scholarly journals Temporal Variability of Water Table Depth in Topohydrosequence of Undulating Ground Moraine in Central Poland

2018 ◽  
Vol 27 (5) ◽  
pp. 2097-2106
Author(s):  
Michał Kozłowski ◽  
Jolanta Komisarek ◽  
Katarzyna Wiatrowska
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.


Agronomy ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 416
Author(s):  
Barbara Jagosz ◽  
Stanisław Rolbiecki ◽  
Roman Rolbiecki ◽  
Ariel Łangowski ◽  
Hicran A. Sadan ◽  
...  

Climate warming increases the water needs of plants. The aim of this study was to estimate the water needs of grapevines in central Poland. Water needs were calculated using the crop coefficients method. Reference evapotranspiration was assessed by the Blaney–Criddle’s equation, modified for climate conditions in Poland. Crop coefficients were assumed according to the Doorenbos and Pruitt method. Water needs were calculated using the data from four meteorological stations. Rainfall deficit with the probability occurrence of normal years, medium dry years, and very dry years was determined by the Ostromęcki’s method. Water needs of grapevines during the average growing season were estimated at 438 mm. Upward time trend in the water needs both in the period of May–October and June–August was estimated. Temporal variability in the water needs was significant for all of the provinces. These changes were mainly impacted by a significant increasing tendency in mean air temperature and less by precipitation totals that did not show a clear changing tendency. Due to climate change, vineyards will require irrigation in the near future. The use of resource-efficient irrigation requires a precise estimate of the grapevines’ water needs. The study identified the water requirements for grapevines in central Poland.


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.


2021 ◽  
Vol 131 ◽  
pp. 108122
Author(s):  
Thomas G. Sim ◽  
Graeme T. Swindles ◽  
Paul J. Morris ◽  
Andy J. Baird ◽  
Dan J. Charman ◽  
...  

2021 ◽  
Author(s):  
Michal Horsák ◽  
Veronika Horsáková ◽  
Marek Polášek ◽  
Radovan Coufal ◽  
Petra Hájková ◽  
...  

2021 ◽  
Author(s):  
Ain Kull ◽  
Iuliia Burdun ◽  
Gert Veber ◽  
Oleksandr Karasov ◽  
Martin Maddison ◽  
...  

<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>


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