Topographic and hydrogeologic controls of groundwater dynamics in generalized hydrologic landscapes with a humid climate

Author(s):  
Ezra Haaf ◽  
Alireza Kavousi ◽  
Thomas Reimann ◽  
Markus Giese ◽  
Roland Barthel

<p>The study investigates how topographic and hydrogeological properties influence groundwater dynamics. Using the concept of the fundamental hydrologic landscape (FHL; Winter, 2001), the impact of slope angle, wavelength and amplitude, as well as boundary conditions and hydraulic conductivity on groundwater dynamics is systematically assessed. This type of global sensitivity study has been done for stream flow (e.g. Carlier et al., 2019) or within groundwater focusing solely on groundwater flow and fractions of regional versus local recharge at steady state (e.g. Gleeson and Manning, 2008). In contrast, we study the influence of controls on groundwater level dynamics by using transient models. The coupled, physically based Groundwater and Surface-Water Flow simulator GSFLOW (Markstrom et al., 2008) is employed, to run a set of simulations for a FHL, where topographic and hydrogeological properties are varied across a range of possible value. The model is run at a daily time-step with climate data obtained from a measuring station in Southern Germany. Subsequently, groundwater level time series are read from the model domain across the set of simulations. These time series are decomposed into amplitude, magnitude, timing, flashiness and inter-annual variability by using dynamics indices (Heudorfer et al., 2019). Sensitivity of groundwater dynamics to the different topographic and hydrogeological controls is discussed and contrasted with the results from a prior empirical study (Haaf et al., under review). This type of global sensitivity study may aid understanding hypothesis testing of climate change impacts on groundwater level dynamics.</p><p> </p><p>Carlier C, Wirth SB, Cochand F, Hunkeler D, Brunner P. 2019. Exploring Geological and Topographical Controls on Low Flows with Hydrogeological Models. Groundwater, 57: 48-62. DOI: 10.1111/gwat.12845.<br>Gleeson T, Manning AH. 2008. Regional groundwater flow in mountainous terrain: Three-dimensional simulations of topographic and hydrogeologic controls. Water Resources Research, 44. DOI:10.1029/2008wr006848.<br>Haaf E, Giese M, Heudorfer B, Stahl K, Barthel R. Physiographic and climatic controls on groundwater dynamics on the regional scale. (under review).<br>Heudorfer B, Haaf E, Stahl K, Barthel R. 2019. Index-Based Characterization and Quantification of Groundwater Dynamics. Water Resources Research, 55: 5575-5592. DOI: 10.1029/2018wr024418.<br>Markstrom SL, Niswonger RG, Regan RS, Prudic DE, Barlow, PM. 2008. GSFLOW-Coupled Ground-water and Surface-water FLOW model based on the integration of the Precipitation-Runoff Modeling System (PRMS) and the Modular Ground-Water Flow Model (MODFLOW-2005): U.S. Geological Survey Techniques and Methods 6-D1, 240 p.<br>Winter TC. 2001. The concept of hydrologic landscapes. Journal of the American Water Resources Association, 37: 335-349. DOI: DOI 10.1111/j.1752-1688.2001.tb00973.x.</p>

2008 ◽  
Vol 349 (3-4) ◽  
pp. 524-535 ◽  
Author(s):  
Dekui Yuan ◽  
Binling Lin ◽  
Roger Falconer

2017 ◽  
Vol 8 (4) ◽  
pp. 931-949 ◽  
Author(s):  
Tongbi Tu ◽  
Ali Ercan ◽  
M. Levent Kavvas

Abstract. Groundwater closely interacts with surface water and even climate systems in most hydroclimatic settings. Fractal scaling analysis of groundwater dynamics is of significance in modeling hydrological processes by considering potential temporal long-range dependence and scaling crossovers in the groundwater level fluctuations. In this study, it is demonstrated that the groundwater level fluctuations in confined aquifer wells with long observations exhibit site-specific fractal scaling behavior. Detrended fluctuation analysis (DFA) was utilized to quantify the monofractality, and multifractal detrended fluctuation analysis (MF-DFA) and multiscale multifractal analysis (MMA) were employed to examine the multifractal behavior. The DFA results indicated that fractals exist in groundwater level time series, and it was shown that the estimated Hurst exponent is closely dependent on the length and specific time interval of the time series. The MF-DFA and MMA analyses showed that different levels of multifractality exist, which may be partially due to a broad probability density distribution with infinite moments. Furthermore, it is demonstrated that the underlying distribution of groundwater level fluctuations exhibits either non-Gaussian characteristics, which may be fitted by the Lévy stable distribution, or Gaussian characteristics depending on the site characteristics. However, fractional Brownian motion (fBm), which has been identified as an appropriate model to characterize groundwater level fluctuation, is Gaussian with finite moments. Therefore, fBm may be inadequate for the description of physical processes with infinite moments, such as the groundwater level fluctuations in this study. It is concluded that there is a need for generalized governing equations of groundwater flow processes that can model both the long-memory behavior and the Brownian finite-memory behavior.


2017 ◽  
Author(s):  
Tongbi Tu ◽  
Ali Ercan ◽  
M. Levent Kavvas

Abstract. Groundwater closely interacts with surface water and even climate systems in most hydro-climatic settings. Fractal scaling analysis of groundwater dynamics is of significance in modeling hydrological processes by considering potential temporal long-range dependence and scaling crossovers in the groundwater level fluctuations. In this study, it is demonstrated that the groundwater level fluctuations of confined aquifer wells with long observations exhibit site-specific fractal scaling behavior. Detrended fluctuation analysis (DFA) was utilized to quantify the monofractality; and Multifractal detrended fluctuation analysis (MF-DFA) and Multiscale Multifractal Analysis (MMA) were employed to examine the multifractal behavior. The DFA results indicated that fractals exist in groundwater level time series, and it was shown that the estimated Hurst exponent is closely dependent on the length and specific time interval of the time series. The MF-DFA and MMA analyses showed that different levels of multifractality exist, which may be partially due to a broad probability density distribution with infinite moments. Furthermore, it is demonstrated that the underlying distribution of groundwater level fluctuations exhibits either non-Gaussian characteristics which may be fitted by the Lévy stable distribution or Gaussian characteristics depending on the site characteristics. However, fractional Brownian motion (fBm), which has been identified as an appropriate model to characterize groundwater level fluctuation is Gaussian with finite moments. Therefore, fBm may be inadequate for the description of physical processes with infinite moments, such as the groundwater level fluctuations in this study. It is concluded that there is a need for generalized governing equations of groundwater flow processes, which can model both the long-memory behavior as well as the Brownian finite-memory behavior.


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