Hydrogeological, topographical and drain factors controlling water table depth variation and potential nitrate reduction in subsurface drained clayey till area

2021 ◽  
Author(s):  
Hafsa Mahmood ◽  
Rasmus Rumph Frederiksen
Keyword(s):  
Boundary Conditions ◽  
Water Table ◽  
Nitrate Reduction ◽  
Hydraulic Properties ◽  
Root Zone ◽  
Water Table Depth ◽  
Geophysical Data ◽  
N Retention ◽  
Depth Variation ◽  
Drain Flow

<p>Nutrient losses in agricultural areas have detrimental effects not only on the surface water quality but are also unfavorable for sustainable agriculture practices. In Denmark, there are currently nitrate regulations applied for ID15 catchments (15 square km scale), nevertheless, it is crucial to know how much nitrogen is retained in the root zone, saturated zone, riparian zone as N-retention varies widely within ID15 catchments. Currently, N-retention mapping does not incorporate N-retention in the root zone on ID15 scale. N-retention in the root zone of subsurface drained clayey areas is potentially influenced by the variation in water table depth. Therefore, we will evaluate the effect of shallow hydrogeology, topography and drain parameters on local (sub-field scale) water table depth variation using a case study in eastern Jutland, Denmark.</p><p>The aim of the study was to assess which hydrogeological variables, drain parameters and topographical variables control water table depth variation in the root zone. This analysis was aided by a groundwater flow model code (MODFLOW). For the following purpose, hydrological data (drain flow at the outlet and depth to the water table in piezometers) and geophysical data (subsurface electrical conductivity) were collected. The geophysical data was collected by two ground-based electromagnetic systems (DUALEM and tTEM). The electrical conductivities were directly translated into two zones of homogeneous hydraulic conductivities based on a threshold value. Hydraulic properties were varied for each zone. Areas with no geophysical data were simulated using Direct Sampling, a Multi Points Statistics method. We generated several flow models, which had a varying spatial distribution of hydraulic zones and varying hydraulic properties (input factors). Moreover, boundary conditions (lateral fluxes), topographical smoothing and drain parameters (drain conductance and drain depths) were some of the other input factors we considered in this work. Model boundary conditions data were obtained from the national hydrological model. The variation in input factors was related to variation in simulated water table depths and drain flow at the outlet using a one-at-a-time sensitivity analysis.</p><p>Drain flow fraction, depth to the water table and drain discharge are analyzed as the quantity of interest for both wet and dry periods. Drain fraction is calculated as the ratio of the area contributing to the drainage to the area contributing to the recharge within the same area. The results will discover crucial controlling components of water table depth with which variations in N-retention can be estimated between different fields. The emphasis is to discover the connection between hydrogeological, topographical, and drain variables, and water table depth. We will examine potential implications for evaluating drain fraction and potential nitrate reduction.</p>

Estimating drain flow from measured water table depth in layered soils under free and controlled drainage

2018 ◽  
Vol 556 ◽  
pp. 339-348 ◽  
Author(s):  
Samaneh Saadat ◽  
Laura Bowling ◽  
Jane Frankenberger ◽  
Eileen Kladivko
Keyword(s):  
Water Table ◽  
Water Table Depth ◽  
Controlled Drainage ◽  
Layered Soils ◽  
Drain Flow ◽  
Measured Water

scholarly journals Temporal water table changes in soil toposequence of the Poznań Lakeland (western Poland)

2017 ◽  
Vol 68 (4) ◽  
pp. 167-173
Author(s):  
Michał Kozłowski ◽  
Jolanta Komisarek
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Water Table ◽  
Root Zone ◽  
Linear Regression Analysis ◽  
Temporal Trends ◽  
Water Table Depth ◽  
The Mean ◽  
The Impact

Abstract The paper presents results of determination of temporal changes in water table depths in the toposequence of Retisols/Luvisols and Phaeozems/Gleysols. Assessment of temporal trends in the water table depth was made with the use of the linear regression analysis. The results obtained indicate that the mean water table depth and mean high and low water table depths were deeper in the soil at the upper part of the slope in comparison with soil located at the footslope. A higher amplitude of water table was observed in Retisols than in Gleysols but the highest variability of water table level was noted in the soils at the footslope compared to those at the slope summit. In Retisols, with each month of observation from 1993 to 2012, the water table showed a tendency to increase. These trends were the highest from January to April, which may be related to the tendency of increasing monthly sums of precipitation in December, January and February. In the Gleysol at the footslope, in the period 1993–2012 and in the vegetation season, the water table depth showed a tendency to decrease. This trend may be due to the impact of water table on the soil water content at the root zone, which is used in the process of evapotranspiration.

scholarly journals Large-scale regionalization of water table depth in peatlands optimized for greenhouse gas emission upscaling

2014 ◽  
Vol 18 (9) ◽  
pp. 3319-3339 ◽  
Author(s):  
M. Bechtold ◽  
B. Tiemeyer ◽  
A. Laggner ◽  
T. Leppelt ◽  
E. Frahm ◽  
...  
Keyword(s):  
Land Cover ◽  
Boundary Conditions ◽  
Water Level ◽  
Water Table ◽  
Ghg Emissions ◽  
Water Table Depth ◽  
Water Levels ◽  
Predictor Variables ◽  
Organic Soils ◽  
Depth Information

Abstract. Fluxes of the three main greenhouse gases (GHG) CO2, CH4 and N2O from peat and other soils with high organic carbon contents are strongly controlled by water table depth. Information about the spatial distribution of water level is thus a crucial input parameter when upscaling GHG emissions to large scales. Here, we investigate the potential of statistical modeling for the regionalization of water levels in organic soils when data covers only a small fraction of the peatlands of the final map. Our study area is Germany. Phreatic water level data from 53 peatlands in Germany were compiled in a new data set comprising 1094 dip wells and 7155 years of data. For each dip well, numerous possible predictor variables were determined using nationally available data sources, which included information about land cover, ditch network, protected areas, topography, peatland characteristics and climatic boundary conditions. We applied boosted regression trees to identify dependencies between predictor variables and dip-well-specific long-term annual mean water level (WL) as well as a transformed form (WLt). The latter was obtained by assuming a hypothetical GHG transfer function and is linearly related to GHG emissions. Our results demonstrate that model calibration on WLt is superior. It increases the explained variance of the water level in the sensitive range for GHG emissions and avoids model bias in subsequent GHG upscaling. The final model explained 45% of WLt variance and was built on nine predictor variables that are based on information about land cover, peatland characteristics, drainage network, topography and climatic boundary conditions. Their individual effects on WLt and the observed parameter interactions provide insight into natural and anthropogenic boundary conditions that control water levels in organic soils. Our study also demonstrates that a large fraction of the observed WLt variance cannot be explained by nationally available predictor variables and that predictors with stronger WLt indication, relying, for example, on detailed water management maps and remote sensing products, are needed to substantially improve model predictive performance.

scholarly journals Large-scale regionalization of water table depth in peatlands optimized for greenhouse gas emission upscaling

2014 ◽  
Vol 11 (4) ◽  
pp. 3857-3909 ◽  
Author(s):  
M. Bechtold ◽  
B. Tiemeyer ◽  
A. Laggner ◽  
T. Leppelt ◽  
E. Frahm ◽  
...  
Keyword(s):  
Land Cover ◽  
Boundary Conditions ◽  
Water Level ◽  
Water Table ◽  
Ghg Emissions ◽  
Water Table Depth ◽  
Water Levels ◽  
Predictor Variables ◽  
Organic Soils ◽  
Depth Information

Abstract. Fluxes of the three main greenhouse gases (GHG) CO2, CH4 and N2O from peat and other organic soils are strongly controlled by water table depth. Information about the spatial distribution of water level is thus a crucial input parameter when upscaling GHG emissions to large scales. Here, we investigate the potential of statistical modeling for the regionalization of water levels in organic soils when data covers only a small fraction of the peatlands of the final map. Our study area is Germany. Phreatic water level data from 53 peatlands in Germany were compiled in a new dataset comprising 1094 dip wells and 7155 years of data. For each dip well, numerous possible predictor variables were determined using nationally available data sources, which included information about land cover, ditch network, protected areas, topography, peatland characteristics and climatic boundary conditions. We applied boosted regression trees to identify dependencies between predictor variables and dip well specific long-term annual mean water level (WL) as well as a transformed form of it (WLt). The latter was obtained by assuming a hypothetical GHG transfer function and is linearly related to GHG emissions. Our results demonstrate that model calibration on WLt is superior. It increases the explained variance of the water level in the sensitive range for GHG emissions and avoids model bias in subsequent GHG upscaling. The final model explained 45% of WLt variance and was built on nine predictor variables that are based on information about land cover, peatland characteristics, drainage network, topography and climatic boundary conditions. Their individual effects on WLt and the observed parameter interactions provide insights into natural and anthropogenic boundary conditions that control water levels in organic soils. Our study also demonstrates that a large fraction of the observed WLt variance cannot be explained by nationally available predictor variables and that predictors with stronger WLt indication, relying e.g. on detailed water management maps and remote sensing products, are needed to substantially improve model predictive performance.

scholarly journals ESTIMATIVA DE FLUXO DE DRENAGEM E ALTURA DE LENÇOL FREÁTICO EM SOLOS DE TEXTURAS DISTINTAS

Irriga ◽  
2018 ◽  
Vol 1 (1) ◽  
pp. 70 ◽  
Author(s):  
Pedro Ramualyson Fernandes Sampaio ◽  
Eder Duarte Fanaya Junior ◽  
José Leôncio de Almeida Silva ◽  
Jarbas Honorio de Miranda ◽  
Sergio Nascimento Duarte
Keyword(s):  
Zea Mays ◽  
Water Table ◽  
Drainage System ◽  
Water Table Depth ◽  
Annual Rainfall ◽  
Silty Clay ◽  
Drainage Flow ◽  
Initial Water ◽  
Drain Spacing ◽  
Drain Flow

ESTIMATIVA DE FLUXO DE DRENAGEM E ALTURA DE LENÇOL FREÁTICO EM SOLOS DE TEXTURAS DISTINTAS  PEDRO RAMUALYSON FERNANDES SAMPAIO1; EDER DUARTE FANAYA JÚNIOR1; JOSÉ LEÔNCIO DE ALMEIDA SILVA2; JARBAS HONORIO DE MIRANDA3 E SERGIO NASCIMENTO DUARTE3 1Engenheiro Agrônomo, Doutorando, Escola Superior de Agricultura “Luiz de Queiroz”/ESALQ-USP, Programa de Pós-Graduação em Engenharia de Sistemas Agrícolas, Av. Pádua Dias, 11 - São Dimas, 13418-900, Piracicaba - SP, Brasil, [email protected]; [email protected] Agrônomo, Doutorando, Universidade Federal de Viçosa/UFV, Programa de Pós-Graduação em Engenharia Agrícola, Av. Peter Henry Rolfs, s/n, Campus Universitário, Viçosa – MG, CEP: 36570-900, Brasil, [email protected] Agrônomo, Doutor, Professor Associado, Escola Superior de Agricultura “Luiz de Queiroz”/ESALQ-USP, Programa de Pós-Graduação em Engenharia de Sistemas Agrícolas, Av. Pádua Dias, 11 - São Dimas, 13418-900, Piracicaba - SP, Brasil, [email protected]; [email protected]  1 RESUMO O excesso de água no solo, devido aos altos níveis estacionais ou periódicos do lençol freático, tem-se constituído no principal risco para limitar a produtividade das culturas, e a sua profundidade influi indiretamente no crescimento e no desenvolvimento vegetal, influenciando às condições de umidade do perfil, de aeração e propriedades térmicas do solo. O presente trabalho teve como objetivo estudar o comportamento do lençol freático e o fluxo de drenos, em cinco anos extremos, que apresentam baixa, média e elevada pluviosidade anual, na cidade de Piracicaba-SP. O estudo foi realizado utilizando o software de Sistema de Drenagem - SISDRENA. Foram avaliados uma série temporal de cinco anos, com pluviosidade média anual abaixo, próxima e acima da média histórica para a cidade de Piracicaba, SP, Brasil. A partir destes anos, realizou-se a estimativa da altura do lençol freático e do fluxo de drenagem para cada um desses períodos, em cada tipo de solo estudado, com texturas Franco-argilosa, Argilosa e Franco-argilo-Siltosa. Foram realizadas simulações com diferentes espaçamentos entre drenos, variando de 10 a 100 m, a uma altura inicial de 0,55 m, para a cultura do milho (Zea mays). Em solos com menor coeficiente de drenagem, ocorre a diminuição do fluxo de drenagem a partir do espaçamento de 20 m. Em períodos chuvosos, com elevada pluviosidade anual, ocorreu uma maior altura do lençol freático para os três tipos de texturas de solos estudados. Palavras-chave: Irrigação; Sisdrena; Infiltração.  P. R. F. SAMPAIO1; E. D. FANAYA JÚNIOR1; J. L. DE A. SILVA2; J. H. DE MIRANDA3; S. N. DUARTE3ESTIMATING DRAINAGE FLOW AND WATER TABLE DEPTH FOR YEARS WITH LOW MEDIUM AND HIGH RAINFALL    2 ABSTRACT Excessive water in the soil, due to seasonally or periodically high water table levels, is often the main factor limiting crop yield. Water table depth can indirectly affect plant growth and development, due to adverse moisture, aeration soil and thermal conditions in the soil profile. The aim of this study was to evaluate the water table depth and the drain flow for five year periods with low, medium and high annual rainfall. The study was conducted using the Drainage System software - SISDRENA. Water table depth and drainage flow were simulated in three soils (Franco-clay, clay and Franco-silty-clay) for each one of these periods. Simulations were performed for maize (Zea mays), with drain spacing ranging from 10 to 100 m and an initial water table height of 0.55 m. In soils with lower drainage coefficient, there was decreased drain flow when the drain spacing exceeded 20m. During rainy periods, with a high annual rainfall rate, the water table was elevated in all three soil types. Keywords: Irrigation; Sisdrena; Infiltration.

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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