Modelling of shallow water table dynamics using conceptual and physically based integrated surface-water–groundwater  hydrologic models

Abstract. We present a new conceptual scheme of the interaction between unsaturated and saturated zones of the MOBIDIC (MOdello Bilancio Idrologico DIstributo e Continuo) hydrological model which is applicable to shallow water table conditions. First, MODFLOW was coupled to MOBIDIC as the physically based alternative to the conceptual groundwater component of the MOBIDIC–MODFLOW. Then, assuming a hydrostatic equilibrium moisture profile in the unsaturated zone, a dynamic specific yield that is dependent on the water table level was added to MOBIDIC–MODFLOW, and calculation of the groundwater recharge in MOBIDIC was revisited using a power-type equation based on the infiltration rate, soil moisture deficit, and a calibration parameter linked to the initial water table depth, soil type, and rainfall intensity. Using the water table fluctuation (WTF) method for a homogeneous soil column, the parameter of the proposed groundwater recharge equation was determined for four soil types, i.e. sand, loamy sand, sandy loam, and loam under a pulse of rain with different intensities. The fidelity of the introduced modifications in MOBIDIC–MODFLOW was assessed by comparison of the simulated water tables against those of MIKE SHE, a physically based integrated hydrological modelling system simulating surface and groundwater flow, in two numerical experiments: a two-dimensional case of a hypothetical watershed in a vertical plane (constant slope) under a 1 cm d−1 uniform rainfall rate and a quasi-real three-dimensional watershed under 1 month of a measured daily rainfall hyetograph. The comparative analysis confirmed that the simplified approach can mimic simple and complex groundwater systems with an acceptable level of accuracy. In addition, the computational efficiency of the proposed approach (MIKE SHE took 180 times longer to solve the three-dimensional case than the MOBIDIC–MODFLOW framework) demonstrates its applicability to real catchment case studies.

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Modelling of shallow water table dynamics using conceptual and physically based integrated surface water-groundwater hydrologic models

10.5194/hess-2018-359 ◽

2018 ◽

Author(s):

Mohammad Bizhanimanzar ◽

Robert Leconte ◽

Mathieu Nuth

Keyword(s):

Shallow Water ◽

Groundwater Recharge ◽

Water Table ◽

Sandy Loam ◽

Soil Column ◽

Vertical Plane ◽

Specific Yield ◽

Shallow Water Table ◽

Mike She ◽

Physically Based

Abstract. We present a new conceptual scheme of the interaction between unsaturated and saturated zones of the MOBIDIC (Modello Bilancio Idrologico DIstributo e Continuo) hydrological model which is applicable to shallow water table conditions. First, a hydrostatic equilibrium moisture profile was assumed for simulating changes in water table levels. This resulted in a water table based expression of specific yield, which was included in the coupled MOBIDIC-MODFLOW modelling framework for capturing shallow water tables fluctuations. Second, the groundwater recharge was defined using a power type equation based on infiltration rate, soil moisture deficit and a calibration parameter linked to initial water table level, soil type and rainfall intensity. Using the Water Table Fluctuation (WTF) method, the water table rise for a homogeneous soil column under a pulse of rain with different intensities (up to 30 mm/day) the parameter of the proposed groundwater recharge equation was determined for four soil types i.e., sand, loamy sand, sandy loam and loam. The simulated water table levels were compared against those simulated by MIKE-SHE, a physically based integrated hydrological modelling system simulating surface and groundwater flow. Two numerical experiments were carried out: a two-dimensional case of a hypothetical watershed in a vertical plane (constant slope) under a 1 cm/day uniform rainfall rate, and a quasi-real three dimensional watershed under one month of measured daily rainfall hyetograph. The comparative analysis confirmed that the simplified approach can mimic simple and complex groundwater systems with an acceptable level of accuracy. In addition, the computational efficiency of the proposed approach (MIKE-SHE took 180 times longer to solve the 3D case than the MOBIDIC-MODFLOW framework) demonstrates its applicability to real catchment case studies.

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Modelling of the shallow water table at high spatial resolution using Random Forests

10.5194/hess-2019-212 ◽

2019 ◽

Author(s):

Julian Koch ◽

Helen Berger ◽

Hans Jørgen Henriksen ◽

Torben Obel Sonnenborg

Keyword(s):

Shallow Water ◽

Water Table ◽

Spatial Resolution ◽

Random Forests ◽

Shallow Groundwater ◽

Coefficient Of Determination ◽

Shallow Water Table ◽

Simple Method ◽

Physically Based ◽

Physically Based Modelling

Abstract. Machine learning provides a great potential to model hydrological variables at a spatial resolution beyond the capabilities of traditional physically-based modelling. This study features an application of Random Forests (RF) to model the depth to the shallow water table, for a wintertime minimum event, at 50 m resolution over a 15,000 km2 large domain in Denmark. In Denmark, the shallow groundwater poses severe risks of groundwater induced flood events affecting both, urban and agricultural areas. The risk is especially critical in wintertime, when the shallow groundwater is close to terrain. In order to advance modelling capabilities of the shallow groundwater system and to provide estimates at scales required for decision making, this study introduces a simple method to unify RF and physically-based modelling. Results from the national water resources model in Denmark (DK-model) at 500 m resolution are employed as covariate in the RF model. Thereby, RF ensures physical consistency at coarse scale and fully exhausts high-resolution information from readily available environmental variables. The vertical distance to the nearest waterbody was rated the most important covariate in the trained RF model followed by the DK-model. The validation test of the trained RF model was very satisfying with a mean absolute error of 79 cm and a coefficient of determination of 0.55. The resulting map underlines the severity of groundwater flooding risk in Denmark, as the average depth to the shallow groundwater is 1.9 m and approximately 29 % of the area is characterised with a depth less than 1 m during a typical wintertime minimum event. This study brings forward a novel method to assess the spatial patterns of covariate importance of the RF predictions which contributes to an increased interpretability of the RF model. Quantifying uncertainty of RF models is still rare for hydrological applications. Two approaches, namely Random Forests Regression Kriging (RFRK) and Quantile Regression Forests (QRF) were tested to estimate uncertainties related to the predicted groundwater levels. This study argues that the uncertainty sources captured by RFRK and QRF can be considered independent and hence, they can be combined to a total variance through simple uncertainty propagation.

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Modelling of the shallow water table at high spatial resolution using random forests

Hydrology and Earth System Sciences ◽

10.5194/hess-23-4603-2019 ◽

2019 ◽

Vol 23 (11) ◽

pp. 4603-4619 ◽

Cited By ~ 5

Author(s):

Julian Koch ◽

Helen Berger ◽

Hans Jørgen Henriksen ◽

Torben Obel Sonnenborg

Keyword(s):

Shallow Water ◽

Water Table ◽

Spatial Resolution ◽

Random Forests ◽

Shallow Groundwater ◽

Coefficient Of Determination ◽

Shallow Water Table ◽

Simple Method ◽

Physically Based ◽

Physically Based Modelling

Abstract. Machine learning provides great potential for modelling hydrological variables at a spatial resolution beyond the capabilities of physically based modelling. This study features an application of random forests (RF) to model the depth to the shallow water table, for a wintertime minimum event, at a 50 m resolution over a 15 000 km2 domain in Denmark. In Denmark, the shallow groundwater poses severe risks with respect to groundwater-induced flood events, affecting both urban and agricultural areas. The risk is especially critical in wintertime, when the shallow groundwater is close to terrain. In order to advance modelling capabilities of the shallow groundwater system and to provide estimates at the scales required for decision-making, this study introduces a simple method to unify RF and physically based modelling. Results from the national water resources model in Denmark (DK-model) at a 500 m resolution are employed as covariates in the RF model. Thus, RF ensures physical consistency at a coarse scale and fully exhausts high-resolution information from readily available environmental variables. The vertical distance to the nearest water body was rated as the most important covariate in the trained RF model followed by the DK-model. The evaluation test of the trained RF model was very satisfying with a mean absolute error of 76 cm and a coefficient of determination of 0.56. The resulting map underlines the severity of groundwater flooding risk in Denmark, as the average depth to the shallow groundwater is 1.9 m and approximately 29 % of the area is characterized as having a depth of less than 1 m during a typical wintertime minimum event. This study brings forward a novel method for assessing the spatial patterns of covariate importance of the RF predictions that contributes to an increased interpretability of the RF model. Quantifying the uncertainty of RF models is still rare for hydrological applications. Two approaches, namely random forests regression kriging (RFRK) and quantile regression forests (QRF), were tested to estimate uncertainties related to the predicted groundwater levels.

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Comparison of IHM and MIKE SHE Model Performance for Modeling Hydrologic Dynamics in Shallow Water Table Settings

Vadose Zone Journal ◽

10.2136/vzj2014.03.0023 ◽

2015 ◽

Vol 14 (7) ◽

pp. vzj2014.03.0023 ◽

Cited By ~ 4

Author(s):

Jing Zhang ◽

Mark Ross

Keyword(s):

Shallow Water ◽

Water Table ◽

Model Performance ◽

Shallow Water Table ◽

Mike She

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Catchment-Scale Integrated Surface Water-Groundwater Hydrologic Modelling Using Conceptual and Physically Based Models: A Model Comparison Study

Water ◽

10.3390/w12020363 ◽

2020 ◽

Vol 12 (2) ◽

pp. 363 ◽

Cited By ~ 4

Author(s):

Mohammad Bizhanimanzar ◽

Robert Leconte ◽

Mathieu Nuth

Keyword(s):

Surface Water ◽

Groundwater Recharge ◽

Water Table ◽

Model Comparison ◽

Unsaturated Flow ◽

Regional Scale ◽

Catchment Scale ◽

Time Step ◽

Mike She ◽

Physically Based

This paper presents a comparative analysis of the use of an externally linked (MOBIDIC-MODFLOW) and a physically based (MIKE SHE) surface water-groundwater model to capture the integrated hydrologic responses of the Thomas Brook catchment, in Canada. The main objective of the study is to investigate the effect of simplification in representation of the hydrological processes in MOBIDIC-MODFLOW on its simulation accuracy. To this aim, MOBIDIC and MODFLOW were coupled in order to sequentially exchange the groundwater recharge and baseflow discharges within each computation time step. Using identical sets of hydrogeological properties for the two models, the coefficients of the gravity and capillary reservoirs in MOBIDIC were calibrated so as to closely predict the hydrological budget of the catchment simulated with MIKE SHE. The simulated results show that the two models can closely replicate the observed water table responses at two monitoring wells. However, in very shallow water table locations, the instantaneous response of the water table was not precisely captured in MOBIDIC-MODFLOW. Additionally, the simplified conceptualization of the unsaturated flow in MOBIDIC-MODFLOW resulted in overestimated groundwater recharge during spring and underestimation during summer. Moreover, the computational efficiency of MOBIDIC-MODFLOW, as compared to MIKE SHE, along with less required input data, confirms its potential for regional scale groundwater-surface water interaction modelling applications.

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