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- Barthel, Roland, 1967, et al.
(författare)
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Systematic visual analysis of groundwater hydrographs: potential benefits and challenges
- 2022
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Ingår i: Hydrogeology Journal. - : Springer Science and Business Media LLC. - 1431-2174 .- 1435-0157. ; 30, s. 359-78
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Tidskriftsartikel (refereegranskat)abstract
- Visual analysis of time series in hydrology is frequently seen as a crucial step to becoming acquainted with the nature of the data, as well as detecting unexpected errors, biases, etc. Human eyes, in particular those of a trained expert, are well suited to recognize irregularities and distinct patterns. However, there are limits as to what the eye can resolve and process; moreover, visual analysis is by definition subjective and has low reproducibility. Visual inspection is frequently mentioned in publications, but rarely described in detail, even though it may have significantly affected decisions made in the process of performing the underlying study. This paper presents a visual analysis of groundwater hydrographs that has been performed in relation to attempts to classify groundwater time series as part of developing a new concept for prediction in data-scarce groundwater systems. Within this concept, determining the similarity of groundwater hydrographs is essential. As standard approaches for similarity analysis of groundwater hydrographs do not yet exist, different approaches were developed and tested. This provided the opportunity to carry out a comparison between visual analysis and formal, automated classification approaches. The presented visual classification was carried out on two sets of time series from central Europe and Fennoscandia. It is explained why and where visual classification can be beneficial but also where the limitations and challenges associated with the approach lie. It is concluded that systematic visual analysis of time series in hydrology, despite its subjectivity and low reproducibility, should receive much more attention.
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| 2. |
- Haaf, Ezra, 1985, et al.
(författare)
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Data-driven Estimation of Groundwater Level Time-Series Using Comparative Regional Analysis
- 2022
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- A new method is presented to efficiently estimate daily groundwater level time series at unmonitored sites by linking groundwater dynamics to local hydrogeological system controls. The presented approach is based on the concept of comparative regional analysis, an approach widely used in surface water hydrology, but uncommon in hydrogeology. The method uses regression analysis to estimate cumulative frequency distributions of groundwater levels (groundwater head duration curves (HDC)) at unmonitored locations using physiographic and climatic site descriptors. The HDC is then used to construct a groundwater hydrograph using time series from distance-weighted neighboring monitored (donor) locations. For estimating times series at unmonitored sites, in essence, spatio-temporal interpolation, stepwise multiple linear regression, extreme gradient boosting, and nearest neighbors are compared. The methods were applied to ten-year daily groundwater level time series at 157 sites in alluvial unconfined aquifers in Southern Germany. Models of HDCs were physically plausible and showed that physiographic and climatic controls on groundwater level fluctuations are nonlinear and dynamic, varying in significance from “wet” to “dry” aquifer conditions. Extreme gradient boosting yielded a significantly higher predictive skill than nearest neighbor and multiple linear regression. However, donor site selection is of key importance. The study presents a novel approach for regionalization and infilling of groundwater level time series that also aids conceptual understanding of controls on groundwater dynamics, both central tasks for water resources managers.
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