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.

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.

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.

Remotely sensed temperature is a proxy of greenhouse gas emissions in intact and managed peatlands

2021 ◽  
Author(s):  
Ain Kull ◽  
Iuliia Burdun ◽  
Gert Veber ◽  
Oleksandr Karasov ◽  
Martin Maddison ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Water Table ◽  
Ecosystem Respiration ◽  
Ghg Emissions ◽  
Remotely Sensed ◽  
Water Table Depth ◽  
Gas Emissions

<p>Besides water table depth, soil temperature is one of the main drivers of greenhouse gas (GHG) emissions in intact and managed peatlands. In this work, we evaluate the performance of remotely sensed land surface temperature (LST) as a proxy of greenhouse gas emissions in intact, drained and extracted peatlands. For this, we used chamber-measured carbon dioxide (CO<sub>2</sub>) and methane (CH<sub>4</sub>) data from seven peatlands in Estonia collected during vegetation season in 2017–2020. Additionally, we used temperature and water table depth data measured in situ. We studied relationships between CO<sub>2</sub>, CH<sub>4</sub>, in-situ parameters and remotely sensed LST from Landsat 7 and 8, and MODIS Terra. Results of our study suggest that LST has stronger relationships with surface and soil temperature as well as with ecosystem respiration (R<sub>eco</sub>) over drained and extracted sites than over intact ones. Over the extracted cites the correlation between R<sub>eco</sub> CO<sub>2</sub> and LST is 0.7, and over the drained sites correlation is 0.5. In natural sites, we revealed a moderate positive relationship between LST and CO<sub>2</sub> emitted in hollows (correlation is 0.6) while it is weak in hummocks (correlation is 0.3). Our study contributes to the better understanding of relationships between greenhouse gas emissions and their remotely sensed proxies over peatlands with different management status and enables better spatial assessment of GHG emissions in drainage affected northern temperate peatlands.</p>

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 A PROBABILISTIC MODEL FOR THE DETERMINATION OF HYDRAULIC BOUNDARY CONDITIONS IN A DYNAMIC COASTAL SYSTEM

2011 ◽  
Vol 1 (32) ◽  
pp. 38 ◽  
Author(s):  
Jacco Groeneweg ◽  
Joost Beckers ◽  
Caroline Gautier
Keyword(s):  
Wind Speed ◽  
Boundary Conditions ◽  
Water Level ◽  
Wind Direction ◽  
Wadden Sea ◽  
Water Levels ◽  
Tidal Basin ◽  
Wind Fields ◽  
Coastal System ◽  
Advanced Method

In 2011 new Hydraulic Boundary Conditions must be established for the statutory assessment of flood protection in the Wadden Sea area, which is a complex tidal system in the northern part of the Netherlands. The aim is to base these normative wave conditions on the wave simulation model SWAN and the probabilistic method Hydra-K, to be consistent with other systems as the Holland Coast and the Zeeland Delta. Assumptions made for the latter water systems, like steady state wind forcing, uniform water levels and neglect of currents, are not valid in the tidal basin of the Wadden Sea. A schematic temporal variation of both wind direction and wind speed is applied to define wind fields that drive the hydrodynamic computations. Both wind fields and resulting water level and current fields form the input of SWAN computations for a large number of combinations of basic wind speed and wind direction, offshore surge level and phase difference between tide and maximum wind speed. The result is a large database of SWAN results that is used as a look-up table in Hydra-K to transform the offshore statistics to the load on the primary sea defenses. In general the more advanced method leads to wave heights that are up to 10% lower and wave periods that are 10-20% smaller than those obtained with the method that is presently applied for the Holland Coast and the Zeeland Delta. These differences can be ascribed to the inclusion of currents and positive shoreward tilt in water level. The inclusion of relevant physics in the hydrodynamic computations increases the accuracy of the resulting HBC. Therefore, the more advanced method will be applied to determine the HBC for 2011.

scholarly journals High CO<sub>2</sub> fluxes from grassland on histic Gleysol along soil carbon and drainage gradients

2014 ◽  
Vol 11 (3) ◽  
pp. 749-761 ◽  
Author(s):  
K. Leiber-Sauheitl ◽  
R. Fuß ◽  
C. Voigt ◽  
A. Freibauer
Keyword(s):  
Organic Carbon ◽  
Water Table ◽  
Ecosystem Respiration ◽  
Mineral Soil ◽  
Ghg Emissions ◽  
Organic Soils ◽  
Organic Carbon Content ◽  
Peat Layer ◽  
Organic Carbon Concentration ◽  
High Organic Carbon Content

Abstract. Drained organic soils are anthropogenic emission hotspots of greenhouse gases (GHGs). Most studies have focused on deep peat soils and on peats with high organic carbon content. In contrast, histic Gleysols are characterized by shallow peat layers, which are left over from peat cutting activities or by peat mixed with mineral soil. It is unknown whether they emit less GHGs than deep Histosols when drained. We present the annual carbon and GHG balance of grasslands for six sites on nutrient-poor histic Gleysols with a shallow (30 cm) histic horizon or mixed with mineral soil in Northern Germany (soil organic carbon concentration (Corg) from 9 to 52%). The net GHG balance, corrected for carbon export by harvest, was around 4 t CO2–C–eq ha−1 yr−1 on soils with peat layer and little drainage (mean annual water table < 20 cm below surface). The net GHG balance reached 7–9 t CO2–C–eq ha−1 yr−1 on soils with sand mixed into the peat layer and water tables between 14 cm and 39 cm below surface. GHG emissions from drained histic Gleysols (i) were as high as those from deep Histosols, (ii) increase linearly from shallow to deeper drainage, (iii) but are not affected by Corg content of the histic horizon. Ecosystem respiration (Reco) was linearly correlated with water table level even if it was below the histic horizon. The Reco/GPP ratio was 1.5 at all sites, so that we ruled out a major influence of the inter-site variability in vegetation composition on annual net ecosystem exchange (NEE). The IPCC definition of organic soils includes shallow histic topsoil, unlike most national and international definitions of Histosols. Our study confirms that this broader definition is appropriate considering anthropogenic GHG emissions from drained organic soils. Countries currently apply soil maps in national GHG inventories which are likely not to include histic Gleysols. The land area with GHG emission hotspots due to drainage is likely to be much higher than anticipated. Deeply drained histic Gleysols are GHG hotspots that have so far been neglected or underestimated. Peat mixing with sand does not mitigate GHG emissions. Our study implies that rewetting organic soils, including histic Gleysols, has a much higher relevance for GHG mitigation strategies than currently recognized.

Interaction of water table management and mice infestation on greenhouse gas emissions from intensively used grasslands on Histosol

2020 ◽  
Author(s):  
Bärbel Tiemeyer ◽  
Sebastian Heller ◽  
Sebastian Willi Oehmke ◽  
Ullrich Dettmann
Keyword(s):  
Water Table ◽  
Agricultural Land ◽  
Ghg Emissions ◽  
Flux Measurement ◽  
Soil Surface ◽  
Water Levels ◽  
Mild Winter ◽  
Western Germany ◽  
Water Table Management ◽  
North Western

&lt;p&gt;During the last century, drainage turned the majority of the bogs and fens in Germany into productive agricultural land, causing substantial emissions of greenhouse gases (GHG). The project &amp;#8216;SWAMPS&amp;#8217; focuses both on maintaining the trafficability for conventional intensive grassland use and on the reduction of GHG emissions by managing the groundwater level by submerged drains and blocked ditches. Here, we aim to evaluate the interaction of water table management and a severe mice infestation on the emissions of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;), nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) and methane (CH&lt;sub&gt;4&lt;/sub&gt;).&lt;/p&gt;&lt;p&gt;We set up two field sites on both fen and bog peat in North-Western Germany. Submerged drains were installed at a distance of 4 to 5 m and with a target ditch level of 45 to 50 cm below mean soil surface. On the parcels with blocked ditches, the target ditch level is adjusted at 30 to 35 cm. The control parcels are drained by ditches and/or drainage pipes. Since 2017, diurnal CO&lt;sub&gt;2&lt;/sub&gt; flux measurement campaigns have been realised once every three to four weeks with transparent and opaque chambers and a portable gas analyser. CH&lt;sub&gt;4&lt;/sub&gt; and N&lt;sub&gt;2&lt;/sub&gt;O samples are taken biweekly and additionally more frequently after fertilizer application.&lt;/p&gt;&lt;p&gt;However, our experimental design was disrupted when, after an extremely dry summer and a dry and mild winter, the mice population grew strongly in 2019. We monitored both the number of mouse holes and the damage by mice. At the bog site, nearly no grass was left at the control site at the end of the year, while at the fen site, less, but still significant damage was observed. In this year, this was typical for the situation in North-Western Germany, where around 150,000 ha of grassland were severely damaged by mice. The sites with water table management were less effected by mice, but as food became scarce, they started to move into these wetter areas as well.&lt;/p&gt;&lt;p&gt;Despite higher water levels, CO&lt;sub&gt;2&lt;/sub&gt; emissions in 2019 were partially higher than in previous years, especially at those sites affected by mice. With this presentation, we would like to discuss the effects of mice damage on soil respiration and on possibilities to disentangle water management effects from this (experimental and agricultural) calamity. &amp;#160;&lt;/p&gt;

scholarly journals Particle Tracking Using Dynamic Water-Level Data

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 2063
Author(s):  
Yuan Gao
Keyword(s):  
Groundwater Flow ◽  
Water Level ◽  
Water Table ◽  
Flow Direction ◽  
Water Levels ◽  
Subsurface Water ◽  
Pressure Transducers ◽  
Level Data ◽  
Water Level Data ◽  
Fluid Particles

The movement of fluid particles about historic subsurface releases is often governed by dynamic subsurface water levels. Motivations for tracking the movement of fluid particles include tracking the fate of subsurface contaminants and resolving the fate of water stored in subsurface aquifers. This study provides a novel method for predicting the movement of subsurface particles relying on dynamic water-level data derived from continuously recording pressure transducers. At least three wells are needed to measure water levels which are used to determine the plain of the water table. Based on Darcy’s law, particle flow pathlines at the study site are obtained using the slope of the water table. The results show that hydrologic conditions, e.g., seasonal transpiration and precipitation, influence local groundwater flow. The changes of water level in short periods caused by the hydrologic variations made the hydraulic gradient diversify considerably, thus altering the direction of groundwater flow. Although a range of groundwater flow direction and gradient with time can be observed by an initial review of water levels in rose charts, the net groundwater flow at all field sites is largely constant in one direction which is driven by the gradients with higher magnitude.

scholarly journals Natural Nitrogen Isotope Ratios as a Potential Indicator of N2O Production Pathways in a Floodplain Fen

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 409
Author(s):  
Mohit Masta ◽  
Holar Sepp ◽  
Jaan Pärn ◽  
Kalle Kirsimäe ◽  
Ülo Mander
Keyword(s):  
Water Table ◽  
Isotope Composition ◽  
Nitrogen Isotope ◽  
Water Table Depth ◽  
Organic Soils ◽  
Site Preference ◽  
N2o Emissions ◽  
N2o Production ◽  
Nitrifier Denitrification ◽  
Anoxic Environment

Nitrous oxide (N2O), a major greenhouse gas and ozone depleter, is emitted from drained organic soils typically developed in floodplains. We investigated the effect of the water table depth and soil oxygen (O2) content on N2O fluxes and their nitrogen isotope composition in a drained floodplain fen in Estonia. Measurements were done at natural water table depth, and we created a temporary anoxic environment by experimental flooding. From the suboxic peat (0.5–6 mg O2/L) N2O emissions peaked at 6 mg O2/L and afterwards decreased with decreasing O2. From the anoxic and oxic peat (0 and >6 mg O2/L, respectively) N2O emissions were low. Under anoxic conditions the δ15N/δ14N ratio of the top 10 cm peat layer was low, gradually decreasing to 30 cm. In the suboxic peat, δ15N/δ14N ratios increased with depth. In samples of peat fluctuating between suboxic and anoxic, the elevated 15N/14N ratios (δ15N = 7–9‰ ambient N2) indicated intensive microbial processing of nitrogen. Low values of site preference (SP; difference between the central and peripheral 15N atoms) and δ18O-N2O in the captured gas samples indicate nitrifier denitrification in the floodplain fen.

scholarly journals Carbon dioxide flux and net primary production of a boreal treed bog: responses to warming and water table manipulations

2014 ◽  
Vol 11 (9) ◽  
pp. 12937-12983 ◽  
Author(s):  
T. M. Munir ◽  
M. Perkins ◽  
E. Kaing ◽  
M. Strack
Keyword(s):  
Carbon Dioxide ◽  
Primary Production ◽  
Water Level ◽  
Water Table ◽  
Forest Floor ◽  
Net Primary Production ◽  
Carbon Dioxide Flux ◽  
Water Levels ◽  
Co2 Uptake ◽  
Experimental Site

Abstract. Mid-latitude treed bogs are significant carbon (C) stocks and are highly sensitive to global climate change. In a dry continental treed bog, we compared three sites; control, recent (1–3 years; experimental) and older drained (10–13 years; drained) with water levels at 38, 74 and 120 cm below the surface, respectively. At each site we measured carbon dioxide (CO2) fluxes and tree root respiration (Rr) (across hummock-hollow microtopography of the forest floor) and net primary production (NPP) of trees during the growing seasons (May to October) of 2011–2013. The carbon (C) balance was calculated by adding net CO2 exchange of the forest floor (NEff–Rr) to the NPP of the trees. From cooler and wetter 2011 to driest and warmest 2013, The control site was a~C sink of 92, 70 and 76 g m−2, experimental site was a C source of 14, 57 and 135 g m−2, and drained site was a progressively smaller source of 26, 23 and 13 g m−2, respectively. Although all microforms at the experimental site had large net CO2 emissions, the longer-term drainage and deeper water level at the drained site resulted in the replacement of mosses with vascular plants (shrubs) at the hummocks and lichens at the hollows leading to the highest CO2 uptake at drained hummocks and significant losses at hollows. The tree NPP was highest at the drained site. We also quantified the impact of climatic warming at all water table treatments by equipping additional plots with open-top chambers (OTCs) that caused a passive warming on average of ∼1 °C and differential air warming of ∼6 °C (at mid-day full sun) across the study years. Warming significantly enhanced the shrub growth and CO2 sink function of the drained hummocks (exceeding the cumulative respiration losses at hollows induced by the lowered water level × warming). There was an interaction of water level with warming across hummocks that resulted in largest net CO2 uptake at warmed drained hummocks. Thus in 2013, the warming treatment enhanced the sink function of control by 13 g m−2, reduced the source function of experimental by 10 g m−2, and significantly enhanced the sink function of the drained site by 73 g m−2. Therefore, drying and warming in continental bogs is expected to initially accelerate C losses via respiration but persistent drought and warming is expected to restore the peatland's original C sink function as a result of transitional shift of vegetation between the microforms and increased NPP of trees over time.

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