High temporal resolution measurements of CO2, CH4 and N2O in a Norwegian mire ecosystem using automated light-dark chambers

2020 ◽  
Author(s):  
Linsey Avila ◽  
Klaus Steenberg Larsen ◽  
Andreas Ibrom ◽  
Norbert Pirk ◽  
Poul Larsen
Keyword(s):  
Water Table ◽  
Natural Water ◽  
Water Levels ◽  
Organic Soils ◽  
High Temporal Resolution ◽  
Decomposition Rates ◽  
Microbial Decomposition ◽  
Enhanced Production ◽  
Nature Restoration ◽  
Ch4 And N2o

<p>Regeneration of natural hydrology in previously drained peatlands is becoming a widespread practice in nature restoration projects around the world. The drained peatlands are well known for their high emissions of CO<sub>2</sub> caused by increased microbial decomposition rates in these very organic soils when suddenly exposed to higher levels of oxygen availability. Restoring natural water levels reduces again the decomposition rates and CO<sub>2</sub> emissions. It remains uncertain, however, how rates of the much stronger greenhouse gases, CH<sub>4</sub> and N<sub>2</sub>O, respond to the restored water table and these fluxes can potentially offset the GHG balance of rewetting peatlands.</p><p> </p><p>In a new project in Norway (close to Trysil, Innlandet), we installed five ECO<sub>2</sub>flux automated chambers and one eddy flux tower in each of two areas of drained peatlands.  The automatic chambers were placed with different distances to the ditches reflecting variation in water table with greatest water level variability at the edges of the ditches. After two years, the ditches will be filled and the natural water table will be regenerated in one of the areas in order to follow the differences in the fluxes of CO<sub>2</sub>, CH<sub>4</sub> and N<sub>2</sub>O upon rewetting.</p><p> </p><p>We here present an analysis of the first year’s data from the ECO<sub>2</sub>flux chambers including the total greenhouse gas budget for the period measured. The fluxes of CO<sub>2</sub> showed only little spatial heterogeneity whereas we observed a significant spatial pattern of higher fluxes of CH<sub>4</sub> in plots where the water table was closer to the surface. The driest plots, i.e. the edges of the drain ditches, showed also the lowest emissions of CH<sub>4</sub>. The trend was similar in the two areas. This is an indicating that planned rewetting after two years of the project may lead to enhanced production and emission of CH<sub>4</sub> in the area. So far, we observed no N<sub>2</sub>O emissions above the detection limit of the system indicating that CO<sub>2</sub> and CH<sub>4</sub> are the major components of the GHG budget.</p>

scholarly journals Large-scale regionalization of water table depth in peatlands optimized for greenhouse gas emission upscaling

2014 ◽  
Vol 18 (9) ◽  
pp. 3319-3339 ◽  
Author(s):  
M. Bechtold ◽  
B. Tiemeyer ◽  
A. Laggner ◽  
T. Leppelt ◽  
E. Frahm ◽  
...  
Keyword(s):  
Land Cover ◽  
Boundary Conditions ◽  
Water Level ◽  
Water Table ◽  
Ghg Emissions ◽  
Water Table Depth ◽  
Water Levels ◽  
Predictor Variables ◽  
Organic Soils ◽  
Depth Information

Abstract. Fluxes of the three main greenhouse gases (GHG) CO2, CH4 and N2O from peat and other soils with high organic carbon contents are strongly controlled by water table depth. Information about the spatial distribution of water level is thus a crucial input parameter when upscaling GHG emissions to large scales. Here, we investigate the potential of statistical modeling for the regionalization of water levels in organic soils when data covers only a small fraction of the peatlands of the final map. Our study area is Germany. Phreatic water level data from 53 peatlands in Germany were compiled in a new data set comprising 1094 dip wells and 7155 years of data. For each dip well, numerous possible predictor variables were determined using nationally available data sources, which included information about land cover, ditch network, protected areas, topography, peatland characteristics and climatic boundary conditions. We applied boosted regression trees to identify dependencies between predictor variables and dip-well-specific long-term annual mean water level (WL) as well as a transformed form (WLt). The latter was obtained by assuming a hypothetical GHG transfer function and is linearly related to GHG emissions. Our results demonstrate that model calibration on WLt is superior. It increases the explained variance of the water level in the sensitive range for GHG emissions and avoids model bias in subsequent GHG upscaling. The final model explained 45% of WLt variance and was built on nine predictor variables that are based on information about land cover, peatland characteristics, drainage network, topography and climatic boundary conditions. Their individual effects on WLt and the observed parameter interactions provide insight into natural and anthropogenic boundary conditions that control water levels in organic soils. Our study also demonstrates that a large fraction of the observed WLt variance cannot be explained by nationally available predictor variables and that predictors with stronger WLt indication, relying, for example, on detailed water management maps and remote sensing products, are needed to substantially improve model predictive performance.

scholarly journals Large-scale regionalization of water table depth in peatlands optimized for greenhouse gas emission upscaling

2014 ◽  
Vol 11 (4) ◽  
pp. 3857-3909 ◽  
Author(s):  
M. Bechtold ◽  
B. Tiemeyer ◽  
A. Laggner ◽  
T. Leppelt ◽  
E. Frahm ◽  
...  
Keyword(s):  
Land Cover ◽  
Boundary Conditions ◽  
Water Level ◽  
Water Table ◽  
Ghg Emissions ◽  
Water Table Depth ◽  
Water Levels ◽  
Predictor Variables ◽  
Organic Soils ◽  
Depth Information

Abstract. Fluxes of the three main greenhouse gases (GHG) CO2, CH4 and N2O from peat and other organic soils are strongly controlled by water table depth. Information about the spatial distribution of water level is thus a crucial input parameter when upscaling GHG emissions to large scales. Here, we investigate the potential of statistical modeling for the regionalization of water levels in organic soils when data covers only a small fraction of the peatlands of the final map. Our study area is Germany. Phreatic water level data from 53 peatlands in Germany were compiled in a new dataset comprising 1094 dip wells and 7155 years of data. For each dip well, numerous possible predictor variables were determined using nationally available data sources, which included information about land cover, ditch network, protected areas, topography, peatland characteristics and climatic boundary conditions. We applied boosted regression trees to identify dependencies between predictor variables and dip well specific long-term annual mean water level (WL) as well as a transformed form of it (WLt). The latter was obtained by assuming a hypothetical GHG transfer function and is linearly related to GHG emissions. Our results demonstrate that model calibration on WLt is superior. It increases the explained variance of the water level in the sensitive range for GHG emissions and avoids model bias in subsequent GHG upscaling. The final model explained 45% of WLt variance and was built on nine predictor variables that are based on information about land cover, peatland characteristics, drainage network, topography and climatic boundary conditions. Their individual effects on WLt and the observed parameter interactions provide insights into natural and anthropogenic boundary conditions that control water levels in organic soils. Our study also demonstrates that a large fraction of the observed WLt variance cannot be explained by nationally available predictor variables and that predictors with stronger WLt indication, relying e.g. on detailed water management maps and remote sensing products, are needed to substantially improve model predictive performance.

General considerations for modeling water table dynamics in peatlands

2021 ◽  
Author(s):  
Alex Cobb ◽  
Charles Harvey
Keyword(s):  
Water Table ◽  
Time Derivative ◽  
Water Levels ◽  
Richards Equation ◽  
Specific Yield ◽  
High Temporal Resolution ◽  
Precipitation Data ◽  
Water Table Fluctuations ◽  
Peatland Hydrology ◽  
Vertical Gradients

<p>A basic and universal characteristic of peatlands is that the water table frequently rises near the surface of the soil profile. Surface peat is naturally loose and open-structured, and often has microtopographic features; the water table frequently rises above the level of local depressions. Therefore, water table fluctuations in peatlands cause rapid changes in the permeability and effective porosity of the medium through which flow occurs. We use a simple model based on Boussinesq's equation to explore the challenges that arise from these basic and universal physical aspects of peatland hydrology. We show that simulation of water table fluctuations in peatlands requires precipitation data with a high temporal resolution, and careful attention to the time derivative for accuracy of the mean water tables and correct water balance for two reasons. First, large vertical gradients in specific yield can result in large mass balance errors analogous to errors from naive discretization of the Richards equation; a change of variables from water table elevation to water storage can eliminate these errors and also speed up calculations by allowing larger time steps. Second, large vertical gradients in permeability near the peat surface cause a strongly nonlinear response to precipitation, so that time-averaged precipitation data or neglect of diurnal cycles of evapotranspiration results in erroneously high water levels, and careful time stepping is required around rain storms.  Consideration of these features of peatland hydrology results in efficient hydrologic models that can be used to predict spatial and temporal patterns in greenhouse gas uptake and emissions in peatlands.</p>

scholarly journals Assessment of Automatically Monitored Water Levels and Water Quality Indicators in Rivers with Different Hydromorphological Conditions and Pollution Levels in Greece

Hydrology ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 86
Author(s):  
Angeliki Mentzafou ◽  
George Varlas ◽  
Anastasios Papadopoulos ◽  
Georgios Poulis ◽  
Elias Dimitriou
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Quality Indicators ◽  
High Frequency ◽  
Automatic Monitoring ◽  
Water Levels ◽  
High Temporal Resolution ◽  
Water Quality Indicators ◽  
Pollution Levels ◽  
Riverine Ecosystems

Water resources, especially riverine ecosystems, are globally under qualitative and quantitative degradation due to human-imposed pressures. High-temporal-resolution data obtained from automatic stations can provide insights into the processes that link catchment hydrology and streamwater chemistry. The scope of this paper was to investigate the statistical behavior of high-frequency measurements at sites with known hydromorphological and pollution pressures. For this purpose, hourly time series of water levels and key water quality indicators (temperature, electric conductivity, and dissolved oxygen concentrations) collected from four automatic monitoring stations under different hydromorphological conditions and pollution pressures were statistically elaborated. Based on the results, the hydromorphological conditions and pollution pressures of each station were confirmed to be reflected in the results of the statistical analysis performed. It was proven that the comparative use of the statistics and patterns of the water level and quality high-frequency time series could be used in the interpretation of the current site status as well as allowing the detection of possible changes. This approach can be used as a tool for the definition of thresholds, and will contribute to the design of management and restoration measures for the most impacted areas.

Modelling response of infiltration loss toward water table depth using RBFN, RNN, ANFIS techniques

2021 ◽  
Vol 25 (2) ◽  
pp. 227-234
Author(s):  
Sandeep Samantaray ◽  
Abinash Sahoo
Keyword(s):  
Neural Network ◽  
Mean Square Error ◽  
Water Table ◽  
Environmental Sustainability ◽  
Model Development ◽  
Water Table Depth ◽  
Water Levels ◽  
Coefficient Of Determination ◽  
Mean Square ◽  
Inference System

Accurate prediction of water table depth over long-term in arid agricultural areas are very much important for maintaining environmental sustainability. Because of intricate and diverse hydrogeological features, boundary conditions, and human activities researchers face enormous difficulties for predicting water table depth. A virtual study on forecast of water table depth using various neural networks is employed in this paper. Hybrid neural network approach like Adaptive Neuro Fuzzy Inference System (ANFIS), Recurrent Neural Network (RNN), Radial Basis Function Neural Network (RBFN) is employed here to appraisal water levels as a function of average temperature, precipitation, humidity, evapotranspiration and infiltration loss data. Coefficient of determination (R2), Root mean square error (RMSE), and Mean square error (MSE) are used to evaluate performance of model development. While ANFIS algorithm is used, Gbell function gives best value of performance for model development. Whole outcomes establish that, ANFIS accomplishes finest as related to RNN and RBFN for predicting water table depth in watershed.

scholarly journals Hydrogeology of Brahmaputra Basin, India

2003 ◽  
Vol 28 ◽  
Author(s):  
Barendra Purkait
Keyword(s):  
Ground Water ◽  
Water Table ◽  
Land Surface ◽  
Flood Plain ◽  
Water Levels ◽  
The South ◽  
Drainage Pattern ◽  
The North ◽  
The World ◽  
Brahmaputra Basin

The Ganga-Brahmaputra river system together forms one of the largest deltas in the world comprising some 59570 sq km. The waterpower resources of the Brahmaputra have been presumed to be the fourth biggest in the world being 19.83 x 103 m3s1. The entire lower portion of the Brahmaputra consists of a vast network of distributary channels, which are dry in the cold season but are inundated during monsoon. The catchment area of the entire river is about 580,000 sq km, out of which 195,000 sq km lies in India. The maximum discharge as measured at Pandu in 1962 was of the order of 72800 m3 s-1 while the minimum was 1750 m3 s-1 in 1968. The drainage pattern in the valley is of antecedent type while the yazoo drainage pattern is most significant over the composite flood plain to the south of the Brahmaputra. The Brahmaputra valley is covered by Recent alluvium throughout its stretch except a few isolated sedimentary hills in the upper Assam, inselbergs/bornhardt of gneissic hills in the Darrang, Kamrup and Goalpara districts and a few inlying patches of Older Alluvium in the Darrang and Goalpara districts. The basin is very unstable. The present configuration of the basin is the result of uplift and subsidence of the Precambrian crystalline landmasses. Four geotectonic provinces can be delineated in the N-E India through which the Brahmaputra flows. These are bounded by major tectonic lineaments such as the basement E-W trending Dauki fault, a NE-SW trending structural feature of imbricate thrusts known as 'belt of Schuppen' and the NW-SE trending Mishmi thrust. Hydrogeologically, the Brahmaputra basin can be divided into two distinct categories, viz(a) dissected alluvial plain and (b) the inselberg zone. The first category is rep resented in the flood plain extending from the south of Sub-Himalayan piedmont fan zone in the north to right upto the main rock promontory of Garo Hills and Shillong Plateau. The inselberg zone is characterized by fractured, jointed and weathered ancient crystalline rocks with interhill narrow valley plains, consisting of thin to occasionally thick piles of assorted sediments. From the subsurface lithological data, two broad groups of aquifers are identified. These are i) shallow water table and ii) deeper water table or confined ones, separated by a system of aquicludes. The shallow aquifer materials, in general, consist of white to greyish white, fine grained micaceous sand and the thickness ranges from 1.2 to 10.3 m. The sand and clay ratio varies from 1: 2.5 to 1:26. The bedrock occurs at depth ranges of 30.4 to 39.5 m. The materials of the deeper aquifers comprise grey to greyish white, fine to medium grained sand. The sand and clay ratio varies from 1:2 to 1:7. The effective size of the aquifer materials varies from 0.125 to 0.062 mm with uniformity co-efficient around 4.00, porosity 38 to 42%, co-efficient of permeability 304 to 390 galls per day/0.3m2. The ground water is mildly alkaline with pH value 6.5 to 8.5, chloride 10 to 40 ppm, bi-carbonate 50 to 350 ppm, iron content ranges from a fraction of a ppm to 50 ppm. Total dissolved solids are low, hardness as CaCo3 50 to 300 ppm, specific conductance at 25 °C 150 to 650 mhos/cm. The yield from shallow aquifers is 1440 litres to 33750 litres/hour and for deeper aquifers ~ 1700 litres/hour at a drawdown of 13.41 m, specific capacity 21 litres/minute. The temperatures of ground water are 23°-25° C during winter, 24°-26° C during pre-monsoon and 27°- 28° C during peak monsoon. The general hydraulic gradient in the north bank is 1:800 whereas in the south bank it is 1: 300-400 The Tertiary sediments yield a range of water from 200 to 300 l.p.m whereas the yield from the Older Alluvium is 500 to 700 1.p.m. The estimated transmissibility and co-efficient of storage is of the order of ~ 800 1.p.m/ m and 8.2 x 10-3 respectively. Depths to water levels range from 5.3 to 10m below land surface (b.l.s). In the Younger or Newer Alluvium, ground water occurs both under water table and confined conditions. Depths to water levels vary from ground level to 10 m b.l.s. Depth to water ranges from 6 m b.l.s. to 2 m above land surface. The yield of the deep tubewells ranges from 2 to 4 kl/minute for a drawdown of 3 m to 6 m. The transmissibility of the aquifers varies from 69 to 1600 l.p.m/m and the storage co-fficient is of the order of 3.52 x 10-2.

scholarly journals Partitioning CO<sub>2</sub> net ecosystem exchange fluxes on the microsite scale in the Lena River Delta, Siberia

2018 ◽  
Author(s):  
Tim Eckhardt ◽  
Christian Knoblauch ◽  
Lars Kutzbach ◽  
Gillian Simpson ◽  
Evgeny Abakumov ◽  
...  
Keyword(s):  
Water Table ◽  
Net Ecosystem Exchange ◽  
Growing Season ◽  
Arctic Tundra ◽  
High Water ◽  
Water Levels ◽  
River Delta ◽  
Lena River ◽  
Hydrological Conditions ◽  
Lena River Delta

Abstract. Arctic tundra ecosystems are currently facing rates of amplified climate change. This is critical as these ecosystems store significant amounts of carbon in their soils, which can be mineralized to CO2 and CH4 and released to the atmosphere. To understand how the CO2 net ecosystem exchange (NEE) fluxes will react to changing climatic conditions, it is necessary to understand the individual responses of the physiological processes contributing to CO2 NEE. Therefore, this study aimed: (i) to partition NEE fluxes at the soil-plant-atmosphere interface in an arctic tundra ecosystem; and (ii) to identify the main environmental drivers of these fluxes. Hereby, the NEE fluxes were partitioned into gross primary productivity (GPP) and ecosystem respiration (Reco) and further into autotrophic (RA) and heterotrophic respiration (RH). The study examined flux data collected during the growing season in 2015 using closed chamber measurements in a polygonal tundra landscape in the Lena River Delta, northeastern Siberia. The measured fluxes on the microscale (1 m–10 m) were used to model the NEE, GPP, Reco, RH, RA and net ecosystem production (NPP) over the growing season. Here, for the first time, the differing response of in situ measured RA and RH fluxes from permafrost-affected soils to hydrological conditions have been examined. It was shown that low RA fluxes are associated to a high water table, most likely due to the submersion of mosses, while an effect of water table fluctuations on RH fluxes was not observed. Furthermore, this work found the polygonal tundra in the Lena River Delta to be a sink for atmospheric CO2 during the growing season. Spatial heterogeneity was apparent with the net CO2 uptake at a wet, depressed polygon center being more than twice as high as that measured at a drier polygon rim. In addition to higher GPP fluxes, the differences in NEE between the two microsites were caused by lower Reco fluxes at the center compared to the rim. Here, the contrasting hydrological conditions caused the CO2 flux differences between the microsites, where high water levels lad to lower decomposition rates due to anoxic conditions.

Environmental Microbiology: Tannins & Microbial Decomposition of Leaves on the Forest Floor

2010 ◽  
Vol 72 (8) ◽  
pp. 506-512 ◽  
Author(s):  
M. Brian Traw ◽  
Nancy Gift
Keyword(s):  
Scientific Inquiry ◽  
Forest Floor ◽  
Bacterial Culture ◽  
White Oak ◽  
Decomposition Rates ◽  
Microbial Decomposition ◽  
Simple Question ◽  
Leaf Tissues ◽  
Student Inquiry ◽  
Tulip Poplar

Tannins are plant chemicals that humans find useful in products as diverse as tea and leather. Why do plants produce these compounds? One possible answer is defense against pathogens and herbivores. In this series of laboratory exercises, student inquiry begins with a simple question: What happens to the multitude of leaves that drop each autumn? This inquiry brings students from the outdoors to the laboratory, where they observe differences in leaf decomposition rates and the natural abundance of bacteria and tannin concentrations in leaf tissues of red oak, white oak, and tulip poplar. In the process, students increase their understanding of plant chemistry, bacterial culture, graphing, and natural history, while experiencing the iterative nature of scientific inquiry.

Links between hydrological patterns and lateral carbon fluxes: a comparison between a wet and a drained site on a Siberian permafrost floodplain tundra

2021 ◽  
Author(s):  
Sandra Raab ◽  
Mathias Goeckede ◽  
Jorien Vonk ◽  
Anke Hildebrandt ◽  
Martin Heimann
Keyword(s):  
Organic Carbon ◽  
Water Table ◽  
Surface Waters ◽  
Carbon Fluxes ◽  
Flow Patterns ◽  
Control Site ◽  
Water Levels ◽  
Soil Conditions ◽  
Transport Patterns ◽  
Carbon Transport

&lt;p&gt;As a major reservoir for organic carbon, permafrost areas play a pivotal role in global climate change. Vertical carbon fluxes as well as lateral transport from land to groundwaters and surface waters towards the ocean are highly dependent on various abiotic and biotic factors. These include for example temperature, groundwater depth, or vegetation community. During summer months, when soils thaw and lateral carbon transport within suprapermafrost groundwater bodies and surface waters occurs, flow patterns and therefore carbon redistribution may differ significantly between dry and wet conditions. Since dry soil conditions are expected to become more frequent in the future, associated shifts in carbon transport patterns play an important role in quantifying the carbon input into the water body linked to permafrost degradation.&lt;/p&gt;&lt;p&gt;This study focuses on hydrological and carbon transport patterns within a floodplain tundra site near Chersky, Northeast Siberia. We compared a wet control site with a site affected by a drainage ring built in 2004 to study the effect of water availability on carbon production and transport. Water table depths at both sites were continuously monitored with a distributed sensor network over the summer seasons 2016-2020. At several locations, water samples were collected in 2016 and 2017 to determine organic carbon concentrations (DOC) as well as carbon isotopes (e.g. &amp;#8710;&lt;sup&gt;14&lt;/sup&gt;C-DOC). Suprapermafrost groundwater and surface water from the drainage ditch and the nearby Ambolikha river were included in the analysis.&lt;/p&gt;&lt;p&gt;Our results focus on the physical hydrological conditions as well as on DOC and &amp;#8710;&lt;sup&gt;14&lt;/sup&gt;C-DOC observations. The spatio-temporal dynamics of water table depth revealed systematic differences between control and drained sites. The drained area showed a stronger decrease in water tables towards peak summer season in July and stronger reactions to precipitation events. The control area responded less pronounced to short-term changes. At the drained site, the main groundwater flow direction was stable throughout the measurement period. The control site was characterized by a shift in water flow confluence depending on increasing and decreasing water levels. DOC and &amp;#8710;&lt;sup&gt;14&lt;/sup&gt;C-DOC data showed that the highest concentrations of organic carbon and oldest DOC can be found in late summer. DOC concentrations were higher at the drained site compared to the wet site. We will show that the distribution of dissolved carbon can be directly related to hydrological flow patterns, and that understanding of these redistribution processes is essential for interpreting the carbon budget in disturbed permafrost.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals Interactions among temperature, moisture, and oxygen concentrations in controlling decomposition rates in a boreal forest soil

2017 ◽  
Vol 14 (3) ◽  
pp. 703-710 ◽  
Author(s):  
Carlos A. Sierra ◽  
Saadatullah Malghani ◽  
Henry W. Loescher
Keyword(s):  
Boreal Forest ◽  
High Temperatures ◽  
High Water ◽  
High Water Content ◽  
Organic Soils ◽  
Soil Core ◽  
Decomposition Rates ◽  
Environmental Controls ◽  
Wide Range ◽  
Oxygen Concentrations

Abstract. Determining environmental controls on soil organic matter decomposition is of importance for developing models that predict the effects of environmental change on global soil carbon stocks. There is uncertainty about the environmental controls on decomposition rates at temperature and moisture extremes, particularly at high water content levels and high temperatures. It is uncertain whether observed declines in decomposition rates at high temperatures are due to declines in the heat capacity of extracellular enzymes as predicted by thermodynamic theory, or due to simultaneous declines in soil moisture. It is also uncertain whether oxygen limits decomposition rates at high water contents. Here we present the results of a full factorial experiment using organic soils from a boreal forest incubated at high temperatures (25 and 35 °C), a wide range of water-filled pore space (WFPS; 15, 30, 60, 90 %), and contrasting oxygen concentrations (1 and 20 %). We found support for the hypothesis that decomposition rates are high at high temperatures, provided that enough moisture and oxygen are available for decomposition. Furthermore, we found that decomposition rates are mostly limited by oxygen concentrations at high moisture levels; even at 90 % WFPS, decomposition proceeded at high rates in the presence of oxygen. Our results suggest an important degree of interaction among temperature, moisture, and oxygen in determining decomposition rates at the soil core scale.

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