Analysis of Long-Term Water Table Depth Records from a Hydrosequence of Soils in Central Ohio

1984 ◽  
Vol 48 (1) ◽  
pp. 119-125 ◽  
Author(s):  
T. M. Zobeck ◽  
A. Ritchie
2020 ◽  
Author(s):  
Karen Hei-Laan Yeung ◽  
Carole Helfter ◽  
Neil Mullinger ◽  
Mhairi Coyle ◽  
Eiko Nemitz

<p>Peatlands North of 45˚ represent one of the largest terrestrial carbon (C) stores. They play an important role in the global C-cycle, and their ability to sequester carbon is controlled by multiple, often competing, factors including precipitation, temperature and phenology. Land-atmosphere exchange of carbon dioxide (CO<sub>2</sub>) is dynamic, and exhibits marked seasonal and inter-annual variations which can effect the overall carbon sink strength in both the short- and long-term.</p><p>Due to increased incidences of climate anomalies in recent years, long-term datasets are essential to disambiguate natural variability in Net Ecosystem Exchange (NEE) from shorter-term fluctuations. This is particularly important at high latitudes (>45˚N) where the majority of global peatlands are found. With increasing pressure from stressors such as climate and land-use change, it has been predicted that with a ca. 3<sup>o</sup>C global temperature rise by 2100, UK peatlands could become a net source of C.</p><p>NEE of CO<sub>2</sub> has been measured using the eddy-covariance (EC) method at Auchencorth Moss (55°47’32 N, 3°14’35 W, 267 m a.s.l.), a temperate, lowland, ombrotrophic peatland in central Scotland, continuously since 2002. Alongside EC data, we present a range of meteorological parameters measured at site including soil temperature, total solar and photosynthetically active radiation (PAR), rainfall, and, since April 2007, half-hourly water table depth readings. The length of record and range of measurements make this dataset an important resource as one of the longest term records of CO<sub>2</sub> fluxes from a temperate peatland.</p><p>Although seasonal cycles of gross primary productivity (GPP) were highly variable between years, the site was a consistent CO<sub>2</sub> sink for the period 2002-2012. However, net annual losses of CO<sub>2</sub> have been recorded on several occasions since 2013. Whilst NEE tends to be positively correlated with the length of growing season, anomalies in winter weather also explain some of the variability in CO<sub>2</sub> sink strength the following summer.</p><p>Additionally, water table depth (WTD) plays a crucial role, affecting both GPP and ecosystem respiration (R<sub>eco</sub>). Relatively dry summers in recent years have contributed to shifting the balance between R<sub>eco</sub> and GPP: prolonged periods of low WTD were typically accompanied by an increase in R<sub>eco</sub>, and a decrease in GPP, hence weakening the overall CO<sub>2</sub> sink strength. Extreme events such as drought periods and cold winter temperatures can have significant and complex effects on NEE, particularly when such meteorological anomalies co-occur. For example, a positive annual NEE occurred in 2003 when Europe experienced heatwave and summer drought. More recently, an unusually long spell of snow lasting until the end of March delayed the onset of the 2018 growing season by up to 1.5 months compared to previous years. This was followed by a prolonged dry spell in summer 2018, which weakened GPP, increased R<sub>eco</sub> and led to a net annual loss of 47.4 ton CO<sub>2</sub>-C km<sup>-2</sup>. It is clear that the role of Northern peatlands within the carbon cycle is being modified, driven by changes in climate at both local and global scales.</p>


2021 ◽  
Vol 914 (1) ◽  
pp. 012037
Author(s):  
N I Fawzi ◽  
I Z Qurani ◽  
R Darajat

Abstract Conventionally, agriculture in peatland requires soil drainage to enable the crops to grow. This often results in being over-drained and makes it vulnerable to fires. The risk can be contained by applying water management trinity (WMT), which creates canals for water regulation and reservoirs instead of drainage. This study aimed to examine, elaborate, and validate the WMT effect and community involvement in minimizing fire risk in peatland. We collected water table depth every two weeks from 1 April 2017 to 31 December 2020 in a coconut plantation under WMT and employed Focus Groups Discussions (FGD) in five villages in Pulau Burung District, Indragiri Hilir Regency, Riau. The result showed that the existence of WMT for more than three decades has successfully maintained water table depth between 30 and 70 cm that is influenced by seasons. The fire occurrence based on the FGD interview has been validated with hotspot data from NASA’s FIRMS. This research also employed SWOT analysis to examine the local fire mitigation strategy. The progress in lowering fire incidents and risk should be intervened with finding long-term solutions to increase farmers’ capability on sustainable agriculture. Our finding reveals that the main strength in lowering fire risk is people’s awareness in every village on the negative impact of land burning, along with the existence of WMT.


1980 ◽  
Vol 11 (3-4) ◽  
pp. 159-168 ◽  
Author(s):  
Henrik Kærgaard

In an earlier paper I have shown an example of how long term drawdowns can be used for the computation of long term storage in artesian and semiartesian areas. In most cases the long term storage is more or less equivalent to the specific yield at the water table; the storage mechanisms of consolidation playing a minor role in long term situations. The specific yield in artesian areas is a very important parameter in the prediction of long term effects of ground water withdrawal. Especially the stream depletion will often mainly be governed by draw-downs in upper nonpumped aquifers near the water table, and these drawdowns depend to a great extent on the specific yield at the water table. A determination of long term storage will often necessitate long term draw-down data, however, under certain circumstances a determination can be made on the basis of a pumping test of limited duration (3-5 weeks) provided drawdown observations at the water table can be made. In this paper some formulas dealing with water table drawdowns in different geohydrologic systems are reviewed, and two cases in which these formulas have been used in practice are presented.


Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2148
Author(s):  
Jonathan A. Lafond ◽  
Silvio J. Gumiere ◽  
Virginie Vanlandeghem ◽  
Jacques Gallichand ◽  
Alain N. Rousseau ◽  
...  

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.


Author(s):  
Sandeep Samantaray ◽  
Abinash Sahoo

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.


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

2010 ◽  
Vol 40 (8) ◽  
pp. 1485-1496 ◽  
Author(s):  
Sakari Sarkkola ◽  
Hannu Hökkä ◽  
Harri Koivusalo ◽  
Mika Nieminen ◽  
Erkki Ahti ◽  
...  

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.


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