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.

Effect of forest drainage on the peat bulk density of pine mires in Finland

1998 ◽  
Vol 28 (2) ◽  
pp. 178-186 ◽  
Author(s):  
Kari Minkkinen ◽  
Jukka Laine
Keyword(s):  
Organic Matter ◽  
Bulk Density ◽  
Nutrient Status ◽  
Climatic Conditions ◽  
Tree Stand ◽  
Stand Volume ◽  
Peat Surface ◽  
The Mean ◽  
Forest Drainage ◽  
Site Types

Drainage of peatlands for forestry causes the water level to draw down, which results in subsidence of peat surface and increased peat bulk density (Db). Later on, an accelerated rate of organic matter decomposition and the pressure of the growing tree stand further compacts the peat. We measured the peat Db (0-80 cm) in 180 undrained and 209 drained (ca. 60-year-old) peatland sites representing three nutrient levels of pine fens and five macroclimatic regions from southern to northern Finland. Db was affected by climatic conditions, nutrient status, and the tree stand volume of the site. Db was significantly higher in drained than in undrained sites in all regions and site types: the mean (±SD) Db in the whole material was 82 ± 23 kg ·m-3 for the undrained sites and 133 ± 22 kg ·m-3 for the drained sites. The increase in Db was significant in all regions down to a depth of 60 cm and in southern Finland, even deeper than 80 cm. When the increase in carbon concentration was taken into consideration, the average postdrainage increase in the Db of the 0-80 cm layer equalled the amount of carbon in the 54-cm layer in average undrained peat. As the reported subsidences of peat surface in forest drainage areas in Finland are usually below this limit, the carbon storage of peat is likely to increase after drainage.

scholarly journals CADANGAN, KEHILANGAN, DAN AKUMULASI KARBON PADA PERKEBUNAN KELAPA SAWIT DI LAHAN GAMBUT TROPIKA

Jurnal Solum ◽  
2011 ◽  
Vol 8 (1) ◽  
pp. 1
Author(s):  
Maswar Maswar ◽  
Oteng Haridjaja ◽  
Supiandi Sabiham ◽  
Meine Van Noordwijk
Keyword(s):  
Bulk Density ◽  
Water Table ◽  
Oil Palm ◽  
Carbon Stocks ◽  
Ash Content ◽  
Water Table Depth ◽  
Carbon Accumulation ◽  
Carbon Loss ◽  
Litter Bags ◽  
Oil Palm Plantation

Peat land conversion to oil palm plantation affects carbon stocks and can change a net sink of atmospheric carbon (C) into a net source. The influence of location, type of peat, drainage practices and fertilization is insufficiently known. A study was conducted in West Aceh from May 2008 until October 2009  in oil palm plantations of various age.  Carbon stocks and  C loss were calculated from data of bulk density (BD), ash content, carbon content, and peat depth. A new method for C loss estimates using ash as internal tracer was developed and tested. Peat land characteristics after drainage and conversion to oil palm plantation were investigated by field observation and laboratory analysis of peat soil samples in the laboratory. Results showed that: 1) Distance from the drain influences the rates of: a) water table depth, b) subsidence, with rates of 1,1  to 9,2 cm/year and 22.67 – 57.23% influence of C loss, and c) soil carbon loss. 2) Ash content and bulk density of the peat are related, indicating the partial loss of soil C during compaction. 3) An “internal tracer” estimate of peat C loss yields estimates of CO2 flux up to 48 t CO2-eq ha-1 y-1 for young oil palm, highly correlated with measured rates of subsidence of the surface and water table depth. 4) Patterns of weight loss of surface litter, measured in litter bags, respond to inherent quality (C/N). Some data for oil palm on shallow peat suggest that a net sink for C can be maintained under such conditions.Key words: Carbon stock, carbon loss, carbon accumulation,  oil palm, tropical peat

Environmental and biotic controls on bryophyte productivity along forest to peatland ecotones

2007 ◽  
Vol 85 (5) ◽  
pp. 463-475 ◽  
Author(s):  
Ilka E. Bauer ◽  
Diana Tirlea ◽  
Jagtar S. Bhatti ◽  
Ruth C. Errington
Keyword(s):  
Bulk Density ◽  
Water Table ◽  
Canopy Cover ◽  
Biotic Interactions ◽  
Environmental Variation ◽  
Water Table Depth ◽  
Tree Canopy ◽  
Total Biomass ◽  
Tree Canopy Cover ◽  
Length Increment

Bryophyte growth and production can be critical measurements in quantifying carbon input into peatlands. For any species, total biomass produced in a given year is determined by three main factors: abundance of the species, bulk density, and annual (length) increment. We examined the relationship of these parameters to environmental factors (water table depth, tree canopy cover) and biotic interactions (presence of other species) in seven common peatland bryophytes. Correlations suggest that bulk density changed in response to environmental variation in Sphagnum angustifolium (C. Jens. ex Russ.) C. Jens. in Tolf, Sphagnum fuscum (Schimp.) Klinggr., and Aulacomnium palustre (Hedw.) Schwaegr., and it remained constant in Pleurozium schreberi (Brid.) Mitt., Hylocomium splendens (Hedw.) Schimp. in B.S.G., Tomenthypnum nitens (Hedw.) Loeske, and Hamatocaulis vernicosus (Mitt.) Hedenäs. Length increment was dependent on water table depth in S. angustifolium, P. schreberi, and Hamatocaulis vernicosus, and changed with canopy cover in H. splendens at one of two sites examined. Overall, our results suggest that (i) in some species, changes in bulk density are likely to be an important component of changes in productivity in response to environmental variation; (ii) local vigour tends to increase with abundance, but may not do so in all cases; and (iii) phenomena such as biotic interactions and environmental extremes may lead to non-linearity of productivity responses to environmental change.

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

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
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