scholarly journals Contrasting responses of growing season ecosystem CO2exchange to variation in temperature and water table depth in two peatlands in northern Alberta, Canada

2011 ◽  
Vol 116 (G1) ◽  
Author(s):  
Angela C. Adkinson ◽  
Kamran H. Syed ◽  
Lawrence B. Flanagan
Keyword(s):  
Water Table ◽  
Growing Season ◽  
Water Table Depth ◽  
Northern Alberta

scholarly journals From sink to source: long-term (2002-2019) trends and anomalies in net ecosystem exchange of CO2 from a Scottish temperate peatland.

2020 ◽  
Author(s):  
Karen Hei-Laan Yeung ◽  
Carole Helfter ◽  
Neil Mullinger ◽  
Mhairi Coyle ◽  
Eiko Nemitz
Keyword(s):  
Water Table ◽  
Ecosystem Respiration ◽  
Net Ecosystem Exchange ◽  
Growing Season ◽  
Water Table Depth ◽  
Sink Strength ◽  
Summer Drought ◽  
C Cycle ◽  
Dry Spell

<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>

scholarly journals Modeling the irrigation requirements for an experimental site in Northern Alberta, Canada

2014 ◽  
Author(s):  
Michel Rahbeh ◽  
David Chanasyk ◽  
Shane Patterson
Keyword(s):  
Water Table ◽  
Root Zone ◽  
Winter Season ◽  
Growing Season ◽  
Annual Rainfall ◽  
Quality Model ◽  
Experimental Site ◽  
Supplementary Irrigation ◽  
Northern Alberta ◽  
Irrigation Requirements

A combined methodology of the Root Zone Water Quality Model (RZWQM), the generation of stochastic rainfall realizations, and an historical meteorological record were used to determine the supplementary irrigation requirement for an experimental site located in northern Alberta. The site receives an annual rainfall of approximately 500 mm yr -1, and contains a fluctuating water table. The simulated results showed maximum irrigation requirements of 270 mm, however, half that amount can be required during an average or wet growing season of mean rainfall of 350 and 500 mm, respectively. The irrigation requirements were influenced by rainfall amount and distribution, downward flux and the subsequent fluctuation of the water table and the depth of water table at the beginning of the growing season, which was influenced by the winter season precipitation. The simulated results suggested that a water table less than 2 m deep from the ground surface can significantly reduce the irrigation requirements. Therefore, the winter precipitation and initial depth of the water table are suitable indicators of the likely requirement of irrigation during the growing season.

scholarly journals Modeling the irrigation requirements for an experimental site in Northern Alberta, Canada

2014 ◽  
Author(s):  
Michel Rahbeh ◽  
David Chanasyk ◽  
Shane Patterson
Keyword(s):  
Water Table ◽  
Root Zone ◽  
Winter Season ◽  
Growing Season ◽  
Annual Rainfall ◽  
Quality Model ◽  
Experimental Site ◽  
Supplementary Irrigation ◽  
Northern Alberta ◽  
Irrigation Requirements

A combined methodology of the Root Zone Water Quality Model (RZWQM), the generation of stochastic rainfall realizations, and an historical meteorological record were used to determine the supplementary irrigation requirement for an experimental site located in northern Alberta. The site receives an annual rainfall of approximately 500 mm yr -1, and contains a fluctuating water table. The simulated results showed maximum irrigation requirements of 270 mm, however, half that amount can be required during an average or wet growing season of mean rainfall of 350 and 500 mm, respectively. The irrigation requirements were influenced by rainfall amount and distribution, downward flux and the subsequent fluctuation of the water table and the depth of water table at the beginning of the growing season, which was influenced by the winter season precipitation. The simulated results suggested that a water table less than 2 m deep from the ground surface can significantly reduce the irrigation requirements. Therefore, the winter precipitation and initial depth of the water table are suitable indicators of the likely requirement of irrigation during the growing season.

scholarly journals Quantitative Estimation of Soil-Ground Water Storage Utilization during the Crop Growing Season in Arid Regions with Shallow Water Table Depth

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3351
Author(s):  
Tianxing Zhao ◽  
Yan Zhu ◽  
Jingwei Wu ◽  
Ming Ye ◽  
Wei Mao ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Ground Water ◽  
Shallow Water ◽  
Water Table ◽  
Soil Moisture Content ◽  
Water Storage ◽  
Growing Season ◽  
Water Table Depth ◽  
Arid Areas ◽  
Shallow Water Table

Water storage in unsaturated and saturated zones during the crop non-growing season is one of the important supplementary water resources to meet crop water requirements in arid areas with shallow water table depth. It is necessary to analyze utilization of the soil-ground water storage during the crop growing season and its attribution to irrigation during the non-growing season. To facilitate the analysis, a new method based on measurements of soil moisture content and water table depth is developed. The measurements used in this study include (1) 15-year data of soil moisture content within a depth of 1 m from the land surface and water table depth measured in Jiefangzha, including its four subareas and (2) 4-year data of the same kind in Yonglian, located in arid northern China. The soil-ground water storage utilization is calculated as the difference of water storage between the beginning and end of the crop growing season in the whole computational soil profile. The results of average soil-ground water storage utilization in Jiefangzha and its four subareas and Yonglian are 121 mm, 126 mm, 113 mm, 124 mm, 185 mm and 117 mm, and the corresponding average utilization efficiencies in the non-growing season are 32.2%, 32.5%, 31.5%, 31.6%, 57.3% and 47.6%, respectively. Further, the water table fluctuation method was used to estimate the variation in water storage. The coefficients of soil-ground water storage utilization, soil-ground water storage utilization below 1 m soil depth and ground water utilization are defined, and their average values are 0.271, 0.111 and 0.026 in Jiefangzha, respectively. Then, the contribution of soil-ground water storage utilization to actual evapotranspiration is evaluated, which are over 23.5% in Jiefangzha and Yonglian. These results indicate that the soil-ground water storage plays an important role in the ecological environment in arid areas with shallow water table depth.

scholarly journals Performance of weather parameters in predicting growing season water table depth variations on drained forested peatlands – a case study from southern Finland

Silva Fennica ◽  
2016 ◽  
Vol 50 (4) ◽  
Author(s):  
Hannu Hökkä ◽  
Jori Uusitalo ◽  
Harri Lindeman ◽  
Jari Ala-Ilomäki
Keyword(s):  
Water Table ◽  
Growing Season ◽  
Water Table Depth ◽  
Weather Parameters

scholarly journals Modeling the irrigation requirements for an experimental site in Northern Alberta, Canada

2014 ◽  
Author(s):  
Michel Rahbeh ◽  
David Chanasyk ◽  
Shane Patterson
Keyword(s):  
Water Table ◽  
Root Zone ◽  
Winter Season ◽  
Growing Season ◽  
Annual Rainfall ◽  
Quality Model ◽  
Experimental Site ◽  
Supplementary Irrigation ◽  
Northern Alberta ◽  
Irrigation Requirements

A combined methodology of the Root Zone Water Quality Model (RZWQM), the generation of stochastic rainfall realizations, and an historical meteorological record were used to determine the supplementary irrigation requirement for an experimental site located in northern Alberta. The site receives an annual rainfall of approximately 500 mm yr -1, and contains a fluctuating water table. The simulated results showed maximum irrigation requirements of 270 mm, however, half that amount can be required during an average or wet growing season of mean rainfall of 350 and 500 mm, respectively. The irrigation requirements were influenced by rainfall amount and distribution, downward flux and the subsequent fluctuation of the water table and the depth of water table at the beginning of the growing season, which was influenced by the winter season precipitation. The simulated results suggested that a water table less than 2 m deep from the ground surface can significantly reduce the irrigation requirements. Therefore, the winter precipitation and initial depth of the water table are suitable indicators of the likely requirement of irrigation during the growing season.

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.

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