any condition. Second, starting from numerical and modelling needs, we present the design of a software that is intended to be the first building block of a new, customisable, land-surface model that is integrated with process-based hydrology. WHETGEO is developed as an open-source code, adopting the Object-Oriented paradigm and a generic programming approach in order to improve its usability and expandability. WHETGEO is fully integrated in the GEOframe/OMS3 system allowing the use of the many ancillary tools it provides. Finally the paper presents the 1D deployment of WHETGEO, WHETGEO-1D, which has been tested against the available analytical solutions presented in Appendix.


2017 ◽  
Author(s):  
Gautam Bisht ◽  
Maoyi Huang ◽  
Tian Zhou ◽  
Xingyuan Chen ◽  
Heng Dai ◽  
...  

Abstract. A fully coupled three-dimensional surface and subsurface land model is developed and applied to a site along the Columbia River to simulate three-way interactions among river water, groundwater, and land surface processes. The model features the coupling of the Community Land Model version 4.5 (CLM4.5) and a massively-parallel multi-physics reactive transport model (PFLOTRAN). The coupled model, named PFLOTRAN_CLM v1.0, is applied to a 400 m × 400 m study domain instrumented with groundwater monitoring wells along the Columbia River shoreline. PFLOTRAN_CLM v1.0 simulations are performed at three spatial resolutions over a five-year period to evaluate the impact of hydro-climatic conditions and spatial resolution on simulated variables. Results show that the coupled model is capable of simulating groundwater-river water interactions driven by river stage variability along managed river reaches, which are of global significance as a result of over 30,000 dams constructed worldwide during the past half century. Our numerical experiments suggest that the land-surface energy partitioning is strongly modulated by groundwater-river water interactions through expanding the periodically inundated fraction of the riparian zone, and enhancing moisture availability in the vadose zone via capillary rise in response to the river stage change. Furthermore, spatial resolution is found to impact significantly the accuracy of estimated the mass exchange rates at the boundaries of the aquifer, and it becomes critical when surface and subsurface become more tightly coupled with groundwater table within six to seven meters below the surface. Inclusion of lateral subsurface flow impacted both the surface energy budget and subsurface transport processes. The coupled model developed in this study can be used for improving mechanistic understanding of ecosystem functioning, biogeochemical cycling, and land-atmosphere interactions along river corridors under historical and future hydro-climatic changes. The dataset presented in this study can also serve as a good benchmarking case for testing other integrated models.


2009 ◽  
Vol 9 (1) ◽  
pp. 2319-2380 ◽  
Author(s):  
A. de Meij ◽  
A. Gzella ◽  
P. Thunis ◽  
C. Cuvelier ◽  
B. Bessagnet ◽  
...  

Abstract. The objective of this study is to evaluate the impact of meteorological input data on calculated gas and aerosol concentrations. We use two different meteorological models (MM5 and WRF) together with the chemistry transport model CHIMERE. We focus on the Po valley area (Italy) for January and June 2005. Firstly we evaluate the meteorological parameters with observations. The analysis shows that the performance of both models is similar, however some small differences are still noticeable. Secondly, we analyze the impact of using MM5 and WRF on calculated PM10 and O3 concentrations. In general CHIMERE/MM5 and CHIMERE/WRF underestimate the PM10 concentrations for January. The difference in PM10 concentrations for January between CHIMERE/MM5 and CHIMERE/WRF is around a factor 1.6 (PM10 higher for CHIMERE/MM5). This difference and the larger underestimation in PM10 concentrations by CHIMERE/WRF are related to the differences in heat fluxes and the resulting PBL heights calculated by WRF. In general the PBL height by WRF meteorology is a factor 2.8 higher at noon in January than calculated by MM5. This study showed that the difference in microphysics scheme has an impact on the profile of cloud liquid water (CLW) calculated by the meteorological driver and therefore on the production of SO4 aerosol. A sensitivity analysis shows that changing the Noah Land Surface Model (LSM) for the 5-layer soil temperature model, the calculated monthly mean PM10 concentrations increase by 30%, due to the change in the heat fluxes and the resulting PBL heights. For June, PM10 calculated concentrations by CHIMERE/MM5 and CHIMERE/WRF are similar and agree with the observations. Calculated O3 values for June are in general overestimated by a factor 1.3 by CHIMERE/MM5 and CHIMRE/WRF. The reason for this is that daytime NO2 concentrations are a higher than the observations and nighttime NO concentrations (titration effect) are underestimated.


2009 ◽  
Vol 9 (17) ◽  
pp. 6611-6632 ◽  
Author(s):  
A. de Meij ◽  
A. Gzella ◽  
C. Cuvelier ◽  
P. Thunis ◽  
B. Bessagnet ◽  
...  

Abstract. The objective of this study is to evaluate the impact of meteorological input data on calculated gas and aerosol concentrations. We use two different meteorological models (MM5 and WRF) together with the chemistry transport model CHIMERE. We focus on the Po valley area (Italy) for January and June 2005. Firstly we evaluate the meteorological parameters with observations. The analysis shows that the performance of both models in calculating surface parameters is similar, however differences are still observed. Secondly, we analyze the impact of using MM5 and WRF on calculated PM10 and O3 concentrations. In general CHIMERE/MM5 and CHIMERE/WRF underestimate the PMv concentrations for January. The difference in PM10 concentrations for January between CHIMERE/MM5 and CHIMERE/WRF is around a factor 1.6 (PM10 higher for CHIMERE/MM5). This difference and the larger underestimation in PM10 concentrations by CHIMERE/WRF are related to the differences in heat fluxes and the resulting PBL heights calculated by WRF. In general the PBL height by WRF meteorology is a factor 2.8 higher at noon in January than calculated by MM5. This study showed that the difference in microphysics scheme has an impact on the profile of cloud liquid water (CLW) calculated by the meteorological driver and therefore on the production of SO4 aerosol. A sensitivity analysis shows that changing the Noah Land Surface Model (LSM) in our WRF pre-processing for the 5-layer soil temperature model, calculated monthly mean PMv concentrations increase by 30%, due to the change in the heat fluxes and the resulting PBL heights. For June, PM10 calculated concentrations by CHIMERE/MM5 and CHIMERE/WRF are similar and agree with the observations. Calculated O3 values for June are in general overestimated by a factor 1.3 by CHIMERE/MM5 and CHIMERE/WRF. High temporal correlations are found between modeled and observed O3 concentrations.


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