Using Isomap to differentiate between anthropogenic and natural effects on groundwater dynamics in a complex geological setting

Böttcher, Steven; Merz, Christoph; Lischeid, Gunnar; Dannowski, Ralf

doi:10.1016/j.jhydrol.2014.09.048

Cited by 12 publications

(8 citation statements)

References 23 publications

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“…Five wells, coloured in light blue, plot close to a common regression line (r 2 = 0.957). This is a typical phenomenon often found: Damping usually clearly increases with depth for soil hydrological time series (Hohenbrink and Lischeid 2015;Lischeid et al 2017), and correspondingly damping of time series of groundwater head increases with thickness of the overlying vadose zone in unconfined aquifers (Lischeid et al 2010;Böttcher et al 2014).…”

Section: Groundwater Datamentioning

confidence: 77%

“…Principal component analysis has been used in hydrology for many decades but has only rarely been applied to time series, in contrast to other disciplines like climatology. However, it has proven to be a powerful tool to identify and to quantify the impact of river water stage on riparian groundwater head (Lehr et al 2015), of groundwater production wells on adjacent lakes (Böttcher et al 2014), of different crops and tillage practices on soil water content (Hohenbrink et al 2016), or of climatic gradients on stream discharge (Thomas et al 2012). Application of PCA on a data set comprising soil matrix potential, groundwater head and stream discharge nicely illustrated the hydrological continuum within a catchment (Lischeid et al 2017).…”

Section: Principal Component Analysis Of Hydrological Time Seriesmentioning

confidence: 99%

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Forensic hydrology: what function tells about structure in complex settings

et al. 2016

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Facing the challenges of the European Water Framework Directive and competing demands requires a sound knowledge of the hydrological system. This is a major challenge in regions like Northeast Germany. The landscape has been massively reshaped during repeated advances and retreats of glaciation during the Pleistocene. This resulted in a complex setting of unconsolidated sediments with high textural heterogeneity and with layered aquifer systems, partly confined, but usually of unknown number and extent of single aquifers. The Institute of Landscape Hydrology aims both at a better understanding of hydrological processes and at providing a basis for sustainable water resources management in this region. That would require sound information about the respective regions of interest that are rarely available at sufficient degree of detail. Thus, there is urgent need for alternative approaches. For example, time series of groundwater head, lake water level and stream runoff do not only depend on (unknown) geological structures, but in turn can reveal information about major geological features. To that end, different approaches have been developed and successfully applied at different scales, based both on advanced time series analysis and dimension reduction approaches and on well-known and rather simple methods. This approach has been coined ''forensic hydrology'': Like in a crime story, numerous pieces of evidence are combined in a systematic way to end up with a consistent conceptual model about the prevailing cause-effect relationships. An example is given for the Quillow catchment in Northeast Germany in a rather complex geological setting.

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Section: Groundwater Datamentioning

confidence: 77%

Section: Principal Component Analysis Of Hydrological Time Seriesmentioning

confidence: 99%

Forensic hydrology: what function tells about structure in complex settings

et al. 2016

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“…However, the transferability of their results from a “simulated world” to the “real world” still has to be proven based on soil moisture time series measured under field conditions. In fact, that approach has already been successfully applied to groundwater head time series (Böttcher et al, 2014; Lehr et al, 2015; Lischeid et al, 2010; Page et al, 2012).…”

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confidence: 99%

Disentangling the Effects of Land Management and Soil Heterogeneity on Soil Moisture Dynamics

Hohenbrink

Lischeid

Schindler

et al. 2016

Vadose Zone Journal

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Soil moisture is the essential control of water and energy dynamics at arable sites. Time series of soil moisture reflect the interplay of various processes, each of which influences the overall soil moisture dynamics. In this study we tested an approach to break down observed soil moisture behavior into the respective contributions of individual processes. We applied a principal component analysis to soil moisture time series from a field experiment comprising two crop rotation systems and two different soil tillage practices. We concentrated on 57 soil moisture time series measured over nearly 4 yr at 12 plots and five soil depths, down to 1.5 m. About 77.9% of the variance was reflected by the first component being almost identical to a time series of averaged soil moisture. It described the effect of the meteorological boundary conditions. The second component described the effect of the input signal damping increasing with soil depth and accounted for 7.8% of total variance. The signal transformation over depth proved to be more or less uniform throughout the test site, despite considerable soil heterogeneity. Another 3.6% of the total variance (third component) was unambiguously explained by the different cropping systems. On the contrary, different soil tillage practices had no significant effect. The suggested approach opens up many possibilities to analyze and better understand complex soil system behavior. The data-based approach of time series analysis provides modelindependent, quantitative information about the key factors and processes controlling soil water dynamics. Hence, it is especially valuable for model building, calibration, and evaluation.

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“…Instead, processes identified by PCA help to constrain the structure of process based models right from the beginning of the modeling process. In fact, that approach has been successful in analyzing groundwater head data (Böttcher et al, 2014;Lewandowski et al, 2009) as well as discharge data (Thomas et al, 2012).…”

Section: Potential Fields Of Applicationmentioning

confidence: 99%