scholarly journals Water Table Depth, Surface Saturation, and Drought Response in Bog Turtle (Glyptemys muhlenbergii) Wetlands

Wetlands ◽  
2012 ◽  
Vol 32 (6) ◽  
pp. 1011-1021 ◽  
Author(s):  
Jeffrey B. Feaga ◽  
Carola A. Haas ◽  
James A. Burger
Keyword(s):  
Water Table ◽  
Water Table Depth ◽  
Drought Response ◽  
Bog Turtle ◽  
Glyptemys Muhlenbergii ◽  
Surface Saturation

scholarly journals Temporal and Local Heterogeneities of Water Table Depth under Different Agricultural Water Management Conditions

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2148
Author(s):  
Jonathan A. Lafond ◽  
Silvio J. Gumiere ◽  
Virginie Vanlandeghem ◽  
Jacques Gallichand ◽  
Alain N. Rousseau ◽  
...  
Keyword(s):  
Water Management ◽  
Water Table ◽  
Cropping Systems ◽  
Irrigation Management ◽  
Sprinkler Irrigation ◽  
Water Table Depth ◽  
Management Systems ◽  
Integrated Water Management ◽  
Growing Seasons ◽  
Good Drainage

Integrated water management has become a priority for cropping systems where subirrigation is possible. Compared to conventional sprinkler irrigation, the controlling water table can lead to a substantial increase in yield and water use efficiency with less pumping energy requirements. Knowing the spatiotemporal distribution of water table depth (WTD) and soil properties should help perform intelligent, integrated water management. Observation wells were installed in cranberry fields with different water management systems: Bottom, with good drainage and controlled WTD management; Surface, with good drainage and sprinkler irrigation management; Natural, without drainage, or with imperfectly drained and conventional sprinkler irrigation. During the 2017–2020 growing seasons, WTD was monitored on an hourly basis, while precipitation was measured at each site. Multi-frequential periodogram analysis revealed a dominant periodic component of 40 days each year in WTD fluctuations for the Bottom and Surface systems; for the Natural system, periodicity was heterogeneous and ranged from 2 to 6 weeks. Temporal cross correlations with precipitation show that for almost all the sites, there is a 3 to 9 h lag before WTD rises; one exception is a subirrigation site. These results indicate that automatic water table management based on continuously updated knowledge could contribute to integrated water management systems, by using precipitation-based models to predict WTD.

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.

The distinct roles of water table depth and soil properties in controlling alternative woodland-grassland states in the Cerrado

Oecologia ◽  
2021 ◽  
Author(s):  
Jonathan W. F. Ribeiro ◽  
Natashi A. L. Pilon ◽  
Davi R. Rossatto ◽  
Giselda Durigan ◽  
Rosana M. Kolb
Keyword(s):  
Soil Properties ◽  
Water Table ◽  
Water Table Depth

Role of tree stand evapotranspiration in maintaining satisfactory drainage conditions in drained peatlands

2010 ◽  
Vol 40 (8) ◽  
pp. 1485-1496 ◽  
Author(s):  
Sakari Sarkkola ◽  
Hannu Hökkä ◽  
Harri Koivusalo ◽  
Mika Nieminen ◽  
Erkki Ahti ◽  
...  
Keyword(s):  
Bulk Density ◽  
Water Table ◽  
Interactive Effect ◽  
Late Summer ◽  
Water Table Depth ◽  
Separate Analysis ◽  
Tree Stand ◽  
Stand Volume ◽  
Linear Effect ◽  
Subsequent Decrease

Ditch networks in drained peatland forests are maintained regularly to prevent water table rise and subsequent decrease in tree growth. The growing tree stand itself affects the level of water table through evapotranspiration, the magnitude of which is closely related to the living stand volume. In this study, regression analysis was applied to quantify the relationship between the late summer water table depth (DWT) and tree stand volume, mean monthly summertime precipitation (Ps), drainage network condition, and latitude. The analysis was based on several large data sets from southern to northern Finland, including concurrent measurements of stand volume and summer water table depth. The identified model demonstrated a nonlinear effect of stand volume on DWT, a linear effect of Ps on DWT, and an interactive effect of both stand volume and Ps. Latitude and ditch depth showed only marginal influence on DWT. A separate analysis indicated that an increase of 10 m3·ha–1 in stand volume corresponded with a drop of 1 cm in water table level during the growing season. In a subsample of the data, high bulk density peat showed deeper DWT than peat with low bulk density at the same stand volume.

scholarly journals Ecology of peatland testate amoebae in Svalbard and the development of transfer functions for reconstructing past water-table depth and pH

2021 ◽  
Vol 131 ◽  
pp. 108122
Author(s):  
Thomas G. Sim ◽  
Graeme T. Swindles ◽  
Paul J. Morris ◽  
Andy J. Baird ◽  
Dan J. Charman ◽  
...  
Keyword(s):  
Water Table ◽  
Transfer Functions ◽  
Testate Amoebae ◽  
Water Table Depth

Spring water table depth mediates within‐site variation of soil temperature in groundwater‐fed mires

2021 ◽  
Author(s):  
Michal Horsák ◽  
Veronika Horsáková ◽  
Marek Polášek ◽  
Radovan Coufal ◽  
Petra Hájková ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Water Table ◽  
Spring Water ◽  
Water Table Depth ◽  
Site Variation

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>

Assessment of groundwater utilization status and prediction of water table depth using different heuristic models in an Indian interbasin

2018 ◽  
Vol 23 (20) ◽  
pp. 10261-10285 ◽  
Author(s):  
Sucharita Pradhan ◽  
Shiv Kumar ◽  
Yogendra Kumar ◽  
Harish Chandra Sharma
Keyword(s):  
Water Table ◽  
Water Table Depth

scholarly journals Modelling effects of seasonal variation in water table depth on net ecosystem CO<sub>2</sub> exchange of a tropical peatland

2014 ◽  
Vol 11 (3) ◽  
pp. 577-599 ◽  
Author(s):  
M. Mezbahuddin ◽  
R. F. Grant ◽  
T. Hirano
Keyword(s):  
Seasonal Variation ◽  
Nutrient Uptake ◽  
Water Table ◽  
Water Table Depth ◽  
Hydrological Processes ◽  
Plant Nutrient ◽  
Predictive Capacity ◽  
Tropical Peatland ◽  
Tropical Peat ◽  
Dry Seasons

Abstract. Seasonal variation in water table depth (WTD) determines the balance between aggradation and degradation of tropical peatlands. Longer dry seasons together with human interventions (e.g. drainage) can cause WTD drawdowns making tropical peatland C storage highly vulnerable. Better predictive capacity for effects of WTD on net CO2 exchange is thus essential to guide conservation of tropical peat deposits. Mathematical modelling of basic eco-hydrological processes under site-specific conditions can provide such predictive capacity. We hereby deploy a process-based mathematical model ecosys to study effects of seasonal variation in WTD on net ecosystem productivity (NEP) of a drainage affected tropical peat swamp forest at Palangkaraya, Indonesia. Simulated NEP suggested that the peatland was a C source (NEP ~ −2 g C m−2 d−1, where a negative sign represents a C source and a positive sign a C sink) during rainy seasons with shallow WTD, C neutral or a small sink (NEP ~ +1 g C m−2 d−1) during early dry seasons with intermediate WTD and a substantial C source (NEP ~ −4 g C m−2 d−1) during late dry seasons with deep WTD from 2002 to 2005. These values were corroborated by regressions (P < 0.0001) of hourly modelled vs. eddy covariance (EC) net ecosystem CO2 fluxes which yielded R2 > 0.8, intercepts approaching 0 and slopes approaching 1. We also simulated a gradual increase in annual NEP from 2002 (−609 g C m−2) to 2005 (−373 g C m−2) with decreasing WTD which was attributed to declines in duration and intensity of dry seasons following the El Niño event of 2002. This increase in modelled NEP was corroborated by EC-gap filled annual NEP estimates. Our modelling hypotheses suggested that (1) poor aeration in wet soils during shallow WTD caused slow nutrient (predominantly phosphorus) mineralization and consequent slow plant nutrient uptake that suppressed gross primary productivity (GPP) and hence NEP (2) better soil aeration during intermediate WTD enhanced nutrient mineralization and hence plant nutrient uptake, GPP and NEP and (3) deep WTD suppressed NEP through a combination of reduced GPP due to plant water stress and increased ecosystem respiration (Re) from enhanced deeper peat aeration. These WTD effects on NEP were modelled from basic eco-hydrological processes including microbial and root oxidation-reduction reactions driven by soil and root O2 transport and uptake which in turn drove soil and plant carbon, nitrogen and phosphorus transformations within a soil-plant-atmosphere water transfer scheme driven by water potential gradients. Including these processes in ecosystem models should therefore provide an improved predictive capacity for WTD management programs intended to reduce tropical peat degradation.

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