Microwave remote sensing of soil water content

NASA Technical Reports Server (NTRS)

Cihlar, J.; Ulaby, F. T.

1975-01-01

Microwave remote sensing of soils to determine water content was considered. A layered water balance model was developed for determining soil water content in the upper zone (top 30 cm), while soil moisture at greater depths and near the surface during the diurnal cycle was studied using experimental measurements. Soil temperature was investigated by means of a simulation model. Based on both models, moisture and temperature profiles of a hypothetical soil were generated and used to compute microwave soil parameters for a clear summer day. The results suggest that, (1) soil moisture in the upper zone can be predicted on a daily basis for 1 cm depth increments, (2) soil temperature presents no problem if surface temperature can be measured with infrared radiometers, and (3) the microwave response of a bare soil is determined primarily by the moisture at and near the surface. An algorithm is proposed for monitoring large areas which combines the water balance and microwave methods.

Effect of Climate Change on Soil Temperature in Swedish Boreal Forests

PubMed Central

Jungqvist, Gunnar; Oni, Stephen K.; Teutschbein, Claudia; Futter, Martyn N.

2014-01-01

Complex non-linear relationships exist between air and soil temperature responses to climate change. Despite its influence on hydrological and biogeochemical processes, soil temperature has received less attention in climate impact studies. Here we present and apply an empirical soil temperature model to four forest sites along a climatic gradient of Sweden. Future air and soil temperature were projected using an ensemble of regional climate models. Annual average air and soil temperatures were projected to increase, but complex dynamics were projected on a seasonal scale. Future changes in winter soil temperature were strongly dependent on projected snow cover. At the northernmost site, winter soil temperatures changed very little due to insulating effects of snow cover but southern sites with little or no snow cover showed the largest projected winter soil warming. Projected soil warming was greatest in the spring (up to 4°C) in the north, suggesting earlier snowmelt, extension of growing season length and possible northward shifts in the boreal biome. This showed that the projected effects of climate change on soil temperature in snow dominated regions are complex and general assumptions of future soil temperature responses to climate change based on air temperature alone are inadequate and should be avoided in boreal regions. PMID:24747938

Effect of climate change on soil temperature in Swedish boreal forests.

PubMed

Jungqvist, Gunnar; Oni, Stephen K; Teutschbein, Claudia; Futter, Martyn N

2014-01-01

Complex non-linear relationships exist between air and soil temperature responses to climate change. Despite its influence on hydrological and biogeochemical processes, soil temperature has received less attention in climate impact studies. Here we present and apply an empirical soil temperature model to four forest sites along a climatic gradient of Sweden. Future air and soil temperature were projected using an ensemble of regional climate models. Annual average air and soil temperatures were projected to increase, but complex dynamics were projected on a seasonal scale. Future changes in winter soil temperature were strongly dependent on projected snow cover. At the northernmost site, winter soil temperatures changed very little due to insulating effects of snow cover but southern sites with little or no snow cover showed the largest projected winter soil warming. Projected soil warming was greatest in the spring (up to 4°C) in the north, suggesting earlier snowmelt, extension of growing season length and possible northward shifts in the boreal biome. This showed that the projected effects of climate change on soil temperature in snow dominated regions are complex and general assumptions of future soil temperature responses to climate change based on air temperature alone are inadequate and should be avoided in boreal regions.

Simulation of herbicide degradation in different soils by use of Pedo-transfer functions (PTF) and non-linear kinetics.

PubMed

von Götz, N; Richter, O

1999-03-01

The degradation behaviour of bentazone in 14 different soils was examined at constant temperature and moisture conditions. Two soils were examined at different temperatures. On the basis of these data the influence of soil properties and temperature on degradation was assessed and modelled. Pedo-transfer functions (PTF) in combination with a linear and a non-linear model were found suitable to describe the bentazone degradation in the laboratory as related to soil properties. The linear PTF can be combined with a rate related to the temperature to account for both soil property and temperature influence at the same time.

Changes in photosynthesis and soil moisture drive the seasonal soil respiration-temperature hysteresis relationship

USDA-ARS?s Scientific Manuscript database

In nearly all large-scale models, CO2 efflux from soil (i.e., soil respiration) is represented as a function of soil temperature. However, the relationship between soil respiration and soil temperature is highly variable at the local scale, and there is often a pronounced hysteresis in the soil resp...

Western US high June 2015 temperatures and their relation to global warming and soil moisture

NASA Astrophysics Data System (ADS)

Philip, Sjoukje Y.; Kew, Sarah F.; Hauser, Mathias; Guillod, Benoit P.; Teuling, Adriaan J.; Whan, Kirien; Uhe, Peter; Oldenborgh, Geert Jan van

2018-04-01

The Western US states Washington (WA), Oregon (OR) and California (CA) experienced extremely high temperatures in June 2015. The temperature anomalies were so extreme that they cannot be explained with global warming alone. We investigate the hypothesis that soil moisture played an important role as well. We use a land surface model and a large ensemble from the weather@home modelling effort to investigate the coupling between soil moisture and temperature in a warming world. Both models show that May was anomalously dry, satisfying a prerequisite for the extreme heat wave, and they indicate that WA and OR are in a wet-to-dry transitional soil moisture regime. We use two different land surface-atmosphere coupling metrics to show that there was strong coupling between temperature, latent heat flux and the effect of soil moisture deficits on the energy balance in June 2015 in WA and OR. June temperature anomalies conditioned on wet/dry conditions show that both the mean and extreme temperatures become hotter for dry soils, especially in WA and OR. Fitting a Gaussian model to temperatures using soil moisture as a covariate shows that the June 2015 temperature values fit well in the extrapolated empirical temperature/drought lines. The high temperature anomalies in WA and OR are thus to be expected, given the dry soil moisture conditions and that those regions are in the transition from a wet to a dry regime. CA is already in the dry regime and therefore the necessity of taking soil moisture into account is of lower importance.

Modeling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices

NASA Astrophysics Data System (ADS)

Reichstein, Markus; Rey, Ana; Freibauer, Annette; Tenhunen, John; Valentini, Riccardo; Banza, Joao; Casals, Pere; Cheng, Yufu; Grünzweig, Jose M.; Irvine, James; Joffre, Richard; Law, Beverly E.; Loustau, Denis; Miglietta, Franco; Oechel, Walter; Ourcival, Jean-Marc; Pereira, Joao S.; Peressotti, Alessandro; Ponti, Francesca; Qi, Ye; Rambal, Serge; Rayment, Mark; Romanya, Joan; Rossi, Federica; Tedeschi, Vanessa; Tirone, Giampiero; Xu, Ming; Yakir, Dan

2003-12-01

Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, interannual and spatial variability of soil respiration as affected by water availability, temperature, and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e.g., leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical nonlinear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content, and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and intersite variability of soil respiration with a mean absolute error of 0.82 μmol m-2 s-1. The parameterized model exhibits the following principal properties: (1) At a relative amount of upper-layer soil water of 16% of field capacity, half-maximal soil respiration rates are reached. (2) The apparent temperature sensitivity of soil respiration measured as Q10 varies between 1 and 5 depending on soil temperature and water content. (3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly timescale, we employed the approach by [2002] that used monthly precipitation and air temperature to globally predict soil respiration (T&P model). While this model was able to explain some of the month-to-month variability of soil respiration, it failed to capture the intersite variability, regardless of whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf area index. Thus, for a monthly timescale, we developed a simple T&P&LAI model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time step model and explained 50% of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index. Before application at the continental or global scale, this approach should be further tested in boreal, cold-temperate, and tropical biomes as well as for non-woody vegetation.

Insights from intercomparison of microbial and conventional soil models

NASA Astrophysics Data System (ADS)

Allison, S. D.; Li, J.; Luo, Y.; Mayes, M. A.; Wang, G.

2014-12-01

Changing the structure of soil biogeochemical models to represent coupling between microbial biomass and carbon substrate pools could improve predictions of carbon-climate feedbacks. So-called "microbial models" with this structure make very different predictions from conventional models based on first-order decay of carbon substrate pools. Still, the value of microbial models is uncertain because microbial physiological parameters are poorly constrained and model behaviors have not been fully explored. To address these issues, we developed an approach for inter-comparing microbial and conventional models. We initially focused on soil carbon responses to microbial carbon use efficiency (CUE) and temperature. Three scenarios were implemented in all models at a common reference temperature (20°C): constant CUE (held at 0.31), varied CUE (-0.016°C-1), and 50% acclimated CUE (-0.008°C-1). Whereas the conventional model always showed soil carbon losses with increasing temperature, the microbial models each predicted a temperature threshold above which warming led to soil carbon gain. The location of this threshold depended on CUE scenario, with higher temperature thresholds under the acclimated and constant scenarios. This result suggests that the temperature sensitivity of CUE and the structure of the soil carbon model together regulate the long-term soil carbon response to warming. Compared to the conventional model, all microbial models showed oscillatory behavior in response to perturbations and were much less sensitive to changing inputs. Oscillations were weakest in the most complex model with explicit enzyme pools, suggesting that multi-pool coupling might be a more realistic representation of the soil system. This study suggests that model structure and CUE parameterization should be carefully evaluated when scaling up microbial models to ecosystems and the globe.

Soil thermal dynamics, snow cover, and frozen depth under five temperature treatments in an ombrotrophic bog: Constrained forecast with data assimilation: Forecast With Data Assimilation

DOE PAGES

Huang, Yuanyuan; Jiang, Jiang; Ma, Shuang; ...

2017-08-18

We report that accurate simulation of soil thermal dynamics is essential for realistic prediction of soil biogeochemical responses to climate change. To facilitate ecological forecasting at the Spruce and Peatland Responses Under Climatic and Environmental change site, we incorporated a soil temperature module into a Terrestrial ECOsystem (TECO) model by accounting for surface energy budget, snow dynamics, and heat transfer among soil layers and during freeze-thaw events. We conditioned TECO with detailed soil temperature and snow depth observations through data assimilation before the model was used for forecasting. The constrained model reproduced variations in observed temperature from different soil layers,more » the magnitude of snow depth, the timing of snowfall and snowmelt, and the range of frozen depth. The conditioned TECO forecasted probabilistic distributions of soil temperature dynamics in six soil layers, snow, and frozen depths under temperature treatments of +0.0, +2.25, +4.5, +6.75, and +9.0°C. Air warming caused stronger elevation in soil temperature during summer than winter due to winter snow and ice. And soil temperature increased more in shallow soil layers in summer in response to air warming. Whole ecosystem warming (peat + air warmings) generally reduced snow and frozen depths. The accuracy of forecasted snow and frozen depths relied on the precision of weather forcing. Uncertainty is smaller for forecasting soil temperature but large for snow and frozen depths. Lastly, timely and effective soil thermal forecast, constrained through data assimilation that combines process-based understanding and detailed observations, provides boundary conditions for better predictions of future biogeochemical cycles.« less

Soil thermal dynamics, snow cover, and frozen depth under five temperature treatments in an ombrotrophic bog: Constrained forecast with data assimilation: Forecast With Data Assimilation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Yuanyuan; Jiang, Jiang; Ma, Shuang

We report that accurate simulation of soil thermal dynamics is essential for realistic prediction of soil biogeochemical responses to climate change. To facilitate ecological forecasting at the Spruce and Peatland Responses Under Climatic and Environmental change site, we incorporated a soil temperature module into a Terrestrial ECOsystem (TECO) model by accounting for surface energy budget, snow dynamics, and heat transfer among soil layers and during freeze-thaw events. We conditioned TECO with detailed soil temperature and snow depth observations through data assimilation before the model was used for forecasting. The constrained model reproduced variations in observed temperature from different soil layers,more » the magnitude of snow depth, the timing of snowfall and snowmelt, and the range of frozen depth. The conditioned TECO forecasted probabilistic distributions of soil temperature dynamics in six soil layers, snow, and frozen depths under temperature treatments of +0.0, +2.25, +4.5, +6.75, and +9.0°C. Air warming caused stronger elevation in soil temperature during summer than winter due to winter snow and ice. And soil temperature increased more in shallow soil layers in summer in response to air warming. Whole ecosystem warming (peat + air warmings) generally reduced snow and frozen depths. The accuracy of forecasted snow and frozen depths relied on the precision of weather forcing. Uncertainty is smaller for forecasting soil temperature but large for snow and frozen depths. Lastly, timely and effective soil thermal forecast, constrained through data assimilation that combines process-based understanding and detailed observations, provides boundary conditions for better predictions of future biogeochemical cycles.« less

The sensitivity of soil respiration to soil temperature, moisture, and carbon supply at the global scale.

PubMed

Hursh, Andrew; Ballantyne, Ashley; Cooper, Leila; Maneta, Marco; Kimball, John; Watts, Jennifer

2017-05-01

Soil respiration (Rs) is a major pathway by which fixed carbon in the biosphere is returned to the atmosphere, yet there are limits to our ability to predict respiration rates using environmental drivers at the global scale. While temperature, moisture, carbon supply, and other site characteristics are known to regulate soil respiration rates at plot scales within certain biomes, quantitative frameworks for evaluating the relative importance of these factors across different biomes and at the global scale require tests of the relationships between field estimates and global climatic data. This study evaluates the factors driving Rs at the global scale by linking global datasets of soil moisture, soil temperature, primary productivity, and soil carbon estimates with observations of annual Rs from the Global Soil Respiration Database (SRDB). We find that calibrating models with parabolic soil moisture functions can improve predictive power over similar models with asymptotic functions of mean annual precipitation. Soil temperature is comparable with previously reported air temperature observations used in predicting Rs and is the dominant driver of Rs in global models; however, within certain biomes soil moisture and soil carbon emerge as dominant predictors of Rs. We identify regions where typical temperature-driven responses are further mediated by soil moisture, precipitation, and carbon supply and regions in which environmental controls on high Rs values are difficult to ascertain due to limited field data. Because soil moisture integrates temperature and precipitation dynamics, it can more directly constrain the heterotrophic component of Rs, but global-scale models tend to smooth its spatial heterogeneity by aggregating factors that increase moisture variability within and across biomes. We compare statistical and mechanistic models that provide independent estimates of global Rs ranging from 83 to 108 Pg yr -1 , but also highlight regions of uncertainty where more observations are required or environmental controls are hard to constrain. © 2016 John Wiley & Sons Ltd.

Modification of Soil Temperature and Moisture Budgets by Snow Processes

NASA Astrophysics Data System (ADS)

Feng, X.; Houser, P.

2006-12-01

Snow cover significantly influences the land surface energy and surface moisture budgets. Snow thermally insulates the soil column from large and rapid temperature fluctuations, and snow melting provides an important source for surface runoff and soil moisture. Therefore, it is important to accurately understand and predict the energy and moisture exchange between surface and subsurface associated with snow accumulation and ablation. The objective of this study is to understand the impact of land surface model soil layering treatment on the realistic simulation of soil temperature and soil moisture. We seek to understand how many soil layers are required to fully take into account soil thermodynamic properties and hydrological process while also honoring efficient calculation and inexpensive computation? This work attempts to address this question using field measurements from the Cold Land Processes Field Experiment (CLPX). In addition, to gain a better understanding of surface heat and surface moisture transfer process between land surface and deep soil involved in snow processes, numerical simulations were performed at several Meso-Cell Study Areas (MSAs) of CLPX using the Center for Ocean-Land-Atmosphere (COLA) Simplified Version of the Simple Biosphere Model (SSiB). Measurements of soil temperature and soil moisture were analyzed at several CLPX sites with different vegetation and soil features. The monthly mean vertical profile of soil temperature during October 2002 to July 2003 at North Park Illinois River exhibits a large near surface variation (<5 cm), reveals a significant transition zone from 5 cm to 25 cm, and becomes uniform beyond 25cm. This result shows us that three soil layers are reasonable in solving the vertical variation of soil temperature at these study sites. With 6 soil layers, SSiB also captures the vertical variation of soil temperature during entire winter season, featuring with six soil layers, but the bare soil temperature is underestimated and root-zone soil temperature is overestimated during snow melting; which leads to overestimated temperature variations down to 20 cm. This is caused by extra heat loss from upper soil level and insufficient heat transport from the deep soil. Further work will need to verify if soil temperature displays similar vertical thermal structure for different vegetation and soil types during snow season. This study provides insight to the surface and subsurface thermodynamic and hydrological processes involved in snow modeling which is important for accurate snow simulation.

Critical shear stress for erosion of cohesive soils subjected to temperatures typical of wildfires

USGS Publications Warehouse

Moody, J.A.; Dungan, Smith J.; Ragan, B.W.

2005-01-01

[1] Increased erosion is a well-known response after wildfire. To predict and to model erosion on a landscape scale requires knowledge of the critical shear stress for the initiation of motion of soil particles. As this soil property is temperature-dependent, a quantitative relation between critical shear stress and the temperatures to which the soils have been subjected during a wildfire is required. In this study the critical shear stress was measured in a recirculating flume using samples of forest soil exposed to different temperatures (40??-550??C) for 1 hour. Results were obtained for four replicates of soils derived from three different types of parent material (granitic bedrock, sandstone, and volcanic tuffs). In general, the relation between critical shear stress and temperature can be separated into three different temperature ranges (275??C), which are similar to those for water repellency and temperature. The critical shear stress was most variable (1.0-2.0 N m-2) for temperatures 2.0 N m-2) between 175?? and 275??C, and was essentially constant (0.5-0.8 N m-2) for temperatures >275??C. The changes in critical shear stress with temperature were found to be essentially independent of soil type and suggest that erosion processes in burned watersheds can be modeled more simply than erosion processes in unburned watersheds. Wildfire reduces the spatial variability of soil erodibility associated with unburned watersheds by eliminating the complex effects of vegetation in protecting soils and by reducing the range of cohesion associated with different types of unburned soils. Our results indicate that modeling the erosional response after a wildfire depends primarily on determining the spatial distribution of the maximum soil temperatures that were reached during the wildfire. Copyright 2005 by the American Geophysical Union.

Impacts of Soil-aquifer Heat and Water Fluxes on Simulated Global Climate

NASA Technical Reports Server (NTRS)

Krakauer, N.Y.; Puma, Michael J.; Cook, B. I.

2013-01-01

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 50m 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 >1K in the Arctic. The soil-aquifer water and heat fluxes both slightly decrease interannual variability in soil moisture and in landsurface temperature, and decrease the soil moisture memory of the land surface on seasonal to 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.

Diurnal hysteresis between soil CO2 and soil temperature is controlled by soil water content

Treesearch

Diego A. Riveros-Iregui; Ryan E. Emanuel; Daniel J. Muth; L. McGlynn Brian; Howard E. Epstein; Daniel L. Welsch; Vincent J. Pacific; Jon M. Wraith

2007-01-01

Recent years have seen a growing interest in measuring and modeling soil CO2 efflux, as this flux represents a large component of ecosystem respiration and is a key determinant of ecosystem carbon balance. Process-based models of soil CO2 production and efflux, commonly based on soil temperature, are limited by nonlinearities such as the observed diurnal hysteresis...

Unusually high soil nitrogen oxide emissions influence air quality in a high-temperature agricultural region

PubMed Central

Oikawa, P. Y.; Ge, C.; Wang, J.; Eberwein, J. R.; Liang, L. L.; Allsman, L. A.; Grantz, D. A.; Jenerette, G. D.

2015-01-01

Fertilized soils have large potential for production of soil nitrogen oxide (NOx=NO+NO2), however these emissions are difficult to predict in high-temperature environments. Understanding these emissions may improve air quality modelling as NOx contributes to formation of tropospheric ozone (O3), a powerful air pollutant. Here we identify the environmental and management factors that regulate soil NOx emissions in a high-temperature agricultural region of California. We also investigate whether soil NOx emissions are capable of influencing regional air quality. We report some of the highest soil NOx emissions ever observed. Emissions vary nonlinearly with fertilization, temperature and soil moisture. We find that a regional air chemistry model often underestimates soil NOx emissions and NOx at the surface and in the troposphere. Adjusting the model to match NOx observations leads to elevated tropospheric O3. Our results suggest management can greatly reduce soil NOx emissions, thereby improving air quality. PMID:26556236

Modelling the effect of low soil temperatures on transpiration by Scots pine

NASA Astrophysics Data System (ADS)

Mellander, Per-Erik; Stähli, Manfred; Gustafsson, David; Bishop, Kevin

2006-06-01

For ecosystem modelling of the Boreal forest it is important to include processes associated with low soil temperature during spring-early summer, as these affect the tree water uptake. The COUP model, a physically based SVAT model, was tested with 2 years of soil and snow physical measurements and sap flow measurements in a 70-year-old Scots pine stand in the boreal zone of northern Sweden. During the first year the extent and duration of soil frost was manipulated in the field. The model was successful in reproducing the timing of the soil warming after the snowmelt and frost thaw. A delayed soil warming, into the growing season, severely reduced the transpiration. We demonstrated the potential for considerable overestimation of transpiration by the model if the reduction of the trees' capacity to transpire due to low soil temperatures is not taken into account. We also demonstrated that the accumulated effect of aboveground conditions could be included when simulating the relationship between soil temperature and tree water uptake. This improved the estimated transpiration for the control plot and when soil warming was delayed into the growing season. The study illustrates the need of including antecedent conditions on root growth in the model in order to catch these effects on transpiration. The COUP model is a promising tool for predicting transpiration in high-latitude stands.

Simultaneous Assimilation of AMSR-E Brightness Temperature and MODIS LST to Improve Soil Moisture with Dual Ensemble Kalman Smoother

NASA Astrophysics Data System (ADS)

Huang, Chunlin; Chen, Weijin; Wang, Weizhen; Gu, Juan

2017-04-01

Uncertainties in model parameters can easily cause systematic differences between model states and observations from ground or satellites, which significantly affect the accuracy of soil moisture estimation in data assimilation systems. In this paper, a novel soil moisture assimilation scheme is developed to simultaneously assimilate AMSR-E brightness temperature (TB) and MODIS Land Surface Temperature (LST), which can correct model bias by simultaneously updating model states and parameters with dual ensemble Kalman filter (DEnKS). The Common Land Model (CoLM) and a Q-h Radiative Transfer Model (RTM) are adopted as model operator and observation operator, respectively. The assimilation experiment is conducted in Naqu, Tibet Plateau, from May 31 to September 27, 2011. Compared with in-situ measurements, the accuracy of soil moisture estimation is tremendously improved in terms of a variety of scales. The updated soil temperature by assimilating MODIS LST as input of RTM can reduce the differences between the simulated and observed brightness temperatures to a certain degree, which helps to improve the estimation of soil moisture and model parameters. The updated parameters show large discrepancy with the default ones and the former effectively reduces the states bias of CoLM. Results demonstrate the potential of assimilating both microwave TB and MODIS LST to improve the estimation of soil moisture and related parameters. Furthermore, this study also indicates that the developed scheme is an effective soil moisture downscaling approach for coarse-scale microwave TB.

Interactions between soil thermal and hydrological dynamics in the response of Alaska ecosystems to fire disturbance

USGS Publications Warehouse

Yi, Shuhua; McGuire, A. David; Harden, Jennifer; Kasischke, Eric; Manies, Kristen L.; Hinzman, Larry; Liljedahl, Anna K.; Randerson, J.; Liu, Heping; Romanovsky, Vladimir E.; Marchenko, Sergey S.; Kim, Yongwon

2009-01-01

Soil temperature and moisture are important factors that control many ecosystem processes. However, interactions between soil thermal and hydrological processes are not adequately understood in cold regions, where the frozen soil, fire disturbance, and soil drainage play important roles in controlling interactions among these processes. These interactions were investigated with a new ecosystem model framework, the dynamic organic soil version of the Terrestrial Ecosystem Model, that incorporates an efficient and stable numerical scheme for simulating soil thermal and hydrological dynamics within soil profiles that contain a live moss horizon, fibrous and amorphous organic horizons, and mineral soil horizons. The performance of the model was evaluated for a tundra burn site that had both preburn and postburn measurements, two black spruce fire chronosequences (representing space-for-time substitutions in well and intermediately drained conditions), and a poorly drained black spruce site. Although space-for-time substitutions present challenges in model-data comparison, the model demonstrates substantial ability in simulating the dynamics of evapotranspiration, soil temperature, active layer depth, soil moisture, and water table depth in response to both climate variability and fire disturbance. Several differences between model simulations and field measurements identified key challenges for evaluating/improving model performance that include (1) proper representation of discrepancies between air temperature and ground surface temperature; (2) minimization of precipitation biases in the driving data sets; (3) improvement of the measurement accuracy of soil moisture in surface organic horizons; and (4) proper specification of organic horizon depth/properties, and soil thermal conductivity.

Developing a New Thermophysical Model for Lunar Regolith Soil at Low Temperatures

NASA Astrophysics Data System (ADS)

Woods-Robinson, R.; Siegler, M. A.; Paige, D. A.

2016-12-01

The thermophysical properties of the lunar regolith soil have been thoroughly investigated within the temperature range of 100 - 400 K. Extensive laboratory measurements of temperature-dependent thermal conductivity and specific heat have been performed on lunar samples collected from the Apollo and Luna missions. However, recent thermal emission measurements from the Lunar Reconnaissance Orbiter Diviner Lunar Radiometer Experiment have revealed temperatures near the poles as low 20 K, far below where existing thermophysical models begin to break down. In the absence of comprehensive laboratory measurements of lunar soil thermal properties at these low temperatures (20 - 100 K), we investigate solid state theory and lunar simulant materials to derive a physically-based theoretical model of specific heat and thermal conductivity in lunar soils in the full range 20 - 400 K. The primary distinctions between this model and its predecessors are: The focus on soil bulk density as a master variable The temperature dependence of the solid conduction component of thermal conductivity at low temperatures, and The concept that the composition and modal petrology of grains - both amorphous and crystalline components - could significantly influence thermal properties of the bulk soil. The simplest version of this model, which assumes that the soil behaves predominantly as a homogeneous particulate material composed of amorphous grains, shows that at low temperatures (20 - 100 K), specific heat is likely higher than expected from current models ( 0.027 J/gK at 20 K) and that thermal conductivity is almost an order of magnitude lower than has generally been assumed in the literature.Any higher-order approximation is difficult at this stage; the thermal conductivity at low temperature could vary drastically depending on the constituent grain materials, their degree of crystallinity, and contributions from phonon scattering modes, among other factors. We use a one-dimensional thermal model to illustrate the effects of our model on diurnal surface temperature variations in permanently shadowed regions on the moon. We aim to lay the theoretical foundation for a new approach to model thermal properties of regolith materials, and to justify the importance of new laboratory measurements of lunar soil below 100 K.

Remotely monitoring evaporation rate and soil water status using thermal imaging and "three-temperatures model (3T Model)" under field-scale conditions.

PubMed

Qiu, Guo Yu; Zhao, Ming

2010-03-01

Remote monitoring of soil evaporation and soil water status is necessary for water resource and environment management. Ground based remote sensing can be the bridge between satellite remote sensing and ground-based point measurement. The primary object of this study is to provide an algorithm to estimate evaporation and soil water status by remote sensing and to verify its accuracy. Observations were carried out in a flat field with varied soil water content. High-resolution thermal images were taken with a thermal camera; soil evaporation was measured with a weighing lysimeter; weather data were recorded at a nearby meteorological station. Based on the thermal imaging and the three-temperatures model (3T model), we developed an algorithm to estimate soil evaporation and soil water status. The required parameters of the proposed method were soil surface temperature, air temperature, and solar radiation. By using the proposed method, daily variation in soil evaporation was estimated. Meanwhile, soil water status was remotely monitored by using the soil evaporation transfer coefficient. Results showed that the daily variation trends of measured and estimated evaporation agreed with each other, with a regression line of y = 0.92x and coefficient of determination R(2) = 0.69. The simplicity of the proposed method makes the 3T model a potentially valuable tool for remote sensing.

Miscanthus Establishment and Overwintering in the Midwest USA: A Regional Modeling Study of Crop Residue Management on Critical Minimum Soil Temperatures

PubMed Central

Kucharik, Christopher J.; VanLoocke, Andy; Lenters, John D.; Motew, Melissa M.

2013-01-01

Miscanthus is an intriguing cellulosic bioenergy feedstock because its aboveground productivity is high for low amounts of agrochemical inputs, but soil temperatures below −3.5°C could threaten successful cultivation in temperate regions. We used a combination of observed soil temperatures and the Agro-IBIS model to investigate how strategic residue management could reduce the risk of rhizome threatening soil temperatures. This objective was addressed using a historical (1978–2007) reconstruction of extreme minimum 10 cm soil temperatures experienced across the Midwest US and model sensitivity studies that quantified the impact of crop residue on soil temperatures. At observation sites and for simulations that had bare soil, two critical soil temperature thresholds (50% rhizome winterkill at −3.5°C and −6.0°C for different Miscanthus genotypes) were reached at rhizome planting depth (10 cm) over large geographic areas. The coldest average annual extreme 10 cm soil temperatures were between −8°C to −11°C across North Dakota, South Dakota, and Minnesota. Large portions of the region experienced 10 cm soil temperatures below −3.5°C in 75% or greater for all years, and portions of North and South Dakota, Minnesota, and Wisconsin experienced soil temperatures below −6.0°C in 50–60% of all years. For simulated management options that established varied thicknesses (1–5 cm) of miscanthus straw following harvest, extreme minimum soil temperatures increased by 2.5°C to 6°C compared to bare soil, with the greatest warming associated with thicker residue layers. While the likelihood of 10 cm soil temperatures reaching −3.5°C was greatly reduced with 2–5 cm of surface residue, portions of the Dakotas, Nebraska, Minnesota, and Wisconsin still experienced temperatures colder than −3.5°C in 50–80% of all years. Nonetheless, strategic residue management could help increase the likelihood of overwintering of miscanthus rhizomes in the first few years after establishment, although low productivity and biomass availability during these early stages could hamper such efforts. PMID:23844244

Simulating sunflower canopy temperatures to infer root-zone soil water potential

NASA Technical Reports Server (NTRS)

Choudhury, B. J.; Idso, S. B.

1983-01-01

A soil-plant-atmosphere model for sunflower (Helianthus annuus L.), together with clear sky weather data for several days, is used to study the relationship between canopy temperature and root-zone soil water potential. Considering the empirical dependence of stomatal resistance on insolation, air temperature and leaf water potential, a continuity equation for water flux in the soil-plant-atmosphere system is solved for the leaf water potential. The transpirational flux is calculated using Monteith's combination equation, while the canopy temperature is calculated from the energy balance equation. The simulation shows that, at high soil water potentials, canopy temperature is determined primarily by air and dew point temperatures. These results agree with an empirically derived linear regression equation relating canopy-air temperature differential to air vapor pressure deficit. The model predictions of leaf water potential are also in agreement with observations, indicating that measurements of canopy temperature together with a knowledge of air and dew point temperatures can provide a reliable estimate of the root-zone soil water potential.

Global sensitivity analysis for identifying important parameters of nitrogen nitrification and denitrification under model uncertainty and scenario uncertainty

NASA Astrophysics Data System (ADS)

Chen, Zhuowei; Shi, Liangsheng; Ye, Ming; Zhu, Yan; Yang, Jinzhong

2018-06-01

Nitrogen reactive transport modeling is subject to uncertainty in model parameters, structures, and scenarios. By using a new variance-based global sensitivity analysis method, this paper identifies important parameters for nitrogen reactive transport with simultaneous consideration of these three uncertainties. A combination of three scenarios of soil temperature and two scenarios of soil moisture creates a total of six scenarios. Four alternative models describing the effect of soil temperature and moisture content are used to evaluate the reduction functions used for calculating actual reaction rates. The results show that for nitrogen reactive transport problem, parameter importance varies substantially among different models and scenarios. Denitrification and nitrification process is sensitive to soil moisture content status rather than to the moisture function parameter. Nitrification process becomes more important at low moisture content and low temperature. However, the changing importance of nitrification activity with respect to temperature change highly relies on the selected model. Model-averaging is suggested to assess the nitrification (or denitrification) contribution by reducing the possible model error. Despite the introduction of biochemical heterogeneity or not, fairly consistent parameter importance rank is obtained in this study: optimal denitrification rate (Kden) is the most important parameter; reference temperature (Tr) is more important than temperature coefficient (Q10); empirical constant in moisture response function (m) is the least important one. Vertical distribution of soil moisture but not temperature plays predominant role controlling nitrogen reaction. This study provides insight into the nitrogen reactive transport modeling and demonstrates an effective strategy of selecting the important parameters when future temperature and soil moisture carry uncertainties or when modelers face with multiple ways of establishing nitrogen models.

Site-level model intercomparison of high latitude and high altitude soil thermal dynamics in tundra and barren landscapes

NASA Astrophysics Data System (ADS)

Ekici, A.; Chadburn, S.; Chaudhary, N.; Hajdu, L. H.; Marmy, A.; Peng, S.; Boike, J.; Burke, E.; Friend, A. D.; Hauck, C.; Krinner, G.; Langer, M.; Miller, P. A.; Beer, C.

2015-07-01

Modeling soil thermal dynamics at high latitudes and altitudes requires representations of physical processes such as snow insulation, soil freezing and thawing and subsurface conditions like soil water/ice content and soil texture. We have compared six different land models: JSBACH, ORCHIDEE, JULES, COUP, HYBRID8 and LPJ-GUESS, at four different sites with distinct cold region landscape types, to identify the importance of physical processes in capturing observed temperature dynamics in soils. The sites include alpine, high Arctic, wet polygonal tundra and non-permafrost Arctic, thus showing how a range of models can represent distinct soil temperature regimes. For all sites, snow insulation is of major importance for estimating topsoil conditions. However, soil physics is essential for the subsoil temperature dynamics and thus the active layer thicknesses. This analysis shows that land models need more realistic surface processes, such as detailed snow dynamics and moss cover with changing thickness and wetness, along with better representations of subsoil thermal dynamics.

Specifics of soil temperature under winter oilseed rape canopy

NASA Astrophysics Data System (ADS)

Krčmářová, Jana; Středa, Tomáš; Pokorný, Radovan

2014-09-01

The aim of this study was to evaluate the course of soil temperature under the winter oilseed rape canopy and to determine relationships between soil temperature, air temperature and partly soil moisture. In addition, the aim was to describe the dependence by means of regression equations usable for pests and pathogens prediction, crop development, and yields models. The measurement of soil and near the ground air temperatures was performed at the experimental field Žabiče (South Moravia, the Czech Republic). The course of temperature was determined under or in the winter oilseed rape canopy during spring growth season in the course of four years (2010 - 2012 and 2014). In all years, the standard varieties (Petrol, Sherpa) were grown, in 2014 the semi-dwarf variety PX104 was added. Automatic soil sensors were positioned at three depths (0.05, 0.10 and 0.20 m) under soil surface, air temperature sensors in 0.05 m above soil surfaces. The course of soil temperature differs significantly between standard (Sherpa and Petrol) and semi-dwarf (PX104) varieties. Results of the cross correlation analysis showed, that the best interrelationships between air and soil temperature were achieved in 2 hours delay for the soil temperature in 0.05 m, 4 hour delay for 0.10 m and 7 hour delay for 0.20 m for standard varieties. For semi-dwarf variety, this delay reached 6 hour for the soil temperature in 0.05 m, 7 hour delay for 0.10 m and 11 hour for 0.20 m. After the time correction, the determination coefficient (R2) reached values from 0.67 to 0.95 for 0.05 m, 0.50 to 0.84 for 0.10 m in variety Sherpa during all experimental years. For variety PX104 this coefficient reached values from 0.51 to 0.72 in 0.05 m depth and from 0.39 to 0.67 in 0.10 m depth in the year 2014. The determination coefficient in the 0.20 m depth was lower for both varieties; its values were from 0.15 to 0.65 in variety Sherpa. In variety PX104 the values of R2 from 0.23 to 0.57 were determined. When using multiple regressions with quadratic spacing (modelling of hourly soil temperature based on the hourly near surface air temperature and hourly soil moisture in the 0.10-0.40 m profile), the difference between the measured and modelled soil temperatures in the depth of 0.05 m was -3.92 to 3.99°C. The regression equation paired with alternative agrometeorological instruments enables relatively accurate modelling of soil temperatures (R2 = 0.95).

Investigation of remote sensing techniques of measuring soil moisture

NASA Technical Reports Server (NTRS)

Newton, R. W. (Principal Investigator); Blanchard, A. J.; Nieber, J. L.; Lascano, R.; Tsang, L.; Vanbavel, C. H. M.

1981-01-01

Major activities described include development and evaluation of theoretical models that describe both active and passive microwave sensing of soil moisture, the evaluation of these models for their applicability, the execution of a controlled field experiment during which passive microwave measurements were acquired to validate these models, and evaluation of previously acquired aircraft microwave measurements. The development of a root zone soil water and soil temperature profile model and the calibration and evaluation of gamma ray attenuation probes for measuring soil moisture profiles are considered. The analysis of spatial variability of soil information as related to remote sensing is discussed as well as the implementation of an instrumented field site for acquisition of soil moisture and meteorologic information for use in validating the soil water profile and soil temperature profile models.

Surprisingly robust projections of soil temperature and moisture for North American drylands in the 21st century

NASA Astrophysics Data System (ADS)

Bradford, J. B.; Schlaepfer, D.; Palmquist, K. A.; Lauenroth, W.

2017-12-01

Climate projections for western North America suggest temperature increases that are relatively consistent across climate models. However, precipitation projections are less consistent, especially in the Southwest, promoting uncertainty about the future of soil moisture and drought. We utilized a daily time-step ecosystem water balance model to characterize soil temperature and moisture patterns at a 10-km resolution across western North America for historical (1980-2010), mid-century (2020-2050), and late century (2070-2100). We simulated soil moisture and temperature under two representative concentration pathways and eleven climate models (selected strategically to represent the range of variability in projections among the full set of models in the CMIP5 database and perform well in hind-cast comparisons for the region), and we use the results to identify areas with robust projections, e.g. areas where the large majority of models agree in the direction of change in long-term average soil moisture or temperature. Rising air temperatures will increase average soil temperatures across western North America and expand the area of mesic and thermic soil temperature regimes while decreasing the area of cryic and frigid regimes. Future soil moisture conditions are relatively consistent across climate models for much of the region, including many areas with variable precipitation trajectories. Consistent projections for drier soils are expected in most of Arizona and New Mexico, similar to previous studies. Other regions with projections for declining soil moisture include the central and southern U.S. Great Plains and large parts of southern British Columbia. By contrast, areas with robust projections for increasing soil moisture include northeastern Montana, southern Alberta and Saskatchewan, and many areas in the intermountain west dominated by big sagebrush. In addition, seasonal moisture patterns in much of the western US drylands are expected to shift toward cool-season water availability, with potentially important consequences for ecosystem structure and function. These results provide a framework for coping with variability in climate projections and assessing climate change impacts on dryland ecosystems.

Effects of meteorological models on the solution of the surface energy balance and soil temperature variations in bare soils

NASA Astrophysics Data System (ADS)

Saito, Hirotaka; Šimůnek, Jiri

2009-07-01

SummaryA complete evaluation of the soil thermal regime can be obtained by evaluating the movement of liquid water, water vapor, and thermal energy in the subsurface. Such an evaluation requires the simultaneous solution of the system of equations for the surface water and energy balance, and subsurface heat transport and water flow. When only daily climatic data is available, one needs not only to estimate diurnal cycles of climatic data, but to calculate the continuous values of various components in the energy balance equation, using different parameterization methods. The objective of this study is to quantify the impact of the choice of different estimation and parameterization methods, referred together to as meteorological models in this paper, on soil temperature predictions in bare soils. A variety of widely accepted meteorological models were tested on the dataset collected at a proposed low-level radioactive-waste disposal site in the Chihuahua Desert in West Texas. As the soil surface was kept bare during the study, no vegetation effects were evaluated. A coupled liquid water, water vapor, and heat transport model, implemented in the HYDRUS-1D program, was used to simulate diurnal and seasonal soil temperature changes in the engineered cover installed at the site. The modified version of HYDRUS provides a flexible means for using various types of information and different models to evaluate surface mass and energy balance. Different meteorological models were compared in terms of their prediction errors for soil temperatures at seven observation depths. The results obtained indicate that although many available meteorological models can be used to solve the energy balance equation at the soil-atmosphere interface in coupled water, vapor, and heat transport models, their impact on overall simulation results varies. For example, using daily average climatic data led to greater prediction errors, while relatively simple meteorological models may significantly improve soil temperature predictions. On the other hand, while models for the albedo and soil emissivity had little impact on soil temperature predictions, the choice of the atmospheric emissivity models had a greater impact. A comparison of all the different models indicates that the error introduced at the soil atmosphere interface propagates to deeper layers. Therefore, attention needs to be paid not only to the precise determination of the soil hydraulic and thermal properties, but also to the selection of proper meteorological models for the components involved in the surface energy balance calculations.

Modulation of Soil Initial State on WRF Model Performance Over China

NASA Astrophysics Data System (ADS)

Xue, Haile; Jin, Qinjian; Yi, Bingqi; Mullendore, Gretchen L.; Zheng, Xiaohui; Jin, Hongchun

2017-11-01

The soil state (e.g., temperature and moisture) in a mesoscale numerical prediction model is typically initialized by reanalysis or analysis data that may be subject to large bias. Such bias may lead to unrealistic land-atmosphere interactions. This study shows that the Climate Forecast System Reanalysis (CFSR) dramatically underestimates soil temperature and overestimates soil moisture over most parts of China in the first (0-10 cm) and second (10-25 cm) soil layers compared to in situ observations in July 2013. A correction based on the global optimal dual kriging is employed to correct CFSR bias in soil temperature and moisture using in situ observations. To investigate the impacts of the corrected soil state on model forecasts, two numerical model simulations—a control run with CFSR soil state and a disturbed run with the corrected soil state—were conducted using the Weather Research and Forecasting model. All the simulations are initiated 4 times per day and run 48 h. Model results show that the corrected soil state, for example, warmer and drier surface over the most parts of China, can enhance evaporation over wet regions, which changes the overlying atmospheric temperature and moisture. The changes of the lifting condensation level, level of free convection, and water transport due to corrected soil state favor precipitation over wet regions, while prohibiting precipitation over dry regions. Moreover, diagnoses indicate that the remote moisture flux convergence plays a dominant role in the precipitation changes over the wet regions.

Soil temperature extrema recovery rates after precipitation cooling

NASA Technical Reports Server (NTRS)

Welker, J. E.

1984-01-01

From a one dimensional view of temperature alone variations at the Earth's surface manifest themselves in two cyclic patterns of diurnal and annual periods, due principally to the effects of diurnal and seasonal changes in solar heating as well as gains and losses of available moisture. Beside these two well known cyclic patterns, a third cycle has been identified which occurs in values of diurnal maxima and minima soil temperature extrema at 10 cm depth usually over a mesoscale period of roughly 3 to 14 days. This mesoscale period cycle starts with precipitation cooling of soil and is followed by a power curve temperature recovery. The temperature recovery clearly depends on solar heating of the soil with an increased soil moisture content from precipitation combined with evaporation cooling at soil temperatures lowered by precipitation cooling, but is quite regular and universal for vastly different geographical locations, and soil types and structures. The regularity of the power curve recovery allows a predictive model approach over the recovery period. Multivariable linear regression models alloy predictions of both the power of the temperature recovery curve as well as the total temperature recovery amplitude of the mesoscale temperature recovery, from data available one day after the temperature recovery begins.

Effect of soil temperature on optical frequency transfer through unidirectional dense-wavelength-division-multiplexing fiber-optic links.

PubMed

Pinkert, T J; Böll, O; Willmann, L; Jansen, G S M; Dijck, E A; Groeneveld, B G H M; Smets, R; Bosveld, F C; Ubachs, W; Jungmann, K; Eikema, K S E; Koelemeij, J C J

2015-02-01

Results of optical frequency transfer over a carrier-grade dense-wavelength-division-multiplexing (DWDM) optical fiber network are presented. The relation between soil temperature changes on a buried optical fiber and frequency changes of an optical carrier through the fiber is modeled. Soil temperatures, measured at various depths by the Royal Netherlands Meteorology Institute (KNMI) are compared with observed frequency variations through this model. A comparison of a nine-day record of optical frequency measurements through the 2×298  km fiber link with soil temperature data shows qualitative agreement. A soil temperature model is used to predict the link stability over longer periods (days-months-years). We show that optical frequency dissemination is sufficiently stable to distribute and compare, e.g., rubidium frequency standards over standard DWDM optical fiber networks using unidirectional fibers.

Process-based modeling of temperature and water profiles in the seedling recruitment zone: Part I. Model validation

USDA-ARS?s Scientific Manuscript database

Process-based modeling provides detailed spatial and temporal information of the soil environment in the shallow seedling recruitment zone across field topography where measurements of soil temperature and water may not sufficiently describe the zone. Hourly temperature and water profiles within the...

Modeling the effects of tree species and incubation temperature on soil's extracellular enzyme activity in 78-year-old tree plantations

NASA Astrophysics Data System (ADS)

Zhou, Xiaoqi; Wang, Shen S. J.; Chen, Chengrong

2017-12-01

Forest plantations have been widely used as an effective measure for increasing soil carbon (C), and nitrogen (N) stocks and soil enzyme activities play a key role in soil C and N losses during decomposition of soil organic matter. However, few studies have been carried out to elucidate the mechanisms behind the differences in soil C and N cycling by different tree species in response to climate warming. Here, we measured the responses of soil's extracellular enzyme activity (EEA) to a gradient of temperatures using incubation methods in 78-year-old forest plantations with different tree species. Based on a soil enzyme kinetics model, we established a new statistical model to investigate the effects of temperature and tree species on soil EEA. In addition, we established a tree species-enzyme-C/N model to investigate how temperature and tree species influence soil C/N contents over time without considering plant C inputs. These extracellular enzymes included C acquisition enzymes (β-glucosidase, BG), N acquisition enzymes (N-acetylglucosaminidase, NAG; leucine aminopeptidase, LAP) and phosphorus acquisition enzymes (acid phosphatases). The results showed that incubation temperature and tree species significantly influenced all soil EEA and Eucalyptus had 1.01-2.86 times higher soil EEA than coniferous tree species. Modeling showed that Eucalyptus had larger soil C losses but had 0.99-2.38 times longer soil C residence time than the coniferous tree species over time. The differences in the residual soil C and N contents between Eucalyptus and coniferous tree species, as well as between slash pine (Pinus elliottii Engelm. var. elliottii) and hoop pine (Araucaria cunninghamii Ait.), increase with time. On the other hand, the modeling results help explain why exotic slash pine can grow faster, as it has 1.22-1.38 times longer residual soil N residence time for LAP, which mediate soil N cycling in the long term, than native coniferous tree species like hoop pine and kauri pine (Agathis robusta C. Moore). Our results will be helpful for understanding the mechanisms of soil C and N cycling by different tree species, which will have implications for forest management.

Long-term sensitivity of soil carbon turnover to warming.

PubMed

Knorr, W; Prentice, I C; House, J I; Holland, E A

2005-01-20

The sensitivity of soil carbon to warming is a major uncertainty in projections of carbon dioxide concentration and climate. Experimental studies overwhelmingly indicate increased soil organic carbon (SOC) decomposition at higher temperatures, resulting in increased carbon dioxide emissions from soils. However, recent findings have been cited as evidence against increased soil carbon emissions in a warmer world. In soil warming experiments, the initially increased carbon dioxide efflux returns to pre-warming rates within one to three years, and apparent carbon pool turnover times are insensitive to temperature. It has already been suggested that the apparent lack of temperature dependence could be an artefact due to neglecting the extreme heterogeneity of soil carbon, but no explicit model has yet been presented that can reconcile all the above findings. Here we present a simple three-pool model that partitions SOC into components with different intrinsic turnover rates. Using this model, we show that the results of all the soil-warming experiments are compatible with long-term temperature sensitivity of SOC turnover: they can be explained by rapid depletion of labile SOC combined with the negligible response of non-labile SOC on experimental timescales. Furthermore, we present evidence that non-labile SOC is more sensitive to temperature than labile SOC, implying that the long-term positive feedback of soil decomposition in a warming world may be even stronger than predicted by global models.

Modeling soil temperature change in Seward Peninsula, Alaska

NASA Astrophysics Data System (ADS)

Debolskiy, M. V.; Nicolsky, D.; Romanovsky, V. E.; Muskett, R. R.; Panda, S. K.

2017-12-01

Increasing demand for assessment of climate change-induced permafrost degradation and its consequences promotes creation of high-resolution modeling products of soil temperature changes. This is especially relevant for areas with highly vulnerable warm discontinuous permafrost in the Western Alaska. In this study, we apply ecotype-based modeling approach to simulate high-resolution permafrost distribution and its temporal dynamics in Seward Peninsula, Alaska. To model soil temperature dynamics, we use a transient soil heat transfer model developed at the Geophysical Institute Permafrost Laboratory (GIPL-2). The model solves one dimensional nonlinear heat equation with phase change. The developed model is forced with combination of historical climate and different future scenarios for 1900-2100 with 2x2 km resolution prepared by Scenarios Network for Alaska and Arctic Planning (2017). Vegetation, snow and soil properties are calibrated by ecotype and up-scaled by using Alaska Existing Vegetation Type map for Western Alaska (Flemming, 2015) with 30x30 m resolution provided by Geographic Information Network of Alaska (UAF). The calibrated ecotypes cover over 75% of the study area. We calibrate the model using a data assimilation technique utilizing available observations of air, surface and sub-surface temperatures and snow cover collected by various agencies and research groups (USGS, Geophysical Institute, USDA). The calibration approach takes into account a natural variability between stations in the same ecotype and finds an optimal set of model parameters (snow and soil properties) within the study area. This approach allows reduction in microscale heterogeneity and aggregated soil temperature data from shallow boreholes which is highly dependent on local conditions. As a result of this study we present a series of preliminary high resolution maps for the Seward Peninsula showing changes in the active layer depth and ground temperatures for the current climate and future climate change scenarios.

Higher climatological temperature sensitivity of soil carbon in cold than warm climates

NASA Astrophysics Data System (ADS)

Koven, Charles D.; Hugelius, Gustaf; Lawrence, David M.; Wieder, William R.

2017-11-01

The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models (ESMs). To assess the climatological temperature sensitivity of soil carbon, we calculate apparent soil carbon turnover times that reflect long-term and broad-scale rates of decomposition. Here, we show that the climatological temperature control on carbon turnover in the top metre of global soils is more sensitive in cold climates than in warm climates and argue that it is critical to capture this emergent ecosystem property in global-scale models. We present a simplified model that explains the observed high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Current ESMs fail to capture this pattern, except in an ESM that explicitly resolves vertical gradients in soil climate and carbon turnover. An observed weak tropical temperature sensitivity emerges in a different model that explicitly resolves mineralogical control on decomposition. These results support projections of strong carbon-climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behaviour.

Temperature sensitivity of soil microbial communities: An application of macromolecular rate theory to microbial respiration

NASA Astrophysics Data System (ADS)

Alster, Charlotte J.; Koyama, Akihiro; Johnson, Nels G.; Wallenstein, Matthew D.; von Fischer, Joseph C.

2016-06-01

There is compelling evidence that microbial communities vary widely in their temperature sensitivity and may adapt to warming through time. To date, this sensitivity has been largely characterized using a range of models relying on versions of the Arrhenius equation, which predicts an exponential increase in reaction rate with temperature. However, there is growing evidence from laboratory and field studies that observe nonmonotonic responses of reaction rates to variation in temperature, indicating that Arrhenius is not an appropriate model for quantitatively characterizing temperature sensitivity. Recently, Hobbs et al. (2013) developed macromolecular rate theory (MMRT), which incorporates thermodynamic temperature optima as arising from heat capacity differences between isoenzymes. We applied MMRT to measurements of respiration from soils incubated at different temperatures. These soils were collected from three grassland sites across the U.S. Great Plains and reciprocally transplanted, allowing us to isolate the effects of microbial community type from edaphic factors. We found that microbial community type explained roughly 30% of the variation in the CO2 production rate from the labile C pool but that temperature and soil type were most important in explaining variation in labile and recalcitrant C pool size. For six out of the nine soil × inoculum combinations, MMRT was superior to Arrhenius. The MMRT analysis revealed that microbial communities have distinct heat capacity values and temperature sensitivities sometimes independent of soil type. These results challenge the current paradigm for modeling temperature sensitivity of soil C pools and understanding of microbial enzyme dynamics.

Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS

PubMed Central

Wang, De-Cai; Zhang, Gan-Lin; Zhao, Ming-Song; Pan, Xian-Zhang; Zhao, Yu-Guo; Li, De-Cheng; Macmillan, Bob

2015-01-01

Numerous studies have investigated the direct retrieval of soil properties, including soil texture, using remotely sensed images. However, few have considered how soil properties influence dynamic changes in remote images or how soil processes affect the characteristics of the spectrum. This study investigated a new method for mapping regional soil texture based on the hypothesis that the rate of change of land surface temperature is related to soil texture, given the assumption of similar starting soil moisture conditions. The study area was a typical flat area in the Yangtze-Huai River Plain, East China. We used the widely available land surface temperature product of MODIS as the main data source. We analyzed the relationships between the content of different particle soil size fractions at the soil surface and land surface day temperature, night temperature and diurnal temperature range (DTR) during three selected time periods. These periods occurred after rainfalls and between the previous harvest and the subsequent autumn sowing in 2004, 2007 and 2008. Then, linear regression models were developed between the land surface DTR and sand (> 0.05 mm), clay (< 0.001 mm) and physical clay (< 0.01 mm) contents. The models for each day were used to estimate soil texture. The spatial distribution of soil texture from the studied area was mapped based on the model with the minimum RMSE. A validation dataset produced error estimates for the predicted maps of sand, clay and physical clay, expressed as RMSE of 10.69%, 4.57%, and 12.99%, respectively. The absolute error of the predictions is largely influenced by variations in land cover. Additionally, the maps produced by the models illustrate the natural spatial continuity of soil texture. This study demonstrates the potential for digitally mapping regional soil texture variations in flat areas using readily available MODIS data. PMID:26090852

Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS.

PubMed

Wang, De-Cai; Zhang, Gan-Lin; Zhao, Ming-Song; Pan, Xian-Zhang; Zhao, Yu-Guo; Li, De-Cheng; Macmillan, Bob

2015-01-01

Numerous studies have investigated the direct retrieval of soil properties, including soil texture, using remotely sensed images. However, few have considered how soil properties influence dynamic changes in remote images or how soil processes affect the characteristics of the spectrum. This study investigated a new method for mapping regional soil texture based on the hypothesis that the rate of change of land surface temperature is related to soil texture, given the assumption of similar starting soil moisture conditions. The study area was a typical flat area in the Yangtze-Huai River Plain, East China. We used the widely available land surface temperature product of MODIS as the main data source. We analyzed the relationships between the content of different particle soil size fractions at the soil surface and land surface day temperature, night temperature and diurnal temperature range (DTR) during three selected time periods. These periods occurred after rainfalls and between the previous harvest and the subsequent autumn sowing in 2004, 2007 and 2008. Then, linear regression models were developed between the land surface DTR and sand (> 0.05 mm), clay (< 0.001 mm) and physical clay (< 0.01 mm) contents. The models for each day were used to estimate soil texture. The spatial distribution of soil texture from the studied area was mapped based on the model with the minimum RMSE. A validation dataset produced error estimates for the predicted maps of sand, clay and physical clay, expressed as RMSE of 10.69%, 4.57%, and 12.99%, respectively. The absolute error of the predictions is largely influenced by variations in land cover. Additionally, the maps produced by the models illustrate the natural spatial continuity of soil texture. This study demonstrates the potential for digitally mapping regional soil texture variations in flat areas using readily available MODIS data.

Evaluating the performance of coupled snow-soil models in SURFEXv8 to simulate the permafrost thermal regime at a high Arctic site

NASA Astrophysics Data System (ADS)

Barrere, Mathieu; Domine, Florent; Decharme, Bertrand; Morin, Samuel; Vionnet, Vincent; Lafaysse, Matthieu

2017-09-01

Climate change projections still suffer from a limited representation of the permafrost-carbon feedback. Predicting the response of permafrost temperature to climate change requires accurate simulations of Arctic snow and soil properties. This study assesses the capacity of the coupled land surface and snow models ISBA-Crocus and ISBA-ES to simulate snow and soil properties at Bylot Island, a high Arctic site. Field measurements complemented with ERA-Interim reanalyses were used to drive the models and to evaluate simulation outputs. Snow height, density, temperature, thermal conductivity and thermal insulance are examined to determine the critical variables involved in the soil and snow thermal regime. Simulated soil properties are compared to measurements of thermal conductivity, temperature and water content. The simulated snow density profiles are unrealistic, which is most likely caused by the lack of representation in snow models of the upward water vapor fluxes generated by the strong temperature gradients within the snowpack. The resulting vertical profiles of thermal conductivity are inverted compared to observations, with high simulated values at the bottom of the snowpack. Still, ISBA-Crocus manages to successfully simulate the soil temperature in winter. Results are satisfactory in summer, but the temperature of the top soil could be better reproduced by adequately representing surface organic layers, i.e., mosses and litter, and in particular their water retention capacity. Transition periods (soil freezing and thawing) are the least well reproduced because the high basal snow thermal conductivity induces an excessively rapid heat transfer between the soil and the snow in simulations. Hence, global climate models should carefully consider Arctic snow thermal properties, and especially the thermal conductivity of the basal snow layer, to perform accurate predictions of the permafrost evolution under climate change.

Validation of A One-Dimensional Snow-Land Surface Model at the Sleepers River Watershed

NASA Astrophysics Data System (ADS)

Sun, Wen-Yih; Chern, Jiun-Dar

A one-dimensional land surface model, based on conservations of heat and water substance inside the soil and snow, is presented. To validate the model, a stand-alone experiment is carried out with five years of meteorological and hydrological observations collected from the NOAA-ARS Cooperative Snow Research Project (1966-1974) at the Sleepers River watershed in Danville, Vermont, U.S.A. The numerical results show that the model is capable of reproducing the observed soil temperature at different depths during the winter as well as a rapid increase of soil temperature after snow melts in the spring. The model also simulates the density, temperature, thickness, and equivalent water depth of snow reasonably well. The numerical results are sensitive to the fresh snow density and the soil properties used in the model, which affect the heat exchange between the snowpack and the soil.

A surface temperature and moisture parameterization for use in mesoscale numerical models

NASA Technical Reports Server (NTRS)

Tremback, C. J.; Kessler, R.

1985-01-01

A modified multi-level soil moisture and surface temperature model is presented for use as in defining lower boundary conditions in mesoscale weather models. Account is taken of the hydraulic and thermal diffusion properties of the soil, their variations with soil type, and the mixing ratio at the surface. Techniques are defined for integrating the surface input into the multi-level scheme. Sample simulation runs were performed with the modified model and the original model defined by Pielke, et al. (1977, 1981). The models were applied to regional weather forecasting over soils composed of sand and clay loam. The new form of the model avoided iterations necessary in the earlier version of the model and achieved convergence at reasonable profiles for surface temperature and moisture in regions where the earlier version of the model failed.

Near infrared spectroscopy to estimate the temperature reached on burned soils: strategies to develop robust models.

NASA Astrophysics Data System (ADS)

Guerrero, César; Pedrosa, Elisabete T.; Pérez-Bejarano, Andrea; Keizer, Jan Jacob

2014-05-01

The temperature reached on soils is an important parameter needed to describe the wildfire effects. However, the methods for measure the temperature reached on burned soils have been poorly developed. Recently, the use of the near-infrared (NIR) spectroscopy has been pointed as a valuable tool for this purpose. The NIR spectrum of a soil sample contains information of the organic matter (quantity and quality), clay (quantity and quality), minerals (such as carbonates and iron oxides) and water contents. Some of these components are modified by the heat, and each temperature causes a group of changes, leaving a typical fingerprint on the NIR spectrum. This technique needs the use of a model (or calibration) where the changes in the NIR spectra are related with the temperature reached. For the development of the model, several aliquots are heated at known temperatures, and used as standards in the calibration set. This model offers the possibility to make estimations of the temperature reached on a burned sample from its NIR spectrum. However, the estimation of the temperature reached using NIR spectroscopy is due to changes in several components, and cannot be attributed to changes in a unique soil component. Thus, we can estimate the temperature reached by the interaction between temperature and the thermo-sensible soil components. In addition, we cannot expect the uniform distribution of these components, even at small scale. Consequently, the proportion of these soil components can vary spatially across the site. This variation will be present in the samples used to construct the model and also in the samples affected by the wildfire. Therefore, the strategies followed to develop robust models should be focused to manage this expected variation. In this work we compared the prediction accuracy of models constructed with different approaches. These approaches were designed to provide insights about how to distribute the efforts needed for the development of robust models, since this step is the bottle-neck of this technique. In the first approach, a plot-scale model was used to predict the temperature reached in samples collected in other plots from the same site. In a plot-scale model, all the heated aliquots come from a unique plot-scale sample. As expected, the results obtained with this approach were deceptive, because this approach was assuming that a plot-scale model would be enough to represent the whole variability of the site. The accuracy (measured as the root mean square error of prediction, thereinafter RMSEP) was 86ºC, and the bias was also high (>30ºC). In the second approach, the temperatures predicted through several plot-scale models were averaged. The accuracy was improved (RMSEP=65ºC) respect the first approach, because the variability from several plots was considered and biased predictions were partially counterbalanced. However, this approach implies more efforts, since several plot-scale models are needed. In the third approach, the predictions were obtained with site-scale models. These models were constructed with aliquots from several plots. In this case, the results were accurate, since the RMSEP was around 40ºC, the bias was very small (<1ºC) and the R2 was 0.92. As expected, this approach clearly outperformed the second approach, in spite of the fact that the same efforts were needed. In a plot-scale model, only one interaction between temperature and soil components was modelled. However, several different interactions between temperature and soil components were present in the calibration matrix of a site-scale model. Consequently, the site-scale models were able to model the temperature reached excluding the influence of the differences in soil composition, resulting in more robust models respect that variation. Summarizing, the results were highlighting the importance of an adequate strategy to develop robust and accurate models with moderate efforts, and how a wrong strategy can result in deceptive predictions.

Vegetation management with fire modifies peatland soil thermal regime.

PubMed

Brown, Lee E; Palmer, Sheila M; Johnston, Kerrylyn; Holden, Joseph

2015-05-01

Vegetation removal with fire can alter the thermal regime of the land surface, leading to significant changes in biogeochemistry (e.g. carbon cycling) and soil hydrology. In the UK, large expanses of carbon-rich upland environments are managed to encourage increased abundance of red grouse (Lagopus lagopus scotica) by rotational burning of shrub vegetation. To date, though, there has not been any consideration of whether prescribed vegetation burning on peatlands modifies the thermal regime of the soil mass in the years after fire. In this study thermal regime was monitored across 12 burned peatland soil plots over an 18-month period, with the aim of (i) quantifying thermal dynamics between burned plots of different ages (from <2 to 15 + years post burning), and (ii) developing statistical models to determine the magnitude of thermal change caused by vegetation management. Compared to plots burned 15 + years previously, plots recently burned (<2-4 years) showed higher mean, maximum and range of soil temperatures, and lower minima. Statistical models (generalised least square regression) were developed to predict daily mean and maximum soil temperature in plots burned 15 + years prior to the study. These models were then applied to predict temperatures of plots burned 2, 4 and 7 years previously, with significant deviations from predicted temperatures illustrating the magnitude of burn management effects. Temperatures measured in soil plots burned <2 years previously showed significant statistical disturbances from model predictions, reaching +6.2 °C for daily mean temperatures and +19.6 °C for daily maxima. Soil temperatures in plots burnt 7 years previously were most similar to plots burned 15 + years ago indicating the potential for soil temperatures to recover as vegetation regrows. Our findings that prescribed peatland vegetation burning alters soil thermal regime should provide an impetus for further research to understand the consequences of thermal regime change for carbon processing and release, and hydrological processes, in these peatlands. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Modeling soil heating and moisture transport under extreme conditions: Forest fires and slash pile burns

NASA Astrophysics Data System (ADS)

Massman, W. J.

2012-10-01

Heating any soil during a sufficiently intense wildfire or prescribed burn can alter it irreversibly, causing many significant, long-term biological, chemical, and hydrological effects. Given the climate-change-driven increasing probability of wildfires and the increasing use of prescribed burns by land managers, it is important to better understand the dynamics of the coupled heat and moisture transport in soil during these extreme heating events. Furthermore, improved understanding and modeling of heat and mass transport during extreme conditions should provide insights into the associated transport mechanisms under more normal conditions. The present study describes a numerical model developed to simulate soil heat and moisture transport during fires where the surface heating often ranges between 10,000 and 100,000 W m-2 for several minutes to several hours. Basically, the model extends methods commonly used to model coupled heat flow and moisture evaporation at ambient conditions into regions of extreme dryness and heat. But it also incorporates some infrequently used formulations for temperature dependencies of the soil specific heat, thermal conductivity, and the water retention curve, as well as advective effects due to the large changes in volume that occur when liquid water is rapidly volatilized. Model performance is tested against laboratory measurements of soil temperature and moisture changes at several depths during controlled heating events. Qualitatively, the model agrees with the laboratory observations, namely, it simulates an increase in soil moisture ahead of the drying front (due to the condensation of evaporated soil water at the front) and a hiatus in the soil temperature rise during the strongly evaporative stage of the soil drying. Nevertheless, it is shown that the model is incapable of producing a physically realistic solution because it does not (and, in fact, cannot) represent the relationship between soil water potential and soil moisture at extremely low soil moisture contents (i.e., residual or bound water: θ < 0.01 m3 m-3, for example). Diagnosing the model's performance yields important insights into how to make progress on modeling soil evaporation and heating under conditions of high temperatures and very low soil moisture content.

HCMM energy budget data as a model input for assessing regions of high potential groundwater pollution

NASA Technical Reports Server (NTRS)

Moore, D. G. (Principal Investigator); Heilman, J.; Tunheim, J. A.; Baumberger, V.

1978-01-01

The author has identified the following significant results. To investigate the general relationship between surface temperature and soil moisture profiles, a series of model calculations were carried out. Soil temperature profiles were calculated during a complete diurnal cycle for a variety of moisture profiles. Preliminary results indicate the surface temperature difference between two sites measured at about 1400 hours is related to the difference in soil moisture within the diurnal damping depth (about 50 cm). The model shows this temperature difference to vary considerably throughout the diurnal cycle.

Low soil moisture during hot periods drives apparent negative temperature sensitivity of soil respiration in a dryland ecosystem: A multi-model comparison

USGS Publications Warehouse

Tucker, Colin; Reed, Sasha C.

2016-01-01

Arid and semiarid ecosystems (drylands) may dominate the trajectory of biosphere-to-atmosphere carbon (C) flux over the coming century. Accordingly, understanding dryland CO2 efflux controls is important for understanding C cycling at the global-scale: key unknowns regarding how temperature and moisture interact to regulate dryland C cycling remain. Further, the patchiness of dryland vegetation can create ‘islands of fertility’, with spatially heterogeneous rates of soil respiration (Rs). At our study site in southeastern Utah, USA we added or removed litter (0 to 650% of control) in paired plots that were either associated with a shrub or with interspaces between vascular plants. We measured Rs, soil temperature, and water content (θ) on eight sampling dates between October 2013 and November 2014. Rs was highest following monsoon rains in late summer when soil temperature was ~30°C. During mid-summer, Rs was low, associated with high soil temperatures (>40°C), resulting in an apparent negative temperature sensitivity of Rs at high temperatures, and positive temperature sensitivity at low-moderate temperatures. We used Bayesian statistical methods to compare multiple competing models capturing a wide range of hypothesized relationships between temperature, moisture, and Rs. The best fit model indicates apparent negative temperature sensitivity of soil respiration at high temperatures reflects the control of soil moisture – not high temperatures – in limiting Rs. The modeled Q10 ranged from 2.7 at 5°C to 1.4 at 45°C. Litter addition had no effect on temperature sensitivity or reference respiration (Rref = Rs at 20°C and optimum moisture) beneath shrubs, and little effect on Rref in interspaces, yet Rref was 1.5 times higher beneath shrubs than in interspaces. Together, these results suggest reduced Rs often observed at high temperatures in drylands is dominated by the control of moisture, and that variable litter inputs – at least over the short-term – exert minimal control over Rs.

Response of Soil Respiration to Soil Temperature and Moisture in a 50-Year-Old Oriental Arborvitae Plantation in China

PubMed Central

Yu, Xinxiao; Zha, Tianshan; Pang, Zhuo; Wu, Bin; Wang, Xiaoping; Chen, Guopeng; Li, Chunping; Cao, Jixin; Jia, Guodong; Li, Xizhi; Wu, Hailong

2011-01-01

China possesses large areas of plantation forests which take up great quantities of carbon. However, studies on soil respiration in these plantation forests are rather scarce and their soil carbon flux remains an uncertainty. In this study, we used an automatic chamber system to measure soil surface flux of a 50-year-old mature plantation of Platycladus orientalis at Jiufeng Mountain, Beijing, China. Mean daily soil respiration rates (Rs) ranged from 0.09 to 4.87 µmol CO2 m−2s−1, with the highest values observed in August and the lowest in the winter months. A logistic model gave the best fit to the relationship between hourly Rs and soil temperature (Ts), explaining 82% of the variation in Rs over the annual cycle. The annual total of soil respiration estimated from the logistic model was 645±5 g C m−2 year−1. The performance of the logistic model was poorest during periods of high soil temperature or low soil volumetric water content (VWC), which limits the model's ability to predict the seasonal dynamics of Rs. The logistic model will potentially overestimate Rs at high Ts and low VWC. Seasonally, Rs increased significantly and linearly with increasing VWC in May and July, in which VWC was low. In the months from August to November, inclusive, in which VWC was not limiting, Rs showed a positively exponential relationship with Ts. The seasonal sensitivity of soil respiration to Ts (Q10) ranged from 0.76 in May to 4.38 in October. It was suggested that soil temperature was the main determinant of soil respiration when soil water was not limiting. PMID:22163012

Responses of two nonlinear microbial models to warming and increased carbon input

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Y. P.; Jiang, J.; Chen-Charpentier, Benito

A number of nonlinear microbial models of soil carbon decomposition have been developed. Some of them have been applied globally but have yet to be shown to realistically represent soil carbon dynamics in the field. A thorough analysis of their key differences is needed to inform future model developments. In this paper, we compare two nonlinear microbial models of soil carbon decomposition: one based on reverse Michaelis–Menten kinetics (model A) and the other on regular Michaelis–Menten kinetics (model B). Using analytic approximations and numerical solutions, we find that the oscillatory responses of carbon pools to a small perturbation in theirmore » initial pool sizes dampen faster in model A than in model B. Soil warming always decreases carbon storage in model A, but in model B it predominantly decreases carbon storage in cool regions and increases carbon storage in warm regions. For both models, the CO 2 efflux from soil carbon decomposition reaches a maximum value some time after increased carbon input (as in priming experiments). This maximum CO 2 efflux (F max) decreases with an increase in soil temperature in both models. However, the sensitivity of F max to the increased amount of carbon input increases with soil temperature in model A but decreases monotonically with an increase in soil temperature in model B. These differences in the responses to soil warming and carbon input between the two nonlinear models can be used to discern which model is more realistic when compared to results from field or laboratory experiments. Lastly, these insights will contribute to an improved understanding of the significance of soil microbial processes in soil carbon responses to future climate change.« less

Responses of two nonlinear microbial models to warming and increased carbon input

DOE PAGES

Wang, Y. P.; Jiang, J.; Chen-Charpentier, Benito; ...

2016-02-18

A number of nonlinear microbial models of soil carbon decomposition have been developed. Some of them have been applied globally but have yet to be shown to realistically represent soil carbon dynamics in the field. A thorough analysis of their key differences is needed to inform future model developments. In this paper, we compare two nonlinear microbial models of soil carbon decomposition: one based on reverse Michaelis–Menten kinetics (model A) and the other on regular Michaelis–Menten kinetics (model B). Using analytic approximations and numerical solutions, we find that the oscillatory responses of carbon pools to a small perturbation in theirmore » initial pool sizes dampen faster in model A than in model B. Soil warming always decreases carbon storage in model A, but in model B it predominantly decreases carbon storage in cool regions and increases carbon storage in warm regions. For both models, the CO 2 efflux from soil carbon decomposition reaches a maximum value some time after increased carbon input (as in priming experiments). This maximum CO 2 efflux (F max) decreases with an increase in soil temperature in both models. However, the sensitivity of F max to the increased amount of carbon input increases with soil temperature in model A but decreases monotonically with an increase in soil temperature in model B. These differences in the responses to soil warming and carbon input between the two nonlinear models can be used to discern which model is more realistic when compared to results from field or laboratory experiments. Lastly, these insights will contribute to an improved understanding of the significance of soil microbial processes in soil carbon responses to future climate change.« less

A hot future for European droughts

NASA Astrophysics Data System (ADS)

Teuling, Adriaan J.

2018-05-01

Low soil moisture conditions can induce drought but also elevate temperatures. Detailed modelling of the drought-temperature link now shows that rising global temperature will bring drier soils and higher heatwave temperatures in Europe.

Matematical modeling of galophytic plants productivity taking into account the temperature factor and soil salinity level

NASA Astrophysics Data System (ADS)

Natalia, Slyusar; Pisman, Tamara; Pechurkin, Nikolai S.

Among the most challenging tasks faced by contemporary ecology is modeling of biological production process in different plant communities. The difficulty of the task is determined by the complexity of the study material. Models showing the influence of climate and climate change on plant growth, which would also involve soil site parameters, could be of both practical and theoretical interest. In this work a mathematical model has been constructed to describe the growth dynamics of different plant communities of halophytic meadows as dependent upon the temperature factor and soil salinity level, which could be further used to predict yields of these plant communities. The study was performed on plants of halophytic meadows in the coastal area of Lake of the Republic of Khakasia in 2004 - 2006. Every plant community grew on the soil of a different level of salinity - the amount of the solid residue of the saline soil aqueous extract. The mathematical model was analyzed using field data of 2004 and 2006, the years of contrasting air temperatures. Results of model investigations show that there is a correlation between plant growth and the temperature of the air for plant communities growing on soils containing the lowest (0.1Thus, results of our study, in which we used a mathematical model describing the development of plant communities of halophytic meadows and field measurements, suggest that both climate conditions (temperature) and ecological factors of the plants' habitat (soil salinity level) should be taken into account when constructing models for predicting crop yields.

Soil respiration patterns and rates at three Taiwanese forest plantations: dependence on elevation, temperature, precipitation, and litterfall.

PubMed

Huang, Yu-Hsuan; Hung, Chih-Yu; Lin, I-Rhy; Kume, Tomonori; Menyailo, Oleg V; Cheng, Chih-Hsin

2017-11-15

Soil respiration contributes to a large quantity of carbon emissions in the forest ecosystem. In this study, the soil respiration rates at three Taiwanese forest plantations (two lowland and one mid-elevation) were investigated. We aimed to determine how soil respiration varies between lowland and mid-elevation forest plantations and identify the relative importance of biotic and abiotic factors affecting soil respiration. The results showed that the temporal patterns of soil respiration rates were mainly influenced by soil temperature and soil water content, and a combined soil temperature and soil water content model explained 54-80% of the variation. However, these two factors affected soil respiration differently. Soil temperature positively contributed to soil respiration, but a bidirectional relationship between soil respiration and soil water content was revealed. Higher soil moisture content resulted in higher soil respiration rates at the lowland plantations but led to adverse effects at the mid-elevation plantation. The annual soil respiration rates were estimated as 14.3-20.0 Mg C ha -1  year -1 at the lowland plantations and 7.0-12.2 Mg C ha -1  year -1 at the mid-elevation plantation. When assembled with the findings of previous studies, the annual soil respiration rates increased with the mean annual temperature and litterfall but decreased with elevation and the mean annual precipitation. A conceptual model of the biotic and abiotic factors affecting the spatial and temporal patterns of the soil respiration rate was developed. Three determinant factors were proposed: (i) elevation, (ii) stand characteristics, and (iii) soil temperature and soil moisture. The results indicated that changes in temperature and precipitation significantly affect soil respiration. Because of the high variability of soil respiration, more studies and data syntheses are required to accurately predict soil respiration in Taiwanese forests.

EFFECTS OF ELECTROOSMOSIS ON SOIL TEMPERATURE AND HYDRAULIC HEAD: II. NUMERICAL SIMULATION

EPA Science Inventory

A numerical model to simulate the distributions of voltage, soil temperature, and hydraulic head during the field test of electroosmosis was developed. The two-dimensional governing equations for the distributions of voltage, soil temperature, and hydraulic head within a cylindri...

Global soil consumption of atmospheric carbon monoxide: an analysis using a process-based biogeochemistry model

NASA Astrophysics Data System (ADS)

Liu, Licheng; Zhuang, Qianlai; Zhu, Qing; Liu, Shaoqing; van Asperen, Hella; Pihlatie, Mari

2018-06-01

Carbon monoxide (CO) plays an important role in controlling the oxidizing capacity of the atmosphere by reacting with OH radicals that affect atmospheric methane (CH4) dynamics. We develop a process-based biogeochemistry model to quantify the CO exchange between soils and the atmosphere with a 5 min internal time step at the global scale. The model is parameterized using the CO flux data from the field and laboratory experiments for 11 representative ecosystem types. The model is then extrapolated to global terrestrial ecosystems using monthly climate forcing data. Global soil gross consumption, gross production, and net flux of the atmospheric CO are estimated to be from -197 to -180, 34 to 36, and -163 to -145 Tg CO yr-1 (1 Tg = 1012 g), respectively, when the model is driven with satellite-based atmospheric CO concentration data during 2000-2013. Tropical evergreen forest, savanna and deciduous forest areas are the largest sinks at 123 Tg CO yr-1. The soil CO gross consumption is sensitive to air temperature and atmospheric CO concentration, while the gross production is sensitive to soil organic carbon (SOC) stock and air temperature. By assuming that the spatially distributed atmospheric CO concentrations ( ˜ 128 ppbv) are not changing over time, the global mean CO net deposition velocity is estimated to be 0.16-0.19 mm s-1 during the 20th century. Under the future climate scenarios, the CO deposition velocity will increase at a rate of 0.0002-0.0013 mm s-1 yr-1 during 2014-2100, reaching 0.20-0.30 mm s-1 by the end of the 21st century, primarily due to the increasing temperature. Areas near the Equator, the eastern US, Europe and eastern Asia will be the largest sinks due to optimum soil moisture and high temperature. The annual global soil net flux of atmospheric CO is primarily controlled by air temperature, soil temperature, SOC and atmospheric CO concentrations, while its monthly variation is mainly determined by air temperature, precipitation, soil temperature and soil moisture.

Estimating soil temperature using neighboring station data via multi-nonlinear regression and artificial neural network models.

PubMed

Bilgili, Mehmet; Sahin, Besir; Sangun, Levent

2013-01-01

The aim of this study is to estimate the soil temperatures of a target station using only the soil temperatures of neighboring stations without any consideration of the other variables or parameters related to soil properties. For this aim, the soil temperatures were measured at depths of 5, 10, 20, 50, and 100 cm below the earth surface at eight measuring stations in Turkey. Firstly, the multiple nonlinear regression analysis was performed with the "Enter" method to determine the relationship between the values of target station and neighboring stations. Then, the stepwise regression analysis was applied to determine the best independent variables. Finally, an artificial neural network (ANN) model was developed to estimate the soil temperature of a target station. According to the derived results for the training data set, the mean absolute percentage error and correlation coefficient ranged from 1.45% to 3.11% and from 0.9979 to 0.9986, respectively, while corresponding ranges of 1.685-3.65% and 0.9988-0.9991, respectively, were obtained based on the testing data set. The obtained results show that the developed ANN model provides a simple and accurate prediction to determine the soil temperature. In addition, the missing data at the target station could be determined within a high degree of accuracy.

Using Historical Precipitation, Temperature, and Runoff Observations to Evaluate Evaporation Formulations in Land Surface Models

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Mahanama, P. P.

2012-01-01

Key to translating soil moisture memory into subseasonal precipitation and air temperature forecast skill is a realistic treatment of evaporation in the forecast system used - in particular, a realistic treatment of how evaporation responds to variations in soil moisture. The inherent soil moisture-evaporation relationships used in today's land surface models (LSMs), however, arguably reflect little more than guesswork given the lack of evaporation and soil moisture data at the spatial scales represented by regional and global models. Here we present a new approach for evaluating this critical aspect of LSMs. Seasonally averaged precipitation is used as a proxy for seasonally-averaged soil moisture, and seasonally-averaged air temperature is used as a proxy for seasonally-averaged evaporation (e.g., more evaporative cooling leads to cooler temperatures) the relationship between historical precipitation and temperature measurements accordingly mimics in certain important ways nature's relationship between soil moisture and evaporation. Additional information on the relationship is gleaned from joint analysis of precipitation and streamflow measurements. An experimental framework that utilizes these ideas to guide the development of an improved soil moisture-evaporation relationship is described and demonstrated.

Application of Modular Modeling System to Predict Evaporation, Infiltration, Air Temperature, and Soil Moisture

NASA Technical Reports Server (NTRS)

Boggs, Johnny; Birgan, Latricia J.; Tsegaye, Teferi; Coleman, Tommy; Soman, Vishwas

1997-01-01

Models are used for numerous application including hydrology. The Modular Modeling System (MMS) is one of the few that can simulate a hydrology process. MMS was tested and used to compare infiltration, soil moisture, daily temperature, and potential and actual evaporation for the Elinsboro sandy loam soil and the Mattapex silty loam soil in the Microwave Radiometer Experiment of Soil Moisture Sensing at Beltsville Agriculture Research Test Site in Maryland. An input file for each location was created to nut the model. Graphs were plotted, and it was observed that the model gave a good representation for evaporation for both plots. In comparing the two plots, it was noted that infiltration and soil moisture tend to peak around the same time, temperature peaks in July and August and the peak evaporation was observed on September 15 and July 4 for the Elinsboro Mattapex plot respectively. MMS can be used successfully to predict hydrological processes as long as the proper input parameters are available.

Soil moisture sensitivity of autotrophic and heterotrophic forest floor respiration in boreal xeric pine and mesic spruce forests

NASA Astrophysics Data System (ADS)

Ťupek, Boris; Launiainen, Samuli; Peltoniemi, Mikko; Heikkinen, Jukka; Lehtonen, Aleksi

2016-04-01

Litter decomposition rates of the most process based soil carbon models affected by environmental conditions are linked with soil heterotrophic CO2 emissions and serve for estimating soil carbon sequestration; thus due to the mass balance equation the variation in measured litter inputs and measured heterotrophic soil CO2 effluxes should indicate soil carbon stock changes, needed by soil carbon management for mitigation of anthropogenic CO2 emissions, if sensitivity functions of the applied model suit to the environmental conditions e.g. soil temperature and moisture. We evaluated the response forms of autotrophic and heterotrophic forest floor respiration to soil temperature and moisture in four boreal forest sites of the International Cooperative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests) by a soil trenching experiment during year 2015 in southern Finland. As expected both autotrophic and heterotrophic forest floor respiration components were primarily controlled by soil temperature and exponential regression models generally explained more than 90% of the variance. Soil moisture regression models on average explained less than 10% of the variance and the response forms varied between Gaussian for the autotrophic forest floor respiration component and linear for the heterotrophic forest floor respiration component. Although the percentage of explained variance of soil heterotrophic respiration by the soil moisture was small, the observed reduction of CO2 emissions with higher moisture levels suggested that soil moisture response of soil carbon models not accounting for the reduction due to excessive moisture should be re-evaluated in order to estimate right levels of soil carbon stock changes. Our further study will include evaluation of process based soil carbon models by the annual heterotrophic respiration and soil carbon stocks.

Measured and simulated soil water evaporation from four Great Plains soils

USDA-ARS?s Scientific Manuscript database

The amount of soil water lost during stage one and stage two soil water evaporation is of interest to crop water use modelers. The ratio of measured soil surface temperature (Ts) to air temperature (Ta) was tested as a signal for the transition in soil water evaporation from stage one to stage two d...

Shifts in the Physiology and Stoichiometric Needs of Soil Microbial Communities from Subarctic Soils in Response to Warming: Icelandic Geothermal Gradients as a Model.

NASA Astrophysics Data System (ADS)

Marañón-Jiménez, S.; Soong, J.; Leblans, N. I. W.; Sigurdsson, B. D.; Peñuelas, J.; Richter, A.; Asensio, D.; Fransen, E.; Janssens, I. A.

2017-12-01

Large amounts of CO2 can be released to the atmosphere from a faster mineralization of soil organic matter at warmer temperatures, thus inducing climate change feedbacks. Specifically, soils at high northern latitudes store more than half of the global surface soil carbon and are particularly vulnerable to temperature-driven C losses, since they warm more rapidly. Alterations to the temperature sensitivity, physiological functioning and stoichiometric constrains of soil microorganisms in response to rising temperatures can play a key role in these soil carbon (C) losses. We present results of several incubation experiments using soils from geothermal soil temperature gradients in Iceland that have undergone a range of warming intensities for seven years, encompassing the full range of IPCC warming scenarios for the northern region. Soil microbes from warmed soils did not show changes in their temperature sensitivity at the physiological level. On the contrary, seven years of chronic soil warming provoked a permanent increase of microbial metabolic quotients (i.e., respiration per unit of biomass), and a subsequent reduction in the C retained in biomass as substrate became limiting. After the initial depletion of labile soil C, increasing energy demands for metabolic maintenance and resource acquisition at higher temperatures may have triggered permanent functional changes or community shifts towards increasing respiratory costs of soil decomposers. Pointing to this, microbial communities showed a strong C limitation even at ambient soil temperatures, obscuring any metabolic response to nitrogen and phosphorous additions. The tight C:N stoichiometric constrains of soil microbial communities and the strong C limitation for microbial biomass may lead to a reduced capacity of microbial N retention, explaining the equivalent soil C and N losses found in response to soil warming. These results highlight the need to incorporate potential changes in microbial physiological functioning and stoichiometric needs into models, in order to accurately predict future changes in soil C stocks in response to global warming.

Temperature sensitivity of soil microbial activity modeled by the square root equation as a unifying model to differentiate between direct temperature effects and microbial community adaptation.

PubMed

Bååth, Erland

2018-07-01

Numerous models have been used to express the temperature sensitivity of microbial growth and activity in soil making it difficult to compare results from different habitats. Q10 still is one of the most common ways to express temperature relationships. However, Q10 is not constant with temperature and will differ depending on the temperature interval used for the calculation. The use of the square root (Ratkowsky) relationship between microbial activity (A) and temperature below optimum temperature, √A = a × (T-T min ), is proposed as a simple and adequate model that allow for one descriptor, T min (a theoretical minimum temperature for growth and activity), to estimate correct Q10-values over the entire in situ temperature interval. The square root model can adequately describe both microbial growth and respiration, allowing for an easy determination of T min . Q10 for any temperature interval can then be calculated by Q10 = [(T + 10 - T min )/(T-T min )] 2 , where T is the lowest temperature in the Q10 comparison. T min also describes the temperature adaptation of the microbial community. An envelope of T min covering most natural soil habitats varying between -15°C (cold habitats like Antarctica/Arctic) to 0°C (tropical habitats like rain forests and deserts) is suggested, with an 0.3°C increase in T min per 1°C increase in mean annual temperature. It is shown that the main difference between common temperature relationships used in global models is differences in the assumed temperature adaptation of the soil microbial community. The use of the square root equation will allow for one descriptor, T min , determining the temperature response of soil microorganisms, and at the same time allow for comparing temperature sensitivity of microbial activity between habitats, including future projections. © 2018 John Wiley & Sons Ltd.

Research of the diurnal soil respiration dynamic in two typical vegetation communities in Tianjin estuarine wetland

NASA Astrophysics Data System (ADS)

Zhang, Q.; Meng, W. Q.; Li, H. Y.

2016-08-01

Understanding the differences and diurnal variations of soil respiration in different vegetation communities in coastal wetland is to provide basic reliable scientific evidence for the carbon "source" function of wetland ecosystems in Tianjin.Measured soil respiration rate which changed during a day between two typical vegetation communities (Phragmites australis, Suaeda salsa) in coastal wetland in October, 2015. Soil temperature and moisture were measured at the same time. Each of the diurnal curves of soil temperature in two communities had a single peak value, and the diurnal variations of soil moisture showed a "two peak-one valley" trend. The diurnal dynamic of soil respiration under the two communities had obvious volatility which showed a single peak form with its maximum between 12:00-14:00 and minimum during 18:00. The diurnal average of soil respiration rate in Phragmites australis communities was 3.37 times of that in Suaeda salsa communities. Significant relationships were found by regression analysis among soil temperature, soil moisture and soil respiration rate in Suaeda salsa communities. There could be well described by exponential models which was y = -0.245e0.105t between soil respiration rate and soil temperature, by quadratic models which was y = -0.276×2 + 15.277× - 209.566 between soil respiration rate and soil moisture. But the results of this study showed that there were no significant correlations between soil respiration and soil temperature and soil moisture in Phragmites australis communities (P > 0.05). Therefore, under the specific wetland environment conditions in Tianjin, soil temperature and moisture were not main factors influencing the diurnal variations of soil respiration rate in Phragmites australis communities.

Soil Water and Temperature System (SWATS) Instrument Handbook

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cook, David R.

2016-04-01

The soil water and temperature system (SWATS) provides vertical profiles of soil temperature, soil-water potential, and soil moisture as a function of depth below the ground surface at hourly intervals. The temperature profiles are measured directly by in situ sensors at the Central Facility and many of the extended facilities of the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility Southern Great Plains (SGP) site. The soil-water potential and soil moisture profiles are derived from measurements of soil temperature rise in response to small inputs of heat. Atmospheric scientists use the data in climate models tomore » determine boundary conditions and to estimate the surface energy flux. The data are also useful to hydrologists, soil scientists, and agricultural scientists for determining the state of the soil.« less

Spatial variation of corn canopy temperature as dependent upon soil texture and crop rooting characteristics

NASA Technical Reports Server (NTRS)

Choudhury, B. J.

1983-01-01

A soil plant atmosphere model for corn (Zea mays L.) together with the scaling theory for soil hydraulic heterogeneity are used to study the sensitivity of spatial variation of canopy temperature to field averaged soil texture and crop rooting characteristics. The soil plant atmosphere model explicitly solves a continuity equation for water flux resulting from root water uptake, changes in plant water storage and transpirational flux. Dynamical equations for root zone soil water potential and the plant water storage models the progressive drying of soil, and day time dehydration and night time hydration of the crop. The statistic of scaling parameter which describes the spatial variation of soil hydraulic conductivity and matric potential is assumed to be independent of soil texture class. The field averaged soil hydraulic characteristics are chosen to be representative of loamy sand and clay loam soils. Two rooting characteristics are chosen, one shallow and the other deep rooted. The simulation shows that the range of canopy temperatures in the clayey soil is less than 1K, but for the sandy soil the range is about 2.5 and 5.0 K, respectively, for the shallow and deep rooted crops.

Forest thinning and soil respiration in a ponderosa pine plantation in the Sierra Nevada.

PubMed

Tang, Jianwu; Qi, Ye; Xu, Ming; Misson, Laurent; Goldstein, Allen H

2005-01-01

Soil respiration is controlled by soil temperature, soil water, fine roots, microbial activity, and soil physical and chemical properties. Forest thinning changes soil temperature, soil water content, and root density and activity, and thus changes soil respiration. We measured soil respiration monthly and soil temperature and volumetric soil water continuously in a young ponderosa pine (Pinus ponderosa Dougl. ex P. Laws. & C. Laws.) plantation in the Sierra Nevada Mountains in California from June 1998 to May 2000 (before a thinning that removed 30% of the biomass), and from May to December 2001 (after thinning). Thinning increased the spatial homogeneity of soil temperature and respiration. We conducted a multivariate analysis with two independent variables of soil temperature and water and a categorical variable representing the thinning event to simulate soil respiration and assess the effect of thinning. Thinning did not change the sensitivity of soil respiration to temperature or to water, but decreased total soil respiration by 13% at a given temperature and water content. This decrease in soil respiration was likely associated with the decrease in root density after thinning. With a model driven by continuous soil temperature and water time series, we estimated that total soil respiration was 948, 949 and 831 g C m(-2) year(-1) in the years 1999, 2000 and 2001, respectively. Although thinning reduced soil respiration at a given temperature and water content, because of natural climate variability and the thinning effect on soil temperature and water, actual cumulative soil respiration showed no clear trend following thinning. We conclude that the effect of forest thinning on soil respiration is the combined result of a decrease in root respiration, an increase in soil organic matter, and changes in soil temperature and water due to both thinning and interannual climate variability.

Benchmark Data Set for Wheat Growth Models: Field Experiments and AgMIP Multi-Model Simulations.

NASA Technical Reports Server (NTRS)

Asseng, S.; Ewert, F.; Martre, P.; Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P.J.; Rotter, R. P.

2015-01-01

The data set includes a current representative management treatment from detailed, quality-tested sentinel field experiments with wheat from four contrasting environments including Australia, The Netherlands, India and Argentina. Measurements include local daily climate data (solar radiation, maximum and minimum temperature, precipitation, surface wind, dew point temperature, relative humidity, and vapor pressure), soil characteristics, frequent growth, nitrogen in crop and soil, crop and soil water and yield components. Simulations include results from 27 wheat models and a sensitivity analysis with 26 models and 30 years (1981-2010) for each location, for elevated atmospheric CO2 and temperature changes, a heat stress sensitivity analysis at anthesis, and a sensitivity analysis with soil and crop management variations and a Global Climate Model end-century scenario.

Three phase heat and mass transfer model for unsaturated soil freezing process: Part 2 - model validation

NASA Astrophysics Data System (ADS)

Zhang, Yaning; Xu, Fei; Li, Bingxi; Kim, Yong-Song; Zhao, Wenke; Xie, Gongnan; Fu, Zhongbin

2018-04-01

This study aims to validate the three-phase heat and mass transfer model developed in the first part (Three phase heat and mass transfer model for unsaturated soil freezing process: Part 1 - model development). Experimental results from studies and experiments were used for the validation. The results showed that the correlation coefficients for the simulated and experimental water contents at different soil depths were between 0.83 and 0.92. The correlation coefficients for the simulated and experimental liquid water contents at different soil temperatures were between 0.95 and 0.99. With these high accuracies, the developed model can be well used to predict the water contents at different soil depths and temperatures.

Relationship between fire temperature and changes in chemical soil properties: a conceptual model of nutrient release

NASA Astrophysics Data System (ADS)

Thomaz, Edivaldo L.; Doerr, Stefan H.

2014-05-01

The purpose of this study was to evaluate the effects of fire temperatures (i.e., soil heating) on nutrient release and aggregate physical changes in soil. A preliminary conceptual model of nutrient release was established based on results obtained from a controlled burn in a slash-and-burn agricultural system located in Brazil. The study was carried out in clayey subtropical soil (humic Cambisol) from a plot that had been fallow for 8 years. A set of three thermocouples were placed in four trenches at the following depths: 0 cm on the top of the mineral horizon, 1.0 cm within the mineral horizon, and 2 cm within the mineral horizon. Three soil samples (true independent sample) were collected approximately 12 hours post-fire at depths of 0-2.5 cm. Soil chemical changes were more sensitive to fire temperatures than aggregate physical soil characteristics. Most of the nutrient response to soil heating was not linear. The results demonstrated that moderate temperatures (< 400°C) had a major effect on nutrient release (i.e., the optimum effect), whereas high temperatures (> 500 °C) decreased soil fertility.

Time and temperature dependent adsorption-desorption behaviour of pretilachlor in soil.

PubMed

Kaur, Paawan; Kaur, Pervinder

2018-06-04

Understanding and quantifying the adsorption-desorption behaviour of herbicide in soil is imperative for predicting their fate and transport in the environment. In the present study, the effect of time and temperature on the adsorption-desorption behaviour of pretilachlor in soils was investigated using batch equilibration technique. The adsorption-desorption kinetics of pretilachlor in soils was two step process and was well described by pseudo-second-order kinetic model. Freundlich model accurately predicted the sorption behaviour of pretilachlor. The adsorption-desorption of pretilachlor varied significantly with the concentration, temperature and properties of soil viz. organic matter and clay content. All the studied soils had non-linear slopes (n < 1) and degree of nonlinearity increased with increase in clay, organic matter content and temperature (p < 0.05). Desorption of pretilachlor was hysteretic in studied soils and hysteresis coefficient varied from 0.023 to 0.275. Thermodynamic analysis showed that pretilachlor adsorption onto soils was a feasible, spontaneous and endothermic process which becomes more favourable at high temperature. It could be inferred that the adsorption of pretilachlor on soils was physical in nature. Copyright © 2018 Elsevier Inc. All rights reserved.

Aspects of spatial and temporal aggregation in estimating regional carbon dioxide fluxes from temperate forest soils

NASA Technical Reports Server (NTRS)

Kicklighter, David W.; Melillo, Jerry M.; Peterjohn, William T.; Rastetter, Edward B.; Mcguire, A. David; Steudler, Paul A.; Aber, John D.

1994-01-01

We examine the influence of aggregation errors on developing estimates of regional soil-CO2 flux from temperate forests. We find daily soil-CO2 fluxes to be more sensitive to changes in soil temperatures (Q(sub 10) = 3.08) than air temperatures (Q(sub 10) = 1.99). The direct use of mean monthly air temperatures with a daily flux model underestimates regional fluxes by approximately 4%. Temporal aggregation error varies with spatial resolution. Overall, our calibrated modeling approach reduces spatial aggregation error by 9.3% and temporal aggregation error by 15.5%. After minimizing spatial and temporal aggregation errors, mature temperate forest soils are estimated to contribute 12.9 Pg C/yr to the atmosphere as carbon dioxide. Georeferenced model estimates agree well with annual soil-CO2 fluxes measured during chamber studies in mature temperate forest stands around the globe.

Modelling soil temperature and moisture and corresponding seasonality of photosynthesis and transpiration in a boreal spruce ecosystem

NASA Astrophysics Data System (ADS)

Wu, S. H.; Jansson, P.-E.

2012-05-01

Recovery of photosynthesis and transpiration is strongly restricted by low temperatures in air and/or soil during the transition period from winter to spring in boreal zones. The extent to which air temperature (Ta) and soil temperature (Ts) influence the seasonality of photosynthesis and transpiration of a boreal spruce ecosystem was investigated using a process-based ecosystem model (CoupModel) together with eddy covariance (EC) data from one eddy flux tower and nearby soil measurements at Knottåsen, Sweden. A Monte Carlo based uncertainty method (GLUE) provided prior and posterior distributions of simulations representing a wide range of soil conditions and performance indicators. The simulated results showed sufficient flexibility to predict the measured cold and warm Ts in the moist and dry plots around the eddy flux tower. Moreover, the model presented a general ability to describe both biotic and abiotic processes for the Norway spruce stand. The dynamics of sensible heat fluxes were well described the corresponding latent heat fluxes and net ecosystem exchange of CO2. The parameter ranges obtained are probably valid to represent regional characteristics of boreal conifer forests, but were not easy to constrain to a smaller range than that produced by the assumed prior distributions. Finally, neglecting the soil temperature response function resulted in fewer behavioural models and probably more compensatory errors in other response functions for regulating the seasonality of ecosystem fluxes.

Wildfires effects on soils: water repellency, NIR models and post-fire treatments. My personal view (SSS Division Outstanding ECS Award Lecture)

NASA Astrophysics Data System (ADS)

Arcenegui, Victoria

2017-04-01

I first was intrigued by fire, because all summers we had some of them in our location, and then I was involve in fire effects on soils. We had, and also have, a lot of question to answer. I am absolutely sure that soil science was my best choice. Soils are amazing, a lot of things are happening in soils. Soils and fire, are my main research topics. I studied the immediately effect of fire on soils, focus on the effect of fire in soil water repellency and aggregate stability. Two physical properties that are crucial to post-fire soil response. I also construct NIR models to know the maximum temperature reached in soils. It is well known that temperature is a key factor affecting soils properties. Then, it is a really important tool to predict the temperature reached in a soil after a wildfire. Currently, I am involve in a project to investigate what are the best post-fire treatments in our soils and how this treatments affects soil properties.

Validation of the Soil Moisture Active Passive (SMAP) satellite soil moisture retrieval in an Arctic tundra environment

NASA Astrophysics Data System (ADS)

Wrona, Elizabeth; Rowlandson, Tracy L.; Nambiar, Manoj; Berg, Aaron A.; Colliander, Andreas; Marsh, Philip

2017-05-01

This study examines the Soil Moisture Active Passive soil moisture product on the Equal Area Scalable Earth-2 (EASE-2) 36 km Global cylindrical and North Polar azimuthal grids relative to two in situ soil moisture monitoring networks that were installed in 2015 and 2016. Results indicate that there is no relationship between the Soil Moisture Active Passive (SMAP) Level-2 passive soil moisture product and the upscaled in situ measurements. Additionally, there is very low correlation between modeled brightness temperature using the Community Microwave Emission Model and the Level-1 C SMAP brightness temperature interpolated to the EASE-2 Global grid; however, there is a much stronger relationship to the brightness temperature measurements interpolated to the North Polar grid, suggesting that the soil moisture product could be improved with interpolation on the North Polar grid.

Impact of surface processes and climate variability on clumped isotope thermometry of soil carbonates, southern Central Andes, Argentina (Invited)

NASA Astrophysics Data System (ADS)

Huntington, K. W.; Peters, N.; Roe, G.; Hoke, G. D.; Eiler, J.

2010-12-01

Soil carbonates archive a potentially rich record of past climate, but rates of pedogenic carbonate formation, erosion, and deposition impact how the isotopic composition and formation temperature of carbonate-bearing paleosols reflect the local environmental conditions under which they form. We investigate these processes using conventional stable isotope (δ18O and δ13C) and clumped isotope thermometry data for Quaternary pedogenic carbonates from the southern Central Andes at ~33°S, Argentina. The study area spans over 2 km of relief in the Río Mendoza and Río de las Cuevas valleys, accessing a range of mean annual temperature conditions and vegetative cover and exhibiting large seasonal variations in temperature, precipitation, and soil moisture. Variations in soil conditions influence carbonate precipitation and dissolution reactions and the rate and depth of pedogenic carbonate formation. Because soil temperature varies predictably as a function of depth in the soil and seasonal and secular variations in air temperature, clumped isotope thermometry of samples collected in soil pits offers a direct way to estimate the seasonality of pedogenic carbonate formation and potential biases in the long-term climate record. We explore potential complications due to the effects of radiative solar heating on the relationship between air and soil temperatures by examining clumped isotope thermometry results in the context of site-to-site variations in vegetative cover. Temperature estimates from clumped isotope thermometry of pedogenic carbonate collected 5-110 cm below geomorphically stable soil surfaces from 1200-3400 m a.s.l. are compared to temperature profiles predicted by simple rule-based models of soil carbonate formation. The models use climate reanalysis daily diagnostic data (soil temperature, soil moisture, and latent heat flux as a proxy for evaporation) and weather station data as input to assess how varying rates of pedogenic carbonate formation integrated over millennial timescales might impact the geologic record of temperature and isotopic composition.

Soil heating and evaporation under extreme conditions: Forest fires and slash pile burns

NASA Astrophysics Data System (ADS)

Massman, W. J.

2011-12-01

Heating any soil during a sufficiently intense wild fire or prescribed burn can alter soil irreversibly, resulting in many significant and well known, long term biological, chemical, and hydrological effects. To better understand how fire impacts soil, especially considering the increasing probability of wildfires that is being driven by climate change and the increasing use of prescribe burns by land managers, it is important to better understand the dynamics of the coupled heat and moisture transport in soil during these extreme heating events. Furthermore, improving understanding of heat and mass transport during such extreme conditions should also provide insights into the associated transport mechanisms under more normal conditions as well. Here I describe the development of a new model designed to simulate soil heat and moisture transport during fires where the surface heating often ranges between 10,000 and 100,000 Wm-2 for several minutes to several hours. Model performance is tested against laboratory measurements of soil temperature and moisture changes at several depths during controlled heating events created with an extremely intense radiant heater. The laboratory tests employed well described soils with well known physical properties. The model, on the other hand, is somewhat unusual in that it employs formulations for temperature dependencies of the soil specific heat, thermal conductivity, and the water retention curve (relation between soil moisture and soil moisture potential). It also employs a new formulation for the surface evaporation rate as a component of the upper boundary condition, as well as the Newton-Raphson method and the generalized Thomas algorithm for inverting block tri-diagonal matrices to solve for soil temperature and soil moisture potential. Model results show rapid evaporation rates with significant vapor transfer not only to the free atmosphere above the soil, but to lower depths of the soil, where the vapor re-condenses ahead of the heating front. Consequently the trajectory of the solution (soil volumetric water content versus soil temperature) is very unusual and highly nonlinear, which may explain why more traditional methods (i.e., those based on finite difference or finite element approaches) tend to show more numerical instabilities than the Newton-Raphson method when used to model these extreme conditions. But, despite the intuitive and qualitative appeal of the model's numerical solution, it underestimates the rate of soil moisture loss observed during the laboratory trials, although the soil temperatures are reasonably well simulated.

Sensitivity of Land Surface Parameters on Thunderstorm Simulation through HRLDAS-WRF Coupling Mode

NASA Astrophysics Data System (ADS)

Kumar, Dinesh; Kumar, Krishan; Mohanty, U. C.; Kisore Osuri, Krishna

2016-07-01

Land surface characteristics play an important role in large scale, regional and mesoscale atmospheric process. Representation of land surface characteristics can be improved through coupling of mesoscale atmospheric models with land surface models. Mesoscale atmospheric models depend on Land Surface Models (LSM) to provide land surface variables such as fluxes of heat, moisture, and momentum for lower boundary layer evolution. Studies have shown that land surface properties such as soil moisture, soil temperature, soil roughness, vegetation cover, have considerable effect on lower boundary layer. Although, the necessity to initialize soil moisture accurately in NWP models is widely acknowledged, monitoring soil moisture at regional and global scale is a very tough task due to high spatial and temporal variability. As a result, the available observation network is unable to provide the required spatial and temporal data for the most part of the globe. Therefore, model for land surface initializations rely on updated land surface properties from LSM. The solution for NWP land-state initialization can be found by combining data assimilation techniques, satellite-derived soil data, and land surface models. Further, it requires an intermediate step to use observed rainfall, satellite derived surface insolation, and meteorological analyses to run an uncoupled (offline) integration of LSM, so that the evolution of modeled soil moisture can be forced by observed forcing conditions. Therefore, for accurate land-state initialization, high resolution land data assimilation system (HRLDAS) is used to provide the essential land surface parameters. Offline-coupling of HRLDAS-WRF has shown much improved results over Delhi, India for four thunder storm events. The evolution of land surface variables particularly soil moisture, soil temperature and surface fluxes have provided more realistic condition. Results have shown that most of domain part became wetter and warmer after assimilation of soil moisture and soil temperature at the initial condition which helped to improve the exchange fluxes at lower atmospheric level. Mixing ratio were increased along with elevated theta-e at lower level giving a signature of improvement in LDAS experiment leading to a suitable condition for convection. In the analysis, moisture convergence, mixing ratio and vertical velocities have improved significantly in terms of intensity and time lag. Surface variables like soil moisture, soil temperature, sensible heat flux and latent heat flux have progressed in a possible realistic pattern. Above discussion suggests that assimilation of soil moisture and soil temperature improves the overall simulations significantly.

Preliminary assessment of soil moisture over vegetation

NASA Technical Reports Server (NTRS)

Carlson, T. N.

1986-01-01

Modeling of surface energy fluxes was combined with in-situ measurement of surface parameters, specifically the surface sensible heat flux and the substrate soil moisture. A vegetation component was incorporated in the atmospheric/substrate model and subsequently showed that fluxes over vegetation can be very much different than those over bare soil for a given surface-air temperature difference. The temperature signatures measured by a satellite or airborne radiometer should be interpreted in conjunction with surface measurements of modeled parameters. Paradoxically, analyses of the large-scale distribution of soil moisture availability shows that there is a very high correlation between antecedent precipitation and inferred surface moisture availability, even when no specific vegetation parameterization is used in the boundary layer model. Preparatory work was begun in streamlining the present boundary layer model, developing better algorithms for relating surface temperatures to substrate moisture, preparing for participation in the French HAPEX experiment, and analyzing aircraft microwave and radiometric surface temperature data for the 1983 French Beauce experiments.

Diel hysteresis between soil respiration and soil temperature in a biological soil crust covered desert ecosystem

PubMed Central

Li, Xinrong; Zhang, Peng; Chen, Yongle

2018-01-01

Soil respiration induced by biological soil crusts (BSCs) is an important process in the carbon (C) cycle in arid and semi-arid ecosystems, where vascular plants are restricted by the harsh environment, particularly the limited soil moisture. However, the interaction between temperature and soil respiration remains uncertain because of the number of factors that control soil respiration, including temperature and soil moisture, especially in BSC-dominated areas. In this study, the soil respiration in moss-dominated crusts and lichen-dominated crusts was continuously measured using an automated soil respiration system over a one-year period from November 2015 to October 2016 in the Shapotou region of the Tengger Desert, northern China. The results indicated that over daily cycles, the half-hourly soil respiration rates in both types of BSC-covered areas were commonly related to the soil temperature. The observed diel hysteresis between the half-hourly soil respiration rates and soil temperature in the BSC-covered areas was limited by nonlinearity loops with semielliptical shapes, and soil temperature often peaked later than the half-hourly soil respiration rates in the BSC-covered areas. The average lag times between the half-hourly soil respiration rates and soil temperature for both types of BSC-covered areas were two hours over the diel cycles, and they were negatively and linearly related to the volumetric soil water content. Our results highlight the diel hysteresis phenomenon that occurs between soil respiration rates and soil temperatures in BSC-covered areas and the negative response of this phenomenon to soil moisture, which may influence total C budget evaluations. Therefore, the interactive effects of soil temperature and moisture on soil respiration in BSC-covered areas should be considered in global carbon cycle models of desert ecosystems. PMID:29624606

Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble

NASA Astrophysics Data System (ADS)

Lorenz, Ruth; Argüeso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Chéruy, Frédérique; Ducharne, Agnès.; Hagemann, Stefan; Meier, Arndt; Milly, P. C. D.; Seneviratne, Sonia I.

2016-01-01

We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.

The Implement of a Multi-layer Frozen Soil Scheme into SSiB3 and its Evaluation over Cold Regions

NASA Astrophysics Data System (ADS)

Li, Q.

2016-12-01

The SSiB3 is a biophysics-based model of land-atmosphere interactions and is designed for global and regional studies. It has three soil layers, three snow layers, as well as one vegetation layer. Soil moisture of the three soil layers, interception water store for the canopy, subsurface soil temperature, ground temperature, canopy temperature and snow water equivalent are all predicted based on the water and energy balance at canopy, soil and snow. SSiB3 substantially enhances the model's capability for cold season studies and produces reasonable results compared with observations. However, frozen soil processes are ignored in the SSiB3 and may have effects on the interannual variability of soil temperature and deep soil memory. A multi-layer comprehensive frozen soil scheme (FSM), which is developed for climate study has been implemented into the SSiB3 to describe soil heat transfer and water flow affected by frozen processed in soil. In the coupled SSiB3-FSM, both liquid water and ice content have been taken into account in the frozen soil hydrologic and thermal property parameterization. The maximum soil layer depth could reach 10 meters thick depending on land conditions. To better evaluate the models' performance, the coupled offline SSiB3-FSM and SSiB3 have been driven from 1948 to 1958 by the Princeton global meteorological data set, respectively. For the 10yrs run, the coupled SSiB3-FSM almost captures the features over different regions, especially cold regions. In order to analysis and compare the differences of SSIB3-FSM and SSIB3 in detail, monthly mean surface temperature for different regions are compared with CAMS data. The statistical results of surface skin temperature show that high latitude regions, Africa, Eastern Australia, and North American monsoon regions have been greatly improved in SSIB3-FSM. For the global statistics, the RMSE of the surface temperature simulated by SSiB3-FSM can be improved about 0.6K compared to SSiB3. In this study, the improvements in the coupled SSiB3-FSM have also been analyzed.

Importance of Soil Temperature for the Growth of Temperate Crops under a Tropical Climate and Functional Role of Soil Microbial Diversity.

PubMed

Sabri, Nurul Syazwani Ahmad; Zakaria, Zuriati; Mohamad, Shaza Eva; Jaafar, A Bakar; Hara, Hirofumi

2018-04-28

A soil cooling system that prepares soil for temperate soil temperatures for the growth of temperate crops under a tropical climate is described herein. Temperate agriculture has been threatened by the negative impact of temperature increases caused by climate change. Soil temperature closely correlates with the growth of temperate crops, and affects plant processes and soil microbial diversity. The present study focuses on the effects of soil temperatures on lettuce growth and soil microbial diversity that maintains the growth of lettuce at low soil temperatures. A model temperate crop, loose leaf lettuce, was grown on eutrophic soil under soil cooling and a number of parameters, such as fresh weight, height, the number of leaves, and root length, were evaluated upon harvest. Under soil cooling, significant differences were observed in the average fresh weight (P<0.05) and positive development of the roots, shoots, and leaves of lettuce. Janthinobacterium (8.142%), Rhodoplanes (1.991%), Arthrospira (1.138%), Flavobacterium (0.857%), Sphingomonas (0.790%), Mycoplana (0.726%), and Pseudomonas (0.688%) were the dominant bacterial genera present in cooled soil. Key soil fungal communities, including Pseudaleuria (18.307%), Phoma (9.968%), Eocronartium (3.527%), Trichosporon (1.791%), and Pyrenochaeta (0.171%), were also recovered from cooled soil. The present results demonstrate that the growth of temperate crops is dependent on soil temperature, which subsequently affects the abundance and diversity of soil microbial communities that maintain the growth of temperate crops at low soil temperatures.

Climate response of the soil nitrogen cycle in three forest types of a headwater Mediterranean catchment

NASA Astrophysics Data System (ADS)

Lupon, Anna; Gerber, Stefan; Sabater, Francesc; Bernal, Susana

2015-05-01

Future changes in climate may affect soil nitrogen (N) transformations, and consequently, plant nutrition and N losses from terrestrial to stream ecosystems. We investigated the response of soil N cycling to changes in soil moisture, soil temperature, and precipitation across three Mediterranean forest types (evergreen oak, beech, and riparian) by fusing a simple process-based model (which included climate modifiers for key soil N processes) with measurements of soil organic N content, mineralization, nitrification, and concentration of ammonium and nitrate. The model describes sources (atmospheric deposition and net N mineralization) and sinks (plant uptake and hydrological losses) of inorganic N from and to the 0-10 cm soil pool as well as net nitrification. For the three forest types, the model successfully recreated the magnitude and temporal pattern of soil N processes and N concentrations (Nash-Sutcliffe coefficient = 0.49-0.96). Changes in soil water availability drove net N mineralization and net nitrification at the oak and beech forests, while temperature and precipitation were the strongest climatic factors for riparian soil N processes. In most cases, net N mineralization and net nitrification showed a different sensitivity to climatic drivers (temperature, soil moisture, and precipitation). Our model suggests that future climate change may have a minimal effect on the soil N cycle of these forests (<10% change in mean annual rates) because positive warming and negative drying effects on the soil N cycle may counterbalance each other.

Improving Soil Moisture and Temperature Profile and Surface Turbulent Fluxes Estimations in Irrigated Field by Assimilating Multi-source Data into Land Surface Model

NASA Astrophysics Data System (ADS)

Chen, Weijing; Huang, Chunlin; Shen, Huanfeng; Wang, Weizhen

2016-04-01

The optimal estimation of hydrothermal conditions in irrigation field is restricted by the deficiency of accurate irrigation information (when and how much to irrigate). However, the accurate estimation of soil moisture and temperature profile and surface turbulent fluxes are crucial to agriculture and water management in irrigated field. In the framework of land surface model, soil temperature is a function of soil moisture - subsurface moisture influences the heat conductivity at the interface of layers and the heat storage in different layers. In addition, soil temperature determines the phase of soil water content with the transformation between frozen and unfrozen. Furthermore, surface temperature affects the partitioning of incoming radiant energy into ground (sensible and latent heat flux), as a consequence changes the delivery of soil moisture and temperature. Given the internal positive interaction lying in these variables, we attempt to retrieve the accurate estimation of soil moisture and temperature profile via assimilating the observations from the surface under unknown irrigation. To resolve the input uncertainty of imprecise irrigation quantity, original EnKS is implemented with inflation and localization (referred to as ESIL) aiming at solving the underestimation of the background error matrix and the extension of observation information from the top soil to the bottom. EnKS applied in this study includes the states in different time points which tightly connect with adjacent ones. However, this kind of relationship gradually vanishes along with the increase of time interval. Thus, the localization is also employed to readjust temporal scale impact between states and filter out redundant or invalid correlation. Considering the parameter uncertainty which easily causes the systematic deviation of model states, two parallel filters are designed to recursively estimate both states and parameters. The study area consists of irrigated farmland and is located in an artificial oasis in the semi-arid region of northwestern China. Land surface temperature (LST) and soil volumetric water content (SVW) at first layer measured at Daman station are taken as observations in the framework of data assimilation. The study demonstrates the feasibility of ESIL in improving the soil moisture and temperature profile under unknown irrigation. ESIL promotes the coefficient correlation with in-situ measurements for soil moisture and temperature at first layer from 0.3421 and 0.7027 (ensemble simulation) to 0.8767 and 0.8304 meanwhile all the RMSE of soil moisture and temperature in deeper layers dramatically decrease more than 40 percent in different degree. To verify the reliability of ESIL in practical application, thereby promoting the utilization of satellite data, we test ESIL with varying observation internal interval and standard deviation. As a consequence, ESIL shows stabilized and promising effectiveness in soil moisture and soil temperature estimation.

Remote measurement of soil moisture over vegetation using infrared temperature measurements

NASA Technical Reports Server (NTRS)

Carlson, Toby N.

1991-01-01

Better methods for remote sensing of surface evapotranspiration, soil moisture, and fractional vegetation cover were developed. The objectives were to: (1) further develop a model of water movement through the soil/plant/atmosphere system; (2) use this model, in conjunction with measurements of infrared surface temperature and vegetation fraction; (3) determine the magnitude of radiometric temperature response to water stress in vegetation; (4) show at what point one can detect that sensitivity to water stress; and (5) determine the practical limits of the methods. A hydrological model that can be used to calculate soil water content versus depth given conventional meteorological records and observations of vegetation cover was developed. An outline of the results of these initiatives is presented.

Climatological temperature senstivity of soil carbon turnover: Observations, simple scaling models, and ESMs

NASA Astrophysics Data System (ADS)

Koven, C. D.; Hugelius, G.; Lawrence, D. M.; Wieder, W. R.

2016-12-01

The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models. To assess the likely long-term response of soils to climate change, spatial gradients in soil carbon turnover times can identify broad-scale and long-term controls on the rate of carbon cycling as a function of climate and other factors. Here we show that the climatological temperature control on carbon turnover in the top meter of global soils is more sensitive in cold climates than in warm ones. We present a simplified model that explains the high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Critically, current Earth system models (ESMs) fail to capture this pattern, however it emerges from an ESM that explicitly resolves vertical gradients in soil climate and turnover. The weak tropical temperature sensitivity emerges from a different model that explicitly resolves mineralogical control on decomposition. These results support projections of strong future carbon-climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behavior.

Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area

NASA Astrophysics Data System (ADS)

Wang, W.; Rinke, A.; Moore, J. C.; Cui, X.; Ji, D.; Li, Q.; Zhang, N.; Wang, C.; Zhang, S.; Lawrence, D. M.; McGuire, A. D.; Zhang, W.; Delire, C.; Koven, C.; Saito, K.; MacDougall, A.; Burke, E.; Decharme, B.

2015-03-01

We perform a land surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP) varies between 6 modern stand-alone land surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic). We also examine the variability in simulated permafrost area and distribution introduced by 5 different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes). There is good agreement (99-135 x 104 km2) between the two diagnostic methods based on air temperature which are also consistent with the best current observation-based estimate of actual permafrost area (101 x 104 km2). However the uncertainty (1-128 x 104 km2) using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index), while permafrost distribution using air temperature based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification and snow cover. Models are particularly poor at simulating permafrost distribution using definition that soil temperature remains at or below 0°C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in permafrost distribution can be made for the Tibetan Plateau.

Evaluating the Impact of Global Warming on Water Balance of Maize by High-precision Controlled Experiment and MLCan model

NASA Astrophysics Data System (ADS)

Ma, Y.; Song, X.; Kumar, P.; Wu, Y.; Woo, D.; Le, P. V.; Ma, C.

2016-12-01

Increased temperature affects the agricultural hydrologic cycle not only by changing precipitation levels, evapotranspiration and the magnitude and timing of run-off, but also by impacting water flows and soil water dynamics. Accurate prediction of hydrologic change under global warming requires high-precision experiment and mathematical model to determine water interaction between interfaces in the soil-plant-atmosphere continuum. In this study, the weighting lysimeter and chamber were coupled to monitor water balance component dynamics of maize under controlled ambient temperature and elevated temperature of 2°C conditions. A mechanistic multilayer canopy-soil-root system model (MLCan) was used to predict hydrologic fluxes variation under different elevated temperature scenarios after calibration with experimental results. The results showed that maize growth period reduced 8 days under increased temperature of 2°C. The mean daily evapotranspiration, soil water storage change, and drainage was 2.66 mm, -2.75 mm, and 0.22 mm under controlled temperature condition, respectively. When temperature was elevated by 2°C, the average daily ET for maize significantly increased about 6.7% (p<0.05). However, there were non-significant impacts of increased temperature on the daily soil water storage change and drainage (p>0.05). Quantification of changes in water balance components induced by temperature increase for maize is critical for optimizing irrigation water management practices and improving water use efficiency.

Weaker soil carbon-climate feedbacks resulting from microbial and abiotic interactions

NASA Astrophysics Data System (ADS)

Tang, Jinyun; Riley, William J.

2015-01-01

The large uncertainty in soil carbon-climate feedback predictions has been attributed to the incorrect parameterization of decomposition temperature sensitivity (Q10; ref. ) and microbial carbon use efficiency. Empirical experiments have found that these parameters vary spatiotemporally, but such variability is not included in current ecosystem models. Here we use a thermodynamically based decomposition model to test the hypothesis that this observed variability arises from interactions between temperature, microbial biogeochemistry, and mineral surface sorptive reactions. We show that because mineral surfaces interact with substrates, enzymes and microbes, both Q10 and microbial carbon use efficiency are hysteretic (so that neither can be represented by a single static function) and the conventional labile and recalcitrant substrate characterization with static temperature sensitivity is flawed. In a 4-K temperature perturbation experiment, our fully dynamic model predicted more variable but weaker soil carbon-climate feedbacks than did the static Q10 and static carbon use efficiency model when forced with yearly, daily and hourly variable temperatures. These results imply that current Earth system models probably overestimate the response of soil carbon stocks to global warming. Future ecosystem models should therefore consider the dynamic interactions between sorptive mineral surfaces, substrates and microbial processes.

Modeling critical zone processes in intensively managed environments

NASA Astrophysics Data System (ADS)

Kumar, Praveen; Le, Phong; Woo, Dong; Yan, Qina

2017-04-01

Processes in the Critical Zone (CZ), which sustain terrestrial life, are tightly coupled across hydrological, physical, biochemical, and many other domains over both short and long timescales. In addition, vegetation acclimation resulting from elevated atmospheric CO2 concentration, along with response to increased temperature and altered rainfall pattern, is expected to result in emergent behaviors in ecologic and hydrologic functions, subsequently controlling CZ processes. We hypothesize that the interplay between micro-topographic variability and these emergent behaviors will shape complex responses of a range of ecosystem dynamics within the CZ. Here, we develop a modeling framework ('Dhara') that explicitly incorporates micro-topographic variability based on lidar topographic data with coupling of multi-layer modeling of the soil-vegetation continuum and 3-D surface-subsurface transport processes to study ecological and biogeochemical dynamics. We further couple a C-N model with a physically based hydro-geomorphologic model to quantify (i) how topographic variability controls the spatial distribution of soil moisture, temperature, and biogeochemical processes, and (ii) how farming activities modify the interaction between soil erosion and soil organic carbon (SOC) dynamics. To address the intensive computational demand from high-resolution modeling at lidar data scale, we use a hybrid CPU-GPU parallel computing architecture run over large supercomputing systems for simulations. Our findings indicate that rising CO2 concentration and air temperature have opposing effects on soil moisture, surface water and ponding in topographic depressions. Further, the relatively higher soil moisture and lower soil temperature contribute to decreased soil microbial activities in the low-lying areas due to anaerobic conditions and reduced temperatures. The decreased microbial relevant processes cause the reduction of nitrification rates, resulting in relatively lower nitrate concentration. Results from geomorphologic model also suggest that soil erosion and deposition plays a dominant role in SOC both above- and below-ground. In addition, tillage can change the amplitude and frequency of C-N oscillation. This work sheds light in developing practical means for reducing soil erosion and carbon loss when the landscape is affected by human activities.

Subgrade stabilization alternatives to lime and cement.

DOT National Transportation Integrated Search

2010-04-15

This project involved four distinct research activities, (1) the influence of temperature on lime-stabilized soils, (2) the influence of temperature on cement-stabilized soils (3) temperature modeling of stabilized subgrade and (4) use of calcium chl...

Simulating soybean canopy temperature as affected by weather variables and soil water potential

NASA Technical Reports Server (NTRS)

Choudhury, B. J.

1982-01-01

Hourly weather data for several clear sky days during summer at Phoenix and Baltimore which covered a wide range of variables were used with a plant atmosphere model to simulate soybean (Glycine max L.) leaf water potential, stomatal resistance and canopy temperature at various soil water potentials. The air and dew point temperatures were found to be the significant weather variables affecting the canopy temperatures. Under identical weather conditions, the model gives a lower canopy temperature for a soybean crop with a higher rooting density. A knowledge of crop rooting density, in addition to air and dew point temperatures is needed in interpreting infrared radiometric observations for soil water status. The observed dependence of stomatal resistance on the vapor pressure deficit and soil water potential is fairly well represented. Analysis of the simulated leaf water potentials indicates overestimation, possibly due to differences in the cultivars.

Soil Moisture Project Evaluation Workshop

NASA Technical Reports Server (NTRS)

Gilbert, R. H. (Editor)

1980-01-01

Approaches planned or being developed for measuring and modeling soil moisture parameters are discussed. Topics cover analysis of spatial variability of soil moisture as a function of terrain; the value of soil moisture information in developing stream flow data; energy/scene interactions; applications of satellite data; verifying soil water budget models; soil water profile/soil temperature profile models; soil moisture sensitivity analysis; combinations of the thermal model and microwave; determing planetary roughness and field roughness; how crust or a soil layer effects microwave return; truck radar; and truck/aircraft radar comparison.

Soil Moisture-Atmosphere Feedbacks on Atmospheric Tracers: The Effects of Soil Moisture on Precipitation and Near-Surface Chemistry

NASA Astrophysics Data System (ADS)

Tawfik, Ahmed B.

The atmospheric component is described by rapid fluctuations in typical state variables, such as temperature and water vapor, on timescales of hours to days and the land component evolves on daily to yearly timescales. This dissertation examines the connection between soil moisture and atmospheric tracers under varying degrees of soil moisture-atmosphere coupling. Land-atmosphere coupling is defined over the United States using a regional climate model. A newly examined soil moisture-precipitation feedback is identified for winter months extending the previous summer feedback to colder temperature climates. This feedback is driven by the freezing and thawing of soil moisture, leading to coupled land-atmosphere conditions near the freezing line. Soil moisture can also affect the composition of the troposphere through modifying biogenic emissions of isoprene (C5H8). A novel first-order Taylor series decomposition indicates that isoprene emissions are jointly driven by temperature and soil moisture in models. These compounds are important precursors for ozone formation, an air pollutant and a short-lived forcing agent for climate. A mechanistic description of commonly observed relationships between ground-level ozone and meteorology is presented using the concept of soil moisture-temperature coupling regimes. The extent of surface drying was found to be a better predictor of ozone concentrations than temperature or humidity for the Eastern U.S. This relationship is evaluated in a coupled regional chemistry-climate model under several land-atmosphere coupling and isoprene emissions cases. The coupled chemistry-climate model can reproduce the observed soil moisture-temperature coupling pattern, yet modeled ozone is insensitive to changes in meteorology due to the balance between isoprene and the primary atmospheric oxidant, the hydroxyl radical (OH). Overall, this work highlights the importance of soil moisture-atmosphere coupling for previously neglected cold climate regimes, controlling isoprene emissions variability, and providing a processed-based description of observed ozone-meteorology relationships. From the perspective of ozone air quality, the lack of sensitivity of ozone to meteorology suggests a systematic deficiency in chemistry models in high isoprene emission regions. This shortcoming must be addressed to better estimate tropospheric ozone radiative forcing and to understanding how ozone air quality may respond to future warming.

Sensitivity of decomposition rates of soil organic matter with respect to simultaneous changes in temperature and moisture

NASA Astrophysics Data System (ADS)

Sierra, Carlos A.; Trumbore, Susan E.; Davidson, Eric A.; Vicca, Sara; Janssens, I.

2015-03-01

The sensitivity of soil organic matter decomposition to global environmental change is a topic of prominent relevance for the global carbon cycle. Decomposition depends on multiple factors that are being altered simultaneously as a result of global environmental change; therefore, it is important to study the sensitivity of the rates of soil organic matter decomposition with respect to multiple and interacting drivers. In this manuscript, we present an analysis of the potential response of decomposition rates to simultaneous changes in temperature and moisture. To address this problem, we first present a theoretical framework to study the sensitivity of soil organic matter decomposition when multiple driving factors change simultaneously. We then apply this framework to models and data at different levels of abstraction: (1) to a mechanistic model that addresses the limitation of enzyme activity by simultaneous effects of temperature and soil water content, the latter controlling substrate supply and oxygen concentration for microbial activity; (2) to different mathematical functions used to represent temperature and moisture effects on decomposition in biogeochemical models. To contrast model predictions at these two levels of organization, we compiled different data sets of observed responses in field and laboratory studies. Then we applied our conceptual framework to: (3) observations of heterotrophic respiration at the ecosystem level; (4) laboratory experiments looking at the response of heterotrophic respiration to independent changes in moisture and temperature; and (5) ecosystem-level experiments manipulating soil temperature and water content simultaneously.

Effect of a controlled burn on the thermophysical properties of a dry soil using a new model of soil heat flow and a new high temperature heat flux sensor

Treesearch

W. J. Massman; J. M. Frank

2004-01-01

Some fires can be beneficial to soils but, if a fire is sufficiently intense, soil can be irreversible altered. We measured soil temperatures and heat fluxes at several soil depths before, during, and after a controlled surface burn at Manitou Experimental Forest (southern Colorado, USA) to evaluate its effects on the soil's thermophysical properties (thermal...

Modelling soil temperature and moisture and corresponding seasonality of photosynthesis and transpiration in a boreal spruce ecosystem

NASA Astrophysics Data System (ADS)

Wu, S. H.; Jansson, P.-E.

2013-02-01

Recovery of photosynthesis and transpiration is strongly restricted by low temperatures in air and/or soil during the transition period from winter to spring in boreal zones. The extent to which air temperature (Ta) and soil temperature (Ts) influence the seasonality of photosynthesis and transpiration of a boreal spruce ecosystem was investigated using a process-based ecosystem model (CoupModel) together with eddy covariance (EC) data from one eddy flux tower and nearby soil measurements at Knottåsen, Sweden. A Monte Carlo-based uncertainty method (GLUE) provided prior and posterior distributions of simulations representing a wide range of soil conditions and performance indicators. The simulated results showed sufficient flexibility to predict the measured cold and warm Ts in the moist and dry plots around the eddy flux tower. Moreover, the model presented a general ability to describe both biotic and abiotic processes for the Norway spruce stand. The dynamics of sensible heat fluxes were well described by the corresponding latent heat fluxes and net ecosystem exchange of CO2. The parameter ranges obtained are probably valid to represent regional characteristics of boreal conifer forests, but were not easy to constrain to a smaller range than that produced by the assumed prior distributions. Finally, neglecting the soil temperature response function resulted in fewer behavioural models and probably more compensatory errors in other response functions for regulating the seasonality of ecosystem fluxes.

Modeling Effects of Temperature, Soil, Moisture, Nutrition and Variety As Determinants of Severity of Pythium Damping-Off and Root Disease in Subterranean Clover

PubMed Central

You, Ming P.; Rensing, Kelly; Renton, Michael; Barbetti, Martin J.

2017-01-01

Subterranean clover (Trifolium subterraneum) is a critical pasture legume in Mediterranean regions of southern Australia and elsewhere, including Mediterranean-type climatic regions in Africa, Asia, Australia, Europe, North America, and South America. Pythium damping-off and root disease caused by Pythium irregulare is a significant threat to subterranean clover in Australia and a study was conducted to define how environmental factors (viz. temperature, soil type, moisture and nutrition) as well as variety, influence the extent of damping-off and root disease as well as subterranean clover productivity under challenge by this pathogen. Relationships were statistically modeled using linear and generalized linear models and boosted regression trees. Modeling found complex relationships between explanatory variables and the extent of Pythium damping-off and root rot. Linear modeling identified high-level (4 or 5-way) significant interactions for each dependent variable (dry shoot and root weight, emergence, tap and lateral root disease index). Furthermore, all explanatory variables (temperature, soil, moisture, nutrition, variety) were found significant as part of some interaction within these models. A significant five-way interaction between all explanatory variables was found for both dry shoot and root dry weights, and a four way interaction between temperature, soil, moisture, and nutrition was found for both tap and lateral root disease index. A second approach to modeling using boosted regression trees provided support for and helped clarify the complex nature of the relationships found in linear models. All explanatory variables showed at least 5% relative influence on each of the five dependent variables. All models indicated differences due to soil type, with the sand-based soil having either higher weights, greater emergence, or lower disease indices; while lowest weights and less emergence, as well as higher disease indices, were found for loam soil and low temperature. There was more severe tap and lateral root rot disease in higher moisture situations. PMID:29184544

Modeling of soil nitrification responses to temperature reveals thermodynamic differences between ammonia-oxidizing activity of archaea and bacteria.

PubMed

Taylor, Anne E; Giguere, Andrew T; Zoebelein, Conor M; Myrold, David D; Bottomley, Peter J

2017-04-01

Soil nitrification potential (NP) activities of ammonia-oxidizing archaea and bacteria (AOA and AOB, respectively) were evaluated across a temperature gradient (4-42 °C) imposed upon eight soils from four different sites in Oregon and modeled with both the macromolecular rate theory and the square root growth models to quantify the thermodynamic responses. There were significant differences in response by the dominant AOA and AOB contributing to the NPs. The optimal temperatures (T opt ) for AOA- and AOB-supported NPs were significantly different (P<0.001), with AOA having T opt >12 °C greater than AOB. The change in heat capacity associated with the temperature dependence of nitrification (ΔC P ‡ ) was correlated with T opt across the eight soils, and the ΔC P ‡ of AOB activity was significantly more negative than that of AOA activity (P<0.01). Model results predicted, and confirmatory experiments showed, a significantly lower minimum temperature (T min ) and different, albeit very similar, maximum temperature (T max ) values for AOB than for AOA activity. The results also suggested that there may be different forms of AOA AMO that are active over different temperature ranges with different T min , but no evidence of multiple T min values within the AOB. Fundamental differences in temperature-influenced properties of nitrification driven by AOA and AOB provides support for the idea that the biochemical processes associated with NH 3 oxidation in AOA and AOB differ thermodynamically from each other, and that also might account for the difficulties encountered in attempting to model the response of nitrification to temperature change in soil environments.

Modeling of soil nitrification responses to temperature reveals thermodynamic differences between ammonia-oxidizing activity of archaea and bacteria

PubMed Central

Taylor, Anne E; Giguere, Andrew T; Zoebelein, Conor M; Myrold, David D; Bottomley, Peter J

2017-01-01

Soil nitrification potential (NP) activities of ammonia-oxidizing archaea and bacteria (AOA and AOB, respectively) were evaluated across a temperature gradient (4–42 °C) imposed upon eight soils from four different sites in Oregon and modeled with both the macromolecular rate theory and the square root growth models to quantify the thermodynamic responses. There were significant differences in response by the dominant AOA and AOB contributing to the NPs. The optimal temperatures (Topt) for AOA- and AOB-supported NPs were significantly different (P<0.001), with AOA having Topt>12 °C greater than AOB. The change in heat capacity associated with the temperature dependence of nitrification (ΔCP‡) was correlated with Topt across the eight soils, and the ΔCP‡ of AOB activity was significantly more negative than that of AOA activity (P<0.01). Model results predicted, and confirmatory experiments showed, a significantly lower minimum temperature (Tmin) and different, albeit very similar, maximum temperature (Tmax) values for AOB than for AOA activity. The results also suggested that there may be different forms of AOA AMO that are active over different temperature ranges with different Tmin, but no evidence of multiple Tmin values within the AOB. Fundamental differences in temperature-influenced properties of nitrification driven by AOA and AOB provides support for the idea that the biochemical processes associated with NH3 oxidation in AOA and AOB differ thermodynamically from each other, and that also might account for the difficulties encountered in attempting to model the response of nitrification to temperature change in soil environments. PMID:27996979

Soil Temperature and Moisture Effects on Soil Respiration and Microbial Community Abundance

DTIC Science & Technology

2015-04-13

highest abundance of bacteria and archaea. Across all soils, if the moisture content was optimal but the temperature was around 5°C, the respiration...9 3.3 Abundance of soil bacteria and archaea ..................................................................... 10 4...ARTEMIS Army Terrestrial-Environmental Modeling and Intelligence System ATCC American Type Culture Collection Ca Calcium CEC Cation Exchange Capacity

A comparison of spatial interpolation methods for soil temperature over a complex topographical region

NASA Astrophysics Data System (ADS)

Wu, Wei; Tang, Xiao-Ping; Ma, Xue-Qing; Liu, Hong-Bin

2016-08-01

Soil temperature variability data provide valuable information on understanding land-surface ecosystem processes and climate change. This study developed and analyzed a spatial dataset of monthly mean soil temperature at a depth of 10 cm over a complex topographical region in southwestern China. The records were measured at 83 stations during the period of 1961-2000. Nine approaches were compared for interpolating soil temperature. The accuracy indicators were root mean square error (RMSE), modelling efficiency (ME), and coefficient of residual mass (CRM). The results indicated that thin plate spline with latitude, longitude, and elevation gave the best performance with RMSE varying between 0.425 and 0.592 °C, ME between 0.895 and 0.947, and CRM between -0.007 and 0.001. A spatial database was developed based on the best model. The dataset showed that larger seasonal changes of soil temperature were from autumn to winter over the region. The northern and eastern areas with hilly and low-middle mountains experienced larger seasonal changes.

Numerical Modeling of Coupled Water Flow and Heat Transport in Soil and Snow

NASA Astrophysics Data System (ADS)

Kelleners, T.

2015-12-01

A numerical model is developed to calculate coupled water flow and heat transport in seasonally frozen soil and snow. Both liquid water flow and water vapor flow are included. The effect of dissolved ions on soil water freezing point depression is included by combining an expression for osmotic head with the Clapeyron equation and the van Genuchten soil water retention function. The coupled water flow and heat transport equations are solved using the Thomas algorithm and Picard iteration. Ice pressure is always assumed zero and frost heave is neglected. The new model is tested using data from a high-elevation rangeland soil that is subject to significant soil freezing and a mountainous forest soil that is snow-covered for about 8 months of the year. Soil hydraulic parameters are mostly based on measurements and only vegetation parameters are fine-tuned to match measured and calculated soil water content, soil & snow temperature, and snow height. Modeling statistics for both systems show good performance for temperature, intermediate performance for snow height, and relatively low performance for soil water content, in accordance with earlier results with an older version of the model.

Temperature Dynamics in Very Shallow Water Bodies: the Role of Heat Fluxes at the Soil-Water Interface

NASA Astrophysics Data System (ADS)

Pivato, M.; Carniello, L.; Silvestri, S.; Marani, M.; Gardner, J.

2016-12-01

Water temperature represents one of the crucial factors driving the ecological processes in water bodies. Many contributions are available in the literature that describe temperature dynamics in deep basins as lakes or seas. Those basins are typically stratified which makes important to represent the vertical profile of the water temperature. Dealing with shallow water bodies, such as rivers, shallow lakes and lagoons, simplifies the problem because the water temperature can be assumed uniform in the water column. Conversely, the heat exchange at the soil-water interface assumes an important role in the water temperature dynamics. Notwithstanding, very few studies and data about this process are available in the literature. In order to provide more insight on the soil contribution to water temperature dynamics, we performed ad hoc field measurements in the Venice lagoon,. We selected a location on a tidal flat in the northern part of the lagoon, close to the Sant'Erasmo Island, where we measured the temperature within the water column and the first 1.5 m of the soil. Data collection started in July 2015 and is still ongoing. We used the data to characterize the heat flux at the water-soil interface in different periods of the year and to develop a "point" model for describing the evolution of the temperature in the water column. The insight on the process provided by the data and by the point model: i) enabled us to determine the soil thermal properties (diffusivity and heat capacity); ii) confirms the uniform profile of the water temperature in the water column; iii) demonstrates that the heat flux at the soil-water interface is comparable with other fluxes at the air-water interface and iv) highlights the important role exerted by advective water fluxes. The latter will be accounted for developing a module for describing the dynamic of the temperature to be coupled with an already existing 2D hydrodynamic model of the Venice lagoon.

Probing soil C metabolism in response to temperature: results from experiments and modeling

NASA Astrophysics Data System (ADS)

Dijkstra, P.; Dalder, J.; Blankinship, J.; Selmants, P. C.; Schwartz, E.; Koch, G. W.; Hart, S.; Hungate, B. A.

2010-12-01

C use efficiency (CUE) is one of the least understood aspects of soil C cycling, has a very large effect on soil respiration and C sequestration, and decreases with elevated temperature. CUE is directly related to substrate partitioning over energy production and biosynthesis. The production of energy and metabolic precursors occurs in well-known processes such as glycolysis and Krebs cycle. We have developed a new stable isotope approach using position-specific 13C-labeled metabolic tracers to measure these fundamental metabolic processes in intact soil communities (1). We use this new approach, combined with models of soil metabolic flux patterns, to analyze the response of microbial energy production, biosynthesis, and CUE to temperature. The method consists of adding small but precise amounts of position-specific 13C -labeled metabolic tracers to parallel soil incubations, in this case 1-13C and 2,3-13C pyruvate and 1-13C and U-13C glucose. The measurement of CO2 released from the labeled tracers is used to calculate the C flux rates through various metabolic pathways. A simplified metabolic model consisting of 23 reactions is iteratively solved using results of the metabolic tracer experiments and information on microbial precursor demand under different temperatures. This new method enables direct study of fundamental aspects of microbial energy production, C use efficiency, and soil organic matter formation in response to temperature. (1) Dijkstra P, Blankinship JC, Selmants PC, Hart SC, Koch GW, Schwarz E and Hungate BA. Probing metabolic flux patterns of soil microbial communities using parallel position-specific tracer labeling. Soil Biology and Biochemistry (accepted)

Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble

USGS Publications Warehouse

Lorenz, Ruth; Argueso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Cheruy, Frederique; Ducharne, Agnes; Hagemann, Stefan; Meier, Arndt; Milly, Paul C.D.; Seneviratne, Sonia I

2016-01-01

We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.

Flow pathways in the Slapton Wood catchment using temperature as a tracer

NASA Astrophysics Data System (ADS)

Birkinshaw, Stephen J.; Webb, Bruce

2010-03-01

SummaryThis study investigates the potential of temperature as a tracer to provide insights into flow pathways. The approach couples fieldwork and modelling experiments for the Eastergrounds Hollow within the Slapton Wood catchment, South Devon, UK. Measurements in the Eastergrounds Hollow were carried out for soil temperature, spring temperature, and the stream temperature and use was made of an existing 1989-1991 data set for the entire Slapton Wood catchment. The predominant flow in this hollow is a result of subsurface stormflow, and previous work has suggested that the water flows vertically down through the soil and then subsurface stormflow occurs at the soil/bedrock interface where the water is deflected laterally. The depth of the subsurface stormflow was previously thought to be around 2.2 m. However, analysis of the new spring, stream and soil temperature data suggests a deeper pathway for the subsurface stormflow. Modelling of water flow and heat transport was carried out using SHETRAN and this was calibrated to reproduce the water flow in the entire Slapton Wood catchment and soil temperatures in the Eastergrounds Hollow. The model was tested for the entire Eastergrounds Hollow with two different soil depths. A depth of 2.2 m, based on previous knowledge, was unable to reproduce the Eastergrounds spring temperature. A depth of 3.7 m produced an excellent comparison between measured and simulated stream and spring temperatures in the Eastergrounds Hollow. This work suggests that the depth of the flow pathways that produce the subsurface stormflow are deeper than previously thought. It also provides a demonstration on the use of temperature as a tracer to understand flow pathways.

A Comparison of Arrhenius and Macromolecular Rate Theory for Predicting Temperature Responses of Soil CO2 Production

NASA Astrophysics Data System (ADS)

Alster, C. J.; Koyama, A.; Johnson, N. G.; von Fischer, J.

2015-12-01

Soil microbes catalyze many key ecosystem functions, including soil respiration, and are thus important for understanding global carbon cycles and other biogeochemical cycles. One important component in predicting rates of respiration is determining how microbial communities respond to temperature. A range of models have been developed for determining temperature sensitivity of soil biological activities, most of which are based on the Arrhenius equation. This equation predicts an exponential increase in rate with temperature, despite field and laboratory results suggesting a temperature optimum below the denaturation point. Recently, Schipper et al. (2014) developed a novel theory, Macromolecular Rate Theory (MMRT), which explains this trend due to heat capacity (CP) changes associated with enzymes. We applied MMRT to respiration data collected using a reciprocal transplant design with soils from three different sites across the U.S. Great Plains to isolate the effects of microbial community type from edaphic factors. We found that MMRT provided a better fit to the data than Arrhenius in 8 out of the 9 soil x inocula combinations. Our analysis revealed that the microbial communities have distinct CP values largely independent of soil type. These results have significant implications for fundamental understanding of microbial enzyme dynamics in soils as well as for ecosystem and global carbon modeling.

X-Ray Fluorescence to Estimate the Maximum Temperature Reached at Soil Surface during Experimental Slash-and-Burn Fires.

PubMed

Melquiades, Fábio L; Thomaz, Edivaldo L

2016-05-01

An important aspect for the evaluation of fire effects in slash-and-burn agricultural system, as well as in wildfire, is the soil burn severity. The objective of this study is to estimate the maximum temperature reached in real soil burn events using energy dispersive X-ray fluorescence (EDXRF) as an analytical tool, combined with partial least square (PLS) regression. Muffle-heated soil samples were used for PLS regression model calibration and two real slash-and-burn soils were tested as external samples in the model. It was possible to associate EDXRF spectra alterations to the maximum temperature reached in the heat affected soils with about 17% relative standard deviation. The results are promising since the analysis is fast, nondestructive, and conducted after the burn event, although local calibration for each type of burned soil is necessary. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Application of the two-source energy balance model to partition evapotranspiration in an arid wine vineyard

NASA Astrophysics Data System (ADS)

Kool, Dilia; Kustas, William P.; Agam, Nurit

2016-04-01

The partitioning of evapotranspiration (ET) into transpiration (T), a productive water use, and soil water evaporation (E), which is generally considered a water loss, is highly relevant to agriculture in the light of increasing desertification and water scarcity. This task is challenged by the complexity of soil and plant interactions, coupled with changes in atmospheric and soil water content conditions. Many of the processes controlling water/energy exchange are not adequately modeled. The two-source energy balance model (TSEB) was evaluated and adapted for independent E and T estimations in an isolated drip-irrigated wine vineyard in the arid Negev desert. The TSEB model estimates ET by computing vegetation and soil energy fluxes using remotely sensed composite surface temperature, local weather data (solar radiation, air temperature and humidity, and wind speed), and vegetation metrics (row spacing, canopy height and width, and leaf area). The soil and vegetation energy fluxes are computed numerically using a system of temperature gradient and resistance equations; where soil and canopy temperatures are derived from the composite surface temperature. For estimation of ET, the TSEB model has been shown to perform well for various agricultural crops under a wide range of environmental conditions, but validation of T and E fluxes is limited to one study in a well-watered cotton crop. Extending the TSEB approach to water-limited vineyards demands careful consideration regarding how the complex canopy structure of vineyards will influence the accuracy of the partitioning between E and T. Data for evaluation of the TSEB model were collected over a season (bud break till harvest). Composite, canopy, and soil surface temperatures were measured using infrared thermometers. The composite vegetation and soil surface energy fluxes were assessed using independent measurements of net radiation, and soil, sensible and latent heat flux. The below canopy energy balance was assessed at the dry midrow position as well as the wet irrigated position directly underneath the vine row, where net radiation and soil heat flux were measured, sensible heat flux was computed indirectly, and E was calculated as the residual. While the below canopy energy balance approach used in this study allowed continuous assessment of E at daily intervals, instantaneous E fluxes could not be assessed due to vertical variability in shading below the canopy. Seasonal partitioning indicated that total E amounted to 9-11% of ET. Initial evaluation of the TSEB model indicated that discrepancies between modeled and measured fluxes can largely be attributed to net radiation partitioning. In addition, large diurnal variation at the soil surface requires adaptation of the soil heat flux formulations. Improved estimation of energy fluxes by accounting for the relatively complex canopy structure of vineyards will be highlighted.

Temperature effect on mineralization of SOM, plant litter and priming: modified by soil type?

NASA Astrophysics Data System (ADS)

Azzaroli Bleken, Marina; Berland Frøseth, Randi

2015-04-01

The purpose of this study was to provide improved temperature response functions to be used in models of soil organic carbon (SOC) and litter mineralization, with focus on the winter period. Our working hypothesis were: 1) decomposition of SOM and plant residue occurs also at temperature close to the freezing point; 2) the effect of temperature on SOC decomposition is stronger in clayey than in sandy soil; 3) decomposition and response to temperature of added plant litter is not affected by soil type. A silty clay loam (27% clay, 3% sand) and a sandy loam (6% clay, 51% sand) with similar weather and cultivation history were pre-incubated at about 15° C for about 4.5 months. Clover leaves labelled with 13C were added to half of the samples, and soil with and without clover was incubated for 142 days at 0, 4, 8.5 or 15 °C. Mineralization of SOC and clover leaves was observed also at 0° C. In the absence of added plant material, SOC decomposition followed a first order reaction which was twice as fast in the sandy soil as in the clay soil. The decomposition rate of clover leaves was also higher in the sandy soil than in the clay soil. However, the influence of temperature on SOC and on clover decomposition was the same in both soils. In presence of plant material, there was a positive priming effect on SOC, which initially correlated with decomposition of plant litter. There was a progressively lower priming effect at higher temperatures, particularly in the sandy soil, that could be understood as substrates exhaustion in a restricted volume of influence around the added clover leaves. We provide parameterised Arrhenius and alternative modifying linear temperature functions together with decay rates at reference temperature, which can be used for predicting decay rates of SOC per se and of the labile pool of clover leaves. We also show the superiority of these functions compared to the use of Q10 as temperature factor. Further, we suggest approaches for modelling the priming effect caused by plant litter. Reference: Frøseth RB, Bleken MA(2015) Effect of low temperature and soil type on the decomposition rate of soil organic carbon and clover leaves, and related priming effect. Soil Biology and Biochemistry 80:156-166.

Modelling in situ enzyme potential of soils: a tool to predict soil respiration from agricultural fields

NASA Astrophysics Data System (ADS)

Shahbaz Ali, Rana; Poll, Christian; Demyan, Scott; Nkwain Funkuin, Yvonne; Ingwersen, Joachim; Wizemann, Hans-Dieter; Kandeler, Ellen

2014-05-01

The fate of soil organic carbon (SOC) is one of the largest uncertainties in predicting future climate and terrestrial ecosystem functions. Extra-cellular enzymes, produced by microorganisms, perform the very first step in SOC degradation and serve as key components in global carbon cycling. Very little information is available about the seasonal variation in the temperature sensitivity of soil enzymes. Here we aim to model in situ enzyme potentials involved in the degradation of either labile or recalcitrant organic compounds to understand the temporal variability of degradation processes. To identify the similarities in seasonal patterns of soil respiration and in situ enzyme potentials, we compared the modelled in situ enzyme activities with weekly measured soil CO2 emissions. Arable soil samples from two different treatments (4 years fallow and currently vegetated plots; treatments represent range of carbon input into soil) were collected every month from April, 2012 to April, 2013, from two different study regions (Kraichgau and Swabian Alb) in Southwest Germany. The vegetation plots were under crop rotation in both study areas. We measured activities of three enzymes including β-glucosidase, xylanase and phenoloxidase at five different temperatures. We also measured soil microbial biomass in form of microbial carbon (Cmic). Land-use and area had significant effects (P < 0.001) on the microbial biomass; fallow plots having less Cmic than vegetation plots. Potential activities of β-glucosidase (P < 0.001) and xylanase (P < 0.01) were significantly higher in the vegetation plots of the Swabian Alb region than in the Kraichgau region. In both study areas, enzyme activities were higher during vegetation period and lower during winter which points to the importance of carbon input and/or temperature and soil moisture. We calculated the temperature sensitivity (Q10) of enzyme activities based on laboratory measurements of enzyme activities at a range of incubation temperatures. Q10 of β-glucosidase activity changed significantly across the year (Q10 values ranges from 1.5 to 2.0 in Kraichgau and 1.6 to 2.1 in Swabian Alb), while for xylanase activity, no significant effects were found (Q10 values ranges from 1.2 to 3.0 in Kraichgau and 1.3 to 3.3 in Swabian Alb) in both study regions. By using laboratory based enzyme activities, calculated Q10 values, and daily soil temperature data, we modelled in situ enzyme potentials in soils for labile and recalcitrant carbon pools for both study regions. We observed an increase in modelled in situ enzyme activities during the summer period and a substantial decrease during winter indicating temperature as a strong controlling factor. A significant higher positive correlation of soil surface CO2 flux with modelled in situ β-glucosidase activity was found in both study regions compared to modelled in situ xylanase activity. These results demonstrate that (1) Q10 values are site and season specific and should be added into carbon models and (2) the indication of the relevance of greater contribution of labile carbon pool to soil CO2 emissions.

Calibration of soil moisture flow simulation models aided by the active heated fiber optic distributed temperature sensing AHFO

NASA Astrophysics Data System (ADS)

Rodriguez-Sinobas, Leonor; Zubelzu, Sergio; Sobrino, Fernando Fernando; Sánchez, Raúl

2017-04-01

Most of the studies dealing with the development of water flow simulation models in soils, are calibrated using experimental data measured by soil probe sensors or tensiometers which locate at specific points in the study area. However since the beginning of the XXI century, the use of Distributed Fiber Optic Temperature Measurement for estimating temperature variation along a cable of fiber optic has been assessed in multiple environmental applications. Recently, its application combined with an active heating pulses technique (AHFO) has been reported as a sensor to estimate soil moisture. This method applies a known amount of heat to the soil and monitors the temperature evolution, which mainly depends on the soil moisture content. Thus, it allows estimations of soil water content every 12.5 cm along the fiber optic cable, as long as 1500 m , with 2 % accuracy , every second. This study presents the calibration of a soil water flow model (developed in Hydrus 2D) with the AHFO technique. The model predicts the distribution of soil water content of a green area irrigated by sprinkler irrigation. Several irrigation events have been evaluated in a green area located at the ETSI Agronómica, Agroalimentaria y Biosistemas in Madrid where an installation of 147 m of fiber optic cable at 15 cm depth is deployed. The Distribute Temperature Sensing unit was a SILIXA ULTIMA SR (Silixa Ltd, UK) and has spatial and temporal resolution of 0.29 m. Data logged in the DTS unit before, during and after the irrigation event were used to calibrate the estimations in the Hydrus 2D model during the infiltration and redistribution of soil water content within the irrigation interval. References: Karandish, F., & Šimůnek, J. (2016). A field-modeling study for assessing temporal variations of soil-water-crop interactions under water-saving irrigation strategies. Agricultural Water Management, 178, 291-303. Li, Y., Šimůnek, J., Jing, L., Zhang, Z., & Ni, L. (2014). Evaluation of water movement and water losses in a direct-seeded-rice field experiment using Hydrus-1D. Agricultural Water Management, 142, 38-46. Tan, X., Shao, D., & Liu, H. (2014). Simulating soil water regime in lowland paddy fields under different water managements using HYDRUS-1D. Agricultural Water Management, 132, 69-78.

A dynamic organic soil biogeochemical model for simulating the effects of wildfire on soil environmental conditions and carbon dynamics of black spruce forests

Treesearch

Shuhua Yi; A. David McGuire; Eric Kasischke; Jennifer Harden; Kristen Manies; Michelle Mack; Merritt Turetsky

2010-01-01

Ecosystem models have not comprehensively considered how interactions among fire disturbance, soil environmental conditions, and biogeochemical processes affect ecosystem dynamics in boreal forest ecosystems. In this study, we implemented a dynamic organic soil structure in the Terrestrial Ecosystem Model (DOS-TEM) to investigate the effects of fire on soil temperature...

A weighting lysimeter for a laboratory experiment on water and energy fluxes measurements and hydrological models verification

NASA Astrophysics Data System (ADS)

Corbari, Chiara; paleari, roberto; mantovani, federico; tarro, stefano; mancini, marco

2017-04-01

Weighting lysimeters allow a direct measurement of water loss from the soil, determining the soil water balance, and thus providing an interesting tool to validate hydrological models. Lysimeters, which world originates from the greek words "lysis" (movement) and "metron" (to measure) have been used to measure percolation of water through the soils for over 300 years. The aim of this study is twofold: 1) to perform water and energy flux measurements under different meteorological conditions, irrigation practice (surface flood, drip and groundwater capillary rise), and soil coverage (bare soil and basil crop), 2) to verify hydrological model FEST-EWB parameterization at the lysimeter scale. A weighting lysimeter has been constructed in the Hydraulic Laboratory of Politecnico di Milano. It consists of a steel box of 1.5 x 1.5 x 1 m containing reconstructed soil. The box is mounted on a scale with four load cells with a nominal weight of 6000 kg and a precision of 0,5 kg. The lysimeter is fully instrumented to measure all the main components of the hydrological cycle. Profiles of soil moisture and temperature are provided by 7 probes; ground heat flux is measured by a heat flux plate and two thermocouples; the drainage flux is measured by a tipping bucket rain gauge; the four components of radiation are provided by a net radiometer; air temperature and humidity are measured by a thermo-hygrometer. Data are collected every 10 minutes on a datalogger. A thermal camera is also installed to provide accurate maps of land surface temperature. The different instruments have been subjected to a rigorous calibration process. A low cost station is also installed based on an Arduino micro-controller measuring soil moisture and temperature, air humidity and temperature and solar radiation. The idea is to understand whether low cost instruments can be used to monitor the fundamental hydrological variables. The measured fluxes (e.g. evapotranspiration, soil moisture, land surface temperature) are then used to verify the correctness of the hydrological model FEST-EWB parameterization. A general good accuracy of 2-6 % between observed and modeled fluxes is obtained.

High Temperature and Salinity Enhance Soil Nitrogen Mineralization in a Tidal Freshwater Marsh

PubMed Central

Gao, Haifeng; Bai, Junhong; He, Xinhua; Zhao, Qingqing; Lu, Qiongqiong; Wang, Junjing

2014-01-01

Soil nitrogen (N) mineralization in wetlands is sensitive to various environmental factors. To compare the effects of salinity and temperature on N mineralization, wetland soils from a tidal freshwater marsh locating in the Yellow River Delta was incubated over a 48-d anaerobic incubation period under four salinity concentrations (0, 10, 20 and 35‰) and four temperature levels (10, 20, 30 and 40°C). The results suggested that accumulated ammonium nitrogen (NH4 +-N) increased with increasing incubation time under all salinity concentrations. Higher temperatures and salinities significantly enhanced soil N mineralization except for a short-term (≈10 days) inhibiting effect found under 35‰ salinity. The incubation time, temperature, salinity and their interactions exhibited significant effects on N mineralization (P<0.001) except the interactive effect of salinity and temperature (P>0.05), while temperature exhibited the greatest effect (P<0.001). Meanwhile, N mineralization processes were simulated using both an effective accumulated temperature model and a one-pool model. Both models fit well with the simulation of soil N mineralization process in the coastal freshwater wetlands under a range of 30 to 40°C (R2 = 0.88–0.99, P<0.01). Our results indicated that an enhanced NH4 +-N release with increasing temperature and salinity deriving from the projected global warming could have profound effects on nutrient cycling in coastal wetland ecosystems. PMID:24733366

Modelling Soil Heat and Water Flow as a Coupled Process in Land Surface Models

NASA Astrophysics Data System (ADS)

García González, Raquel; Verhoef, Anne; Vidale, Pier Luigi; Braud, Isabelle

2010-05-01

To improve model estimates of soil water and heat flow by land surface models (LSMs), in particular in the first few centimetres of the near-surface soil profile, we have to consider in detail all the relevant physical processes involved (see e.g. Milly, 1982). Often, thermal and iso-thermal vapour fluxes in LSMs are neglected and the simplified Richard's equation is used as a result. Vapour transfer may affect the water fluxes and heat transfer in LSMs used for hydrometeorological and climate simulations. Processes occurring in the top 50 cm soil may be relevant for water and heat flux dynamics in the deeper layers, as well as for estimates of evapotranspiration and heterotrophic respiration, or even for climate and weather predictions. Water vapour transfer, which was not incorporated in previous versions of the MOSES/JULES model (Joint UK Land Environment Simulator; Cox et al., 1999), has now been implemented. Furthermore, we also assessed the effect of the soil vertical resolution on the simulated soil moisture and temperature profiles and the effect of the processes occurring at the upper boundary, mainly in terms of infiltration rates and evapotranspiration. SiSPAT (Simple Soil Plant Atmosphere Transfer Model; Braud et al., 1995) was initially used to quantify the changes that we expect to find when we introduce vapour transfer in JULES, involving parameters such as thermal vapour conductivity and diffusivity. Also, this approach allows us to compare JULES to a more complete and complex numerical model. Water vapour flux varied with soil texture, depth and soil moisture content, but overall our results suggested that water vapour fluxes change temperature gradients in the entire soil profile and introduce an overall surface cooling effect. Increasing the resolution smoothed and reduced temperature differences between liquid (L) and liquid/vapour (LV) simulations at all depths, and introduced a temperature increase over the entire soil profile. Thermal gradients rather than soil water potential gradients seem to cause temporal and spatial (vertical) soil temperature variability. We conclude that a multi-soil layer configuration may improve soil water dynamics, heat transfer and coupling of these processes, as well as evapotranspiration estimates and land surface-atmosphere coupling. However, a compromise should be reached between numerical and process-simulation aspects. References: Braud I., A.C. Dantas-Antonino, M. Vauclin, J.L. Thony and P. Ruelle, 1995b: A Simple Soil Plant Atmo- sphere Transfer model (SiSPAT), Development and field verification, J. Hydrol, 166: 213-250 Cox, P.M., R.A. Betts, C.B. Bunton, R.L.H. Essery, P.R. Rowntree, and J. Smith (1999), The impact of new land surface physics on the GCM simulation of climate and climate sensitivity. Clim. Dyn., 15, 183-203. Milly, P.C.D., 1982. Moisture and heat transport in hysteric inhomogeneous porous media: a matric head- based formulation and a numerical model, Water Resour. Res., 18:489-498

Incorporating an enzymatic model of effects of temperature, moisture, and substrate supply on soil respiration into an ecosystem model for two forests of northeastern USA

NASA Astrophysics Data System (ADS)

Sihi, Debjani; Davidson, Eric; Chen, Min; Savage, Kathleen; Richardson, Andrew; Keenan, Trevor; Hollinger, David

2017-04-01

Soils represent the largest terrestrial carbon (C) pool, and microbial decomposition of soil organic matter (SOM) to carbon dioxide, also called heterotrophic respiration (Rh), is an important component of the global C cycle. Temperature sensitivity of Rh is often represented with a simple Q10 function in ecosystem models and earth system models (ESMs), sometimes accompanied by an empirical soil moisture modifier. More explicit representation of the effects of soil moisture, substrate supply, and their interactions with temperature has been proposed to disentangle the confounding factors of apparent temperature sensitivity of SOM decomposition and improve performance of ecosystem models and ESMs. The objective of this work was to incorporate into an ecosystem model a more mechanistic, but still parsimonious, model of environmental factors controlling Rh. The Dual Arrhenius and Michaelis-Menten (DAMM) model simulates Rh using Michaelis-Menten, Arrhenius, and diffusion functions. Soil moisture affects Rh and its apparent temperature sensitivity in DAMM by regulating the diffusion of oxygen and soluble carbon substrates to the enzymatic reaction site. However, in its current configuration, DAMM depends on assumptions or inputs from other models regarding soil C inputs. Here we merged the DAMM soil flux model with a parsimonious ecosystem flux model, FöBAAR (Forest Biomass, Assimilation, Allocation and Respiration) by replacing FöBAAR's algorithms for Rh with those of DAMM. Classical root trenching experiments provided data to partition soil CO2 efflux into Rh (trenched plot) and root respiration (untrenched minus trenched plots). We used three years of high-frequency soil flux data from automated soil chambers (trenched and untrenched plots) and landscape-scale ecosystem fluxes from eddy covariance towers from two mid-latitude forests (Harvard Forest, MA and Howland Forest, ME) of northeastern USA to develop and validate the merged model and to quantify the uncertainties in a multiple constraints approach. The optimized DAMM-FöBAAR model better captured the seasonal dynamics of Rh compared to the FöBAAR-only model for the Harvard Forest, as indicated by lower cost functions (model-data mismatch). However, DAMM-FöBAAR showed less improvement over FöBAAR-only for the boreal transition forest at Howland. The frequency of droughts is lower at Howland, due to a shallow water table, resulting in only brief water limitation affecting Rh in some years. At both sites, the declining trend of soil respiration during drought episodes was captured by the DAMM-FöBAAR model, but not the FöBAAR-only model, which simulates Rh using only a Q10 type function. Greater confidence in model prediction resulting from the inclusion of mechanistic simulation of moisture limitation on substrate availability, an emergent property of DAMM, depends on site conditions, climate, and the temporal scale of interest. While the DAMM functions require a few more parameters than a simple Q10 function, we have demonstrated that they can be included in an ecosystem model and reduce the cost function. Moreover, the mechanistic structure of the soil moisture effects using DAMM functions should be more generalizable than other commonly used empirical functions.

Global Soil Moisture Estimation from L-Band Satellite Data: The Impact of Radiative Transfer Modeling in Assimilation and Retrieval Systems

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle; Reichle, Rolf; Gruber, Alexander; Bechtold, Michel; Quets, Jan; Vrugt, Jasper; Wigneron, Jean-Pierre

2018-01-01

The SMOS and SMAP missions have collected a wealth of global L-band Brightness temperature (Tb) observations. The retrieval of surface Soil moisture estimates, and the estimation of other geophysical Variables, such as root-zone soil moisture and temperature, via data Assimilation into land surface models largely depends on accurate Radiative transfer modeling (RTM). This presentation will focus on various configuration aspects of the RTM (i) for the inversion of SMOS Tb to surface soil moisture, and (ii) for the forward modeling as part of a SMOS Tb data assimilation System to estimate a consistent set of geophysical land surface Variables, using the GEOS-5 Catchment Land Surface Model.

Testing of two source energy balance model under irrigated and dryland conditions using high resolution airborne imagery

USDA-ARS?s Scientific Manuscript database

Two Source Model (TSM) calculates the heat and water exchange and interaction between soil-atmosphere and vegetation-atmosphere separately. This is achieved through decomposition of radiometric surface temperature to soil and vegetation component temperatures either from multi-angular remotely sense...

Role of the Soil Thermal Inertia in the short term variability of the surface temperature and consequences for the soil-moisture temperature feedback

NASA Astrophysics Data System (ADS)

Cheruy, Frederique; Dufresne, Jean-Louis; Ait Mesbah, Sonia; Grandpeix, Jean-Yves; Wang, Fuxing

2017-04-01

A simple model based on the surface energy budget at equilibrium is developed to compute the sensitivity of the climatological mean daily temperature and diurnal amplitude to the soil thermal inertia. It gives a conceptual framework to quantity the role of the atmospheric and land surface processes in the surface temperature variability and relies on the diurnal amplitude of the net surface radiation, the sensitivity of the turbulent fluxes to the surface temperature and the thermal inertia. The performances of the model are first evaluated with 3D numerical simulations performed with the atmospheric (LMDZ) and land surface (ORCHIDEE) modules of the Institut Pierre Simon Laplace (IPSL) climate model. A nudging approach is adopted, it prevents from using time-consuming long-term simulations required to account for the natural variability of the climate and allow to draw conclusion based on short-term (several years) simulations. In the moist regions the diurnal amplitude and the mean surface temperature are controlled by the latent heat flux. In the dry areas, the relevant role of the stability of the boundary layer and of the soil thermal inertia is demonstrated. In these regions, the sensitivity of the surface temperature to the thermal inertia is high, due to the high contribution of the thermal flux to the energy budget. At high latitudes, when the sensitivity of turbulent fluxes is dominated by the day-time sensitivity of the sensible heat flux to the surface temperature and when this later is comparable to the thermal inertia term of the sensitivity equation, the surface temperature is also partially controlled by the thermal inertia which can rely on the snow properties; In the regions where the latent heat flux exhibits a high day-to-day variability, such as transition regions, the thermal inertia has also significant impact on the surface temperature variability . In these not too wet (energy limited) and not too dry (moisture-limited) soil moisture (SM) ''hot spots'', it is generally admitted that the variability of the surface temperature is explained by the soil moisture trough its control on the evaporation. This work suggests that the impact of the soil moisture on the temperature through its impact on the thermal inertia can be as important as its direct impact on the evaporation. Contrarily to the evaporation related soil-moisture temperature negative feedback, the thermal inertia soil-moisture related feedback newly identified by this work is a positive feedback which limits the cooling when the soil moisture increases. These results suggest that uncertainties in the representation of the soil and snow thermal properties can be responsible of significant biases in numerical simulations and emphasize the need to carefully document and evaluate these quantities in the Land Surface Modules implemented in the climate models.

Soil biological activity at European scale - two calculation concepts

NASA Astrophysics Data System (ADS)

Krüger, Janine; Rühlmann, Jörg

2014-05-01

The CATCH-C project aims to identify and improve the farm-compatibility of Soil Management Practices including to promote productivity, climate change mitigation and soil quality. The focus of this work concentrates on turnover conditions for soil organic matter (SOM). SOM is fundamental for the maintenance of quality and functions of soils while SOM storage is attributed a great importance in terms of climate change mitigation. The turnover conditions depend on soil biological activity characterized by climate and soil properties. To assess the turnover conditions two model concepts are applied: (I) Biological active time (BAT) regression approach derived from CANDY model (Franko & Oelschlägel 1995) expresses the variation of air temperature, precipitation and soil texture as a timescale and an indicator of biological activity for soil organic matter (SOM) turnover. (II) Re_clim parameter within the Introductory Carbon Balance Model (Andrén & Kätterer 1997) states the soil temperature and soil water to estimate soil biological activity. The modelling includes two strategies to cover the European scale and conditions. BAT was calculated on a 20x20 km grid basis. The European data sets of precipitation and air temperature (time period 1901-2000, monthly resolution), (Mitchell et al. 2004) were used to derive long-term averages. As we focus on agricultural areas we included CORINE data (2006) to extract arable land. The resulting BATs under co-consideration of the main soil textures (clay, silt, sand and loam) were investigated per environmental zone (ENZs, Metzger et al. 2005) that represents similar conditions for precipitation, temperature and relief to identify BAT ranges and hence turnover conditions for each ENZ. Re_clim was quantified by climatic time series of more than 250 weather stations across Europe presented by Klein Tank et al. (2002). Daily temperature, precipitation and potential evapotranspiration (maximal thermal extent) were used to calculate soil temperature and water storage in the arable layer thereby differentiating soil textures exclusively in main types (clay, silt, sand and loam). Similar to the BAT investigation it was of further interest to investigate how the re_clim parameter range behaves per ENZ. We will discuss the analyzed results of both strategies in a comparative manner to assess SOM turnover conditions across Europe. Both concepts help to separate different turnover activities and to indicate organic matter input in order to maintain the given SOM. The assessment could provide local recommendations for local adaptations of soil management practices. CATCH-C is funded within the 7th Framework Programme for Research, Technological Development and Demonstration, Theme 2 - Biotechnologies, Agriculture & Food (Grant Agreement N° 289782).

Lessons from simultaneous measurements of soil respiration and net ecosystem exchange of CO2 in temperate forests

NASA Astrophysics Data System (ADS)

Renchon, A.; Pendall, E.

2017-12-01

Land-surface exchanges of CO2 play a key role in ameliorating or exacerbating climate change. The eddy-covariance method allows direct measurement of net ecosystem-atmosphere exchange of CO2 (NEE), but partitioning daytime NEE into its components - gross primary productivity (GPP) and ecosystem respiration (RE) - remains challenging. Continuous measurements of soil respiration (RS), along with flux towers, have the potential to better constrain data and models of RE and GPP. We use simultaneous half-hourly NEE and RS data to: (1) compare the short-term (fortnightly) apparent temperature sensitivity (Q10) of nighttime RS and RE; (2) assess whether daytime RS can be estimated using nighttime response functions; and (3) compare the long-term (annual) responses of nighttime RS and nighttime RE to interacting soil moisture and soil temperature. We found that nighttime RS has a lower short-term Q10 than nighttime RE. This suggests that the Q10 of nighttime RE is strongly influenced by the Q10 of nighttime above-ground respiration, or possibly by a bias in RE measurements. The short-term Q10 of RS and RE decreased with increasing temperature. In general, daytime RS could be estimated using nighttime RS temperature and soil moisture (r2 = 0.9). However, this results from little to no diurnal variation in RS, and estimating daytime RS as the average of nighttime RS gave similar results (r2 = 0.9). Furthermore, we observed a day-night hysteresis of RS response to temperature, especially when using air temperature and sometimes when using soil temperature at 5cm depth. In fact, during some months, soil respiration observations were lower during daytime compared to nighttime, despite higher temperature in daytime. Therefore, daytime RS modelled from nighttime RS temperature response was overestimated during these periods. RS and RE responses to the combination of soil moisture and soil temperature were similar, and consistent with the DAMM model of soil-C decomposition. These findings underscore the value of continuous measurements of RS in flux tower footprints. Findings are also relevant to recent research on light inhibition of leaf respiration and contribute to improved understanding of ecosystem carbon cycle - climate feedback processes.

Some effects of topography, soil moisture, and sea-surface temperature on continental precipitation as computed with the GISS coarse mesh climate model

NASA Technical Reports Server (NTRS)

Spar, J.; Cohen, C.

1981-01-01

The effects of terrain elevation, soil moisture, and zonal variations in sea/surface temperature on the mean daily precipitation rates over Australia, Africa, and South America in January were evaluated. It is suggested that evaporation of soil moisture may either increase or decrease the model generated precipitation, depending on the surface albedo. It was found that a flat, dry continent model best simulates the January rainfall over Australia and South America, while over Africa the simulation is improved by the inclusion of surface physics, specifically soil moisture and albedo variations.

[Soil moisture estimation method based on both ground-based remote sensing data and air temperature in a summer maize ecosystem.

PubMed

Wang, Min Zheng; Zhou, Guang Sheng

2016-06-01

Soil moisture is an important component of the soil-vegetation-atmosphere continuum (SPAC). It is a key factor to determine the water status of terrestrial ecosystems, and is also the main source of water supply for crops. In order to estimate soil moisture at different soil depths at a station scale, based on the energy balance equation and the water deficit index (WDI), a soil moisture estimation model was established in terms of the remote sensing data (the normalized difference vegetation index and surface temperature) and air temperature. The soil moisture estimation model was validated based on the data from the drought process experiment of summer maize (Zea mays) responding to different irrigation treatments carried out during 2014 at Gucheng eco-agrometeorological experimental station of China Meteorological Administration. The results indicated that the soil moisture estimation model developed in this paper was able to evaluate soil relative humidity at different soil depths in the summer maize field, and the hypothesis was reasonable that evapotranspiration deficit ratio (i.e., WDI) linearly depended on soil relative humidity. It showed that the estimation accuracy of 0-10 cm surface soil moisture was the highest (R 2 =0.90). The RMAEs of the estimated and measured soil relative humidity in deeper soil layers (up to 50 cm) were less than 15% and the RMSEs were less than 20%. The research could provide reference for drought monitoring and irrigation management.

Introducing litter quality to the ecosystem model LPJ-GUESS: Effects on short- and long-term soil carbon dynamics

NASA Astrophysics Data System (ADS)

Portner, Hanspeter; Wolf, Annett; Rühr, Nadine; Bugmann, Harald

2010-05-01

Many biogeochemical models have been applied to study the response of the carbon cycle to changes in climate, whereby the process of carbon uptake (photosynthesis) has usually gained more attention than the equally important process of carbon release by respiration. The decomposition of soil organic matter is driven by a combination of factors like soil temperature, soil moisture and litter quality. We have introduced dependence on litter substrate quality to heterotrophic soil respiration in the ecosystem model LPJ-GUESS [Smith et al.(2001)]. We were interested in differences in model projections before and after the inclusion of the dependency both in respect to short- and long-term soil carbon dynamics. The standard implementation of heterotrophic soil respiration in LPJ-GUESS is a simple carbon three-pool model whose decay rates are dependent on soil temperature and soil moisture. We have added dependence on litter quality by coupling LPJ-GUESS to the soil carbon model Yasso07 [Tuomi et al.(2008)]. The Yasso07 model is based on an extensive number of measurements of litter decomposition of forest soils. Apart from the dependence on soil temperature and soil moisture, the Yasso07 model uses carbon soil pools representing different substrate qualities: acid hydrolyzable, water soluble, ethanol soluble, lignin compounds and humus. Additionally Yasso07 differentiates between woody and non-woody litter. In contrary to the reference implementation of LPJ-GUESS, in the new model implementation, the litter now is divided according to its specific quality and added to the corresponding soil carbon pool. The litter quality thereby differs between litter source (leaves, roots, stems) and plant functional type (broadleaved, needleleaved, grass). The two contrasting model implementations were compared and validated at one specific CarboEuropeIP site (Lägern, Switzerland) and on a broader scale all over Switzerland. Our focus lay on the soil respiration for the years 2006 and 2007 [Rühr(2009)] and present soil carbon stocks [Heim et al.(2009)]. Our Results show, that for short-term soil carbon dynamics, e.g. estimates of heterotrophic soil respiration on an annual basis, the inclusion of the dependency on litter quality is not necessary, as the differences are minor only. However, when considering long-term soil carbon dynamics, e.g. simulated estimates of present soil carbon content, the dependency on litter quality shows effect, as there are correlations with specific site factors such as site location and forest type. The inclusion of the dependence on litter quality therefore may be of importance for the projection of future soil carbon dynamics, as forest types may well be altered due to climatic change. References [Heim et al.(2009)] A. Heim, L. Wehrli, W. Eugster, and M.W.I. Schmidt. Effects of sampling design on the probability to detect soil carbon stock changes at the swiss CarboEurope site Lägeren. Geoderma, 149(3-4):347-354, 2009. [Rühr(2009)] Nadine Katrin Rühr. Soil respiration in a mixed mountain forest : environmental drivers and partitioning of component fluxes. PhD thesis, ETH, 2009. [Smith et al.(2001)] Benjamin Smith, I. Colin Prentice, and Martin T. Sykes. Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within european climate space. Global Ecology and Biogeography, 10(6):621-637, 2001. [Tuomi et al.(2008)] Mikko Tuomi, Pekka Vanhala, Kristiina Karhu, Hannu Fritze, and Jari Liski. Heterotrophic soil respiration-Comparison of different models describing its temperature dependence. Ecological Modelling, 211(1-2): 182-190, 2008.

Modeling daily soil temperature over diverse climate conditions in Iran—a comparison of multiple linear regression and support vector regression techniques

NASA Astrophysics Data System (ADS)

Delbari, Masoomeh; Sharifazari, Salman; Mohammadi, Ehsan

2018-02-01

The knowledge of soil temperature at different depths is important for agricultural industry and for understanding climate change. The aim of this study is to evaluate the performance of a support vector regression (SVR)-based model in estimating daily soil temperature at 10, 30 and 100 cm depth at different climate conditions over Iran. The obtained results were compared to those obtained from a more classical multiple linear regression (MLR) model. The correlation sensitivity for the input combinations and periodicity effect were also investigated. Climatic data used as inputs to the models were minimum and maximum air temperature, solar radiation, relative humidity, dew point, and the atmospheric pressure (reduced to see level), collected from five synoptic stations Kerman, Ahvaz, Tabriz, Saghez, and Rasht located respectively in the hyper-arid, arid, semi-arid, Mediterranean, and hyper-humid climate conditions. According to the results, the performance of both MLR and SVR models was quite well at surface layer, i.e., 10-cm depth. However, SVR performed better than MLR in estimating soil temperature at deeper layers especially 100 cm depth. Moreover, both models performed better in humid climate condition than arid and hyper-arid areas. Further, adding a periodicity component into the modeling process considerably improved the models' performance especially in the case of SVR.

Applications of a thermal-based two-source energy balance model using Priestley-Taylor approach for surface temperature partitioning under advective conditions

NASA Astrophysics Data System (ADS)

Song, Lisheng; Kustas, William P.; Liu, Shaomin; Colaizzi, Paul D.; Nieto, Hector; Xu, Ziwei; Ma, Yanfei; Li, Mingsong; Xu, Tongren; Agam, Nurit; Tolk, Judy A.; Evett, Steven R.

2016-09-01

In this study ground measured soil and vegetation component temperatures and composite temperature from a high spatial resolution thermal camera and a network of thermal-IR sensors collected in an irrigated maize field and in an irrigated cotton field are used to assess and refine the component temperature partitioning approach in the Two-Source Energy Balance (TSEB) model. A refinement to TSEB using a non-iterative approach based on the application of the Priestley-Taylor formulation for surface temperature partitioning and estimating soil evaporation from soil moisture observations under advective conditions (TSEB-A) was developed. This modified TSEB formulation improved the agreement between observed and modeled soil and vegetation temperatures. In addition, the TSEB-A model output of evapotranspiration (ET) and the components evaporation (E), transpiration (T) when compared to ground observations using the stable isotopic method and eddy covariance (EC) technique from the HiWATER experiment and with microlysimeters and a large monolithic weighing lysimeter from the BEAREX08 experiment showed good agreement. Difference between the modeled and measured ET measurements were less than 10% and 20% on a daytime basis for HiWATER and BEAREX08 data sets, respectively. The TSEB-A model was found to accurately reproduce the temporal dynamics of E, T and ET over a full growing season under the advective conditions existing for these irrigated crops located in arid/semi-arid climates. With satellite data this TSEB-A modeling framework could potentially be used as a tool for improving water use efficiency and conservation practices in water limited regions. However, TSEB-A requires soil moisture information which is not currently available routinely from satellite at the field scale.

The effect of soil moisture anomalies on maize yield in Germany

NASA Astrophysics Data System (ADS)

Peichl, Michael; Thober, Stephan; Meyer, Volker; Samaniego, Luis

2018-03-01

Crop models routinely use meteorological variations to estimate crop yield. Soil moisture, however, is the primary source of water for plant growth. The aim of this study is to investigate the intraseasonal predictability of soil moisture to estimate silage maize yield in Germany. We also evaluate how approaches considering soil moisture perform compare to those using only meteorological variables. Silage maize is one of the most widely cultivated crops in Germany because it is used as a main biomass supplier for energy production in the course of the German Energiewende (energy transition). Reduced form fixed effect panel models are employed to investigate the relationships in this study. These models are estimated for each month of the growing season to gain insights into the time-varying effects of soil moisture and meteorological variables. Temperature, precipitation, and potential evapotranspiration are used as meteorological variables. Soil moisture is transformed into anomalies which provide a measure for the interannual variation within each month. The main result of this study is that soil moisture anomalies have predictive skills which vary in magnitude and direction depending on the month. For instance, dry soil moisture anomalies in August and September reduce silage maize yield more than 10 %, other factors being equal. In contrast, dry anomalies in May increase crop yield up to 7 % because absolute soil water content is higher in May compared to August due to its seasonality. With respect to the meteorological terms, models using both temperature and precipitation have higher predictability than models using only one meteorological variable. Also, models employing only temperature exhibit elevated effects.

Elevated CO2 and temperature increase soil C losses from a soybean-maize ecosystem.

PubMed

Black, Christopher K; Davis, Sarah C; Hudiburg, Tara W; Bernacchi, Carl J; DeLucia, Evan H

2017-01-01

Warming temperatures and increasing CO 2 are likely to have large effects on the amount of carbon stored in soil, but predictions of these effects are poorly constrained. We elevated temperature (canopy: +2.8 °C; soil growing season: +1.8 °C; soil fallow: +2.3 °C) for 3 years within the 9th-11th years of an elevated CO 2 (+200 ppm) experiment on a maize-soybean agroecosystem, measured respiration by roots and soil microbes, and then used a process-based ecosystem model (DayCent) to simulate the decadal effects of warming and CO 2 enrichment on soil C. Both heating and elevated CO 2 increased respiration from soil microbes by ~20%, but heating reduced respiration from roots and rhizosphere by ~25%. The effects were additive, with no heat × CO 2 interactions. Particulate organic matter and total soil C declined over time in all treatments and were lower in elevated CO 2 plots than in ambient plots, but did not differ between heat treatments. We speculate that these declines indicate a priming effect, with increased C inputs under elevated CO 2 fueling a loss of old soil carbon. Model simulations of heated plots agreed with our observations and predicted loss of ~15% of soil organic C after 100 years of heating, but simulations of elevated CO 2 failed to predict the observed C losses and instead predicted a ~4% gain in soil organic C under any heating conditions. Despite model uncertainty, our empirical results suggest that combined, elevated CO 2 and temperature will lead to long-term declines in the amount of carbon stored in agricultural soils. © 2016 John Wiley & Sons Ltd.

Simulation of Soil Frost and Thaw Fronts Dynamics with Community Land Model 4.5

NASA Astrophysics Data System (ADS)

Gao, J.; Xie, Z.

2016-12-01

Freeze-thaw processes in soils, including changes in frost and thaw fronts (FTFs) , are important physical processes. The movement of FTFs affects soil water and thermal characteristics, as well as energy and water exchanges between land surface and the atmosphere, and then the land surface hydrothermal process. In this study, a two-directional freeze and thaw algorithm for simulating FTFs is incorporated into the community land surface model CLM4.5, which is called CLM4.5-FTF. The simulated FTFs depth and soil temperature of CLM4.5-FTF compared well with the observed data both in D66 station (permafrost) and Hulugou station (seasonally frozen soil). Because the soil temperature profile within a soil layer can be estimated according to the position of FTFs, CLM4.5 performed better in soil temperature simulation. Permafrost and seasonally frozen ground conditions in China from 1980 to 2010 were simulated using the CLM4.5-FTF. Numerical experiments show that the spatial distribution of simulated maximum frost depth by CLM4.5-FTF has seasonal variation obviously. Significant positive active-layer depth trends for permafrost regions and negative maximum freezing depth trends for seasonal frozen soil regions are simulated in response to positive air temperature trends except west of Black Sea.

Soil Temperature and Moisture Profile (STAMP) System Handbook

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cook, David R.

The soil temperature and moisture profile system (STAMP) provides vertical profiles of soil temperature, soil water content (soil-type specific and loam type), plant water availability, soil conductivity, and real dielectric permittivity as a function of depth below the ground surface at half-hourly intervals, and precipitation at one-minute intervals. The profiles are measured directly by in situ probes at all extended facilities of the SGP climate research site. The profiles are derived from measurements of soil energy conductivity. Atmospheric scientists use the data in climate models to determine boundary conditions and to estimate the surface energy flux. The data are alsomore » useful to hydrologists, soil scientists, and agricultural scientists for determining the state of the soil. The STAMP system replaced the SWATS system in early 2016.« less

Effects of soil water and heat relationship under various snow cover during freezing-thawing periods in Songnen Plain, China.

PubMed

Fu, Qiang; Hou, Renjie; Li, Tianxiao; Jiang, Ruiqi; Yan, Peiru; Ma, Ziao; Zhou, Zhaoqiang

2018-01-22

In this study, the spatial variations of soil water and heat under bare land (BL), natural snow (NS), compacted snow (CS) and thick snow (TS) treatments were analyzed. The relationship curve between soil temperature and water content conforms to the exponential filtering model, by means of the functional form of the model, it was defined as soil water and heat relation function model. On this basis, soil water and heat function models of 10, 20, 40, 60, 100, and 140 cm were established. Finally, a spatial variation law of the relationship effect was described based on analysising of the differences between the predicted and measured results. During freezing period, the effects of external factors on soil were hindered by snow cover. As the snow increased, the accuracy of the function model gradually improved. During melting period, infiltration by snowmelt affected the relationship between the soil temperature and moisture. With the increasing of snow, the accuracy of the function models gradually decreased. The relationship effects of soil water and heat increased with increasing depth within the frozen zone. In contrast, below the frozen layer, the relationship of soil water and heat was weaker, and the function models were less accurate.

Numerical Modeling of Water Fluxes in the Root Zone of Irrigated Pecan

NASA Astrophysics Data System (ADS)

Shukla, M. K.; Deb, S.

2010-12-01

Information is still limited on the coupled liquid water, water vapor, heat transport and root water uptake for irrigated pecan. Field experiments were conducted in a sandy loam mature pecan field in Las Cruces, New Mexico. Three pecan trees were chosen to monitor diurnal soil water content under the canopy (approximately half way between trunk and the drip line) and outside the drip line (bare spot) along a transect at the depths of 5, 10, 20, 40, and 60 cm using TDR sensors. Soil temperature sensors were installed at an under-canopy locations and bare spot to monitor soil temperature data at depths of 5, 10, 20, and 40 cm. Simulations of the coupled transport of liquid water, water vapor, and heat with and without root water uptake were carried out using the HYDRUS-1D code. Measured soil hydraulic and thermal properties, continuous meteorological data, and pecan characteristics, e.g. rooting depth, leaf area index, were used in the model simulations. Model calibration was performed for a 26-day period from DOY 204 through DOY 230, 2009 based on measured soil water content and soil temperature data at different soil depths, while the model was validated for a 90-day period from DOY 231 through DOY 320, 2009 at bare spot. Calibrated parameters were also used to apply the model at under-canopy locations for a 116-day period from DOY 204 to 320. HYDRUS-1D simulated water contents and soil temperatures correlated well with the measured data at each depth. Numerical assessment of various transport mechanisms and quantitative estimates of isothermal and thermal water fluxes with and without root water uptake in the unsaturated zone within canopy and bare spot is in progress and will be presented in the conference.

Combined effect of temperature and copper pollution on soil bacterial community: climate change and regional variation aspects.

PubMed

Henriques, Isabel; Araújo, Susana; Pereira, Anabela; Menezes-Oliveira, Vanessa B; Correia, António; Soares, Amadeu M V M; Scott-Fordsmand, Janeck J; Amorim, Mónica J B

2015-01-01

The aim of this study was to assess the combined effects of temperature and copper (Cu) contamination in the structure of soil bacterial community. For this, contaminated or spiked and control soils from two different geographic origins (PT-Portugal and DK-Denmark) were used. The DK soil was from a historically contaminated study field, representing a long-term exposure to Cu while the PT soil was from a clean site and freshly spiked with Cu. Soil bacterial communities were exposed in mesocosms during 84 days to 3 different temperatures based on values typically found in each geographic region and temperature conditions that simulated a warming scenario. Obtained results indicate that Cu stress alters the structure of bacterial community and that this effect is, to some extent, temperature-dependent. Effects on bacterial diversity for both soils were also observed. Differences in the DK and PT communities' response were apparent, with the community from the historically contaminated soil being more resilient to temperature fluctuations. This study presents evidence to support the hypothesis that temperature alters the effect of metals on soils. Further, our results suggest that the definition of soils quality criteria must be based on studies performed under temperatures selected for the specific geographic region. Studies taking into account temperature changes are needed to model and predict risks, this is important to e.g. future adjustments of the maximum permissible levels for soil metal contamination. Copyright © 2014 Elsevier Inc. All rights reserved.

Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area

USGS Publications Warehouse

Wang, A.; Moore, J.C.; Cui, Xingquan; Ji, D.; Li, Q.; Zhang, N.; Wang, C.; Zhang, S.; Lawrence, D.M.; McGuire, A.D.; Zhang, W.; Delire, C.; Koven, C.; Saito, K.; MacDougall, A.; Burke, E.; Decharme, B.

2016-01-01

 We perform a land-surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP) varies among six modern stand-alone land-surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic). We also examine the variability in simulated permafrost area and distribution introduced by five different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes). There is good agreement (99 to 135  ×  104 km2) between the two diagnostic methods based on air temperature which are also consistent with the observation-based estimate of actual permafrost area (101  × 104 km2). However the uncertainty (1 to 128  ×  104 km2) using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on the TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index), while permafrost distribution using air-temperature-based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification, vegetation types and snow cover. Models are particularly poor at simulating permafrost distribution using the definition that soil temperature remains at or below 0 °C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land-surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in future permafrost distribution can be made for the Tibetan Plateau.

Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area

NASA Astrophysics Data System (ADS)

Wang, W.; Rinke, A.; Moore, J. C.; Cui, X.; Ji, D.; Li, Q.; Zhang, N.; Wang, C.; Zhang, S.; Lawrence, D. M.; McGuire, A. D.; Zhang, W.; Delire, C.; Koven, C.; Saito, K.; MacDougall, A.; Burke, E.; Decharme, B.

2016-02-01

We perform a land-surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP) varies among six modern stand-alone land-surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic). We also examine the variability in simulated permafrost area and distribution introduced by five different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes). There is good agreement (99 to 135 × 104 km2) between the two diagnostic methods based on air temperature which are also consistent with the observation-based estimate of actual permafrost area (101 × 104 km2). However the uncertainty (1 to 128 × 104 km2) using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on the TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index), while permafrost distribution using air-temperature-based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification, vegetation types and snow cover. Models are particularly poor at simulating permafrost distribution using the definition that soil temperature remains at or below 0 °C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land-surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in future permafrost distribution can be made for the Tibetan Plateau.

Three phase heat and mass transfer model for unsaturated soil freezing process: Part 1 - model development

NASA Astrophysics Data System (ADS)

Xu, Fei; Zhang, Yaning; Jin, Guangri; Li, Bingxi; Kim, Yong-Song; Xie, Gongnan; Fu, Zhongbin

2018-04-01

A three-phase model capable of predicting the heat transfer and moisture migration for soil freezing process was developed based on the Shen-Chen model and the mechanisms of heat and mass transfer in unsaturated soil freezing. The pre-melted film was taken into consideration, and the relationship between film thickness and soil temperature was used to calculate the liquid water fraction in both frozen zone and freezing fringe. The force that causes the moisture migration was calculated by the sum of several interactive forces and the suction in the pre-melted film was regarded as an interactive force between ice and water. Two kinds of resistance were regarded as a kind of body force related to the water films between the ice grains and soil grains, and a block force instead of gravity was introduced to keep balance with gravity before soil freezing. Lattice Boltzmann method was used in the simulation, and the input variables for the simulation included the size of computational domain, obstacle fraction, liquid water fraction, air fraction and soil porosity. The model is capable of predicting the water content distribution along soil depth and variations in water content and temperature during soil freezing process.

The Impact of Spring Subsurface Soil Temperature Anomaly in the Western U.S. on North American Summer Precipitation: A Case Study Using Regional Climate Model Downscaling

DTIC Science & Technology

2012-06-02

regional climate model downscaling , J. Geophys. Res., 117, D11103, doi:10.1029/2012JD017692. 1. Introduction [2] Modeling studies and data analyses...based on ground and satellite data have demonstrated that the land surface state variables, such as soil moisture, snow, vegetation, and soil temperature... downscaling rather than simply applying reanal- ysis data as LBC for both Eta control and sensitivity experiments as done in many RCM sensitivity studies

Impact of soil moisture initialization on boreal summer subseasonal forecasts: mid-latitude surface air temperature and heat wave events

NASA Astrophysics Data System (ADS)

Seo, Eunkyo; Lee, Myong-In; Jeong, Jee-Hoon; Koster, Randal D.; Schubert, Siegfried D.; Kim, Hye-Mi; Kim, Daehyun; Kang, Hyun-Suk; Kim, Hyun-Kyung; MacLachlan, Craig; Scaife, Adam A.

2018-05-01

This study uses a global land-atmosphere coupled model, the land-atmosphere component of the Global Seasonal Forecast System version 5, to quantify the degree to which soil moisture initialization could potentially enhance boreal summer surface air temperature forecast skill. Two sets of hindcast experiments are performed by prescribing the observed sea surface temperature as the boundary condition for a 15-year period (1996-2010). In one set of the hindcast experiments (noINIT), the initial soil moisture conditions are randomly taken from a long-term simulation. In the other set (INIT), the initial soil moisture conditions are taken from an observation-driven offline Land Surface Model (LSM) simulation. The soil moisture conditions from the offline LSM simulation are calibrated using the forecast model statistics to minimize the inconsistency between the LSM and the land-atmosphere coupled model in their mean and variability. Results show a higher boreal summer surface air temperature prediction skill in INIT than in noINIT, demonstrating the potential benefit from an accurate soil moisture initialization. The forecast skill enhancement appears especially in the areas in which the evaporative fraction—the ratio of surface latent heat flux to net surface incoming radiation—is sensitive to soil moisture amount. These areas lie in the transitional regime between humid and arid climates. Examination of the extreme 2003 European and 2010 Russian heat wave events reveal that the regionally anomalous soil moisture conditions during the events played an important role in maintaining the stationary circulation anomalies, especially those near the surface.

Effects of short-term variability of meteorological variables on soil temperature in permafrost regions

NASA Astrophysics Data System (ADS)

Beer, Christian; Porada, Philipp; Ekici, Altug; Brakebusch, Matthias

2018-03-01

Effects of the short-term temporal variability of meteorological variables on soil temperature in northern high-latitude regions have been investigated. For this, a process-oriented land surface model has been driven using an artificially manipulated climate dataset. Short-term climate variability mainly impacts snow depth, and the thermal diffusivity of lichens and bryophytes. These impacts of climate variability on insulating surface layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is 0.1 to 0.8 °C higher when climate variability is reduced. Earth system models project warming of the Arctic region but also increasing variability of meteorological variables and more often extreme meteorological events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness in response to climate change will be lower (i) when taking into account future changes in short-term variability of meteorological variables and (ii) when representing dynamic snow and lichen and bryophyte functions in land surface models.

Modeling soil thermal and carbon dynamics of a fire chronosequence in interior Alaska

USGS Publications Warehouse

Zhuang, Q.; McGuire, A.D.; O'Neill, K. P.; Harden, J.W.; Romanovsky, V.E.; Yarie, J.

2003-01-01

In this study, the dynamics of soil thermal, hydrologic, and ecosystem processes were coupled to project how the carbon budgets of boreal forests will respond to changes in atmospheric CO2, climate, and fire disturbance. The ability of the model to simulate gross primary production and ecosystem respiration was verified for a mature black spruce ecosystem in Canada, the age-dependent pattern of the simulated vegetation carbon was verified with inventory data on aboveground growth of Alaskan black spruce forests, and the model was applied to a postfire chronosequence in interior Alaska. The comparison between the simulated soil temperature and field-based estimates during the growing season (May to September) of 1997 revealed that the model was able to accurately simulate monthly temperatures at 10 cm (R > 0.93) for control and burned stands of the fire chronosequence. Similarly, the simulated and field-based estimates of soil respiration for control and burned stands were correlated (R = 0.84 and 0.74 for control and burned stands, respectively). The simulated and observed decadal to century-scale dynamics of soil temperature and carbon dynamics, which are represented by mean monthly values of these variables during the growing season, were correlated among stands (R = 0.93 and 0.71 for soil temperature at 20- and 10-cm depths, R = 0.95 and 0.91 for soil respiration and soil carbon, respectively). Sensitivity analyses indicate that along with differences in fire and climate history a number of other factors influence the response of carbon dynamics to fire disturbance. These factors include nitrogen fixation, the growth of moss, changes in the depth of the organic layer, soil drainage, and fire severity.

Experimental determination of soil heat storage for the simulation of heat transport in a coastal wetland

NASA Astrophysics Data System (ADS)

Swain, Michael; Swain, Matthew; Lohmann, Melinda; Swain, Eric

2012-02-01

SummaryTwo physical experiments were developed to better define the thermal interaction of wetland water and the underlying soil layer. This information is important to numerical models of flow and heat transport that have been developed to support biological studies in the South Florida coastal wetland areas. The experimental apparatus consists of two 1.32 m diameter by 0.99 m tall, trailer-mounted, well-insulated tanks filled with soil and water. A peat-sand-soil mixture was used to represent the wetland soil, and artificial plants were used as a surrogate for emergent wetland vegetation based on size and density observed in the field. The tanks are instrumented with thermocouples to measure vertical and horizontal temperature variations and were placed in an outdoor environment subject to solar radiation, wind, and other factors affecting the heat transfer. Instruments also measure solar radiation, relative humidity, and wind speed. Tests indicate that heat transfer through the sides and bottoms of the tanks is negligible, so the experiments represent vertical heat transfer effects only. The temperature fluctuations measured in the vertical profile through the soil and water are used to calibrate a one-dimensional heat-transport model. The model was used to calculate the thermal conductivity of the soil. Additionally, the model was used to calculate the total heat stored in the soil. This information was then used in a lumped parameter model to calculate an effective depth of soil which provides the appropriate heat storage to be combined with the heat storage in the water column. An effective depth, in the model, of 5.1 cm of wetland soil represents the heat storage needed to match the data taken in the tank containing 55.9 cm of peat/sand/soil mix. The artificial low-density laboratory sawgrass reduced the solar energy absorbed by the 35.6 cm of water and 55.9 cm of soil at midday by less than 5%. The maximum heat transfer into the underlying peat-sand-soil mix lags behind maximum solar radiation by approximately 2 h. A slightly longer temperature lag was observed between the maximum solar radiation and maximum water temperature both with and without soil.

Experimental determination of soil heat storage for the simulation of heat transport in a coastal wetland

USGS Publications Warehouse

Swain, Michael; Swain, Matthew; Lohmann, Melinda; Swain, Eric

2012-01-01

Two physical experiments were developed to better define the thermal interaction of wetland water and the underlying soil layer. This information is important to numerical models of flow and heat transport that have been developed to support biological studies in the South Florida coastal wetland areas. The experimental apparatus consists of two 1.32. m diameter by 0.99. m tall, trailer-mounted, well-insulated tanks filled with soil and water. A peat-sand-soil mixture was used to represent the wetland soil, and artificial plants were used as a surrogate for emergent wetland vegetation based on size and density observed in the field. The tanks are instrumented with thermocouples to measure vertical and horizontal temperature variations and were placed in an outdoor environment subject to solar radiation, wind, and other factors affecting the heat transfer. Instruments also measure solar radiation, relative humidity, and wind speed.Tests indicate that heat transfer through the sides and bottoms of the tanks is negligible, so the experiments represent vertical heat transfer effects only. The temperature fluctuations measured in the vertical profile through the soil and water are used to calibrate a one-dimensional heat-transport model. The model was used to calculate the thermal conductivity of the soil. Additionally, the model was used to calculate the total heat stored in the soil. This information was then used in a lumped parameter model to calculate an effective depth of soil which provides the appropriate heat storage to be combined with the heat storage in the water column. An effective depth, in the model, of 5.1. cm of wetland soil represents the heat storage needed to match the data taken in the tank containing 55.9. cm of peat/sand/soil mix. The artificial low-density laboratory sawgrass reduced the solar energy absorbed by the 35.6. cm of water and 55.9. cm of soil at midday by less than 5%. The maximum heat transfer into the underlying peat-sand-soil mix lags behind maximum solar radiation by approximately 2. h. A slightly longer temperature lag was observed between the maximum solar radiation and maximum water temperature both with and without soil. ?? 2012 Elsevier B.V.

An annual model of SSM/I radiobrightness for dry soil

NASA Technical Reports Server (NTRS)

Liou, Yuei-An; England, A. W.

1992-01-01

An annual model is presented of the temperature structure within a homogeneous, dry soil halfspace that is subject to both diurnal and annual insolation, radiant heating from the atmosphere, sensible heat exchange with the atmosphere, and radiant cooling. The thermal constitutive properties of the soil are assumed to be constant so that the heat flow equation can be solved analytically. For computational economy, a variable time interval Laplace transform method is developed to predict the temperature.

Soil CO2 efflux from two mountain forests in the eastern Himalayas, Bhutan: components and controls

NASA Astrophysics Data System (ADS)

Wangdi, Norbu; Mayer, Mathias; Prasad Nirola, Mani; Zangmo, Norbu; Orong, Karma; Uddin Ahmed, Iftekhar; Darabant, Andras; Jandl, Robert; Gratzer, Georg; Schindlbacher, Andreas

2017-01-01

The biogeochemistry of mountain forests in the Hindu Kush Himalaya range is poorly studied, although climate change is expected to disproportionally affect the region. We measured the soil CO2 efflux (Rs) at a high-elevation (3260 m) mixed forest and a lower-elevation (2460 m) broadleaf forest in Bhutan, eastern Himalayas, during 2015. Trenching was applied to estimate the contribution of autotrophic (Ra) and heterotrophic (Rh) soil respiration. The temperature (Q10) and the moisture sensitivities of Rh were determined under controlled laboratory conditions and were used to model Rh in the field. The higher-elevation mixed forest had a higher standing tree stock, reflected in higher soil C stocks and basal soil respiration. Annual Rs was similar between the two forest sites (14.5 ± 1.2 t C ha-1 for broadleaf; 12.8 ± 1.0 t C ha-1 for mixed). Modelled annual contribution of Rh was ˜ 65 % of Rs at both sites with a higher heterotrophic contribution during winter and lower contribution during the monsoon season. Rh, estimated from trenching, was in the range of modelled Rh but showed higher temporal variability. The measured temperature sensitivity of Rh was similar at the mixed and broadleaf forest sites (Q10 2.2-2.3) under intermediate soil moisture but decreased (Q10 1.5 at both sites) in dry soil. Rs closely followed the annual course of field soil temperature at both sites. Covariation between soil temperature and moisture (cold dry winters and warm wet summers) was likely the main cause for this close relationship. Under the prevailing weather conditions, a simple temperature-driven model was able to explain more than 90 % of the temporal variation in Rs. A longer time series and/or experimental climate manipulations are required to understand the effects of eventually occurring climate extremes such as monsoon failures.

One-dimensional soil temperature assimilation experiment based on unscented particle filter and Common Land Model

NASA Astrophysics Data System (ADS)

Fu, Xiao Lei; Jin, Bao Ming; Jiang, Xiao Lei; Chen, Cheng

2018-06-01

Data assimilation is an efficient way to improve the simulation/prediction accuracy in many fields of geosciences especially in meteorological and hydrological applications. This study takes unscented particle filter (UPF) as an example to test its performance at different two probability distribution, Gaussian and Uniform distributions with two different assimilation frequencies experiments (1) assimilating hourly in situ soil surface temperature, (2) assimilating the original Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) once per day. The numerical experiment results show that the filter performs better when increasing the assimilation frequency. In addition, UPF is efficient for improving the soil variables (e.g., soil temperature) simulation/prediction accuracy, though it is not sensitive to the probability distribution for observation error in soil temperature assimilation.

Modelling of mercury emissions from background soils.

PubMed

Scholtz, M T; Van Heyst, B J; Schroeder, W H

2003-03-20

Emissions of volatile mercury species from natural soils are believed to be a significant contributor to the atmospheric burden of mercury, but only order-of-magnitude estimates of emissions from these sources are available. The scaling-up of mercury flux measurements to regional or global scales is confounded by a limited understanding of the physical, chemical and biochemical processes that occur in the soil, a complex environmental matrix. This study is a first step toward the development of an air-surface exchange model for mercury (known as the mercury emission model (MEM)). The objective of the study is to model the partitioning and movement of inorganic Hg(II) and Hg(0) in open field soils, and to use MEM to interpret published data on mercury emissions to the atmosphere. MEM is a multi-layered, dynamic finite-element soil and atmospheric surface-layer model that simulates the exchange of heat, moisture and mercury between soils and the atmosphere. The model includes a simple formulation of the reduction of inorganic Hg(II) to Hg(0). Good agreement was found between the meteorological dependence of observed mercury emission fluxes, and hourly modelled fluxes, and it is concluded that MEM is able to simulate well the soil and atmospheric processes influencing the emission of Hg(0) to the atmosphere. The heretofore unexplained close correlation between soil temperature and mercury emission flux is fully modelled by MEM and is attributed to the temperature dependence of the Hg(0) Henry's Law coefficient and the control of the volumetric soil-air fraction on the diffusion of Hg(0) near the surface. The observed correlation between solar radiation intensity and mercury flux, appears in part to be due to the surface-energy balance between radiation, and sensible and latent heat fluxes which determines the soil temperature. The modelled results imply that empirical correlations that are based only on flux chamber data, may not extend to the open atmosphere for all weather scenarios.

Impact of climate change on soil thermal and moisture regimes in Serbia: An analysis with data from regional climate simulations under SRES-A1B.

PubMed

Mihailović, D T; Drešković, N; Arsenić, I; Ćirić, V; Djurdjević, V; Mimić, G; Pap, I; Balaž, I

2016-11-15

We considered temporal and spatial variations to the thermal and moisture regimes of the most common RSGs (Reference Soil Groups) in Serbia under the A1B scenario for the 2021-2050 and 2071-2100 periods, with respect to the 1961-1990 period. We utilized dynamically downscaled global climate simulations from the ECHAM5 model using the coupled regional climate model EBU-POM (Eta Belgrade University-Princeton Ocean Model). We analysed the soil temperature and moisture time series using simple statistics and a Kolmogorov complexity (KC) analysis. The corresponding metrics were calculated for 150 sites. In the future, warmer and drier regimes can be expected for all RSGs in Serbia. The calculated soil temperature and moisture variations include increases in the mean annual soil temperature (up to 3.8°C) and decreases in the mean annual soil moisture (up to 11.3%). Based on the KC values, the soils in Serbia are classified with respect to climate change impacts as (1) less sensitive (Vertisols, Umbrisols and Dystric Cambisols) or (2) more sensitive (Chernozems, Eutric Cambisols and Planosols). Copyright © 2016 Elsevier B.V. All rights reserved.

Modeling Coupled Movement of Water, Vapor, and Energy in Soils and at the Soil-Atmosphere Interface Using HYDRUS

NASA Astrophysics Data System (ADS)

Simunek, Jiri; Brunetti, Giuseppe; Saito, Hirotaka; Bristow, Keith

2017-04-01

Mass and energy fluxes in the subsurface are closely coupled and cannot be evaluated without considering their mutual interactions. However, only a few numerical models consider coupled water, vapor and energy transport in both the subsurface and at the soil-atmosphere interface. While hydrological and thermal processes in the subsurface are commonly implemented in existing models, which often consider both isothermally and thermally induced water and vapor flow, the interactions at the soil-atmosphere interface are often simplified, and the effects of slope inclination, slope azimuth, variable surface albedo and plant shading on incoming radiation and spatially variable surface mass and energy balance, and consequently on soil moisture and temperature distributions, are rarely considered. In this presentation we discuss these missing elements and our attempts to implement them into the HYDRUS model. We demonstrate implications of some of these interactions and their impact on the spatial distributions of soil temperature and water content, and their effect on soil evaporation. Additionally, we will demonstrate the use of the HYDRUS model to simulate processes relevant to the ground source heat pump systems.

Merging a mechanistic enzymatic model of soil heterotrophic respiration into an ecosystem model in two AmeriFlux sites of northeastern USA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sihi, Debjani; Davidson, Eric A.; Chen, Min

Heterotrophic respiration (Rh), microbial processing of soil organic matter to carbon dioxide (CO 2), is a major, yet highly uncertain, carbon (C) flux from terrestrial systems to the atmosphere. Temperature sensitivity of Rh is often represented with a simple Q 10 function in ecosystem models and earth system models (ESMs), sometimes accompanied by an empirical soil moisture modifier. More explicit representation of the effects of soil moisture, substrate supply, and their interactions with temperature has been proposed as a way to disentangle the confounding factors of apparent temperature sensitivity of Rh and improve the performance of ecosystem models and ESMs.more » The objective of this work was to insert into an ecosystem model a more mechanistic, but still parsimonious, model of environmental factors controlling Rh and evaluate the model performance in terms of soil and ecosystem respiration. The Dual Arrhenius and Michaelis-Menten (DAMM) model simulates Rh using Michaelis-Menten, Arrhenius, and diffusion functions. Soil moisture affects Rh and its apparent temperature sensitivity in DAMM by regulating the diffusion of oxygen, soluble C substrates, and extracellular enzymes to the enzymatic reaction site. Here, we merged the DAMM soil flux model with a parsimonious ecosystem flux model, FöBAAR (Forest Biomass, Assimilation, Allocation and Respiration). We used high-frequency soil flux data from automated soil chambers and landscape-scale ecosystem fluxes from eddy covariance towers at two AmeriFlux sites (Harvard Forest, MA and Howland Forest, ME) in the northeastern USA to estimate parameters, validate the merged model, and to quantify the uncertainties in a multiple constraints approach. The optimized DAMM-FöBAAR model better captured the seasonal and inter-annual dynamics of soil respiration (Soil R) compared to the FöBAAR-only model for the Harvard Forest, where higher frequency and duration of drying events significantly regulate substrate supply to heterotrophs. However, DAMM-FöBAAR showed improvement over FöBAAR-only at the boreal transition Howland Forest only in unusually dry years. The frequency of synoptic-scale dry periods is lower at Howland, resulting in only brief water limitation of Rh in some years. At both sites, the declining trend of soil R during drying events was captured by the DAMM-FöBAAR model; however, model performance was also contingent on site conditions, climate, and the temporal scale of interest. While the DAMM functions require a few more parameters than a simple Q10 function, we have demonstrated that they can be included in an ecosystem model and reduce the model-data mismatch. Moreover, the mechanistic structure of the soil moisture effects using DAMM functions should be more generalizable than the wide variety of empirical functions that are commonly used, and these DAMM functions could be readily incorporated into other ecosystem models and ESMs.« less

Temperature Effects on Microbial CH4 and CO2 Production in Permafrost-Affected Soils From the Barrow Environmental Observatory

NASA Astrophysics Data System (ADS)

Graham, D. E.; Roy Chowdhury, T.; Zheng, J.; Moon, J. W.; Yang, Z.; Gu, B.; Wullschleger, S. D.

2015-12-01

Warmer Arctic temperatures are increasing the annual soil thaw depth and prolonging the thaw season in Alaskan permafrost zones. This change exposes organic matter buried in the soils and permafrost to microbial degradation and mineralization to form CO2 and CH4. The proportion and fluxes of these greenhouse gases released into the atmosphere control the global feedback on warming. To improve representations of these biogeochemical processes in terrestrial ecosystem models we compared soil properties and microbial activities in core samples of polygonal tundra from the Barrow Environmental Observatory. Measurements of soil water potential through the soil column characterized water binding to the organic and mineral components. This suction combines with temperature to control freezing, gas diffusion and microbial activity. The temperature-dependence of CO2 and CH4 production from anoxic soil incubations at -2, +4 or +8 °C identified a significant lag in methanogenesis relative to CO2 production by anaerobic respiration and fermentation. Changes in the abundance of methanogen signature genes during incubations indicate that microbial population shifts caused by thawing and warmer temperatures drive changes in the mixtures of soil carbon degradation products. Comparisons of samples collected across the microtopographic features of ice-wedge polygons address the impacts of water saturation, iron reduction and organic matter content on CH4 production and oxidation. These combined measurements build process understanding that can be applied across scales to constrain key response factors in models that address Arctic soil warming.

Temperature sensitivity of soil respiration rates enhanced by microbial community response.

PubMed

Karhu, Kristiina; Auffret, Marc D; Dungait, Jennifer A J; Hopkins, David W; Prosser, James I; Singh, Brajesh K; Subke, Jens-Arne; Wookey, Philip A; Agren, Göran I; Sebastià, Maria-Teresa; Gouriveau, Fabrice; Bergkvist, Göran; Meir, Patrick; Nottingham, Andrew T; Salinas, Norma; Hartley, Iain P

2014-09-04

Soils store about four times as much carbon as plant biomass, and soil microbial respiration releases about 60 petagrams of carbon per year to the atmosphere as carbon dioxide. Short-term experiments have shown that soil microbial respiration increases exponentially with temperature. This information has been incorporated into soil carbon and Earth-system models, which suggest that warming-induced increases in carbon dioxide release from soils represent an important positive feedback loop that could influence twenty-first-century climate change. The magnitude of this feedback remains uncertain, however, not least because the response of soil microbial communities to changing temperatures has the potential to either decrease or increase warming-induced carbon losses substantially. Here we collect soils from different ecosystems along a climate gradient from the Arctic to the Amazon and investigate how microbial community-level responses control the temperature sensitivity of soil respiration. We find that the microbial community-level response more often enhances than reduces the mid- to long-term (90 days) temperature sensitivity of respiration. Furthermore, the strongest enhancing responses were observed in soils with high carbon-to-nitrogen ratios and in soils from cold climatic regions. After 90 days, microbial community responses increased the temperature sensitivity of respiration in high-latitude soils by a factor of 1.4 compared to the instantaneous temperature response. This suggests that the substantial carbon stores in Arctic and boreal soils could be more vulnerable to climate warming than currently predicted.

Evaluating soil carbon in global climate models: benchmarking, future projections, and model drivers

NASA Astrophysics Data System (ADS)

Todd-Brown, K. E.; Randerson, J. T.; Post, W. M.; Allison, S. D.

2012-12-01

The carbon cycle plays a critical role in how the climate responds to anthropogenic carbon dioxide. To evaluate how well Earth system models (ESMs) from the Climate Model Intercomparison Project (CMIP5) represent the carbon cycle, we examined predictions of current soil carbon stocks from the historical simulation. We compared the soil and litter carbon pools from 17 ESMs with data on soil carbon stocks from the Harmonized World Soil Database (HWSD). We also examined soil carbon predictions for 2100 from 16 ESMs from the rcp85 (highest radiative forcing) simulation to investigate the effects of climate change on soil carbon stocks. In both analyses, we used a reduced complexity model to separate the effects of variation in model drivers from the effects of model parameters on soil carbon predictions. Drivers included NPP, soil temperature, and soil moisture, and the reduced complexity model represented one pool of soil carbon as a function of these drivers. The ESMs predicted global soil carbon totals of 500 to 2980 Pg-C, compared to 1260 Pg-C in the HWSD. This 5-fold variation in predicted soil stocks was a consequence of a 3.4-fold variation in NPP inputs and 3.8-fold variability in mean global turnover times. None of the ESMs correlated well with the global distribution of soil carbon in the HWSD (Pearson's correlation <0.40, RMSE 9-22 kg m-2). On a biome level there was a broad range of agreement between the ESMs and the HWSD. Some models predicted HWSD biome totals well (R2=0.91) while others did not (R2=0.23). All of the ESM terrestrial decomposition models are structurally similar with outputs that were well described by a reduced complexity model that included NPP and soil temperature (R2 of 0.73-0.93). However, MPI-ESM-LR outputs showed only a moderate fit to this model (R2=0.51), and CanESM2 outputs were better described by a reduced model that included soil moisture (R2=0.74), We also found a broad range in soil carbon responses to climate change predicted by the ESMs, with changes of -480 to 230 Pg-C from 2005-2100. All models that reported NPP and heterotrophic respiration showed increases in both of these processes over the simulated period. In two of the models, soils switched from a global sink for carbon to a net source. Of the remaining models, half predicted that soils were a sink for carbon throughout the time period and the other half predicted that soils were a carbon source.. Heterotrophic respiration in most of the models from 2005-2100 was well explained by a reduced complexity model dependent on soil carbon, soil temperature, and soil moisture (R2 values >0.74). However, MPI-ESM (R2=0.45) showed only moderate fit to this model. Our analysis shows that soil carbon predictions from ESMs are highly variable, with much of this variability due to model parameterization and variations in driving variables. Furthermore, our reduced complexity models show that most variation in ESM outputs can be explained by a simple one-pool model with a small number of drivers and parameters. Therefore, agreement between soil carbon predictions across models could improve substantially by reconciling differences in driving variables and the parameters that link soil carbon with environmental drivers. However it is unclear if this model agreement would reflect what is truly happening in the Earth system.

The role of minerals and mean annual temperature on soil carbon accumulation: A modeling analysis

NASA Astrophysics Data System (ADS)

Abramoff, R. Z.; Georgiou, K.; Tang, J.; Torn, M. S.; Riley, W. J.

2016-12-01

Soil organic carbon (SOC) is the largest actively cycling terrestrial C pool with mean residence times that can exceed 10,000 years. There is strong evidence suggesting that SOC dynamics depend on soil temperature and C inputs to soil through net primary production (NPP), but it is unclear what the relative importance of these factors is relative to SOC protection by minerals. Recent empirical studies have suggested that mineral protection explains more variation in SOC stock sizes and C respiration fluxes than does NPP or climate. Our previous modeling has demonstrated that representing the chemistry of mineral sorption in a microbially-explicit model affects the temperature sensitivity of SOC dynamics. We apply this modeling framework to interpret observations of SOC stocks, mineral surface availability, mean annual temperature (MAT), and NPP collected along a 4,000 km transect in South America. We use a Random Forest machine learning algorithm and regression to analyze our model output and the empirical data. This analysis shows that mineral surface availability is the dominant control over C respiration and SOC stock, and is substantially larger than the effects of belowground NPP. We further show that minerals interact with MAT to determine the observed range of SOC stocks along this transect in the present day, as well as projected SOC stocks under long-term warming. Our model-data comparison suggests that soil mineralogy and MAT will explain the majority of the spatial variation in SOC stock over decadal-to-millennial timescales. We extend the analysis of these interactions using the ACME Land Model (ALM) coupled with an explicit representation of microbes, minerals, and vertical transport of solutes and gases. The model results confirm the dominant effects of minerals on organic matter decomposition throughout the soil column.

Coupled MODEL Intercomparison Project PHASE 5 (CMIP5) Projected Twenty-First Century Warming over Southern Africa: Role of LOCAL Feedbacks

NASA Astrophysics Data System (ADS)

Shongwe, M.

2014-12-01

The warming rates projected by an ensemble of the Coupled Model Intercomparion Project Phase 5 (CMIP5) global climate models (GCMs) over southern Africa (south of 10 degrees latitude) are investigated. In all RCPs, CMIP5 models project a higher warming rate over the southwestern parts centred around the arid Kalahari and Namib deserts. The higher warming rates over these areas outpace global warming by up to a factor 2 in some GCMs. The projected warming is associated with an increase in heat waves. There is notable consensus across the models with little intermodel spread, suggesting a strong robustness of the projections. Mechanisms underlying the enhanced warming are investigated. A positive soil moisture-temperature feedback is suggested to contribute to the accelerated temperature increase. A decrease in soil moisture is projected by the GCMs over the area of highest warming. The reduction in soil wetness reduces evapotranspiration rates over the area where evaporation is dependent on available soil moisture. The reduction is evapotranspiration affects the partitioning of turbulent energy fluxes from the soil surface into the atmosphere and translates into an increase of the Bowen ratio featuring an increase in sensible relative to latent heat flux. An increase in sensible heat flux leads to an increase in near-surface temperature. The increase in temperature leads to a higher vapour pressure deficit and evaporative demand and evapotranspiration from the dry soils, possibly leading to a further decrease in soil moisture. A precipitation-soil moisture feedback is also suggested. A decrease in mean precipitation and an increase in drought conditions are projected over the area of enhanced warming. The reduced precipitation results in drier soils. The drier soil translates to reduced evapotranspiration for cloud and rainfall formation. However, the role played by the soil moisture-precipitation feedback loop is still inconclusive and characterized by some degree of uncertainty given that the strength of the local moisture recycling has not been explicitly quantified. An alternative mechanism involving the impact of soil moisture anomalies on boundary-layer stability and precipitation formation will be investigated.

A model of the ground surface temperature for micrometeorological analysis

NASA Astrophysics Data System (ADS)

Leaf, Julian S.; Erell, Evyatar

2017-07-01

Micrometeorological models at various scales require ground surface temperature, which may not always be measured in sufficient spatial or temporal detail. There is thus a need for a model that can calculate the surface temperature using only widely available weather data, thermal properties of the ground, and surface properties. The vegetated/permeable surface energy balance (VP-SEB) model introduced here requires no a priori knowledge of soil temperature or moisture at any depth. It combines a two-layer characterization of the soil column following the heat conservation law with a sinusoidal function to estimate deep soil temperature, and a simplified procedure for calculating moisture content. A physically based solution is used for each of the energy balance components allowing VP-SEB to be highly portable. VP-SEB was tested using field data measuring bare loess desert soil in dry weather and following rain events. Modeled hourly surface temperature correlated well with the measured data (r 2 = 0.95 for a whole year), with a root-mean-square error of 2.77 K. The model was used to generate input for a pedestrian thermal comfort study using the Index of Thermal Stress (ITS). The simulation shows that the thermal stress on a pedestrian standing in the sun on a fully paved surface, which may be over 500 W on a warm summer day, may be as much as 100 W lower on a grass surface exposed to the same meteorological conditions.

Radiocarbon Evidence That Millennial and Fast-Cycling Soil Carbon are Equally Sensitive to Warming

NASA Astrophysics Data System (ADS)

Vaughn, L. S.; Torn, M. S.; Porras, R. C.

2017-12-01

Within the century, the Arctic is expected to shift from a sink to a source of atmospheric CO2 due to climate-induced increases in soil carbon mineralization. The magnitude of this effect remains uncertain, due in large part to unknown temperature sensitivities of organic matter decomposition. In particular, the distribution of temperature sensitivities across soil carbon pools remains unknown. New experimental approaches are needed, because studies that fit multi-pool models to CO2 flux measurements may be sensitive to model assumptions, statistical effects, and non-steady-state changes in substrate availability or microbial activity. In this study, we developed a new methodology using natural abundance radiocarbon to evaluate temperature sensitivities across soil carbon pools. In two incubation experiments with soils from Barrow, AK, we (1) evaluated soil carbon age and decomposability, (2) disentangled the effects of temperature and substrate depletion on carbon mineralization, and (3) compared the temperature sensitivities of fast- and slow-cycling soil carbon pools. From a long-term incubation, both respired CO2 and the remaining soil organic matter were highly depleted in radiocarbon. At 20 cm depth, median Δ14C values were -167‰ in respired CO2 and -377‰ in soil organic matter, corresponding to turnover times of 1800 and 4800 years, respectively. Such negative Δ14C values indicate both storage and decomposition of old, stabilized carbon, while radiocarbon differences between the mineralized and non-mineralized fractions suggest that decomposability varies along a turnover time gradient. Applying a new analytical method combining CO2 flux and Δ14C, we found that fast- and slow-cycling carbon pools were equally sensitive to temperature, with a Q10 of 2 irrespective of turnover time. We conclude that in these Arctic soils, ancient soil carbon is vulnerable to warming under thawed, aerobic conditions. In contrast to many previous studies, we found no difference in temperature sensitivity of decomposition between fast- and slow-cycling pools. These findings suggest that in these soils, carbon stabilization mechanisms other than chemical recalcitrance mediate temperature sensitivities, and even old SOC will be readily decomposable as climate warms.

Local Versus Remote Contributions of Soil Moisture to Near-Surface Temperature Variability

NASA Technical Reports Server (NTRS)

Koster, R.; Schubert, S.; Wang, H.; Chang, Y.

2018-01-01

Soil moisture variations have a straightforward impact on overlying air temperatures, wetter soils can induce higher evaporative cooling of the soil and thus, locally, cooler temperatures overall. Not known, however, is the degree to which soil moisture variations can affect remote air temperatures through their impact on the atmospheric circulation. In this talk we describe a two-pronged analysis that addresses this question. In the first segment, an extensive ensemble of NASA/GSFC GEOS-5 atmospheric model simulations is analyzed statistically to isolate and quantify the contributions of various soil moisture states, both local and remote, to the variability of air temperature at a given local site. In the second segment, the relevance of the derived statistical relationships is evaluated by applying them to observations-based data. Results from the second segment suggest that the GEOS-5-based relationships do, at least to first order, hold in nature and thus may provide some skill to forecasts of air temperature at subseasonal time scales, at least in certain regions.

A new mechanistic framework to predict OCS fluxes in soils

NASA Astrophysics Data System (ADS)

Sauze, Joana; Ogee, Jérôme; Launois, Thomas; Kesselmeier, Jürgen; Van Diest, Heidi; Wingate, Lisa

2015-04-01

A better description of the amplitude of photosynthetic and respiratory gross CO2 fluxes at large scales is needed to improve our predictions of the current and future global CO2 cycle. Carbonyl sulfide (COS) is the most abundant sulphur gas in the atmosphere and has been proposed as a new tracer of gross photosynthesis, as the uptake of COS from the atmosphere is dominated by the activity of carbonic anhydrase (CA), an enzyme abundant in leaves that also catalyses CO2 hydration during photosynthesis. However, soils also exchange COS with the atmosphere and there is growing evidence that this flux must also be accounted for in atmospheric budgets. In this context a new mechanistic description of soil-atmosphere COS exchange is clearly needed. Soils can take up COS from the atmosphere as the soil biota also contain CA, and COS emissions from soils have also been reported in agricultural fields or anoxic soils. Previous studies have also shown that soil COS fluxes present an optimum soil water content and soil temperature. Here we propose a new mechanistic framework to predict the fluxes of COS between the soils and the atmosphere. We describe the COS soil budget by a first-order reaction-diffusion-production equation, assuming that the hydrolysis of COS by CA is total and irreversible. To describe COS diffusion through the soil matrix, we use different formulations of soil air-filled pore space and temperature, depending on the turbulence level above the soil surface. Using this model we are able to explain the observed presence of an optimum temperature for soil COS uptake and show how this optimum can shift to cooler temperatures in the presence of soil COS emissions. Our model can also explain the observed optimum with soil moisture content previously described in the literature (e.g. Van Diest & Kesselmeier, 2008) as a result of diffusional constraints on COS hydrolysis. These diffusional constraints are also responsible for the response of COS uptake to soil weight and depth observed by Kesselmeier et al. (1999). In order to simulate the exact COS uptake rates and patterns observed on several soils collected from a range of biomes (Van Diest & Kesselmeier, 2008) different CA activities had to be evoked in each soil type, coherent with the expected soil microbial population size and diversity. A better description of the drivers governing soil CA activity and COS emissions from soils is needed before incorporating our new mechanistic model of soil-atmosphere COS uptake in large-scale ecosystem models and COS atmospheric budgets.

Simulation of nitrous oxide effluxes, crop yields and soil physical properties using the LandscapeDNDC model in managed ecosystem

NASA Astrophysics Data System (ADS)

Nyckowiak, Jedrzej; Lesny, Jacek; Haas, Edwin; Juszczak, Radoslaw; Kiese, Ralf; Butterbach-Bahl, Klaus; Olejnik, Janusz

2014-05-01

Modeling of nitrous oxide emissions from soil is very complex. Many different biological and chemical processes take place in soils which determine the amount of emitted nitrous oxide. Additionaly, biogeochemical models contain many detailed factors which may determine fluxes and other simulated variables. We used the LandscapeDNDC model in order to simulate N2O emissions, crop yields and soil physical properties from mineral cultivated soils in Poland. Nitrous oxide emissions from soils were modeled for fields with winter wheat, winter rye, spring barley, triticale, potatoes and alfalfa crops. Simulations were carried out for the plots of the Brody arable experimental station of Poznan University of Life Science in western Poland and covered the period 2003 - 2012. The model accuracy and its efficiency was determined by comparing simulations result with measurements of nitrous oxide emissions (measured with static chambers) from about 40 field campaigns. N2O emissions are strongly dependent on temperature and soil water content, hence we compared also simulated soil temperature at 10cm depth and soil water content at the same depth with the daily measured values of these driving variables. We compared also simulated yield quantities for each individual experimental plots with yield quantities which were measured in the period 2003-2012. We conclude that the LandscapeDNDC model is capable to simulate soil N2O emissions, crop yields and physical properties of soil with satisfactorily good accuracy and efficiency.

Potential Predictability of U.S. Summer Climate with "Perfect" Soil Moisture

NASA Technical Reports Server (NTRS)

Yang, Fanglin; Kumar, Arun; Lau, K.-M.

2004-01-01

The potential predictability of surface-air temperature and precipitation over the United States continent was assessed for a GCM forced by observed sea surface temperatures and an estimate of observed ground soil moisture contents. The latter was obtained by substituting the GCM simulated precipitation, which is used to drive the GCM's land-surface component, with observed pentad-mean precipitation at each time step of the model's integration. With this substitution, the simulated soil moisture correlates well with an independent estimate of observed soil moisture in all seasons over the entire US continent. Significant enhancements on the predictability of surface-air temperature and precipitation were found in boreal late spring and summer over the US continent. Anomalous pattern correlations of precipitation and surface-air temperature over the US continent in the June-July-August season averaged for the 1979-2000 period increased from 0.01 and 0.06 for the GCM simulations without precipitation substitution to 0.23 and 0.3 1, respectively, for the simulations with precipitation substitution. Results provide an estimate for the limits of potential predictability if soil moisture variability is to be perfectly predicted. However, this estimate may be model dependent, and needs to be substantiated by other modeling groups.

Modeling and risk assessment for soil temperatures beneath prescribed forest fires

Treesearch

Haiganoush K. Preisler; Sally M. Haase; Stephen S. Sackett

2000-01-01

Prescribed fire is a management tool used by wildland resource management organizations in many ecosystems to reduce hazardous fuels and to achieve a host of other objectives. To study the effects of fire in naturally accumulating fuel conditions, the ambient soil temperature is monitored beneath prescribed burns. In this study we developed a stochastic model for...

An Indirect Data Assimilation Scheme for Deep Soil Temperature in the Pleim-Xiu Land Surface Model

EPA Science Inventory

The Pleim-Xiu land surface model (PX LSM) has been improved by the addition of a 2nd indirect data assimilation scheme. The first, which was described previously, is a technique where soil moisture in nudged according to the biases in 2-m air temperature and relative humidity be...

Impact of aerodynamic resistance formulations used in two-source modeling of energy exchange from the soil and vegetation using land surface temperature

USDA-ARS?s Scientific Manuscript database

Application of the Two-Source Energy Balance (TSEB) Model using land surface temperature (LST) requires aerodynamic resistance parameterizations for the flux exchange above the canopy layer, within the canopy air space and at the soil/substrate surface. There are a number of aerodynamic resistance f...

Comparison of three approaches to model grapevine organogenesis in conditions of fluctuating temperature, solar radiation and soil water content.

PubMed

Pallas, B; Loi, C; Christophe, A; Cournède, P H; Lecoeur, J

2011-04-01

There is increasing interest in the development of plant growth models representing the complex system of interactions between the different determinants of plant development. These approaches are particularly relevant for grapevine organogenesis, which is a highly plastic process dependent on temperature, solar radiation, soil water deficit and trophic competition. The extent to which three plant growth models were able to deal with the observed plasticity of axis organogenesis was assessed. In the first model, axis organogenesis was dependent solely on temperature, through thermal time. In the second model, axis organogenesis was modelled through functional relationships linking meristem activity and trophic competition. In the last model, the rate of phytomer appearence on each axis was modelled as a function of both the trophic status of the plant and the direct effect of soil water content on potential meristem activity. The model including relationships between trophic competition and meristem behaviour involved a decrease in the root mean squared error (RMSE) for the simulations of organogenesis by a factor nine compared with the thermal time-based model. Compared with the model in which axis organogenesis was driven only by trophic competition, the implementation of relationships between water deficit and meristem behaviour improved organogenesis simulation results, resulting in a three times divided RMSE. The resulting model can be seen as a first attempt to build a comprehensive complete plant growth model simulating the development of the whole plant in fluctuating conditions of temperature, solar radiation and soil water content. We propose a new hypothesis concerning the effects of the different determinants of axis organogenesis. The rate of phytomer appearance according to thermal time was strongly affected by the plant trophic status and soil water deficit. Furthermore, the decrease in meristem activity when soil water is depleted does not result from source/sink imbalances.

Survey of in-situ and remote sensing methods for soil moisture determination

NASA Technical Reports Server (NTRS)

Schmugge, T. J.; Jackson, T. J.; Mckim, H. L.

1981-01-01

General methods for determining the moisture content in the surface layers of the soil based on in situ or point measurements, soil water models and remote sensing observations are surveyed. In situ methods described include gravimetric techniques, nuclear techniques based on neutron scattering or gamma-ray attenuation, electromagnetic techniques, tensiometric techniques and hygrometric techniques. Soil water models based on column mass balance treat soil moisture contents as a result of meteorological inputs (precipitation, runoff, subsurface flow) and demands (evaporation, transpiration, percolation). The remote sensing approaches are based on measurements of the diurnal range of surface temperature and the crop canopy temperature in the thermal infrared, measurements of the radar backscattering coefficient in the microwave region, and measurements of microwave emission or brightness temperature. Advantages and disadvantages of the various methods are pointed out, and it is concluded that a successful monitoring system must incorporate all of the approaches considered.

A MIXED MODEL ANALYSIS OF SOIL CO2 EFFLUX AND NIGHT-TIME RESPIRATION RESPONSES TO ELEVATED CO2 AND TEMPERATURE

EPA Science Inventory

Abstract: We investigated the effects of elevated soil temperature and atmospheric CO2 on soil CO2 efflux and system respiration responses. The study was conducted in sun-lit controlled-environment chambers using two-year-old Douglas-fir seedlings grown in reconstructed litter-so...

Bare soil respiration in a temperate climate: multiyear evaluation of a coupled CO2 transport and carbon turnover model

NASA Astrophysics Data System (ADS)

Herbst, M.; Hellebrand, H. J.; Bauer, J.; Vanderborght, J.; Vereecken, H.

2006-12-01

The modelling of soil respiration plays an important role in the prediction of climate change. Soil respiration is usually divided in autotrophic and heterotrophic fractions orginating from root respiration and microbial decomposition of soil organic carbon, respectively. We report on the coupling of a one dimensional water, heat and CO2 flux model (SOILCO2) with a model of carbon turnover (RothC) for the prediction of soil heterotrophic respiration. The coupled model was tested using soil temperature, soil moisture, and CO2 flux measurements in a bare soil experimental plot located in Bornim, Germany. A seven year record of soil and CO2 measurements covering a broad range of atmospheric and soil conditions was availabe to evaluate the model performance. After calibrating the decomposition rate constant of the humic fraction pool, the overall model performance on CO2 efflux prediction was acceptable. The root mean square error for the CO2 efflux prediction was 0.12 cm ³/cm ²/d. During the severe summer draught of 2003 very high CO2 efluxes were measured, which could not be explained by the model. Those high fluxes were attributed to a pressure pumping effect. The soil temperature dependency of CO2 production was well described by th e model, whereas the biggest opportunity for improvement is seen in a better description of the soil moisture dependency of CO2 production. The calibration of the humus decomposition rate constant revealed a value of 0.09 1/d, which is higher than the original value suggested by the RothC model developers but within the range of literature values.

Evaluation of the North American Land Data Assimilation System over the southern Great Plains during the warm season

NASA Astrophysics Data System (ADS)

Robock, Alan; Luo, Lifeng; Wood, Eric F.; Wen, Fenghua; Mitchell, Kenneth E.; Houser, Paul R.; Schaake, John C.; Lohmann, Dag; Cosgrove, Brian; Sheffield, Justin; Duan, Qingyun; Higgins, R. Wayne; Pinker, Rachel T.; Tarpley, J. Dan; Basara, Jeffery B.; Crawford, Kenneth C.

2003-11-01

North American Land Data Assimilation System (NLDAS) land surface models have been run for a retrospective period forced by atmospheric observations from the Eta analysis and actual precipitation and downward solar radiation to calculate land hydrology. We evaluated these simulations using in situ observations over the southern Great Plains for the periods of May-September of 1998 and 1999 by comparing the model outputs with surface latent, sensible, and ground heat fluxes at 24 Atmospheric Radiation Measurement/Cloud and Radiation Testbed stations and with soil temperature and soil moisture observations at 72 Oklahoma Mesonet stations. The standard NLDAS models do a fairly good job but with differences in the surface energy partition and in soil moisture between models and observations and among models during the summer, while they agree quite well on the soil temperature simulations. To investigate why, we performed a series of experiments accounting for differences between model-specified soil types and vegetation and those observed at the stations, and differences in model treatment of different soil types, vegetation properties, canopy resistance, soil column depth, rooting depth, root density, snow-free albedo, infiltration, aerodynamic resistance, and soil thermal diffusivity. The diagnosis and model enhancements demonstrate how the models can be improved so that they can be used in actual data assimilation mode.

Using a spatially-distributed hydrologic biogeochemistry model with nitrogen transport to study the spatial variation of carbon stocks and fluxes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; He, Y.; Davis, K. J.

2017-12-01

Most current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve topographically driven land surface heterogeneity (e.g., lateral water flow, soil moisture, soil temperature, solar radiation) or the spatial pattern of nutrient availability. A spatially distributed forest biogeochemical model with nitrogen transport, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM, and adding an advection dominated nitrogen transport module. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model, and is augmented by adding a topographic solar radiation module. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while nitrogen is transported among model grids via surface and subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation, while BBGC provides Flux-PIHM with spatially-distributed leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills Critical Zone Observatory. The model-predicted aboveground vegetation carbon and soil carbon distributions generally agree with the macro patterns observed within the watershed. The importance of abiotic variables (including soil moisture, soil temperature, solar radiation, and soil mineral nitrogen) in predicting aboveground carbon distribution is calculated using a random forest. The result suggests that the spatial pattern of aboveground carbon is controlled by the distribution of soil mineral nitrogen. A Flux-PIHM-BGC simulation without the nitrogen transport module is also executed. The model without nitrogen transport fails in predicting the spatial patterns of vegetation carbon, which indicates the importance of having a nitrogen transport module in spatially distributed ecohydrologic modeling.

Guiding Empirical and Theoretical Explorations of Organic Matter Decay By Synthesizing Temperature Responses of Enzyme Kinetics, Microbes, and Isotope Fluxes

NASA Astrophysics Data System (ADS)

Billings, S. A.; Ballantyne, F.; Lehmeier, C.; Min, K.

2014-12-01

Soil organic matter (SOM) transformation rates generally increase with temperature, but whether this is realized depends on soil-specific features. To develop predictive models applicable to all soils, we must understand two key, ubiquitous features of SOM transformation: the temperature sensitivity of myriad enzyme-substrate combinations and temperature responses of microbial physiology and metabolism, in isolation from soil-specific conditions. Predicting temperature responses of production of CO2 vs. biomass is also difficult due to soil-specific features: we cannot know the identity of active microbes nor the substrates they employ. We highlight how recent empirical advances describing SOM decay can help develop theoretical tools relevant across diverse spatial and temporal scales. At a molecular level, temperature effects on purified enzyme kinetics reveal distinct temperature sensitivities of decay of diverse SOM substrates. Such data help quantify the influence of microbial adaptations and edaphic conditions on decay, have permitted computation of the relative availability of carbon (C) and nitrogen (N) liberated upon decay, and can be used with recent theoretical advances to predict changes in mass specific respiration rates as microbes maintain biomass C:N with changing temperature. Enhancing system complexity, we can subject microbes to temperature changes while controlling growth rate and without altering substrate availability or identity of the active population, permitting calculation of variables typically inferred in soils: microbial C use efficiency (CUE) and isotopic discrimination during C transformations. Quantified declines in CUE with rising temperature are critical for constraining model CUE estimates, and known changes in δ13C of respired CO2 with temperature is useful for interpreting δ13C-CO2 at diverse scales. We suggest empirical studies important for advancing knowledge of how microbes respond to temperature, and ideas for theoretical work to enhance the relevance of such work to the world's soils.

Inversion of Farmland Soil Moisture in Large Region Based on Modified Vegetation Index

NASA Astrophysics Data System (ADS)

Wang, J. X.; Yu, B. S.; Zhang, G. Z.; Zhao, G. C.; He, S. D.; Luo, W. R.; Zhang, C. C.

2018-04-01

Soil moisture is an important parameter for agricultural production. Efficient and accurate monitoring of soil moisture is an important link to ensure the safety of agricultural production. Remote sensing technology has been widely used in agricultural moisture monitoring because of its timeliness, cyclicality, dynamic tracking of changes in things, easy access to data, and extensive monitoring. Vegetation index and surface temperature are important parameters for moisture monitoring. Based on NDVI, this paper introduces land surface temperature and average temperature for optimization. This article takes the soil moisture in winter wheat growing area in Henan Province as the research object, dividing Henan Province into three main regions producing winter wheat and dividing the growth period of winter wheat into the early, middle and late stages on the basis of phenological characteristics and regional characteristics. Introducing appropriate correction factor during the corresponding growth period of winter wheat, correcting the vegetation index in the corresponding area, this paper establishes regression models of soil moisture on NDVI and soil moisture on modified NDVI based on correlation analysis and compare models. It shows that modified NDVI is more suitable as a indicator of soil moisture because of the better correlation between soil moisture and modified NDVI and the higher prediction accuracy of the regression model of soil moisture on modified NDVI. The research in this paper has certain reference value for winter wheat farmland management and decision-making.

Assimilation of Freeze - Thaw Observations into the NASA Catchment Land Surface Model

NASA Technical Reports Server (NTRS)

Farhadi, Leila; Reichle, Rolf H.; DeLannoy, Gabrielle J. M.; Kimball, John S.

2014-01-01

The land surface freeze-thaw (F-T) state plays a key role in the hydrological and carbon cycles and thus affects water and energy exchanges and vegetation productivity at the land surface. In this study, we developed an F-T assimilation algorithm for the NASA Goddard Earth Observing System, version 5 (GEOS-5) modeling and assimilation framework. The algorithm includes a newly developed observation operator that diagnoses the landscape F-T state in the GEOS-5 Catchment land surface model. The F-T analysis is a rule-based approach that adjusts Catchment model state variables in response to binary F-T observations, while also considering forecast and observation errors. A regional observing system simulation experiment was conducted using synthetically generated F-T observations. The assimilation of perfect (error-free) F-T observations reduced the root-mean-square errors (RMSE) of surface temperature and soil temperature by 0.206 C and 0.061 C, respectively, when compared to model estimates (equivalent to a relative RMSE reduction of 6.7 percent and 3.1 percent, respectively). For a maximum classification error (CEmax) of 10 percent in the synthetic F-T observations, the F-T assimilation reduced the RMSE of surface temperature and soil temperature by 0.178 C and 0.036 C, respectively. For CEmax=20 percent, the F-T assimilation still reduces the RMSE of model surface temperature estimates by 0.149 C but yields no improvement over the model soil temperature estimates. The F-T assimilation scheme is being developed to exploit planned operational F-T products from the NASA Soil Moisture Active Passive (SMAP) mission.

HCMM energy budget data as a model input for assessing regions of high potential groundwater pollution. [South Dakota

NASA Technical Reports Server (NTRS)

Moore, D. G. (Principal Investigator); Heilman, J. L.

1980-01-01

The author has identified the following significant results. Day thermal data were analyzed to assess depth to groundwater in the test site. HCMM apparent temperature was corrected for atmospheric effects using lake temperature of the Oahe Reservoir in central South Dakota. Soil surface temperatures were estimated using an equation developed for ground studies. A significant relationship was found between surface soil temperature and depth to groundwater, as well as between the surface soil-maximum air temperature differential and soil water content (% of field capacity) in the 0 cm and 4 cm layer of the profile. Land use for the data points consisted of row crops, small grains, stubble, and pasture.

Uncertainties in the temperature sensitivity of decomposition in tropical and subtropical ecosystems: Implications for models

NASA Astrophysics Data System (ADS)

Holland, Elisabeth A.; Neff, Jason C.; Townsend, Alan R.; McKeown, Becky

2000-12-01

Tropical ecosystems play a central role in the global carbon cycle. Large changes in tropical temperature over geologic time and the significant responses of tropical ecosystems to shorter-term variations such as El Niño/La Niña argue for a robust understanding of the temperature sensitivity of tropical decomposition. To examine the responsiveness of heterotrophic respiration to temperature, we measured rates of heterotrophic respiration from a wide range of tropical soils in a series of laboratory incubations. Under conditions of optimal soil water and nonlimiting substrate availability, heterotrophic respiration rose exponentially with rising temperature. The meanQ10measured across all temperature ranges in these short-term incubations was 2.37, but there was significant variation inQ10s across sites. The source of this variation could not be explained by soil carbon or nitrogen content, soil texture, site climate, or lignin to nitrogen ratio. At the beginning of the incubation, heterotrophic respiration increased exponentially with temperature for all sites, despite the fact that the fluxes differed by an order of magnitude. When substrate availability became limiting later in the incubation, the temperature response changed, and heterotrophic response declined above 35°C. The documented changes in temperature sensitivity with substrate availability argue for using temperature relationships developed under optimal conditions of substrate availability for models which include temperature regulation of heterotrophic respiration. To evaluate the significance of this natural variation in temperature control over decomposition, we used the Century ecosystem model gridded for the areas between the tropics of Cancer and Capricorn. These simulations used the mean and upper and lower confidence limits of the normalized exponential temperature response of our experimental studies. We found that systems with the lowest temperature sensitivity accumulated a total of 70 Pg more carbon in soil organic carbon and respired 5.5 Pg yr-1 less carbon compared to the systems with the highest sensitivity.

Assimilation of Surface Temperature in Land Surface Models

NASA Technical Reports Server (NTRS)

Lakshmi, Venkataraman

1998-01-01

Hydrological models have been calibrated and validated using catchment streamflows. However, using a point measurement does not guarantee correct spatial distribution of model computed heat fluxes, soil moisture and surface temperatures. With the advent of satellites in the late 70s, surface temperature is being measured two to four times a day from various satellite sensors and different platforms. The purpose of this paper is to demonstrate use of satellite surface temperature in (a) validation of model computed surface temperatures and (b) assimilation of satellite surface temperatures into a hydrological model in order to improve the prediction accuracy of soil moistures and heat fluxes. The assimilation is carried out by comparing the satellite and the model produced surface temperatures and setting the "true"temperature midway between the two values. Based on this "true" surface temperature, the physical relationships of water and energy balance are used to reset the other variables. This is a case of nudging the water and energy balance variables so that they are consistent with each other and the true" surface temperature. The potential of this assimilation scheme is demonstrated in the form of various experiments that highlight the various aspects. This study is carried over the Red-Arkansas basin in the southern United States (a 5 deg X 10 deg area) over a time period of a year (August 1987 - July 1988). The land surface hydrological model is run on an hourly time step. The results show that satellite surface temperature assimilation improves the accuracy of the computed surface soil moisture remarkably.

Generation and mobility of radon in soil

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rose, A.W.; Jester, W.A.; Ciolkosz, E.J.

This study has confirmed large seasonal and daily variations of Rn in soil gas, developed models for the effects of temperature and moisture on air-water Rn partition, inhibited Rn diffusion from wet soil into sparse large air-filled pores and effects of diffusion into bedrock, demonstrated that organic matter is a major host for 226Ra in soils and that organic-bound Ra largely determines the proportion of 222Rn emanated to pore space, shown that in contrast 220Rn is emanated mainly from 224Ra in Fe-oxides, detected significant disequilibrium between 226Ra and 238U in organic matter and in some recent glacial soils, demonstrated bymore » computer models that air convection driven by temperature differences is expected in moderately permeable soils on hillsides.« less

Generation and mobility of radon in soil. Technical report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rose, A.W.; Jester, W.A.; Ciolkosz, E.J.

This study has confirmed large seasonal and daily variations of Rn in soil gas, developed models for the effects of temperature and moisture on air-water Rn partition, inhibited Rn diffusion from wet soil into sparse large air-filled pores and effects of diffusion into bedrock, demonstrated that organic matter is a major host for 226Ra in soils and that organic-bound Ra largely determines the proportion of 222Rn emanated to pore space, shown that in contrast 220Rn is emanated mainly from 224Ra in Fe-oxides, detected significant disequilibrium between 226Ra and 238U in organic matter and in some recent glacial soils, demonstrated bymore » computer models that air convection driven by temperature differences is expected in moderately permeable soils on hillsides.« less

Modeling short-term concentration fluctuations of semi-volatile pollutants in the soil-plant-atmosphere system.

PubMed

Bao, Zhongwen; Haberer, Christina M; Maier, Uli; Beckingham, Barbara; Amos, Richard T; Grathwohl, Peter

2016-11-01

Temperature changes can drive cycling of semi-volatile pollutants between different environmental compartments (e.g. atmosphere, soil, plants). To evaluate the impact of daily temperature changes on atmospheric concentration fluctuations we employed a physically based model coupling soil, plants and the atmosphere, which accounts for heat transport, effective gas diffusion, sorption and biodegradation in the soil as well as eddy diffusion and photochemical oxidation in the atmospheric boundary layer of varying heights. The model results suggest that temperature-driven re-volatilization and uptake in soils cannot fully explain significant diurnal concentration fluctuations of atmospheric pollutants as for example observed for polychlorinated biphenyls (PCBs). This holds even for relatively low water contents (high gas diffusivity) and high sorption capacity of the topsoil (high organic carbon content and high pollutant concentration in the topsoil). Observed concentration fluctuations, however, can be easily matched if a rapidly-exchanging environmental compartment, such as a plant layer, is introduced. At elevated temperatures, plants release organic pollutants, which are rapidly distributed in the atmosphere by eddy diffusion. For photosensitive compounds, e.g. some polycyclic aromatic hydrocarbons (PAHs), decreasing atmospheric concentrations would be expected during daytime for the bare soil scenario. This decline is buffered by a plant layer, which acts as a ground-level reservoir. The modeling results emphasize the importance of a rapidly-exchanging compartment above ground to explain short-term atmospheric concentration fluctuations. Copyright © 2016 Elsevier B.V. All rights reserved.

A model for evaluating stream temperature response to climate change scenarios in Wisconsin

USGS Publications Warehouse

Westenbroek, Stephen M.; Stewart, Jana S.; Buchwald, Cheryl A.; Mitro, Matthew G.; Lyons, John D.; Greb, Steven

2010-01-01

Global climate change is expected to alter temperature and flow regimes for streams in Wisconsin over the coming decades. Stream temperature will be influenced not only by the predicted increases in average air temperature, but also by changes in baseflow due to changes in precipitation patterns and amounts. In order to evaluate future stream temperature and flow regimes in Wisconsin, we have integrated two existing models in order to generate a water temperature time series at a regional scale for thousands of stream reaches where site-specific temperature observations do not exist. The approach uses the US Geological Survey (USGS) Soil-Water-Balance (SWB) model, along with a recalibrated version of an existing artificial neural network (ANN) stream temperature model. The ANN model simulates stream temperatures on the basis of landscape variables such as land use and soil type, and also includes climate variables such as air temperature and precipitation amounts. The existing ANN model includes a landscape variable called DARCY designed to reflect the potential for groundwater recharge in the contributing area for a stream segment. SWB tracks soil-moisture and potential recharge at a daily time step, providing a way to link changing climate patterns and precipitation amounts over time to baseflow volumes, and presumably to stream temperatures. The recalibrated ANN incorporates SWB-derived estimates of potential recharge to supplement the static estimates of groundwater flow potential derived from a topographically based model (DARCY). SWB and the recalibrated ANN will be supplied with climate drivers from a suite of general circulation models and emissions scenarios, enabling resource managers to evaluate possible changes in stream temperature regimes for Wisconsin.

An update on remote measurement of soil moisture over vegetation using infrared temperature measurements: A FIFE perspective

NASA Technical Reports Server (NTRS)

Carlson, Toby N.

1988-01-01

Using model development, image analysis and micrometeorological measurements, the object is to push beyond the present limitations of using the infrared temperature method for remotely determining surface energy fluxes and soil moisture over vegetation. Model development consists of three aspects: (1) a more complex vegetation formulation which is more flexible and realistic; (2) a method for modeling the fluxes over patchy vegetation cover; and (3) a method for inferring a two-layer soil vertical moisture gradient from analyses of horizontal variations in surface temperatures. HAPEX and FIFE satellite data will be used along with aircraft thermal infrared and solar images as input for the models. To test the models, moisture availability and bulk canopy resistances will be calculated from data collected locally at the Rock Springs experimental field site and, eventually, from the FIFE project.

The relative importance of physical erosion and soil water dynamics on chemical weathering and soil formation: learning from field and model results

NASA Astrophysics Data System (ADS)

Vanwalleghem, T.; Román, A.; Giraldez, J. V.

2015-12-01

A new model is presented that integrates the effect of landscape evolution and soil formation. This model is based on a daily spatially-explicit soil water balance. Average soil water content, temperature and deep percolation fluxes are linked to weathering and soil formation processes. Model input (temperature and precipitation) for the last 25 000 years was generated on a daily time by combining palaeoclimate data and the WXGEN weather generator. The soil-landscape model was applied to a 48 km2 semi-natural catchment in Southern Spain, with soils developed on granite. Model-generated runoff was used for a first validation against discharge observations. Next, soil formation output was contrasted against experimental data from 10 soil profiles along two catenas. Field data showed an important variation in mobile regolith thickness, between 0,44 and 1,10m, and in chemical weathering along the catena. Southern slopes were characterized by shallower, stonier and carbon-poor soils, while soils on north-facing slopes were deeper, more fine-textured and had a higher carbon content. Chemical depletion fraction was found to vary between 0,41 and 0,72. The lowest overall weathering intensity was found on plateau positions. South facing slopes revealed slightly lower weathering compared to north facing slopes. We attribute this to higher runoff generation and physical erosion rates on north facing slopes, transporting weathered material downslope. Model results corroborate these findings and show continuously wet soils on north-facing slopes with more runoff generation and a steady deep percolation flux during the wet winter season. On south-facing slopes, infiltration is higher and percolation is more erratic over time. Soils on the footslopes then were shown to be significantly impacted by deposition of sediment through lateral erosion fluxes.

Soil warming increases metabolic quotients of soil microorganisms without changes in temperature sensitivity of soil respiration

NASA Astrophysics Data System (ADS)

Marañón-Jiménez, Sara; Soong, Jenniffer L.; Leblans, Niki I. W.; Sigurdsson, Bjarni D.; Dauwe, Steven; Fransen, Erik; Janssens, Ivan A.

2017-04-01

Increasing temperatures can accelerate soil organic matter (SOM) decomposition and release large amounts of CO2 to the atmosphere, potentially inducing climate change feedbacks. Alterations to the temperature sensitivity and metabolic pathways of soil microorganisms in response to soil warming can play a key role in these soil carbon (C) losses. Here, we present results of an incubation experiment using soils from a geothermal gradient in Iceland that have been subjected to different intensities of soil warming (+0, +1, +3, +5, +10 and +20 °C above ambient) over seven years. We hypothesized that 7 years of soil warming would led to a depletion of labile organic substrates, with a subsequent decrease of the "apparent" temperature sensitivity of soil respiration. Associated to this C limitation and more sub-optimal conditions for microbial growth, we also hypothesized increased microbial metabolic quotients (soil respiration per unit of microbial biomass), which is associated with increases in the relative amount of C invested into catabolic pathways along the warming gradient. Soil respiration and basal respiration rates decreased with soil warming intensity, in parallel with a decline in soil C availability. Contrasting to our first hypothesis, we did not detect changes in the temperature sensitivity of soil respiration with soil warming or on the availability of nutrients and of labile C substrates at the time of incubation. However, in agreement to our second hypothesis, microbial metabolic quotients (soil respiration per unit of microbial biomass) increased at warmer temperatures, while the C retained in biomass decreased as substrate became limiting. Long-term (7 years) temperature increases thus triggered a change in the metabolic functioning of the soil microbial communities towards increasing energy costs for maintenance or resource acquisition, thereby lowering the capacity of C retention and stabilization of warmed soils. These results highlight the need to incorporate the potential changes in microbial physiological functioning into models, in order to accurately predict future changes in soil C stocks in response to global warming.

Exploring the Influence of Topography on Belowground C Processes Using a Coupled Hydrologic-Biogeochemical Model

NASA Astrophysics Data System (ADS)

Shi, Y.; Davis, K. J.; Eissenstat, D. M.; Kaye, J. P.; Duffy, C.; Yu, X.; He, Y.

2014-12-01

Belowground carbon processes are affected by soil moisture and soil temperature, but current biogeochemical models are 1-D and cannot resolve topographically driven hill-slope soil moisture patterns, and cannot simulate the nonlinear effects of soil moisture on carbon processes. Coupling spatially-distributed physically-based hydrologic models with biogeochemical models may yield significant improvements in the representation of topographic influence on belowground C processes. We will couple the Flux-PIHM model to the Biome-BGC (BBGC) model. Flux-PIHM is a coupled physically-based land surface hydrologic model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Because PIHM is capable of simulating lateral water flow and deep groundwater, Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. The coupled Flux-PIHM-BBGC model will be tested at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). The abundant observations, including eddy covariance fluxes, soil moisture, groundwater level, sap flux, stream discharge, litterfall, leaf area index, above ground carbon stock, and soil carbon efflux, make SSHCZO an ideal test bed for the coupled model. In the coupled model, each Flux-PIHM model grid will couple a BBGC cell. Flux-PIHM will provide BBGC with soil moisture and soil temperature information, while BBGC provides Flux-PIHM with leaf area index. Preliminary results show that when Biome- BGC is driven by PIHM simulated soil moisture pattern, the simulated soil carbon is clearly impacted by topography.

Research on the Effects of Drying Temperature on Nitrogen Detection of Different Soil Types by Near Infrared Sensors.

PubMed

Nie, Pengcheng; Dong, Tao; He, Yong; Xiao, Shupei

2018-01-29

Soil is a complicated system whose components and mechanisms are complex and difficult to be fully excavated and comprehended. Nitrogen is the key parameter supporting plant growth and development, and is the material basis of plant growth as well. An accurate grasp of soil nitrogen information is the premise of scientific fertilization in precision agriculture, where near infrared sensors are widely used for rapid detection of nutrients in soil. However, soil texture, soil moisture content and drying temperature all affect soil nitrogen detection using near infrared sensors. In order to investigate the effects of drying temperature on the nitrogen detection in black soil, loess and calcium soil, three kinds of soils were detected by near infrared sensors after 25 °C placement (ambient temperature), 50 °C drying (medium temperature), 80 °C drying (medium-high temperature) and 95 °C drying (high temperature). The successive projections algorithm based on multiple linear regression (SPA-MLR), partial least squares (PLS) and competitive adaptive reweighted squares (CARS) were used to model and analyze the spectral information of different soil types. The predictive abilities were assessed using the prediction correlation coefficients (R P ), the root mean squared error of prediction (RMSEP), and the residual predictive deviation (RPD). The results showed that the loess (R P = 0.9721, RMSEP = 0.067 g/kg, RPD = 4.34) and calcium soil (R P = 0.9588, RMSEP = 0.094 g/kg, RPD = 3.89) obtained the best prediction accuracy after 95 °C drying. The detection results of black soil (R P = 0.9486, RMSEP = 0.22 g/kg, RPD = 2.82) after 80 °C drying were the optimum. In conclusion, drying temperature does have an obvious influence on the detection of soil nitrogen by near infrared sensors, and the suitable drying temperature for different soil types was of great significance in enhancing the detection accuracy.

Enhanced simulations of CH4 and CO2 production in permafrost-affected soils address soil moisture controls on anaerobic decomposition

NASA Astrophysics Data System (ADS)

Graham, D. E.; Zheng, J.; Moon, J. W.; Painter, S. L.; Thornton, P. E.; Gu, B.; Wullschleger, S. D.

2017-12-01

Rapid warming of Arctic ecosystems exposes soil organic carbon (SOC) to accelerated microbial decomposition, leading to increased emissions of carbon dioxide (CO2) and methane (CH4) that have a positive feedback on global warming. The magnitude, timing, and form of carbon release will depend not only on changes in temperature, but also on biogeochemical and hydrological properties of soils. In this synthesis study, we assessed the decomposability of thawed organic carbon from active layer soils and permafrost from the Barrow Environmental Observatory across different microtopographic positions under anoxic conditions. The main objectives of this study were to (i) examine environmental conditions and soil properties that control anaerobic carbon decomposition and carbon release (as both CO2 and CH4); (ii) develop a common set of parameters to simulate anaerobic CO2 and CH4 production; and (iii) evaluate uncertainties generated from representations of pH and temperature effects in the current model framework. A newly developed anaerobic carbon decomposition framework simulated incubation experiment results across a range of soil water contents. Anaerobic CO2 and CH4 production have different temperature and pH sensitivities, which are not well represented in current biogeochemical models. Distinct dynamics of CH4 production at -2° C suggest methanogen biomass and growth rate limit activity in these near-frozen soils, compared to warmer temperatures. Anaerobic CO2 production is well constrained by the model using data-informed labile carbon pool and fermentation rate initialization to accurately simulate its temperature sensitivity. On the other hand, CH4 production is controlled by water content, methanogenesis biomass, and the presence of alternative electron acceptors, producing a high temperature sensitivity with large uncertainties for methanogenesis. This set of environmental constraints to methanogenesis is likely to undergo drastic changes due to permafrost thawing, and extrapolation of methanogenesis rates into a future warmer climate remains challenging.

Results from Assimilating AMSR-E Soil Moisture Estimates into a Land Surface Model Using an Ensemble Kalman Filter in the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Crosson, William L.; Case, Jonathan L.; Hale, Robert

2010-01-01

Improve simulations of soil moisture/temperature, and consequently boundary layer states and processes, by assimilating AMSR-E soil moisture estimates into a coupled land surface-mesoscale model Provide a new land surface model as an option in the Land Information System (LIS)

HCMM energy budget data as a model input for assessing regions of high potential groundwater pollution. [South Dakota

NASA Technical Reports Server (NTRS)

Moore, D. G. (Principal Investigator); Heilman, J. L.

1980-01-01

The author has identified the following significant results. Significant relationships were found between surface soil temperatures estimated from HCMM radiometric temperatures and depth to ground water and near surface soil moisture.

Exploring the sensitivity of soil carbon dynamics to climate change, fire disturbance and permafrost thaw in a black spruce ecosystem

Treesearch

J.A. O' Donnell; J.W. Harden; A.D. McGuire; V.E. Romanovsky

2011-01-01

In the boreal region, soil organic carbon (OC) dynamics are strongly governed by the interaction between wildfire and permafrost. Using a combination of field measurements, numerical modeling of soil thermal dynamics, and mass-balance modeling of OC dynamics, we tested the sensitivity of soil OC storage to a suite of individual climate factors (air temperature, soil...

Thermogravimetric study of thermal decontamination of soils polluted by hexachlorobenzene, 4-chlorobiphenyl, naphthalene, or n-decane.

PubMed

Risoul, V; Pichon, C; Trouvé, G; Peters, W A; Gilot, P; Prado, G

1999-02-15

To determine decontamination behavior as affected by temperature, shallow beds of a clay-rich, a calcerous, and a sedimentary soil, artificially polluted with hexachlorobenzene, 4-chlorobiphenyl, naphthalene, or n-decane, were separately heated at 5 degrees C min-1 in a thermogravimetric analyzer. Temperatures for deep cleaning of the calcerous and the sedimentary soil increased with increasing boiling point (bp) of the aromatic contaminants, but removal efficiencies still approached 100% well below the bp. Decontamination rates were therefore modelled according to a pollutant evaporation-diffusion transport model. For the calcerous and sedimentary soils, this model reasonably correlated removal of roughly the first 2/3 of the naphthalene, but gave only fair predictions for hexachlorobenzene and 4-chlorobiphenyl. It was necessary to heat the clay soil above the aromatics bp to achieve high decontamination efficiencies. Weight loss data imply that for temperatures from near ambient to as much as 150 degrees C, interactions of each aromatic with the clay soil, or its decomposition products, result in lower net volatilization of the contaminated vs. neat clay. A similar effect was observed in heating calcerous soil polluted with hexachlorobenzene from near ambient to about 140 degrees C. Decontamination mechanisms remain to be established, although the higher temperatures needed to remove aromatics from the clay may reflect a more prominent role for surface desorption than evaporation. This would be consistent with our estimates that the clay can accommodate all of the initial pollutant loadings within a single surface monolayer, whereas the calcerous and sedimentary soils cannot.

Modelling the sensitivity of soil mercury storage to climate-induced changes in soil carbon pools

NASA Astrophysics Data System (ADS)

Hararuk, O.; Obrist, D.; Luo, Y.

2013-04-01

Substantial amounts of mercury (Hg) in the terrestrial environment reside in soils and are associated with soil organic carbon (C) pools, where they accumulated due to increased atmospheric deposition resulting from anthropogenic activities. The purpose of this study was to examine potential sensitivity of surface soil Hg pools to global change variables, particularly affected by predicted changes in soil C pools, in the contiguous US. To investigate, we included a soil Hg component in the Community Land Model based on empirical statistical relationships between soil Hg / C ratios and precipitation, latitude, and clay; and subsequently explored the sensitivity of soil C and soil Hg densities (i.e., areal-mass) to climate scenarios in which we altered annual precipitation, carbon dioxide (CO2) concentrations and temperature. Our model simulations showed that current sequestration of Hg in the contiguous US accounted for 15 230 metric tons of Hg in the top 0-40 cm of soils, or for over 300 000 metric tons when extrapolated globally. In the simulations, US soil Hg pools were most sensitive to changes in precipitation because of strong effects on soil C pools, plus a direct effect of precipitation on soil Hg / C ratios. Soil Hg pools were predicted to increase beyond present-day values following an increase in precipitation amounts and decrease following a reduction in precipitation. We found pronounced regional differences in sensitivity of soil Hg to precipitation, which were particularly high along high-precipitation areas along the West and East Coasts. Modelled increases in CO2 concentrations to 700 ppm stimulated soil C and Hg accrual, while increased air temperatures had small negative effects on soil C and Hg densities. The combined effects of increased CO2, increased temperature and increased or decreased precipitation were strongly governed by precipitation and CO2 showing pronounced regional patterns. Based on these results, we conclude that the combination of precipitation and CO2 should be emphasised when assessing how climate-induced changes in soil C may affect sequestration of Hg in soils.

Predicting key malaria transmission factors, biting and entomological inoculation rates, using modelled soil moisture in Kenya.

PubMed

Patz, J A; Strzepek, K; Lele, S; Hedden, M; Greene, S; Noden, B; Hay, S I; Kalkstein, L; Beier, J C

1998-10-01

While malaria transmission varies seasonally, large inter-annual heterogeneity of malaria incidence occurs. Variability in entomological parameters, biting rates and entomological inoculation rates (EIR) have been strongly associated with attack rates in children. The goal of this study was to assess the weather's impact on weekly biting and EIR in the endemic area of Kisian, Kenya. Entomological data collected by the U.S. Army from March 1986 through June 1988 at Kisian, Kenya was analysed with concurrent weather data from nearby Kisumu airport. A soil moisture model of surface-water availability was used to combine multiple weather parameters with landcover and soil features to improve disease prediction. Modelling soil moisture substantially improved prediction of biting rates compared to rainfall; soil moisture lagged two weeks explained up to 45% of An. gambiae biting variability, compared to 8% for raw precipitation. For An. funestus, soil moisture explained 32% variability, peaking after a 4-week lag. The interspecies difference in response to soil moisture was significant (P < 0.00001). A satellite normalized differential vegetation index (NDVI) of the study site yielded a similar correlation (r = 0.42 An. gambiae). Modelled soil moisture accounted for up to 56% variability of An. gambiae EIR, peaking at a lag of six weeks. The relationship between temperature and An. gambiae biting rates was less robust; maximum temperature r2 = -0.20, and minimum temperature r2 = 0.12 after lagging one week. Benefits of hydrological modelling are compared to raw weather parameters and to satellite NDVI. These findings can improve both current malaria risk assessments and those based on El Niño forecasts or global climate change model projections.

Modeling soil respiration and variations of source components using a multi-factor global climate change experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Xiongwen; Post, Wilfred M; Norby, Richard J

2011-01-01

Soil respiration is an important component of the global carbon cycle and is highly responsive to changes in soil temperature and moisture. Accurate prediction of soil respiration and its changes under future climatic conditions requires a clear understanding of the processes involved. In spite of this, most current empirical soil respiration models incorporate just few of the underlying mechanisms that may influence its response. In this study, a new partial process-based component model built on source components of soil respiration was tested using data collected from a multi-factor climate change experiment that manipulates CO2 concentrations, temperature and precipitation. These resultsmore » were then compared to results generated using several other established models. The component model we tested performed well across different treatments of global climate change. In contrast, some other models, which worked well predicting ambient environmental conditions, were unable to predict the changes under different climate change treatments. Based on the component model, the relative proportions of heterotrophic respiration (Rh) in the total soil respiration at different treatments varied from 0.33 to 0.85. There is a significant increase in the proportion of Rh under the elevated atmospheric CO2 concentration in comparison ambient conditions. The dry treatment resulted in higher proportion of Rh at elevated CO2 and ambient T than under elevated CO2 and elevated T. Also, the ratios between root growth and root maintenance respiration varied across different treatments. Neither increased temperature nor elevated atmospheric CO2 changed Q10 values significantly, while the average Q10 value at wet sites was significantly higher than it at dry sites. There was a higher possibility of increased soil respiration under drying relative to wetting conditions across all treatments based on monthly data, indicating that soil respiration may also be related to soil moisture at previous time periods. Our results reveal that the extent, time delay and contribution of different source components need to be included into mechanistic/processes-based soil respiration models at corresponding scale.« less

A Model of Thermal Conductivity for Planetary Soils: 1. Theory for Unconsolidated Soils

NASA Technical Reports Server (NTRS)

Piqueux, S.; Christensen, P. R.

2009-01-01

We present a model of heat conduction for mono-sized spherical particulate media under stagnant gases based on the kinetic theory of gases, numerical modeling of Fourier s law of heat conduction, theoretical constraints on the gas thermal conductivity at various Knudsen regimes, and laboratory measurements. Incorporating the effect of the temperature allows for the derivation of the pore-filling gas conductivity and bulk thermal conductivity of samples using additional parameters (pressure, gas composition, grain size, and porosity). The radiative and solid-to-solid conductivities are also accounted for. Our thermal model reproduces the well-established bulk thermal conductivity dependency of a sample with the grain size and pressure and also confirms laboratory measurements finding that higher porosities generally lead to lower conductivities. It predicts the existence of the plateau conductivity at high pressure, where the bulk conductivity does not depend on the grain size. The good agreement between the model predictions and published laboratory measurements under a variety of pressures, temperatures, gas compositions, and grain sizes provides additional confidence in our results. On Venus, Earth, and Titan, the pressure and temperature combinations are too high to observe a soil thermal conductivity dependency on the grain size, but each planet has a unique thermal inertia due to their different surface temperatures. On Mars, the temperature and pressure combination is ideal to observe the soil thermal conductivity dependency on the average grain size. Thermal conductivity models that do not take the temperature and the pore-filling gas composition into account may yield significant errors.

Design of a global soil moisture initialization procedure for the simple biosphere model

NASA Technical Reports Server (NTRS)

Liston, G. E.; Sud, Y. C.; Walker, G. K.

1993-01-01

Global soil moisture and land-surface evapotranspiration fields are computed using an analysis scheme based on the Simple Biosphere (SiB) soil-vegetation-atmosphere interaction model. The scheme is driven with observed precipitation, and potential evapotranspiration, where the potential evapotranspiration is computed following the surface air temperature-potential evapotranspiration regression of Thomthwaite (1948). The observed surface air temperature is corrected to reflect potential (zero soil moisture stress) conditions by letting the ratio of actual transpiration to potential transpiration be a function of normalized difference vegetation index (NDVI). Soil moisture, evapotranspiration, and runoff data are generated on a daily basis for a 10-year period, January 1979 through December 1988, using observed precipitation gridded at a 4 deg by 5 deg resolution.

A simplified, data-constrained approach to estimate the permafrost carbon-climate feedback: The PCN Incubation-Panarctic Thermal (PInc-PanTher) Scaling Approach

NASA Astrophysics Data System (ADS)

Koven, C. D.; Schuur, E.; Schaedel, C.; Bohn, T. J.; Burke, E.; Chen, G.; Chen, X.; Ciais, P.; Grosse, G.; Harden, J. W.; Hayes, D. J.; Hugelius, G.; Jafarov, E. E.; Krinner, G.; Kuhry, P.; Lawrence, D. M.; MacDougall, A.; Marchenko, S. S.; McGuire, A. D.; Natali, S.; Nicolsky, D.; Olefeldt, D.; Peng, S.; Romanovsky, V. E.; Schaefer, K. M.; Strauss, J.; Treat, C. C.; Turetsky, M. R.

2015-12-01

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation-Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a 3-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100.

Land surface dynamics monitoring using microwave passive satellite sensors

NASA Astrophysics Data System (ADS)

Guijarro, Lizbeth Noemi

Soil moisture, surface temperature and vegetation are variables that play an important role in our environment. There is growing demand for accurate estimation of these geophysical parameters for the research of global climate models (GCMs), weather, hydrological and flooding models, and for the application to agricultural assessment, land cover change, and a wide variety of other uses that meet the needs for the study of our environment. The different studies covered in this dissertation evaluate the capabilities and limitations of microwave passive sensors to monitor land surface dynamics. The first study evaluates the 19 GHz channel of the SSM/I instrument with a radiative transfer model and in situ datasets from the Illinois stations and the Oklahoma Mesonet to retrieve land surface temperature and surface soil moisture. The surface temperatures were retrieved with an average error of 5 K and the soil moisture with an average error of 6%. The results show that the 19 GHz channel can be used to qualitatively predict the spatial and temporal variability of surface soil moisture and surface temperature at regional scales. In the second study, in situ observations were compared with sensor observations to evaluate aspects of low and high spatial resolution at multiple frequencies with data collected from the Southern Great Plains Experiment (SGP99). The results showed that the sensitivity to soil moisture at each frequency is a function of wavelength and amount of vegetation. The results confirmed that L-band is more optimal for soil moisture, but each sensor can provide soil moisture information if the vegetation water content is low. The spatial variability of the emissivities reveals that resolution suffers considerably at higher frequencies. The third study evaluates C- and X-bands of the AMSR-E instrument. In situ datasets from the Soil Moisture Experiments (SMEX03) in South Central Georgia were utilized to validate the AMSR-E soil moisture product and to derive surface soil moisture with a radiative transfer model. The soil moisture was retrieved with an average error of 2.7% at X-band and 6.7% at C-band. The AMSR-E demonstrated its ability to successfully infer soil moisture during the SMEX03 experiment.

Improved Seasonal Prediction of European Summer Temperatures With New Five-Layer Soil-Hydrology Scheme

NASA Astrophysics Data System (ADS)

Bunzel, Felix; Müller, Wolfgang A.; Dobrynin, Mikhail; Fröhlich, Kristina; Hagemann, Stefan; Pohlmann, Holger; Stacke, Tobias; Baehr, Johanna

2018-01-01

We evaluate the impact of a new five-layer soil-hydrology scheme on seasonal hindcast skill of 2 m temperatures over Europe obtained with the Max Planck Institute Earth System Model (MPI-ESM). Assimilation experiments from 1981 to 2010 and 10-member seasonal hindcasts initialized on 1 May each year are performed with MPI-ESM in two soil configurations, one using a bucket scheme and one a new five-layer soil-hydrology scheme. We find the seasonal hindcast skill for European summer temperatures to improve with the five-layer scheme compared to the bucket scheme and investigate possible causes for these improvements. First, improved indirect soil moisture assimilation allows for enhanced soil moisture-temperature feedbacks in the hindcasts. Additionally, this leads to improved prediction of anomalies in the 500 hPa geopotential height surface, reflecting more realistic atmospheric circulation patterns over Europe.

Temporal and spatial variability of soil biological activity at European scale

NASA Astrophysics Data System (ADS)

Mallast, Janine; Rühlmann, Jörg

2015-04-01

The CATCH-C project aims to identify and improve the farm-compatibility of Soil Management Practices including to promote productivity, climate change mitigation and soil quality. The focus of this work concentrates on turnover conditions for soil organic matter (SOM). SOM is fundamental for the maintenance of quality and functions of soils while SOM storage is attributed a great importance in terms of climate change mitigation. The turnover conditions depend on soil biological activity characterized by climate and soil properties. Soil biological activity was investigated using two model concepts: a) Re_clim parameter within the ICBM (Introductory Carbon Balance Model) (Andrén & Kätterer 1997) states a climatic factor summarizing soil water storage and soil temperature and its influence on soil biological activity. b) BAT (biological active time) approach derived from model CANDY (CArbon and Nitrogen Dynamic) (Franko & Oelschlägel 1995) expresses the variation of soil moisture, soil temperature and soil aeration as a time scale and an indicator of biological activity for soil organic matter (SOM) turnover. During an earlier stage both model concepts, Re_clim and BAT, were applied based on a monthly data to assess spatial variability of turnover conditions across Europe. This hampers the investigation of temporal variability (e.g. intra-annual). The improved stage integrates daily data of more than 350 weather stations across Europe presented by Klein Tank et al. (2002). All time series data (temperature, precipitation and potential evapotranspiration and soil texture derived from the European Soil Database (JRC 2006)), are used to calculate soil biological activity in the arable layer. The resulting BAT and Re_clim values were spatio-temporal investigated. While "temporal" refers to a long-term trend analysis, "spatial" includes the investigation of soil biological activity variability per environmental zone (ENZ, Metzger et al. 2005 representing similar conditions for precipitation, temperature and relief) to identify ranges and hence turnover conditions for each ENZ. We will discuss the analyzed results of both concepts to assess SOM turnover conditions across Europe for historical weather data and for Spain focusing on climate scenarios. Both concepts help to separate different turnover activities and to indicate organic matter input in order to maintain the given SOM. The assessment could provide recommendations for adaptations of soil management practices. CATCH-C is funded within the 7th Framework Programme for Research, Technological Development and Demonstration, Theme 2 - Biotechnologies, Agriculture & Food (Grant Agreement N° 289782).

Water and heat transport in boreal soils: Implications for soil response to climate change

USGS Publications Warehouse

Fan, Z.; Neff, J.C.; Harden, J.W.; Zhang, T.; Veldhuis, H.; Czimczik, C.I.; Winston, G.C.; O'Donnell, J. A.

2011-01-01

Soil water content strongly affects permafrost dynamics by changing the soil thermal properties. However, the movement of liquid water, which plays an important role in the heat transport of temperate soils, has been under-represented in boreal studies. Two different heat transport models with and without convective heat transport were compared to measurements of soil temperatures in four boreal sites with different stand ages and drainage classes. Overall, soil temperatures during the growing season tended to be over-estimated by 2-4??C when movement of liquid water and water vapor was not represented in the model. The role of heat transport in water has broad implications for site responses to warming and suggests reduced vulnerability of permafrost to thaw at drier sites. This result is consistent with field observations of faster thaw in response to warming in wet sites compared to drier sites over the past 30. years in Canadian boreal forests. These results highlight that representation of water flow in heat transport models is important to simulate future soil thermal or permafrost dynamics under a changing climate. ?? 2011 Elsevier B.V.

Water and heat transport in boreal soils: Implications for soil response to climate change

USGS Publications Warehouse

Fan, Zhaosheng; Harden, Jennifer W.; Winston, G.C.; O'Donnell, Jonathan A.; Neff, Jason C.; Zhang, Tingjun; Veldhuis, Hugo; Czimczik, C.I.

2011-01-01

Soil water content strongly affects permafrost dynamics by changing the soil thermal properties. However, the movement of liquid water, which plays an important role in the heat transport of temperate soils, has been under-represented in boreal studies. Two different heat transport models with and without convective heat transport were compared to measurements of soil temperatures in four boreal sites with different stand ages and drainage classes. Overall, soil temperatures during the growing season tended to be over-estimated by 2–4 °C when movement of liquid water and water vapor was not represented in the model. The role of heat transport in water has broad implications for site responses to warming and suggests reduced vulnerability of permafrost to thaw at drier sites. This result is consistent with field observations of faster thaw in response to warming in wet sites compared to drier sites over the past 30 years in Canadian boreal forests. These results highlight that representation of water flow in heat transport models is important to simulate future soil thermal or permafrost dynamics under a changing climate.

SMOS brightness temperature assimilation into the Community Land Model

NASA Astrophysics Data System (ADS)

Rains, Dominik; Han, Xujun; Lievens, Hans; Montzka, Carsten; Verhoest, Niko E. C.

2017-11-01

SMOS (Soil Moisture and Ocean Salinity mission) brightness temperatures at a single incident angle are assimilated into the Community Land Model (CLM) across Australia to improve soil moisture simulations. Therefore, the data assimilation system DasPy is coupled to the local ensemble transform Kalman filter (LETKF) as well as to the Community Microwave Emission Model (CMEM). Brightness temperature climatologies are precomputed to enable the assimilation of brightness temperature anomalies, making use of 6 years of SMOS data (2010-2015). Mean correlation R with in situ measurements increases moderately from 0.61 to 0.68 (11 %) for upper soil layers if the root zone is included in the updates. A reduced improvement of 5 % is achieved if the assimilation is restricted to the upper soil layers. Root-zone simulations improve by 7 % when updating both the top layers and root zone, and by 4 % when only updating the top layers. Mean increments and increment standard deviations are compared for the experiments. The long-term assimilation impact is analysed by looking at a set of quantiles computed for soil moisture at each grid cell. Within hydrological monitoring systems, extreme dry or wet conditions are often defined via their relative occurrence, adding great importance to assimilation-induced quantile changes. Although still being limited now, longer L-band radiometer time series will become available and make model output improved by assimilating such data that are more usable for extreme event statistics.

Temperature responses of individual soil organic matter components

NASA Astrophysics Data System (ADS)

Feng, Xiaojuan; Simpson, Myrna J.

2008-09-01

Temperature responses of soil organic matter (SOM) remain unclear partly due to its chemical and compositional heterogeneity. In this study, the decomposition of SOM from two grassland soils was investigated in a 1-year laboratory incubation at six different temperatures. SOM was separated into solvent extractable compounds, suberin- and cutin-derived compounds, and lignin-derived monomers by solvent extraction, base hydrolysis, and CuO oxidation, respectively. These SOM components have distinct chemical structures and stabilities and their decomposition patterns over the course of the experiment were fitted with a two-pool exponential decay model. The stability of SOM components was also assessed using geochemical parameters and kinetic parameters derived from model fitting. Compared with the solvent extractable compounds, a low percentage of lignin monomers partitioned into the labile SOM pool. Suberin- and cutin-derived compounds were poorly fitted by the decay model, and their recalcitrance was shown by the geochemical degradation parameter (ω - C16/∑C16), which was observed to stabilize during the incubation. The temperature sensitivity of decomposition, expressed as Q10, was derived from the relationship between temperature and SOM decay rates. SOM components exhibited varying temperature responses and the decomposition of lignin monomers exhibited higher Q10 values than the decomposition of solvent extractable compounds. Our study shows that Q10 values derived from soil respiration measurements may not be reliable indicators of temperature responses of individual SOM components.

Laboratory and numerical experiments on water and energy fluxes during freezing and thawing in the unsaturated zone

NASA Astrophysics Data System (ADS)

Holländer, Hartmut; Montasir Islam, Md.; Šimunek, Jirka

2017-04-01

Frozen soil has a major effect in many hydrologic processes, and its effects are difficult to predict. A prime example is flood forecasting during spring snowmelt within the Canadian Prairies. One key driver for the extent of flooding is the antecedent soil moisture and the possibility for water to infiltrate into frozen soils. Therefore, these situations are crucial for accurate flood prediction during every spring. The main objective of this study was to evaluate the water flow and heat transport within HYDRUS-1D version 4.16 and with Hansson's model, which is a detailed freezing/thawing module (Hansson et al., 2004), to predict the impact of frozen and partly frozen soil on infiltration. We developed a standardized data set of water flow and heat transport into (partial) frozen soil by laboratory experiments using fine sand. Temperature, soil moisture, and percolated water were observed at different freezing conditions as well as at thawing conditions. Significant variation in soil moisture was found between the top and the bottom of the soil column at the starting of the thawing period. However, with increasing temperature, the lower depth of the soil column showed higher moisture as the soil became enriched with moisture due to the release of heat by soil particles during the thawing cycle. We applied vadose zone modeling using the results from the laboratory experiments. The simulated water content by HYDRUS-1D 4.16 showed large errors compared to the observed data showing by negative Nash-Sutcliffe Efficiency. Hansson's model was not able to predict soil water fluxes due to its unstable behavior (Šimunek et al., 2016). The soil temperature profile simulated using HYDRUS-1D 4.16 was not able to predict the release of latent heat during the phase change of water that was visible in Hansson's model. Hansson's model includes the energy gain/loss due to the phase change in the amount of latent energy stored in the modified heat transport equation. However, in situations when the thermal heat gradient was large, the latent heat was not the key process, and HYDRUS-1D 4.16 was predicting better soil temperatures compared to Hansson's model. The newly developed data showed their usefulness for the evaluation and validation of the numerical models. We claim that these laboratory results will be useful for the validation of numerical models and for developing scientific knowledge to suggest potential code variations or new code development in numerical models. References: Hansson, K., J. Šimunek, M. Mizoguchi, L.-C. Lundin, and M. T. van Genuchten (2004), Water Flow and Heat Transport in Frozen Soil, Vadose Zone J, 3(2), 693-704. Šimunek, J., M. T. van Genuchten, and M. Sejna (2016), Recent developments and applications of the HYDRUS computer software packages, Vadose Zone J, 15(7).

Overcoming uncertainty with carbonyl sulfide-based GPP estimates: observing and modeling soil COS fluxes in terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Whelan, M.; Hilton, T. W.; Berry, J. A.; Berkelhammer, M. B.; Desai, A. R.; Rastogi, B.; Campbell, J. E.

2015-12-01

Significant carbonyl sulfide (COS) exchange by soils limits the applicability of net ecosystem COS flux observations as a proxy for stomatal trace gas exchange. High frequency measurements of COS over urban and natural ecosystems offer a potential window into processes regulating the carbon and water cycle: photosynthetic carbon uptake and stomatal conductance. COS diffuses through plant stomata and is irreversibly consumed by enzymes involved in photosynthesis. In certain environments, the magnitude of soil COS fluxes may constitute one-quarter of COS uptake by plants. Here we present a way of anticipating conditions when anomalously large soil COS fluxes are likely to occur and be taken into account. Previous studies have pointed to either a tendency for soil uptake of COS from the atmosphere with a soil moisture optimum, or exponential COS production coincident with temperature. Data from field and laboratory studies were used to deconvolve the two processes. CO2 and COS fluxes were observed from forest, desert, grassland, and agricultural soils under a range of temperature and soil moisture conditions. We demonstrate how to estimate temperature and soil moisture impacts on COS soil production based on our cross-site incubations. By building a model of soil COS exchange that combines production and consumption terms, we offer a framework for interpreting the two disparate conclusions about soil COS exchange in previous studies. Such a construction should be used in ecosystem and continental scale modeling of COS fluxes to anticipate where the influence of soil COS exchange needs to be accounted for, resulting in greater utility of carbonyl sulfide as a tracer of plant physiological processes.

Numerical and Experimental Investigation of Soil Heterogeneity around Landmines in Natural Soil

NASA Astrophysics Data System (ADS)

Wallen, B.; Smits, K. M.; Howington, S. E.

2015-12-01

The environment in which landmines are placed is oftentimes highly heterogeneous. These heterogeneities such as differences in soil type, packing and moisture, combined with changes in surface and climate conditions can oftentimes mask the presence of the mine. Understanding the impact of heterogeneity on heat and mass transfer behavior in the vicinity of landmines is paramount to properly identifying landmine locations for demining operations. This study investigates the impact of soil heterogeneity on soil moisture and temperature distributions around buried objects with the goal of increasing our ability to model and predict the environmental conditions that are most dynamic to mine detection performance. A ten-day field experiment was conducted in which two anti-personnel landmines at different depths and a limestone block of comparable size were buried. The site was instrumented with a series of sensors, monitoring atmospheric, surface and subsurface conditions to include measurements of soil moisture, soil and air temperature, relative humidity, vapor concentration, and meteorological conditions such as wind speed and net radiation. Infrared thermal imaging was used to provide continuous profiles of surface temperature conditions. The soil was well characterized in the laboratory to provide good understanding of field conditions for numerical modeling efforts. Experimental results demonstrate the strongest thermal contrast between shallow landmine emplacement and the surrounding soil occurring as the sun approaches its zenith and two hours after sunset until the sun directly impacts the soil above the landmine. A finite-element model of fluid flow and heat transport through porous media is compared against experimental observations, capturing the diurnal variation. A validated model, like this one, offers the opportunity to improve landmine detection probabilities and reduce false alarms caused by environmental variability.

Assessment of SMOS Soil Moisture Retrieval Parameters Using Tau-Omega Algorithms for Soil Moisture Deficit Estimation

NASA Technical Reports Server (NTRS)

Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; O'Neill, Peggy; Islam, Tanvir; Gupta, Manika

2014-01-01

Soil Moisture and Ocean Salinity (SMOS) is the latest mission which provides flow of coarse resolution soil moisture data for land applications. However, the efficient retrieval of soil moisture for hydrological applications depends on optimally choosing the soil and vegetation parameters. The first stage of this work involves the evaluation of SMOS Level 2 products and then several approaches for soil moisture retrieval from SMOS brightness temperature are performed to estimate Soil Moisture Deficit (SMD). The most widely applied algorithm i.e. Single channel algorithm (SCA), based on tau-omega is used in this study for the soil moisture retrieval. In tau-omega, the soil moisture is retrieved using the Horizontal (H) polarisation following Hallikainen dielectric model, roughness parameters, Fresnel's equation and estimated Vegetation Optical Depth (tau). The roughness parameters are empirically calibrated using the numerical optimization techniques. Further to explore the improvement in retrieval models, modifications have been incorporated in the algorithms with respect to the sources of the parameters, which include effective temperatures derived from the European Center for Medium-Range Weather Forecasts (ECMWF) downscaled using the Weather Research and Forecasting (WRF)-NOAH Land Surface Model and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) while the s is derived from MODIS Leaf Area Index (LAI). All the evaluations are performed against SMD, which is estimated using the Probability Distributed Model following a careful calibration and validation integrated with sensitivity and uncertainty analysis. The performance obtained after all those changes indicate that SCA-H using WRF-NOAH LSM downscaled ECMWF LST produces an improved performance for SMD estimation at a catchment scale.

Temperature Responses of Soil Organic Matter Components With Varying Recalcitrance

NASA Astrophysics Data System (ADS)

Simpson, M. J.; Feng, X.

2007-12-01

The response of soil organic matter (SOM) to global warming remains unclear partly due to the chemical heterogeneity of SOM composition. In this study, the decomposition of SOM from two grassland soils was investigated in a one-year laboratory incubation at six different temperatures. SOM was separated into solvent- extractable compounds, suberin- and cutin-derived compounds, and lignin monomers by solvent extraction, base hydrolysis, and CuO oxidation, respectively. These SOM components had distinct chemical structures and recalcitrance, and their decomposition was fitted by a two-pool exponential decay model. The stability of SOM components was assessed using geochemical parameters and kinetic parameters derived from model fitting. Lignin monomers exhibited much lower decay rates than solvent-extractable compounds and a relatively low percentage of lignin monomers partitioned into the labile SOM pool, which confirmed the generally accepted recalcitrance of lignin compounds. Suberin- and cutin-derived compounds had a poor fitting for the exponential decay model, and their recalcitrance was shown by the geochemical degradation parameter which stabilized during the incubation. The aliphatic components of suberin degraded faster than cutin-derived compounds, suggesting that cutin-derived compounds in the soil may be at a higher stage of degradation than suberin- derived compounds. The temperature sensitivity of decomposition, expressed as Q10, was derived from the relationship between temperature and SOM decay rates. SOM components exhibited varying temperature responses and the decomposition of the recalcitrant lignin monomers had much higher Q10 values than soil respiration or the solvent-extractable compounds decomposition. Our study shows that the decomposition of recalcitrant SOM is highly sensitive to temperature, more so than bulk soil mineralization. This observation suggests a potential acceleration in the degradation of the recalcitrant SOM pool with global warming.

Evaluating the Effect of Ground Temperature on Phreatic Evaporation in Bare Soil Area

NASA Astrophysics Data System (ADS)

Manting, S.; Wang, B.; Liu, P.

2017-12-01

Phreatic water evaporation is an important link in water conversion, and it is also the main discharge of shallow groundwater. The influencing factors of phreatic evaporation intensity include meteorological elements, soil lithology, ground temperature, water table depth and plant growth status, etc. However, the effect of ground temperature on phreatic evaporation is neglected in the traditional phreatic evaporation study, while from the principle of water vapor conversion, the ground temperature is the main energy controlling the process. Taking the homogeneous sand in bare soil area for example, the effect of different temperature difference between ground temperature and air temperature on phreatic evaporation was studied by constructing soil column experiment and Hydrus numerical simulation model. Based on analysis of the process and trend of soil water content in different depths, the influence mechanism of ground temperature on phreatic evaporation was discussed quantitatively. The experimental results show that the change trend of daily evaporation is basically the same. But considering the effect of ground temperature the evaporation amount is significantly larger than that of without considering the temperature. When the temperature (-2.3 ° 13.6 °) is lower than the ground temperature (20 °), the average value of evaporation increased by about 33.7%; When the temperature (22 ° -33.2 °) is higher than the ground temperature (20 °), the average increase of evaporation is about 10.08%. The effect of ground temperature on the evaporation is very significant in winter and summer. Soil water content increased with the increase of water table depth, while the soil water content at the same depth was different due to the temperature difference, and the soil water content was also different. The larger the temperature difference, the greater the difference of soil water content. The slope of the trend line of the phreatic evaporation is also increased accordingly. That is, under the influence of ground temperature, water vapor conversion rate increased, resulting in increased soil moisture and increased phreatic evaporation. Therefore, considering the ground temperature, it has important theoretical and practical value for scientific understanding and revealing the phreatic evaporation process.

Sorption-desorption of fipronil in some soils, as influenced by ionic strength, pH and temperature.

PubMed

Singh, Anand; Srivastava, Anjana; Srivastava, Prakash C

2016-08-01

The sorption-desorpion of fipronil insecticide is influenced by soil properties and variables such as pH, ionic strength, temperature, etc. A better understanding of soil properties and these variables in sorption-desorption processes by quantification of fipronil using liquid chromatography may help to optimise suitable soil management to reduce contamination of surface and groundwaters. In the present investigation, the sorption-desorption of fipronil was studied in some soils at varying concentrations, ionic strengths, temperatures and pH values, and IR specta of fipronil sorbed onto soils were studied. The sorption of fipronil onto soils conformed to the Freundlich isotherm model. The sorption-desorption of fipronil varied with ionic strength in each of the soils. Sorption decreased but desorption increased with temperature. Sorption did not change with increasing pH, but for desorption there was no correlation. The cumulative desorption of fipronil from soil was significantly and inversely related to soil organic carbon content. IR spectra of sorbed fipronil showed the involvement of amino, nitrile, sulfone, chloro and fluoro groups and the pyrazole nucleus of the fipronil molecule. The sorption of fipronil onto soils appeared to be a physical process with the involvement of hydrogen bonding. An increase in soil organic carbon may help to reduce desorption of fipronil. High-temperature regimes are more conducive to the desorption. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

Warming accelerates decomposition of decades-old carbon in forest soils.

PubMed

Hopkins, Francesca M; Torn, Margaret S; Trumbore, Susan E

2012-06-26

Global climate carbon-cycle models predict acceleration of soil organic carbon losses to the atmosphere with warming, but the size of this feedback is poorly known. The temperature sensitivity of soil carbon decomposition is commonly determined by measuring changes in the rate of carbon dioxide (CO(2)) production under controlled laboratory conditions. We added measurements of carbon isotopes in respired CO(2) to constrain the age of carbon substrates contributing to the temperature response of decomposition for surface soils from two temperate forest sites with very different overall rates of carbon cycling. Roughly one-third of the carbon respired at any temperature was fixed from the atmosphere more than 10 y ago, and the mean age of respired carbon reflected a mixture of substrates of varying ages. Consistent with global ecosystem model predictions, the temperature sensitivity of the carbon fixed more than a decade ago was the same as the temperature sensitivity for carbon fixed less than 10 y ago. However, we also observed an overall increase in the mean age of carbon respired at higher temperatures, even correcting for potential substrate limitation effects. The combination of several age constraints from carbon isotopes showed that warming had a similar effect on respiration of decades-old and younger (<10 y) carbon but a greater effect on decomposition of substrates of intermediate (between 7 and 13 y) age. Our results highlight the vulnerability of soil carbon to warming that is years-to-decades old, which makes up a large fraction of total soil carbon in forest soils globally.

Genotype and plant trait effects on soil CO2 efflux responses to altered precipitation in switchgrass

USDA-ARS?s Scientific Manuscript database

Background/Question/Methods Global climate change models predict increasing drought during the growing season, which will alter many ecosystem processes including soil CO2 efflux (JCO2), with potential consequences for carbon retention in soils. Soil moisture, soil temperature and plant traits such...

Long-term monitoring of temperature in the subsoil using Fiber Optic Distributed Sensing

NASA Astrophysics Data System (ADS)

Susanto, Kusnahadi; Malet, Jean-Philippe; Gance, Julien; Marc, Vincent

2017-04-01

Monitoring changes in soil water content in the vadose zone of soils is a great importance for various hydrological, agronomical, ecological and environmental studies. By using soil temperature measurements with Fiber-Optic Distributed Temperature Sensing (FO-DTS), we can indirectly document soil water changes at high spatial and temporal frequency. In this research, we installed an observatory of soil temperature on a representative black marl slope of the long-term Draix-Bléone hydrological observatory (South French Alps, Réseau de Basins-Versants / RBV). A 350 m long reinforced fiber optic cable was buried at 0.05, 0.10 and 0.15 m of depths and installed at the soil surface. The total length of the monitored profile is 60 m, and it three different soil units consisting of argillaceous weathered black marls, silty colluvium under grass and silty colluvium under forest. Soil temperature is measured every 6 minutes at a spatial resolution of 0.50 m using a double-ended configuration. Both passive and active (heating of the FO) is used to document soil water changes. We present the analysis of a period of 6 months of temperature measurements (January-July 2016). Changes in soil temperature at various temporal scales (rainfall event, season) and for the three units are discussed. These changes indicate different processes of water infiltration at different velocities in relation to the presence of roots and the soil permeability. We further test several inversion strategies to estimate soil water content from the thermal diffusivity of the soils using simple and more complex thermal models. Some limitations of using this indirect technique for long-term monitoring are also presented. The work is supported by the research project HYDROSLIDE and the large infrastructure project CRITEX funded by the French Research Agency (ANR).

Spatial and temporal variability of soil temperature, moisture and surface soil properties

NASA Technical Reports Server (NTRS)

Hajek, B. F.; Dane, J. H.

1993-01-01

The overall objectives of this research were to: (l) Relate in-situ measured soil-water content and temperature profiles to remotely sensed surface soil-water and temperature conditions; to model simultaneous heat and water movement for spatially and temporally changing soil conditions; (2) Determine the spatial and temporal variability of surface soil properties affecting emissivity, reflectance, and material and energy flux across the soil surface. This will include physical, chemical, and mineralogical characteristics of primary soil components and aggregate systems; and (3) Develop surface soil classes of naturally occurring and distributed soil property assemblages and group classes to be tested with respect to water content, emissivity and reflectivity. This document is a report of studies conducted during the period funded by NASA grants. The project was designed to be conducted over a five year period. Since funding was discontinued after three years, some of the research started was not completed. Additional publications are planned whenever funding can be obtained to finalize data analysis for both the arid and humid locations.

Identifying (subsurface) anthropogenic heat sources that influence temperature in the drinking water distribution system

NASA Astrophysics Data System (ADS)

Agudelo-Vera, Claudia M.; Blokker, Mirjam; de Kater, Henk; Lafort, Rob

2017-09-01

The water temperature in the drinking water distribution system and at customers' taps approaches the surrounding soil temperature at a depth of 1 m. Water temperature is an important determinant of water quality. In the Netherlands drinking water is distributed without additional residual disinfectant and the temperature of drinking water at customers' taps is not allowed to exceed 25 °C. In recent decades, the urban (sub)surface has been getting more occupied by various types of infrastructures, and some of these can be heat sources. Only recently have the anthropogenic sources and their influence on the underground been studied on coarse spatial scales. Little is known about the urban shallow underground heat profile on small spatial scales, of the order of 10 m × 10 m. Routine water quality samples at the tap in urban areas have shown up locations - so-called hotspots - in the city, with relatively high soil temperatures - up to 7 °C warmer - compared to the soil temperatures in the surrounding rural areas. Yet the sources and the locations of these hotspots have not been identified. It is expected that with climate change during a warm summer the soil temperature in the hotspots can be above 25 °C. The objective of this paper is to find a method to identify heat sources and urban characteristics that locally influence the soil temperature. The proposed method combines mapping of urban anthropogenic heat sources, retrospective modelling of the soil temperature, analysis of water temperature measurements at the tap, and extensive soil temperature measurements. This approach provided insight into the typical range of the variation of the urban soil temperature, and it is a first step to identifying areas with potential underground heat stress towards thermal underground management in cities.

Different Mechanisms of Soil Microbial Response to Global Change Result in Different Outcomes in the MIMICS-CN Model

NASA Astrophysics Data System (ADS)

Kyker-Snowman, E.; Wieder, W. R.; Grandy, S.

2017-12-01

Microbial-explicit models of soil carbon (C) and nitrogen (N) cycling have improved upon simulations of C and N stocks and flows at site-to-global scales relative to traditional first-order linear models. However, the response of microbial-explicit soil models to global change factors depends upon which parameters and processes in a model are altered by those factors. We used the MIcrobial-MIneral Carbon Stabilization Model with coupled N cycling (MIMICS-CN) to compare modeled responses to changes in temperature and plant inputs at two previously-modeled sites (Harvard Forest and Kellogg Biological Station). We spun the model up to equilibrium, applied each perturbation, and evaluated 15 years of post-perturbation C and N pools and fluxes. To model the effect of increasing temperatures, we independently examined the impact of decreasing microbial C use efficiency (CUE), increasing the rate of microbial turnover, and increasing Michaelis-Menten kinetic rates of litter decomposition, plus several combinations of the three. For plant inputs, we ran simulations with stepwise increases in metabolic litter, structural litter, whole litter (structural and metabolic), or labile soil C. The cumulative change in soil C or N varied in both sign and magnitude across simulations. For example, increasing kinetic rates of litter decomposition resulted in net releases of both C and N from soil pools, while decreasing CUE produced short-term increases in respiration but long-term accumulation of C in litter pools and shifts in soil C:N as microbial demand for C increased and biomass declined. Given that soil N cycling constrains the response of plant productivity to global change and that soils generate a large amount of uncertainty in current earth system models, microbial-explicit models are a critical opportunity to advance the modeled representation of soils. However, microbial-explicit models must be improved by experiments to isolate the physiological and stoichiometric parameters of soil microbes that shift under global change.

Long-term fertilization of a boreal Norway spruce forest increases the temperature sensitivity of soil organic carbon mineralization

PubMed Central

Coucheney, Elsa; Strömgren, Monika; Lerch, Thomas Z; Herrmann, Anke M

2013-01-01

Boreal ecosystems store one-third of global soil organic carbon (SOC) and are particularly sensitive to climate warming and higher nutrient inputs. Thus, a better description of how forest managements such as nutrient fertilization impact soil carbon (C) and its temperature sensitivity is needed to better predict feedbacks between C cycling and climate. The temperature sensitivity of in situ soil C respiration was investigated in a boreal forest, which has received long-term nutrient fertilization (22 years), and compared with the temperature sensitivity of C mineralization measured in the laboratory. We found that the fertilization treatment increased both the response of soil in situ CO2 effluxes to a warming treatment and the temperature sensitivity of C mineralization measured in the laboratory (Q10). These results suggested that soil C may be more sensitive to an increase in temperature in long-term fertilized in comparison with nutrient poor boreal ecosystems. Furthermore, the fertilization treatment modified the SOC content and the microbial community composition, but we found no direct relationship between either SOC or microbial changes and the temperature sensitivity of C mineralization. However, the relation between the soil C:N ratio and the fungal/bacterial ratio was changed in the combined warmed and fertilized treatment compared with the other treatments, which suggest that strong interaction mechanisms may occur between nutrient input and warming in boreal soils. Further research is needed to unravel into more details in how far soil organic matter and microbial community composition changes are responsible for the change in the temperature sensitivity of soil C under increasing mineral N inputs. Such research would help to take into account the effect of fertilization managements on soil C storage in C cycling numerical models. PMID:24455147

Is the Pearl River basin, China, drying or wetting? Seasonal variations, causes and implications

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Li, Jianfeng; Gu, Xihui; Shi, Peijun

2018-07-01

Soil moisture plays crucial roles in the hydrological cycle and is also a critical link between land surface and atmosphere. The Pearl River basin (PRb) is climatically subtropical and tropical and is highly sensitive to climate changes. In this study, seasonal soil moisture changes across the PRb were analyzed using the Variable Infiltration Capacity (VIC) model forced by the gridded 0.5° × 0.5° climatic observations. Seasonal changes of soil moisture in both space and time were investigated using the Mann-Kendall trend test method. Potential influencing factors behind seasonal soil moisture changes such as precipitation and temperature were identified using the Maximum Covariance Analysis (MCA) technique. The results indicated that: (1) VIC model performs well in describing changing properties of soil moisture across the PRb; (2) Distinctly different seasonal features of soil moisture can be observed. Soil moisture in spring decreased from east to west parts of the PRb. In summer however, soil moisture was higher in east and west parts but was lower in central parts of the PRb; (3) A significant drying trend was identified over the PRb in autumn, while no significant drying trends can be detected in other seasons; (4) The increase/decrease in precipitation can generally explain the wetting/drying tendency of soil moisture. However, warming temperature contributed significantly to the drying trends and these drying trends were particularly evident during autumn and winter; (5) Significant decreasing precipitation and increasing temperature combined to trigger substantially decreasing soil moisture in autumn. In winter, warming temperature is the major reason behind decreased soil moisture although precipitation is in slightly decreasing tendency. Season variations of soil moisture and related implications for hydro-meteorological processes in the subtropical and tropical river basins over the globe should arouse considerable human concerns.

Spatial and seasonal dynamics of surface soil carbon in the Luquillo Experimental Forest, Puerto Rico.

Treesearch

Hongqing Wang; Joseph D. Cornell; Charles A.S. Hall; David P. Marley

2002-01-01

We developed a spatially-explicit version of the CENTURY soil model to characterize the storage and flux of soil organic carbon (SOC, 0–30 cm depth) in the Luquillo Experimental Forest (LEF), Puerto Rico as a function of climate, vegetation, and soils. The model was driven by monthly estimates of average air temperature, precipitation, and potential evapotranspiration...

Dissipation of the herbicide oxyfluorfen in subtropical soils and its potential to contaminate groundwater.

PubMed

Yen, Jui-Hung; Sheu, Wey-Shin; Wang, Yei-Shung

2003-02-01

The dissipation and mobility of the herbicide oxyfluorfen (2-chloro-alpha,alpha,alpha-trifluoro-p-tolyl 3-ethoxy-4-nitrophenyl ether) in field soil of Taiwan were investigated in the laboratory with six tea garden soils. The dissipation coefficients of oxyfluorfen in soils of different moisture content (30%, 60%, and 90% of soil field capacity) and soil temperature (10 degrees C, 25 degrees C, and 40 degrees C) were studied. Results indicate that the half-life of oxyfluorfen ranged from 72 to 160 days for six tea garden soils. It was found that if the temperature is high, the dissipation rate is rapid, and there is almost no dissipation at 10 degrees C. Possible contamination of groundwater by the herbicide oxyfluorfen was assessed using the behavior assessment model and the groundwater pollution-potential (GWP) model. The results obtained after evaluating the residue and travel time using the GWP model illustrated that oxyfluorfen is not very mobile in soil and may not contaminate groundwater under normal conditions. But in the case of soil of extremely low organic carbon content and coarse texture, oxyfluorfen has the potential to contaminate groundwater less than 3m deep.

Evaluation of an improved intermediate complexity snow scheme in the ORCHIDEE land surface model

NASA Astrophysics Data System (ADS)

Wang, Tao; Ottlé, Catherine; Boone, Aaron; Ciais, Philippe; Brun, Eric; Morin, Samuel; Krinner, Gerhard; Piao, Shilong; Peng, Shushi

2013-06-01

Snow plays an important role in land surface models (LSM) for climate and model applied over Fran studies, but its current treatment as a single layer of constant density and thermal conductivity in ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) induces significant deficiencies. The intermediate complexity snow scheme ISBA-ES (Interaction between Soil, Biosphere and Atmosphere-Explicit Snow) that includes key snow processes has been adapted and implemented into ORCHIDEE, referred to here as ORCHIDEE-ES. In this study, the adapted scheme is evaluated against the observations from the alpine site Col de Porte (CDP) with a continuous 18 year data set and from sites distributed in northern Eurasia. At CDP, the comparisons of snow depth, snow water equivalent, surface temperature, snow albedo, and snowmelt runoff reveal that the improved scheme in ORCHIDEE is capable of simulating the internal snow processes better than the original one. Preliminary sensitivity tests indicate that snow albedo parameterization is the main cause for the large difference in snow-related variables but not for soil temperature simulated by the two models. The ability of the ORCHIDEE-ES to better simulate snow thermal conductivity mainly results in differences in soil temperatures. These are confirmed by performing sensitivity analysis of ORCHIDEE-ES parameters using the Morris method. These features can enable us to more realistically investigate interactions between snow and soil thermal regimes (and related soil carbon decomposition). When the two models are compared over sites located in northern Eurasia from 1979 to 1993, snow-related variables and 20 cm soil temperature are better reproduced by ORCHIDEE-ES than ORCHIDEE, revealing a more accurate representation of spatio-temporal variability.

CONSERVB: A numerical method to compute soil water content and temperature profiles under a bare surface

NASA Technical Reports Server (NTRS)

Vanbavel, C. H. M.; Lascano, R. J.

1982-01-01

A comprehensive, yet fairly simple model of water disposition in a bare soil profile under the sequential impact of rain storms and other atmospheric influences, as they occur from hour to hour is presented. This model is intended mostly to support field studies of soil moisture dynamics by our current team, to serve as a background for the microwave measurements, and, eventually, to serve as a point of departure for soil moisture predictions for estimates based in part upon airborne measurements. The main distinction of the current model is that it accounts not only for the moisture flow in the soil-atmosphere system, but also for the energy flow and, hence, calculates system temperatures. Also, the model is of a dynamic nature, capable of supporting any required degree of resolution in time and space. Much critical testing of the sample is needed before the complexities of the hydrology of a vegetated surface can be related meaningfully to microwave observations.

Modelling carbon and nitrogen turnover in variably saturated soils

NASA Astrophysics Data System (ADS)

Batlle-Aguilar, J.; Brovelli, A.; Porporato, A.; Barry, D. A.

2009-04-01

Natural ecosystems provide services such as ameliorating the impacts of deleterious human activities on both surface and groundwater. For example, several studies have shown that a healthy riparian ecosystem can reduce the nutrient loading of agricultural wastewater, thus protecting the receiving surface water body. As a result, in order to develop better protection strategies and/or restore natural conditions, there is a growing interest in understanding ecosystem functioning, including feedbacks and nonlinearities. Biogeochemical transformations in soils are heavily influenced by microbial decomposition of soil organic matter. Carbon and nutrient cycles are in turn strongly sensitive to environmental conditions, and primarily to soil moisture and temperature. These two physical variables affect the reaction rates of almost all soil biogeochemical transformations, including microbial and fungal activity, nutrient uptake and release from plants, etc. Soil water saturation and temperature are not constants, but vary both in space and time, thus further complicating the picture. In order to interpret field experiments and elucidate the different mechanisms taking place, numerical tools are beneficial. In this work we developed a 3D numerical reactive-transport model as an aid in the investigation the complex physical, chemical and biological interactions occurring in soils. The new code couples the USGS models (MODFLOW 2000-VSF, MT3DMS and PHREEQC) using an operator-splitting algorithm, and is a further development an existing reactive/density-dependent flow model PHWAT. The model was tested using simplified test cases. Following verification, a process-based biogeochemical reaction network describing the turnover of carbon and nitrogen in soils was implemented. Using this tool, we investigated the coupled effect of moisture content and temperature fluctuations on nitrogen and organic matter cycling in the riparian zone, in order to help understand the relative sensitivity of biological transformations to these processes.

Effects of prolonged soil drought on CH4 oxidation in a temperate spruce forest

NASA Astrophysics Data System (ADS)

Borken, W.; Brumme, R.; Xu, Y.-J.

2000-03-01

Our objective was to determine potential impacts of changes in rainfall amount and distribution on soil CH4 oxidation in a temperate forest ecosystem. We constructed a roof below the canopy of a 65-year-old Norway spruce forest (Picea abies (L.) Karst.) and simulated two climate change scenarios: (1) an extensively prolonged summer drought of 172 days followed by a rewetting period of 19 days in 1993 and (2) a less intensive summer drought of 108 days followed by a rewetting period of 33 days in 1994. CH4 oxidation, soil matric potential, and soil temperature were measured hourly to daily over a 2-year period. The results showed that annual CH4 oxidation in the drought experiment increased by 102% for the climate change scenario 1 and by 41% for the climate change scenario 2, compared to those of the ambient plot (1.33 kg CH4 ha-1 in 1993 and 1.65 kg CH4 ha-1 in 1994). We tested the relationships between CH4 oxidation rates, water-filled pore space (WFPS), soil matric potential, gas diffusivity, and soil temperature. Temporal variability in the CH4 oxidation rates corresponded most closely to soil matric potential. Employing soil matric potential and soil temperature, we developed a nonlinear model for estimating CH4 oxidation rates. Modeled results were in strong agreement with the measured CH4 oxidation for the ambient (r2 = 0.80) and drought plots (r2 = 0.89) over two experimental years, suggesting that soil matric potential is a highly reliable parameter for modeling CH4 oxidation rate.

High-resolution Mapping of Permafrost and Soil Freeze/thaw Dynamics in the Tibetan Plateau Based on Multi-sensor Satellite Observations

NASA Astrophysics Data System (ADS)

Zhang, W.; Yi, Y.; Yang, K.; Kimball, J. S.

2016-12-01

The Tibetan Plateau (TP) is underlain by the world's largest extent of alpine permafrost ( 2.5×106 km2), dominated by sporadic and discontinuous permafrost with strong sensitivity to climate warming. Detailed permafrost distributions and patterns in most of the TP region are still unknown due to extremely sparse in-situ observations in this region characterized by heterogeneous land cover and large temporal dynamics in surface soil moisture conditions. Therefore, satellite-based temperature and moisture observations are essential for high-resolution mapping of permafrost distribution and soil active layer changes in the TP region. In this study, we quantify the TP regional permafrost distribution at 1-km resolution using a detailed satellite data-driven soil thermal process model (GIPL2). The soil thermal model is calibrated and validated using in-situ soil temperature/moisture observations from the CAMP/Tibet field campaign (9 sites: 0-300 cm soil depth sampling from 1997-2007), a multi-scale soil moisture and temperature monitoring network in the central TP (CTP-SMTMN, 57 sites: 5-40 cm, 2010-2014) and across the whole plateau (China Meteorology Administration, 98 sites: 0-320 cm, 2000-2015). Our preliminary results using the CAMP/Tibet and CTP-SMTMN network observations indicate strong controls of surface thermal and soil moisture conditions on soil freeze/thaw dynamics, which vary greatly with underlying topography, soil texture and vegetation cover. For regional mapping of soil freeze/thaw and permafrost dynamics, we use the most recent soil moisture retrievals from the NASA SMAP (Soil Moisture Active Passive) sensor to account for the effects of temporal soil moisture dynamics on soil thermal heat transfer, with surface thermal conditions defined by MODIS (Moderate Resolution Imaging Spectroradiometer) land surface temperature records. Our study provides the first 1-km map of spatial patterns and recent changes of permafrost conditions in the TP.

The intraannual variability of land-atmosphere coupling over North America in the Canadian Regional Climate Model (CRCM5)

NASA Astrophysics Data System (ADS)

Yang Kam Wing, G.; Sushama, L.; Diro, G. T.

2016-12-01

This study investigates the intraannual variability of soil moisture-temperature coupling over North America. To this effect, coupled and uncoupled simulations are performed with the fifth-generation Canadian Regional Climate Model (CRCM5), driven by ERA-Interim. In coupled simulations, land and atmosphere interact freely; in uncoupled simulations, the interannual variability of soil moisture is suppressed by prescribing climatological values for soil liquid and frozen water contents. The study also explores projected changes to coupling by comparing coupled and uncoupled CRCM5 simulations for current (1981-2010) and future (2071-2100) periods, driven by the Canadian Earth System Model. Coupling differs for the northern and southern parts of North America. Over the southern half, it is persistent throughout the year while for the northern half, strongly coupled regions generally follow the freezing line during the cold months. Detailed analysis of the southern Canadian Prairies reveals seasonal differences in the underlying coupling mechanism. During spring and fall, as opposed to summer, the interactive soil moisture phase impacts the snow depth and surface albedo, which further impacts the surface energy budget and thus the surface air temperature; the air temperature then influences the snow depth in a feedback loop. Projected changes to coupling are also season specific: relatively drier soil conditions strengthen coupling during summer, while changes in soil moisture phase, snow depth, and cloud cover impact coupling during colder months. Furthermore, results demonstrate that soil moisture variability amplifies the frequency of temperature extremes over regions of strong coupling in current and future climates.

Modelling hydrological conditions in the maritime forest region of south-western Nova Scotia

NASA Astrophysics Data System (ADS)

Yanni, Shelagh; Keys, Kevin; Meng, Fan-Rui; Yin, Xiwei; Clair, Tom; Arp, Paul A.

2000-02-01

Hydrological processes and conditions were quantified for the Mersey River Basin (two basins: one exiting below Mill Falls, and one exiting below George Lake), the Roger's Brook Basin, Moosepit Brook, and for other selected locations at and near Kejimkujik National Park in Nova Scotia, Canada, from 1967 to 1990. Addressed variables included precipitation (rain, snow, fog), air temperature, stream discharge, snowpack accumulations, throughfall, soil and subsoil moisture, soil temperature and soil frost, at a monthly resolution. It was found that monthly per hectare stream discharge was essentially independent of catchment area from <20 km2 to more than 1000 km2. The forest hydrology model ForHyM2 was used to simulate monthly rates of stream discharge, throughfall and snowpack water equivalents for mature forest conditions. These simulations were in good agreement with the historical records once the contributions of fog and mist to the area-wide water budget were taken into account, each on a monthly basis. The resulting simulations establish a hydrologically consistent, continuous, comprehensive and partially verified record for basin-wide outcomes for all major hydrological processes and conditions, be these related to stream discharge, soil moisture, soil temperature, snowpack accumulations, soil frost, throughfall, interception and soil percolation.

Non-isothermal infiltration and tracer transport experiments on large soil columns

NASA Astrophysics Data System (ADS)

Sobotkova, Martina; Snehota, Michal; Cejkova, Eva; Tesar, Miroslav

2016-04-01

Isothermal and non-isothermal infiltration experiments were carried out in the laboratory on large undisturbed soil columns (19 cm in diameter, 25 cm high) taken at the experimental catchments Roklan (Sumava Mountains, Czech Republic) and Uhlirska (Jizera Mountains, Czech republic). The aim of the study was twofold. The first goal was to obtain water flow and heat transport data for indirect parameter estimation of thermal and hydraulic properties of soils from two sites by inverse modelling. The second aim was to investigate the extent of impact of the temperature on saturated hydraulic conductivity (Ksat) and dispersity of solute transport. The temperature of infiltrating water in isothermal experiment (20 °C) was equal to the initial temperature of the sample. For non-isothermal experiment water temperature was 5°C, while the initial temperature of the sample was 20°C as in previous case. The experiment was started by flooding the sample surface. Then water level was maintained at constant level throughout the infiltration run using the optical sensor and peristaltic pump. Concentration pulse of deuterium was applied at the top of the soil sample, during the steady state flow. Initial pressure head in the sample was close to field capacity. Two tensiometers and two temperature sensors were inserted in the soil sample in two depths (9 and 15 cm below the top of the sample). Two additional temperature sensors monitored the temperature entering and leaving the samples. Water drained freely through the perforated plate at the bottom of sample by gravity. Inflow and outflow water flux densities, water pressure heads and soil temperatures were monitored continuously during experiments. Effluent was sampled in regular time intervals and samples were analysed for deuterium concentrations by laser spectroscopy to develop breakthrough curves. The outcome of experiments are the series of measured water fluxes, pressure heads and temperatures ready for inverse modelling by dual permeability. The saturated hydraulic conductivity of soil columns was higher in the case of higher temperature of flowing water. The change was however not proportional to Ksat change induced by temperature change of viscosity only.

Impact of fire disturbance on soil thermal and carbon dynamics in Alaskan Tundra and Boreal forest ecosystems

NASA Astrophysics Data System (ADS)

Jiang, Y.; Rastetter, E.; Shaver, G. R.; Rocha, A. V.

2012-12-01

In Alaska, fire disturbance is a major component influencing the soil water and energy balance in both tundra and boreal forest ecosystems. Fire-caused changes in soil environment further affect both above- and below-ground carbon cycles depending on different fire severities. Understanding the effects of fire disturbance on soil thermal change requires implicit modeling work on the post-fire soil thawing and freezing processes. In this study, we model the soil temperature profiles in multiple burned and non-burned sites using a well-developed soil thermal model which fully couples soil water and heat transport. The subsequent change in carbon dynamics is analyzed based on site level observations and simulations from the Multiple Element Limitation (MEL) model. With comparison between burned and non-burned sites, we compare and contrast fire effects on soil thermal and carbon dynamics in continuous permafrost (Anaktuvik fire in north slope), discontinuous permafrost (Erickson Creek fire at Hess Creek) and non-permafrost zone (Delta Junction fire in interior Alaska). Then we check the post-fire recovery of soil temperature profiles at sites with different fire severities in both tundra and boreal forest fire areas. We further project the future changes in soil thermal and carbon dynamics using projected climate data from Scenarios Network for Alaska & Arctic Planning (SNAP). This study provides information to improve the understanding of fire disturbance on soil thermal and carbon dynamics and the consequent response under a warming climate.

Evaluating the influence of antecedent soil moisture on variability of the North American Monsoon precipitation in the coupled MM5/VIC modeling system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Chunmei; Leung, Lai R.; Gochis, David

2009-11-29

The influence of antecedent soil moisture on North American monsoon system (NAMS) precipitation variability was explored using the MM5 mesoscale model coupled with the Variable Infiltration Capacity (VIC) land surface model. Sensitivity experiments were performed with extreme wet and dry initial soil moisture conditions for both the 1984 wet monsoon year and the 1989 dry year. The MM5-VIC model reproduced the key features of NAMS in 1984 and 1989 especially over northwestern Mexico. Our modeling results indicate that the land surface has memory of the initial soil wetness prescribed at the onset of the monsoon that persists over most ofmore » the region well into the monsoon season (e.g. until August). However, in contrast to the classical thermal contrast concept, where wetter soils lead to cooler surface temperatures, less land-sea thermal contrast, weaker monsoon circulations and less precipitation, the coupled model consistently demonstrated a positive soil moisture – precipitation feedback. Specifically, anomalously wet premonsoon soil moisture always lead to enhanced monsoon precipitation, and the reverse was also true. The surface temperature changes induced by differences in surface energy flux partitioning associated with pre-monsoon soil moisture anomalies changed the surface pressure and consequently the flow field in the coupled model, which in turn changed moisture convergence and, accordingly, precipitation patterns. Both the largescale circulation change and local land-atmospheric interactions in response to premonsoon soil moisture anomalies play important roles in the coupled model’s positive soil moisture monsoon precipitation feedback. However, the former may be sensitive to the strength and location of the thermal anomalies, thus leaving open the possibility of both positive and negative soil moisture precipitation feedbacks.« less

Evaluation of a surface/vegetation parameterization using satellite measurements of surface temperature

NASA Technical Reports Server (NTRS)

Taconet, O.; Carlson, T.; Bernard, R.; Vidal-Madjar, D.

1986-01-01

Ground measurements of surface-sensible heat flux and soil moisture for a wheat-growing area of Beauce in France were compared with the values derived by inverting two boundary layer models with a surface/vegetation formulation using surface temperature measurements made from NOAA-AVHRR. The results indicated that the trends in the surface heat fluxes and soil moisture observed during the 5 days of the field experiment were effectively captured by the inversion method using the remotely measured radiative temperatures and either of the two boundary layer methods, both of which contain nearly identical vegetation parameterizations described by Taconet et al. (1986). The sensitivity of the results to errors in the initial sounding values or measured surface temperature was tested by varying the initial sounding temperature, dewpoint, and wind speed and the measured surface temperature by amounts corresponding to typical measurement error. In general, the vegetation component was more sensitive to error than the bare soil model.

Changes in the Size of the Active Microbial Pool Explain Short-Term Soil Respiratory Responses to Temperature and Moisture

PubMed Central

Salazar-Villegas, Alejandro; Blagodatskaya, Evgenia; Dukes, Jeffrey S.

2016-01-01

Heterotrophic respiration contributes a substantial fraction of the carbon flux from soil to atmosphere, and responds strongly to environmental conditions. However, the mechanisms through which short-term changes in environmental conditions affect microbial respiration still remain unclear. Microorganisms cope with adverse environmental conditions by transitioning into and out of dormancy, a state in which they minimize rates of metabolism and respiration. These transitions are poorly characterized in soil and are generally omitted from decomposition models. Most current approaches to model microbial control over soil CO2 production relate responses to total microbial biomass (TMB) and do not differentiate between microorganisms in active and dormant physiological states. Indeed, few data for active microbial biomass (AMB) exist with which to compare model output. Here, we tested the hypothesis that differences in soil microbial respiration rates across various environmental conditions are more closely related to differences in AMB (e.g., due to activation of dormant microorganisms) than in TMB. We measured basal respiration (SBR) of soil incubated for a week at two temperatures (24 and 33°C) and two moisture levels (10 and 20% soil dry weight [SDW]), and then determined TMB, AMB, microbial specific growth rate, and the lag time before microbial growth (tlag) using the Substrate-Induced Growth Response (SIGR) method. As expected, SBR was more strongly correlated with AMB than with TMB. This relationship indicated that each g active biomass C contributed ~0.04 g CO2-C h−1 of SBR. TMB responded very little to short-term changes in temperature and soil moisture and did not explain differences in SBR among the treatments. Maximum specific growth rate did not respond to environmental conditions, suggesting that the dominant microbial populations remained similar. However, warmer temperatures and increased soil moisture both reduced tlag, indicating that favorable abiotic conditions activated soil microorganisms. We conclude that soil respiratory responses to short-term changes in environmental conditions are better explained by changes in AMB than in TMB. These results suggest that decomposition models that explicitly represent microbial carbon pools should take into account the active microbial pool, and researchers should be cautious in comparing modeled microbial pool sizes with measurements of TMB. PMID:27148213

Simulated Seasonal Spatio-Temporal Patterns of Soil Moisture, Temperature, and Net Radiation in a Deciduous Forest

NASA Technical Reports Server (NTRS)

Ballard, Jerrell R., Jr.; Howington, Stacy E.; Cinnella, Pasquale; Smith, James A.

2011-01-01

The temperature and moisture regimes in a forest are key components in the forest ecosystem dynamics. Observations and studies indicate that the internal temperature distribution and moisture content of the tree influence not only growth and development, but onset and cessation of cambial activity [1], resistance to insect predation[2], and even affect the population dynamics of the insects [3]. Moreover, temperature directly affects the uptake and metabolism of population from the soil into the tree tissue [4]. Additional studies show that soil and atmospheric temperatures are significant parameters that limit the growth of trees and impose treeline elevation limitation [5]. Directional thermal infrared radiance effects have long been observed in natural backgrounds [6]. In earlier work, we illustrated the use of physically-based models to simulate directional effects in thermal imaging [7-8]. In this paper, we illustrated the use of physically-based models to simulate directional effects in thermal, and net radiation in a adeciduous forest using our recently developed three-dimensional, macro-scale computational tool that simulates the heat and mass transfer interaction in a soil-root-stem systems (SRSS). The SRSS model includes the coupling of existing heat and mass transport tools to stimulate the diurnal internal and external temperatures, internal fluid flow and moisture distribution, and heat flow in the system.

Soil Methane uptake Model (MeMo): a process based model for global methane consumption by soils

NASA Astrophysics Data System (ADS)

Murguia-Flores, F.; Arndt, S.; Ganesan, A.; Hornibrook, E. R. C.; Murray-Tortarolo, G.

2016-12-01

Atmospheric methane (CH4) is a powerful greenhouse gas, responsible for 20% of global warming. The only terrestrial and biological sink is the uptake in the soils by methanotrophic bacteria, however there is large spatial and temporal heterogeneity in the magnitude of this sink. One way to provide a global understanding of this process is by using a mathematical model to simulate the mechanisms of the underlying physical and biological drivers. Here we present the soil Methane uptake Model (MeMo) a process-based model for the global methane consumption by soils. We have built on previous models by Ridgwell et al., (1999) and Curry et al., (2007), by making several advances. First, a general analytical solution of the one-dimensional diffusion-reaction equation was implemented that accounts for a maximum uptake depth and for a CH4 flux coming from below the surface (i.e. CH4 production in the soil). Secondly, we revisited and improved the effect of nitrogen inhibition, soil moisture and soil temperature on CH4 uptake in the light of newly available data and advances in our understanding of these drivers. Using observed forcing data, we estimated a global mean CH4 uptake of 31.2±1.2 Tg y-1 for the period 1990-2009 with an increasing trend of 0.1 Tg y-2. Our model represented the latitudinal pattern of uptake shown by field observations, with the highest uptake per unit area occurring over dry tropical forest and the lowest uptake in the polar desert. The highest seasonality occurred in the Northern Hemisphere, showing that the main driver of variability in a given year is from a combination of temperature and soil moisture. Our model showed that CH4 uptake is reduced from previous studies by approximately 10% at the regions with the highest nitrogen deposition: East Asia and Europe. Finally, our results suggest that more field measurements are needed to improve the modelling of the process, such as the basal oxidation rate for different ecosystems, the Q10 temperature response across different conditions and long term field CH4 uptake records.

Mechanistic modeling of thermo-hydrological processes and microbial interactions at pore to profile scales resolve methane emission dynamics from permafrost soil

NASA Astrophysics Data System (ADS)

Ebrahimi, Ali; Or, Dani

2017-04-01

The sensitivity of the Earth's polar regions to raising global temperatures is reflected in rapidly changing hydrological processes with pronounced seasonal thawing of permafrost soil and increased biological activity. Of particular concern is the potential release of large amounts of soil carbon and the stimulation of other soil-borne GHG emissions such as methane. Soil methanotrophic and methanogenic microbial communities rapidly adjust their activity and spatial organization in response to permafrost thawing and a host of other environmental factors. Soil structural elements such as aggregates and layering and hydration status affect oxygen and nutrient diffusion processes thereby contributing to methanogenic activity within temporal anoxic niches (hotspots or hot-layers). We developed a mechanistic individual based model to quantify microbial activity dynamics within soil pore networks considering, hydration, temperature, transport processes and enzymatic activity associated with methane production in soil. The model was the upscaled from single aggregates (or hotspots) to quantifying emissions from soil profiles in which freezing/thawing processes provide macroscopic boundary conditions for microbial activity at different soil depths. The model distinguishes microbial activity in aerate bulk soil from aggregates (or submerged parts of the profile) for resolving methane production and oxidation rates. Methane transport pathways through soil by diffusion and ebullition of bubbles vary with hydration dynamics and affect emission patterns. The model links seasonal thermal and hydrologic dynamics with evolution of microbial community composition and function affecting net methane emissions in good agreement with experimental data. The mechanistic model enables systematic evaluation of key controlling factors in thawing permafrost and microbial response (e.g., nutrient availability, enzyme activity, PH) on long term methane emissions and carbon decomposition rates in the rapidly changing polar regions.

The role of permafrost and soil water in distribution of alpine grassland and its NDVI dynamics on the Qinghai-Tibetan Plateau

NASA Astrophysics Data System (ADS)

Wang, Xiaoyun; Yi, Shuhua; Wu, Qingbai; Yang, Kun; Ding, Yongjian

2016-12-01

Soil temperature and soil water are two important factors controlling vegetation growth. Climate warming and associated permafrost degradation might change these soil conditions and affect alpine grassland on the Qinghai-Tibetan Plateau. However, our current understanding of the role of soil temperature and water at the plateau scale is inadequate. In this study, we used plateau scale soil water content, frozen soil type, vegetation index and land surface temperature datasets to investigate the spatial distribution, limiting factors of vegetation growth and normalized difference vegetation index (NDVI) changing trends in two major alpine grasslands, alpine meadow and alpine steppe, in relation to soil temperature and soil water conditions. Our results showed that: 1) alpine meadow is mainly distributed in seasonal frozen soil areas (55.90% of alpine meadow) with a soil water content between 0.15 and 0.25 m3/m3 and alpine steppe is mainly found in seasonal frozen and sub-stable permafrost areas (69.38% of alpine steppe) with a soil water content between 0.05 and 0.20 m3/m3; 2) at the plateau scale, there were 35.6% (more in colder regions) of alpine meadow pixels and 33.6% (more in wetter regions) of alpine steppe pixels having increase NDVI changing trends during 1982-2012, respectively; and the values having decrease NDVI changing trends are 7.3% and 9.7%, respectively; and 3) the vegetation growth of alpine meadow is mainly limited by soil temperature, while that of alpine steppe is limited by both soil temperature and soil water. We also find the limiting factors of temperature or water can only explain < 50% variation of vegetation growth trends in alpine grasslands. Our findings warrant the use of process-based ecosystem models to consider other factors, such as grazing, erosion and soil texture, among others, in addition to soil temperature and water to make proper projections when simulating the responses of vegetation growth to climate warming in alpine grasslands with different hydro-thermal conditions.

Latitude variation of the subsurface lunar temperature: Lunar Prospector thermal neutrons

NASA Astrophysics Data System (ADS)

Little, R. C.; Feldman, W. C.; Maurice, S.; Genetay, I.; Lawrence, D. J.; Lawson, S. L.; Gasnault, O.; Barraclough, B. L.; Elphic, R. C.; Prettyman, T. H.; Binder, A. B.

2003-05-01

Planetary thermal neutron fluxes provide a sensitive proxy for mafic and feldspathic terranes and are also necessary for translating measured gamma-ray line strengths to elemental abundances. Both functions require a model for near-surface temperatures and a knowledge of the dependence of thermal neutron flux on temperature. We have explored this dependence for a representative sample of lunar soil compositions and surface temperatures using the Monte Carlo N-Particle Code (MCNP™)(MNCP is a trademark of the Regents of the University of California, Los Alamos National Laboratory). For all soil samples, the neutron density is found to be independent of temperature, in accord with neutron moderation theory. The thermal neutron flux, however, does vary with temperature in a way that depends on Δ, the ratio of macroscopic absorption to energy-loss cross sections of soil compositions. The weakest dependence is for the largest Δ (which corresponds to the Apollo 17 high-Ti basalt in our soil selection), and the largest dependence is for the lowest Δ (which corresponds to ferroan anorthosite, [FAN] in our selection). For the lunar model simulated, the depth at which the thermal neutron population is most sensitive to temperature is ~30 g cm-2. These simulations were compared with the flux of thermal neutrons measured using the Lunar Prospector neutron spectrometer over the lunar highlands using a subsurface temperature profile that varies with latitude, λ, as Cos1/4λ. Model results assuming equatorial temperatures of 200 and 250 K are in reasonable agreement with measured data. This range of equatorial temperatures is not inconsistent with the average temperature measured below the diurnal thermal wave at the equator, Tmeas = 252 +/- 3 K [Langseth and Keihm, 1977].

The Temperature Sensitivity (Q10) of Soil Respiration: Controlling Factors and Spatial Prediction at Regional Scale Based on Environmental Soil Classes

NASA Astrophysics Data System (ADS)

Meyer, N.; Welp, G.; Amelung, W.

2018-02-01

The temperature sensitivity of heterotrophic soil respiration is crucial for modeling carbon dynamics but it is variable. Presently, however, most models employ a fixed value of 1.5 or 2.0 for the increase of soil respiration per 10°C increase in temperature (Q10). Here we identified the variability of Q10 at a regional scale (Rur catchment, Germany/Belgium/Netherlands). We divided the study catchment into environmental soil classes (ESCs), which we define as unique combinations of land use, aggregated soil groups, and texture. We took nine soil samples from each ESC (108 samples) and incubated them at four soil moisture levels and five temperatures (5-25°C). We hypothesized that Q10 variability is controlled by soil organic carbon (SOC) degradability and soil moisture and that ESC can be used as a widely available proxy for Q10, owing to differences in SOC degradability. Measured Q10 values ranged from 1.2 to 2.8 and were correlated with indicators of SOC degradability (e.g., pH, r = -0.52). The effect of soil moisture on Q10 was variable: Q10 increased with moisture in croplands but decreased in forests. The ESC captured significant parts of Q10 variability under dry (R2 = 0.44) and intermediate (R2 = 0.36) moisture conditions, where Q10 increased in the order cropland

A mechanistic, globally-applicable model of plant nitrogen uptake, retranslocation and fixation

NASA Astrophysics Data System (ADS)

Fisher, J. B.; Tan, S.; Malhi, Y.; Fisher, R. A.; Sitch, S.; Huntingford, C.

2008-12-01

Nitrogen is one of the nutrients that can most limit plant growth, and nitrogen availability may be a controlling factor on biosphere responses to climate change. We developed a plant nitrogen assimilation model based on a) advective transport through the transpiration stream, b) retranslocation whereby carbon is expended to resorb nitrogen from leaves, c) active uptake whereby carbon is expended to acquire soil nitrogen, and d) biological nitrogen fixation whereby carbon is expended for symbiotic nitrogen fixers. The model relies on 9 inputs: 1) net primary productivity (NPP), 2) plant C:N ratio, 3) available soil nitrogen, 4) root biomass, 5) transpiration rate, 6) saturated soil depth,7) leaf nitrogen before senescence, 8) soil temperature, and 9) ability to fix nitrogen. A carbon cost of retranslocation is estimated based on leaf nitrogen and compared to an active uptake carbon cost based on root biomass and available soil nitrogen; for nitrogen fixers both costs are compared to a carbon cost of fixation dependent on soil temperature. The NPP is then allocated to optimize growth while maintaining the C:N ratio. The model outputs are total plant nitrogen uptake, remaining NPP available for growth, carbon respired to the soil and updated available soil nitrogen content. We test and validate the model (called FUN: Fixation and Uptake of Nitrogen) against data from the UK, Germany and Peru, and run the model under simplified scenarios of primary succession and climate change. FUN is suitable for incorporation into a land surface scheme of a General Circulation Model and will be coupled with a soil model and dynamic global vegetation model as part of a land surface model (JULES).

Analysing the mechanisms of soil water and vapour transport in the desert vadose zone of the extremely arid region of northern China

NASA Astrophysics Data System (ADS)

Du, Chaoyang; Yu, Jingjie; Wang, Ping; Zhang, Yichi

2018-03-01

The transport of water and vapour in the desert vadose zone plays a critical role in the overall water and energy balances of near-surface environments in arid regions. However, field measurements in extremely dry environments face many difficulties and challenges, so few studies have examined water and vapour transport processes in the desert vadose zone. The main objective of this study is to analyse the mechanisms of soil water and vapour transport in the desert vadose zone (depth of ∼350 cm) by using measured and modelled data in an extremely arid environment. The field experiments are implemented in an area of the Gobi desert in northwestern China to measure the soil properties, daily soil moisture and temperature, daily water-table depth and temperature, and daily meteorological records from DOYs (Days of Year) 114-212 in 2014 (growing season). The Hydrus-1D model, which simulates the coupled transport of water, vapour and heat in the vadose zone, is employed to simulate the layered soil moisture and temperature regimes and analyse the transport processes of soil water and vapour. The measured results show that the soil water and temperatures near the land surface have visible daily fluctuations across the entire soil profile. Thermal vapour movement is the most important component of the total water flux and the soil temperature gradient is the major driving factor that affects vapour transport in the desert vadose zone. The most active water and heat exchange occurs in the upper soil layer (depths of 0-25 cm). The matric potential change from the precipitation mainly re-draws the spatio-temporal distribution of the isothermal liquid water in the soil near the land surface. The matric potential has little effect on the isothermal vapour and thermal liquid water flux. These findings offer new insights into the liquid water and vapour movement processes in the extremely arid environment.

Soil Variable Permeability and Water Phase Change Dynamics in a Wastewater Spray Irrigation Agricultural System Located in a Seasonably Cold Climate

NASA Astrophysics Data System (ADS)

Darnault, C. J. G.; Daniel, T. J.; Billy, G.; Hopkins, I.; Guo, L.; Jin, Z.; Gall, H. E.; Lin, H.

2017-12-01

The permeability of the upper meter of soils in frozen conditions, commonly referred to as the active layer, can vary exponentially given the time of year. Variable moisture contents along with temperature, radiation, and slope angle of the soil surface can result in variable depths of frozen soils, which can cause the formation of low permeability ice lenses well into the spring thaw period. The wastewater irrigation site known as the "Living Filter" located in State College, PA has been in continuous operation since 1962. On average 5500 m3/day of wastewater is applied to the site annually, even in the winter months when average temperatures can dip as low as -7 °C during the month of January. The Living Filter is not permitted to discharge to surface water and is intended to recharge the Spring Creek basin that directly underlies the site, therefore runoff from the site is not permitted. We hypothesize that water infiltrates the upper meter of the subsurface during the winter in several different ways such as preferential pathways in the ice layer created by plant stems and weak patches of ice thawed by the warm wastewater. 2D conceptual models of the phase change between ice and water in the soil were created in order to predict soil permeability and its change in temperature. The 2D conceptual models can be correlated between observed soil moisture content and soil temperature data in order to validate the model given spray irrigation and weather patterns. By determining the permeability of the frozen soils, irrigation practices can be adjusted for the winter months so as to reduce the risk of any accidental wastewater runoff. The impact of this study will result in a better understanding of the multiphase dynamics of the active layer and their implication on soil hydrology at the Living Filter and other seasonally frozen sites.

Soil and vegetation parameter uncertainty on future terrestrial carbon sinks

NASA Astrophysics Data System (ADS)

Kothavala, Z.; Felzer, B. S.

2013-12-01

We examine the role of the terrestrial carbon cycle in a changing climate at the centennial scale using an intermediate complexity Earth system climate model that includes the effects of dynamic vegetation and the global carbon cycle. We present a series of ensemble simulations to evaluate the sensitivity of simulated terrestrial carbon sinks to three key model parameters: (a) The temperature dependence of soil carbon decomposition, (b) the upper temperature limits on the rate of photosynthesis, and (c) the nitrogen limitation of the maximum rate of carboxylation of Rubisco. We integrated the model in fully coupled mode for a 1200-year spin-up period, followed by a 300-year transient simulation starting at year 1800. Ensemble simulations were conducted varying each parameter individually and in combination with other variables. The results of the transient simulations show that terrestrial carbon uptake is very sensitive to the choice of model parameters. Changes in net primary productivity were most sensitive to the upper temperature limit on the rate of photosynthesis, which also had a dominant effect on overall land carbon trends; this is consistent with previous research that has shown the importance of climatic suppression of photosynthesis as a driver of carbon-climate feedbacks. Soil carbon generally decreased with increasing temperature, though the magnitude of this trend depends on both the net primary productivity changes and the temperature dependence of soil carbon decomposition. Vegetation carbon increased in some simulations, but this was not consistent across all configurations of model parameters. Comparing to global carbon budget observations, we identify the subset of model parameters which are consistent with observed carbon sinks; this serves to narrow considerably the future model projections of terrestrial carbon sink changes in comparison with the full model ensemble.

Catalytic power of enzymes decreases with temperature: New insights for understanding soil C cycling and microbial ecology under warming.

PubMed

Alvarez, Gaël; Shahzad, Tanvir; Andanson, Laurence; Bahn, Michael; Wallenstein, Matthew D; Fontaine, Sébastien

2018-04-23

Most current models of soil C dynamics predict that climate warming will accelerate soil C mineralization, resulting in a long-term CO 2 release and positive feedback to global warming. However, ecosystem warming experiments show that CO 2 loss from warmed soils declines to control levels within a few years. Here, we explore the temperature dependence of enzymatic conversion of polymerized soil organic C (SOC) into assimilable compounds, which is presumed the rate-limiting step of SOC mineralization. Combining literature review, modelling and enzyme assays, we studied the effect of temperature on activity of enzymes considering their thermal inactivation and catalytic activity. We defined the catalytic power of enzymes (E power ) as the cumulative amount of degraded substrate by one unit of enzyme until its complete inactivation. We show a universal pattern of enzyme's thermodynamic properties: activation energy of catalytic activity (EA cat ) < activation energy of thermal inactivation (EA inact ). By investing in stable enzymes (high EA inact ) having high catalytic activity (low EA cat ), microorganisms may maximize the E power of their enzymes. The counterpart of such EAs' hierarchical pattern is the higher relative temperature sensitivity of enzyme inactivation than catalysis, resulting in a reduction in E power under warming. Our findings could explain the decrease with temperature in soil enzyme pools, microbial biomass (MB) and carbon use efficiency (CUE) reported in some warming experiments and studies monitoring the seasonal variation in soil enzymes. They also suggest that a decrease in soil enzyme pools due to their faster inactivation under warming contributes to the observed attenuation of warming effect on soil C mineralization. This testable theory predicts that the ultimate response of SOC degradation to warming can be positive or negative depending on the relative temperature response of E power and microbial production of enzymes. © 2018 John Wiley & Sons Ltd.

Dissolved organic carbon fluxes from soils in the Alaskan coastal temperate rainforest

NASA Astrophysics Data System (ADS)

D'Amore, D. V.; Edwards, R.; Hood, E. W.; Herendeen, P. A.; Valentine, D.

2011-12-01

Soil saturation and temperature are the primary factors that influence soil carbon cycling. Interactions between these factors vary by soil type, climate, and landscape position, causing uncertainty in predicting soil carbon flux from. The soils of the North American perhumid coastal temperate rainforest (NCTR) store massive amounts of carbon, yet there is no estimate of dissolved organic carbon (DOC) export from different soil types in the region. There are also no working models that describe the influence of soil saturation and temperature on the export of DOC from soils. To address this key information gap, we measured soil water table elevation, soil temperature, and soil and stream DOC concentrations to calculate DOC flux across a soil hydrologic gradient that included upland soils, forested wetland soils, and sloping bog soils in the NCTR of southeast Alaska. We found that increased soil temperature and frequent fluctuations of soil water tables promoted the export of large quantities of DOC from wetland soils and relatively high amounts of DOC from mineral soils. Average area-weighted DOC flux ranged from 7.7 to 33.0 g C m-2 y-1 across a gradient of hydropedologic soil types. The total area specific export of carbon as DOC for upland, forested wetland and sloping bog catchments was 77, 306, and 329 Kg C ha-1 y-1 respectively. The annual rate of carbon export from wetland soils in this region is among the highest reported in the literature. These findings highlight the importance of terrestrial-aquatic fluxes of DOC as a pathway for carbon loss in the NCTR.

Estimating the effect of shallow groundwater on diurnal heat transport in a vadose zone

NASA Astrophysics Data System (ADS)

Jiang, Jianmei; Zhao, Lin; Zhai, Zhe

2016-09-01

The influence of shallow groundwater on the diurnal heat transport of the soil profile was analyzed using a soil sensor automatic monitoring system that continuously measures temperature and water content of soil profiles to simulate heat transport based on the Philip and de Vries (PDV) model. Three experiments were conducted to measure soil properties at depths of 5 cm, 10 cm, 20 cm, and 30 cm when groundwater tables reached 10 cm, 30 cm, and 60 cm (Experiments I, II, and III). Results show that both the soil temperature near shallow groundwater and the soil water content were effectively simulated by the PDV model. The root mean square errors of the temperature at depths of 5 cm, 10 cm, and 20 cm were 1.018°C, 0.909°C, and 0.255°C, respectively. The total heat flux generated the convergent and divergent planes in space-time fields with valley values of-161.5W•m-2 at 7:30 and-234.6W•m-2 at 11:10 in Experiments II and III, respectively. The diurnal heat transport of the saturated soil occurred in five stages, while that of saturated-unsaturated and unsaturated soil profiles occurred in four stages because high moisture content led to high thermal conductivity, which hastened the heat transport.

Distribution and interactions of pentachlorophenol in soils: The roles of soil iron oxides and organic matter.

PubMed

Diagboya, Paul N; Olu-Owolabi, Bamidele I; Adebowale, Kayode O

2016-08-01

Soil iron oxides (IOs) and organic matter (OM) play varying roles in pentachlorophenol (PCP) retention and mobility, but the extent and mechanism are still unknown. Therefore, in order to have a better understanding of the adsorption of PCP on soils, batch sorption studies were carried out on whole soils and soils selectively treated to remove IOs (IOR) and OM (OMR). The effects of pH, time, and temperature were investigated. Results showed that PCP sorption was temperature and pH dependent; sorption decreased as both temperature and pH increased. Sorption was partly surface adsorption and partly partitioning within voids of IOs components as revealed by the kinetics models. The surface adsorption was multi-layer in nature. Equilibria were faster in the IOR soils than the untreated and OMR soils. IOs played greater roles in PCP sorption than OM. Removal of soil components, especially the IOs, as experienced in soils plagued by soil erosion, may lead to increased risks of PCP pollution of environmental media especially the aquifer. Copyright © 2016 Elsevier B.V. All rights reserved.

Distribution and interactions of pentachlorophenol in soils: The roles of soil iron oxides and organic matter

NASA Astrophysics Data System (ADS)

Diagboya, Paul N.; Olu-Owolabi, Bamidele I.; Adebowale, Kayode O.

2016-08-01

Soil iron oxides (IOs) and organic matter (OM) play varying roles in pentachlorophenol (PCP) retention and mobility, but the extent and mechanism are still unknown. Therefore, in order to have a better understanding of the adsorption of PCP on soils, batch sorption studies were carried out on whole soils and soils selectively treated to remove IOs (IOR) and OM (OMR). The effects of pH, time, and temperature were investigated. Results showed that PCP sorption was temperature and pH dependent; sorption decreased as both temperature and pH increased. Sorption was partly surface adsorption and partly partitioning within voids of IOs components as revealed by the kinetics models. The surface adsorption was multi-layer in nature. Equilibria were faster in the IOR soils than the untreated and OMR soils. IOs played greater roles in PCP sorption than OM. Removal of soil components, especially the IOs, as experienced in soils plagued by soil erosion, may lead to increased risks of PCP pollution of environmental media especially the aquifer.

Using dry spell dynamics of land surface temperature to evaluate large-scale model representation of soil moisture control on evapotranspiration

NASA Astrophysics Data System (ADS)

Taylor, Christopher M.; Harris, Philip P.; Gallego-Elvira, Belen; Folwell, Sonja S.

2017-04-01

The soil moisture control on the partition of land surface fluxes between sensible and latent heat is a key aspect of land surface models used within numerical weather prediction and climate models. As soils dry out, evapotranspiration (ET) decreases, and the excess energy is used to warm the atmosphere. Poor simulations of this dynamic process can affect predictions of mean, and in particular, extreme air temperatures, and can introduce substantial biases into projections of climate change at regional scales. The lack of reliable observations of fluxes and root zone soil moisture at spatial scales that atmospheric models use (typically from 1 to several hundred kilometres), coupled with spatial variability in vegetation and soil properties, makes it difficult to evaluate the flux partitioning at the model grid box scale. To overcome this problem, we have developed techniques to use Land Surface Temperature (LST) to evaluate models. As soils dry out, LST rises, so it can be used under certain circumstances as a proxy for the partition between sensible and latent heat. Moreover, long time series of reliable LST observations under clear skies are available globally at resolutions of the order of 1km. Models can exhibit large biases in seasonal mean LST for various reasons, including poor description of aerodynamic coupling, uncertainties in vegetation mapping, and errors in down-welling radiation. Rather than compare long-term average LST values with models, we focus on the dynamics of LST during dry spells, when negligible rain falls, and the soil moisture store is drying out. The rate of warming of the land surface, or, more precisely, its warming rate relative to the atmosphere, emphasises the impact of changes in soil moisture control on the surface energy balance. Here we show the application of this approach to model evaluation, with examples at continental and global scales. We can compare the behaviour of both fully-coupled land-atmosphere models, and land surface models forced by observed meteorology. This approach provides insight into a fundamental process that affects predictions on multiple time scales, and which has an important impact for society.

Modeling thermal dynamics of active layer soils and near-surface permafrost using a fully coupled water and heat transport model

USGS Publications Warehouse

Jiang, Yueyang; Zhuang, Qianlai; O'Donnell, Jonathan A.

2012-01-01

Thawing and freezing processes are key components in permafrost dynamics, and these processes play an important role in regulating the hydrological and carbon cycles in the northern high latitudes. In the present study, we apply a well-developed soil thermal model that fully couples heat and water transport, to simulate the thawing and freezing processes at daily time steps across multiple sites that vary with vegetation cover, disturbance history, and climate. The model performance was evaluated by comparing modeled and measured soil temperatures at different depths. We use the model to explore the influence of climate, fire disturbance, and topography (north- and south-facing slopes) on soil thermal dynamics. Modeled soil temperatures agree well with measured values for both boreal forest and tundra ecosystems at the site level. Combustion of organic-soil horizons during wildfire alters the surface energy balance and increases the downward heat flux through the soil profile, resulting in the warming and thawing of near-surface permafrost. A projection of 21st century permafrost dynamics indicates that as the climate warms, active layer thickness will likely increase to more than 3 meters in the boreal forest site and deeper than one meter in the tundra site. Results from this coupled heat-water modeling approach represent faster thaw rates than previously simulated in other studies. We conclude that the discussed soil thermal model is able to well simulate the permafrost dynamics and could be used as a tool to analyze the influence of climate change and wildfire disturbance on permafrost thawing.

Multi-model assessment of the impact of soil moisture initialization on mid-latitude summer predictability

NASA Astrophysics Data System (ADS)

Ardilouze, Constantin; Batté, L.; Bunzel, F.; Decremer, D.; Déqué, M.; Doblas-Reyes, F. J.; Douville, H.; Fereday, D.; Guemas, V.; MacLachlan, C.; Müller, W.; Prodhomme, C.

2017-12-01

Land surface initial conditions have been recognized as a potential source of predictability in sub-seasonal to seasonal forecast systems, at least for near-surface air temperature prediction over the mid-latitude continents. Yet, few studies have systematically explored such an influence over a sufficient hindcast period and in a multi-model framework to produce a robust quantitative assessment. Here, a dedicated set of twin experiments has been carried out with boreal summer retrospective forecasts over the 1992-2010 period performed by five different global coupled ocean-atmosphere models. The impact of a realistic versus climatological soil moisture initialization is assessed in two regions with high potential previously identified as hotspots of land-atmosphere coupling, namely the North American Great Plains and South-Eastern Europe. Over the latter region, temperature predictions show a significant improvement, especially over the Balkans. Forecast systems better simulate the warmest summers if they follow pronounced dry initial anomalies. It is hypothesized that models manage to capture a positive feedback between high temperature and low soil moisture content prone to dominate over other processes during the warmest summers in this region. Over the Great Plains, however, improving the soil moisture initialization does not lead to any robust gain of forecast quality for near-surface temperature. It is suggested that models biases prevent the forecast systems from making the most of the improved initial conditions.

Forest productivity varies with soil moisture more than temperature in a small montane watershed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Liang; Zhou, Hang; Link, Timothy E

Mountainous terrain creates variability in microclimate, including nocturnal cold air drainage and resultant temperature inversions. Driven by the elevational temperature gradient, vapor pressure deficit (VPD) also varies with elevation. Soil depth and moisture availability often increase from ridgetop to valley bottom. These variations complicate predictions of forest productivity and other biological responses. We analyzed spatiotemporal air temperature (T) and VPD variations in a forested, 27-km 2 catchment that varied from 1000 to 1650 m in elevation. Temperature inversions occurred on 76% of mornings in the growing season. The inversion had a clear upper boundary at midslope (~1370 m a.s.l.). Vapormore » pressure was relatively constant across elevations, therefore VPD was mainly controlled by T in the watershed. Here, we assessed the impact of microclimate and soil moisture on tree height, forest productivity, and carbon stable isotopes (δ 13C) using a physiological forest growth model (3-PG). Simulated productivity and tree height were tested against observations derived from lidar data. The effects on photosynthetic gas-exchange of dramatic elevational variations in T and VPD largely cancelled as higher temperature (increasing productivity) accompanies higher VPD (reducing productivity). Although it was not measured, the simulations suggested that realistic elevational variations in soil moisture predicted the observed decline in productivity with elevation. Therefore, in this watershed, the model parameterization should have emphasized soil moisture rather than precise descriptions of temperature inversions.« less

Forest productivity varies with soil moisture more than temperature in a small montane watershed

DOE PAGES

Wei, Liang; Zhou, Hang; Link, Timothy E; ...

2018-05-16

Mountainous terrain creates variability in microclimate, including nocturnal cold air drainage and resultant temperature inversions. Driven by the elevational temperature gradient, vapor pressure deficit (VPD) also varies with elevation. Soil depth and moisture availability often increase from ridgetop to valley bottom. These variations complicate predictions of forest productivity and other biological responses. We analyzed spatiotemporal air temperature (T) and VPD variations in a forested, 27-km 2 catchment that varied from 1000 to 1650 m in elevation. Temperature inversions occurred on 76% of mornings in the growing season. The inversion had a clear upper boundary at midslope (~1370 m a.s.l.). Vapormore » pressure was relatively constant across elevations, therefore VPD was mainly controlled by T in the watershed. Here, we assessed the impact of microclimate and soil moisture on tree height, forest productivity, and carbon stable isotopes (δ 13C) using a physiological forest growth model (3-PG). Simulated productivity and tree height were tested against observations derived from lidar data. The effects on photosynthetic gas-exchange of dramatic elevational variations in T and VPD largely cancelled as higher temperature (increasing productivity) accompanies higher VPD (reducing productivity). Although it was not measured, the simulations suggested that realistic elevational variations in soil moisture predicted the observed decline in productivity with elevation. Therefore, in this watershed, the model parameterization should have emphasized soil moisture rather than precise descriptions of temperature inversions.« less

Directional infrared temperature and emissivity of vegetation: Measurements and models

NASA Technical Reports Server (NTRS)

Norman, J. M.; Castello, S.; Balick, L. K.

1994-01-01

Directional thermal radiance from vegetation depends on many factors, including the architecture of the plant canopy, thermal irradiance, emissivity of the foliage and soil, view angle, slope, and the kinetic temperature distribution within the vegetation-soil system. A one dimensional model, which includes the influence of topography, indicates that thermal emissivity of vegetation canopies may remain constant with view angle, or emissivity may increase or decrease as view angle from nadir increases. Typically, variations of emissivity with view angle are less than 0.01. As view angle increases away from nadir, directional infrared canopy temperature usually decreases but may remain nearly constant or even increase. Variations in directional temperature with view angle may be 5C or more. Model predictions of directional emissivity are compared with field measurements in corn canopies and over a bare soil using a method that requires two infrared thermometers, one sensitive to the 8 to 14 micrometer wavelength band and a second to the 14 to 22 micrometer band. After correction for CO2 absorption by the atmosphere, a directional canopy emissivity can be obtained as a function of view angle in the 8 to 14 micrometer band to an accuracy of about 0.005. Modeled and measured canopy emissivities for corn varied slightly with view angle (0.990 at nadir and 0.982 at 75 deg view zenith angle) and did not appear to vary significantly with view angle for the bare soil. Canopy emissivity is generally nearer to unity than leaf emissivity may vary by 0.02 with wavelength even though leaf emissivity. High spectral resolution, canopy thermal emissivity may vary by 0.02 with wavelength even though leaf emissivity may vary by 0.07. The one dimensional model provides reasonably accurate predictions of infrared temperature and can be used to study the dependence of infrared temperature on various plant, soil, and environmental factors.

Effect of soil moisture on seasonal variation in indoor radon concentration: modelling and measurements in 326 Finnish houses

PubMed Central

Arvela, H.; Holmgren, O.; Hänninen, P.

2016-01-01

The effect of soil moisture on seasonal variation in soil air and indoor radon is studied. A brief review of the theory of the effect of soil moisture on soil air radon has been presented. The theoretical estimates, together with soil moisture measurements over a period of 10 y, indicate that variation in soil moisture evidently is an important factor affecting the seasonal variation in soil air radon concentration. Partitioning of radon gas between the water and air fractions of soil pores is the main factor increasing soil air radon concentration. On two example test sites, the relative standard deviation of the calculated monthly average soil air radon concentration was 17 and 26 %. Increased soil moisture in autumn and spring, after the snowmelt, increases soil gas radon concentrations by 10–20 %. In February and March, the soil gas radon concentration is in its minimum. Soil temperature is also an important factor. High soil temperature in summer increased the calculated soil gas radon concentration by 14 %, compared with winter values. The monthly indoor radon measurements over period of 1 y in 326 Finnish houses are presented and compared with the modelling results. The model takes into account radon entry, climate and air exchange. The measured radon concentrations in autumn and spring were higher than expected and it can be explained by the seasonal variation in the soil moisture. The variation in soil moisture is a potential factor affecting markedly to the high year-to-year variation in the annual or seasonal average radon concentrations, observed in many radon studies. PMID:25899611

Identifying environmental features for land management decisions

NASA Technical Reports Server (NTRS)

1983-01-01

Pairs of HCMM day-night thermal infrared (IR) data were selected to examine patterns of surface temperature and thermal inertia (TI) of peninsular Florida. GOES and NOAA-6 thermal IR, as well as National Climatic Center temperatures and rainfall, were also used. The HCMM apparent thermal inertia (ATI) images closely correspond to the General Soil Map of Florida, based on soil drainage classes. Areas with low ATI overlay well-drained soils, such as deep sands and drained organic soils. Areas with high ATI overlay areas with wetlands and bodies of water. The HCMM ATI images also correspond well with GOES-detected winter nocturnal cold-prone areas. Use of HCMM data with Carlson's energy balance model shows both high moisture availability (MA) and high thermal inertia (TI) of wetland-type surfaces and low MA and low TI of upland, well-drained soils. Since soil areas with low TI develop higher temperatures during the day, then antecedent patterns of highest maximum daytime surface temperature can also be used to predict nocturnal cold-prone areas in Florida.

An integrated soil-crop system model for water and nitrogen management in North China

PubMed Central

Liang, Hao; Hu, Kelin; Batchelor, William D.; Qi, Zhiming; Li, Baoguo

2016-01-01

An integrated model WHCNS (soil Water Heat Carbon Nitrogen Simulator) was developed to assess water and nitrogen (N) management in North China. It included five main modules: soil water, soil temperature, soil carbon (C), soil N, and crop growth. The model integrated some features of several widely used crop and soil models, and some modifications were made in order to apply the WHCNS model under the complex conditions of intensive cropping systems in North China. The WHCNS model was evaluated using an open access dataset from the European International Conference on Modeling Soil Water and N Dynamics. WHCNS gave better estimations of soil water and N dynamics, dry matter accumulation and N uptake than 14 other models. The model was tested against data from four experimental sites in North China under various soil, crop, climate, and management practices. Simulated soil water content, soil nitrate concentrations, crop dry matter, leaf area index and grain yields all agreed well with measured values. This study indicates that the WHCNS model can be used to analyze and evaluate the effects of various field management practices on crop yield, fate of N, and water and N use efficiencies in North China. PMID:27181364

Inversion of parameters for semiarid regions by a neural network

NASA Technical Reports Server (NTRS)

Zurk, Lisa M.; Davis, Daniel; Njoku, Eni G.; Tsang, Leung; Hwang, Jenq-Neng

1992-01-01

Microwave brightness temperatures obtained from a passive radiative transfer model are inverted through use of a neural network. The model is applicable to semiarid regions and produces dual-polarized brightness temperatures for 6.6-, 10.7-, and 37-GHz frequencies. A range of temperatures is generated by varying three geophysical parameters over acceptable ranges: soil moisture, vegetation moisture, and soil temperature. A multilayered perceptron (MLP) neural network is trained with a subset of the generated temperatures, and the remaining temperatures are inverted using a backpropagation method. Several synthetic terrains are devised and inverted by the network under local constraints. All the inversions show good agreement with the original geophysical parameters, falling within 5 percent of the actual value of the parameter range.

A revised Pitzer model for low-temperature soluble salt assemblages at the Phoenix site, Mars

NASA Astrophysics Data System (ADS)

Toner, J. D.; Catling, D. C.; Light, B.

2015-10-01

The Wet Chemistry Laboratory (WCL) on the Mars Phoenix Lander measured ions in a soil-water extraction and found Na+, K+, H+ (pH), Ca2+, Mg2+, SO42-, ClO4-, and Cl-. Equilibrium models offer insights into salt phases that were originally present in the Phoenix soil, which dissolved to form the measured WCL solution; however, there are few experimental datasets for single cation perchlorates (ClO4-), and none for mixed perchlorates, at low temperatures, which are needed to build models. In this study, we measure ice and salt solubilities in binary and ternary solutions in the Na-Ca-Mg-ClO4 system, and then use this data, along with existing data, to construct a low-temperature Pitzer model for perchlorate brines. We then apply our model to a nominal WCL solution. Previous studies have modeled either freezing of a WCL solution or evaporation at a single temperature. For the first time, we model evaporation at subzero temperatures, which is relevant for dehydration conditions that might occur at the Phoenix site. Our model indicates that a freezing WCL solution will form ice, KClO4, hydromagnesite (3MgCO3·Mg(OH)2·3H2O), calcite (CaCO3), meridianiite (MgSO4·11H2O), MgCl2·12H2O, NaClO4·2H2O, and Mg(ClO4)2·6H2O at the eutectic (209 K). The total water held in hydrated salt phases at the eutectic is ∼1.2 wt.%, which is much greater than hydrated water contents when evaporation is modeled at 298.15 K (∼0.3 wt.%). Evaporation of WCL solutions at lower temperatures (down to 210 K) results in lower water activities and the formation of more dehydrated minerals, e.g. kieserite (MgSO4·H2O) instead of meridianiite. Potentially habitable brines, with water activity aw > 0.6, can occur when soil temperatures are above 220 K and when the soil liquid water content is greater than 0.4 wt.% (100 ×gH2O gsoil-1). In general, modeling indicates that mineral assemblages derived from WCL-type solutions are characteristic of the soil temperature, water content, and water activity conditions under which they formed, and are useful indicators of past environmental conditions.

Effects of Vegetation and of Heat and Vapor Fluxes from Soil on Snowpack Evolution and Radiobrightness

NASA Technical Reports Server (NTRS)

Chung, Y. C.; England, A. W.; DeRoo, R. D.; Weininger, Etai

2006-01-01

The radiobrightness of a snowpack is strongly linked to the snow moisture content profile, to the point that the only operational inversion algorithms require dry snow. Forward dynamic models do not include the effects of freezing and thawing of the soil beneath the snowpack and the effect of vegetation within the snow or above the snow. To get a more realistic description of the evolution of the snowpack, we reported an addition to the Snow-Soil-Vegetation-Atmosphere- Transfer (SSVAT) model, wherein we coupled soil processes of the Land Surface Process (LSP) model with the snow model SNTHERM. In the near future we will be adding a radiobrightness prediction based on the modeled moisture, temperature and snow grain size profiles. The initial investigations with this SSVAT for a late winter and early spring snow pack indicate that soil processes warm the snowpack and the soil. Vapor diffusion needs to be considered whenever the ground is thawed. In the early spring, heat flow from the ground into a snow and a strong temperature gradient across the snow lead to thermal convection. The buried vegetation can be ignored for a late winter snow pack. The warmer surface snow temperature will affect radiobrightness since it is most sensitive to snow surface characteristics. Comparison to data shows that SSVAT provides a more realistic representation of the temperature and moisture profiles in the snowpack and its underlying soil than SNTHERM. The radiobrightness module will be optimized for the prediction of brightness when the snow is moist. The liquid water content of snow causes considerable absorption compared to dry snow, and so longer wavelengths are likely to be most revealing as to the state of a moist snowpack. For volumetric moisture contents below about 7% (the pendular regime), the water forms rings around the contact points between snow grains. Electrostatic modeling of these pendular rings shows that the absorption of these rings is significantly higher than a sphere of the same volume. The first implementation of the radiobrightness module will therefore be a simple radiative transfer model without scattering.

Thermal interaction of underground pipeline with freezing heaving soil

NASA Astrophysics Data System (ADS)

Podorozhnikov, S. Y.; Mikhailov, P.; Puldas, L.; Shabarov, A.

2018-05-01

A mathematical model and a method for calculating the stress-strain state of a pipeline describing the heat-power interaction in the "underground pipeline - soil" system in the conditions of negative temperatures in the soils of soils are offered. Some results of computational-parametric research are presented.

Warming accelerates decomposition of decades-old carbon in forest soils

DOE PAGES

Hopkins, F. M.; Torn, M. S.; Trumbore, S. E.

2012-06-11

Global climate carbon-cycle models predict acceleration of soil organic carbon losses to the atmosphere with warming, but the size of this feedback is poorly known. The temperature sensitivity of soil carbon decomposition is commonly determined by measuring changes in the rate of carbon dioxide (CO 2) production under controlled laboratory conditions. We added measurements of carbon isotopes in respired CO 2 to constrain the age of carbon substrates contributing to the temperature response of decomposition for surface soils from two temperate forest sites with very different overall rates of carbon cycling. Roughly one-third of the carbon respired at any temperaturemore » was fixed from the atmosphere more than 10 y ago, and the mean age of respired carbon reflected a mixture of substrates of varying ages. Consistent with global ecosystem model predictions, the temperature sensitivity of the carbon fixed more than a decade ago was the same as the temperature sensitivity for carbon fixed less than 10 y ago. However, we also observed an overall increase in the mean age of carbon respired at higher temperatures, even correcting for potential substrate limitation effects. The combination of several age constraints from carbon isotopes showed that warming had a similar effect on respiration of decades-old and younger (<10 y) carbon but a greater effect on decomposition of substrates of intermediate (between 7 and 13 y) age. Our results highlight the vulnerability of soil carbon to warming that is years-to-decades old, which makes up a large fraction of total soil carbon in forest soils globally.« less

Soil moisture status estimation over Three Gorges area with Landsat TM data based on temperature vegetation dryness index

NASA Astrophysics Data System (ADS)

Xu, Lina; Niu, Ruiqing; Li, Jiong; Dong, Yanfang

2011-12-01

Soil moisture is the important indicator of climate, hydrology, ecology, agriculture and other parameters of the land surface and atmospheric interface. Soil moisture plays an important role on the water and energy exchange at the land surface/atmosphere interface. Remote sensing can provide information on large area quickly and easily, so it is significant to do research on how to monitor soil moisture by remote sensing. This paper presents a method to assess soil moisture status using Landsat TM data over Three Gorges area in China based on TVDI. The potential of Temperature- Vegetation Dryness Index (TVDI) from Landsat TM data in assessing soil moisture was investigated in this region. After retrieving land surface temperature and vegetation index a TVDI model based on the features of Ts-NDVI space is established. And finally, soil moisture status is estimated according to TVDI. It shows that TVDI has the advantages of stability and high accuracy to estimating the soil moisture status.

Biogenic nitric oxide emission from a spruce forest soil in mountainous terrain

NASA Astrophysics Data System (ADS)

Falge, Eva; Bargsten, Anika; Behrendt, Thomas; Meixner, Franz X.

2010-05-01

The process-based spatial simulation model SVAT-CN was used to estimate biogenic nitric oxide (NO) emission by soils of a Norway spruce forest (Weidenbrunnen) in the Fichtelgebirge, Germany. SVAT-CN core is a combination of a multiple-layer soil water balance model and a multi-layered canopy gas exchange model. The soil modules comprise a flexible hybrid between a layered bucket model and classical basic liquid flow theory. Further soil processes include: heat transport, distribution of transpiration demand proportionally to soil resistance, reduction of leaf physiological parameters with limiting soil moisture. Spruce forest soils usually are characterized by a thick organic layer (raw humus), with the topmost centimetres being the location where most of the biogenic NO is produced. Within individual spruce forest stands the understory might be composed of patches characterized by different species (e.g. Vaccinium myrtillus, Picea abies, Deschampsia caespitosa), and NO production potentials. The effect of soil physical and chemical parameters and understory types on NO emission from the organic layer was investigated in laboratory incubation and fumigation experiments on soils sampled below the various understory covers found at the Weidenbrunnen site. Results from the laboratory experiments were used to parameterize multi-factorial regression models of soil NO emission with respect to its response to soil temperature and moisture. Parameterization of the spatial model SVAT-CN includes horizontal heterogeneity of over- and understory PAI, understory species distribution, soil texture, bulk density, thickness of organic layer. Simulations are run for intensive observations periods of 2007 and 2008 of the EGER (ExchanGE processes in mountainous Regions) project, a late summer/fall and an early summer period, providing estimates for different understory types (young spruce, blueberry, grass, and moss/litter patches). Validation of the model is being carried out at point scale, by comparison with measured soil moisture and temperature data at 12 locations at the Weidenbrunnen site. In addition model output is compared to soil NO emission data from dynamic chambers. Understory type was found to have a strong influence on the magnitude of soil NO emissions, with emissions from blueberry and young spruce one order of magnitude larger than those from grass or moss/litter patches.

Testing a full‐range soil‐water retention function in modeling water potential and temperature

USGS Publications Warehouse

Andraski, Brian J.; Jacobson, Elizabeth A.

2000-01-01

Recent work has emphasized development of full‐range water‐retention functions that are applicable under both wet and dry soil conditions, but evaluation of such functions in numerical modeling has been limited. Here we show that simulations using the Rossi‐Nimmo (RN) full‐range function compared favorably with those using the common Brooks‐Corey function and that the RN function can improve prediction of water potentials in near‐surface soil, particularly under dry conditions. Simulations using the RN function also improved prediction of temperatures throughout the soil profile. Such improvements could be important for calculations of liquid and vapor flow in near‐surface soils and in deep unsaturated zones of arid and semiarid regions.

Evaluation of the North American Land Data Assimilation System over the Southern Great Plains during the warm season

NASA Astrophysics Data System (ADS)

Robock, A.; Luo, L.; Wood, E. F.; Wen, F.; Mitchell, K. E.; Houser, P. R.; Schaake, J. C.; Nldas Team

2003-04-01

To conduct land data assimilation, validated land surface models are needed. The first step in the North American Land Data Assimilation System (NLDAS) is to evaluate four such state-of-the-art models. These models (VIC, Noah, Mosaic, and Sacramento) have been run for a retrospective period forced by atmospheric observations from the Eta analysis and actual precipitation and downward solar radiation (on a 1/8 degree North American grid) to calculate land hydrology. First we show that the forcing data set agrees very well with local observations and that simulations forced with local observations differ little from those forced with the NLDAS forcing data set. Then we evaluated the simulations using in situ observations over the Southern Great Plains for the periods of May-September of 1998 and 1999 by comparing the model outputs with surface latent, sensible, and ground heat fluxes at 24 Atmospheric Radiation Measurement/Cloud and Radiation Testbed stations and with soil temperature and soil moisture observations at 72 Oklahoma Mesonet stations. The standard NLDAS models do a fairly good job but with differences in the surface energy partition and in soil moisture between models and observations and among models during the summer, while they agree quite well on the soil temperature simulations. To investigate why, we performed a series of experiments accounting for differences between model-specified soil types and vegetation and those observed at the stations, and differences in model treatment of different soil types, vegetation properties, canopy resistance, soil column depth, rooting depth, root density, snow-free albedo, infiltration, aerodynamic resistance, and soil thermal diffusivity. The diagnosis and model enhancements demonstrate how the models can be improved so that they can be used in actual data assimilation mode.

Electrical and thermal behavior of unsaturated soils: experimental results

NASA Astrophysics Data System (ADS)

Nouveau, Marie; Grandjean, Gilles; Leroy, Philippe; Philippe, Mickael; Hedri, Estelle; Boukcim, Hassan

2016-05-01

When soil is affected by a heat source, some of its properties are modified, and in particular, the electrical resistivity due to changes in water content. As a result, these changes affect the thermal properties of soil, i.e., its thermal conductivity and diffusivity. We experimentally examine the changes in electrical resistivity and thermal conductivity for four soils with different grain size distributions and clay content over a wide range of temperatures, from 20 to 100 °C. This temperature range corresponds to the thermal conditions in the vicinity of a buried high voltage cable or a geothermal system. Experiments were conducted at the field scale, at a geothermal test facility, and in the laboratory using geophysical devices and probing systems. The results show that the electrical resistivity decreases and the thermal conductivity increases with temperature up to a critical temperature depending on soil types. At this critical temperature, the air volume in the pore space increases with temperature, and the resulting electrical resistivity also increases. For higher temperatures , the thermal conductivity increases sharply with temperature up to a second temperature limit. Beyond it, the thermal conductivity drops drastically. This limit corresponds to the temperature at which most of the water evaporates from the soil pore space. Once the evaporation is completed, the thermal conductivity stabilizes. To explain these experimental results, we modeled the electrical resistivity variations with temperature and water content in the temperature range 20 - 100°C, showing that two critical temperatures influence the main processes occurring during heating at temperatures below 100 °C.

PALADYN v1.0, a comprehensive land surface-vegetation-carbon cycle model of intermediate complexity

NASA Astrophysics Data System (ADS)

Willeit, Matteo; Ganopolski, Andrey

2016-10-01

PALADYN is presented; it is a new comprehensive and computationally efficient land surface-vegetation-carbon cycle model designed to be used in Earth system models of intermediate complexity for long-term simulations and paleoclimate studies. The model treats in a consistent manner the interaction between atmosphere, terrestrial vegetation and soil through the fluxes of energy, water and carbon. Energy, water and carbon are conserved. PALADYN explicitly treats permafrost, both in physical processes and as an important carbon pool. It distinguishes nine surface types: five different vegetation types, bare soil, land ice, lake and ocean shelf. Including the ocean shelf allows the treatment of continuous changes in sea level and shelf area associated with glacial cycles. Over each surface type, the model solves the surface energy balance and computes the fluxes of sensible, latent and ground heat and upward shortwave and longwave radiation. The model includes a single snow layer. Vegetation and bare soil share a single soil column. The soil is vertically discretized into five layers where prognostic equations for temperature, water and carbon are consistently solved. Phase changes of water in the soil are explicitly considered. A surface hydrology module computes precipitation interception by vegetation, surface runoff and soil infiltration. The soil water equation is based on Darcy's law. Given soil water content, the wetland fraction is computed based on a topographic index. The temperature profile is also computed in the upper part of ice sheets and in the ocean shelf soil. Photosynthesis is computed using a light use efficiency model. Carbon assimilation by vegetation is coupled to the transpiration of water through stomatal conductance. PALADYN includes a dynamic vegetation module with five plant functional types competing for the grid cell share with their respective net primary productivity. PALADYN distinguishes between mineral soil carbon, peat carbon, buried carbon and shelf carbon. Each soil carbon type has its own soil carbon pools generally represented by a litter, a fast and a slow carbon pool in each soil layer. Carbon can be redistributed between the layers by vertical diffusion and advection. For the vegetated macro surface type, decomposition is a function of soil temperature and soil moisture. Carbon in permanently frozen layers is assigned a long turnover time which effectively locks carbon in permafrost. Carbon buried below ice sheets and on flooded ocean shelves is treated differently. The model also includes a dynamic peat module. PALADYN includes carbon isotopes 13C and 14C, which are tracked through all carbon pools. Isotopic discrimination is modelled only during photosynthesis. A simple methane module is implemented to represent methane emissions from anaerobic carbon decomposition in wetlands (including peatlands) and flooded ocean shelf. The model description is accompanied by a thorough model evaluation in offline mode for the present day and the historical period.

Temperature Sensitivity as a Microbial Trait Using Parameters from Macromolecular Rate Theory

PubMed Central

Alster, Charlotte J.; Baas, Peter; Wallenstein, Matthew D.; Johnson, Nels G.; von Fischer, Joseph C.

2016-01-01

The activity of soil microbial extracellular enzymes is strongly controlled by temperature, yet the degree to which temperature sensitivity varies by microbe and enzyme type is unclear. Such information would allow soil microbial enzymes to be incorporated in a traits-based framework to improve prediction of ecosystem response to global change. If temperature sensitivity varies for specific soil enzymes, then determining the underlying causes of variation in temperature sensitivity of these enzymes will provide fundamental insights for predicting nutrient dynamics belowground. In this study, we characterized how both microbial taxonomic variation as well as substrate type affects temperature sensitivity. We measured β-glucosidase, leucine aminopeptidase, and phosphatase activities at six temperatures: 4, 11, 25, 35, 45, and 60°C, for seven different soil microbial isolates. To calculate temperature sensitivity, we employed two models, Arrhenius, which predicts an exponential increase in reaction rate with temperature, and Macromolecular Rate Theory (MMRT), which predicts rate to peak and then decline as temperature increases. We found MMRT provided a more accurate fit and allowed for more nuanced interpretation of temperature sensitivity in all of the enzyme × isolate combinations tested. Our results revealed that both the enzyme type and soil isolate type explain variation in parameters associated with temperature sensitivity. Because we found temperature sensitivity to be an inherent and variable property of an enzyme, we argue that it can be incorporated as a microbial functional trait, but only when using the MMRT definition of temperature sensitivity. We show that the Arrhenius metrics of temperature sensitivity are overly sensitive to test conditions, with activation energy changing depending on the temperature range it was calculated within. Thus, we propose the use of the MMRT definition of temperature sensitivity for accurate interpretation of temperature sensitivity of soil microbial enzymes. PMID:27909429

On the assimilation of satellite derived soil moisture in numerical weather prediction models

NASA Astrophysics Data System (ADS)

Drusch, M.

2006-12-01

Satellite derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived soil moisture over the southern United States through a nudging scheme using 6-hourly departures. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived soil moisture data sets will be discussed.

Using a spatially-distributed hydrologic biogeochemistry model to study the spatial variation of carbon processes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; Davis, K. J.; He, Y.

2016-12-01

Forest carbon processes are affected by, among other factors, soil moisture, soil temperature, soil nutrients and solar radiation. Most of the current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve the topographically driven hill-slope land surface heterogeneity or the spatial pattern of nutrient availability. A spatially distributed forest ecosystem model, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while soil nitrogen is transported among model grids via subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation information, while BBGC provides Flux-PIHM with leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). Model results suggest that the vegetation and soil carbon distribution is primarily constrained by nitorgen availability (affected by nitorgen transport via topographically driven subsurface flow), and also constrained by solar radiation and root zone soil moisture. The predicted vegetation and soil carbon distribution generally agrees with the macro pattern observed within the watershed. The coupled ecosystem-hydrologic model provides an important tool to study the impact of topography on watershed carbon processes, as well as the impact of climate change on water resources.

Importance of soil thermal regime in terrestrial ecosystem carbon dynamics in the circumpolar north

NASA Astrophysics Data System (ADS)

Jiang, Yueyang; Zhuang, Qianlai; Sitch, Stephen; O'Donnell, Jonathan A.; Kicklighter, David; Sokolov, Andrei; Melillo, Jerry

2016-07-01

In the circumpolar north (45-90°N), permafrost plays an important role in vegetation and carbon (C) dynamics. Permafrost thawing has been accelerated by the warming climate and exerts a positive feedback to climate through increasing soil C release to the atmosphere. To evaluate the influence of permafrost on C dynamics, changes in soil temperature profiles should be considered in global C models. This study incorporates a sophisticated soil thermal model (STM) into a dynamic global vegetation model (LPJ-DGVM) to improve simulations of changes in soil temperature profiles from the ground surface to 3 m depth, and its impacts on C pools and fluxes during the 20th and 21st centuries. With cooler simulated soil temperatures during the summer, LPJ-STM estimates 0.4 Pg C yr- 1 lower present-day heterotrophic respiration but 0.5 Pg C yr- 1 higher net primary production than the original LPJ model resulting in an additional 0.8 to 1.0 Pg C yr- 1 being sequestered in circumpolar ecosystems. Under a suite of projected warming scenarios, we show that the increasing active layer thickness results in the mobilization of permafrost C, which contributes to a more rapid increase in heterotrophic respiration in LPJ-STM compared to the stand-alone LPJ model. Except under the extreme warming conditions, increases in plant production due to warming and rising CO2, overwhelm the e nhanced ecosystem respiration so that both boreal forest and arctic tundra ecosystems remain a net C sink over the 21st century. This study highlights the importance of considering changes in the soil thermal regime when quantifying the C budget in the circumpolar north.

CO2 fluxes and ecosystem dynamics at five European treeless peatlands - merging data and process oriented modelling

NASA Astrophysics Data System (ADS)

Metzger, C.; Jansson, P.-E.; Lohila, A.; Aurela, M.; Eickenscheidt, T.; Belelli-Marchesini, L.; Dinsmore, K. J.; Drewer, J.; van Huissteden, J.; Drösler, M.

2014-06-01

The carbon dioxide (CO2) exchange of five different peatland systems across Europe with a wide gradient in landuse intensity, water table depth, soil fertility and climate was simulated with the process oriented CoupModel. The aim of the study was to find out to what extent CO2 fluxes measured at different sites, can be explained by common processes and parameters implemented in the model. The CoupModel was calibrated to fit measured CO2 fluxes, soil temperature, snow depth and leaf area index (LAI) and resulting differences in model parameters were analysed. Finding site independent model parameters would mean that differences in the measured fluxes could be explained solely by model input data: water table, meteorological data, management and soil inventory data. The model, utilizing a site independent configuration for most of the parameters, captured seasonal variability in the major fluxes well. Parameters that differed between sites included the rate of soil organic decomposition, photosynthetic efficiency, and regulation of the mobile carbon (C) pool from senescence to shooting in the next year. The largest difference between sites was the rate coefficient for heterotrophic respiration. Setting it to a common value would lead to underestimation of mean total respiration by a factor of 2.8 up to an overestimation by a factor of 4. Despite testing a wide range of different responses to soil water and temperature, heterotrophic respiration rates were consistently lowest on formerly drained sites and highest on the managed sites. Substrate decomposability, pH and vegetation characteristics are possible explanations for the differences in decomposition rates. Applying common parameter values for the timing of plant shooting and senescence, and a minimum temperature for photosynthesis, had only a minor effect on model performance, even though the gradient in site latitude ranged from 48° N (South-Germany) to 68° N (northern Finland). This was also true for common parameters defining the moisture and temperature response for decomposition. CoupModel is able to describe measured fluxes at different sites or under different conditions, providing that the rate of soil organic decomposition, photosynthetic efficiency, and the regulation of the mobile carbon (C) pool are estimated from available information on specific soil conditions, vegetation and management of the ecosystems.

Landscape-Scale Soil Carbon Inventories by Microclimate Decomposition

NASA Astrophysics Data System (ADS)

Beaudette, D. E.; O'Geen, A. T.

2008-12-01

Estimation of carbon stocks in rangeland and foothill ecosystems is poised to become an important service once legislation regulating greenhouse gas emissions is passed. Trading of carbon credits and greenhouse gas emission/sequestration budgets for vegetated areas is largely dependent on an accurate and scale- dependent inventory of existing conditions. Soil survey presents one possible resource for surface carbon stocks, however these data are usually not mapped at the landscape-scale. Soil-landscape modeling techniques have been successfully used in several instances to predict the spatial variation in soil carbon. Most of these studies have used site exposure (aspect angle) as a categorical proxy for terrain-induced microclimate. Our objective was to model parameters related to soil microclimate (soil temperature and moisture) for the production of detailed maps of soil carbon and organic matter quality (i.e. C:N ratio). We used a solar radiation model and long-term monitoring of soil moisture and temperature to generate several models of soil microclimate. Parameterization of the ESRA (European Solar Radiation Atlas) solar radiation model (clear-sky version) was accomplished with daily estimates of the Linke turbidity factor, using local pyranometer measurements (11 year record). Our estimated daily radiance values correlated well with local weather station data (R2 = 0.965, p < 0.001). This model is included in the popular, open source GRASS GIS. A preliminary study based on 35 sites, spanning two contrasting landform types (and lithology), revealed a statistically significant relationship between annual radiation load and carbon (R2 = 0.75, p < 0.001). A highly significant relationship between C:N ratio and annual radiation load was identified as well (R2 = 0.99, p < 0.001). Solar radiation models are simple to use, and have the potential to refine previous soil-landscape modeling efforts that relied on aspect class or angle. Models linking surface processes with microclimate can be used to directly generate estimates of carbon, or used to down-scale soil survey-based estimates.

An improved thermo-time domain reflectometry method for determination of ice contents in partially frozen soils

NASA Astrophysics Data System (ADS)

Tian, Zhengchao; Ren, Tusheng; Kojima, Yuki; Lu, Yili; Horton, Robert; Heitman, Joshua L.

2017-12-01

Measuring ice contents (θi) in partially frozen soils is important for both engineering and environmental applications. Thermo-time domain reflectometry (thermo-TDR) probes can be used to determine θi based on the relationship between θi and soil heat capacity (C). This approach, however, is accurate in partially frozen soils only at temperatures below -5 °C, and it performs poorly on clayey soils. In this study, we present and evaluate a soil thermal conductivity (λ)-based approach to determine θi with thermo-TDR probes. Bulk soil λ is described with a simplified de Vries model that relates λ to θi. From this model, θi is estimated using inverse modeling of thermo-TDR measured λ. Soil bulk density (ρb) and thermo-TDR measured liquid water content (θl) are also needed for both C-based and λ-based approaches. A theoretical analysis is performed to quantify the sensitivity of C-based and λ-based θi estimates to errors in these input parameters. The analysis indicates that the λ-based approach is less sensitive to errors in the inputs (C, λ, θl, and ρb) than is the C-based approach when the same or the same percentage errors occur. Further evaluations of the C-based and λ-based approaches are made using experimentally determined θi at different temperatures on eight soils with various textures, total water contents, and ρb. The results show that the λ-based thermo-TDR approach significantly improves the accuracy of θi measurements at temperatures ≤-5 °C. The root mean square errors of λ-based θi estimates are only half those of C-based θi. At temperatures of -1 and -2 °C, the λ-based thermo-TDR approach also provides reasonable θi, while the C-based approach fails. We conclude that the λ-based thermo-TDR method can reliably determine θi even at temperatures near the freezing point of water (0 °C).

Disentangling residence time and temperature sensitivity of microbial decomposition in a global soil carbon model

NASA Astrophysics Data System (ADS)

Exbrayat, J.-F.; Pitman, A. J.; Abramowitz, G.

2014-12-01

Recent studies have identified the first-order representation of microbial decomposition as a major source of uncertainty in simulations and projections of the terrestrial carbon balance. Here, we use a reduced complexity model representative of current state-of-the-art models of soil organic carbon decomposition. We undertake a systematic sensitivity analysis to disentangle the effect of the time-invariant baseline residence time (k) and the sensitivity of microbial decomposition to temperature (Q10) on soil carbon dynamics at regional and global scales. Our simulations produce a range in total soil carbon at equilibrium of ~ 592 to 2745 Pg C, which is similar to the ~ 561 to 2938 Pg C range in pre-industrial soil carbon in models used in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). This range depends primarily on the value of k, although the impact of Q10 is not trivial at regional scales. As climate changes through the historical period, and into the future, k is primarily responsible for the magnitude of the response in soil carbon, whereas Q10 determines whether the soil remains a sink, or becomes a source in the future mostly by its effect on mid-latitude carbon balance. If we restrict our simulations to those simulating total soil carbon stocks consistent with observations of current stocks, the projected range in total soil carbon change is reduced by 42% for the historical simulations and 45% for the future projections. However, while this observation-based selection dismisses outliers, it does not increase confidence in the future sign of the soil carbon feedback. We conclude that despite this result, future estimates of soil carbon and how soil carbon responds to climate change should be more constrained by available data sets of carbon stocks.

Simulated Surface Energy Budgets Over the Southeastern US: The GHCC Satellite Assimilation System and the NCEP Early Eta

NASA Technical Reports Server (NTRS)

Lapenta, William M.; Suggs, Ron; McNider, Richard T.; Jedlovec, Gary

1999-01-01

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. An advantage of this technique for short-range forecasts (0-48h) is that it does not require a complex land-surface formulation within the atmospheric model. As a result, we can avoid having to specify land surface characteristics such as vegetation resistances, green fraction, leaf area index, soil physical and hydraulic characteristics, stream flow, runoff, and the vertical and horizontal distribution of soil moisture.

Establishment and analysis of High-Resolution Assimilation Dataset of water-energy cycle over China

NASA Astrophysics Data System (ADS)

Wen, Xiaohang; Liao, Xiaohan; Dong, Wenjie; Yuan, Wenping

2015-04-01

For better prediction and understanding of water-energy exchange process and land-atmospheric interaction, the in-situ observed meteorological data which were acquired from China Meteorological Administration (CMA) were assimilated in the Weather Research and Forecasting (WRF) model and the monthly Green Vegetation Coverage (GVF) data, which was calculated by the Normalized Difference Vegetation Index (NDVI) of Earth Observing System Moderate-Resolution Imaging Spectroradiometer (EOS-MODIS), Digital Elevation Model (DEM) data of the Shuttle Radar Topography Mission (SRTM) system were also integrated in the WRF model over China. Further, the High-Resolution Assimilation Dataset of water-energy cycle over China (HRADC) was produced by WRF model. This dataset include 25 km horizontal resolution near surface meteorological data such as air temperature, humidity, ground temperature, and pressure at 19 levels, soil temperature and soil moisture at 4 levels, green vegetation coverage, latent heat flux, sensible heat flux, and ground heat flux for 3 hours. In this study, we 1) briefly introduce the cycling 3D-Var assimilation method; 2) Compare results of meteorological elements such as 2 m temperature, precipitation and ground temperature generated by the HRADC with the gridded observation data from CMA, and Global Land Data Assimilation System (GLDAS) output data from National Aeronautics and Space Administration (NASA). It is found that the results of 2 m temperature were improved compared with the control simulation and has effectively reproduced the observed patterns, and the simulated results of ground temperature, 0-10 cm soil temperature and specific humidity were as much closer to GLDAS outputs. Root mean square errors are reduced in assimilation run than control run, and the assimilation run of ground temperature, 0-10 cm soil temperature, radiation and surface fluxes were agreed well with the GLDAS outputs over China. The HRADC could be used in further research on the long period climatic effects and characteristics of water-energy cycle over China.

Calculations of microwave brightness temperature of rough soil surfaces: Bare field

NASA Technical Reports Server (NTRS)

Mo, T.; Schmugge, T. J.; Wang, J. R.

1985-01-01

A model for simulating the brightness temperatures of soils with rough surfaces is developed. The surface emissivity of the soil media is obtained by the integration of the bistatic scattering coefficients for rough surfaces. The roughness of a soil surface is characterized by two parameters, the surface height standard deviation sigma and its horizontal correlation length l. The model calculations are compared to the measured angular variations of the polarized brightness temperatures at both 1.4 GHz and 5 GHz frequences. A nonlinear least-squares fitting method is used to obtain the values of delta and l that best characterize the surface roughness. The effect of shadowing is incorporated by introducing a function S(theta), which represents the probability that a point on a rough surface is not shadowed by other parts of the surface. The model results for the horizontal polarization are in excellent agreement with the data. However, for the vertical polarization, some discrepancies exist between the calculations and data, particularly at the 1.4 GHz frequency. Possible causes of the discrepancy are discussed.

Assimilation of Global Radar Backscatter and Radiometer Brightness Temperature Observations to Improve Soil Moisture and Land Evaporation Estimates

NASA Technical Reports Server (NTRS)

Lievens, H.; Martens, B.; Verhoest, N. E. C.; Hahn, S.; Reichle, R. H.; Miralles, D. G.

2017-01-01

Active radar backscatter (s?) observations from the Advanced Scatterometer (ASCAT) and passive radiometer brightness temperature (TB) observations from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated either individually or jointly into the Global Land Evaporation Amsterdam Model (GLEAM) to improve its simulations of soil moisture and land evaporation. To enable s? and TB assimilation, GLEAM is coupled to the Water Cloud Model and the L-band Microwave Emission from the Biosphere (L-MEB) model. The innovations, i.e. differences between observations and simulations, are mapped onto the model soil moisture states through an Ensemble Kalman Filter. The validation of surface (0-10 cm) soil moisture simulations over the period 2010-2014 against in situ measurements from the International Soil Moisture Network (ISMN) shows that assimilating s? or TB alone improves the average correlation of seasonal anomalies (Ran) from 0.514 to 0.547 and 0.548, respectively. The joint assimilation further improves Ran to 0.559. Associated enhancements in daily evaporative flux simulations by GLEAM are validated based on measurements from 22 FLUXNET stations. Again, the singular assimilation improves Ran from 0.502 to 0.536 and 0.533, respectively for s? and TB, whereas the best performance is observed for the joint assimilation (Ran = 0.546). These results demonstrate the complementary value of assimilating radar backscatter observations together with brightness temperatures for improving estimates of hydrological variables, as their joint assimilation outperforms the assimilation of each observation type separately.

Improved soil water deficit estimation through the integration of canopy temperature measurements into a soil water balance model

USDA-ARS?s Scientific Manuscript database

Correct prediction of the dynamics of total available water in the root zone (TAWr) is critical for irrigation management as shown in the soil water balance model presented in FAO paper 56 (Allen et al., 1998). In this study, we propose a framework to improve TAWr estimation by incorporating the cro...

One-dimensional simulation of temperature and moisture in atmospheric and soil boundary layers

NASA Technical Reports Server (NTRS)

Bornstein, R. D.; Santhanam, K.

1981-01-01

Meteorologists are interested in modeling the vertical flow of heat and moisture through the soil in order to better simulate the vertical and temporal variations of the atmospheric boundary layer. The one dimensional planetary boundary layer model of is modified by the addition of transport equations to be solved by a finite difference technique to predict soil moisture.

Mechanistic modeling of reactive soil nitrogen emissions across agricultural management practices

NASA Astrophysics Data System (ADS)

Rasool, Q. Z.; Miller, D. J.; Bash, J. O.; Venterea, R. T.; Cooter, E. J.; Hastings, M. G.; Cohan, D. S.

2017-12-01

The global reactive nitrogen (N) budget has increased by a factor of 2-3 from pre-industrial levels. This increase is especially pronounced in highly N fertilized agricultural regions in summer. The reactive N emissions from soil to atmosphere can be in reduced (NH3) or oxidized (NO, HONO, N2O) forms, depending on complex biogeochemical transformations of soil N reservoirs. Air quality models like CMAQ typically neglect soil emissions of HONO and N2O. Previously, soil NO emissions estimated by models like CMAQ remained parametric and inconsistent with soil NH3 emissions. Thus, there is a need to more mechanistically and consistently represent the soil N processes that lead to reactive N emissions to the atmosphere. Our updated approach estimates soil NO, HONO and N2O emissions by incorporating detailed agricultural fertilizer inputs from EPIC, and CMAQ-modeled N deposition, into the soil N pool. EPIC addresses the nitrification, denitrification and volatilization rates along with soil N pools for agricultural soils. Suitable updates to account for factors like nitrite (NO2-) accumulation not addressed in EPIC, will also be made. The NO and N2O emissions from nitrification and denitrification are computed mechanistically using the N sub-model of DAYCENT. These mechanistic definitions use soil water content, temperature, NH4+ and NO3- concentrations, gas diffusivity and labile C availability as dependent parameters at various soil layers. Soil HONO emissions found to be most probable under high NO2- availability will be based on observed ratios of HONO to NO emissions under different soil moistures, pH and soil types. The updated scheme will utilize field-specific soil properties and N inputs across differing manure management practices such as tillage. Comparison of the modeled soil NO emission rates from the new mechanistic and existing schemes against field measurements will be discussed. Our updated framework will help to predict the diurnal and daily variability of different reactive N emissions (NO, HONO, N2O) with soil temperature, moisture and N inputs.

Agent-Based Modeling of Physical Factors That May Control the Growth of Coccidioides immitis (Valley Fever Fungus) in Soils

NASA Astrophysics Data System (ADS)

Gettings, M. E.; Fisher, F. S.

2003-12-01

A model of the spread and survival of the fungus Coccidioides immitis in soil via wind-borne spore transport has been completed using public domain agent-based modeling software. The hypothetical model posits that for a successful new site to become established, four factors must be simultaneously satisfied. 1) There must be transport of spores from a source site to sites with favorable soil geology, texture, topographic aspect, and lack of biomass competition. 2) There must be sufficient moisture for fungal growth. 3) Temperature of the surface and soil must be favorable for growth. Finally, 4) the temperature and moisture must remain in favorable ranges for a long enough time interval for the fungus to grow down to depths at which spores will survive subsequent heat, aridity, and ultraviolet radiation of the hot, dry season typical of the Southwest U.S. climate. Using agent-based modeling software, a model was built so that the effects of combinations of these controlling factors could be evaluated using realistic temperature, rain and wind models. The rain probability and amount, temperature annual and diurnal variation, and wind direction and intensity were based on the weather records at Tucson, Arizona for the 107-year period from 1894 to 2001. Favorable ground was defined using a fractal tree algorithm that emulates a drainage network in accordance with observations that favorable sites are often adjacent to drainage channels. Numerous model runs produced the following five conclusions. 1) If any property is not isotropic, for example wind direction or narrow paths of rainstorms, parts of the favorable areas will never become colonized no matter how long the model runs. 2)The spread of sites is extremely sensitive to moisture duration. The amount of wind and temperature after a rain control the length of time before a site becomes too dry. 3) The distribution of wind and rainstorm direction relative to that of the favorable sites is a strong control on the spread of colonization. East-west winds across an area that has mostly north-south favorable sites restricts spread strongly. 4) Soil temperature was the least sensitive control in the model, although it does control the ultimate dormancy of a site. Fifth, the model results cover the spectrum of complete colonization of all favorable sites from a few source sites to none, one, or two new sites in three years of model simulation. This implies the probability of new sites depends on the four factors in a Bayesian way. These results indicate that the complexity introduced in the model from site favorableness, temperature, moisture, and duration of favorable temperature and moisture conditions is adequate to explain observed distributions of real sites.

Latitude Variation of the Subsurface Lunar Temperature: Lunar Prospector Thermal Neutrons

NASA Astrophysics Data System (ADS)

Little, R. C.; Feldman, W. C.; Maurice, S.; Genetay, I.; Lawrence, D. J.; Lawson, S. L.; Gasnault, O.; Barraclough, B. L.; Elphic, R. C.; Prettyman, T. H.; Binder, A. B.

2001-05-01

Planetary thermal neutron fluxes provide a sensitive proxy for mafic and feldspathic terranes, and are also necessary for translating measured gamma-ray line strengths to elemental abundances. Both functions require a model for near surface temperatures and a knowledge of the dependence of thermal neutron flux on temperature. We have explored this dependence for a representative sample of lunar soil compositions and surface temperatures using MCNP. For all soil samples, the neutron density is found to be independent of temperature, in accord with neutron moderation theory. The thermal neutron flux, however, does vary with temperature in a way that depends on D, the ratio of macroscopic absorption to energy-loss cross sections of soil compositions. The weakest dependence is for the largest D (which corresponds to the Apollo 17 high Ti basalt in our soil selection), and the largest dependence is for the lowest D (which corresponds to ferroan anorthosite, [FAN] in our selection). For the lunar model simulated, the depth at which the thermal neutron population is most sensitive to temperature is ~30 g/cm**2. These simulations were compared with the flux of thermal neutrons measured using the Lunar Prospector neutron spectrometer over the lunar highlands using a sub-surface temperature profile that varies with latitude, L, as (Cos L)**0.25. The fit is excellent. The best fitting equatorial temperature is determined to be, Teq=224+/-40 K. This temperature range brackets the average temperature measured below the thermal wave at the equator, Tmeas = 252+/-3K [Langseth and Keihm, 1977]. The present result represents the first measurement of subsurface temperature from orbit using neutrons.

A versatile system for biological and soil chemical tests on a planetary landing craft. II - Hardware development

NASA Technical Reports Server (NTRS)

Martin, J. P.; Kok, B.; Radmer, R.

1976-01-01

A system has been under development which is designed to seek remotely for clues to life in planetary soil samples. The basic approach is a set of experiments, all having a common sensor, a gas analysis mass spectrometer which monitors gas composition in the head spaces above sealed, temperature controlled soil samples. Versatility is obtained with up to three preloaded, sealed fluid injector capsules for each of eleven soil test cells. Tests results with an engineering model has demonstrated performance capability of subsystem components such as soil distribution, gas sampling valves, injector mechanisms, temperature control, and test cell seal.

Distinct findings from the steady-state analysis of a microbial model with time-invariant or seasonal driving forces

NASA Astrophysics Data System (ADS)

Wang, G.; Mayes, M. A.

2017-12-01

Microbially-explicit soil organic matter (SOM) decomposition models are thought to be more biologically realistic than conventional models. Current testing or evaluation of microbial models majorly uses steady-state analysis with time-invariant forces (i.e., soil temperature, moisture and litter input). The findings from such simplified analyses are assumed to be capable of representing the model responses in field soil conditions with seasonal driving forces. Here we show that the steady-state modeling results with seasonal forces may result in distinct findings from the simulations with time-invariant forcing data. We evaluate the response of soil organic C (SOC) to litter addition (L+) in a subtropical pine forest using the calibrated Microbial-ENzyme Decomposition (MEND) model. We implemented two sets of modeling analyses, with each set including two scenarios, i.e., control (CR) vs. litter-addition (L+). The first set (Set1) uses fixed soil temperature and moisture, and constant litter input under Scenario CR vs. increased constant litter input under Scenario L+. The second set (Set2) employs hourly soil temperature and moisture and monthly litter input under Scenario CR. Under Scenario L+ of Set2, A logistic function with an upper plateau represents the increasing trend of litter input to SOM. We conduct long-term simulations to ensure that the models reach steady-states for Set1 or dynamic equilibrium for Set2. Litter addition of Set2 causes an increase of SOC by 29%. However, the steady-state SOC pool sizes of Set1 would not respond to L+ as long as the chemical composition of litter remained the same. Our results indicate the necessity to implement dynamic model simulations with seasonal forcing data, which could lead to modeling results qualitatively different from the steady-state analysis with time-invariant forcing data.

A mathematical model to predict the effect of heat recovery on the wastewater temperature in sewers.

PubMed

Dürrenmatt, David J; Wanner, Oskar

2014-01-01

Raw wastewater contains considerable amounts of energy that can be recovered by means of a heat pump and a heat exchanger installed in the sewer. The technique is well established, and there are approximately 50 facilities in Switzerland, many of which have been successfully using this technique for years. The planning of new facilities requires predictions of the effect of heat recovery on the wastewater temperature in the sewer because altered wastewater temperatures may cause problems for the biological processes used in wastewater treatment plants and receiving waters. A mathematical model is presented that calculates the discharge in a sewer conduit and the spatial profiles and dynamics of the temperature in the wastewater, sewer headspace, pipe, and surrounding soil. The model was implemented in the simulation program TEMPEST and was used to evaluate measured time series of discharge and temperatures. It was found that the model adequately reproduces the measured data and that the temperature and thermal conductivity of the soil and the distance between the sewer pipe and undisturbed soil are the most sensitive model parameters. The temporary storage of heat in the pipe wall and the exchange of heat between wastewater and the pipe wall are the most important processes for heat transfer. The model can be used as a tool to determine the optimal site for heat recovery and the maximal amount of extractable heat. Copyright © 2013 Elsevier Ltd. All rights reserved.

An Experimental and Modeling Study of Evaporation from Bare Soils Subjected to Natural Boundary Conditions at the Land-Atmospheric Interface

NASA Astrophysics Data System (ADS)

Smits, K. M.; Ngo, V. V.; Cihan, A.; Sakaki, T.; Illangasekare, T. H.; kathleen m smits

2011-12-01

Bare soil evaporation is a key process for water exchange between the land and the atmosphere and an important component of the water balance in semiarid and arid regions. However, there is no agreement on the best methodology to determine evaporation under different boundary conditions. Because it is difficult to measure evaporation from soil,with the exception of using lysimeters, numerous formulations have been proposed to establish a relationship between the rate of evaporation and soil moisture and/or soil temperature and thermal properties. Different formulations vary in how they partition available energy and include, among others, a classical bulk aerodynamic formulation which requires knowledge of the relative humidity at the soil surface and a more non-traditional heat balance method which requires knowledge of soil temperature and soil thermal properties. A need exists to systematically compare existing methods to experimental data under highly controlled conditions not achievable in the field. The goal of this work is to perform controlled experiments under transient conditions of soil moisture, temperature and wind at the land/atmospheric interface to test different conceptual and mathematical formulations for evaporation rate estimates and to develop appropriate numerical models to be used in simulations. In this study, to better understand the coupled water-vapor-heat flow processes in the shallow subsurface near the land surface, we modified a previously developed theory that allows non-equilibrium liquid/gas phase change with gas phase vapor diffusion to better account for evaporation under dry soil conditions. This theory was used to compare estimates of evaporation based on different formulations of the bulk aerodynamic and heat balance methods. In order to experimentally validate the numerical formulations/code, we performed a series of two-dimensional physical model experiments under varying boundary conditions using test sand for which the hydraulic and thermal properties were well characterized. We developed a unique two dimensional cell apparatus equipped with a network of sensors for automated and continuous monitoring of soil moisture, soil and air temperature and relative humidity, and wind velocity. Precision data under well-controlled transient heat and wind boundary conditions was generated. Results from numerical simulations were compared with experimental data. Results demonstrate the importance of properly characterizing soil thermal properties and accounting for dry soil conditions to properly estimate evaporation. Initial comparisons of various formulations of evaporation demonstrate the need for joint evaluation of heat and mass transfer for better modeling accuracy. Detailed comparisons are still underway. This knowledge is applicable to many current hydrologic and environmental problems to include climate modeling and the simulation of contaminant transport and volatilization in the shallow subsurface.

Soil Temperature Determines the Reaction of Olive Cultivars to Verticillium dahliae Pathotypes

PubMed Central

Calderón, Rocío; Lucena, Carlos; Trapero-Casas, José L.; Zarco-Tejada, Pablo J.; Navas-Cortés, Juan A.

2014-01-01

Background Development of Verticillium wilt in olive, caused by the soil-borne fungus Verticillium dahliae, can be influenced by biotic and environmental factors. In this study we modeled i) the combined effects of biotic factors (i.e., pathotype virulence and cultivar susceptibility) and abiotic factors (i.e., soil temperature) on disease development and ii) the relationship between disease severity and several remote sensing parameters and plant stress indicators. Methodology Plants of Arbequina and Picual olive cultivars inoculated with isolates of defoliating and non-defoliating V. dahliae pathotypes were grown in soil tanks with a range of soil temperatures from 16 to 32°C. Disease progression was correlated with plant stress parameters (i.e., leaf temperature, steady-state chlorophyll fluorescence, photochemical reflectance index, chlorophyll content, and ethylene production) and plant growth-related parameters (i.e., canopy length and dry weight). Findings Disease development in plants infected with the defoliating pathotype was faster and more severe in Picual. Models estimated that infection with the defoliating pathotype was promoted by soil temperatures in a range of 16 to 24°C in cv. Picual and of 20 to 24°C in cv. Arbequina. In the non-defoliating pathotype, soil temperatures ranging from 16 to 20°C were estimated to be most favorable for infection. The relationship between stress-related parameters and disease severity determined by multinomial logistic regression and classification trees was able to detect the effects of V. dahliae infection and colonization on water flow that eventually cause water stress. Conclusions Chlorophyll content, steady-state chlorophyll fluorescence, and leaf temperature were the best indicators for Verticillium wilt detection at early stages of disease development, while ethylene production and photochemical reflectance index were indicators for disease detection at advanced stages. These results provide a better understanding of the differential geographic distribution of V. dahliae pathotypes and to assess the potential effect of climate change on Verticillium wilt development. PMID:25330093

Numerical determination of vertical water flux based on soil temperature profiles

NASA Astrophysics Data System (ADS)

Tabbagh, Alain; Cheviron, Bruno; Henine, Hocine; Guérin, Roger; Bechkit, Mohamed-Amine

2017-07-01

High sensitivity temperature sensors (0.001 K sensitivity Pt100 thermistors), positioned at intervals of a few centimetres along a vertical soil profile, allow temperature measurements to be made which are sensitive to water flux through the soil. The development of high data storage capabilities now makes it possible to carry out in situ temperature recordings over long periods of time. By directly applying numerical models of convective and conductive heat transfer to experimental data recorded as a function of depth and time, it is possible to calculate Darcy's velocity from the convection transfer term, thus allowing water infiltration/exfiltration through the soil to be determined as a function of time between fixed depths. In the present study we consider temperature data recorded at the Boissy-le-Châtel (Seine et Marne, France) experimental station between April 16th, 2009 and March 8th, 2010, at six different depths and 10-min time intervals. We make use of two numerical finite element models to solve the conduction/convection heat transfer equation and compare their merits. These two models allow us to calculate the corresponding convective flux rate every day using a group of three sensors. The comparison of the two series of calculated values centred at 24 cm shows reliable results for periods longer than 8 days. These results are transformed in infiltration/exfiltration value after determining the soil volumetric heat capacity. The comparison with the rainfall and evaporation data for periods of ten days shows a close accordance with the behaviour of the system governed by rainfall evaporation rate during winter and spring.

Warm-adapted microbial communities enhance their carbon-use efficiency in warmed soils

NASA Astrophysics Data System (ADS)

Rousk, Johannes; Frey, Serita

2017-04-01

Ecosystem models predict that climate warming will stimulate microbial decomposition of soil carbon (C), resulting in a positive feedback to increasing temperatures. The current generation of models assume that the temperature sensitivities of microbial processes do not respond to warming. However, recent studies have suggested that the ability of microbial communities to adapt to warming can lead both strengthened and weakened feedbacks. A further complication is that the balance between microbial C used for growth to that used for respiration - the microbial carbon-use efficiency (CUE) - also has been shown through both modelling and empirical study to respond to warming. In our study, we set out to assess how chronic warming (+5°C over ambient during 9 years) of a temperate hardwood forest floor (Harvard Forest LTER, USA) affected temperature sensitivities of microbial processes in soil. To do this, we first determined the temperature relationships for bacterial growth, fungal growth, and respiration in plots exposed to warmed or ambient conditions. Secondly, we parametrised the established temperature functions microbial growth and respiration with plot-specific measured soil temperature data at a hourly time-resolution over the course of 3 years to estimate the real-time variation of in situ microbial C production and respiration. To estimate the microbial CUE, we also divided the microbial C production with the sum of microbial C production and respiration as a proxy for substrate use. We found that warm-adapted bacterial and fungal communities both shifted their temperature relationships to grow at higher rates in warm conditions which coincided with reduced rates at cool conditions. As such, their optimal temperature (Topt), minimum temperature (Tmin) and temperature sensitivity (Q10) were all increased. The temperature relationship for temperature, in contrast, was only marginally shifted in the same direction, but at a much smaller effect size, with negligible changes in Topt, Tmin and Q10 for respiration. When these physiological changes were scaled with soil temperature data to estimate real-time variation in situ during three years, the warm-adaptation resulted in elevated microbial CUEs during summer temperatures in warm-adapted communities and reduced microbial CUEs during winter temperatures. By comparing simulated microbial CUEs in cold-adapted communities exposed to warmed conditions to microbial CUEs in the warm-adapted communities exposed to those temperatures, we could demonstrate that the shifts towards warm-adapted microbial communities had selected for elevated microbial CUEs for the full range of in situ soil temperatures during three years. Our results suggest that microbial adaptation to warming will enhance microbial CUEs, shifting their balance of C use from respiration to biomass production. If our estimates scale to ecosystem level, this would imply that warm-adapted microbial communities will ultimately have the potential to store more C in soil than their cold-adapted counter parts could when exposed to warmer temperatures.

An Ecosystem Simulation Model for Methane Production and Emission from Wetlands

NASA Technical Reports Server (NTRS)

Potter, C. S.; Peterson, David L. (Technical Monitor)

1997-01-01

Previous experimental studies suggest that methane emission from wetland is influenced by multiple interactive pathways of gas production and transport through soil and sediment layers to the atmosphere. The objective of this study is to evaluate a new simulation model of methane production and emission in wetland soils that was developed initially to help identify key processes that regulate methanogenesis and net flux of CH4 to the air, but which is designed ultimately for regional simulation using remotely sensed inputs for land cover characteristics. The foundation for these computer simulations is based on a well-documented model (CASA) of ecosystem production and carbon cycling in the terrestrial blaspheme. Modifications to represent flooded wetland soils and anaerobic decomposition include three new sub-models for: (1) layered soil temperature and water table depth (WTD) as a function of daily climate drivers, (2) CH4 production within the anoxic soil layer as a function of WTD and CO2 production under poorly drained conditions, and (3) CH4 gaseous transport pathways (molecular diffusion, ebullition, and plant vascular transport) as a function of WTD and ecosystem type. The model was applied and tested using climate and ecological data to characterize tundra wetland sites near Fairbanks, Alaska studied previously by Whalen and Reeburgh. Comparison of model predictions to measurements of soil temperature and thaw depth, water-table depth, and CH4 emissions over a two year period suggest that inter-site differences in soil physical conditions and methane fluxes could be reproduced accurately for selected periods. Day-to-day comparison of predicted emissions to measured CH4 flux rates reveals good agreement during the early part of the thaw season, but the model tends to underestimate production of CH4 during the months of July and August in both test years. Important seasonal effects, including that of falling WTD during these periods, are apparently overlooked in the model formulation. Nevertheless, reasonably close agreement was achieved between the model's mean daily and seasonal estimates of CH4 flux and observed emission rates for northern wetland ecosystems. Several features of the model are identified as crucial to more accurate prediction of wetland methane emission, including the capacity to incorporate influences of localized topographic and hydrologic features on site-specific soil temperature and WTD dynamics, and mechanistic simulation of methane emission transport pathways from within the soil profile.

A new model integrating short- and long-term aging of copper added to soils

PubMed Central

Zeng, Saiqi; Li, Jumei; Wei, Dongpu

2017-01-01

Aging refers to the processes by which the bioavailability/toxicity, isotopic exchangeability, and extractability of metals added to soils decline overtime. We studied the characteristics of the aging process in copper (Cu) added to soils and the factors that affect this process. Then we developed a semi-mechanistic model to predict the lability of Cu during the aging process with descriptions of the diffusion process using complementary error function. In the previous studies, two semi-mechanistic models to separately predict short-term and long-term aging of Cu added to soils were developed with individual descriptions of the diffusion process. In the short-term model, the diffusion process was linearly related to the square root of incubation time (t1/2), and in the long-term model, the diffusion process was linearly related to the natural logarithm of incubation time (lnt). Both models could predict short-term or long-term aging processes separately, but could not predict the short- and long-term aging processes by one model. By analyzing and combining the two models, we found that the short- and long-term behaviors of the diffusion process could be described adequately using the complementary error function. The effect of temperature on the diffusion process was obtained in this model as well. The model can predict the aging process continuously based on four factors—soil pH, incubation time, soil organic matter content and temperature. PMID:28820888

Testing the capability of ORCHIDEE land surface model to simulate Arctic ecosystems: Sensitivity analysis and site-level model calibration

NASA Astrophysics Data System (ADS)

Dantec-Nédélec, S.; Ottlé, C.; Wang, T.; Guglielmo, F.; Maignan, F.; Delbart, N.; Valdayskikh, V.; Radchenko, T.; Nekrasova, O.; Zakharov, V.; Jouzel, J.

2017-06-01

The ORCHIDEE land surface model has recently been updated to improve the representation of high-latitude environments. The model now includes improved soil thermodynamics and the representation of permafrost physical processes (soil thawing and freezing), as well as a new snow model to improve the representation of the seasonal evolution of the snow pack and the resulting insulation effects. The model was evaluated against data from the experimental sites of the WSibIso-Megagrant project (www.wsibiso.ru). ORCHIDEE was applied in stand-alone mode, on two experimental sites located in the Yamal Peninsula in the northwestern part of Siberia. These sites are representative of circumpolar-Arctic tundra environments and differ by their respective fractions of shrub/tree cover and soil type. After performing a global sensitivity analysis to identify those parameters that have most influence on the simulation of energy and water transfers, the model was calibrated at local scale and evaluated against in situ measurements (vertical profiles of soil temperature and moisture, as well as active layer thickness) acquired during summer 2012. The results show how sensitivity analysis can identify the dominant processes and thereby reduce the parameter space for the calibration process. We also discuss the model performance at simulating the soil temperature and water content (i.e., energy and water transfers in the soil-vegetation-atmosphere continuum) and the contribution of the vertical discretization of the hydrothermal properties. This work clearly shows, at least at the two sites used for validation, that the new ORCHIDEE vertical discretization can represent the water and heat transfers through complex cryogenic Arctic soils—soils which present multiple horizons sometimes with peat inclusions. The improved model allows us to prescribe the vertical heterogeneity of the soil hydrothermal properties.

Is Miscanthus a High Risk Biofuel Feedstock Prospect for the Upper Midwest US?

NASA Astrophysics Data System (ADS)

Kucharik, C. J.; VanLoocke, A. D.

2011-12-01

Miscanthus is a highly productive C4 perennial rhizomatous grass that is native to Southeast Asia, but its potential as a feedstock for cellulosic biofuel in the Midwest US is intriguing given extremely high productivity for low amounts of agrochemical inputs. However, Miscanthus x giganteus, a key variety currently studied is not planted from seed, but rather from rhizomes planted at a soil depth of 5 to 10 cm. Therefore, it is costly to establish on the basis of both time and money, making it a potentially risky investment in geographic regions that experience cold wintertime temperatures that can effectively kill the crop. The 50% kill threshold for M. giganteus rhizomes occurs when soil temperatures fall below -3.5C, which may contribute to a high risk of improper establishment during the first few seasons. Our first objective here was to study a historical, simulated reconstruction of daily wintertime soil temperatures at high spatial resolution (5 min) across the Midwest US from 1948-2007, and use this information to quantify the frequency that lethal soil temperature thresholds for Miscanthus were reached. A second objective was to investigate how the use of crop residues could impact wintertime soil temperatures. In this study, a dynamic agroecosystem model (Agro-IBIS) that has been modified to simulate Miscanthus growth and phenology was used in conjunction with high-resolution datasets of soil texture and daily gridded weather data. Model simulations suggest that across the states of North and South Dakota, Nebraska, Minnesota, Wisconsin, Michigan, and the northern half of Iowa, the kill threshold of -3.5C at a 10cm soil depth was reached in 70-95% of the simulation years. A boundary representing a 50% likelihood of reaching -3.5C at 10cm depth in any given year runs approximately from east central Colorado, thought northern Kansas and Missouri, through central Illinois, central Indiana, and central Ohio. An analysis of monthly mean 10cm soil temperatures illustrates that temperatures colder than the kill threshold generally exist in January and February north and west of a line running from central Nebraska to north central Illinois, through southeastern Wisconsin and northern lower Michigan. These results suggest that a bioclimatic limit to successful establishment might be positioned somewhere through the central portion of the Corn Belt, but this depends on how risk is defined in the future. Model simulations suggest that a significant warming trend of wintertime soil temperatures existed across the region; soil temperatures have increased 3 to 4C in the past 60 years at 10cm as well as to depths as great as 50 to 100cm across northern and western portions of the Midwest. This warming trend, in combination with the strategic use of straw and other crop residues may reduce the risk of failure of establishing Miscanthus x giganteus. However, any adaptive management will not completely eliminate the high risk of cold soil temperatures in regions that are currently being targeted to support cellulosic biofuel production in the next several decades.

Influence of pyrolysis temperature on composted sewage sludge biochar priming effect in a loamy soil.

PubMed

Méndez, A; Tarquis, A M; Saa-Requejo, A; Guerrero, F; Gascó, G

2013-10-01

Biochar is a carbon-rich solid product obtained by the pyrolysis of organic materials. The carbon stability of biochar allows that it can be applied to soil for long-term carbon storage. This carbon stability is greatly influenced by the pyrolysis temperature and the raw material used for biochar production. The aim of the present work is to study the soil carbon sequestration after the application of biochar from sewage sludge (SL) pyrolysis at two different temperatures (400 and 600 °C). For this purpose, soil CO2 emissions were measured for 80 d in an incubation experiment after soil amendment with the SL and each biochar at a dosage of 8 wt%. Biochar reduced the CO2 emissions during incubation between 11% and 32% relative to the SL treatment. The CO2 data were fit to a dual exponential model, and the CO2 emissions were simulated at different times (1, 5 and 10 yr). Additionally, the kinetics of the CO2 evolution from SL, two biochar samples, soil and amended soil were well fit to a dual first-order kinetic model with correlation coefficients greater than 0.93. The simulation of CO2 emissions from the soil by applying the proposed double first-order kinetic model (kg CO2-C ha(-1)) showed a reduction of CO2 emissions between 301 and 932 kg CO2-C ha(-1)with respect to the direct application of raw sewage sludge after 10 yr. Copyright © 2013 Elsevier Ltd. All rights reserved.

Maximum Entropy Production Modeling of Evapotranspiration Partitioning on Heterogeneous Terrain and Canopy Cover: advantages and limitations.

NASA Astrophysics Data System (ADS)

Gutierrez-Jurado, H. A.; Guan, H.; Wang, J.; Wang, H.; Bras, R. L.; Simmons, C. T.

2015-12-01

Quantification of evapotranspiration (ET) and its partition over regions of heterogeneous topography and canopy poses a challenge using traditional approaches. In this study, we report the results of a novel field experiment design guided by the Maximum Entropy Production model of ET (MEP-ET), formulated for estimating evaporation and transpiration from homogeneous soil and canopy. A catchment with complex terrain and patchy vegetation in South Australia was instrumented to measure temperature, humidity and net radiation at soil and canopy surfaces. Performance of the MEP-ET model to quantify transpiration and soil evaporation was evaluated during wet and dry conditions with independently and directly measured transpiration from sapflow and soil evaporation using the Bowen Ratio Energy Balance (BREB). MEP-ET transpiration shows remarkable agreement with that obtained through sapflow measurements during wet conditions, but consistently overestimates the flux during dry periods. However, an additional term introduced to the original MEP-ET model accounting for higher stomatal regulation during dry spells, based on differences between leaf and air vapor pressure deficits and temperatures, significantly improves the model performance. On the other hand, MEP-ET soil evaporation is in good agreement with that from BREB regardless of moisture conditions. The experimental design allows a plot and tree scale quantification of evaporation and transpiration respectively. This study confirms for the first time that the MEP-ET originally developed for homogeneous open bare soil and closed canopy can be used for modeling ET over heterogeneous land surfaces. Furthermore, we show that with the addition of an empirical function simulating the plants ability to regulate transpiration, and based on the same measurements of temperature and humidity, the method can produce reliable estimates of ET during both wet and dry conditions without compromising its parsimony.

PEATBOG: a biogeochemical model for analyzing coupled carbon and nitrogen dynamics in northern peatlands

NASA Astrophysics Data System (ADS)

Wu, Y.; Blodau, C.

2013-08-01

Elevated nitrogen deposition and climate change alter the vegetation communities and carbon (C) and nitrogen (N) cycling in peatlands. To address this issue we developed a new process-oriented biogeochemical model (PEATBOG) for analyzing coupled carbon and nitrogen dynamics in northern peatlands. The model consists of four submodels, which simulate: (1) daily water table depth and depth profiles of soil moisture, temperature and oxygen levels; (2) competition among three plants functional types (PFTs), production and litter production of plants; (3) decomposition of peat; and (4) production, consumption, diffusion and export of dissolved C and N species in soil water. The model is novel in the integration of the C and N cycles, the explicit spatial resolution belowground, the consistent conceptualization of movement of water and solutes, the incorporation of stoichiometric controls on elemental fluxes and a consistent conceptualization of C and N reactivity in vegetation and soil organic matter. The model was evaluated for the Mer Bleue Bog, near Ottawa, Ontario, with regards to simulation of soil moisture and temperature and the most important processes in the C and N cycles. Model sensitivity was tested for nitrogen input, precipitation, and temperature, and the choices of the most uncertain parameters were justified. A simulation of nitrogen deposition over 40 yr demonstrates the advantages of the PEATBOG model in tracking biogeochemical effects and vegetation change in the ecosystem.

PEATBOG: a biogeochemical model for analyzing coupled carbon and nitrogen dynamics in northern peatlands

NASA Astrophysics Data System (ADS)

Wu, Y.; Blodau, C.

2013-03-01

Elevated nitrogen deposition and climate change alter the vegetation communities and carbon (C) and nitrogen (N) cycling in peatlands. To address this issue we developed a new process-oriented biogeochemical model (PEATBOG) for analyzing coupled carbon and nitrogen dynamics in northern peatlands. The model consists of four submodels, which simulate: (1) daily water table depth and depth profiles of soil moisture, temperature and oxygen levels; (2) competition among three plants functional types (PFTs), production and litter production of plants; (3) decomposition of peat; and (4) production, consumption, diffusion and export of dissolved C and N species in soil water. The model is novel in the integration of the C and N cycles, the explicit spatial resolution belowground, the consistent conceptualization of movement of water and solutes, the incorporation of stoichiometric controls on elemental fluxes and a consistent conceptualization of C and N reactivity in vegetation and soil organic matter. The model was evaluated for the Mer Bleue Bog, near Ottawa, Ontario, with regards to simulation of soil moisture and temperature and the most important processes in the C and N cycles. Model sensitivity was tested for nitrogen input, precipitation, and temperature, and the choices of the most uncertain parameters were justified. A simulation of nitrogen deposition over 40 yr demonstrates the advantages of the PEATBOG model in tracking biogeochemical effects and vegetation change in the ecosystem.

Modeling uncertainty and correlation in soil properties using Restricted Pairing and implications for ensemble-based hillslope-scale soil moisture and temperature estimation

NASA Astrophysics Data System (ADS)

Flores, A. N.; Entekhabi, D.; Bras, R. L.

2007-12-01

Soil hydraulic and thermal properties (SHTPs) affect both the rate of moisture redistribution in the soil column and the volumetric soil water capacity. Adequately constraining these properties through field and lab analysis to parameterize spatially-distributed hydrology models is often prohibitively expensive. Because SHTPs vary significantly at small spatial scales individual soil samples are also only reliably indicative of local conditions, and these properties remain a significant source of uncertainty in soil moisture and temperature estimation. In ensemble-based soil moisture data assimilation, uncertainty in the model-produced prior estimate due to associated uncertainty in SHTPs must be taken into account to avoid under-dispersive ensembles. To treat SHTP uncertainty for purposes of supplying inputs to a distributed watershed model we use the restricted pairing (RP) algorithm, an extension of Latin Hypercube (LH) sampling. The RP algorithm generates an arbitrary number of SHTP combinations by sampling the appropriate marginal distributions of the individual soil properties using the LH approach, while imposing a target rank correlation among the properties. A previously-published meta- database of 1309 soils representing 12 textural classes is used to fit appropriate marginal distributions to the properties and compute the target rank correlation structure, conditioned on soil texture. Given categorical soil textures, our implementation of the RP algorithm generates an arbitrarily-sized ensemble of realizations of the SHTPs required as input to the TIN-based Realtime Integrated Basin Simulator with vegetation dynamics (tRIBS+VEGGIE) distributed parameter ecohydrology model. Soil moisture ensembles simulated with RP- generated SHTPs exhibit less variance than ensembles simulated with SHTPs generated by a scheme that neglects correlation among properties. Neglecting correlation among SHTPs can lead to physically unrealistic combinations of parameters that exhibit implausible hydrologic behavior when input to the tRIBS+VEGGIE model.

Comparison of effects of cold-region soil/snow processes and the uncertainties from model forcing data on permafrost physical characteristics

DOE PAGES

Barman, Rahul; Jain, Atul K.

2016-03-28

Here, we used a land surface model to (1) evaluate the influence of recent improvements in modeling cold-region soil/snow physics on near-surface permafrost physical characteristics (within 0–3 m soil column) in the northern high latitudes (NHL) and (2) compare them with uncertainties from climate and land-cover data sets. Specifically, four soil/snow processes are investigated: deep soil energetics, soil organic carbon (SOC) effects on soil properties, wind compaction of snow, and depth hoar formation. In the model, together they increased the contemporary NHL permafrost area by 9.2 × 10 6 km 2 (from 2.9 to 12.3—without and with these processes, respectively)more » and reduced historical degradation rates. In comparison, permafrost area using different climate data sets (with annual air temperature difference of ~0.5°C) differed by up to 2.3 × 10 6 km 2, with minimal contribution of up to 0.7 × 10 6 km 2 from substantial land-cover differences. Individually, the strongest role in permafrost increase was from deep soil energetics, followed by contributions from SOC and wind compaction, while depth hoar decreased permafrost. The respective contribution on 0–3 m permafrost stability also followed a similar pattern. However, soil temperature and moisture within vegetation root zone (~0–1 m), which strongly influence soil biogeochemistry, were only affected by the latter three processes. The ecosystem energy and water fluxes were impacted the least due to these soil/snow processes. While it is evident that simulated permafrost physical characteristics benefit from detailed treatment of cold-region biogeophysical processes, we argue that these should also lead to integrated improvements in modeling of biogeochemistry.« less

Soil Methanotrophy Model (MeMo v1.0): a process-based model to quantify global uptake of atmospheric methane by soil

NASA Astrophysics Data System (ADS)

Murguia-Flores, Fabiola; Arndt, Sandra; Ganesan, Anita L.; Murray-Tortarolo, Guillermo; Hornibrook, Edward R. C.

2018-06-01

Soil bacteria known as methanotrophs are the sole biological sink for atmospheric methane (CH4), a potent greenhouse gas that is responsible for ˜ 20 % of the human-driven increase in radiative forcing since pre-industrial times. Soil methanotrophy is controlled by a plethora of factors, including temperature, soil texture, moisture and nitrogen content, resulting in spatially and temporally heterogeneous rates of soil methanotrophy. As a consequence, the exact magnitude of the global soil sink, as well as its temporal and spatial variability, remains poorly constrained. We developed a process-based model (Methanotrophy Model; MeMo v1.0) to simulate and quantify the uptake of atmospheric CH4 by soils at the global scale. MeMo builds on previous models by Ridgwell et al. (1999) and Curry (2007) by introducing several advances, including (1) a general analytical solution of the one-dimensional diffusion-reaction equation in porous media, (2) a refined representation of nitrogen inhibition on soil methanotrophy, (3) updated factors governing the influence of soil moisture and temperature on CH4 oxidation rates and (4) the ability to evaluate the impact of autochthonous soil CH4 sources on uptake of atmospheric CH4. We show that the improved structural and parametric representation of key drivers of soil methanotrophy in MeMo results in a better fit to observational data. A global simulation of soil methanotrophy for the period 1990-2009 using MeMo yielded an average annual sink of 33.5 ± 0.6 Tg CH4 yr-1. Warm and semi-arid regions (tropical deciduous forest and open shrubland) had the highest CH4 uptake rates of 602 and 518 mg CH4 m-2 yr-1, respectively. In these regions, favourable annual soil moisture content ( ˜ 20 % saturation) and low seasonal temperature variations (variations < ˜ 6 °C) provided optimal conditions for soil methanotrophy and soil-atmosphere gas exchange. In contrast to previous model analyses, but in agreement with recent observational data, MeMo predicted low fluxes in wet tropical regions because of refinements in formulation of the influence of excess soil moisture on methanotrophy. Tundra and mixed forest had the lowest simulated CH4 uptake rates of 176 and 182 mg CH4 m-2 yr-1, respectively, due to their marked seasonality driven by temperature. Global soil uptake of atmospheric CH4 was decreased by 4 % by the effect of nitrogen inputs to the system; however, the direct addition of fertilizers attenuated the flux by 72 % in regions with high agricultural intensity (i.e. China, India and Europe) and by 4-10 % in agriculture areas receiving low rates of N input (e.g. South America). Globally, nitrogen inputs reduced soil uptake of atmospheric CH4 by 1.38 Tg yr-1, which is 2-5 times smaller than reported previously. In addition to improved characterization of the contemporary soil sink for atmospheric CH4, MeMo provides an opportunity to quantify more accurately the relative importance of soil methanotrophy in the global CH4 cycle in the past and its capacity to contribute to reduction of atmospheric CH4 levels under future global change scenarios.

Microwave remote sensing of soil moisture content over bare and vegetated fields

NASA Technical Reports Server (NTRS)

Wang, J. R.; Shiue, J. C.; Mcmurtrey, J. E., III (Principal Investigator)

1980-01-01

The author has identified the following significant results. Ground truth of soil moisture content, and ambient air and soil temperatures were acquired concurrently with measurements of soil moisture in bare fields and fields covered with grass, corn, and soybeans obtained with 1.4 GHz and 5 GHz radiometers mounted on a truck. The biomass of the vegetation was sampled about once a week. The measured brightness temperatures over the bare fields were compared with those of radiative transfer model calculations using as inputs the acquired soil moisture and temperatures data with appropriate values of dielectric constants for soil-water mixtures. A good agreement was found between the calculated and measured results over 10 deg to 70 deg incident angles. The presence of vegetation reduced the sensitivity of soil moisture sensing. At 1.4 GHz the sensitivity reduction ranged from about 20% for 10 cm tall grassland cover to over 50 to 60% for the dense soybean field. At 5 GHz corresponding reduction in sensitivity ranged from approximately 70% to approximately 90%.

Microwave remote sensing of soil moisture content over bare and vegetated fields

NASA Technical Reports Server (NTRS)

Wang, J. R.; Shiue, J. C.; Mcmurtrey, J. E., III

1980-01-01

Remote measurements of soil moisture contents over bare fields and fields covered with orchard grass, corn, and soybean were made during October 1979 with 1.4 GHz and 5 GHz microwave radiometers mounted on a truck. Ground truth of soil moisture content, ambient air, and soil temperatures was acquired concurrently with the radiometric measurements. The biomass of the vegetation was sampled about once a week. The measured brightness temperatures over bare fields were compared with those of radiative transfer model calculations using as inputs the acquired soil moisture and temperature data with appropriate values of dielectric constants for soil-water mixtures. Good agreement was found between the calculated and the measured results over 10-70 deg incident angles. The presence of vegetation was found to reduce the sensitivity of soil moisture sensing. At 1.4 GHz the sensitivity reduction ranged from approximately 20% for 10-cm tall grassland to over 60% for the dense soybean field. At 5 GHz the corresponding reduction in sensitivity ranged from approximately 70 to approximately 90%.

Parameterization and Modeling of Coupled Heat and Mass Transport in the Vadose Zone

NASA Astrophysics Data System (ADS)

Mohanty, B.; Yang, Z.

2016-12-01

The coupled heat and mass transport in the vadose zone is essentially a multiphysics issue. Addressing this issue appropriately has remarkable impacts on soil physical, chemical and biological processes. To data, most coupled heat and water transport modeling has focused on the interactions between liquid water, water vapor and heat transport in homogeneous and layered soils. Comparatively little work has been done on structured soils where preferential infiltration and evaporation flow occurs. Moreover, the traditional coupled heat and water model usually neglects the nonwetting phase air flow, which was found to be significant in the state-of-the-art modeling framework for coupled heat and water transport investigation. However, the parameterizations for the nonwetting phase air permeability largely remain elusive so far. In order to address the above mentioned limitations, this study aims to develop and validate a predictive multiphysics modeling framework for coupled soil heat and water transport in the heterogeneous shallow subsurface. To this end, the following research work is specifically conducted: (a) propose an improved parameterization to better predict the nonwetting phase relative permeability; (b) determine the dynamics, characteristics and processes of simultaneous soil moisture and heat movement in homogeneous and layered soils; and (c) develop a nonisothermal dual permeability model for heterogeneous structured soils. The results of our studies showed that: (a) the proposed modified nonwetting phase relative permeability models are much more accurate, which can be adopted for better parameterization in the subsequent nonisothermal two phase flow models; (b) the isothermal liquid film flow, nonwetting phase gas flow and liquid-vapor phase change non-equilibrium effects are significant in the arid and semiarid environments (Riverside, California and Audubon, Arizona); and (c) the developed nonisothermal dual permeability model is capable of characterizing the preferential evaporation path in the heterogeneous structured soils due to the fact that the capillary forces divert the pore water from coarse-textured soils (high temperature region) toward the fine-textured soils (low temperature region).

A simple temperature-based method to estimate heterogeneous frozen ground within a distributed watershed model

NASA Astrophysics Data System (ADS)

Follum, Michael L.; Niemann, Jeffrey D.; Parno, Julie T.; Downer, Charles W.

2018-05-01

Frozen ground can be important to flood production and is often heterogeneous within a watershed due to spatial variations in the available energy, insulation by snowpack and ground cover, and the thermal and moisture properties of the soil. The widely used continuous frozen ground index (CFGI) model is a degree-day approach and identifies frozen ground using a simple frost index, which varies mainly with elevation through an elevation-temperature relationship. Similarly, snow depth and its insulating effect are also estimated based on elevation. The objective of this paper is to develop a model for frozen ground that (1) captures the spatial variations of frozen ground within a watershed, (2) allows the frozen ground model to be incorporated into a variety of watershed models, and (3) allows application in data sparse environments. To do this, we modify the existing CFGI method within the gridded surface subsurface hydrologic analysis watershed model. Among the modifications, the snowpack and frost indices are simulated by replacing air temperature (a surrogate for the available energy) with a radiation-derived temperature that aims to better represent spatial variations in available energy. Ground cover is also included as an additional insulator of the soil. Furthermore, the modified Berggren equation, which accounts for soil thermal conductivity and soil moisture, is used to convert the frost index into frost depth. The modified CFGI model is tested by application at six test sites within the Sleepers River experimental watershed in Vermont. Compared to the CFGI model, the modified CFGI model more accurately captures the variations in frozen ground between the sites, inter-annual variations in frozen ground depths at a given site, and the occurrence of frozen ground.

Root-soil air gap and resistance to water flow at the soil-root interface of Robinia pseudoacacia.

PubMed

Liu, X P; Zhang, W J; Wang, X Y; Cai, Y J; Chang, J G

2015-12-01

During periods of water deficit, growing roots may shrink, retaining only partial contact with the soil. In this study, known mathematical models were used to calculate the root-soil air gap and water flow resistance at the soil-root interface, respectively, of Robinia pseudoacacia L. under different water conditions. Using a digital camera, the root-soil air gap of R. pseudoacacia was investigated in a root growth chamber; this root-soil air gap and the model-inferred water flow resistance at the soil-root interface were compared with predictions based on a separate outdoor experiment. The results indicated progressively greater root shrinkage and loss of root-soil contact with decreasing soil water potential. The average widths of the root-soil air gap for R. pseudoacacia in open fields and in the root growth chamber were 0.24 and 0.39 mm, respectively. The resistance to water flow at the soil-root interface in both environments increased with decreasing soil water potential. Stepwise regression analysis demonstrated that soil water potential and soil temperature were the best predictors of variation in the root-soil air gap. A combination of soil water potential, soil temperature, root-air water potential difference and soil-root water potential difference best predicted the resistance to water flow at the soil-root interface. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

[Soil organic carbon pools and their turnover under two different types of forest in Xiao-xing'an Mountains, Northeast China].

PubMed

Gao, Fei; Jiang, Hang; Cui, Xiao-yang

2015-07-01

Soil samples collected from virgin Korean pine forest and broad-leaved secondary forest in Xiaoxing'an Mountains, Northeast China were incubated in laboratory at different temperatures (8, 18 and 28 °C) for 160 days, and the data from the incubation experiment were fitted to a three-compartment, first-order kinetic model which separated soil organic carbon (SOC) into active, slow, and resistant carbon pools. Results showed that the soil organic carbon mineralization rates and the cumulative amount of C mineralized (all based on per unit of dry soil mass) of the broad-leaved secondary forest were both higher than that of the virgin Korean pine forest, whereas the mineralized C accounted for a relatively smaller part of SOC in the broad-leaved secondary forest soil. Soil active and slow carbon pools decreased with soil depth, while their proportions in SOC increased. Soil resistant carbon pool and its contribution to SOC were both greater in the broad-leaved secondary forest soil than in the virgin Korean pine forest soil, suggesting that the broad-leaved secondary forest soil organic carbon was relatively more stable. The mean retention time (MRT) of soil active carbon pool ranged from 9 to 24 d, decreasing with soil depth; while the MRT of slow carbon pool varied between 7 and 24 a, increasing with soil depth. Soil active carbon pool and its proportion in SOC increased linearly with incubation temperature, and consequently, decreased the slow carbon pool. Virgin Korean pine forest soils exhibited a higher increasing rate of active carbon pool along temperature gradient than the broad-leaved secondary forest soils, indicating that the organic carbon pool of virgin Korean pine forest soil was relatively more sensitive to temperature change.

Evaluation of hydrologic components of community land model 4 and bias identification

DOE PAGES

Du, Enhao; Vittorio, Alan Di; Collins, William D.

2015-04-01

Runoff and soil moisture are two key components of the global hydrologic cycle that should be validated at local to global scales in Earth System Models (ESMs) used for climate projection. Here, we have evaluated the runoff and surface soil moisture output by the Community Climate System Model (CCSM) along with 8 other models from the Coupled Model Intercomparison Project (CMIP5) repository using satellite soil moisture observations and stream gauge corrected runoff products. A series of Community Land Model (CLM) runs forced by reanalysis and coupled model outputs was also performed to identify atmospheric drivers of biases and uncertainties inmore » the CCSM. Results indicate that surface soil moisture simulations tend to be positively biased in high latitude areas by most selected CMIP5 models except CCSM, FGOALS, and BCC, which share similar land surface model code. With the exception of GISS, runoff simulations by all selected CMIP5 models were overestimated in mountain ranges and in most of the Arctic region. In general, positive biases in CCSM soil moisture and runoff due to precipitation input error were offset by negative biases induced by temperature input error. Excluding the impact from atmosphere modeling, the global mean of seasonal surface moisture oscillation was out of phase compared to observations in many years during 1985–2004. The CLM also underestimated runoff in the Amazon, central Africa, and south Asia, where soils all have high clay content. We hypothesize that lack of a macropore flow mechanism is partially responsible for this underestimation. However, runoff was overestimated in the areas covered by volcanic ash soils (i.e., Andisols), which might be associated with poor soil porosity representation in CLM. Finally, our results indicate that CCSM predictability of hydrology could be improved by addressing the compensating errors associated with precipitation and temperature and updating the CLM soil representation.« less

Using satellite observations to improve model estimates of CO2 and CH4 flux: a Metropolis Hastings Markov Chain Monte Carlo approach

NASA Astrophysics Data System (ADS)

MacBean, Natasha; Disney, Mathias; Lewis, Philip; Ineson, Phil

2010-05-01

Peatlands are wetlands with an organic soil layer of >30cm (Limpens et al., 2008) that occur beneath a living plant layer as a result of the waterlogged nature of the soil restricting complete decay of the biomass (Charman, 2002). Peatlands are important ecosystems; boreal and subarctic peatlands are estimated to contain 455Pg of carbon (Gorham, 1991), about 15-30% of the world's soil carbon (Limpens et al., 2008), and yet constitute less than 3% of the world's total land area (Lai, 2009). Peatlands not only sequester CO2 through photosynthesis and the partial decomposition of organic matter but they release methane (CH4) due to anaerobic microbial activity under waterlogged conditions. The balance is even more complex, as microbial consumption of CH4 can result in additional CO2 being emitted to the atmosphere. Wetlands are the main source of natural CH4 (Le Mer and Roger, 2001). Northern wetlands contribute about 35Tgyr-1 (Bubier and Moore, 1994). The uncertainty on this estimate is large 1 mgm-2yr-1 to 2200 mgm-2yr-1. Given that CH4 is 20 to 30 times more efficient at absorbing infrared radiation than CO2 there is a need to better quantify CH4 emissions and their role in the net carbon balance of peatlands. Two of the key variables in the calculation of CH4 production are water table depth and soil temperature. Water table depth is important as methanogenic bacteria are predominantly active in the anoxic zone. In order to accurately model the water table depth a correct representation of the whole soil moisture profile is important. Soil moisture and soil temperature are important variables in model calculations, as they affect the decomposition of carbon in the soil, as well as influencing the water and energy fluxes at the surface - atmosphere boundary. Microwave measurements of surface soil moisture and thermal measurements of land surface temperature from satellites can theoretically be used to improve the representation of the hydrology and soil temperature profile as a whole. We present results from an Observing System Simulation Experiment (OSSE) designed to investigate the impact of management and climate change on peatland carbon fluxes, as well as how observations from satellites may be able to constrain modeled carbon fluxes. We use an adapted version of the Carnegie-Ames-Stanford Approach (CASA) model (Potter et al., 1993) that includes a representation of methane dynamics (Potter, 1997). The model formulation is further modified to allow for assimilation of satellite observations of surface soil moisture and land surface temperature. The observations are used to update model estimates using a Metropolis Hastings Markov Chain Monte Carlo (MCMC) approach. We examine the effect of temporal frequency and precision of satellite observations with a view to establishing how, and at what level, such observations would make a significant improvement in model uncertainty. We compare this with the system characteristics of existing and future satellites. We believe this is the first attempt to assimilate surface soil moisture and land surface temperature into an ecosystem model that includes a full representation of CH4 flux. Bubier, J., and T. Moore (1994), An ecological perspective on methane emissions from northern wetlands, TREE, 9, 460-464. Charman, D. (2002), Peatlands and Environmental Change, JohnWiley and Sons, Ltd, England. Gorham, E. (1991), Northern peatlands: Role in the carbon cycle and probable responses to climatic warming, Ecological Applications, 1, 182-195. Lai, D. (2009), Methane dynamics in northern peatlands: A review, Pedosphere, 19, 409-421. Le Mer, J., and P. Roger (2001), Production, oxidation, emission and consumption of methane by soils: A review, European Journal of Soil Biology, 37, 25-50. Limpens, J., F. Berendse, J. Canadell, C. Freeman, J. Holden, N. Roulet, H. Rydin, and Potter, C. (1997), An ecosystem simulation model for methane production and emission from wetlands, Global Biogeochemical Cycles, 11, 495-506. Potter, C., J. Randerson, C. Field, P. Matson, P. Vitousek, H. Mooney, and S. Klooster (1993), Terrestrial ecosystem production: A process model based on global satellite and surface data, Global Biogeochemical Cycles, 7, 811-841.

Thermal niche for in situ seed germination by Mediterranean mountain streams: model prediction and validation for Rhamnus persicifolia seeds

PubMed Central

Porceddu, Marco; Mattana, Efisio; Pritchard, Hugh W.; Bacchetta, Gianluigi

2013-01-01

Background and Aims Mediterranean mountain species face exacting ecological conditions of rainy, cold winters and arid, hot summers, which affect seed germination phenology. In this study, a soil heat sum model was used to predict field emergence of Rhamnus persicifolia, an endemic tree species living at the edge of mountain streams of central eastern Sardinia. Methods Seeds were incubated in the light at a range of temperatures (10–25 and 25/10 °C) after different periods (up to 3 months) of cold stratification at 5 °C. Base temperatures (Tb), and thermal times for 50 % germination (θ50) were calculated. Seeds were also buried in the soil in two natural populations (Rio Correboi and Rio Olai), both underneath and outside the tree canopy, and exhumed at regular intervals. Soil temperatures were recorded using data loggers and soil heat sum (°Cd) was calculated on the basis of the estimated Tb and soil temperatures. Key Results Cold stratification released physiological dormancy (PD), increasing final germination and widening the range of germination temperatures, indicative of a Type 2 non-deep PD. Tb was reduced from 10·5 °C for non-stratified seeds to 2·7 °C for seeds cold stratified for 3 months. The best thermal time model was obtained by fitting probit germination against log °Cd. θ50 was 2·6 log °Cd for untreated seeds and 2·17–2·19 log °Cd for stratified seeds. When θ50 values were integrated with soil heat sum estimates, field emergence was predicted from March to April and confirmed through field observations. Conclusions Tb and θ50 values facilitated model development of the thermal niche for in situ germination of R. persicifolia. These experimental approaches may be applied to model the natural regeneration patterns of other species growing on Mediterranean mountain waterways and of physiologically dormant species, with overwintering cold stratification requirement and spring germination. PMID:24201139

Reduced substrate supply limits the temperature response of soil organic carbon decomposition

Treesearch

Cinzia Fissore; Christian P. Giardina; Randall K. Kolka

2013-01-01

Controls on the decomposition rate of soil organic carbon (SOC), especially the more stable fraction of SOC, remain poorly understood, with implications for confidence in efforts to model terrestrial C balance under future climate. We investigated the role of substrate supply in the temperature sensitivity of SOC decomposition in laboratory incubations of coarse-...

The effects of substrate supply on the temperature sensitivity of soil carbon decomposition

Treesearch

Cinzia Fissore; Christian P. Giardina; Randall K. Kolka

2013-01-01

Controls on the decomposition rate of soil organic carbon (SOC), especially the more stable fraction of SOC, remain poorly understood, with implications for confidence in efforts to model terrestrial C balance under future climate. We investigated the role of substrate supply in the temperature sensitivity of SOC decomposition in laboratory incubations of coarse-...

Discrimination of soil hydraulic properties by combined thermal infrared and microwave remote sensing

NASA Technical Reports Server (NTRS)

Vandegriend, A. A.; Oneill, P. E.

1986-01-01

Using the De Vries models for thermal conductivity and heat capacity, thermal inertia was determined as a function of soil moisture for 12 classes of soil types ranging from sand to clay. A coupled heat and moisture balance model was used to describe the thermal behavior of the top soil, while microwave remote sensing was used to estimate the soil moisture content of the same top soil. Soil hydraulic parameters are found to be very highly correlated with the combination of soil moisture content and thermal inertia at the same moisture content. Therefore, a remotely sensed estimate of the thermal behavior of the soil from diurnal soil temperature observations and an independent remotely sensed estimate of soil moisture content gives the possibility of estimating soil hydraulic properties by remote sensing.

Use of thermal inertia determined by HCMM to predict nocturnal cold prone areas in Florida

NASA Technical Reports Server (NTRS)

Allen, L. H., Jr. (Principal Investigator)

1983-01-01

Pairs of HCMM day-night thermal infrared (IR) data were selected during the 1978-79 winter to examine patterns of surface temperature and thermal inertia (TI) of peninsular Florida. The GOES and NOAA-6 thermal IR, as well as National Climatic Center temperatures and rainfall, were also used. The HCMM apparent thermal inertia (ATI) images closely corresponded to the general soil map of Florida, based on soil drainage classes. Areas with low ATI overlay well-drained soils, such as deep sands and drained organic soils, whereas with high ATI overlay areas with wetlands and bodies of water. The HCMM ATI images also corresponded well with GOES-detected winter nocturnal cold-prone areas. Use of HCMM data with Carlson's energy balance model showed both high moisture availability (MA) and high thermal inertia (TI) of wetland-type surfaces and low MA and low TI of upland, well-drained soils. Since soil areas with low TI develop higher temperatures during the day, then antecedent patterns of highest maximum daytime surface temperature can also be used to predict nocturnal cold-prone areas in Florida.

Modeling ground thermal regime of an ancient buried ice body in Beacon Valley, Antarctica using a 1-D heat equation with latent heat effect

NASA Astrophysics Data System (ADS)

Liu, L.; Sletten, R. S.; Hallet, B.; Waddington, E. D.; Wood, S. E.

2013-12-01

An ancient massive ice body buried under several decimeters of debris in Beacon Valley, Antarctica is believed to be over one million years old, making it older than any known glacier or ice cap. It is fundamentally important as a reservoir of water, proxy for climatic information, and an expression of the periglacial landscape. It is also one of Earth's closest analog for widespread, near-surface ice found in Martian soils and ice-cored landforms. We are interested in understanding controls on how long this ice may persist since our physical model of sublimation suggests it should not be stable. In these models, the soil temperatures and the gradient are important because it determines the direction and magnitude of the vapor flux, and thus sublimation rates. To better understand the heat transfer processes and constrain the rates of processes governing ground ice stability, a model of the thermal behavior of the permafrost is applied to Beacon Valley, Antarctica. It calculates soil temperatures based on a 1-D thermal diffusion equation using a fully implicit finite volume method (FVM). This model is constrained by soil physical properties and boundary conditions of in-situ ground surface temperature measurements (with an average of -23.6oC, a maximum of 20.5oC and a minimum of -54.3oC) and ice-core temperature record at ~30 m. Model results are compared to in-situ temperature measurements at depths of 0.10 m, 0.20 m, 0.30 m, and 0.45 m to assess the model's ability to reproduce the temperature profile for given thermal properties of the debris cover and ice. The model's sensitivity to the thermal diffusivity of the permafrost and the overlaying debris is also examined. Furthermore, we incorporate the role of ice condensation/sublimation which is calculated using our vapor diffusion model in the 1-D thermal diffusion model to assess potential latent heat effects that in turn affect ground ice sublimation rates. In general, the model simulates the ground thermal regime well. Detailed temperature comparison suggests that the 1-D thermal diffusion model results closely approximate the measured temperature at all depths with the average square root of the mean squared error (SRMSE) of 0.15oC; a linear correlation between modeled and measured temperatures yields an average R2 value of 0.9997. Prominent seasonal temperature variations diminish with depth, and it equilibrates to mean annual temperature at about 21.5 m depth. The amount of heat generated/consumed by ice condensation/sublimation is insufficient to significantly impact the thermal regime.

A Methodology for Surface Soil Moisture and Vegetation Optical Depth Retrieval Using the Microwave Polarization Difference Index

NASA Technical Reports Server (NTRS)

Owe, Manfred; deJeu, Richard; Walker, Jeffrey; Zukor, Dorothy J. (Technical Monitor)

2001-01-01

A methodology for retrieving surface soil moisture and vegetation optical depth from satellite microwave radiometer data is presented. The procedure is tested with historical 6.6 GHz brightness temperature observations from the Scanning Multichannel Microwave Radiometer over several test sites in Illinois. Results using only nighttime data are presented at this time, due to the greater stability of nighttime surface temperature estimation. The methodology uses a radiative transfer model to solve for surface soil moisture and vegetation optical depth simultaneously using a non-linear iterative optimization procedure. It assumes known constant values for the scattering albedo and roughness. Surface temperature is derived by a procedure using high frequency vertically polarized brightness temperatures. The methodology does not require any field observations of soil moisture or canopy biophysical properties for calibration purposes and is totally independent of wavelength. Results compare well with field observations of soil moisture and satellite-derived vegetation index data from optical sensors.

Temperature sensitivity of soil organic carbon decomposition increased with mean carbon residence time: Field incubation and data assimilation.

PubMed

Zhou, Xuhui; Xu, Xia; Zhou, Guiyao; Luo, Yiqi

2018-02-01

Temperature sensitivity of soil organic carbon (SOC) decomposition is one of the major uncertainties in predicting climate-carbon (C) cycle feedback. Results from previous studies are highly contradictory with old soil C decomposition being more, similarly, or less sensitive to temperature than decomposition of young fractions. The contradictory results are partly from difficulties in distinguishing old from young SOC and their changes over time in the experiments with or without isotopic techniques. In this study, we have conducted a long-term field incubation experiment with deep soil collars (0-70 cm in depth, 10 cm in diameter of PVC tubes) for excluding root C input to examine apparent temperature sensitivity of SOC decomposition under ambient and warming treatments from 2002 to 2008. The data from the experiment were infused into a multi-pool soil C model to estimate intrinsic temperature sensitivity of SOC decomposition and C residence times of three SOC fractions (i.e., active, slow, and passive) using a data assimilation (DA) technique. As active SOC with the short C residence time was progressively depleted in the deep soil collars under both ambient and warming treatments, the residences times of the whole SOC became longer over time. Concomitantly, the estimated apparent and intrinsic temperature sensitivity of SOC decomposition also became gradually higher over time as more than 50% of active SOC was depleted. Thus, the temperature sensitivity of soil C decomposition in deep soil collars was positively correlated with the mean C residence times. However, the regression slope of the temperature sensitivity against the residence time was lower under the warming treatment than under ambient temperature, indicating that other processes also regulated temperature sensitivity of SOC decomposition. These results indicate that old SOC decomposition is more sensitive to temperature than young components, making the old C more vulnerable to future warmer climate. © 2017 John Wiley & Sons Ltd.

Land cover heterogeneity and soil respiration in a west Greenland tundra landscape

NASA Astrophysics Data System (ADS)

Bradley-Cook, J. I.; Burzynski, A.; Hammond, C. R.; Virginia, R. A.

2011-12-01

Multiple direct and indirect pathways underlie the association between land cover classification, temperature and soil respiration. Temperature is a main control of the biological processes that constitute soil respiration, yet the effect of changing atmospheric temperatures on soil carbon flux is unresolved. This study examines associations amongst land cover, soil carbon characteristics, soil respiration, and temperature in an Arctic tundra landscape in western Greenland. We used a 1.34 meter resolution multi-spectral WorldView2 satellite image to conduct an unsupervised multi-staged ISODATA classification to characterize land cover heterogeneity. The four band image was taken on July 10th, 2010, and captures an 18 km by 15 km area in the vicinity of Kangerlussuaq. The four major terrestrial land cover classes identified were: shrub-dominated, graminoid-dominated, mixed vegetation, and bare soil. The bare soil class was comprised of patches where surface soil has been deflated by wind and ridge-top fellfield. We hypothesize that soil respiration and soil carbon storage are associated with land cover classification and temperature. We set up a hierarchical field sampling design to directly observe spatial variation between and within land cover classes along a 20 km temperature gradient extending west from Russell Glacier on the margin of the Greenland Ice Sheet. We used the land cover classification map and ground verification to select nine sites, each containing patches of the four land cover classes. Within each patch we collected soil samples from a 50 cm pit, quantified vegetation, measured active layer depth and determined landscape characteristics. From a subset of field sites we collected additional 10 cm surface soil samples to estimate soil heterogeneity within patches and measured soil respiration using a LiCor 8100 Infrared Gas Analyzer. Soil respiration rates varied with land cover classes, with values ranging from 0.2 mg C/m^2/hr in the bare soil class to over 5 mg C/m^2/hr in the graminoid-dominated class. These findings suggest that shifts in land cover vegetation types, especially soil and vegetation loss (e.g. from wind deflation), can alter landscape soil respiration. We relate soil respiration measurements to soil, vegetation, and permafrost characteristics to understand how ecosystem properties and processes vary at the landscape scale. A long-term goal of this research is to develop a spatially explicit model of soil organic matter, soil respiration, and temperature sensitivity of soil carbon dynamics for a western Greenland permafrost tundra ecosystems.

What are the most crucial soil factors for predicting the distribution of alpine plant species?

NASA Astrophysics Data System (ADS)

Buri, A.; Pinto-Figueroa, E.; Yashiro, E.; Guisan, A.

2017-12-01

Nowadays the use of species distribution models (SDM) is common to predict in space and time the distribution of organisms living in the critical zone. The realized environmental niche concept behind the development of SDM imply that many environmental factors must be accounted for simultaneously to predict species distributions. Climatic and topographic factors are often primary included, whereas soil factors are frequently neglected, mainly due to the paucity of soil information available spatially and temporally. Furthermore, among existing studies, most included soil pH only, or few other soil parameters. In this study we aimed at identifying what are the most crucial soil factors for explaining alpine plant distributions and, among those identified, which ones further improve the predictive power of plant SDMs. To test the relative importance of the soil factors, we performed plant SDMs using as predictors 52 measured soil properties of various types such as organic/inorganic compounds, chemical/physical properties, water related variables, mineral composition or grain size distribution. We added them separately to a standard set of topo-climatic predictors (temperature, slope, solar radiation and topographic position). We used ensemble forecasting techniques combining together several predictive algorithms to model the distribution of 116 plant species over 250 sites in the Swiss Alps. We recorded the variable importance for each model and compared the quality of the models including different soil proprieties (one at a time) as predictors to models having only topo-climatic variables as predictors. Results show that 46% of the soil proprieties tested become the second most important variable, after air temperature, to explain spatial distribution of alpine plants species. Moreover, we also assessed that addition of certain soil factors, such as bulk soil water density, could improve over 80% the quality of some plant species models. We confirm that soil pH remains one of the most important soil factor for predicting plant species distributions, closely followed by water, organic and inorganic carbon related properties. Finally, we were able to extract three main categories of important soil properties for plant species distributions: grain size distribution, acidity and water in the soil.

Validation of Soil Water Content Estimation Method on Agricultural Regions in South Korea

NASA Astrophysics Data System (ADS)

Shin, Y.; Kim, M.

2016-12-01

The continuous water stress caused by decrease of soil water has a direct influence to the crop growth in a upland crop area. The agricultural drought is occured if water requirement is not supplied timely in crop growh process. It is more important to understand the soil characteristics for high accuracy soil moisture estimation because of the soil water contents largely depends on soil properties. The RDA(Rural Development Administration) has provided real-time soil moisture observations corrected for 71 points in the South Korea. In this study, we developed a soil water content estimation method that considered soil hydraulic parameters for the observation points of soil water content in agricultural regions operated by the RDA. SWAP(Soil-Water-Atmosphere-Plant) model was used in the estimation of soil water contents. The soil hydraulic parameters that is the input data of the SWAP model were estimated using the ROSETTA model developed by the U.S. Department of Agriculture(USDA). Meteorological data observed from AWS(Automatic Weather Station) were used including daily maximum temperature(°), daily minimum temperature(°), relative humidity(%), solar radiation, wind speed and precipitation data. We choosed 56 stations there are no missing of meteorological data and have soil physical properties. For the verification of soil water content estimation method, we used Haenam KoFlux observation data that are observed long-term soil water contents over 2009-2015(2014 missing) years. In the case of 2015, there are good reproducibility between observation of soil water contents and results of SWAP model simulation with R2=0.72, RMSE=0.026 and TCC=0.849. In the case of precipitation event, the simulation results were slightly overestimated more than observation. However there are good reproducibility in the case of soil water reduction due to continuous non-precipitation periods. We have simulated the soil water contents of the 56 stations that being operated in the RDA from 4 January 2015 to 31 October 2015 using the SWAP model. The environmental setting of SWAP modle according to the station applied it equally. The results showed a significant difference to the reproducibility according to the observation station.

Separating vegetation and soil temperature using airborne multiangular remote sensing image data

NASA Astrophysics Data System (ADS)

Liu, Qiang; Yan, Chunyan; Xiao, Qing; Yan, Guangjian; Fang, Li

2012-07-01

Land surface temperature (LST) is a key parameter in land process research. Many research efforts have been devoted to increase the accuracy of LST retrieval from remote sensing. However, because natural land surface is non-isothermal, component temperature is also required in applications such as evapo-transpiration (ET) modeling. This paper proposes a new algorithm to separately retrieve vegetation temperature and soil background temperature from multiangular thermal infrared (TIR) remote sensing data. The algorithm is based on the localized correlation between the visible/near-infrared (VNIR) bands and the TIR band. This method was tested on the airborne image data acquired during the Watershed Allied Telemetry Experimental Research (WATER) campaign. Preliminary validation indicates that the remote sensing-retrieved results can reflect the spatial and temporal trend of component temperatures. The accuracy is within three degrees while the difference between vegetation and soil temperature can be as large as twenty degrees.

Disentangling residence time and temperature sensitivity of microbial decomposition in a global soil carbon model

NASA Astrophysics Data System (ADS)

Exbrayat, J.-F.; Pitman, A. J.; Abramowitz, G.

2014-03-01

Recent studies have identified the first-order parameterization of microbial decomposition as a major source of uncertainty in simulations and projections of the terrestrial carbon balance. Here, we use a reduced complexity model representative of the current state-of-the-art parameterization of soil organic carbon decomposition. We undertake a systematic sensitivity analysis to disentangle the effect of the time-invariant baseline residence time (k) and the sensitvity of microbial decomposition to temperature (Q10) on soil carbon dynamics at regional and global scales. Our simulations produce a range in total soil carbon at equilibrium of ~ 592 to 2745 Pg C which is similar to the ~ 561 to 2938 Pg C range in pre-industrial soil carbon in models used in the fifth phase of the Coupled Model Intercomparison Project. This range depends primarily on the value of k, although the impact of Q10 is not trivial at regional scales. As climate changes through the historical period, and into the future, k is primarily responsible for the magnitude of the response in soil carbon, whereas Q10 determines whether the soil remains a sink, or becomes a source in the future mostly by its effect on mid-latitudes carbon balance. If we restrict our simulations to those simulating total soil carbon stocks consistent with observations of current stocks, the projected range in total soil carbon change is reduced by 42% for the historical simulations and 45% for the future projections. However, while this observation-based selection dismisses outliers it does not increase confidence in the future sign of the soil carbon feedback. We conclude that despite this result, future estimates of soil carbon, and how soil carbon responds to climate change should be constrained by available observational data sets.

A semiempirical model for interpreting microwave emission from semiarid land surfaces as seen from space

NASA Technical Reports Server (NTRS)

Kerr, Yann H.; Njoku, Eni G.

1990-01-01

A radiative-transfer model for simulating microwave brightness temperatures over land surfaces is described. The model takes into account sensor viewing conditions (spacecraft altitude, viewing angle, frequency, and polarization) and atmospheric parameters over a soil surface characterized by its moisture, roughness, and temperature and covered with a layer of vegetation characterized by its temperature, water content, single scattering albedo, structure, and percent coverage. In order to reduce the influence of atmospheric and surface temperature effects, the brightness temperatures are expressed as polarization ratios that depend primarily on the soil moisture and roughness, canopy water content, and percentage of cover. The sensitivity of the polarization ratio to these parameters is investigated. Simulation of the temporal evolution of the microwave signal over semiarid areas in the African Sahel is presented and compared to actual satellite data from the SMMR instrument on Nimbus-7.

Towards Improved High-Resolution Land Surface Hydrologic Reanalysis Using a Physically-Based Hydrologic Model and Data Assimilation

NASA Astrophysics Data System (ADS)

Shi, Y.; Davis, K. J.; Zhang, F.; Duffy, C.; Yu, X.

2014-12-01

A coupled physically based land surface hydrologic model, Flux-PIHM, has been developed by incorporating a land surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Flux-PIHM has been implemented and manually calibrated at the Shale Hills watershed (0.08 km2) in central Pennsylvania. Model predictions of discharge, point soil moisture, point water table depth, sensible and latent heat fluxes, and soil temperature show good agreement with observations. When calibrated only using discharge, and soil moisture and water table depth at one point, Flux-PIHM is able to resolve the observed 101 m scale soil moisture pattern at the Shale Hills watershed when an appropriate map of soil hydraulic properties is provided. A Flux-PIHM data assimilation system has been developed by incorporating EnKF for model parameter and state estimation. Both synthetic and real data assimilation experiments have been performed at the Shale Hills watershed. Synthetic experiment results show that the data assimilation system is able to simultaneously provide accurate estimates of multiple parameters. In the real data experiment, the EnKF estimated parameters and manually calibrated parameters yield similar model performances, but the EnKF method significantly decreases the time and labor required for calibration. The data requirements for accurate Flux-PIHM parameter estimation via data assimilation using synthetic observations have been tested. Results show that by assimilating only in situ outlet discharge, soil water content at one point, and the land surface temperature averaged over the whole watershed, the data assimilation system can provide an accurate representation of watershed hydrology. Observations of these key variables are available with national and even global spatial coverage (e.g., MODIS surface temperature, SMAP soil moisture, and the USGS gauging stations). National atmospheric reanalysis products, soil databases and land cover databases (e.g., NLDAS-2, SSURGO, NLCD) can provide high resolution forcing and input data. Therefore the Flux-PIHM data assimilation system could be readily expanded to other watersheds to provide regional scale land surface and hydrologic reanalysis with high spatial temporal resolution.

Climate change and soil salinity: The case of coastal Bangladesh.

PubMed

Dasgupta, Susmita; Hossain, Md Moqbul; Huq, Mainul; Wheeler, David

2015-12-01

This paper estimates location-specific soil salinity in coastal Bangladesh for 2050. The analysis was conducted in two stages: First, changes in soil salinity for the period 2001-2009 were assessed using information recorded at 41 soil monitoring stations by the Soil Research Development Institute. Using these data, a spatial econometric model was estimated linking soil salinity with the salinity of nearby rivers, land elevation, temperature, and rainfall. Second, future soil salinity for 69 coastal sub-districts was projected from climate-induced changes in river salinity and projections of rainfall and temperature based on time trends for 20 Bangladesh Meteorological Department weather stations in the coastal region. The findings indicate that climate change poses a major soil salinization risk in coastal Bangladesh. Across 41 monitoring stations, the annual median projected change in soil salinity is 39 % by 2050. Above the median, 25 % of all stations have projected changes of 51 % or higher.

Simple agrometeorological models for estimating Guineagrass yield in Southeast Brazil.

PubMed

Pezzopane, José Ricardo Macedo; da Cruz, Pedro Gomes; Santos, Patricia Menezes; Bosi, Cristiam; de Araujo, Leandro Coelho

2014-09-01

The objective of this work was to develop and evaluate agrometeorological models to simulate the production of Guineagrass. For this purpose, we used forage yield from 54 growing periods between December 2004-January 2007 and April 2010-March 2012 in irrigated and non-irrigated pastures in São Carlos, São Paulo state, Brazil (latitude 21°57'42″ S, longitude 47°50'28″ W and altitude 860 m). Initially we performed linear regressions between the agrometeorological variables and the average dry matter accumulation rate for irrigated conditions. Then we determined the effect of soil water availability on the relative forage yield considering irrigated and non-irrigated pastures, by means of segmented linear regression among water balance and relative production variables (dry matter accumulation rates with and without irrigation). The models generated were evaluated with independent data related to 21 growing periods without irrigation in the same location, from eight growing periods in 2000 and 13 growing periods between December 2004-January 2007 and April 2010-March 2012. The results obtained show the satisfactory predictive capacity of the agrometeorological models under irrigated conditions based on univariate regression (mean temperature, minimum temperature and potential evapotranspiration or degreedays) or multivariate regression. The response of irrigation on production was well correlated with the climatological water balance variables (ratio between actual and potential evapotranspiration or between actual and maximum soil water storage). The models that performed best for estimating Guineagrass yield without irrigation were based on minimum temperature corrected by relative soil water storage, determined by the ratio between the actual soil water storage and the soil water holding capacity.irrigation in the same location, in 2000, 2010 and 2011. The results obtained show the satisfactory predictive capacity of the agrometeorological models under irrigated conditions based on univariate regression (mean temperature, potential evapotranspiration or degree-days) or multivariate regression. The response of irrigation on production was well correlated with the climatological water balance variables (ratio between actual and potential evapotranspiration or between actual and maximum soil water storage). The models that performed best for estimating Guineagrass yield without irrigation were based on degree-days corrected by the water deficit factor.

Physical robustness of canopy temperature models for crop heat stress simulation across environments and production conditions

USDA-ARS?s Scientific Manuscript database

Despite widespread application in studying climate change impacts, most crop models ignore complex interactions among air temperature, crop and soil water status, CO2 concentration and atmospheric conditions that influence crop canopy temperature. The current study extended previous studies by evalu...

Prediction of soil frost penetration depth in northwest of Iran using air freezing indices

NASA Astrophysics Data System (ADS)

Mohammadi, H.; Moghbel, M.; Ranjbar, F.

2016-11-01

Information about soil frost penetration depth can be effective in finding appropriate solutions to reduce the agricultural crop damage, transportations, and building facilities. Amongst proper methods to achieve this information are the statistical and empirical models capable of estimating soil frost penetration depth. Therefore, the main objective of this research is to calculate soil frost penetration depth in northwest of Iran during the year 2007-2008 to validate two different models accuracy. To do so, the relationship between air and soil temperature in different depths (5-10-20-30-50-100 cm) at three times of the day (3, 9, and 15 GMT) for 14 weather stations over 7 provinces was analyzed using linear regression. Then, two different air freezing indices (AFIs) including Norwegian and Finn AFI was implemented. Finally, the frost penetration depth was calculated by McKeown method and the accuracy of models determined by actual soil frost penetration depth. The results demonstrated that there is a significant correlation between air and soil depth temperature in all studied stations up to the 30 cm under the surface. Also, according to the results, Norwegian index can be effectively used for determination of soil frost depth penetration and the correlation coefficient between actual and estimated soil frost penetration depth is r = 0.92 while the Finn index overestimates the frost depth in all stations with correlation coefficient r = 0.70.

Temperature adaptation of bacterial communities in experimentally warmed forest soils.

PubMed

Rousk, Johannes; Frey, Serita D; Bååth, Erland

2012-10-01

A detailed understanding of the influence of temperature on soil microbial activity is critical to predict future atmospheric CO 2 concentrations and feedbacks to anthropogenic warming. We investigated soils exposed to 3-4 years of continuous 5 °C-warming in a field experiment in a temperate forest. We found that an index for the temperature adaptation of the microbial community, T min for bacterial growth, increased by 0.19 °C per 1 °C rise in temperature, showing a community shift towards one adapted to higher temperature with a higher temperature sensitivity (Q 10(5-15 °C) increased by 0.08 units per 1 °C). Using continuously measured temperature data from the field experiment we modelled in situ bacterial growth. Assuming that warming did not affect resource availability, bacterial growth was modelled to become 60% higher in warmed compared to the control plots, with the effect of temperature adaptation of the community only having a small effect on overall bacterial growth (<5%). However, 3 years of warming decreased bacterial growth, most likely due to substrate depletion because of the initially higher growth in warmed plots. When this was factored in, the result was similar rates of modelled in situ bacterial growth in warmed and control plots after 3 years, despite the temperature difference. We conclude that although temperature adaptation for bacterial growth to higher temperatures was detectable, its influence on annual bacterial growth was minor, and overshadowed by the direct temperature effect on growth rates. © 2012 Blackwell Publishing Ltd.

Experimental and ecosystem model approach to assessing the sensitivity of High arctic deep permafrost to changes in surface temperature and precipitation

NASA Astrophysics Data System (ADS)

Rasmussen, L. H.; Zhang, W.; Elberling, B.; Cable, S.

2016-12-01

Permafrost affected areas in Greenland are expected to experience large temperature increases within the 21st century. Most previous studies on permafrost consider near-surface soil, where changes will happen first. However, how sensitive the deep permafrost temperature is to near-surface conditions through changes in soil thermal properties, snow depth and soil moisture, is not known. In this study, we measured the sensitivity of thermal conductivity (TC) to gravimetric water content (GWC) in frozen and thawed deep permafrost sediments from deltaic, alluvial and fluvial depositional environments in the Zackenberg valley, NE Greenland. We also calibrated a coupled heat and water transfer model, the "CoupModel", for the two closely situated deltaic sites, one with average snow depth and the other with topographic snow accumulation. With the calibrated model, we simulated deep permafrost thermal dynamics in four scenarios with changes in surface forcing: a. 3 °C warming and 20 % increase in precipitation; b. 3 °C warming and 100 % increase in precipitation; c. 6 °C warming and 20 % increase in precipitation; d. 6 °C warming and 100 % increase in precipitation.Our results indicated that frozen sediments had higher TC than thawed sediments. All sediments showed a positive linear relation between TC and soil moisture when frozen, and a logarithmic one when thawed. Fluvial sediments had high sensitivity, but never reached above 12 % GWC, indicating a field effect of water retention capacity. Alluvial sediments were less sensitive to soil moisture than deltaic and fluvial sediments, indicating the importance of unfrozen water in frozen sediment. The deltaic site with snow accumulation had 1 °C higher annual mean ground temperature than the average snow site. The soil temperature at the depth of 18 m increased with 1.5 °C and 3.5 °C in the scenarios with 3 °C and 6 °C warming, respectively. Precipitation had no significant additional effect to warming. We conclude that below-ground sediment properties affect the sensitivity of TC to GWC, that surface temperature changes can significantly affect the deep permafrost within a short period, and that differences in snow depth affect surface temperatures. Geology, pedology and precipitation should thus be considered if estimating future High arctic deep permafrost sensitivity.

Relative skills of soil moisture and vegetation optical depth retrievals for agricultural drought monitoring

USDA-ARS?s Scientific Manuscript database

Soil moisture condition is an important indicator for agricultural drought monitoring. Through the Land Parameter Retrieval Model (LPRM), vegetation optical depth (VOD) as well as surface soil moisture (SM) can be retrieved simultaneously from brightness temperature observations from the Advanced Mi...

Projecting changes in Everglades soil biogeochemistry for carbon and other key elements, to possible 2060 climate and hydrologic scenarios.

PubMed

Orem, William; Newman, Susan; Osborne, Todd Z; Reddy, K Ramesh

2015-04-01

Based on previously published studies of elemental cycling in Everglades soils, we projected how soil biogeochemistry, specifically carbon, nitrogen, phosphorus, sulfur, and mercury might respond to climate change scenarios projected for 2060 by the South Florida Water Management Model. Water budgets and stage hydrographs from this model with future scenarios of a 10% increased or decreased rainfall, a 1.5 °C rise in temperature and associated increase in evapotranspiration (ET) and a 0.5 m rise in sea level were used to predict resulting effects on soil biogeochemistry. Precipitation is a much stronger driver of soil biogeochemical processes than temperature, because of links among water cover, redox conditions, and organic carbon accumulation in soils. Under the 10% reduced rainfall scenario, large portions of the Everglades will experience dry down, organic soil oxidation, and shifts in soil redox that may dramatically alter biogeochemical processes. Lowering organic soil surface elevation may make portions of the Everglades more vulnerable to sea level rise. The 10% increased rainfall scenario, while potentially increasing phosphorus, sulfur, and mercury loading to the ecosystem, would maintain organic soil integrity and redox conditions conducive to normal wetland biogeochemical element cycling. Effects of increased ET will be similar to those of decreased precipitation. Temperature increases would have the effect of increasing microbial processes driving biogeochemical element cycling, but the effect would be much less than that of precipitation. The combined effects of decreased rainfall and increased ET suggest catastrophic losses in carbon- and organic-associated elements throughout the peat-based Everglades.

Soil respiration and carbon loss relationship with temperature and land use conversion in freeze-thaw agricultural area.

PubMed

Ouyang, Wei; Lai, Xuehui; Li, Xia; Liu, Heying; Lin, Chunye; Hao, Fanghua

2015-11-15

Soil respiration (Rs) was hypothesized to have a special response pattern to soil temperature and land use conversion in the freeze-thaw area. The Rs differences of eight types of land use conversions during agricultural development were observed and the impacts of Rs on soil organic carbon (SOC) loss were assessed. The land use conversions during last three decades were categorized into eight types, and the 141 SOC sampling sites were grouped by conversion type. The typical soil sampling sites were subsequently selected for monitoring of soil temperature and Rs of each land use conversion types. The Rs correlations with temperature at difference depths and different conversion types were identified with statistical analysis. The empirical mean error model and the biophysical theoretical model with Arrhenius equation about the Rs sensitivity to temperature were both analyzed and shared the similar patterns. The temperature dependence of soil respiration (Q10) analysis further demonstrated that the averaged value of eight types of land use in this freeze-thaw agricultural area ranged from 1.15 to 1.73, which was lower than the other cold areas. The temperature dependence analysis demonstrated that the Rs in the top layer of natural land covers was more sensitive to temperature and experienced a large vertical difference. The natural land covers exhibited smaller Rs and the farmlands had the bigger value due to tillage practices. The positive relationships between SOC loss and Rs were identified, which demonstrated that Rs was the key chain for SOC loss during land use conversion. The spatial-vertical distributions of SOC concentration with the 1.5-km grid sampling showed that the more SOC loss in the farmland, which was coincided with the higher Rs in farmlands. The analysis of Rs dynamics provided an innovative explanation for SOC loss in the freeze-thaw agricultural area. The analysis of Rs dynamics provided an innovative explanation for SOC loss in the freeze-thaw agricultural area. Copyright © 2015 Elsevier B.V. All rights reserved.

The effect to the water stress to soil CO2 efflux in the Siberian boreal forest

NASA Astrophysics Data System (ADS)

Makhnykina, A. V.; Prokishkin, A. S.; Verkhovets, S. V.; Koshurnikova, N. N.

2017-12-01

The boreal forests in Siberia covered more than 70% area of this region. Due to the climate change this ecosystems represent a very sensitive and significant source of carbon. In forests, total ecosystem respiration tends to be dominated by soil respiration, which accounts for approximately 69% of this large flux (Janssens et al., 2001). Dynamic global vegetation models predict that soil respiration will increase more than total net primary productivity in response to warmer temperatures and increase in precipitation, the terrestrial carbon sink is expected to decline significantly (Bonan et al., 2003). The aim of the present study was to identify the response of the soil CO2 efflux to the different amount of water input for two highly differentiated years by the precipitation conditions in the middle taiga forests in Central Siberia. The study was conducted in the pine forests in Central Siberia (60°N, 90°E), Russia. We used the automated soil CO2 flux system LI-8100 for measuring the soil efflux. Soil temperature was measured with Soil Temperature Probe Type E in three depths 5, 10, 15 cm. Volumetric soil moisture was measured with Theta Probe Model ML2. We constructed the field experiment based on the addition of different amount of water (0%, 25%, 50% and 100% sites) after each rain event during the growing season. We found that the amount of precipitation have a huge impact to the value of soil CO2 efflux. For the more precipitated year (2015) the fluxes were almost twice higher compared to less precipitated year (2016). The max fluxes during the season in 2015 observed at the site without any water input there and the min one - for the 100% precipitation site (natural rain conditions). In 2016 we identified the opposite response: the max soil efflux demonstrated the site with 100% precipitation conditions (Fig. 1). We also detected the high dependence between the soil temperature and soil CO2 efflux for the site with 0% additional water input in more precipitated year (with excluding the precipitation factor). These findings confirmed that the increase of precipitation in the boreal forests will enhance soil CO2 efflux.

Predicting Ascospore Release of Monilinia vaccinii-corymbosi of Blueberry with Machine Learning.

PubMed

Harteveld, Dalphy O C; Grant, Michael R; Pscheidt, Jay W; Peever, Tobin L

2017-11-01

Mummy berry, caused by Monilinia vaccinii-corymbosi, causes economic losses of highbush blueberry in the U.S. Pacific Northwest (PNW). Apothecia develop from mummified berries overwintering on soil surfaces and produce ascospores that infect tissue emerging from floral and vegetative buds. Disease control currently relies on fungicides applied on a calendar basis rather than inoculum availability. To establish a prediction model for ascospore release, apothecial development was tracked in three fields, one in western Oregon and two in northwestern Washington in 2015 and 2016. Air and soil temperature, precipitation, soil moisture, leaf wetness, relative humidity and solar radiation were monitored using in-field weather stations and Washington State University's AgWeatherNet stations. Four modeling approaches were compared: logistic regression, multivariate adaptive regression splines, artificial neural networks, and random forest. A supervised learning approach was used to train the models on two data sets: training (70%) and testing (30%). The importance of environmental factors was calculated for each model separately. Soil temperature, soil moisture, and solar radiation were identified as the most important factors influencing ascospore release. Random forest models, with 78% accuracy, showed the best performance compared with the other models. Results of this research helps PNW blueberry growers to optimize fungicide use and reduce production costs.

Interactions Between Mineral Surfaces, Substrates, Enzymes, and Microbes Result in Hysteretic Temperature Sensitivities and Microbial Carbon Use Efficiencies and Weaker Predicted Carbon-Climate Feedbacks

NASA Astrophysics Data System (ADS)

Riley, W. J.; Tang, J.

2014-12-01

We hypothesize that the large observed variability in decomposition temperature sensitivity and carbon use efficiency arises from interactions between temperature, microbial biogeochemistry, and mineral surface sorptive reactions. To test this hypothesis, we developed a numerical model that integrates the Dynamic Energy Budget concept for microbial physiology, microbial trait-based community structure and competition, process-specific thermodynamically ­­based temperature sensitivity, a non-linear mineral sorption isotherm, and enzyme dynamics. We show, because mineral surfaces interact with substrates, enzymes, and microbes, both temperature sensitivity and microbial carbon use efficiency are hysteretic and highly variable. Further, by mimicking the traditional approach to interpreting soil incubation observations, we demonstrate that the conventional labile and recalcitrant substrate characterization for temperature sensitivity is flawed. In a 4 K temperature perturbation experiment, our fully dynamic model predicted more variable but weaker carbon-climate feedbacks than did the static temperature sensitivity and carbon use efficiency model when forced with yearly, daily, and hourly variable temperatures. These results imply that current earth system models likely over-estimate the response of soil carbon stocks to global warming.

The Impact of Wet Soil and Canopy Temperatures on Daytime Boundary-Layer Growth.

NASA Astrophysics Data System (ADS)

Segal, M.; Garratt, J. R.; Kallos, G.; Pielke, R. A.

1989-12-01

The impact of very wet soil and canopy temperatures on the surface sensible heat flux, and on related daytime boundary-layer properties is evaluated. For very wet soils, two winter situations are considered, related to significant changes in soil surface temperature: (1) due to weather perturbations at a given location, and (2) due to the climatological north-south temperature gradient. Analyses and scaling of the various boundary-layer properties, and soil surface fluxes affecting the sensible beat flux, have been made; related evaluations show that changes in the sensible heat flux at a given location by a factor of 2 to 3 due to temperature changes related to weather perturbations is not uncommon. These changes result in significant alterations in the boundary-layer depth; in the atmospheric boundary-layer warming; and in the break-up time of the nocturnal surface temperature inversion. Investigation of the impact of the winter latitudinal temperature gradient on the above characteristics indicated that the relative increase in very wet soil sensible heat flux, due to the climatological reduction in the surface temperature in northern latitudes, moderates to some extent its reduction due to the corresponding decrease in solar radiation. Numerical model simulations confirmed these analytical evaluations.In addition, the impact of synoptic temperature perturbations during the transition seasons (fall and spring) on canopy sensible heal fluxes, and the related boundary-layer characteristics mentioned above, was evaluated. Analogous features to those found for very wet soil surfaces occurred also for the canopy situations. Likewise, evaluations were also carried out to explore the impact of high midlatitude foreste areas on the boundary-layer characteristics during the winter as compared to those during the summer. Similar impacts were found in both seasons, regardless of the substantial difference in the daily total solar radiation.

Dependence of soil respiration on soil temperature and soil moisture in successional forests in Southern China

USGS Publications Warehouse

Tang, X.-L.; Zhou, G.-Y.; Liu, S.-G.; Zhang, D.-Q.; Liu, S.-Z.; Li, Ji; Zhou, C.-Y.

2006-01-01

The spatial and temporal variations in soil respiration and its relationship with biophysical factors in forests near the Tropic of Cancer remain highly uncertain. To contribute towards an improvement of actual estimates, soil respiration rates, soil temperature, and soil moisture were measured in three successional subtropical forests at the Dinghushan Nature Reserve (DNR) in southern China from March 2003 to February 2005. The overall objective of the present study was to analyze the temporal variations of soil respiration and its biophysical dependence in these forests. The relationships between biophysical factors and soil respiration rates were compared in successional forests to test the hypothesis that these forests responded similarly to biophysical factors. The seasonality of soil respiration coincided with the seasonal climate pattern, with high respiration rates in the hot humid season (April-September) and with low rates in the cool dry season (October-March). Soil respiration measured at these forests showed a clear increasing trend with the progressive succession. Annual mean (±SD) soil respiration rate in the DNR forests was (9.0 ± 4.6) Mg CO2-C/hm2per year, ranging from (6.1 ± 3.2) Mg CO2-C/hm2per year in early successional forests to (10.7 ± 4.9) Mg CO2-C/hm2 per year in advanced successional forests. Soil respiration was correlated with both soil temperature and moisture. The T/M model, where the two biophysical variables are driving factors, accounted for 74%-82% of soil respiration variation in DNR forests. Temperature sensitivity decreased along progressive succession stages, suggesting that advanced-successional forests have a good ability to adjust to temperature. In contrast, moisture increased with progressive succession processes. This increase is caused, in part, by abundant respirators in advanced-successional forest, where more soil moisture is needed to maintain their activities.

Initializing numerical weather prediction models with satellite-derived surface soil moisture: Data assimilation experiments with ECMWF's Integrated Forecast System and the TMI soil moisture data set

NASA Astrophysics Data System (ADS)

Drusch, M.

2007-02-01

Satellite-derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analyzed from the modeled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. For this study, three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) have been performed for the 2-month period of June and July 2002: a control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating TMI (TRMM Microwave Imager) derived soil moisture over the southern United States. In this experimental run the satellite-derived soil moisture product is introduced through a nudging scheme using 6-hourly increments. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analyzed in the nudging experiment is the most accurate estimate when compared against in situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage.

A radiative transfer model for microwave emissions from bare agricultural soils

NASA Technical Reports Server (NTRS)

Burke, W. J.; Paris, J. F.

1975-01-01

A radiative transfer model for microwave emissions from bare, stratified agricultural soils was developed to assist in the analysis of data gathered in the joint soil moisture experiment. The predictions of the model were compared with preliminary X band (2.8 cm) microwave and ground based observations. Measured brightness temperatures at vertical and horizontal polarizations can be used to estimate the moisture content of the top centimeter of soil with + or - 1 percent accuracy. It is also shown that the Stokes parameters can be used to distinguish between moisture and surface roughness effects.

A comparison of radiative transfer models for predicting the microwave emission from soils

NASA Technical Reports Server (NTRS)

Schmugge, T. J.; Choudhury, B. J.

1981-01-01

Noncoherent and coherent numerical models for predicting emission from soils are compared. Coherent models use the boundary conditions on the electric fields across the layer boundaries to calculate the radiation intensity, and noncoherent models consider radiation intensities directly. Interference may cause different results in the two approaches when coupling between soil layers in coherent models causes greater soil moisture sampling depths. Calculations performed at frequencies of 1.4 and 19.4 GHz show little difference between the models at 19.4 GHz, although differences are apparent at the lower frequency. A definition for an effective emissivity is also given for when a nonuniform temperature profile is present, and measurements made from a tower show good agreement with calculations from the coherent model.

Documentation of a deep percolation model for estimating ground-water recharge

USGS Publications Warehouse

Bauer, H.H.; Vaccaro, J.J.

1987-01-01

A deep percolation model, which operates on a daily basis, was developed to estimate long-term average groundwater recharge from precipitation. It has been designed primarily to simulate recharge in large areas with variable weather, soils, and land uses, but it can also be used at any scale. The physical and mathematical concepts of the deep percolation model, its subroutines and data requirements, and input data sequence and formats are documented. The physical processes simulated are soil moisture accumulation, evaporation from bare soil, plant transpiration, surface water runoff, snow accumulation and melt, and accumulation and evaporation of intercepted precipitation. The minimum data sets for the operation of the model are daily values of precipitation and maximum and minimum air temperature, soil thickness and available water capacity, soil texture, and land use. Long-term average annual precipitation, actual daily stream discharge, monthly estimates of base flow, Soil Conservation Service surface runoff curve numbers, land surface altitude-slope-aspect, and temperature lapse rates are optional. The program is written in the FORTRAN 77 language with no enhancements and should run on most computer systems without modifications. Documentation has been prepared so that program modifications may be made for inclusions of additional physical processes or deletion of ones not considered important. (Author 's abstract)

Evaluation of near-surface temperature, humidity, and equivalent temperature from regional climate models applied in type II downscaling

NASA Astrophysics Data System (ADS)

Pryor, S. C.; Schoof, J. T.

2016-04-01

Atmosphere-surface interactions are important components of local and regional climates due to their key roles in dictating the surface energy balance and partitioning of energy transfer between sensible and latent heat. The degree to which regional climate models (RCMs) represent these processes with veracity is incompletely characterized, as is their ability to capture the drivers of, and magnitude of, equivalent temperature (Te). This leads to uncertainty in the simulation of near-surface temperature and humidity regimes and the extreme heat events of relevance to human health, in both the contemporary and possible future climate states. Reanalysis-nested RCM simulations are evaluated to determine the degree to which they represent the probability distributions of temperature (T), dew point temperature (Td), specific humidity (q) and Te over the central U.S., the conditional probabilities of Td|T, and the coupling of T, q, and Te to soil moisture and meridional moisture advection within the boundary layer (adv(Te)). Output from all RCMs exhibits discrepancies relative to observationally derived time series of near-surface T, q, Td, and Te, and use of a single layer for soil moisture by one of the RCMs does not appear to substantially degrade the simulations of near-surface T and q relative to RCMs that employ a four-layer soil model. Output from MM5I exhibits highest fidelity for the majority of skill metrics applied herein, and importantly most realistically simulates both the coupling of T and Td, and the expected relationships of boundary layer adv(Te) and soil moisture with near-surface T and q.

Modeling physical and biogeochemical controls over carbon accumulation in a boreal forest soil

USGS Publications Warehouse

Carrasco, J.J.; Neff, J.C.; Harden, J.W.

2006-01-01

Boreal soils are important to the global C cycle owing to large C stocks, repeated disturbance from fire, and the potential for permafrost thaw to expose previously stable, buried C. To evaluate the primary mechanisms responsible for both short- and long-term C accumulation in boreal soils, we developed a multi-isotope (12,14C) Soil C model with dynamic soil layers that develop through time as soil organic matter burns and reaccumulates. We then evaluated the mechanisms that control organic matter turnover in boreal regions including carbon input rates, substrate recalcitrance, soil moisture and temperature, and the presence of historical permafrost to assess the importance of these factors in boreal C accumulation. Results indicate that total C accumulation is controlled by the rate of carbon input, decomposition rates, and the presence of historical permafrost. However, unlike more temperate ecosystems, one of the key mechanisms involved in C preservation in boreal soils examined here is the cooling of subsurface soil layers as soil depth increases rather than increasing recalcitrance in subsurface soils. The propagation of the 14C bomb spike into soils also illustrates the importance of historical permafrost and twentieth century warming in contemporary boreal soil respiration fluxes. Both 14C and total C simulation data also strongly suggest that boreal SOM need not be recalcitrant to accumulate; the strong role of soil temperature controls on boreal C accumulation at our modeling test site in Manitoba, Canada, indicates that carbon in the deep organic soil horizons is probably relatively labile and thus subject to perturbations that result from changing climatic conditions in the future. Copyright 2006 by the American Geophysical Union.

Climate, soil organic layer, and nitrogen jointly drive forest development after fire in the North American boreal zone

NASA Astrophysics Data System (ADS)

Trugman, A. T.; Fenton, N. J.; Bergeron, Y.; Xu, X.; Welp, L. R.; Medvigy, D.

2016-09-01

Previous empirical work has shown that feedbacks between fire severity, soil organic layer thickness, tree recruitment, and forest growth are important factors controlling carbon accumulation after fire disturbance. However, current boreal forest models inadequately simulate this feedback. We address this deficiency by updating the ED2 model to include a dynamic feedback between soil organic layer thickness, tree recruitment, and forest growth. The model is validated against observations spanning monthly to centennial time scales and ranging from Alaska to Quebec. We then quantify differences in forest development after fire disturbance resulting from changes in soil organic layer accumulation, temperature, nitrogen availability, and atmospheric CO2. First, we find that ED2 accurately reproduces observations when a dynamic soil organic layer is included. Second, simulations indicate that the presence of a thick soil organic layer after a mild fire disturbance decreases decomposition and productivity. The combination of the biological and physical effects increases or decreases total ecosystem carbon depending on local conditions. Third, with a 4°C temperature increase, some forests transition from undergoing succession to needleleaf forests to recruiting multiple cohorts of broadleaf trees, decreasing total ecosystem carbon by ˜40% after 300 years. However, the presence of a thick soil organic layer due to a persistently mild fire regime can prevent this transition and mediate carbon losses even under warmer temperatures. Fourth, nitrogen availability regulates successional dynamics; broadleaf species are less competitive with needleleaf trees under low nitrogen regimes. Fifth, the boreal forest shows additional short-term capacity for carbon sequestration as atmospheric CO2 increases.

Shallow snowpack inhibits soil respiration in sagebrush steppe through multiple biotic and abiotic mechanisms

DOE PAGES

Tucker, Colin L.; Tamang, Shanker; Pendall, Elise; ...

2016-05-01

In sagebrush steppe, snowpack may govern soil respiration through its effect on multiple abiotic and biotic factors. Across the Intermountain West of the United States, snowpack has been declining for decades and is projected to decline further over the next century, making the response of soil respiration to snowpack a potentially important factor in the ecosystem carbon cycle. In this study, we evaluated the direct and indirect roles of the snowpack in driving soil respiration in sagebrush steppe ecosystems by taking advantage of highway snowfences in Wyoming to manipulate snowpack. An important contribution of this study is the use ofmore » Bayesian modeling to quantify the effects of soil moisture and temperature on soil respiration across a wide range of conditions from frozen to hot and dry, while simultaneously accounting for biotic factors (e.g., vegetation cover, root density, and microbial biomass and substrate-use diversity) affected by snowpack. Elevated snow depth increased soil temperature (in the winter) and moisture (winter and spring), and was associated with reduced vegetation cover and microbial biomass carbon. Soil respiration showed an exponential increase with temperature, with a temperature sensitivity that decreased with increasing seasonal temperature (Q 10 = 4.3 [winter], 2.3 [spring], and 1.7 [summer]); frozen soils were associated with unrealistic Q 10 approximate to 7989 due to the liquid-to-ice transition of soil water. Soil respiration was sensitive to soil water content; predicted respiration under very dry conditions was less than 10% of respiration under moist conditions. While higher vegetation cover increased soil respiration, this was not due to increased root density, and may reflect differences in litter inputs. Microbial substrate-use diversity was negatively related to reference respiration (i.e., respiration rate at a reference temperature and optimal soil moisture), although the mechanism remains unclear. Lastly, this study indicates that soil respiration is inhibited by shallow snowpack through multiple mechanisms; thus, future decreases in snowpack across the sagebrush steppe have the potential to reduce losses of soil C, potentially affecting regional carbon balance.« less

Shallow snowpack inhibits soil respiration in sagebrush steppe through multiple biotic and abiotic mechanisms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tucker, Colin L.; Tamang, Shanker; Pendall, Elise

In sagebrush steppe, snowpack may govern soil respiration through its effect on multiple abiotic and biotic factors. Across the Intermountain West of the United States, snowpack has been declining for decades and is projected to decline further over the next century, making the response of soil respiration to snowpack a potentially important factor in the ecosystem carbon cycle. In this study, we evaluated the direct and indirect roles of the snowpack in driving soil respiration in sagebrush steppe ecosystems by taking advantage of highway snowfences in Wyoming to manipulate snowpack. An important contribution of this study is the use ofmore » Bayesian modeling to quantify the effects of soil moisture and temperature on soil respiration across a wide range of conditions from frozen to hot and dry, while simultaneously accounting for biotic factors (e.g., vegetation cover, root density, and microbial biomass and substrate-use diversity) affected by snowpack. Elevated snow depth increased soil temperature (in the winter) and moisture (winter and spring), and was associated with reduced vegetation cover and microbial biomass carbon. Soil respiration showed an exponential increase with temperature, with a temperature sensitivity that decreased with increasing seasonal temperature (Q 10 = 4.3 [winter], 2.3 [spring], and 1.7 [summer]); frozen soils were associated with unrealistic Q 10 approximate to 7989 due to the liquid-to-ice transition of soil water. Soil respiration was sensitive to soil water content; predicted respiration under very dry conditions was less than 10% of respiration under moist conditions. While higher vegetation cover increased soil respiration, this was not due to increased root density, and may reflect differences in litter inputs. Microbial substrate-use diversity was negatively related to reference respiration (i.e., respiration rate at a reference temperature and optimal soil moisture), although the mechanism remains unclear. Lastly, this study indicates that soil respiration is inhibited by shallow snowpack through multiple mechanisms; thus, future decreases in snowpack across the sagebrush steppe have the potential to reduce losses of soil C, potentially affecting regional carbon balance.« less

Impact of biochar produced from post-harvest residue on the adsorption behavior of diesel oil on loess soil.

PubMed

Jiang, Yu Feng; Sun, Hang; Yves, Uwamungu J; Li, Hong; Hu, Xue Fei

2016-02-01

The primary objective of this study was to investigate the effect of biochar, produced from wheat residue at different temperatures, on the adsorption of diesel oil by loess soil. Kinetic and equilibrium data were processed to understand the adsorption mechanism of diesel by biochar-affected loess soil; dynamic and thermodynamic adsorption experiments were conducted to characterize this adsorption. The surface features and chemical structure of biochar, modified at varying pyrolytic temperatures, were investigated using surface scanning electron microscopy and Fourier transform infrared analysis. The kinetic data showed that the adsorption of diesel oil onto loess soil could be described by a pseudo-second-order kinetic model, with the rate-controlling step being intraparticle diffusion. However, in the presence of biochar, boundary layer control and intraparticle diffusion were both involved in the adsorption. Besides, the adsorption equilibrium data were well described by the Freundlich isothermal model. The saturated adsorption capacity weakened as temperature increased, suggesting a spontaneous exothermic process. Thermodynamic parameter analysis showed that adsorption was mainly a physical process and was enhanced by chemical adsorption. The adsorption capacity of loess soil for diesel oil was weakened with increasing pH. The biochar produced by pyrolytic wheat residue increased the adsorption behavior of petroleum pollutants in loess soil.

A Novel Optical Model for Remote Sensing of Near-Surface Soil Moisture

NASA Astrophysics Data System (ADS)

Babaeian, E.; Sadeghi, M.; Jones, S. B.; Tuller, M.

2016-12-01

Common triangle and trapezoid methods that are based on both optical and thermal remote sensing (RS) information have been widely applied in the past to estimate near-surface soil moisture from the soil temperature - vegetation index space (e.g., LST-NDVI). For most cases, this approach assumes a linear relationship between soil moisture and temperature. Though this linearity assumption yields reasonable moisture estimates, it is not always justified as evidenced by laboratory and field measurements. Furthermore, this approach requires optical as well as thermal RS data for definition of the land surface temperature (LST) - vegetation index space, therefore, it is not applicable to satellites that do not provide thermal output such as the ESA Sentinel-2. To overcome these limitations, we propose a novel trapezoid model that only relies on optical NIR and SWIR data. The new model was validated using Sentinel-2 and Landsat-8 data for the semiarid Walnut Gulch (AZ) and sub humid Little Washita (OK) watersheds that vastly differ in land use and surface cover and provide excellent ground-truth moisture information from extensive sensor networks. Preliminary results for 2015-2016 indicate significant potential of the new model with a RMSE smaller than 4% volumetric near-surface moisture content and also confirm the enhanced utility of the high spatially and temporally resolved Sentinel-2 data.

A complex permittivity model for field estimation of soil water contents using time domain reflectometry

USDA-ARS?s Scientific Manuscript database

Accurate electromagnetic sensing of soil water contents (') under field conditions is complicated by the dependence of permittivity on specific surface area, temperature, and apparent electrical conductivity, all which may vary across space or time. We present a physically-based mixing model to pred...

A thermal-based remote sensing modeling system for estimating evapotranspiration from field to global scales

USDA-ARS?s Scientific Manuscript database

Thermal-infrared remote sensing of land surface temperature provides valuable information for quantifying root-zone water availability, evapotranspiration (ET) and crop condition. This paper describes a robust but relatively simple thermal-based energy balance model that parameterizes the key soil/s...

Influence of Temperature, Relative Humidity, and Soil Properties on the Soil-Air Partitioning of Semivolatile Pesticides: Laboratory Measurements and Predictive Models.

PubMed

Davie-Martin, Cleo L; Hageman, Kimberly J; Chin, Yu-Ping; Rougé, Valentin; Fujita, Yuki

2015-09-01

Soil-air partition coefficient (Ksoil-air) values are often employed to investigate the fate of organic contaminants in soils; however, these values have not been measured for many compounds of interest, including semivolatile current-use pesticides. Moreover, predictive equations for estimating Ksoil-air values for pesticides (other than the organochlorine pesticides) have not been robustly developed, due to a lack of measured data. In this work, a solid-phase fugacity meter was used to measure the Ksoil-air values of 22 semivolatile current- and historic-use pesticides and their degradation products. Ksoil-air values were determined for two soils (semiarid and volcanic) under a range of environmentally relevant temperature (10-30 °C) and relative humidity (30-100%) conditions, such that 943 Ksoil-air measurements were made. Measured values were used to derive a predictive equation for pesticide Ksoil-air values based on temperature, relative humidity, soil organic carbon content, and pesticide-specific octanol-air partition coefficients. Pesticide volatilization losses from soil, calculated with the newly derived Ksoil-air predictive equation and a previously described pesticide volatilization model, were compared to previous results and showed that the choice of Ksoil-air predictive equation mainly affected the more-volatile pesticides and that the way in which relative humidity was accounted for was the most critical difference.

Met Éireann high resolution reanalysis for Ireland

NASA Astrophysics Data System (ADS)

Gleeson, Emily; Whelan, Eoin; Hanley, John

2017-03-01

The Irish Meteorological Service, Met Éireann, has carried out a 35-year very high resolution (2.5 km horizontal grid) regional climate reanalysis for Ireland using the ALADIN-HIRLAM numerical weather prediction system. This article provides an overview of the reanalysis, called MÉRA, as well as a preliminary analysis of surface parameters including screen level temperature, 10 m wind speeds, mean sea-level pressure (MSLP), soil temperatures, soil moisture and 24 h rainfall accumulations. The quality of the 3-D variational data assimilation used in the reanalysis is also assessed. Preliminary analysis shows that it takes almost 12 months to spin up the deep soil in terms of moisture, justifying the choice of running year-long spin up periods. Overall, the model performed consistently over the time period. Small biases were found in screen-level temperatures (less than -0.5 °C), MSLP (within 0.5 hPa) and 10 m wind speed (up to 0.5 m s-1) Soil temperatures are well represented by the model. 24 h accumulations of precipitation generally exhibit a small positive bias of ˜ 1 mm per day and negative biases over mountains due to a mismatch between the model orography and the geography of the region. MÉRA outperforms the ERA-Interim reanalysis, particularly in terms of standard deviations in screen-level temperatures and surface winds. This dataset is the first of its kind for Ireland that will be made publically available during spring 2017.

Remote Sensing of Soil Moisture: A Comparison of Optical and Thermal Methods

NASA Astrophysics Data System (ADS)

Foroughi, H.; Naseri, A. A.; Boroomandnasab, S.; Sadeghi, M.; Jones, S. B.; Tuller, M.; Babaeian, E.

2017-12-01

Recent technological advances in satellite and airborne remote sensing have provided new means for large-scale soil moisture monitoring. Traditional methods for soil moisture retrieval require thermal and optical RS observations. In this study we compared the traditional trapezoid model parameterized based on the land surface temperature - normalized difference vegetation index (LST-NDVI) space with the recently developed optical trapezoid model OPTRAM parameterized based on the shortwave infrared transformed reflectance (STR)-NDVI space for an extensive sugarcane field located in Southwestern Iran. Twelve Landsat-8 satellite images were acquired during the sugarcane growth season (April to October 2016). Reference in situ soil moisture data were obtained at 22 locations at different depths via core sampling and oven-drying. The obtained results indicate that the thermal/optical and optical prediction methods are comparable, both with volumetric moisture content estimation errors of about 0.04 cm3 cm-3. However, the OPTRAM model is more efficient because it does not require thermal data and can be universally parameterized for a specific location, because unlike the LST-soil moisture relationship, the reflectance-soil moisture relationship does not significantly vary with environmental variables (e.g., air temperature, wind speed, etc.).

Variable temperature sensitivity of soil organic carbon in North American forests

Treesearch

Cinzia Fissore; Christian P. Giardina; Christopher W. Swanston; Gary M. King; Randall K. Kolka

2009-01-01

We investigated mean residence time (MRT) for soil organic carbon (SOC) sampled from paired hardwood and pine forests located along a 22 °C mean annual temperature (MAT) gradient in North America. We used acid hydrolysis fractionation, radiocarbon analyses, long-term laboratory incubations (525-d), and a three-pool model to describe the size and kinetics of...

The inconvenient truth about eddy covariance flux partitioning and implications for global carbon cycle estimates

NASA Astrophysics Data System (ADS)

Wohlfahrt, Georg; Galvagno, Marta

2016-04-01

Ecosystem respiration (ER) and gross primary productivity (GPP) are key carbon cycle concepts. Global estimates of ER and GPP are largely based on measurements of the net ecosystem CO2 exchange by means of the eddy covariance method from which ER and GPP are inferred using so-called flux partitioning algorithms. Using a simple two-source model of ecosystem respiration, consisting of an above-ground respiration source driven by simulated air temperature and a below-ground respiration source driven by simulated soil temperature, we demonstrate that the two most popular flux partitioning algorithms are unable to provide unbiased estimates of daytime ER (ignoring any reduction of leaf mitochondrial respiration) and thus GPP. The bias is demonstrated to be either positive or negative and to depend in a complex fashion on the driving temperature, the ratio of above- to below-ground respiration, the respective temperature sensitivities, the soil depth where the below-ground respiration source originates from (and thus phase and amplitude of soil vs. surface temperature) and day length. The insights from the modeling analysis are subject to a reality check using direct measurements of ER at a grassland where measurements of ER were conducted both during night and day using automated opaque chambers. Consistent with the modeling analysis we find that using air temperature to extrapolate from nighttime to daytime conditions overestimates daytime ER (by 20% or ca. 65 gC m-2 over a 100 day study period), while soil temperature results in an underestimation (by 4% or 12 gC m-2). We conclude with practical recommendations for eddy covariance flux partitioning in the context of the FLUXNET project.

The activation energy of stabilised/solidified contaminated soils.

PubMed

Chitambira, B; Al-Tabbaa, A; Perera, A S R; Yu, X D

2007-03-15

Developing an understanding of the time-related performance of cement-treated materials is essential in understanding their durability and long-term effectiveness. A number of models have been developed to predict this time-related performance. One such model is the maturity concept which involves use of the 'global' activation energy which derives from the Arrhenius equation. The accurate assessment of the activation energy is essential in the realistic modelling of the accelerated ageing of cement-treated soils. Experimentally, this model is applied to a series of tests performed at different elevated temperatures. Experimental work, related to the results of a time-related performance on a contaminated site in the UK treated with in situ stabilisation/solidification was carried out. Three different cement-based grouts were used on two model site soils which were both contaminated with a number of heavy metals and a hydrocarbon. Uncontaminated soils were also tested. Elevated temperatures up to 60 degrees C and curing periods up to 90 days were used. The resulting global activation energies for the uncontaminated and contaminated soils were compared. Lower values were obtained for the contaminated soils reflecting the effect of the contaminants. The resulting equivalent ages for the uncontaminated and contaminated mixes tested were 5.1-7.4 and 0.8-4.1 years, respectively. This work shows how a specific set of contaminants affect the E(a) values for particular cementitious systems and how the maturity concept can be applied to cement-treated contaminated soils.

Expanding Upon the MEMS Framework: How Temperature Impacts Organo-Mineral Interactions

NASA Astrophysics Data System (ADS)

Smith, K.; Waring, B. G.

2017-12-01

Microbial substrate use efficiency (SUE; the fraction of substrate carbon (C) incorporated into biomass vs. respired) affects the development of soil organic matter (SOM). An emerging theoretical model (the Microbial Efficiency-Matrix Stabilization (MEMS) framework) posits that microbial SUE acts as a filter for plant litter inputs, whereby a larger proportion of microbial products are synthesized from labile (and not recalcitrant) plant substrates. Thus, SOM stability depends on both the efficiency of microbial anabolism as well as the degree to which microbial products stabilize within the mineral soil matrix. In this study, we performed a laboratory microcosm experiment using diverse soils collected in Utah to test how substrate complexity, soil mineralogy, and temperature interact to control SOM formation. Prior to microcosm setup, we first removed organic C from our field soils by washing with concentrated hypochlorite solution. Microcosms were then assembled by mixing C-free soil with one of three substrates (glucose, cellulose, and lignin), and placed in incubators set to different temperatures (18°, 28°, and 38°C). Respiration rates were then estimated by periodically sampling headspace CO2 concentrations in each microcosm. Prior to C removal, we found that field soils exhibited distinct properties ranging from clay-rich vertisols (55:27:18, sand:silt:clay; 1.1% C), to loamy-sand entisols (85:11:4; 0.3% C), and organic-rich mollisols (79:17:4; 1.7% C). In the incubation experiment, consistent with enzyme kinetics theory, respiration rates increased as a function of incubation temperature (p < 0.0001), and that the temperature response of respiration was dependent on substrate (p < 0.0001), with the lignin treatment exhibiting the greatest temperature sensitivity. While respiration was significantly lower in the mollisol treatment (p < 0.0001), other soil effects (including interactions with temperature and substrate) were less clear. Together these results build upon the MEMS framework by highlighting the importance of organo-mineral interactions and temperature as controls on soil C cycling.

Effects of Soil Moisture on the Temperature Sensitivity of Soil Heterotrophic Respiration: A Laboratory Incubation Study

PubMed Central

Zhou, Weiping; Hui, Dafeng; Shen, Weijun

2014-01-01

The temperature sensitivity (Q10) of soil heterotrophic respiration (Rh) is an important ecological model parameter and may vary with temperature and moisture. While Q10 generally decreases with increasing temperature, the moisture effects on Q10 have been controversial. To address this, we conducted a 90-day laboratory incubation experiment using a subtropical forest soil with a full factorial combination of five moisture levels (20%, 40%, 60%, 80%, and 100% water holding capacity - WHC) and five temperature levels (10, 17, 24, 31, and 38°C). Under each moisture treatment, Rh was measured several times for each temperature treatment to derive Q10 based on the exponential relationships between Rh and temperature. Microbial biomass carbon (MBC), microbial community structure and soil nutrients were also measured several times to detect their potential contributions to the moisture-induced Q10 variation. We found that Q10 was significantly lower at lower moisture levels (60%, 40% and 20% WHC) than at higher moisture level (80% WHC) during the early stage of the incubation, but became significantly higher at 20%WHC than at 60% WHC and not significantly different from the other three moisture levels during the late stage of incubation. In contrast, soil Rh had the highest value at 60% WHC and the lowest at 20% WHC throughout the whole incubation period. Variations of Q10 were significantly associated with MBC during the early stages of incubation, but with the fungi-to-bacteria ratio during the later stages, suggesting that changes in microbial biomass and community structure are related to the moisture-induced Q10 changes. This study implies that global warming’s impacts on soil CO2 emission may depend upon soil moisture conditions. With the same temperature rise, wetter soils may emit more CO2 into the atmosphere via heterotrophic respiration. PMID:24647610

Remediation of saturated soil contaminated with petroleum products using air sparging with thermal enhancement.

PubMed

Mohamed, A M I; El-menshawy, Nabil; Saif, Amany M

2007-05-01

Pollutants in the form of non-aqueous phase liquids (NAPLs), such as petroleum products, pose a serious threat to the soil and groundwater. A mathematical model was derived to study the unsteady pollutant concentrations through water saturated contaminated soil under air sparging conditions for different NAPLs and soil properties. The comparison between the numerical model results and the published experimental results showed acceptable agreement. Furthermore, an experimental study was conducted to remove NAPLs from the contaminated soil using the sparging air technique, considering the sparging air velocity, air temperature, soil grain size and different contaminant properties. This study showed that sparging air at ambient temperature through the contaminated soil can remove NAPLs, however, employing hot air sparging can provide higher contaminant removal efficiency, by about 9%. An empirical correlation for the volatilization mass transfer coefficient was developed from the experimental results. The dimensionless numbers used were Sherwood number (Sh), Peclet number (Pe), Schmidt number (Sc) and several physical-chemical properties of VOCs and porous media. Finally, the estimated volatilization mass transfer coefficient was used for calculation of the influence of heated sparging air on the spreading of the NAPL plume through the contaminated soil.

Bayesian Evaluation of Dynamical Soil Carbon Models Using Soil Carbon Flux Data

NASA Astrophysics Data System (ADS)

Xie, H. W.; Romero-Olivares, A.; Guindani, M.; Allison, S. D.

2017-12-01

2016 was Earth's hottest year in the modern temperature record and the third consecutive record-breaking year. As the planet continues to warm, temperature-induced changes in respiration rates of soil microbes could reduce the amount of carbon sequestered in the soil organic carbon (SOC) pool, one of the largest terrestrial stores of carbon. This would accelerate temperature increases. In order to predict the future size of the SOC pool, mathematical soil carbon models (SCMs) describing interactions between the biosphere and atmosphere are needed. SCMs must be validated before they can be chosen for predictive use. In this study, we check two SCMs called CON and AWB for consistency with observed data using Bayesian goodness of fit testing that can be used in the future to compare other models. We compare the fit of the models to longitudinal soil respiration data from a meta-analysis of soil heating experiments using a family of Bayesian goodness of fit metrics called information criteria (IC), including the Widely Applicable Information Criterion (WAIC), the Leave-One-Out Information Criterion (LOOIC), and the Log Pseudo Marginal Likelihood (LPML). These IC's take the entire posterior distribution into account, rather than just one outputted model fit line. A lower WAIC and LOOIC and larger LPML indicate a better fit. We compare AWB and CON with fixed steady state model pool sizes. At equivalent SOC, dissolved organic carbon, and microbial pool sizes, CON always outperforms AWB quantitatively by all three IC's used. AWB monotonically improves in fit as we reduce the SOC steady state pool size while fixing all other pool sizes, and the same is almost true for CON. The AWB model with the lowest SOC is the best performing AWB model, while the CON model with the second lowest SOC is the best performing model. We observe that AWB displays more changes in slope sign and qualitatively displays more adaptive dynamics, which prevents AWB from being fully ruled out for predictive use, but based on IC's, CON is clearly the superior model for fitting the data. Hence, we demonstrate that Bayesian goodness of fit testing with information criteria helps us rigorously determine the consistency of models with data. Models that demonstrate their consistency to multiple data sets with our approach can then be selected for further refinement.

Can Geoengineering Effectively Reduce the Land Warming?

NASA Astrophysics Data System (ADS)

Wang, W.; MacMartin, D.; Moore, J. C.; Ji, D.

2017-12-01

Permafrost, defined as ground that remains at or below 0 C for two or more consecutive years, underlies 24% of the land in the Northern Hemisphere. Under recent climate warming, permafrost has begun to thaw, causing changes in ecosystems and impacting northern communities. Using the multiple land model output from the Permafrost Carbon Network and applying 5 commonly used permafrost diagnostic methods, we assess the projected Northern Hemisphere permafrost area under RCP 8.5 scenario. Both the air and soil relative warming change is compared to highlight the soil warming pattern and intensity. Using the multiple Earth System Models output under abrupt 4×CO2, G1, PI-control, G3, G4, and RCP4.5 experiments, a preliminary attempt is also performed to examine the effectiveness of geoengineering schemes on reducing the land warming. Although there is uncertainty in the projected results due to model and method difference, the soil temperature based methods derived permafrost all present an intense decrease by 48% - 68% until 2100. The projected soil temperature by the more physically complicated model shows a different warming pattern compared with the air, which indicates that some potential land process intervene with the land response to atmospheric change. The simulated soil temperature can be effectively cooled down by 2 - 9 degree under G1 compared with abrupt 4×CO2, and by less than 4 degree under G3 and G4 compared with RCP4.5.

Climate-driven reduction in soil loss due to the dynamic role of vegetation

NASA Astrophysics Data System (ADS)

Constantine, J. A.; Ciampalini, R.; Walker-Springett, K.; Hales, T. C.; Ormerod, S.; Gabet, E. J.; Hall, I. R.

2016-12-01

Simulations of 21st century climate change predict increases in seasonal precipitation that may lead to widespread soil loss and reduced soil carbon stores by increasing the likelihood of surface runoff. Vegetation may counteract this increase through its dynamic response to climate change, possibly mitigating any impact on soil erosion. Here, we document for the first time the potential for vegetation to prevent widespread soil loss by surface-runoff mechanisms (i.e., rill and inter-rill erosion) by implementing a process-based soil erosion model across catchments of Great Britain with varying land-cover, topographic, and soil characteristics. Our model results reveal that, even under a significantly wetter climate, warmer air temperatures can limit soil erosion across areas with permanent vegetation cover because of its role in enhancing primary productivity, which improves leaf interception, soil infiltration-capacity, and the erosive resistance of soil. Consequently, any increase in air temperature associated with climate change will increase the threshold change in rainfall required to accelerate soil loss, and rates of soil erosion could therefore decline by up to 50% from 2070-2099 compared to baseline values under the IPCC-defined medium-emissions scenario SRES A1B. We conclude that enhanced primary productivity due to climate change can introduce a negative-feedback mechanism that limits soil loss by surface runoff as vegetation-induced impacts on soil hydrology and erodibility offset precipitation increases, highlighting the need to expand areas of permanent vegetation cover to reduce the potential for climate-driven soil loss.

DasPy – Open Source Multivariate Land Data Assimilation Framework with High Performance Computing

NASA Astrophysics Data System (ADS)

Han, Xujun; Li, Xin; Montzka, Carsten; Kollet, Stefan; Vereecken, Harry; Hendricks Franssen, Harrie-Jan

2015-04-01

Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. Multivariate data assimilation refers to the simultaneous assimilation of observation data for multiple model state variables into a simulation model. Our main motivation was to develop an open source multivariate land data assimilation framework (DasPy) which is implemented using the Python script language mixed with C++ and Fortran language. This system has been evaluated in several soil moisture, L-band brightness temperature and land surface temperature assimilation studies. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be represented by perturbed atmospheric forcings, perturbed soil and vegetation properties and model initial conditions. The CLM4.5 (Community Land Model) was integrated as the model operator. The CMEM (Community Microwave Emission Modelling Platform), COSMIC (COsmic-ray Soil Moisture Interaction Code) and the two source formulation were integrated as observation operators for assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy is parallelized using the hybrid MPI (Message Passing Interface) and OpenMP (Open Multi-Processing) techniques. All the input and output data flow is organized efficiently using the commonly used NetCDF file format. Online 1D and 2D visualization of data assimilation results is also implemented to facilitate the post simulation analysis. In summary, DasPy is a ready to use open source parallel multivariate land data assimilation framework.

Weathering profiles in soils and rocks on Earth and Mars

NASA Astrophysics Data System (ADS)

Hausrath, E.; Adcock, C. T.; Bamisile, T.; Baumeister, J. L.; Gainey, S.; Ralston, S. J.; Steiner, M.; Tu, V.

2017-12-01

Interactions of liquid water with rock, soil, or sediments can result in significant chemical and mineralogical changes with depth. These changes can include transformation from one phase to another as well as translocation, addition, and loss of material. The resulting chemical and mineralogical depth profiles can record characteristics of the interacting liquid water such as pH, temperature, duration, and abundance. We use a combined field, laboratory, and modeling approach to interpret the environmental conditions preserved in soils and rocks. We study depth profiles in terrestrial field environments; perform dissolution experiments of primary and secondary phases important in soil environments; and perform numerical modeling to quantitatively interpret weathering environments. In our field studies we have measured time-integrated basaltic mineral dissolution rates, and interpreted the impact of pH and temperature on weathering in basaltic and serpentine-containing rocks and soils. These results help us interpret fundamental processes occurring in soils on Earth and on Mars, and can also be used to inform numerical modeling and laboratory experiments. Our laboratory experiments provide fundamental kinetic data to interpret processes occurring in soils. We have measured dissolution rates of Mars-relevant phosphate minerals, clay minerals, and amorphous phases, as well as dissolution rates under specific Mars-relevant conditions such as in concentrated brines. Finally, reactive transport modeling allows a quantitative interpretation of the kinetic, thermodynamic, and transport processes occurring in soil environments. Such modeling allows the testing of conditions under longer time frames and under different conditions than might be possible under either terrestrial field or laboratory conditions. We have used modeling to examine the weathering of basalt, olivine, carbonate, phosphate, and clay minerals, and placed constraints on the duration, pH, and solution chemistry of past aqueous alteration occurring on Mars.

Quantification of the effect of temperature gradients in soils on subsurface radon signal

NASA Astrophysics Data System (ADS)

Haquin, Gustavo; Ilzycer, Danielle; Kamai, Tamir; Zafrir, Hovav; Weisbrod, Noam

2017-04-01

Temperature gradients that develop in soils due to atmospheric temperature cycles are factors of primary importance in determining the rates and directions of subsurface gas flow. Models including mechanisms of thermal convection and thermal diffusion partially explain the impact of temperature gradients on subsurface radon transport. However, the overall impact of temperature gradients on subsurface radon transport is still not well understood. A laboratory setup was designed and built to experimentally investigate the influence of temperature gradients on radon transport under well controlled conditions. A 60 cm diameter and 120 cm tall column was thermally insulated except from the atmosphere-soil interface, such that it was constructed to simulate field conditions where temperature gradients in soils are developed following atmospheric temperature cycles. The column was filled with fine grinded phosphate rock which provided the porous media with radon source. Radon in soil-air was continuously monitored using NaI gamma detectors positioned at different heights along the column. Soil temperature, differential pressure, and relative humidity were monitored along the column. Experiments based on steep and gradual stepwise changes in ambient temperature were conducted. Absolute changes on radon levels in the order of 10-30% were measured at temperature gradients of up to ±20oC/m. Results showed a non-linear correlation between the temperature gradient and the subsurface radon concentration. An asymmetric relationship between the radon concentration and the temperature gradients for ΔT>0 and ΔT<0 was also observed. Laboratory simulations of the time- and depth-dependent temperature wave functions with frequencies ranged from a daily cycle to few days were performed. In response to the harmonic temperature behaviour radon oscillations at similar frequencies were detected correspondingly. In this work a quantitative relationship between radon and temperature gradients will be presented for cases beyond the classical conditions for thermal convection and thermal diffusion.

Carbon exchange in biological soil crust communities under differential temperatures and soil water contents: implications for global change

USGS Publications Warehouse

Grote, Edmund E.; Belnap, Jayne; Housman, David C.; Sparks, Jed P.

2010-01-01

Biological soil crusts (biocrusts) are an integral part of the soil system in arid regions worldwide, stabilizing soil surfaces, aiding vascular plant establishment, and are significant sources of ecosystem nitrogen and carbon. Hydration and temperature primarily control ecosystem CO2 flux in these systems. Using constructed mesocosms for incubations under controlled laboratory conditions, we examined the effect of temperature (5-35 1C) and water content (WC, 20-100%) on CO2 exchange in light cyanobacterially dominated) and dark cyanobacteria/lichen and moss dominated) biocrusts of the cool Colorado Plateau Desert in Utah and the hot Chihuahuan Desert in New Mexico. In light crusts from both Utah and New Mexico, net photosynthesis was highest at temperatures 430 1C. Net photosynthesis in light crusts from Utah was relatively insensitive to changes in soil moisture. In contrast, light crusts from New Mexico tended to exhibit higher rates of net photosynthesis at higher soil moisture. Dark crusts originating from both sites exhibited the greatest net photosynthesis at intermediate soil water content (40-60%). Declines in net photosynthesis were observed in dark crusts with crusts from Utah showing declines at temperatures 425 1C and those originating from New Mexico showing declines at temperatures 435 1C. Maximum net photosynthesis in all crust types from all locations were strongly influenced by offsets in the optimal temperature and water content for gross photosynthesis compared with dark respiration. Gross photosynthesis tended to be maximized at some intermediate value of temperature and water content and dark respiration tended to increase linearly. The results of this study suggest biocrusts are capable of CO2 exchange under a wide range of conditions. However, significant changes in the magnitude of this exchange should be expected for the temperature and precipitation changes suggested by current climate models.

Acclimation and soil moisture constrain sugar maple root respiration in experimentally warmed soil.

PubMed

Jarvi, Mickey P; Burton, Andrew J

2013-09-01

The response of root respiration to warmer soil can affect ecosystem carbon (C) allocation and the strength of positive feedbacks between climatic warming and soil CO2 efflux. This study sought to determine whether fine-root (<1 mm) respiration in a sugar maple (Acer saccharum Marsh.)-dominated northern hardwood forest would adjust to experimentally warmed soil, reducing C return to the atmosphere at the ecosystem scale to levels lower than that would be expected using an exponential temperature response function. Infrared heating lamps were used to warm the soil (+4 to +5 °C) in a mature sugar maple forest in a fully factorial design, including water additions used to offset the effects of warming-induced dry soil. Fine-root-specific respiration rates, root biomass, root nitrogen (N) concentration, soil temperature and soil moisture were measured from 2009 to 2011, with experimental treatments conducted from late 2010 to 2011. Partial acclimation of fine-root respiration to soil warming occurred, with soil moisture deficit further constraining specific respiration rates in heated plots. Fine-root biomass and N concentration remained unchanged. Over the 2011 growing season, ecosystem root respiration was not significantly greater in warmed soil. This result would not be predicted by models that allow respiration to increase exponentially with temperature and do not directly reduce root respiration in drier soil.

Soil and climate modelling to explain soil differences in MIS5e and MIS13 on the Chinese Loess Plateau

NASA Astrophysics Data System (ADS)

Finke, P. A.; Yu, Y.; Yin, Q.; Bernardini, N. J.

2016-12-01

Objective Proxy records indicate that MIS5 (about 120 ka ago) was warmer than MIS13 (about 500 ka ago). Nevertheless, MIS13-soils in the Chinese loess plateau (105 -115°E and 30-40°N) are stronger developed than MIS5-soils. This has been attributed to a stronger East Asian summer monsoon. Other differences are interglacial lengths and loess deposition rates. We aimed to find explanations for soil development differences by using a soil formation model (SoilGen) with climatic inputs obtained from an earth system model (LOVECLIM). Material and Methods The LOVECLIM model is driven by time-varying insolation and greenhouse gas concentrations and was run to give monthly values for temperature, precipitation and evaporation as well the dominant vegetation type. Model results for were corrected for systematic differences between present-day observation data and simulation. Reconstructions were made for both interglacials of the amount of inblown loess, and the mineralogy and grain size distribution of the initial loess as well as the dust. These data were fed into the SoilGen model, which was used to calculate various soil parameters with depth and over time. Results Simulations show a stronger developed MIS13 soil, in terms of weathering (loss of anorthite), and redistribution of calcite, gypsum and clay. This corresponds to observed paleosoils. MIS13-soils are more leached. As simulated temperatures and annual precipitation between MIS5 and MIS13 did not vary strongly, the greater length of MIS13 seemed the main explanation for the stronger leaching and weathering. Closer analysis however showed a larger number of months in MIS13 with a precipitation surplus, even when only considering the first 22 ka. Only in such months significant leaching can occur. Conclusion Using simulation models it was demonstrated that the stronger soil expression in MIS13 than in MIS5 is likely caused by more months with a precipitation surplus, in combination with a longer duration of MIS13.

Permafrost carbon cycles under multifactor global change: a modeling analysis

NASA Astrophysics Data System (ADS)

Li, J.; Natali, S.; Schaedel, C.; Schuur, E. A.; Luo, Y.

2012-12-01

Carbon dioxide (CO2) and methane (CH4) from permafrost zones are projected to be elevated under global change scenarios, but the magnitude and spatiotemporal variation of these greenhouse gas sources are still highly uncertain. Here we implement and evaluate the integration of a methane model into the Community Atmosphere-Biosphere Land Exchange model (CABLE v1.5 of CSIRO, Australia) in order to explore the carbon emissions under warming, elevated CO2 and altered precipitation. The weather data was obtained from a tundra site named eight mile lake in Alaska and the data of years 2004-2009 was used to tune and validate the model. First, data obtained from measurement were transformed to meet the input weather data required by the model. Second, model parameters regarding vegetation and soil were modified to accurately simulate the permafrost site. For example, we modified the resistivity of soil in the model so that the modeled energy balance was found to match with the observations. Currently, the modeled NPP are relatively higher but soil temperature is lower than the observations. Third, a new methane module is being integrated into the model. We simulate the methane production, oxidation and emission processes (ebullition, diffusion and plant-aided transport). We test new functions for soil pH and redox potential that impact microbial methane production and oxidation in soils. We link water table position (WTP) with the available amount of decomposable carbon for methanogens, in combination with spatially explicit simulation of soil temperature. We also validated the model and resolved the discrepancy between the model and observation. In this presentation, we will describe results of simulations to forecast CO2 and CH4 fluxes under climate change scenarios.

Sensitivity properties of a biosphere model based on BATS and a statistical-dynamical climate model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, T.

A biosphere model based on the Biosphere-Atmosphere Transfer Scheme (BATS) and the Saltzman-Vernekar (SV) statistical-dynamical climate model is developed. Some equations of BATS are adopted either intact or with modifications, some are conceptually modified, and still others are replaced with equations of the SV model. The model is designed so that it can be run independently as long as the parameters related to the physiology and physiognomy of the vegetation, the atmospheric conditions, solar radiation, and soil conditions are given. With this stand-alone biosphere model, a series of sensitivity investigations, particularly the model sensitivity to fractional area of vegetation cover,more » soil surface water availability, and solar radiation for different types of vegetation, were conducted as a first step. These numerical experiments indicate that the presence of a vegetation cover greatly enhances the exchanges of momentum, water vapor, and energy between the atmosphere and the surface of the earth. An interesting result is that a dense and thick vegetation cover tends to serve as an environment conditioner or, more specifically, a thermostat and a humidistat, since the soil surface temperature, foliage temperature, and temperature and vapor pressure of air within the foliage are practically insensitive to variation of soil surface water availability and even solar radiation within a wide range. An attempt is also made to simulate the gradual deterioration of environment accompanying gradual degradation of a tropical forest to grasslands. Comparison with field data shows that this model can realistically simulate the land surface processes involving biospheric variations. 46 refs., 10 figs., 6 tabs.« less

Sensitivity properties of a biosphere model based on BATS and a statistical-dynamical climate model

NASA Technical Reports Server (NTRS)

Zhang, Taiping

1994-01-01

A biosphere model based on the Biosphere-Atmosphere Transfer Scheme (BATS) and the Saltzman-Vernekar (SV) statistical-dynamical climate model is developed. Some equations of BATS are adopted either intact or with modifications, some are conceptually modified, and still others are replaced with equations of the SV model. The model is designed so that it can be run independently as long as the parameters related to the physiology and physiognomy of the vegetation, the atmospheric conditions, solar radiation, and soil conditions are given. With this stand-alone biosphere model, a series of sensitivity investigations, particularly the model sensitivity to fractional area of vegetation cover, soil surface water availability, and solar radiation for different types of vegetation, were conducted as a first step. These numerical experiments indicate that the presence of a vegetation cover greatly enhances the exchanges of momentum, water vapor, and energy between the atmosphere and the surface of the earth. An interesting result is that a dense and thick vegetation cover tends to serve as an environment conditioner or, more specifically, a thermostat and a humidistat, since the soil surface temperature, foliage temperature, and temperature and vapor pressure of air within the foliage are practically insensitive to variation of soil surface water availability and even solar radiation within a wide range. An attempt is also made to simulate the gradual deterioration of environment accompanying gradual degradation of a tropical forest to grasslands. Comparison with field data shows that this model can realistically simulate the land surface processes involving biospheric variations.

A simple nudging scheme to assimilate ASCAT soil moisture data in the WRF model

NASA Astrophysics Data System (ADS)

Capecchi, V.; Gozzini, B.

2012-04-01

The present work shows results obtained in a numerical experiment using the WRF (Weather and Research Forecasting, www.wrf-model.org) model. A control run where soil moisture is constrained by GFS global analysis is compared with a test run where soil moisture analysis is obtained via a simple nudging scheme using ASCAT data. The basic idea of the assimilation scheme is to "nudge" the first level (0-10 cm below ground in NOAH model) of volumetric soil moisture of the first-guess (say θ(b,1) derived from global model) towards the ASCAT derived value (say ^θ A). The soil moisture analysis θ(a,1) is given by: { θ + K (^θA - θ ) l = 1 θ(a,1) = θ(b,l) (b,l) l > 1 (b,l) (1) where l is the model soil level. K is a constant scalar value that is user specified and in this study it is equal to 0.2 (same value as in similar studies). Soil moisture is critical for estimating latent and sensible heat fluxes as well as boundary layer structure. This parameter is, however, poorly assimilated in current global and regional numerical models since no extensive soil moisture observation network exists. Remote sensing technologies offer a synoptic view of the dynamics and spatial distribution of soil moisture with a frequent temporal coverage and with a horizontal resolution similar to mesoscale NWP model. Several studies have shown that measurements of normalized backscatter (surface soil wetness) from the Advanced Scatterometer (ASCAT) operating at microwave frequencies and boarded on the meteorological operational (Metop) satellite, offer quality information about surface soil moisture. Recently several studies deal with the implementation of simple assimilation procedures (nudging, Extended Kalman Filter, etc...) to integrate ASCAT data in NWP models. They found improvements in screen temperature predictions, particularly in areas such as North-America and in the Tropics, where it is strong the land-atmosphere coupling. The ECMWF (Newsletter No. 127) is currently implementing and testing an EKF for combining conventional observations and remote sensed soil moisture data in order to produce a more accurate analysis. In the present work verification skills (RMSE, BIAS, correlation) of both control and test run are presented using observed data collected by International Soil Moisture Network. Moreover improvements in temperature predictions are evaluated.

Effects of varying soil moisture contents and vegetation canopies on microwave emissions

NASA Technical Reports Server (NTRS)

Burke, H.-H. K.; Schmugge, T. J.

1982-01-01

Results of NASA airborne passive microwave scans of bare and vegetated fields for comparison with ground truth tests are discussed and a model for atmospheric scattering of radiation by vegetation is detailed. On-board radiometers obtained data at 21, 2.8, and 1.67 cm during three passes over each of 46 fields, 28 of which were bare and the others having wheat or alfalfa. Ground-based sampling included moisture in five layers down to 15 cm in addition to soil temperature. The relationships among the brightness temperature and soil moisture, as well as the surface roughness and the vegetation canopy were examined. A model was developed for the dielectric coefficient and volume scattering for a vegetation medium. L- to C-band data were found useful for retrieving soil information directly. A surface moisture content of 5-35% yielded an emissivity of 0.9-0.7. The data agreed well with a combined multilayer radiative transfer model with simple roughness correction.

The effect of row structure on soil moisture retrieval accuracy from passive microwave data.

PubMed

Xingming, Zheng; Kai, Zhao; Yangyang, Li; Jianhua, Ren; Yanling, Ding

2014-01-01

Row structure causes the anisotropy of microwave brightness temperature (TB) of soil surface, and it also can affect soil moisture retrieval accuracy when its influence is ignored in the inversion model. To study the effect of typical row structure on the retrieved soil moisture and evaluate if there is a need to introduce this effect into the inversion model, two ground-based experiments were carried out in 2011. Based on the observed C-band TB, field soil and vegetation parameters, row structure rough surface assumption (Q p model and discrete model), including the effect of row structure, and flat rough surface assumption (Q p model), ignoring the effect of row structure, are used to model microwave TB of soil surface. Then, soil moisture can be retrieved, respectively, by minimizing the difference of the measured and modeled TB. The results show that soil moisture retrieval accuracy based on the row structure rough surface assumption is approximately 0.02 cm(3)/cm(3) better than the flat rough surface assumption for vegetated soil, as well as 0.015 cm(3)/cm(3) better for bare and wet soil. This result indicates that the effect of row structure cannot be ignored for accurately retrieving soil moisture of farmland surface when C-band is used.

Comparison of evaporative fluxes from porous surfaces resolved by remotely sensed and in-situ temperature and soil moisture data

NASA Astrophysics Data System (ADS)

Wallen, B.; Trautz, A.; Smits, K. M.

2014-12-01

The estimation of evaporation has important implications in modeling climate at the regional and global scale, the hydrological cycle and estimating environmental stress on agricultural systems. In field and laboratory studies, remote sensing and in-situ techniques are used to collect thermal and soil moisture data of the soil surface and subsurface which is then used to estimate evaporative fluxes, oftentimes using the sensible heat balance method. Nonetheless, few studies exist that compare the methods due to limited data availability and the complexity of many of the techniques, making it difficult to understand flux estimates. This work compares different methods used to quantify evaporative flux based on remotely sensed and in-situ temperature and soil moisture data. A series of four laboratory experiments were performed under ambient and elevated air temperature conditions with homogeneous and heterogeneous soil configurations in a small two-dimensional soil tank interfaced with a small wind tunnel apparatus. The soil tank and wind tunnel were outfitted with a suite of sensors that measured soil temperature (surface and subsurface), air temperature, soil moisture, and tank weight. Air and soil temperature measurements were obtained using infrared thermography, heat pulse sensors and thermistors. Spatial and temporal thermal data were numerically inverted to obtain the evaporative flux. These values were then compared with rates of mass loss from direct weighing of the samples. Results demonstrate the applicability of different methods under different surface boundary conditions; no one method was deemed most applicable under every condition. Infrared thermography combined with the sensible heat balance method was best able to determine evaporative fluxes under stage 1 conditions while distributed temperature sensing combined with the sensible heat balance method best determined stage 2 evaporation. The approaches that appear most promising for determining the surface energy balance incorporates soil moisture rate of change over time and atmospheric conditions immediately above the soil surface. An understanding of the fidelity regarding predicted evaporation rates based upon stages of evaporation enables a more deliberate selection of the suite of sensors required for data collection.

Chemically Reactive Nitrogen Trace Species in the Planetary Boundary Layer

DTIC Science & Technology

1996-01-01

56 Biogenic NO Budget Used in the EPA Regional Oxidant Model ......... 58 Conclusions and...Regional Oxidant Model (ROM) ............................... 59 Table 2.4. Air and soil temperatures and average NO flux using W illiam s’ m odel...1985; Penkett, 1988). Yienger and Levy (1995) developed an empirically based model to estimate soil NOx emissions on a global scale. They have reported

Understanding the Day Cent model: Calibration, sensitivity, and identifiability through inverse modeling

USGS Publications Warehouse

Necpálová, Magdalena; Anex, Robert P.; Fienen, Michael N.; Del Grosso, Stephen J.; Castellano, Michael J.; Sawyer, John E.; Iqbal, Javed; Pantoja, Jose L.; Barker, Daniel W.

2015-01-01

The ability of biogeochemical ecosystem models to represent agro-ecosystems depends on their correct integration with field observations. We report simultaneous calibration of 67 DayCent model parameters using multiple observation types through inverse modeling using the PEST parameter estimation software. Parameter estimation reduced the total sum of weighted squared residuals by 56% and improved model fit to crop productivity, soil carbon, volumetric soil water content, soil temperature, N2O, and soil3NO− compared to the default simulation. Inverse modeling substantially reduced predictive model error relative to the default model for all model predictions, except for soil 3NO− and 4NH+. Post-processing analyses provided insights into parameter–observation relationships based on parameter correlations, sensitivity and identifiability. Inverse modeling tools are shown to be a powerful way to systematize and accelerate the process of biogeochemical model interrogation, improving our understanding of model function and the underlying ecosystem biogeochemical processes that they represent.

Soil mapping and processes models to support climate change mitigation and adaptation strategies: a review

NASA Astrophysics Data System (ADS)

Muñoz-Rojas, Miriam; Pereira, Paulo; Brevik, Eric; Cerda, Artemi; Jordan, Antonio

2017-04-01

As agreed in Paris in December 2015, global average temperature is to be limited to "well below 2 °C above pre-industrial levels" and efforts will be made to "limit the temperature increase to 1.5 °C above pre-industrial levels. Thus, reducing greenhouse gas emissions (GHG) in all sectors becomes critical and appropriate sustainable land management practices need to be taken (Pereira et al., 2017). Mitigation strategies focus on reducing the rate and magnitude of climate change by reducing its causes. Complementary to mitigation, adaptation strategies aim to minimise impacts and maximize the benefits of new opportunities. The adoption of both practices will require developing system models to integrate and extrapolate anticipated climate changes such as global climate models (GCMs) and regional climate models (RCMs). Furthermore, integrating climate models driven by socio-economic scenarios in soil process models has allowed the investigation of potential changes and threats in soil characteristics and functions in future climate scenarios. One of the options with largest potential for climate change mitigation is sequestering carbon in soils. Therefore, the development of new methods and the use of existing tools for soil carbon monitoring and accounting have therefore become critical in a global change context. For example, soil C maps can help identify potential areas where management practices that promote C sequestration will be productive and guide the formulation of policies for climate change mitigation and adaptation strategies. Despite extensive efforts to compile soil information and map soil C, many uncertainties remain in the determination of soil C stocks, and the reliability of these estimates depends upon the quality and resolution of the spatial datasets used for its calculation. Thus, better estimates of soil C pools and dynamics are needed to advance understanding of the C balance and the potential of soils for climate change mitigation. Here, we discuss the most recent advances on the application of soil mapping and modeling to support climate change mitigation and adaptation strategies; and These strategies are a key component of the implementation of sustainable land management policies need to be integrated are critical to. The objective of this work is to present a review about the advantages of soil mapping and process modeling for sustainable land management. Muñoz-Rojas, M., Pereira, P., Brevic, E., Cerda, A., Jordan, A. (2017) Soil mapping and processes models for sustainable land management applied to modern challenges. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B. (Eds.) Soil mapping and process modelling for sustainable land use management (Elsevier Publishing House) ISBN: 9780128052006

Mercury emission and dispersion models from soils contaminated by cinnabar mining and metallurgy.

PubMed

Llanos, Willians; Kocman, David; Higueras, Pablo; Horvat, Milena

2011-12-01

The laboratory flux measurement system (LFMS) and dispersion models were used to investigate the kinetics of mercury emission flux (MEF) from contaminated soils. Representative soil samples with respect to total Hg concentration (26-9770 μg g(-1)) surrounding a decommissioned mercury-mining area (Las Cuevas Mine), and a former mercury smelter (Cerco Metalúrgico de Almadenejos), in the Almadén mercury mining district (South Central Spain), were collected. Altogether, 14 samples were analyzed to determine the variation in mercury emission flux (MEF) versus distance from the sources, regulating two major environmental parameters comprising soil temperature and solar radiation. In addition, the fraction of the water-soluble mercury in these samples was determined in order to assess how MEF from soil is related to the mercury in the aqueous soil phase. Measured MEFs ranged from less than 140 to over 10,000 ng m(-2) h(-1), with the highest emissions from contaminated soils adjacent to point sources. A significant decrease of MEF was then observed with increasing distance from these sites. Strong positive effects of both temperature and solar radiation on MEF was observed. Moreover, MEF was found to occur more easily in soils with higher proportions of soluble mercury compared to soils where cinnabar prevails. Based on the calculated Hg emission rates and with the support of geographical information system (GIS) tools and ISC AERMOD software, dispersion models for atmospheric mercury were implemented. In this way, the gaseous mercury plume generated by the soil-originated emissions at different seasons was modeled. Modeling efforts revealed that much higher emissions and larger mercury plumes are generated in dry and warm periods (summer), while the plume is smaller and associated with lower concentrations of atmospheric mercury during colder periods with higher wind activity (fall). Based on the calculated emissions and the model implementation, yearly emissions from the "Cerco Metalúrgico de Almadenejos" decommissioned metallurgical precinct were estimated at 16.4 kg Hg y(-1), with significant differences between seasons.

Modeling pulsed soil respiration in an African savanna ecosystem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fan, Zhaosheng; Neff, Jason C.; Hanan, Niall P.

2015-01-01

Savannas cover 60% of the African continent and play an important role in the global carbon (C) emissions from fire and land use. To better characterize the biophysical controls over soil respiration in these settings, half-hourly observations of volumetric soil-water content, temperature, and the concentration of carbon dioxide (CO2) at different soil depths were continually measured from 2005 to 2007 under trees ("sub-canopy") and between trees ("inter-canopy") in a savanna vegetation near Skukuza, Kruger National Park, South Africa. The measured soil climate and CO2 concentration data were assimilated into a process-based model that estimates the CO2 production and flux withmore » coupled dynamics of dissolved organic C (DOC) and microbial biomass C. Our results show that temporal and spatial variations in CO2 flux were strongly influenced by precipitation and vegetation cover, with two times greater CO2 flux in the subcanopy plots (similar to 2421 g CO2 m(-2) yr(-1)) than in the inter-canopy plots (similar to 1290 g CO2 m(-2) yr(-1)). Precipitation influenced soil respiration by changing soil temperature and moisture; however, our modeling analysis suggests that the pulsed response of soil respiration to precipitation events (known as "Birch effect") is a key control on soil fluxes at this site. At this site, "Birch effect" contributed to approximately 50% and 65% of heterotrophic respiration or 20% and 39% of soil respiration in the sub-canopy and inter-canopy plots, respectively. These results suggest that pulsed response of respiration to precipitation events is an important component of the C cycle of savannas and should be considered in both measurement and modeling studies of carbon exchange in similar ecosystems. (C) 2014 Elsevier B.V. All rights reserved.« less

Thermal and Hydrologic Signatures of Soil Controls on Evaporation: A Combined Energy and Water Balance Approach with Implications for Remote Sensing of Evaporation

NASA Technical Reports Server (NTRS)

Salvucci, Guido D.

2000-01-01

The overall goal of this research is to examine the feasibility of applying a newly developed diagnostic model of soil water evaporation to large land areas using remotely sensed input parameters. The model estimates the rate of soil evaporation during periods when it is limited by the net transport resulting from competing effects of capillary rise and drainage. The critical soil hydraulic properties are implicitly estimated via the intensity and duration of the first stage (energy limited) evaporation, removing a major obstacle in the remote estimation of evaporation over large areas. This duration, or 'time to drying' (t(sub d)) is revealed through three signatures detectable in time series of remote sensing variables. The first is a break in soil albedo that occurs as a small vapor transmission zone develops near the surface. The second is a break in either surface to air temperature differences or in the diurnal surface temperature range, both of which indicate increased sensible heat flux (and/or storage) required to balance the decrease in latent heat flux. The third is a break in the temporal pattern of near surface soil moisture. Soil moisture tends to decrease rapidly during stage I drying (as water is removed from storage), and then become more or less constant during soil limited, or 'stage II' drying (as water is merely transmitted from deeper soil storage). The research tasks address: (1) improvements in model structure, including extensions to transpiration and aggregation over spatially variable soil and topographic landscape attributes; and (2) applications of the model using remotely sensed input parameters.

Thermal and Hydrologic Signatures of Soil Controls on Evaporation: A Combined Energy and Water Balance Approach with Implications for Remote Sensing of Evaporation

NASA Technical Reports Server (NTRS)

Salvucci, Guido D.

1997-01-01

The overall goal of this research is to examine the feasibility of applying a newly developed diagnostic model of soil water evaporation to large land areas using remotely sensed input parameters. The model estimates the rate of soil evaporation during periods when it is limited by the net transport resulting from competing effects of capillary rise and drainage. The critical soil hydraulic properties are implicitly estimated via the intensity and duration of the first stage (energy limited) evaporation, removing a major obstacle in the remote estimation of evaporation over large areas. This duration, or "time to drying" (t(sub d)), is revealed through three signatures detectable in time series of remote sensing variables. The first is a break in soil albedo that occurs as a small vapor transmission zone develops near the surface. The second is a break in either surface to air temperature differences or in the diurnal surface temperature range, both of which indicate increased sensible heat flux (and/or storage) required to balance the decrease in latent heat flux. The third is a break in the temporal pattern of near surface soil moisture. Soil moisture tends to decrease rapidly during stage 1 drying (as water is removed from storage), and then become more or less constant during soil limited, or "stage 2" drying (as water is merely transmitted from deeper soil storage). The research tasks address: (1) improvements in model structure, including extensions to transpiration and aggregation over spatially variable soil and topographic landscape attributes; and (2) applications of the model using remotely sensed input parameters.

Understanding the driving forces behind the losses of soil carbon across England and Wales

NASA Astrophysics Data System (ADS)

Bellamy, Patricia

2010-05-01

More than twice as much carbon is held in soils as in vegetation or the atmosphere, and changes in soil carbon content can have a large effect on the global carbon budget. The possibility that climate change is being reinforced by increased carbon dioxide emissions from soils owing to rising temperature is the subject of a continuing debate. But evidence for the suggested feedback mechanism has to date come solely from small-scale laboratory and field experiments and modelling studies. Here we use data from the National Soil Inventory of England and Wales obtained between 1978 and 2003 to show that carbon was lost from soils across England and Wales over the survey period at a mean rate of 0.6% yr-1 (relative to the existing soil carbon content). We find that the relative rate of carbon loss increased with soil carbon content and was more than 2% yr-1 in soils with carbon contents greater than 100 g kg-1. The relationship between rate of carbon loss and carbon content is irrespective of land use, suggesting a link to climate change. Our findings indicate that losses of soil carbon in England and Wales—and by inference in other temperate regions—are likely to have been offsetting absorption of carbon by terrestrial sinks. To investigate the possible driving forces of the measured losses of soil carbon we applied a simple model of soil carbon turnover to evaluate alternative explanations for the observed trends. We find that neither changes in decomposition resulting from the effects of climate change on soil temperature and moisture, nor changes in carbon input from vegetation, could account on their own for the overall trends. Of other explanations, results indicate that past changes in land use and management were probably dominant. The climate change signal, such as it is, is masked by these other changes. A more sophisticated model of carbon change (DAYCENT) has now been applied across the whole range of soils in England and Wales. This model has been validated using the NSI data and three different ways of initialising the model have been tried. This has shown that the observed sites cannot be considered to have been at equilibrium when first measured. Without a detailed long term record on past land use and management it is not possible to accurately determine why this is. However it has been shown that the assumed initial state is important for predicting magnitude and direction of losses, but less important for predicting differences between scenarios. Assuming that the model's assumptions about climate effects on plant growth and carbon turnover rates are essentially correct, running DAYCENT for a range of climate scenarios showed the only climatic factor that had any significant effect on the carbon loss rates under our conditions was summer soil temperature, in arable soils only. Changes in soil moisture appeared to be too small to have any effect.

Impacts of differing aerodynamic resistance formulae on modeled energy exchange at the above-canopy/within-canopy/soil interface

USDA-ARS?s Scientific Manuscript database

Application of the Two-Source Energy Balance (TSEB) Model using land surface temperature (LST) requires aerodynamic resistance parameterizations for the flux exchange above the canopy layer, within the canopy air space and at the soil/substrate surface. There are a number of aerodynamic resistance f...

Microwave soil moisture measurements and analysis

NASA Technical Reports Server (NTRS)

Newton, R. W.; Howell, T. A.; Nieber, J. L.; Vanbavel, C. H. M. (Principal Investigator)

1980-01-01

An effort to develop a model that simulates the distribution of water content and of temperature in bare soil is documented. The field experimental set up designed to acquire the data to test this model is described. The microwave signature acquisition system (MSAS) field measurements acquired in Colby, Kansas during the summer of 1978 are pesented.

Screening variability and change of soil moisture under wide-ranging climate conditions: Snow dynamics effects.

PubMed

Verrot, Lucile; Destouni, Georgia

2015-01-01

Soil moisture influences and is influenced by water, climate, and ecosystem conditions, affecting associated ecosystem services in the landscape. This paper couples snow storage-melting dynamics with an analytical modeling approach to screening basin-scale, long-term soil moisture variability and change in a changing climate. This coupling enables assessment of both spatial differences and temporal changes across a wide range of hydro-climatic conditions. Model application is exemplified for two major Swedish hydrological basins, Norrström and Piteälven. These are located along a steep temperature gradient and have experienced different hydro-climatic changes over the time period of study, 1950-2009. Spatially, average intra-annual variability of soil moisture differs considerably between the basins due to their temperature-related differences in snow dynamics. With regard to temporal change, the long-term average state and intra-annual variability of soil moisture have not changed much, while inter-annual variability has changed considerably in response to hydro-climatic changes experienced so far in each basin.

Interactive Vegetation Phenology, Soil Moisture, and Monthly Temperature Forecasts

NASA Technical Reports Server (NTRS)

Koster, R. D.; Walker, G. K.

2015-01-01

The time scales that characterize the variations of vegetation phenology are generally much longer than those that characterize atmospheric processes. The explicit modeling of phenological processes in an atmospheric forecast system thus has the potential to provide skill to subseasonal or seasonal forecasts. We examine this possibility here using a forecast system fitted with a dynamic vegetation phenology model. We perform three experiments, each consisting of 128 independent warm-season monthly forecasts: 1) an experiment in which both soil moisture states and carbon states (e.g., those determining leaf area index) are initialized realistically, 2) an experiment in which the carbon states are prescribed to climatology throughout the forecasts, and 3) an experiment in which both the carbon and soil moisture states are prescribed to climatology throughout the forecasts. Evaluating the monthly forecasts of air temperature in each ensemble against observations, as well as quantifying the inherent predictability of temperature within each ensemble, shows that dynamic phenology can indeed contribute positively to subseasonal forecasts, though only to a small extent, with an impact dwarfed by that of soil moisture.

Modelling impacts of temperature, and acidifying and eutrophying deposition on DOC trends

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Rowe, Ed; Evans, Chris; Monteith, Don; Vanguelova, Elena; Wade, Andrew; Clark, Joanna

2017-04-01

Surface water dissolved organic carbon (DOC) concentrations in large parts of the northern hemisphere have risen over the past three decades, raising concern about enhanced contributions of carbon to the atmosphere and seas and oceans. The effect of declining acid deposition has been identified as a key control on DOC trends in soil and surface waters, since pH and ionic strength affect sorption and desorption of DOC. However, since DOC is derived mainly from recently-fixed carbon, and organic matter decomposition rates are considered sensitive to temperature, uncertainty persists regarding the extent to the relative importance of different drivers that affect these upward trends. We ran the dynamic model MADOC (Model of Acidity and Soil Organic Carbon) for a range of UK soils (podzols, gleysols and peatland), for which the time-series were available, to consider the likely relative importance of decreased deposition of sulphate and chloride, accumulation of reactive N, and higher temperatures, on DOC production in different soils. Modelled patterns of DOC change generally agreed favourably with measurements collated over 10-20 years, but differed markedly between sites. While the acidifying effect of sulphur deposition appeared to be the predominant control on the observed soil water DOC trends in all the soils considered other than a blanket peat, the model suggested that over the long term, the effects of nitrogen deposition on N-limited soils may have been sufficient to elevate the DOC recovery trajectory significantly. The second most influential cause of rising DOC in the model simulations was N deposition in ecosystems that are N-limited and respond with stimulated plant growth. Although non-marine chloride deposition made some contribution to acidification and recovery, it was not amongst the main drivers of DOC change. Warming had almost no effect on modelled historic DOC trends, but may prove to be a significant driver of DOC in future via its influence on nutrient availability and productivity. This suggests that current and future DOC concentrations could also exceed preindustrial levels due to the increased productivity of N enriched ecosystems, having important implications for drinking water catchment management and the setting and pursuit of appropriate restoration targets.

Modeling transformation of soil organic matter through the soil enzyme activity

NASA Astrophysics Data System (ADS)

Tregubova, Polina; Vladimirov, Artem; Vasilyeva, Nadezda

2017-04-01

The sensitivity of soil heterotrophic respiration to changing environmental conditions is widely investigated nowadays but still remain extremely controversial. The mechanisms are still needed to reveal. In this work we model soil C and N biogeochemical cycles based on general principles of soil carbon and nitrogen dynamics with focusing on biochemical processes occurring in the soil based on well known classes of enzymes and organic compounds that they can transform. According to classic theories, exoenzymes and endoenzymes of bacteria and fungi as stable over a long period catalytic components play a significant role in degradation of plant and animal residues, decomposition of biopolymers of different sizes, humification processes and in releasing of labile compounds essential for the microorganism and plant growth and germination. We test the model regimes sensitivity to such environmental factors as temperature and moisture. Modeling the directions and patterns of soil biochemical activity is important for evaluation of soil agricultural productivity as well as its ecological functions.

A simple model of carbon in the soil profile for agricultural soils in Northwestern Europe

NASA Astrophysics Data System (ADS)

Taghizadeh-Toosi, Arezoo; Hutchings, Nicholas J.; Vejlin, Jonas; Christensen, Bent T.; Olesen, Jørgen E.

2014-05-01

World soil carbon (C) stocks are second to those in the ocean, and represent three times as much C as currently present in the atmosphere. The amount of C in soil may play a significant role in carbon exchanges between the atmosphere and the terrestrial environment. The C-TOOL model is a three-pool linked soil organic carbon (SOC) model in well-drained mineral soils under agricultural land management to allow generalized parameterization for estimating effects of management measures at medium to long time scales for the entire soil profile (0-100 cm). C-TOOL has been developed to enable simulations of SOC turnover in soil using temperature dependent first order kinetics for describing decomposition. Compared with many other SOC models, C-TOOL applies a less complicated structure, which facilitates easier calibration, and it requires only few inputs (i.e., average monthly air temperature, soil clay content,soil carbon-to-nitrogen ratio, and C inputs to the soil from plants and other sources). C-TOOL was parameterized using SOC and radiocarbon data from selected long-term field treatments in United Kingdom, Sweden and Denmark. However, less data were available for evaluation of subsoil C (25-100 cm) from the long-term experiments applied. In Denmark a national 7×7 km grid net was established in 1986 for soil C monitoring down to 100 cm depth. The results of SOC showed a significant decline from 1997 to 2009 in the 0-50 cm soil layer. This was mainly attributed to changes in the 25-50 cm layer, where a decline in SOC was found for all soil texture types. Across the period 1986 to 2009 there was clear tendency for increasing SOC on the sandy soils and reductions on the loamy soils. This effect is linked to land use, since grasslands and dairy farms are more abundant in the western parts of Denmark, where most of the sandy soils are located. The results and the data from soil monitoring have been used to validate the C-TOOL modelling approach used for accounting of changes in SOC of Danish agricultural soils and for verification of the national inventories of SOC changes in agricultural soils. Future work will focus on further evaluating effects on subsoil C as well as improving the estimation of C inputs, particularly root C input at different soil depth. Key words: Soil organic carbon, modelling, C-TOOL, agriculture, management, grassland

Climatic sensitivity of dryland soil CO2 fluxes differs dramatically with biological soil crust successional state

USGS Publications Warehouse

Tucker, Colin; Ferrenberg, Scott; Reed, Sasha C.

2018-01-01

Arid and semiarid ecosystems make up approximately 41% of Earth’s terrestrial surface and are suggested to regulate the trend and interannual variability of the global terrestrial carbon (C) sink. Biological soil crusts (biocrusts) are common dryland soil surface communities of bryophytes, lichens, and/or cyanobacteria that bind the soil surface together and that may play an important role in regulating the climatic sensitivity of the dryland C cycle. Major uncertainties exist in our understanding of the interacting effects of changing temperature and moisture on CO2 uptake (photosynthesis) and loss (respiration) from biocrust and sub-crust soil, particularly as related to biocrust successional state. Here, we used a mesocosm approach to assess how biocrust successional states related to climate treatments. We subjected bare soil (Bare), early successional lightly pigmented cyanobacterial biocrust (Early), and late successional darkly pigmented moss-lichen biocrust (Late) to either ambient or + 5°C above ambient soil temperature for 84 days. Under ambient temperatures, Late biocrust mesocosms showed frequent net uptake of CO2, whereas Bare soil, Early biocrust, and warmed Late biocrust mesocosms mostly lost CO2 to the atmosphere. The inhibiting effect of warming on CO2 exchange was a result of accelerated drying of biocrust and soil. We used these data to parameterize, via Bayesian methods, a model of ecosystem CO2 fluxes, and evaluated the model with data from an autochamber CO2 system at our field site on the Colorado Plateau in SE Utah. In the context of the field experiment, the data underscore the negative effect of warming on fluxes both biocrust CO2 uptake and loss—which, because biocrusts are a dominant land cover type in this ecosystem, may extend to ecosystem-scale C cycling.

The Effect of Soil Hydraulic Properties vs. Soil Texture in Land Surface Models

NASA Technical Reports Server (NTRS)

Gutmann, E. D.; Small, E. E.

2005-01-01

This study focuses on the effect of Soil Hydraulic Property (SHP) selection on modeled surface fluxes following a rain storm in a semi-arid environment. SHPs are often defined based on a Soil Texture Class (STC). To examine the effectiveness of this approach, the Noah land surface model was run with each of 1306 soils in a large SHP database. Within most STCs, the outputs have a range of 350 W/m2 for latent and sensible heat fluxes, and 8K for surface temperature. The average difference between STC median values is only 100 W/m2 for latent and sensible heat. It is concluded that STC explains 5-15% of the variance in model outputs and should not be used to determine SHPs.

Observed Local Impacts of Global Irrigation on Surface Temperature

NASA Astrophysics Data System (ADS)

Chen, L.; Dirmeyer, P.

2017-12-01

Agricultural irrigation has significant potential for altering local climate through reducing soil albedo, increasing evapotranspiration, and enabling greater leaf area. Numerous studies using regional or global climate models have demonstrated the cooling effects of irrigation on mean and extreme temperature, especially over regions where irrigation is extensive. However, these model-based results have not been validated due to the limitations of observational datasets. In this study, multiple satellite-based products, including the Moderate Resolution Imaging Spectroradiometer (MODIS) and Soil Moisture Active Passive (SMAP) data sets, are used to isolate and quantify the local impacts of irrigation on surface climate over the irrigated regions, which are derived from the Global Map of Irrigation Areas (GMIA). The relationships among soil moisture, albedo, evapotranspiration, and surface temperature are explored. Strong evaporative cooling of irrigation on daytime surface temperature is found over the arid and semi-arid regions, such as California's Central Valley, the Great Plains, and central Asia. However, the cooling effects are less evident in most areas of eastern China, India, and the Lower Mississippi River Basin in spite of extensive irrigation over these regions. Results are also compared with irrigation experiments using the Community Earth System Model (CESM) to assess the model's ability to represent land-atmosphere interactions in regards to irrigation.

A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

2011-01-01

Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

Effect of soil property uncertainties on permafrost thaw projections: a calibration-constrained analysis

NASA Astrophysics Data System (ADS)

Harp, D. R.; Atchley, A. L.; Painter, S. L.; Coon, E. T.; Wilson, C. J.; Romanovsky, V. E.; Rowland, J. C.

2016-02-01

The effects of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The null-space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21st century (from calendar year 2006 to 2100) using atmospheric forcings from the Community Earth System Model (CESM) in the Representative Concentration Pathway (RCP) 8.5 greenhouse gas concentration trajectory. A 100-year projection allows for the evaluation of predictive uncertainty (due to soil property (parametric) uncertainty) and the inter-annual climate variability due to year to year differences in CESM climate forcings. After calibrating to measured borehole temperature data at this well-characterized site, soil property uncertainties are still significant and result in significant predictive uncertainties in projected active layer thickness and annual thaw depth-duration even with a specified future climate. Inter-annual climate variability in projected soil moisture content and Stefan number are small. A volume- and time-integrated Stefan number decreases significantly, indicating a shift in subsurface energy utilization in the future climate (latent heat of phase change becomes more important than heat conduction). Out of 10 soil parameters, ALT, annual thaw depth-duration, and Stefan number are highly dependent on mineral soil porosity, while annual mean liquid saturation of the active layer is highly dependent on the mineral soil residual saturation and moderately dependent on peat residual saturation. By comparing the ensemble statistics to the spread of projected permafrost metrics using different climate models, we quantify the relative magnitude of soil property uncertainty to another source of permafrost uncertainty, structural climate model uncertainty. We show that the effect of calibration-constrained uncertainty in soil properties, although significant, is less than that produced by structural climate model uncertainty for this location.

Assimilating soil moisture into an Earth System Model

NASA Astrophysics Data System (ADS)

Stacke, Tobias; Hagemann, Stefan

2017-04-01

Several modelling studies reported potential impacts of soil moisture anomalies on regional climate. In particular for short prediction periods, perturbations of the soil moisture state may result in significant alteration of surface temperature in the following season. However, it is not clear yet whether or not soil moisture anomalies affect climate also on larger temporal and spatial scales. In an earlier study, we showed that soil moisture anomalies can persist for several seasons in the deeper soil layers of a land surface model. Additionally, those anomalies can influence root zone moisture, in particular during explicitly dry or wet periods. Thus, one prerequisite for predictability, namely the existence of long term memory, is evident for simulated soil moisture and might be exploited to improve climate predictions. The second prerequisite is the sensitivity of the climate system to soil moisture. In order to investigate this sensitivity for decadal simulations, we implemented a soil moisture assimilation scheme into the Max-Planck Institute for Meteorology's Earth System Model (MPI-ESM). The assimilation scheme is based on a simple nudging algorithm and updates the surface soil moisture state once per day. In our experiments, the MPI-ESM is used which includes model components for the interactive simulation of atmosphere, land and ocean. Artificial assimilation data is created from a control simulation to nudge the MPI-ESM towards predominantly dry and wet states. First analyses are focused on the impact of the assimilation on land surface variables and reveal distinct differences in the long-term mean values between wet and dry state simulations. Precipitation, evapotranspiration and runoff are larger in the wet state compared to the dry state, resulting in an increased moisture transport from the land to atmosphere and ocean. Consequently, surface temperatures are lower in the wet state simulations by more than one Kelvin. In terms of spatial pattern, the largest differences between both simulations are seen for continental areas, while regions with a maritime climate are least sensitive to soil moisture assimilation.

A simplified, data-constrained approach to estimate the permafrost carbon-climate feedback.

PubMed

Koven, C D; Schuur, E A G; Schädel, C; Bohn, T J; Burke, E J; Chen, G; Chen, X; Ciais, P; Grosse, G; Harden, J W; Hayes, D J; Hugelius, G; Jafarov, E E; Krinner, G; Kuhry, P; Lawrence, D M; MacDougall, A H; Marchenko, S S; McGuire, A D; Natali, S M; Nicolsky, D J; Olefeldt, D; Peng, S; Romanovsky, V E; Schaefer, K M; Strauss, J; Treat, C C; Turetsky, M

2015-11-13

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation-Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2-33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9-112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of -14 to -19 Pg C °C(-1) on a 100 year time scale. For CH4 emissions, our approach assumes a fixed saturated area and that increases in CH4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10-18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming. © 2015 The Authors.

A simplified, data-constrained approach to estimate the permafrost carbon–climate feedback

PubMed Central

Koven, C. D.; Schuur, E. A. G.; Schädel, C.; Bohn, T. J.; Burke, E. J.; Chen, G.; Chen, X.; Ciais, P.; Grosse, G.; Harden, J. W.; Hayes, D. J.; Hugelius, G.; Jafarov, E. E.; Krinner, G.; Kuhry, P.; Lawrence, D. M.; MacDougall, A. H.; Marchenko, S. S.; McGuire, A. D.; Natali, S. M.; Nicolsky, D. J.; Olefeldt, D.; Peng, S.; Romanovsky, V. E.; Schaefer, K. M.; Strauss, J.; Treat, C. C.; Turetsky, M.

2015-01-01

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation–Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2–33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9–112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of −14 to −19 Pg C °C−1 on a 100 year time scale. For CH4 emissions, our approach assumes a fixed saturated area and that increases in CH4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10–18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming. PMID:26438276

A simplified, data-constrained approach to estimate the permafrost carbon–climate feedback

USGS Publications Warehouse

Koven, C.D.; Schuur, E.A.G.; Schädel, C.; Bohn, T. J.; Burke, E. J.; Chen, G.; Chen, X.; Ciais, P.; Grosse, G.; Harden, J.W.; Hayes, D.J.; Hugelius, G.; Jafarov, Elchin E.; Krinner, G.; Kuhry, P.; Lawrence, D.M.; MacDougall, A. H.; Marchenko, Sergey S.; McGuire, A. David; Natali, Susan M.; Nicolsky, D.J.; Olefeldt, David; Peng, S.; Romanovsky, V.E.; Schaefer, Kevin M.; Strauss, J.; Treat, C.C.; Turetsky, M.

2015-01-01

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation–Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2–33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9–112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of −14 to −19 Pg C °C−1 on a 100 year time scale. For CH4 emissions, our approach assumes a fixed saturated area and that increases in CH4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10–18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming.

Anthropogenic warming exacerbates European soil moisture droughts

NASA Astrophysics Data System (ADS)

Samaniego, L.; Thober, S.; Kumar, R.; Wanders, N.; Rakovec, O.; Pan, M.; Zink, M.; Sheffield, J.; Wood, E. F.; Marx, A.

2018-05-01

Anthropogenic warming is anticipated to increase soil moisture drought in the future. However, projections are accompanied by large uncertainty due to varying estimates of future warming. Here, using an ensemble of hydrological and land-surface models, forced with bias-corrected downscaled general circulation model output, we estimate the impacts of 1-3 K global mean temperature increases on soil moisture droughts in Europe. Compared to the 1.5 K Paris target, an increase of 3 K—which represents current projected temperature change—is found to increase drought area by 40% (±24%), affecting up to 42% (±22%) more of the population. Furthermore, an event similar to the 2003 drought is shown to become twice as frequent; thus, due to their increased occurrence, events of this magnitude will no longer be classified as extreme. In the absence of effective mitigation, Europe will therefore face unprecedented increases in soil moisture drought, presenting new challenges for adaptation across the continent.

Revisiting the choice of the driving temperature for eddy covariance CO2 flux partitioning

PubMed Central

Wohlfahrt, Georg; Galvagno, Marta

2017-01-01

So-called CO2 flux partitioning algorithms are widely used to partition the net ecosystem CO2 exchange into the two component fluxes, gross primary productivity and ecosystem respiration. Common CO2 flux partitioning algorithms conceptualize ecosystem respiration to originate from a single source, requiring the choice of a corresponding driving temperature. Using a conceptual dual-source respiration model, consisting of an above- and a below-ground respiration source each driven by a corresponding temperature, we demonstrate that the typical phase shift between air and soil temperature gives rise to a hysteresis relationship between ecosystem respiration and temperature. The hysteresis proceeds in a clockwise fashion if soil temperature is used to drive ecosystem respiration, while a counter-clockwise response is observed when ecosystem respiration is related to air temperature. As a consequence, nighttime ecosystem respiration is smaller than daytime ecosystem respiration when referenced to soil temperature, while the reverse is true for air temperature. We confirm these qualitative modelling results using measurements of day and night ecosystem respiration made with opaque chambers in a short-statured mountain grassland. Inferring daytime from nighttime ecosystem respiration or vice versa, as attempted by CO2 flux partitioning algorithms, using a single-source respiration model is thus an oversimplification resulting in biased estimates of ecosystem respiration. We discuss the likely magnitude of the bias, options for minimizing it and conclude by emphasizing that the systematic uncertainty of gross primary productivity and ecosystem respiration inferred through CO2 flux partitioning needs to be better quantified and reported. PMID:28439145

Contribution of the biological crust to the soil CO2 efflux in a Mediterranean ecosystem

NASA Astrophysics Data System (ADS)

Morillas, Lourdes; Bellucco, Veronica; Lo Cascio, Mauro; Marras, Serena; Spano, Donatella; Mereu, Simone

2016-04-01

Lately, the important role of the soil biological crust (hereafter biocrust) in Mediterranean ecosystems is emerging from a multitude of articles. It is becoming apparent that the biocrust has an important role in regulating ecosystem functions and that it interacts with the woody and herbaceous vegetation to a degree depending on the availability of water among other factors. Here we present the first results of a wider project and focus on the contribution of the biocrust to soil CO2 efflux, and on how the respiration of the biocrust responds to soil water content and temperature. A manipulative experiment was performed in a Mediterranean shrubland ecosystem in Sardinia (Italy) to assess the contribution of the bicocrust to soil CO2 efflux and to identify the main environmental drivers of the CO2 efflux in this ecosystem. For 19 months,in situ soil CO2 efflux was measured over three different surfaces: soil deprived of biocrust (hereafter Soil), biocrust (hereafter BC) and intact soil (hereafter Soil+BC). For these surfaces, three different approaches were used to investigate the dependency of CO2 efflux on soil temperature and soil water content, e.g. a simple linear regression, a multi-linear equation, and a modified version of the most common used Lloyd and Taylor model (Lloyd and Taylor, 1994). Results showed that CO2 effluxes emitted by Soil, BC and Soil+BC were differently driven by soil moisture and temperature: BC respiration was mainly controlled by soil moisture at 5 cm depth, whereas both soil temperature and water content at 20 cm depth determined Soil CO2 efflux. Soil temperature and water content at 5 cm depth drove Soil+BC respiration. We also found that biocrust can contribute substantially (up to 60%) to the total soil respiration depending on its moisture content. This contribution persists even in periods in which deeper soil layers are inactive, as small water pulses can activate lichens, mosses and cyanobacteria associated to the biocrust as well as the metabolism of carbon in soils, while deeper soil layers remain dormant. The important differences observed in CO2 efflux between Soil and Soil+BC suggest that projections on carbon budgets may underestimate soil CO2 efflux in spatially heterogeneous Mediterranean areas. Thus, our results highlight the relevance of accounting for the biocrust contribution to soil respiration and its responses to environmental drivers. The ongoing and planned activities to understand the full complexity of all factors determining respiration in water limited environments are briefly discussed. Lloyd, J., Taylor, J. A., 1994. On the temperature dependence of soil respiration. Funct. Ecol. 8, 315-323.

The microbial temperature sensitivity to warming is controlled by thermal adaptation and is independent of C-quality across a pan-continental survey

NASA Astrophysics Data System (ADS)

Berglund, Eva; Rousk, Johannes

2017-04-01

Climate models predict that warming will result in an increased loss of soil organic matter (SOM). However, field experiments suggest that although warming results in an immediate increase in SOM turnover, the effect diminishes over time. Although the use and subsequent turnover of SOM is dominated by the soil microbial community, the underlying physiology underpinning warming responses are not considered in current climate models. It has been suggested that a reduction in the perceived quality of SOM to the microbial community, and changes in the microbial thermal adaptation, could be important feed-backs to soil warming. Thus, studies distinguishing between temperature relationships and how substrate quality influences microbial decomposition are a priority. We examined microbial communities and temperature sensitivities along a natural climate gradient including 56 independent samples from across Europe. The gradient included mean annual temperatures (MAT) from ca -4 to 18 ˚ C, along with wide spans of environmental factors known to influence microbial communities, such as pH (4.0 to 8.8), nutrients (C/N from 7 to 50), SOM (from 4 to 94%), and plant communities, etc. The extensive ranges of environmental conditions resulted in wide ranges of substrate quality, indexed as microbial respiration per unit SOM, from 5-150 μg CO2g-1 SOM g-1 h-1. We hypothesised microbial communities to (1) be adapted to the temperature of their climate, leading to warm adapted bacterial communities that were more temperature sensitive (higher Q10s) at higher MAT; (2) have temperature sensitivities affected by the quality of SOM, with higher Q10s for lower quality SOM. To determine the microbial use of SOM and its dependence on temperature, we characterized microbial temperature dependences of bacterial growth (leu inc), fungal growth (ac-in-erg) and soil respiration in all 56 sites. Temperature dependences were determined using brief (ca. 1-2 h at 25˚ C) laboratory incubation experiments including temperatures from 0 to 35˚ C. Temperature relationships were modelled using the Ratkowsky model, and cardinal points including minimum temperature (Tmin) for growth and respiration along with temperature sensitivity (Q10) values were used as indices to compare sites. Microbial communities were cold-adapted in cold sites and warm-adapted in warm sites, as shown by Tmin values ranging from ca. -20 ˚ C to 0 ˚ C. For every 1˚ C rise in MAT, Tmin increased by 0.22˚ C and 0.28˚ C for bacteria and fungi, respectively. Soil respiration was less dependent on MAT, increasing 0.16 ˚ C per 1˚ C. Temperature dependence analyses grew stronger when regressed against summer temperatures, and weaker when regressed against winter temperatures. Hence, microbial communities adjusted their temperature dependence for growth more than for respiration, and higher temperatures had more impact than low temperatures did. The correlation between Tmin and MAT resulted in Q10s increasing with MAT, showing that microorganisms from cold regions were less temperature sensitive than those from warmer regions. For every 1˚ C increase in MAT, Q10 increased with 0.04 and 0.03 units for bacterial and fungal growth respectively, and 0.08 units for soil respiration. In contrast to previous studies, we found no relationship between temperature sensitivity and substrate quality. We demonstrate that the strongest driver of variation in microbial temperatures sensitivities (Q10s) is the microbial adaptation to its thermal environment. Surprisingly, the quality of SOM had no influence on the temperature sensitivity. This calls for a revision of the understanding for how microbial decomposers feed-back to climate warming. Specifically, the thermal adaptation of microbial communities need to be incorporated into climate models to capture responses to warming, while the quality of SOM can be ignored.

A Methodology for Soil Moisture Retrieval from Land Surface Temperature, Vegetation Index, Topography and Soil Type

NASA Astrophysics Data System (ADS)

Pradhan, N. R.

2015-12-01

Soil moisture conditions have an impact upon hydrological processes, biological and biogeochemical processes, eco-hydrology, floods and droughts due to changing climate, near-surface atmospheric conditions and the partition of incoming solar and long-wave radiation between sensible and latent heat fluxes. Hence, soil moisture conditions virtually effect on all aspects of engineering / military engineering activities such as operational mobility, detection of landmines and unexploded ordinance, natural material penetration/excavation, peaking factor analysis in dam design etc. Like other natural systems, soil moisture pattern can vary from completely disorganized (disordered, random) to highly organized. To understand this varying soil moisture pattern, this research utilized topographic wetness index from digital elevation models (DEM) along with vegetation index from remotely sensed measurements in red and near-infrared bands, as well as land surface temperature (LST) in the thermal infrared bands. This research developed a methodology to relate a combined index from DEM, LST and vegetation index with the physical soil moisture properties of soil types and the degree of saturation. The advantage in using this relationship is twofold: first it retrieves soil moisture content at the scale of soil data resolution even though the derived indexes are in a coarse resolution, and secondly the derived soil moisture distribution represents both organized and disorganized patterns of actual soil moisture. The derived soil moisture is used in driving the hydrological model simulations of runoff, sediment and nutrients.

Version 3 of the SMAP Level 4 Soil Moisture Product

NASA Technical Reports Server (NTRS)

Reichle, Rolf; Liu, Qing; Ardizzone, Joe; Crow, Wade; De Lannoy, Gabrielle; Kolassa, Jana; Kimball, John; Koster, Randy

2017-01-01

The NASA Soil Moisture Active Passive (SMAP) Level 4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root zone (0-100 cm) soil moisture as well as related land surface states and fluxes from 31 March 2015 to present with a latency of 2.5 days. The ensemble-based L4_SM algorithm is a variant of the Goddard Earth Observing System version 5 (GEOS-5) land data assimilation system and ingests SMAP L-band (1.4 GHz) Level 1 brightness temperature observations into the Catchment land surface model. The soil moisture analysis is non-local (spatially distributed), performs downscaling from the 36-km resolution of the observations to that of the model, and respects the relative uncertainties of the modeled and observed brightness temperatures. Prior to assimilation, a climatological rescaling is applied to the assimilated brightness temperatures using a 6 year record of SMOS observations. A new feature in Version 3 of the L4_SM data product is the use of 2 years of SMAP observations for rescaling where SMOS observations are not available because of radio frequency interference, which expands the impact of SMAP observations on the L4_SM estimates into large regions of northern Africa and Asia. This presentation investigates the performance and data assimilation diagnostics of the Version 3 L4_SM data product. The L4_SM soil moisture estimates meet the 0.04 m3m3 (unbiased) RMSE requirement. We further demonstrate that there is little bias in the soil moisture analysis. Finally, we illustrate where the assimilation system overestimates or underestimates the actual errors in the system.

Biomass-C specific temperature responses of microbial C transformations reveal consistency regardless of microbial community structure across diverse timescales of inquiry

NASA Astrophysics Data System (ADS)

Min, K.; Buckeridge, K. M.; Ziegler, S. E.; Edwards, K. A.; Bagchi, S.; Billings, S. A.

2016-12-01

The responses of heterotrophic microbial process rates to temperature in soils are often investigated in the short-term (hours to months), making it difficult to predict longer-term temperature responses. Here, we integrate the temperature sensitivity obtained from the Arrhenius model with the concepts of microbial resistance, resilience, and susceptibility to assess temporal dynamics of microbial temperature responses. We collected soils along a boreal forest climate gradient (long-term effect), and quantified exo-enzyme activities and CO2 respiration at 5, 15, and 25°C for 84 days (relatively short-term effect). Microbial process rates were examined at two levels (per g microbial biomass-C; and per g dry soil) along with community structure, to characterize driving mechanisms for temporal patterns (e.g., size of biomass, physiological plasticity, community composition). Although temperature sensitivity of exo-enzyme activities on a per g dry soil basis showed both resistance and resilience depending on the types of exo-enzyme, biomass -C-specific responses always exhibited resistance regardless of distinct community composition. Temperature sensitivity of CO2 respiration was constant across time and different communities at both units. This study advances our knowledge in two ways. First, resistant temperature sensitivity of exo-enzymes and respiration at biomass-C specific level across distinct communities and diverse timescales indicates a common relationship between microbial physiology and temperature at a fundamental level, a useful feature allowing microbial process models to be reasonably simplified. Second, different temporal responses of exo-enzymes depending on the unit selected provide a cautionary tale for those projecting future microbial behaviors, because interpretation of ecosystem process rates may vary with the unit of observation.

The hysteresis response of soil CO 2 concentration and soil respiration to soil temperature

DOE PAGES

Zhang, Quan; Katul, Gabriel G.; Oren, Ram; ...

2015-07-20

Diurnal hysteresis between soil temperature (T s) and both CO 2 concentration ([CO 2]) and soil respiration rate (R s) were reported across different field experiments. However, the causes of these hysteresis patterns remain a subject of debate, with biotic and abiotic factors both invoked as explanations. Here, to address these issues, a CO 2 gas transport model is developed by combining a layer-wise mass conservation equation for subsurface gas phase CO 2, Fickian diffusion for gas transfer, and a CO 2 source term that depends on soil temperature, moisture, and photosynthetic rate. Using this model, a hierarchy of numericalmore » experiments were employed to disentangle the causes of the hysteretic [CO 2]-T s and CO 2 flux T s (i.e., F-T s) relations. Model results show that gas transport alone can introduce both [CO 2]-T s and F-T s hystereses and also confirm prior findings that heat flow in soils lead to [CO 2] and F being out of phase with T s, thereby providing another reason for the occurrence of both hystereses. The area (A hys) of the [CO 2]-T s hysteresis near the surface increases, while the A hys of the Rs-Ts hysteresis decreases as soils become wetter. Moreover, a time-lagged carbon input from photosynthesis deformed the [CO 2]-T s and R s-T s patterns, causing a change in the loop direction from counterclockwise to clockwise with decreasing time lag. An asymmetric 8-shaped pattern emerged as the transition state between the two loop directions. Lastly, tracing the pattern and direction of the hysteretic [CO 2]-T s and R s-T s relations can provide new ways to fingerprint the effects of photosynthesis stimulation on soil microbial activity and detect time lags between rhizospheric respiration and photosynthesis.« less

The Contribution of Soil Moisture Information to Forecast Skill: Two Studies

NASA Technical Reports Server (NTRS)

Koster, Randal

2010-01-01

This talk briefly describes two recent studies on the impact of soil moisture information on hydrological and meteorological prediction. While the studies utilize soil moisture derived from the integration of large-scale land surface models with observations-based meteorological data, the results directly illustrate the potential usefulness of satellite-derived soil moisture information (e.g., from SMOS and SMAP) for applications in prediction. The first study, the GEWEX- and ClIVAR-sponsored GLACE-2 project, quantifies the contribution of realistic soil moisture initialization to skill in subseasonal forecasts of precipitation and air temperature (out to two months). The multi-model study shows that soil moisture information does indeed contribute skill to the forecasts, particularly for air temperature, and particularly when the initial local soil moisture anomaly is large. Furthermore, the skill contributions tend to be larger where the soil moisture initialization is more accurate, as measured by the density of the observational network contributing to the initialization. The second study focuses on streamflow prediction. The relative contributions of snow and soil moisture initialization to skill in streamflow prediction at seasonal lead, in the absence of knowledge of meteorological anomalies during the forecast period, were quantified with several land surface models using uniquely designed numerical experiments and naturalized streamflow data covering mUltiple decades over the western United States. In several basins, accurate soil moisture initialization is found to contribute significant levels of predictive skill. Depending on the date of forecast issue, the contributions can be significant out to leads of six months. Both studies suggest that improvements in soil moisture initialization would lead to increases in predictive skill. The relevance of SMOS and SMAP satellite-based soil moisture information to prediction are discussed in the context of these studies.

Coupled Land Surface-Subsurface Hydrogeophysical Inverse Modeling to Estimate Soil Organic Carbon Content in an Arctic Tundra

NASA Astrophysics Data System (ADS)

Tran, A. P.; Dafflon, B.; Hubbard, S.

2017-12-01

Soil organic carbon (SOC) is crucial for predicting carbon climate feedbacks in the vulnerable organic-rich Arctic region. However, it is challenging to achieve this property due to the general limitations of conventional core sampling and analysis methods. In this study, we develop an inversion scheme that uses single or multiple datasets, including soil liquid water content, temperature and ERT data, to estimate the vertical profile of SOC content. Our approach relies on the fact that SOC content strongly influences soil hydrological-thermal parameters, and therefore, indirectly controls the spatiotemporal dynamics of soil liquid water content, temperature and their correlated electrical resistivity. The scheme includes several advantages. First, this is the first time SOC content is estimated by using a coupled hydrogeophysical inversion. Second, by using the Community Land Model, we can account for the land surface dynamics (evapotranspiration, snow accumulation and melting) and ice/liquid phase transition. Third, we combine a deterministic and an adaptive Markov chain Monte Carlo optimization algorithm to better estimate the posterior distributions of desired model parameters. Finally, the simulated subsurface variables are explicitly linked to soil electrical resistivity via petrophysical and geophysical models. We validate the developed scheme using synthetic experiments. The results show that compared to inversion of single dataset, joint inversion of these datasets significantly reduces parameter uncertainty. The joint inversion approach is able to estimate SOC content within the shallow active layer with high reliability. Next, we apply the scheme to estimate OC content along an intensive ERT transect in Barrow, Alaska using multiple datasets acquired in the 2013-2015 period. The preliminary results show a good agreement between modeled and measured soil temperature, thaw layer thickness and electrical resistivity. The accuracy of estimated SOC content will be evaluated by comparison with measurements from soil samples along the transect. Our study presents a new surface-subsurface, deterministic-stochastic hydrogeophysical inversion approach, as well as the benefit of including multiple types of data to estimate SOC and associated hydrological-thermal dynamics.

Integrated In Situ Sensing and Modeling to Assess Carbon Dioxide Emissions from Tropical Wet Forest Soils: The Role of Leaf Cutter Ant Atta Cepholotes

NASA Astrophysics Data System (ADS)

Harmon, T. C.; Fernandez Bou, A. S.; Dierick, D.; Oberbauer, S. F.; Schwendenmann, L.; Swanson, A. C.; Zelikova, T. J.

2016-12-01

This project focuses on the role of leaf cutter ants (LCA) Atta cepholotes in carbon cycling in neotropical wet forests. LCA are abundant in these forests and workers cut and carry vegetation fragments to their nests, where symbiotic fungi break down the plant material and produce the fungal hyphae on which the ants feed. LCA are the dominant herbivores in tropical forest ecosystems, removing 10-50% of vegetation annually. Their nests can achieve large sizes, extending several meters belowground and covering 50 square meters or more of the forest floor. We monitored soil moisture, temperature, and soil CO2 concentrations continuously in nest and control sites at La Selva Biological Station, Costa Rica. Intermittently, we also assessed soil respiration and LCA nest vent fluxes. Observed soil CO2 concentrations varied markedly with soil moisture conditions, ranging from a few thousand to over 60,000 ppm(v). Accordingly, soil CO2 surface efflux varied temporally by an order of magnitude or more (typical range 0.5 to 5 mmol CO2 m-2 s-1) for the same location as a consequence of soil moisture fluctuations. LCA nest vents equivalent CO2 efflux rates (accounting for vent diameter) can be substantially greater than soil surface values, with observed values ranging from about 1 to 50 mmol m-2 s-1 (it is worth noting that correcting for vent diameters yields equivalent CO2 efflux rates greater than 1000 mmol m-2 s-1). Similar to the soil surface efflux, vent efflux varied temporally by factors of 3 or more, suggesting a potential link between the vent productivity and nest activity, moisture content of surrounding soil, and atmospheric conditions (e.g., air temperature, wind). Using a soil model (Hydrus-1D) to account for unsaturated flow, heat transfer, CO2 production and diffusive transport, we captured moisture and temperature dynamics and the order of magnitude of observed CO2 concentration. Modelled surface fluxes also agreed well with observed soil surface CO2 efflux. These results contribute to our understanding of CO2 production and transport in tropical soils, and the role played by the LCA in the soil carbon cycle.

Pushing Boreal Headwaters: Responses of Dissolved Organic Carbon to Increased Hydro-Meteorological Forcing by Forest Harvesting

NASA Astrophysics Data System (ADS)

Schelker, J.; Grabs, T. J.; Bishop, K. H.; Laudon, H.

2012-12-01

Concentrations of dissolved organic carbon (DOC) in stream water show large variations as a response to disturbances such as forestry operations. We used a paired catchment experiment in northern Sweden which shows well quantified increases of DOC concentrations and C-exports as a result of forest harvesting. To identify the drivers of these increases, a physically-based process model (Riparian Flow Integration Model, RIM) was used to inversely simulate the DOC availability in the peat-rich riparian soils of the catchments. DOC availability in soils followed a seasonal signal paralleling the seasonality of soil-temperatures (min: February; max: August) during 2005-2011. Further, high-frequency event sampling of DOC during spring and summer seasons of 2007, 2008 and 2009, respectively, revealed that event size acted as a secondary control of DOC in streams: Spring snowmelt events (as well as one major event in 2009) showed clockwise hysteresis, whereas minor runoff episodes during summer (when DOC availability in soils was highest) were characterized by a counterclockwise behavior. The higher hydro-meteorological forcing consisting of increases of soil temperature and soil moisture after the forest removal governed additional increases in DOC availability in soils. The higher DOC concentrations observed in streams after forest harvesting can therefore be ascribed to i) the increased climatic forcing comprising higher water flows through riparian soils, ii) increased soil temperatures and soil moisture, respectively, favoring an increased production of DOC, and iii) additional variation by event size. Overall these results underline the large impact of forestry operations on stream water quality as well as DOC exports leaving managed boreal forests. Simulated and measured soil water TOC concentration profiles within the three Balsjö catchments (CC-4 = clear-cut with 67% harvest; NO-5 = 35% harvest; NR-7 = northern reference). The simulated curves represent the inversely modeled soil profiles using the average f-parameter calculated for August 2009 for each catchment. Measured values represent TOC concentrations of soil water sampled in mid August 2009. Sample numbers (soil depth in bracket) are given as: n (-0.2m) = 16; n (-0.6m) = 17; n (-0.9m) = 15. Horizontal whiskers indicate the standard deviation of measured values for each soil depth.

Scaling methane oxidation: From laboratory incubation experiments to landfill cover field conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abichou, Tarek, E-mail: abichou@eng.fsu.edu; Mahieu, Koenraad; Chanton, Jeff

2011-05-15

Evaluating field-scale methane oxidation in landfill cover soils using numerical models is gaining interest in the solid waste industry as research has made it clear that methane oxidation in the field is a complex function of climatic conditions, soil type, cover design, and incoming flux of landfill gas from the waste mass. Numerical models can account for these parameters as they change with time and space under field conditions. In this study, we developed temperature, and water content correction factors for methane oxidation parameters. We also introduced a possible correction to account for the different soil structure under field conditions.more » These parameters were defined in laboratory incubation experiments performed on homogenized soil specimens and were used to predict the actual methane oxidation rates to be expected under field conditions. Water content and temperature corrections factors were obtained for the methane oxidation rate parameter to be used when modeling methane oxidation in the field. To predict in situ measured rates of methane with the model it was necessary to set the half saturation constant of methane and oxygen, K{sub m}, to 5%, approximately five times larger than laboratory measured values. We hypothesize that this discrepancy reflects differences in soil structure between homogenized soil conditions in the lab and actual aggregated soil structure in the field. When all of these correction factors were re-introduced into the oxidation module of our model, it was able to reproduce surface emissions (as measured by static flux chambers) and percent oxidation (as measured by stable isotope techniques) within the range measured in the field.« less

Analytical solutions for benchmarking cold regions subsurface water flow and energy transport models: one-dimensional soil thaw with conduction and advection

USGS Publications Warehouse

Kurylyk, Barret L.; McKenzie, Jeffrey M; MacQuarrie, Kerry T. B.; Voss, Clifford I.

2014-01-01

Numerous cold regions water flow and energy transport models have emerged in recent years. Dissimilarities often exist in their mathematical formulations and/or numerical solution techniques, but few analytical solutions exist for benchmarking flow and energy transport models that include pore water phase change. This paper presents a detailed derivation of the Lunardini solution, an approximate analytical solution for predicting soil thawing subject to conduction, advection, and phase change. Fifteen thawing scenarios are examined by considering differences in porosity, surface temperature, Darcy velocity, and initial temperature. The accuracy of the Lunardini solution is shown to be proportional to the Stefan number. The analytical solution results obtained for soil thawing scenarios with water flow and advection are compared to those obtained from the finite element model SUTRA. Three problems, two involving the Lunardini solution and one involving the classic Neumann solution, are recommended as standard benchmarks for future model development and testing.

Polynomial response of 2,4-D mineralization to temperature in soils at varying soil moisture contents, slope positions and depths.

PubMed

Shymko, Janna L; Farenhorst, Annemieke; Zvomuya, Francis

2011-01-01

The herbicide 2,4-D [2,4-(dichlorophenoxy) acetic acid] is a widely used broadleaf control agent in cereal production systems. Although 2,4-D soil-residual activity (half-lives) are typically less than 10 days, this herbicide also has as a short-term leaching potential due to its relatively weak retention by soil constituents. Herbicide residual effects and leaching are influenced by environmental variables such as soil moisture and temperature. The objective of this study was to determine impacts of these environmental variables on the magnitude and extent of 2,4-D mineralization in a cultivated undulating Manitoba prairie landscape. Microcosm incubation experiments were utilized to assess 2,4-D half-lives and total mineralization using a 4 × 4 × 3 × 2 factorial design (with soil temperature at 4 levels: 5, 10, 20 and 40°C; soil moisture at 4 levels: 60, 85, 110, 135 % of field capacity; slope position at 3 levels: upper-, mid- and lower-slopes; and soil depth at 2 levels: 0-5 cm and 5-15 cm). Half-lives (t(½)) varied from 3 days to 51 days with the total 2,4-D mineralization (M(T)) ranging from 5.8 to 50.9 %. The four-way interaction (temperature × moisture × slope × depth) significantly (p < 0.001) influenced both t(½) and M(T). Second-order polynomial equations best described the relations of temperature with t(½) and M(T) as was expected from a biological system. However, the interaction and variability of t(½) and M(T) among different temperatures, soil moistures, slope positions, and soil depth combinations indicates that the complex nature of these interacting factors should be considered when applying 2,4-D in agricultural fields and in utilizing these parameters in pesticide fate models.

Techniques for Improved Retrospective Fine-scale Meteorology

EPA Science Inventory

Pleim-Xiu Land-Surface model (PX LSM) was developed for retrospective meteorological simulations to drive chemical transport models. One of the key features of the PX LSM is the indirect soil moisture and temperature nudging. The idea is to provide a three hourly 2-m temperature ...

Characterization of Anaerobic Chemical Processes in Reservoirs: Problem Description and Conceptual Model Formulation.

DTIC Science & Technology

1981-04-01

also found that almost all the Fe in soil solution was complexed with organic mat- ter. The high degree of Fe complexing in soil solution was...range of pH, the potentials were in conformity with the theoretical slope of 0.06. 45. When a soil is submerged, soil solution concentrations of...Ponnanperuma 1972). Low temperatures lead to extensive accumula- tion of organic acids in the soil solution (International Rice Research Institute (IRRI) 1969

Future soil moisture and temperature extremes imply expanding suitability for rainfed agriculture in temperate drylands

USGS Publications Warehouse

Bradford, John B.; Schlaepfer, Daniel R.; Lauenroth, William K.; Yackulic, Charles B.; Duniway, Michael C.; Hall, Sonia A.; Jia, Gensuo; Jamiyansharav, Khishigbayar; Munson, Seth M.; Wilson, Scott D.; Tietjen, Britta

2017-01-01

The distribution of rainfed agriculture is expected to respond to climate change and human population growth. However, conditions that support rainfed agriculture are driven by interactions among climate, including climate extremes, and soil moisture availability that have not been well defined. In the temperate regions that support much of the world’s agriculture, these interactions are complicated by seasonal temperature fluctuations that can decouple climate and soil moisture. Here, we show that suitability to support rainfed agriculture can be effectively represented by the interactive effects of just two variables: suitability increases where warm conditions occur with wet soil, and suitability decreases with extreme high temperatures. 21st century projections based on ecohydrological modeling of downscaled climate forecasts imply geographic shifts and overall increases in the area suitable for rainfed agriculture in temperate regions, especially at high latitudes, and pronounced, albeit less widespread, declines in suitable areas in low latitude drylands, especially in Europe. These results quantify the integrative direct and indirect impact of rising temperatures on rainfed agriculture.

Experimental Investigation of Soil and Atmospheric Conditions on the Momentum, Mass, and Thermal Boundary Layers Above the Land Atmosphere Interface

NASA Astrophysics Data System (ADS)

Trautz, A.; Smits, K. M.; Illangasekare, T. H.; Schulte, P.

2014-12-01

The purpose of this study is to investigate the impacts of soil conditions (i.e. soil type, saturation) and atmospheric forcings (i.e. velocity, temperature, relative humidity) on the momentum, mass, and temperature boundary layers. The atmospheric conditions tested represent those typically found in semi-arid and arid climates and the soil conditions simulate the three stages of evaporation. The data generated will help identify the importance of different soil conditions and atmospheric forcings with respect to land-atmospheric interactions which will have direct implications on future numerical studies investigating the effects of turbulent air flow on evaporation. The experimental datasets generated for this study were performed using a unique climate controlled closed-circuit wind tunnel/porous media facility located at the Center for Experimental Study of Subsurface Environmental Processes (CESEP) at the Colorado School of Mines. The test apparatus consisting of a 7.3 m long porous media tank and wind tunnel, were outfitted with a sensor network to carefully measure wind velocity, air and soil temperature, relative humidity, soil moisture, and soil air pressure. Boundary layer measurements were made between the heights of 2 and 500 mm above the soil tank under constant conditions (i.e. wind velocity, temperature, relative humidity). The soil conditions (e.g. soil type, soil moisture) were varied between datasets to analyze their impact on the boundary layers. Experimental results show that the momentum boundary layer is very sensitive to the applied atmospheric conditions and soil conditions to a much less extent. Increases in velocity above porous media leads to momentum boundary layer thinning and closely reflect classical flat plate theory. The mass and thermal boundary layers are directly dependent on both atmospheric and soil conditions. Air pressure within the soil is independent of atmospheric temperature and relative humidity - wind velocity and soil moisture effects were observed. This data provides important insight into future work of accurately modeling the exchange processes associated with evaporation under various turbulent atmospheric conditions.

Carbon cycle confidence and uncertainty: Exploring variation among soil biogeochemical models

DOE PAGES

Wieder, William R.; Hartman, Melannie D.; Sulman, Benjamin N.; ...

2017-11-09

Emerging insights into factors responsible for soil organic matter stabilization and decomposition are being applied in a variety of contexts, but new tools are needed to facilitate the understanding, evaluation, and improvement of soil biogeochemical theory and models at regional to global scales. To isolate the effects of model structural uncertainty on the global distribution of soil carbon stocks and turnover times we developed a soil biogeochemical testbed that forces three different soil models with consistent climate and plant productivity inputs. The models tested here include a first-order, microbial implicit approach (CASA-CNP), and two recently developed microbially explicit models thatmore » can be run at global scales (MIMICS and CORPSE). When forced with common environmental drivers, the soil models generated similar estimates of initial soil carbon stocks (roughly 1,400 Pg C globally, 0–100 cm), but each model shows a different functional relationship between mean annual temperature and inferred turnover times. Subsequently, the models made divergent projections about the fate of these soil carbon stocks over the 20th century, with models either gaining or losing over 20 Pg C globally between 1901 and 2010. Single-forcing experiments with changed inputs, tem- perature, and moisture suggest that uncertainty associated with freeze-thaw processes as well as soil textural effects on soil carbon stabilization were larger than direct temper- ature uncertainties among models. Finally, the models generated distinct projections about the timing and magnitude of seasonal heterotrophic respiration rates, again reflecting structural uncertainties that were related to environmental sensitivities and assumptions about physicochemical stabilization of soil organic matter. Here, by providing a computationally tractable and numerically consistent framework to evaluate models we aim to better understand uncertainties among models and generate insights about fac- tors regulating the turnover of soil organic matter.« less

Carbon cycle confidence and uncertainty: Exploring variation among soil biogeochemical models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wieder, William R.; Hartman, Melannie D.; Sulman, Benjamin N.

Emerging insights into factors responsible for soil organic matter stabilization and decomposition are being applied in a variety of contexts, but new tools are needed to facilitate the understanding, evaluation, and improvement of soil biogeochemical theory and models at regional to global scales. To isolate the effects of model structural uncertainty on the global distribution of soil carbon stocks and turnover times we developed a soil biogeochemical testbed that forces three different soil models with consistent climate and plant productivity inputs. The models tested here include a first-order, microbial implicit approach (CASA-CNP), and two recently developed microbially explicit models thatmore » can be run at global scales (MIMICS and CORPSE). When forced with common environmental drivers, the soil models generated similar estimates of initial soil carbon stocks (roughly 1,400 Pg C globally, 0–100 cm), but each model shows a different functional relationship between mean annual temperature and inferred turnover times. Subsequently, the models made divergent projections about the fate of these soil carbon stocks over the 20th century, with models either gaining or losing over 20 Pg C globally between 1901 and 2010. Single-forcing experiments with changed inputs, tem- perature, and moisture suggest that uncertainty associated with freeze-thaw processes as well as soil textural effects on soil carbon stabilization were larger than direct temper- ature uncertainties among models. Finally, the models generated distinct projections about the timing and magnitude of seasonal heterotrophic respiration rates, again reflecting structural uncertainties that were related to environmental sensitivities and assumptions about physicochemical stabilization of soil organic matter. Here, by providing a computationally tractable and numerically consistent framework to evaluate models we aim to better understand uncertainties among models and generate insights about fac- tors regulating the turnover of soil organic matter.« less

Boreal Forest Permafrost Sensitivity Ecotypes to changes in Snow Depth and Soil Moisture

NASA Astrophysics Data System (ADS)

Dabbs, A.; Romanovsky, V. E.; Kholodov, A. L.

2017-12-01

Changes in the global climate, pronounced especially in polar regions due to their accelerated warming, are expected by many global climate models to have large impacts on the moisture budget throughout the world. Permafrost extent and the soil temperature regime are both strongly dependent on soil moisture and snow depth because of their immense effects on the thermal properties of the soil column and surface energy balance respectively. To assess how the ground thermal regime at various ecotypes may react to a change in the moisture budget, we performed a sensitivity analysis using the Geophysical Institute Permafrost Laboratory model, which simulates subsurface temperature dynamics by solving a one-dimensional nonlinear heat equation with phase change. We used snow depth and air temperature data from the Fairbanks International Airport meteorological station as forcing for this sensitivity analysis. We looked at five different ecotypes within the boreal forest region of Alaska: mixed, deciduous and black forests, willow shrubs and tundra. As a result of this analysis, we found that ecotypes with higher soil moisture contents, such as willow shrubs, are most sensitive to changes in snow depth due to the larger amount of latent heat trapped underneath the snow during the freeze up of active layer. In addition, soil within these ecotypes has higher thermal conductivity due to high saturation degree allowing for deeper seasonal freezing. Also, we found that permafrost temperatures were most sensitive to changes in soil moisture in ecotypes that were not completely saturated such as boreal forest. These ecotypes lacked complete saturation because of thick organic layers that have very high porosities or partially drained mineral soils. Contrarily, tundra had very little response to changes in soil moisture due to its thin organic layer and almost completely saturated soil column. This difference arises due to the disparity between the frozen and unfrozen thermal conductivities of the soil. In highly saturated soils, the frozen thermal conductivity of the soil can be more than double that of the unfrozen thermal conductivity while in dryer soils that ratio reduces down to less than 1.5. This difference allows the seasonal freezing to penetrate quicker and deeper causing even more latent heat to be released and trapped.

Estimating Thermal Inertia with a Maximum Entropy Boundary Condition

NASA Astrophysics Data System (ADS)

Nearing, G.; Moran, M. S.; Scott, R.; Ponce-Campos, G.

2012-04-01

Thermal inertia, P [Jm-2s-1/2K-1], is a physical property the land surface which determines resistance to temperature change under seasonal or diurnal heating. It is a function of volumetric heat capacity, c [Jm-3K-1], and thermal conductivity, k [Wm-1K-1] of the soil near the surface: P=√ck. Thermal inertia of soil varies with moisture content due the difference between thermal properties of water and air, and a number of studies have demonstrated that it is feasible to estimate soil moisture given thermal inertia (e.g. Lu et al, 2009, Murray and Verhoef, 2007). We take the common approach to estimating thermal inertia using measurements of surface temperature by modeling the Earth's surface as a 1-dimensional homogeneous diffusive half-space. In this case, surface temperature is a function of the ground heat flux (G) boundary condition and thermal inertia and a daily value of P was estimated by matching measured and modeled diurnal surface temperature fluctuations. The difficulty is in measuring G; we demonstrate that the new maximum entropy production (MEP) method for partitioning net radiation into surface energy fluxes (Wang and Bras, 2011) provides a suitable boundary condition for estimating P. Adding the diffusion representation of heat transfer in the soil reduces the number of free parameters in the MEP model from two to one, and we provided a sensitivity analysis which suggests that, for the purpose of estimating P, it is preferable to parameterize the coupled MEP-diffusion model by the ratio of thermal inertia of the soil to the effective thermal inertia of convective heat transfer to the atmosphere. We used this technique to estimate thermal inertia at two semiarid, non-vegetated locations in the Walnut Gulch Experimental Watershed in southeast AZ, USA and compared these estimates to estimates of P made using the Xue and Cracknell (1995) solution for a linearized ground heat flux boundary condition, and we found that the MEP-diffusion model produced superior thermal inertia estimates. The MEP-diffusion estimates also agreed well with P estimates made using a boundary condition measured with buried flux plates. We further demonstrated the new method using diurnal surface temperature fluctuations estimated from day/night MODIS image pairs and, excluding instances where the soil was extremely dry, found a strong relationship between estimated thermal inertia and measured 5 cm soil moisture. Lu, S., Ju, Z.Q., Ren, T.S. & Horton, R. (2009). A general approach to estimate soil water content from thermal inertia. Agricultural and Forest Meteorology, 149, 1693-1698. Murray, T. & Verhoef, A. (2007). Moving towards a more mechanistic approach in the determination of soil heat flux from remote measurements - I. A universal approach to calculate thermal inertia. Agricultural and Forest Meteorology, 147, 80-87. Wang, J.F. & Bras, R.L. (2011). A model of evapotranspiration based on the theory of maximum entropy production. Water Resources Research, 47. Xue, Y. & Cracknell, A.P. (1995). Advanced thermal inertia modeling. International Journal of Remote Sensing, 16, 431-446.

Remote monitoring of soil moisture using airborne microwave radiometers

NASA Technical Reports Server (NTRS)

Kroll, C. L.

1973-01-01

The current status of microwave radiometry is provided. The fundamentals of the microwave radiometer are reviewed with particular reference to airborne operations, and the interpretative procedures normally used for the modeling of the apparent temperature are presented. Airborne microwave radiometer measurements were made over selected flight lines in Chickasha, Oklahoma and Weslaco, Texas. Extensive ground measurements of soil moisture were made in support of the aircraft mission over the two locations. In addition, laboratory determination of the complex permittivities of soil samples taken from the flight lines were made with varying moisture contents. The data were analyzed to determine the degree of correlation between measured apparent temperatures and soil moisture content.

Calibration and temperature correction of heat dissipation matric potential sensors

USGS Publications Warehouse

Flint, A.L.; Campbell, G.S.; Ellett, K.M.; Calissendorff, C.

2002-01-01

This paper describes how heat dissipation sensors, used to measure soil water matric potential, were analyzed to develop a normalized calibration equation and a temperature correction method. Inference of soil matric potential depends on a correlation between the variable thermal conductance of the sensor's porous ceramic and matric poten-tial. Although this correlation varies among sensors, we demonstrate a normalizing procedure that produces a single calibration relationship. Using sensors from three sources and different calibration methods, the normalized calibration resulted in a mean absolute error of 23% over a matric potential range of -0.01 to -35 MPa. Because the thermal conductivity of variably saturated porous media is temperature dependent, a temperature correction is required for application of heat dissipation sensors in field soils. A temperature correction procedure is outlined that reduces temperature dependent errors by 10 times, which reduces the matric potential measurement errors by more than 30%. The temperature dependence is well described by a thermal conductivity model that allows for the correction of measurements at any temperature to measurements at the calibration temperature.

Soil temperature synchronisation improves estimation of daily variation of ecosystem respiration in Sphagnum peatlands

NASA Astrophysics Data System (ADS)

D'Angelo, Benoît; Gogo, Sébastien; Le Moing, Franck; Jégou, Fabrice; Guimbaud, Christophe; Laggoun, Fatima

2015-04-01

Ecosystem respiration (ER) is a key process in the global C cycle and thus, plays an important role in the climate regulation. Peatlands contain a third of the world soil C in spite of their relatively low global area (3% of land area). Although these ecosystems represent potentially a significant source of C under global change, they are still not taken into account accordingly in global climatic models. Therefore, ER variations have to be accounted for, especially by estimating its dependence to temperature.s The relationship between ER and temperature often relies only on one soil temperature depth and the latter is generally taken in the first 10 centimetres. Previous studies showed that the temperature dependence of ER depends on the depth at which the temperature is recorded. The depth selection for temperature measurement is thus a predominant issue. A way to deal with this is to analyse the time-delay between ER and temperature. The aim of this work is to assess whether using synchronised data in models leads to a better ER daily variation estimation than using non-synchronised data. ER measurements were undertaken in 2013 in 4 Sphagnum peatlands across France: La Guette (N 47°19'44', E 2°17'04', 154m) in July, Landemarais (N 48°26'30', E -1°10'54', 145m) in August, Frasne (N 46°49'35', E 6°10'20', 836m) in September, and Bernadouze (N 42°48'09', E 1°25'24', 1500m) in October. A closed method chamber was used to measure ER hourly during 72 hours in each of the 4 replicates installed in each site. Average ER ranged from 1.75 μmol m-2 s-1 to 6.13 μmol m-2 s-1. A weather station was used to record meteorological data and soil temperature profiles (5, 10, 20 and 30 cm). Synchronised data were determined for each depth by selecting the time-delay leading to the best correlation between ER and soil temperature. The data were used to simulate ER according to commonly used equations: linear, exponential with Q10, Arrhenius, Lloyd and Taylor. Models comparison was performed using RMSE (goodness-of-fit) and AIC (goodness-of-fit and model complexity) as indicators to assess their relative quality. Both indicators showed a wide variation between sites. However, for each site differences between synchronised and non-synchronised data were larger than the differences between models equations. According to the AIC, models using synchronised data produced better ER estimations than models using non-synchronised data, at all depth. RMSE support this result for all sites for superficial peat layer. In some locations, mainly Frasne, synchronised data at 5 cm depth provide better estimation than air temperature, i.e. 25.0 vs. 26.4 for RMSE and 337.1 vs. 379.8 for AIC, respectively. The equation of the most appropriate model varies between sites, but the differences between them are small. At a daily scale, data synchronisation in Sphagnum peatlands improves ER estimation regardless of the model used. Moreover, to estimate ER flux, the use of synchronised data at 5 cm depth seems the most adequate method.

Thermal adaptation of decomposer communities in warming soils

PubMed Central

Bradford, Mark A.

2013-01-01

Temperature regulates the rate of biogeochemical cycles. One way it does so is through control of microbial metabolism. Warming effects on metabolism change with time as physiology adjusts to the new temperature. I here propose that such thermal adaptation is observed in soil microbial respiration and growth, as the result of universal evolutionary trade-offs between the structure and function of both enzymes and membranes. I review the basis for these trade-offs and show that they, like substrate depletion, are plausible mechanisms explaining soil respiration responses to warming. I argue that controversies over whether soil microbes adapt to warming stem from disregarding the evolutionary physiology of cellular metabolism, and confusion arising from the term thermal acclimation to represent phenomena at the organism- and ecosystem-levels with different underlying mechanisms. Measurable physiological adjustments of the soil microbial biomass reflect shifts from colder- to warmer-adapted taxa. Hypothesized declines in the growth efficiency of soil microbial biomass under warming are controversial given limited data and a weak theoretical basis. I suggest that energy spilling (aka waste metabolism) is a more plausible mechanism for efficiency declines than the commonly invoked increase in maintenance-energy demands. Energy spilling has many fitness benefits for microbes and its response to climate warming is uncertain. Modeled responses of soil carbon to warming are sensitive to microbial growth efficiency, but declines in efficiency mitigate warming-induced carbon losses in microbial models and exacerbate them in conventional models. Both modeling structures assume that microbes regulate soil carbon turnover, highlighting the need for a third structure where microbes are not regulators. I conclude that microbial physiology must be considered if we are to have confidence in projected feedbacks between soil carbon stocks, atmospheric CO2, and climate change. PMID:24339821

Soil temperature and water content drive microbial carbon fixation in grassland of permafrost area on the Tibetan plateau

NASA Astrophysics Data System (ADS)

Kong, W.; Guo, G.; Liu, J.

2014-12-01

Soil microbial communities underpin terrestrial biogeochemical cycles and are greatly influenced by global warming and global-warming-induced dryness. However, the response of soil microbial community function to global change remains largely uncertain, particularly in the ecologically vulnerable Tibetan plateau permafrost area with large carbon storage. With the concept of space for time substitution, we investigated the responses of soil CO2-fixing microbial community and its enzyme activity to climate change along an elevation gradient (4400-5100 m) of alpine grassland on the central Tibetan plateau. The elevation gradient in a south-facing hill slope leads to variation in climate and soil physicochemical parameters. The autotrophic microbial communities were characterized by quantitative PCR (qPCR), terminal restriction fragment length polymorphism analysis (T-RFLP) and cloning/sequencing targeting the CO2-fixing gene (RubisCO). The results demonstrated that the autotrophic microbial community abundance, structure and its enzyme activity were mainly driven by soil temperature and water content. Soil temperature increase and water decrease dramatically reduced the abundance of the outnumbered form IC RubisCO-containing microbes, and significantly changed the structure of form IC, IAB and ID RubisCO-containing microbial community. Structural equation model revealed that the RubisCO enzyme was directly derived from RubisCO-containing microbes and its activity was significantly reduced by soil temperature increase and water content decrease. Thus our results provide a novel positive feedback loop of climate warming and warming-induced dryness by that soil microbial carbon fixing potential will reduce by 3.77%-8.86% with the soil temperature increase of 1.94oC and water content decrease of 60%-70%. This positive feedback could be capable of amplifying the climate change given the significant contribution of soil microbial CO2-fixing up to 4.9% of total soil organic carbon.

Temperature and aridity regulate spatial variability of soil multifunctionality in drylands across the globe.

PubMed

Durán, Jorge; Delgado-Baquerizo, Manuel; Dougill, Andrew J; Guuroh, Reginald T; Linstädter, Anja; Thomas, Andrew D; Maestre, Fernando T

2018-05-01

The relationship between the spatial variability of soil multifunctionality (i.e., the capacity of soils to conduct multiple functions; SVM) and major climatic drivers, such as temperature and aridity, has never been assessed globally in terrestrial ecosystems. We surveyed 236 dryland ecosystems from six continents to evaluate the relative importance of aridity and mean annual temperature, and of other abiotic (e.g., texture) and biotic (e.g., plant cover) variables as drivers of SVM, calculated as the averaged coefficient of variation for multiple soil variables linked to nutrient stocks and cycling. We found that increases in temperature and aridity were globally correlated to increases in SVM. Some of these climatic effects on SVM were direct, but others were indirectly driven through reductions in the number of vegetation patches and increases in soil sand content. The predictive capacity of our structural equation modelling was clearly higher for the spatial variability of N- than for C- and P-related soil variables. In the case of N cycling, the effects of temperature and aridity were both direct and indirect via changes in soil properties. For C and P, the effect of climate was mainly indirect via changes in plant attributes. These results suggest that future changes in climate may decouple the spatial availability of these elements for plants and microbes in dryland soils. Our findings significantly advance our understanding of the patterns and mechanisms driving SVM in drylands across the globe, which is critical for predicting changes in ecosystem functioning in response to climate change. © 2018 by the Ecological Society of America.

Soil moisture, dielectric permittivity and emissivity of soil: effective depth of emission measured by the L-band radiometer ELBARA

NASA Astrophysics Data System (ADS)

Usowicz, Boguslaw; Lukowski, Mateusz; Marczewski, Wojciech; Usowicz, Jerzy; Lipiec, Jerzy; Rojek, Edyta; Slominska, Ewa; Slominski, Jan

2014-05-01

Due to the large variation of soil moisture in space and in time, obtaining soil water balance with an aid of data acquired from the surface is still a challenge. Microwave remote sensing is widely used to determine the water content in soil. It is based on the fact that the dielectric constant of the soil is strongly dependent on its water content. This method provides the data in both local and global scales. Very important issue that is still not solved, is the soil depth at which radiometer "sees" the incoming radiation and how this "depth of view" depends on water content and physical properties of soil. The microwave emission comes from its entire profile, but much of this energy is absorbed by the upper layers of soil. As a result, the contribution of each layer to radiation visible for radiometer decreases with depth. The thickness of the surface layer, which significantly contributes to the energy measured by the radiometer is defined as the "penetration depth". In order to improve the physical base of the methodology of soil moisture measurements using microwave remote sensing and to determine the effective emission depth seen by the radiometer, a new algorithm was developed. This algorithm determines the reflectance coefficient from Fresnel equations, and, what is new, the complex dielectric constant of the soil, calculated from the Usowicz's statistical-physical model (S-PM) of dielectric permittivity and conductivity of soil. The model is expressed in terms of electrical resistance and capacity. The unit volume of soil in the model consists of solid, water and air, and is treated as a system made up of spheres, filling volume by overlapping layers. It was assumed that connections between layers and spheres in the layer are represented by serial and parallel connections of "resistors" and "capacitors". The emissivity of the soil surface is calculated from the ratio between the brightness temperature measured by the ELBARA radiometer (GAMMA Remote Sensing AG) and the physical temperature of the soil surface measured by infrared sensor. As the input data for S-PM: volumes of soil components, mineralogical composition, organic matter content, specific surface area and bulk density of the soil were used. Water contents in the model are iteratively changed, until emissivities calculated from the S-PM reach the best agreement with emissivities measured by the radiometer. Final water content will correspond to the soil moisture measured by the radiometer. Then, the examined soil profile will be virtually divided into thin slices where moisture, temperature and thermal properties will be measured and simultaneously modelled via S-PM. In the next step, the slices will be "added" starting from top (soil surface), until the effective soil moisture will be equal to the soil moisture measured by ELBARA. The thickness of obtained stack will be equal to desired "penetration depth". Moreover, it will be verified further by measuring the moisture content using thermal inertia. The work was partially funded by the Government of Poland through an ESA Contract under the PECS ELBARA_PD project No. 4000107897/13/NL/KML.

Why is SMOS Drier than the South Fork In-situ Soil Moisture Network?

NASA Astrophysics Data System (ADS)

Walker, V. A.; Hornbuckle, B. K.; Cosh, M. H.

2014-12-01

Global maps of near-surface soil moisture are currently being produced by the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) satellite mission at 40 km. Within the next few months NASA's Soil Moisture Active Passive (SMAP) satellite mission will begin producing observations of near-surface soil moisture at 10 km. Near-surface soil moisture is the water content of the first 3 to 5 cm of the soil. Observations of near-surface soil moisture are expected to improve weather and climate forecasts. These satellite observations must be validated. We define validation as determining the space/time statistical characteristics of the uncertainty. A standard that has been used for satellite validation is in-situ measurements of near-surface soil moisture made with a network of sensors spanning the extent of a satellite footprint. Such a network of sensors has been established in the South Fork of the Iowa River in Central Iowa by the USDA ARS. Our analysis of data in 2013 indicates that SMOS has a dry bias: SMOS near-surface soil moisture is between 0.05 to 0.10 m^3m^{-3} lower than what is observed by the South Fork network. A dry bias in SMOS observations has also been observed in other regions of North America. There are many possible explanations for this difference: underestimation of vegetation, or soil surface roughness; undetected radio frequency interference (RFI); a retrieval model that is not appropriate for agricultural areas; or the use of an incorrect surface temperature in the retrieval process. We will begin our investigation by testing this last possibility: that SMOS is using a surface temperature that is too low which results in a drier soil moisture that compensates for this error. We will present a comparison of surface temperatures from the European Center for Medium-range Weather Forecasting (ECMWF) used to retrieve near-surface soil moisture from SMOS measurements of brightness temperature, and surface temperatures in the South Fork obtained from both tower and in-situ sensors. We will also use a long-term data set of tower and in-situ sensors collected in agricultural fields to develop a relationship between air temperature and the surface temperature relevant to the terrestrial microwave emission that is detected by SMOS.

A model for nematode locomotion in soil

USGS Publications Warehouse

Hunt, H. William; Wall, Diana H.; DeCrappeo, Nicole; Brenner, John S.

2001-01-01

Locomotion of nematodes in soil is important for both practical and theoretical reasons. We constructed a model for rate of locomotion. The first model component is a simple simulation of nematode movement among finite cells by both random and directed behaviours. Optimisation procedures were used to fit the simulation output to data from published experiments on movement along columns of soil or washed sand, and thus to estimate the values of the model's movement coefficients. The coefficients then provided an objective means to compare rates of locomotion among studies done under different experimental conditions. The second component of the model is an equation to predict the movement coefficients as a function of controlling factors that have been addressed experimentally: soil texture, bulk density, water potential, temperature, trophic group of nematode, presence of an attractant or physical gradient and the duration of the experiment. Parameters of the equation were estimated by optimisation to achieve a good fit to the estimated movement coefficients. Bulk density, which has been reported in a minority of published studies, is predicted to have an important effect on rate of locomotion, at least in fine-textured soils. Soil sieving, which appears to be a universal practice in laboratory studies of nematode movement, is predicted to negatively affect locomotion. Slower movement in finer textured soils would be expected to increase isolation among local populations, and thus to promote species richness. Future additions to the model that might improve its utility include representing heterogeneity within populations in rate of movement, development of gradients of chemical attractants, trade-offs between random and directed components of movement, species differences in optimal temperature and water potential, and interactions among factors controlling locomotion.

Simulating N2O emissions under different tillage systems of irrigated corn using RZ-Shaw model

USDA-ARS?s Scientific Manuscript database

Nitrous oxide (N2O) is potent greenhouse gas (GHG) and agriculture is a global source of N2O emissions from soil fertility management. Yet emissions vary by agronomic practices and environmental factors that govern soil moisture and temperature. Ecosystem models are important tools to estimate N2O e...

Boreal soil carbon dynamics under a changing climate: a model inversion approach

Treesearch

Zhaosheng Fan; Jason C. Neff; Jennifer W. Harden; Kimberly P. Wickland

2008-01-01

Several fundamental but important factors controlling the feedback of boreal organic carbon (OC) to climate change were examined using a mechanistic model of soil OC dynamics, including the combined effects of temperature and moisture on the decomposition of OC and the factors controlling carbon quality and decomposition with depth. To estimate decomposition rates and...

A simplified, data-constrained approach to estimate the permafrost carbon–climate feedback

DOE PAGES

Koven, C. D.; Schuur, E. A. G.; Schadel, C.; ...

2015-10-05

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation–Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soilmore » temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2–33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9–112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of –14 to –19 Pg C °C–1 on a 100 year time scale. For CH 4 emissions, our approach assumes a fixed saturated area and that increases in CH 4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH 4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10–18%. In conclusion, the simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming.« less

Application of soil block without burning process and calcium silicate panels as building wall in mountainous area

NASA Astrophysics Data System (ADS)

Noerwasito, Vincentius Totok; Nasution, Tanti Satriana Rosary

2017-11-01

Utilization of local building materials in a residential location in mountainous area is very important, considering local material as a low-energy building material because of low transport energy. The local building materials used in this study are walls made from soil blocks. The material was made by the surrounding community from compacted soil without burning process. To maximize the potential of soil block to the outdoor temperature in the mountains, it is necessary to add non-local building materials as an insulator from the influence of the outside air. The insulator was calcium silicate panel. The location of the research is Trawas sub-district, Mojokerto regency, which is a mountainous area. The research problem is on applying the composition of local materials and calcium silicate panels that it will be able to meet the requirements as a wall building material and finding to what extent the impact of the wall against indoor temperature. The result from this research was the application of soil block walls insulated by calcium silicate panels in a building model. Besides, because of the utilization of those materials, the building has a specific difference between indoor and outdoor temperature. Thus, this model can be applied in mountainous areas in Indonesia.

SMAP Level 4 Surface and Root Zone Soil Moisture

NASA Technical Reports Server (NTRS)

Reichle, R.; De Lannoy, G.; Liu, Q.; Ardizzone, J.; Kimball, J.; Koster, R.

2017-01-01

The SMAP Level 4 soil moisture (L4_SM) product provides global estimates of surface and root zone soil moisture, along with other land surface variables and their error estimates. These estimates are obtained through assimilation of SMAP brightness temperature observations into the Goddard Earth Observing System (GEOS-5) land surface model. The L4_SM product is provided at 9 km spatial and 3-hourly temporal resolution and with about 2.5 day latency. The soil moisture and temperature estimates in the L4_SM product are validated against in situ observations. The L4_SM product meets the required target uncertainty of 0.04 m(exp. 3)m(exp. -3), measured in terms of unbiased root-mean-square-error, for both surface and root zone soil moisture.

Responses of ecosystem carbon cycling to climate change treatments along an elevation gradient

USGS Publications Warehouse

Wu, Zhuoting; Koch, George W.; Dijkstra, Paul; Bowker, Matthew A.; Hungate, Bruce A.

2011-01-01

Global temperature increases and precipitation changes are both expected to alter ecosystem carbon (C) cycling. We tested responses of ecosystem C cycling to simulated climate change using field manipulations of temperature and precipitation across a range of grass-dominated ecosystems along an elevation gradient in northern Arizona. In 2002, we transplanted intact plant–soil mesocosms to simulate warming and used passive interceptors and collectors to manipulate precipitation. We measured daytime ecosystem respiration (ER) and net ecosystem C exchange throughout the growing season in 2008 and 2009. Warming generally stimulated ER and photosynthesis, but had variable effects on daytime net C exchange. Increased precipitation stimulated ecosystem C cycling only in the driest ecosystem at the lowest elevation, whereas decreased precipitation showed no effects on ecosystem C cycling across all ecosystems. No significant interaction between temperature and precipitation treatments was observed. Structural equation modeling revealed that in the wetter-than-average year of 2008, changes in ecosystem C cycling were more strongly affected by warming-induced reduction in soil moisture than by altered precipitation. In contrast, during the drier year of 2009, warming induced increase in soil temperature rather than changes in soil moisture determined ecosystem C cycling. Our findings suggest that warming exerted the strongest influence on ecosystem C cycling in both years, by modulating soil moisture in the wet year and soil temperature in the dry year.

Coupled land surface-subsurface hydrogeophysical inverse modeling to estimate soil organic carbon content and explore associated hydrological and thermal dynamics in the Arctic tundra

NASA Astrophysics Data System (ADS)

Phuong Tran, Anh; Dafflon, Baptiste; Hubbard, Susan S.

2017-09-01

Quantitative characterization of soil organic carbon (OC) content is essential due to its significant impacts on surface-subsurface hydrological-thermal processes and microbial decomposition of OC, which both in turn are important for predicting carbon-climate feedbacks. While such quantification is particularly important in the vulnerable organic-rich Arctic region, it is challenging to achieve due to the general limitations of conventional core sampling and analysis methods, and to the extremely dynamic nature of hydrological-thermal processes associated with annual freeze-thaw events. In this study, we develop and test an inversion scheme that can flexibly use single or multiple datasets - including soil liquid water content, temperature and electrical resistivity tomography (ERT) data - to estimate the vertical distribution of OC content. Our approach relies on the fact that OC content strongly influences soil hydrological-thermal parameters and, therefore, indirectly controls the spatiotemporal dynamics of soil liquid water content, temperature and their correlated electrical resistivity. We employ the Community Land Model to simulate nonisothermal surface-subsurface hydrological dynamics from the bedrock to the top of canopy, with consideration of land surface processes (e.g., solar radiation balance, evapotranspiration, snow accumulation and melting) and ice-liquid water phase transitions. For inversion, we combine a deterministic and an adaptive Markov chain Monte Carlo (MCMC) optimization algorithm to estimate a posteriori distributions of desired model parameters. For hydrological-thermal-to-geophysical variable transformation, the simulated subsurface temperature, liquid water content and ice content are explicitly linked to soil electrical resistivity via petrophysical and geophysical models. We validate the developed scheme using different numerical experiments and evaluate the influence of measurement errors and benefit of joint inversion on the estimation of OC and other parameters. We also quantify the propagation of uncertainty from the estimated parameters to prediction of hydrological-thermal responses. We find that, compared to inversion of single dataset (temperature, liquid water content or apparent resistivity), joint inversion of these datasets significantly reduces parameter uncertainty. We find that the joint inversion approach is able to estimate OC and sand content within the shallow active layer (top 0.3 m of soil) with high reliability. Due to the small variations of temperature and moisture within the shallow permafrost (here at about 0.6 m depth), the approach is unable to estimate OC with confidence. However, if the soil porosity is functionally related to the OC and mineral content, which is often observed in organic-rich Arctic soil, the uncertainty of OC estimate at this depth remarkably decreases. Our study documents the value of the new surface-subsurface, deterministic-stochastic inversion approach, as well as the benefit of including multiple types of data to estimate OC and associated hydrological-thermal dynamics.

Moisture Limitations Dominate the Seasonality of Heterotrophic Respiration in the Southern Hemisphere

NASA Astrophysics Data System (ADS)

Konings, A. G.; Bloom, A. A.; Liu, J.; Parazoo, N.; Schimel, D.; Bowman, K. W.

2016-12-01

Heterotrophic respiration is the dominant process causing the loss of soil organic carbon, the largest stock of carbon on earth. Temperature, soil moisture, substrate availability, and soil microbial composition can all affect the rate of heterotrophic respiration. Without isotopic or root-specific measurements, it can be difficult to separate the total soil respiration into autotrophic and heterotrophic respiration. As a result, the large-scale variability and seasonality of heterotrophic respiration remains unknown, especially outside the mid-latitudes. In this study, we use remote-sensing based observational constraints to estimate heterotrophic respiration at large scales. We combine net ecosystem exchange estimates from atmospheric inversions of the Carbon Monitoring System-Flux project (CMS-Flux) with a recently derived optimally-scaled GPP dataset based on satellite-observed solar-induced fluorescence variations to estimate total ecosystem respiration. The ecosystem respiration is then separated into autotrophic and heterotrophic components based on a spatially-varying carbon use efficiency retrieved in a model-data fusion framework (CARDAMOM). The three datasets are combined into a Bayesian framework to derive the uncertainty distribution of global heterotrophic respiration allowing only physically realistic solutions (appropriate signs for all fluxes), In most Southern Hemisphere regions where precipitation and temperature are anti-correlated (e.g. dry African woodlands, Sahel, Southern India, etc..), the seasonality of heterotrophic respiration follows precipitation, not temperature. This results in an apparent anti-correlation between heterotrophic respiration and temperature. By comparison, a data-constrained terrestrial ecosystem model that does not simulate an effect of soil moisture on heterotrophic respiration did not show this anti-correlation. Data-driven heterotrophic respiration estimates such as those presented here may be used to benchmark model predictions of heterotrophic respiration in the future.

Two-dimensional microclimate distribution within and above a crop canopy in an arid environment: Modeling and observational studies

NASA Astrophysics Data System (ADS)

Naot, O.; Mahrer, Y.

1991-08-01

A numerical two-dimensional model based on higher-order closure assumptions is developed to simulate the horizontal microclimate distribution over an irrigated field in arid surroundings. The model considers heat, mass, momentum, and radiative fluxes in the soil-plant-atmosphere system. Its vertical domain extends through the whole planetary boundary layer. The model requires temporal solar and atmospheric radiation data, as well as temporal boundary conditions for wind-speed, air temperature, and humidity. These boundary conditions are specified by an auxiliary mesoscale model and are incorporated in the microscale model by a nudging method. Vegetation parameters (canopy height, leaf-angle orientation distribution, leaf-area index, photometric properties, root-density distribution), soil texture, and soil-hydraulic and photometric properties are considered. The model is tested using meteorological data obtained in a drip-irrigated cotton field located in an extremely arid area, where strong fetch effects are expected. Four masts located 50 m before the leading edge of the field and 10, 30, and 100 m inward from the leading edge are used to measure various meteorological parameters and their horizontal and vertical gradients. Calculated values of air and soil temperatures, wind-speed, net radiation and soil, latent, and sensible heat fluxes agreed well with measurements. Large horizontal gradients of air temperature are both observed and measured within the canopy in the first 40 m of the leading edge. Rate of evapotranspiration at both the upwind and the downwind edges of the field are higher by more than 15% of the midfield value. Model calculations show that a stable thermal stratification is maintained above the whole field for 24 h. The aerodynamic and thermal internal boundary layer (IBL) growth is proportional to the square root of the fetch. This is also the observed rate of growth of the thermal IBL over a cool sea surface.

On the appropriate definition of soil profile configuration and initial conditions for land surface-hydrology models in cold regions

NASA Astrophysics Data System (ADS)

Sapriza-Azuri, Gonzalo; Gamazo, Pablo; Razavi, Saman; Wheater, Howard S.

2018-06-01

Arctic and subarctic regions are amongst the most susceptible regions on Earth to global warming and climate change. Understanding and predicting the impact of climate change in these regions require a proper process representation of the interactions between climate, carbon cycle, and hydrology in Earth system models. This study focuses on land surface models (LSMs) that represent the lower boundary condition of general circulation models (GCMs) and regional climate models (RCMs), which simulate climate change evolution at the global and regional scales, respectively. LSMs typically utilize a standard soil configuration with a depth of no more than 4 m, whereas for cold, permafrost regions, field experiments show that attention to deep soil profiles is needed to understand and close the water and energy balances, which are tightly coupled through the phase change. To address this gap, we design and run a series of model experiments with a one-dimensional LSM, called CLASS (Canadian Land Surface Scheme), as embedded in the MESH (Modélisation Environmentale Communautaire - Surface and Hydrology) modelling system, to (1) characterize the effect of soil profile depth under different climate conditions and in the presence of parameter uncertainty; (2) assess the effect of including or excluding the geothermal flux in the LSM at the bottom of the soil column; and (3) develop a methodology for temperature profile initialization in permafrost regions, where the system has an extended memory, by the use of paleo-records and bootstrapping. Our study area is in Norman Wells, Northwest Territories of Canada, where measurements of soil temperature profiles and historical reconstructed climate data are available. Our results demonstrate a dominant role for parameter uncertainty, that is often neglected in LSMs. Considering such high sensitivity to parameter values and dependency on the climate condition, we show that a minimum depth of 20 m is essential to adequately represent the temperature dynamics. We further show that our proposed initialization procedure is effective and robust to uncertainty in paleo-climate reconstructions and that more than 300 years of reconstructed climate time series are needed for proper model initialization.

The role of organo-mineral interactions on the capacity of soils to store carbon

NASA Astrophysics Data System (ADS)

Georgiou, K.; Abramoff, R. Z.; Riley, W. J.; Torn, M. S.

2017-12-01

Observed patterns of soil organic carbon (SOC) content across geochemical regimes are signatures of process and provide opportunities to understand the underlying decomposition and stabilization mechanisms that can guide their representation in models. The type of sorption equation used in soil decomposition models has large implications for both SOC stock and its temperature sensitivity. Here we compared different model formulations of SOC sorption to mineral surfaces, motivated by the myriad of chemical associations between organic and mineral surfaces, and used laboratory and field incubations to inform model parameters. We explored linear, Langmuir, and Freundlich adsorption models, where the latter emerges from heterogeneous compositions of substrate and surface components. We show the effect of model representations on predicted trends of SOC as a function of mineralogy and discuss the role of soil C saturation on emergent patterns. Specifically, our results highlight that the response of mineral-associated (`protected') SOC to changes in plant C inputs depends greatly on the C saturation deficit of the soil and thus, the representation of organo-mineral interactions in models can lead to nonlinear steady-state responses in protected SOC. We also find that, consistent with field experiments, the trend in protected SOC and mineral C saturation capacity is linear, but, interestingly, the slope depends on the degree of C saturation. We contend that this latter finding is an important consideration for field studies that did not find a universal slope and interpreted this as an inability of mineralogy to explain observed patterns. Our results also suggest that warming affects this slope, with higher temperatures causing a decrease in the amount of protected C for a given saturation capacity and C input rate. This means that more C inputs will be needed to keep the same amount of protected C at higher temperatures. Organo-mineral interactions play a key role in governing soil C stabilization and long-term storage, and thus, improving their representation for inclusion in Earth system models is crucial for understanding and predicting feedbacks under global change.

DasPy 1.0 - the Open Source Multivariate Land Data Assimilation Framework in combination with the Community Land Model 4.5

NASA Astrophysics Data System (ADS)

Han, X.; Li, X.; He, G.; Kumbhar, P.; Montzka, C.; Kollet, S.; Miyoshi, T.; Rosolem, R.; Zhang, Y.; Vereecken, H.; Franssen, H.-J. H.

2015-08-01

Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. Multivariate data assimilation refers to the simultaneous assimilation of observation data from multiple model state variables into a simulation model. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. We developed an open source multivariate land data assimilation framework (DasPy) which is implemented using the Python script language mixed with the C++ and Fortran programming languages. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be introduced by perturbed atmospheric forcing data, and represented by perturbed soil and vegetation parameters and model initial conditions. The Community Land Model (CLM) was integrated as the model operator. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. The Community Microwave Emission Modelling platform (CMEM), COsmic-ray Soil Moisture Interaction Code (COSMIC) and the Two-Source Formulation (TSF) were integrated as observation operators for the assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy has been evaluated in several assimilation studies of neutron count intensity (soil moisture), L-band brightness temperature and land surface temperature. DasPy is parallelized using the hybrid Message Passing Interface and Open Multi-Processing techniques. All the input and output data flows are organized efficiently using the commonly used NetCDF file format. Online 1-D and 2-D visualization of data assimilation results is also implemented to facilitate the post simulation analysis. In summary, DasPy is a ready to use open source parallel multivariate land data assimilation framework.

Psychrotolerant bacteria for remediation of oil-contaminated soils in the Arctic

NASA Astrophysics Data System (ADS)

Svarovskaya, L. I.; Altunina, L. K.

2017-12-01

Samples of oil-contaminated peat soil are collected in the region of the Barents Sea in Arctic Kolguyev Island. A model experiment on biodegradation of polluting hydrocarbons by natural microflora exhibiting psychrophilic properties is carried out at +10°C. The geochemical activity of pure hydrocarbon-oxidizing Acinetobacter, Pseudomonas, Bacillus and Rhodococcus cultures isolated from the soil is studied at a lower temperature. The concentration of soil contamination is determined within the range 18-57 g/kg. The biodegradation of oil by natural microflora is 60% under the conditions of a model experiment.

Soil Carbon and Nitrogen Cycle Modeling

NASA Astrophysics Data System (ADS)

Woo, D.; Chaoka, S.; Kumar, P.; Quijano, J. C.

2012-12-01

Second generation bioenergy crops, such as miscanthus (Miscantus × giganteus) and switchgrass (Panicum virgatum), are regarded as clean energy sources, and are an attractive option to mitigate the human-induced climate change. However, the global climate change and the expansion of perennial grass bioenergy crops have the power to alter the biogeochemical cycles in soil, especially, soil carbon storages, over long time scales. In order to develop a predictive understanding, this study develops a coupled hydrological-soil nutrient model to simulate soil carbon responses under different climate scenarios such as: (i) current weather condition, (ii) decreased precipitation by -15%, and (iii) increased temperature up to +3C for four different crops, namely miscanthus, switchgrass, maize, and natural prairie. We use Precision Agricultural Landscape Modeling System (PALMS), version 5.4.0, to capture biophysical and hydrological components coupled with a multilayer carbon and ¬nitrogen cycle model. We apply the model at daily time scale to the Energy Biosciences Institute study site, located in the University of Illinois Research Farms, in Urbana, Illinois. The atmospheric forcing used to run the model was generated stochastically from parameters obtained using available data recorded in Bondville Ameriflux Site. The model simulations are validated with observations of drainage and nitrate and ammonium concentrations recorded in drain tiles during 2011. The results of this study show (1) total soil carbon storage of miscanthus accumulates most noticeably due to the significant amount of aboveground plant carbon, and a relatively high carbon to nitrogen ratio and lignin content, which reduce the litter decomposition rate. Also, (2) the decreased precipitation contributes to the enhancement of total soil carbon storage and soil nitrogen concentration because of the reduced microbial biomass pool. However, (3) an opposite effect on the cycle is introduced by the increased temperature. The simulation results obtained in this study show differences in the soil biogeochemistry induced by the different crops analyzed. Considering the spatial scale at which this crops are cultivated this results suggest there could be important implications in the carbon and nitrogen cycle and indirect feedbacks on climate change. This study also helps us understand the future soil mineral cycle, and ensure a sustainable transition to bioenergy crops.

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

NASA Astrophysics Data System (ADS)

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, Anthony D.; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

2015-12-01

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr-1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil RH with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Yujie; Yang, Jinyan; Zhuang, Qianlai

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here in this study we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbialmore » dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO 2 efflux (R H) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil R H (7.5 ± 2.4 PgCyr -1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil R H with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.« less

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

USGS Publications Warehouse

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, A. David; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

2015-01-01

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr−1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4–0.6) in the simulated spatial pattern of soil RHwith both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = −0.43 to −0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

Characterization of Air and Ground Temperature Relationships within the CMIP5 Historical and Future Climate Simulations

NASA Astrophysics Data System (ADS)

García-García, A.; Cuesta-Valero, F. J.; Beltrami, H.; Smerdon, J. E.

2017-12-01

The relationships between air and ground surface temperatures across North America are examined in the historical and future projection simulations from 32 General Circulation Models (GCMs) included in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The covariability between surface air (2 m) and ground surface temperatures (10 cm) is affected by simulated snow cover, vegetation cover and precipitation through changes in soil moisture at the surface. At high latitudes, the differences between air and ground surface temperatures, for all CMIP5 simulations, are related to the insulating effect of snow cover and soil freezing phenomena. At low latitudes, the differences between the two temperatures, for the majority of simulations, are inversely proportional to leaf area index and precipitation, likely due to induced-changes in latent and sensible heat fluxes at the ground surface. Our results show that the transport of energy across the air-ground interface differs from observations and among GCM simulations, by amounts that depend on the components of the land-surface models that they include. The large variability among GCMs and the marked dependency of the results on the choice of the land-surface model, illustrate the need for improving the representation of processes controlling the coupling of the lower atmosphere and the land surface in GCMs as a means of reducing the variability in their representation of weather and climate phenomena, with potentially important implications for positive climate feedbacks such as permafrost and soil carbon stability.

A new MRI land surface model HAL

NASA Astrophysics Data System (ADS)

Hosaka, M.

2011-12-01

A land surface model HAL is newly developed for MRI-ESM1. It is used for the CMIP simulations. HAL consists of three submodels: SiByl (vegetation), SNOWA (snow) and SOILA (soil) in the current version. It also contains a land coupler LCUP which connects some submodels and an atmospheric model. The vegetation submodel SiByl has surface vegetation processes similar to JMA/SiB (Sato et al. 1987, Hirai et al. 2007). SiByl has 2 vegetation layers (canopy and grass) and calculates heat, moisture, and momentum fluxes between the land surface and the atmosphere. The snow submodel SNOWA can have any number of snow layers and the maximum value is set to 8 for the CMIP5 experiments. Temperature, SWE, density, grain size and the aerosol deposition contents of each layer are predicted. The snow properties including the grain size are predicted due to snow metamorphism processes (Niwano et al., 2011), and the snow albedo is diagnosed from the aerosol mixing ratio, the snow properties and the temperature (Aoki et al., 2011). The soil submodel SOILA can also have any number of soil layers, and is composed of 14 soil layers in the CMIP5 experiments. The temperature of each layer is predicted by solving heat conduction equations. The soil moisture is predicted by solving the Darcy equation, in which hydraulic conductivity depends on the soil moisture. The land coupler LCUP is designed to enable the complicated constructions of the submidels. HAL can include some competing submodels (precise and detailed ones, and simpler ones), and they can run at the same simulations. LCUP enables a 2-step model validation, in which we compare the results of the detailed submodels with the in-situ observation directly at the 1st step, and follows the comparison between them and those of the simpler ones at the 2nd step. When the performances of the detailed ones are good, we can improve the simpler ones by using the detailed ones as reference models.

Toward improving the representation of the water cycle at High Northern Latitudes

NASA Astrophysics Data System (ADS)

Lahoz, William; Svendby, Tove; Hamer, Paul; Blyverket, Jostein; Kristiansen, Jørn; Luijting, Hanneke

2016-04-01

The rapid warming at northern latitude regions in recent decades has resulted in a lengthening of the growing season, greater photosynthetic activity and enhanced carbon sequestration by the ecosystem. These changes are likely to intensify summer droughts, tree mortality and wildfires. A potential major climate change feedback is the release of carbon-bearing compounds from soil thawing. These changes make it important to have information on the land surface (soil moisture and temperature) at high northern latitude regions. The availability of soil moisture measurements from several satellite platforms provides an opportunity to address issues associated with the effects of climate change, e.g., assessing multi-decadal links between increasing temperatures, snow cover, soil moisture variability and vegetation dynamics. The relatively poor information on water cycle parameters for biomes at northern high latitudes make it important that efforts are expended on improving the representation of the water cycle at these latitudes. In a collaboration between NILU and Met Norway, we evaluate the soil moisture observations over Norway from the ESA satellite SMOS (Soil Moisture and Ocean Salinity) using in situ ground based soil moisture measurements, with reference to drought and flood episodes. We will use data assimilation of the quality-controlled SMOS soil moisture observations into a land surface model and a numerical weather prediction model to assess the added value from satellite observations of soil moisture for improving the representation of the water cycle at high northern latitudes. This presentation provides first results from this work. We discuss the evaluation of SMOS soil moisture data (and from other satellites) against ground-based in situ data over Norway; the performance of the SMOS soil moisture data for selected drought and flood conditions over Norway; and the first results from data assimilation experiments with land surface models and numerical weather prediction models. Analyses include information on root zone soil moisture. We provide evidence of the value of satellite soil measurements over Norway, including their fidelity, and their impact at improving the representation of the hydrological cycle over northern high latitudes. We indicate benefits from these results for multi-decadal soil moisture datasets such as that from the ESA CCI for soil moisture.

Calibrated Hydrothermal Parameters, Barrow, Alaska, 2013

DOE Data Explorer

Atchley, Adam; Painter, Scott; Harp, Dylan; Coon, Ethan; Wilson, Cathy; Liljedahl, Anna; Romanovsky, Vladimir

2015-01-29

A model-observation-experiment process (ModEx) is used to generate three 1D models of characteristic micro-topographical land-formations, which are capable of simulating present active thaw layer (ALT) from current climate conditions. Each column was used in a coupled calibration to identify moss, peat and mineral soil hydrothermal properties to be used in up-scaled simulations. Observational soil temperature data from a tundra site located near Barrow, AK (Area C) is used to calibrate thermal properties of moss, peat, and sandy loam soil to be used in the multiphysics Advanced Terrestrial Simulator (ATS) models. Simulation results are a list of calibrated hydrothermal parameters for moss, peat, and mineral soil hydrothermal parameters.

Topsoil organic carbon content of Europe, a new map based on a generalised additive model

NASA Astrophysics Data System (ADS)

de Brogniez, Delphine; Ballabio, Cristiano; Stevens, Antoine; Jones, Robert J. A.; Montanarella, Luca; van Wesemael, Bas

2014-05-01

There is an increasing demand for up-to-date spatially continuous organic carbon (OC) data for global environment and climatic modeling. Whilst the current map of topsoil organic carbon content for Europe (Jones et al., 2005) was produced by applying expert-knowledge based pedo-transfer rules on large soil mapping units, the aim of this study was to replace it by applying digital soil mapping techniques on the first European harmonised geo-referenced topsoil (0-20 cm) database, which arises from the LUCAS (land use/cover area frame statistical survey) survey. A generalized additive model (GAM) was calibrated on 85% of the dataset (ca. 17 000 soil samples) and a backward stepwise approach selected slope, land cover, temperature, net primary productivity, latitude and longitude as environmental covariates (500 m resolution). The validation of the model (applied on 15% of the dataset), gave an R2 of 0.27. We observed that most organic soils were under-predicted by the model and that soils of Scandinavia were also poorly predicted. The model showed an RMSE of 42 g kg-1 for mineral soils and of 287 g kg-1 for organic soils. The map of predicted OC content showed the lowest values in Mediterranean countries and in croplands across Europe, whereas highest OC content were predicted in wetlands, woodlands and in mountainous areas. The map of standard error of the OC model predictions showed high values in northern latitudes, wetlands, moors and heathlands, whereas low uncertainty was mostly found in croplands. A comparison of our results with the map of Jones et al. (2005) showed a general agreement on the prediction of mineral soils' OC content, most probably because the models use some common covariates, namely land cover and temperature. Our model however failed to predict values of OC content greater than 200 g kg-1, which we explain by the imposed unimodal distribution of our model, whose mean is tilted towards the majority of soils, which are mineral. Finally, average OC content predictions for each land cover class compared well between models, with our model always showing smaller standard deviations. We concluded that the chosen model and covariates are appropriate for the prediction of OC content in European mineral soils. We presented in this work the first map of topsoil OC content at European scale based on a harmonised soil dataset. The associated uncertainty map shall support the end-users in a careful use of the predictions.

Thermodynamic parameters of U (VI) sorption onto soils in aquatic systems.

PubMed

Kumar, Ajay; Rout, Sabyasachi; Ghosh, Malay; Singhal, Rakesh Kumar; Ravi, Pazhayath Mana

2013-01-01

The thermodynamic parameters viz. the standard free energy (∆Gº), Standard enthalpy change (∆Hº) and standard entropy change (∆Sº) were determined using the obtained values of distribution coefficient (kd) of U (VI) in two different types of soils (agricultural and undisturbed) by conducting a batch equilibrium experiment with aqueous media (groundwater and deionised water) at two different temperatures 25°C and 50°C. The obtained distribution coefficients (kd) values of U for undisturbed soil in groundwater showed about 75% higher than in agricultural soil at 25°C while in deionised water, these values were highly insignificant for both soils indicating that groundwater was observed to be more favorable for high surface sorption. At 50°C, the increased kd values in both soils revealed that solubility of U decreased with increasing temperature. Batch adsorption results indicated that U sorption onto soils was promoted at higher temperature and an endothermic and spontaneous interfacial process. The high positive values of ∆Sº for agricultural soil suggested a decrease in sorption capacity of U in that soil due to increased randomness at solid-solution interface. The low sorption onto agricultural soil may be due to presence of high amount of coarse particles in the form of sand (56%). Geochemical modeling predicted that mixed hydroxo-carbonato complexes of uranium were the most stable and abundant complexes in equilibrium solution during experimental.

Phosphorus sorption-desorption and effects of temperature, pH and salinity on phosphorus sorption in marsh soils from coastal wetlands with different flooding conditions.

PubMed

Bai, Junhong; Ye, Xiaofei; Jia, Jia; Zhang, Guangliang; Zhao, Qingqing; Cui, Baoshan; Liu, Xinhui

2017-12-01

Wetland soils act as a sink or source of phosphorus (P) to the overlaying water due to phosphorus sorption-desorption processes. Litter information is available on sorption and desorption behaviors of phosphorus in coastal wetlands with different flooding conditions. Laboratory experiments were conducted to investigate phosphorus sorption-desorption processes, fractions of adsorbed phosphorus, and the effects of salinity, pH and temperature on phosphorus sorption on soils in tidal-flooding wetlands (TW), freshwater-flooding wetlands (FW) and seasonal-flooding wetlands (SW) in the Yellow River Delta. Our results showed that the freshly adsorbed phosphorus dominantly exists in Occluded-P and Fe/AlP and their percentages increased with increasing phosphorus adsorbed. Phosphorus sorption isotherms could be better described by the modified Langmuir model than by the modified Freundlich model. A binomial equation could be properly used to describe the effects of salinity, pH, and temperature on phosphorus sorption. Phosphorus sorption generally increased with increasing salinity, pH, and temperature at lower ranges, while decreased in excess of some threshold values. The maximum phosphorus sorption capacity (Q max ) was larger for FW soils (256 mg/kg) compared with TW (218 mg/kg) and SW soils (235 mg/kg) (p < 0.05). The percentage of phosphorus desorption (P des ) in the FW soils (7.5-63.5%) was much lower than those in TW (27.7-124.9%) and SW soils (19.2-108.5%). The initial soil organic matter, pH and the exchangeable Al, Fe and Cd contents were important factors influencing P sorption and desorption. The findings of this study indicate that freshwater restoration can contribute to controlling the eutrophication status of water bodies through increasing P sorption. Copyright © 2017 Elsevier Ltd. All rights reserved.

Soil Respiration in Tibetan Alpine Grasslands: Belowground Biomass and Soil Moisture, but Not Soil Temperature, Best Explain the Large-Scale Patterns

PubMed Central

Geng, Yan; Wang, Yonghui; Yang, Kuo; Wang, Shaopeng; Zeng, Hui; Baumann, Frank; Kuehn, Peter; Scholten, Thomas; He, Jin-Sheng

2012-01-01

The Tibetan Plateau is an essential area to study the potential feedback effects of soils to climate change due to the rapid rise in its air temperature in the past several decades and the large amounts of soil organic carbon (SOC) stocks, particularly in the permafrost. Yet it is one of the most under-investigated regions in soil respiration (Rs) studies. Here, Rs rates were measured at 42 sites in alpine grasslands (including alpine steppes and meadows) along a transect across the Tibetan Plateau during the peak growing season of 2006 and 2007 in order to test whether: (1) belowground biomass (BGB) is most closely related to spatial variation in Rs due to high root biomass density, and (2) soil temperature significantly influences spatial pattern of Rs owing to metabolic limitation from the low temperature in cold, high-altitude ecosystems. The average daily mean Rs of the alpine grasslands at peak growing season was 3.92 µmol CO2 m−2 s−1, ranging from 0.39 to 12.88 µmol CO2 m−2 s−1, with average daily mean Rs of 2.01 and 5.49 µmol CO2 m−2 s−1 for steppes and meadows, respectively. By regression tree analysis, BGB, aboveground biomass (AGB), SOC, soil moisture (SM), and vegetation type were selected out of 15 variables examined, as the factors influencing large-scale variation in Rs. With a structural equation modelling approach, we found only BGB and SM had direct effects on Rs, while other factors indirectly affecting Rs through BGB or SM. Most (80%) of the variation in Rs could be attributed to the difference in BGB among sites. BGB and SM together accounted for the majority (82%) of spatial patterns of Rs. Our results only support the first hypothesis, suggesting that models incorporating BGB and SM can improve Rs estimation at regional scale. PMID:22509373

Modeling Net Ecosystem Carbon Exchange of Alpine Grasslands with a Satellite-Driven Model

PubMed Central

Zhao, Yuping; Zhang, Xianzhou; Fan, Yuzhi; Shi, Peili; He, Yongtao; Yu, Guirui; Li, Yingnian

2015-01-01

Estimate of net ecosystem carbon exchange (NEE) between the atmosphere and terrestrial ecosystems, the balance of gross primary productivity (GPP) and ecosystem respiration (Reco) has significant importance for studying the regional and global carbon cycles. Using models driven by satellite data and climatic data is a promising approach to estimate NEE at regional scales. For this purpose, we proposed a semi-empirical model to estimate NEE in this study. In our model, the component GPP was estimated with a light response curve of a rectangular hyperbola. The component Reco was estimated with an exponential function of soil temperature. To test the feasibility of applying our model at regional scales, the temporal variations in the model parameters derived from NEE observations in an alpine grassland ecosystem on Tibetan Plateau were investigated. The results indicated that all the inverted parameters exhibit apparent seasonality, which is in accordance with air temperature and canopy phenology. In addition, all the parameters have significant correlations with the remote sensed vegetation indexes or environment temperature. With parameters estimated with these correlations, the model illustrated fair accuracy both in the validation years and at another alpine grassland ecosystem on Tibetan Plateau. Our results also indicated that the model prediction was less accurate in drought years, implying that soil moisture is an important factor affecting the model performance. Incorporating soil water content into the model would be a critical step for the improvement of the model. PMID:25849325

Modeling net ecosystem carbon exchange of alpine grasslands with a satellite-driven model.

PubMed

Yan, Wei; Hu, Zhongmin; Zhao, Yuping; Zhang, Xianzhou; Fan, Yuzhi; Shi, Peili; He, Yongtao; Yu, Guirui; Li, Yingnian

2015-01-01

Estimate of net ecosystem carbon exchange (NEE) between the atmosphere and terrestrial ecosystems, the balance of gross primary productivity (GPP) and ecosystem respiration (Reco) has significant importance for studying the regional and global carbon cycles. Using models driven by satellite data and climatic data is a promising approach to estimate NEE at regional scales. For this purpose, we proposed a semi-empirical model to estimate NEE in this study. In our model, the component GPP was estimated with a light response curve of a rectangular hyperbola. The component Reco was estimated with an exponential function of soil temperature. To test the feasibility of applying our model at regional scales, the temporal variations in the model parameters derived from NEE observations in an alpine grassland ecosystem on Tibetan Plateau were investigated. The results indicated that all the inverted parameters exhibit apparent seasonality, which is in accordance with air temperature and canopy phenology. In addition, all the parameters have significant correlations with the remote sensed vegetation indexes or environment temperature. With parameters estimated with these correlations, the model illustrated fair accuracy both in the validation years and at another alpine grassland ecosystem on Tibetan Plateau. Our results also indicated that the model prediction was less accurate in drought years, implying that soil moisture is an important factor affecting the model performance. Incorporating soil water content into the model would be a critical step for the improvement of the model.

Influence of spatial variability of hydraulic characteristics of soils on surface parameters obtained from remote sensing data in infrared and microwaves

NASA Technical Reports Server (NTRS)

Brunet, Y.; Vauclin, M.

1985-01-01

The correct interpretation of thermal and hydraulic soil parameters infrared from remotely sensed data (thermal infrared, microwaves) implies a good understanding of the causes of their temporal and spatial variability. Given this necessity, the sensitivity of the surface variables (temperature, moisture) to the spatial variability of hydraulic soil properties is tested with a numerical model of heat and mass transfer between bare soil and atmosphere. The spatial variability of hydraulic soil properties is taken into account in terms of the scaling factor. For a given soil, the knowledge of its frequency distribution allows a stochastic use of the model. The results are treated statistically, and the part of the variability of soil surface parameters due to that of soil hydraulic properties is evaluated quantitatively.

Ice nucleation by soil dust compared to desert dust aerosols

NASA Astrophysics Data System (ADS)

Moehler, O.; Steinke, I.; Ullrich, R.; Höhler, K.; Schiebel, T.; Hoose, C.; Funk, R.

2015-12-01

A minor fraction of atmospheric aerosol particles, so-called ice-nucleating particles (INPs), initiates the formation of the ice phase in tropospheric clouds and thereby markedly influences the Earth's weather and climate systems. Whether an aerosol particle acts as an INP depends on its size, morphology and chemical compositions. The INP fraction of certain aerosol types also strongly depends on the temperature and the relative humidity. Because both desert dust and soil dust aerosols typically comprise a variety of different particles, it is difficult to assess and predict their contribution to the atmospheric INP abundance. This requires both accurate modelling of the sources and atmospheric distribution of atmospheric dust components and detailed investigations of their ice nucleation activities. The latter can be achieved in laboratory experiments and parameterized for use in weather and climate models as a function of temperature and particle surface area, a parameter called ice-nucleation active site (INAS) density. Concerning ice nucleation activity studies, the soil dust is of particular interest because it contains a significant fraction of organics and biological components, both with the potential for contributing to the atmospheric INP abundance at relatively high temperatures compared to mineral components. First laboratory ice nucleation experiments with a few soil dust samples indicated their INP fraction to be comparable or slightly enhanced to that of desert dust. We have used the AIDA (Aerosol Interaction and Dynamics in the Atmosphere) cloud simulation chamber to study the immersion freezing ability of four different arable soil dusts, sampled in Germany, China and Argentina. For temperatures higher than about -20°C, we found the INP fraction of aerosols generated from these samples by a dry dispersion technique to be significantly higher compared to various desert dust aerosols also investigated in AIDA experiments. In this contribution, we will summarize the experimental results, introduce related INP parameterizations for use in weather and climate models, and briefly discuss possible reasons for the discrepancy between the INP fraction of desert and soil dust aerosols.

ORCHIDEE-MICT (v8.4.1), a land surface model for the high latitudes: model description and validation

NASA Astrophysics Data System (ADS)

Guimberteau, Matthieu; Zhu, Dan; Maignan, Fabienne; Huang, Ye; Yue, Chao; Dantec-Nédélec, Sarah; Ottlé, Catherine; Jornet-Puig, Albert; Bastos, Ana; Laurent, Pierre; Goll, Daniel; Bowring, Simon; Chang, Jinfeng; Guenet, Bertrand; Tifafi, Marwa; Peng, Shushi; Krinner, Gerhard; Ducharne, Agnès; Wang, Fuxing; Wang, Tao; Wang, Xuhui; Wang, Yilong; Yin, Zun; Lauerwald, Ronny; Joetzjer, Emilie; Qiu, Chunjing; Kim, Hyungjun; Ciais, Philippe

2018-01-01

The high-latitude regions of the Northern Hemisphere are a nexus for the interaction between land surface physical properties and their exchange of carbon and energy with the atmosphere. At these latitudes, two carbon pools of planetary significance - those of the permanently frozen soils (permafrost), and of the great expanse of boreal forest - are vulnerable to destabilization in the face of currently observed climatic warming, the speed and intensity of which are expected to increase with time. Improved projections of future Arctic and boreal ecosystem transformation require improved land surface models that integrate processes specific to these cold biomes. To this end, this study lays out relevant new parameterizations in the ORCHIDEE-MICT land surface model. These describe the interactions between soil carbon, soil temperature and hydrology, and their resulting feedbacks on water and CO2 fluxes, in addition to a recently developed fire module. Outputs from ORCHIDEE-MICT, when forced by two climate input datasets, are extensively evaluated against (i) temperature gradients between the atmosphere and deep soils, (ii) the hydrological components comprising the water balance of the largest high-latitude basins, and (iii) CO2 flux and carbon stock observations. The model performance is good with respect to empirical data, despite a simulated excessive plant water stress and a positive land surface temperature bias. In addition, acute model sensitivity to the choice of input forcing data suggests that the calibration of model parameters is strongly forcing-dependent. Overall, we suggest that this new model design is at the forefront of current efforts to reliably estimate future perturbations to the high-latitude terrestrial environment.

Predicting the response of soil organic matter microbial decomposition to moisture

NASA Astrophysics Data System (ADS)

Chenu, Claire; Garnier, Patricia; Monga, Olivier; Moyano, Fernando; Pot, Valérie; Nunan, Naoise; Coucheney, Elsa; Otten, Wilfred

2014-05-01

Next to temperature, soil moisture is a main driver of soil C and N transformations in soils, because it affects microbial activity and survival. The moisture sensitivity of soil organic matter decay may be a source of uncertainty of similar magnitude to that of the temperature sensitivity and receives much less attention. The basic concepts and mechanisms relating soil water to microorganisms were identified early (i.e. in steady state conditions : direct effects on microbial physiology, diffusion substrates, nutrients, extracellular enzymes, diffusion of oxygen, movement of microorganisms). However, accounting for how moisture controls soil microbial activity remains essentially empirical and poorly accounts for soil characteristics. Soil microorganisms live in a complex 3-D framework of mineral and organic particles defining pores of various sizes, connections with adjacent pores, and with pore walls of contrasted nature, which result in a variety of microhabitats. The water regime to which microorganisms are exposed can be predicted to depend the size and connectivity of pores in which they are located. Furthermore, the spatial distribution of microorganisms as well as that of organic matter is very heterogeneous, determining the diffusion distances between substrates and decomposers. A new generation of pore scale models of C dynamics in soil may challenge the difficulty of modelling such a complex system. These models are based on an explicit representation of soil structure (i.e. soil particles and voids), microorganisms and organic matter localisation. We tested here the ability of such a model to account for changes in microbial respiration with soil moisture. In the model MOSAIC II, soil pore space is described using a sphere network coming from a geometrical modelling algorithm. MicroCT tomography images were used to implement this representation of soil structure. A biological sub-model describes the hydrolysis of insoluble SOM into dissolved organic matter, its assimilation, respiration and microbial mortality. A recent improvement of the model was the description of the diffusion of soluble organic matter. We tested the model using the results from an experiment where a simple substrate (fructose) was decomposed by bacteria within a simple media (sand). Separate incubations in microcosms were carried out using five different bacterial communities at two different moisture conditions corresponding to water potentials of -0.01 and -0.1 bars. We calibrated the biological parameters using the experimental data obtained at high water content and we tested the model without any parameters change at low water content. Both the experiments and simulations showed a decrease in mineralisation with a decrease of water content, of which pattern depended on the bacterial species and its physiological characteristics. The model was able to correctly simulate the decrease of connectivity between substrate and microorganism due the decrease of water content. The potential and required developments of such models in describing how heterotrophic respiration is affected by micro-scale distribution and processes in soils and in testing scenarios regarding water regimes in a changing climate is discussed.

Controls on SOC across space and time: Models with different acclimation schemes make similar spatial predictions but divergent warming predictions

NASA Astrophysics Data System (ADS)

Abramoff, R. Z.; Torn, M. S.; Georgiou, K.; Tang, J.; Riley, W. J.

2017-12-01

Researchers use spatial gradients to estimate long-term ecosystem responses to perturbations. This approach is commonly applied to soil organic carbon (SOC) stocks which change slowly but store the majority of terrestrial carbon. Climate warming may reduce SOC stocks if higher temperatures increase decomposition rates. Yet, it is uncertain how vulnerable SOC is to warming, and whether the same factors - such as organo-mineral associations, climate, or plant inputs - determine SOC stocks across space and time. In order to test the "space for time" concept, we developed two versions of the Substrate-Mineral-Microbe Soil (SuMMS) model - one with microbial temperature acclimation and one without - to analyze observed SOC stocks at 24 sites spanning a wide range of soil types and climate. Both model predictions of SOC were strongly correlated with observations (R2 > 0.9), because mineral sorption capacity was the dominant control over steady-state SOC stock as determined by a Random Forest model. However, the two model versions made fundamentally different predictions of the change in SOC following 5°C soil warming from 2016 to 2100 because the initial mean annual temperature (MAT) was the dominant control over the SOC response. The model with microbial acclimation predicted that SOC would decline 10% at all sites along the transect, while the model with no acclimation predicted large surface SOC losses at high latitude sites and SOC gains at low latitude sites where microbial exoenzymes were already at or near their temperature optimum. These simulations suggest that gradient studies cannot be used to infer site-level responses to warming, because the dominant controls on SOC at steady state (i.e., mineral sorption capacity) are different than the dominant controls on the SOC response to a warming perturbation (i.e., initial MAT, capacity for acclimation).

Biogenic emissions of CO2 and N2O at multiple depths increase exponentially during a simulated soil thaw for a northern prairie Mollisol

USDA-ARS?s Scientific Manuscript database

Soil respiration occurs at depths below the surface, but belowground data are lacking to support multilayer models of soil CO2 and N2O emissions. In particular, Q10s for CO2 and N2O within soil profiles are needed to determine if temperature sensitivities calculated at the surface are similar to th...

A mechanistic diagnosis of the simulation of soil CO2 efflux of the ACME Land Model

NASA Astrophysics Data System (ADS)

Liang, J.; Ricciuto, D. M.; Wang, G.; Gu, L.; Hanson, P. J.; Mayes, M. A.

2017-12-01

Accurate simulation of the CO2 efflux from soils (i.e., soil respiration) to the atmosphere is critical to project global biogeochemical cycles and the magnitude of climate change in Earth system models (ESMs). Currently, the simulated soil respiration by ESMs still have a large uncertainty. In this study, a mechanistic diagnosis of soil respiration in the Accelerated Climate Model for Energy (ACME) Land Model (ALM) was conducted using long-term observations at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the central U.S. The results showed that the ALM default run significantly underestimated annual soil respiration and gross primary production (GPP), while incorrectly estimating soil water potential. Improved simulations of soil water potential with site-specific data significantly improved the modeled annual soil respiration, primarily because annual GPP was simultaneously improved. Therefore, accurate simulations of soil water potential must be carefully calibrated in ESMs. Despite improved annual soil respiration, the ALM continued to underestimate soil respiration during peak growing seasons, and to overestimate soil respiration during non-peak growing seasons. Simulations involving increased GPP during peak growing seasons increased soil respiration, while neither improved plant phenology nor increased temperature sensitivity affected the simulation of soil respiration during non-peak growing seasons. One potential reason for the overestimation of the soil respiration during non-peak growing seasons may be that the current model structure is substrate-limited, while microbial dormancy under stress may cause the system to become decomposer-limited. Further studies with more microbial data are required to provide adequate representation of soil respiration and to understand the underlying reasons for inaccurate model simulations.

Experimental fire increases soil carbon dioxide efflux in a grassland long-term multifactor global change experiment.

PubMed

Strong, Aaron L; Johnson, Tera P; Chiariello, Nona R; Field, Christopher B

2017-05-01

Numerous studies have demonstrated that soil respiration rates increase under experimental warming, although the long-term, multiyear dynamics of this feedback are not well constrained. Less is known about the effects of single, punctuated events in combination with other longer-duration anthropogenic influences on the dynamics of soil carbon (C) loss. In 2012 and 2013, we assessed the effects of decadal-scale anthropogenic global change - warming, increased nitrogen (N) deposition, elevated carbon dioxide (CO 2 ), and increased precipitation - on soil respiration rates in an annual-dominated Mediterranean grassland. We also investigated how controlled fire and an artificial wet-up event, in combination with exposure to the longer-duration anthropogenic global change factors, influenced the dynamics of C cycling in this system. Decade-duration surface soil warming (1-2 °C) had no effect on soil respiration rates, while +N addition and elevated CO 2 concentrations increased growing-season soil CO 2 efflux rates by increasing annual aboveground net primary production (NPP) and belowground fine root production, respectively. Low-intensity experimental fire significantly elevated soil CO 2 efflux rates in the next growing season. Based on mixed-effects modeling and structural equation modeling, low-intensity fire increased growing-season soil respiration rates through a combination of three mechanisms: large increases in soil temperature (3-5 °C), significant increases in fine root production, and elevated aboveground NPP. Our study shows that in ecosystems where soil respiration has acclimated to moderate warming, further increases in soil temperature can stimulate greater soil CO 2 efflux. We also demonstrate that punctuated short-duration events such as fire can influence soil C dynamics with implications for both the parameterization of earth system models (ESMs) and the implementation of climate change mitigation policies that involve land-sector C accounting. © 2016 John Wiley & Sons Ltd.

Carbonate clumped isotopes and in situ temperature monitoring for Holocene soils in the San Luis Valley, USA indicate springtime carbonate formation

NASA Astrophysics Data System (ADS)

Hudson, A. M.; Paces, J. B.; Ruleman, C.

2017-12-01

Pedogenic carbonate horizons are abundant in semi-arid and arid regions worldwide and within the geologic record. They present a widely distributed archive of past environmental conditions, driven by global climate or tectonically-controlled elevation changes. Oxygen and carbon isotopes in calcite-rich nodules and clast rinds are widely-applied indicators of past soil water and CO2 composition linked to changing precipitation and plant communities. The temperature of carbonate formation, however, provides key constraint on past water/CO2 values and elucidate why they may have changed in the past. Clumped isotope thermometry can provide this constraint and additional climate information, given the carbonate forming system is well understood. We present preliminary clumped isotope (Δ47) temperatures for Holocene soil carbonates, constrained by 14C and U-Th disequilibrium dating, compared with two years of in situ soil temperature data to better understand the mechanism and seasonality of carbonate formation in the San Luis Valley region of the southern Rocky Mountains. Five temperature-monitoring sites ranging in elevation (1940-2450 m) and latitude (36.2-37.9°N) were installed in a variety of settings (range front, valley center, and canyon). The resulting records show indistinguishable seasonal temperature variations at >60 cm depth. This suggests Δ47 temperatures should be comparable at sites across the region. Temperatures based on Δ47 measurements of Holocene (>1.8 to 11.0 ka BP) carbonates at these sites yield consistent inter-site temperatures of 10±4°C, which are similar to modern springtime soil temperatures at depth. This seasonality matches previous results of isotopic modeling at sites further south along the Rio Grande corridor. Temperatures during March to May show multiple, abrupt warming and cooling cycles on weekly timescales caused by wetting and drying of the soil during spring precipitation events. This may drive carbonate precipitation under low pCO2 conditions before increased plant respiration increases soil pCO2 later in the season.

Regional Climate Variability Under Model Simulations of Solar Geoengineering

NASA Astrophysics Data System (ADS)

Dagon, Katherine; Schrag, Daniel P.

2017-11-01

Solar geoengineering has been shown in modeling studies to successfully mitigate global mean surface temperature changes from greenhouse warming. Changes in land surface hydrology are complicated by the direct effect of carbon dioxide (CO2) on vegetation, which alters the flux of water from the land surface to the atmosphere. Here we investigate changes in boreal summer climate variability under solar geoengineering using multiple ensembles of model simulations. We find that spatially uniform solar geoengineering creates a strong meridional gradient in the Northern Hemisphere temperature response, with less consistent patterns in precipitation, evapotranspiration, and soil moisture. Using regional summertime temperature and precipitation results across 31-member ensembles, we show a decrease in the frequency of heat waves and consecutive dry days under solar geoengineering relative to a high-CO2 world. However in some regions solar geoengineering of this amount does not completely reduce summer heat extremes relative to present day climate. In western Russia and Siberia, an increase in heat waves is connected to a decrease in surface soil moisture that favors persistent high temperatures. Heat waves decrease in the central United States and the Sahel, while the hydrologic response increases terrestrial water storage. Regional changes in soil moisture exhibit trends over time as the model adjusts to solar geoengineering, particularly in Siberia and the Sahel, leading to robust shifts in climate variance. These results suggest potential benefits and complications of large-scale uniform climate intervention schemes.

Impact of wildfire and slope aspect on soil temperature in a mountainous environment

USGS Publications Warehouse

Ebel, Brian A.

2012-01-01

Soil temperature changes after landscape disturbance impact hydrology, ecology, and geomorphology. This study used field measurements to examine wildfire and aspect effects on soil temperatures. Combustion of the litter and duff layers on north-facing slopes removed pre-fire aspect-driven soil temperature controls.Wildfire is one of the most significant disturbances in mountainous landscapes and can affect soil temperature, which can in turn impact ecologic and geomorphologic processes. This study measured the temperature in near-surface soil (i.e., top 30 cm) during the first summer after a wildfire. In mountainous environments, aspect can also affect soil temperature, so north- vs. south-facing aspects were compared using a fully factorial experimental design to explore the effects of both wildfire and aspect on soil temperature. The data showed major wildfire impacts on soil temperatures on north-facing aspects (unburned ∼4–5°C cooler, on average) but little impact on south-facing aspects. Differences in soil temperatures between north-facing and south-facing unburned aspects (north ∼5°C cooler, on average) were also observed. The data led to the conclusion that, for this field site during the summer period, the forest canopy and litter and duff layers on north-facing slopes (when unburned) substantially decreased mean soil temperatures and temperature variability. The sparse trees on south-facing slopes caused little to no difference in soil temperatures following wildfire in south-facing soils for unburned compared with burned conditions. The results indicate that wildfire can reduce or even remove aspect impacts on soil temperature by combusting the forest canopy and litter and duff layers, which then homogenizes soil temperatures across the landscape.

A soil-canopy scheme for use in a numerical model of the atmosphere: 1D stand-alone model

NASA Astrophysics Data System (ADS)

Kowalczyk, E. A.; Garratt, J. R.; Krummel, P. B.

We provide a detailed description of a soil-canopy scheme for use in the CSIRO general circulation models (GCMs) (CSIRO-4 and CSIRO-9), in the form of a one-dimensional stand-alone model. In addition, the paper documents the model's ability to simulate realistic surface fluxes by comparison with mesoscale model simulations (involving more sophisticated soil and boundary-layer treatments) and observations, and the diurnal range in surface quantities, including extreme maximum surface temperatures. The sensitivity of the model to values of the surface resistance is also quantified. The model represents phase 1 of a longer-term plan to improve the atmospheric boundary layer (ABL) and surface schemes in the CSIRO GCMs.

Soil Moisture and Temperature Measuring Networks in the Tibetan Plateau and Their Hydrological Applications

NASA Astrophysics Data System (ADS)

Yang, Kun; Chen, Yingying; Qin, Jun; Lu, Hui

2017-04-01

Multi-sphere interactions over the Tibetan Plateau directly impact its surrounding climate and environment at a variety of spatiotemporal scales. Remote sensing and modeling are expected to provide hydro-meteorological data needed for these process studies, but in situ observations are required to support their calibration and validation. For this purpose, we have established two networks on the Tibetan Plateau to measure densely two state variables (soil moisture and temperature) and four soil depths (0 5, 10, 20, and 40 cm). The experimental area is characterized by low biomass, high soil moisture dynamic range, and typical freeze-thaw cycle. As auxiliary parameters of these networks, soil texture and soil organic carbon content are measured at each station to support further studies. In order to guarantee continuous and high-quality data, tremendous efforts have been made to protect the data logger from soil water intrusion, to calibrate soil moisture sensors, and to upscale the point measurements. One soil moisture network is located in a semi-humid area in central Tibetan Plateau (Naqu), which consists of 56 stations with their elevation varying over 4470 4950 m and covers three spatial scales (1.0, 0.3, 0.1 degree). The other is located in a semi-arid area in southern Tibetan Plateau (Pali), which consists of 25 stations and covers an area of 0.25 degree. The spatiotemporal characteristics of the former network were analyzed, and a new spatial upscaling method was developed to obtain the regional mean soil moisture truth from the point measurements. Our networks meet the requirement for evaluating a variety of soil moisture products, developing new algorithms, and analyzing soil moisture scaling. Three applications with the network data are presented in this paper. 1. Evaluation of Current remote sensing and LSM products. The in situ data have been used to evaluate AMSR-E, AMSR2, SMOS and SMAP products and four modeled outputs by the Global Land Data Assimilation System (GLDAS). 2. Development of New Products. We developed a dual-pass land data assimilation system. The essential idea of the system is to calibrate a land data assimilation system before a normal data assimilation. The calibration is based on satellite data rather than in situ data. Through this way, we may alleviate the impact of uncertainties in determining the error covariance of both observation operator and model operation, as it is always tough to determine the covariance. The performance of the data assimilation system is presented through comparison against the Tibetan Plateau soil moisture measuring networks. And the results are encouraging. 3. Estimation of Soil Parameter Values in a Land Surface Model. We explored the possibility to estimate soil parameter values by assimilating AMSR-E brightness temperature (TB) data. In the assimilation system, the TB is simulated by the coupled system of a land surface model (LSM) and a radiative transfer model (RTM), and the simulation errors highly depend on parameters in both the LSM and the RTM. Thus, sensitive soil parameters may be inversely estimated through minimizing the TB errors. The effectiveness of the estimated parameter values is evaluated against intensive measurements of soil parameters and soil moisture in three grasslands of the Tibetan Plateau and the Mongolian Plateau. The results indicate that this satellite data-based approach can improve the data quality of soil porosity, a key parameter for soil moisture modeling, and LSM simulations with the estimated parameter values reasonably reproduce the measured soil moisture. This demonstrates it is feasible to calibrate LSMs for soil moisture simulations at grid scale by assimilating microwave satellite data, although more efforts are expected to improve the robustness of the model calibration.

Horizon Partitioning of Soil CO2 Sources and their Isotopic Composition (13C) in a Pinus Sylvestris Stand

NASA Astrophysics Data System (ADS)

Goffin, S.; Parent, F.; Plain, C.; Maier, M.; Schack-Kirchner, H.; Aubinet, M.; Longdoz, B.

2012-12-01

The overall aim of this study is to contribute to a better understanding of mechanisms behind soil CO2 efflux using carbon stable isotopes. The approach combines a soil multilayer analysis and the isotopic tool in an in situ study. The specific goal of this work is to quantify the origin and the determinism of 13CO2 and 12CO2 production processes in the different soil layers using the gradient-efflux approach. To meet this, the work includes an experimental setup and a modeling approach. The experimental set up (see also communication of Parent et al., session B008) comprised a combination of different systems, which were installed in a Scot Pine temperate forest at the Hartheim site (Southwestern Germany). Measurements include (i) half hourly vertical profiles of soil CO2 concentration (using soil CO2 probes), soil water content and temperature; (ii) half hourly soil surface CO2 effluxes (automatic chambers); (iii) half hourly isotopic composition of surface CO2 efflux and soil CO2 concentration profile and (iv) estimation of soil diffusivity through laboratory measurements conducted on soil samples taken at several depths. Using the data collected in the experimental part, we developed and used a diffusive transport model to simulate CO2 (13CO2 and 12CO2) flows inside and out of the soil based on Fick's first law. Given the horizontal homogeneity of soil physical parameters in Hartheim, we treated the soil as a structure consisting of distinctive layers of 5 cm thick and expressed the Fick's first law in a discrete formalism. The diffusion coefficient used in each layer was derived from (i) horizon specific relationships, obtained from laboratory measurements, between soil relative diffusivity and its water content and (ii) the soil water content values measured in situ. The concentration profile was obtained from in situ measurements. So, the main model inputs are the profiles of (i) CO2 (13CO2 and 12CO2) concentration, (ii) soil diffusion coefficient and (iii) soil water content. Once the diffusive fluxes deduced at each layer interface, the CO2 (13CO2 and 12CO2) production profile was calculated using the (discretized) mass balance equation in each layer. The results of the Hartheim measurement campaign will be presented. The CO2 source vertical profile and its link with the root and the Carbon organic content distribution will be showed. The dynamic of CO2 sources and their isotopic signature will be linked to climatic variables such soil temperature and soil water content. For example, we will show that the dynamics of CO2 sources was mainly related to temperature while changing of isotopic signature was more correlated to soil moisture.

Soil salinity assessment through satellite thermography for different irrigated and rainfed crops

NASA Astrophysics Data System (ADS)

Ivushkin, Konstantin; Bartholomeus, Harm; Bregt, Arnold K.; Pulatov, Alim; Bui, Elisabeth N.; Wilford, John

2018-06-01

The use of canopy thermography is an innovative approach for salinity stress detection in plants. But its applicability for landscape scale studies using satellite sensors is still not well investigated. The aim of this research is to test the satellite thermography soil salinity assessment approach on a study area with different crops, grown both in irrigated and rainfed conditions, to evaluate whether the approach has general applicability. Four study areas in four different states of Australia were selected to give broad representation of different crops cultivated under irrigated and rainfed conditions. The soil salinity map was prepared by the staff of Geoscience Australia and CSIRO Land and Water and it is based on thorough soil sampling together with environmental modelling. Remote sensing data was captured by the Landsat 5 TM satellite. In the analysis we used vegetation indices and brightness temperature as an indicator for canopy temperature. Applying analysis of variance and time series we have investigated the applicability of satellite remote sensing of canopy temperature as an approach of soil salinity assessment for different crops grown under irrigated and rainfed conditions. We concluded that in all cases average canopy temperatures were significantly correlated with soil salinity of the area. This relation is valid for all investigated crops, grown both irrigated and rainfed. Nevertheless, crop type does influence the strength of the relations. In our case cotton shows only minor temperature difference compared to other vegetation classes. The strongest relations between canopy temperature and soil salinity were observed at the moment of a maximum green biomass of the crops which is thus considered to be the best time for application of the approach.

Modeling carbon cycle process of soil profile in Loess Plateau of China

NASA Astrophysics Data System (ADS)

Yu, Y.; Finke, P.; Guo, Z.; Wu, H.

2011-12-01

SoilGen2 is a process-based model, which could reconstruct soil formation under various climate conditions, parent materials, vegetation types, slopes, expositions and time scales. Both organic and inorganic carbon cycle processes could be simulated, while the later process is important in carbon cycle of arid and semi-arid regions but seldom being studied. After calibrating parameters of dust deposition rate and segments depth affecting elements transportation and deposition in the profile, modeling results after 10000 years were confronted with measurements of two soil profiles in loess plateau of China, The simulated trends of organic carbon and CaCO3 in the profile are similar to measured values. Relative sensitivity analysis for carbon cycle process have been done and the results show that the change of organic carbon in long time scale is more sensitive to precipitation, temperature, plant carbon input and decomposition parameters (decomposition rate of humus, ratio of CO2/(BIO+HUM), etc.) in the model. As for the inorganic carbon cycle, precipitation and potential evaporation are important for simulation quality, while the leaching and deposition of CaCO3 are not sensitive to pCO2 and temperature of atmosphere.

Heat transfer and phase transitions of water in multi-layer cryolithozone-surface systems

NASA Astrophysics Data System (ADS)

Khabibullin, I. L.; Nigametyanova, G. A.; Nazmutdinov, F. F.

2018-01-01

A mathematical model for calculating the distribution of temperature and the dynamics of the phase transfor-mations of water in multilayer systems on permafrost-zone surface is proposed. The model allows one to perform calculations in the annual cycle, taking into account the distribution of temperature on the surface in warm and cold seasons. A system involving four layers, a snow or land cover, a top layer of soil, a layer of thermal-insulation materi-al, and a mineral soil, is analyzed. The calculations by the model allow one to choose the optimal thickness and com-position of the layers which would ensure the stability of structures built on the permafrost-zone surface.

Impact of Land Model Depth on Long Term Climate Variability and Change.

NASA Astrophysics Data System (ADS)

Gonzalez-Rouco, J. F.; García-Bustamante, E.; Hagemann, S.; Lorentz, S.; Jungclaus, J.; de Vrese, P.; Melo, C.; Navarro, J.; Steinert, N.

2017-12-01

The available evidence indicates that the simulation of subsurface thermodynamics in current General Circulation Models (GCMs) is not accurate enough due to the land-surface model imposing a zero heat flux boundary condition that is too close to the surface. Shallow land model components distort the amplitude and phase of the heat propagation in the subsurface with implications for energy storage and land-air interactions. Off line land surface model experiments forced with GCM climate change simulations and comparison with borehole temperature profiles indicate there is a large reduction of the energy storage of the soil using the typical shallow land models included in most GCMs. However, the impact of increasing the depth of the soil model in `on-line' GCM simulations of climate variability or climate change has not yet been systematically explored. The JSBACH land surface model has been used in stand alone mode, driven by outputs of the MPIESM to assess the impacts of progressively increasing the depth of the soil model. In a first stage, preindustrial control simulations are developed increasing the lower depth of the zero flux bottom boundary condition placed for temperature at the base of the fifth model layer (9.83 m) down to 294.6 m (layer 9), thus allowing for the bottom layers to reach equilibrium. Starting from piControl conditions, historical and scenario simulations have been performed since 1850 yr. The impact of increasing depths on the subsurface layer temperatures is analysed as well as the amounts of energy involved. This is done also considering permafrost processes (freezing and thawing). An evaluation on the influence of deepening the bottom boundary on the simulation of low frequency variability and temperature trends is provided.