Investigating soil and groundwater quality at different scales in a forested catchment: The Waldstein case study

G. Lischeid, C. Alewell, J. Bittersohl, A. Göttlein, C. Jungnickel, H. Lange, B. Manderscheid, K. Moritz, B. Ostendorf, H. Sager

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

The impact of anthropogenic depositions on soil and groundwater quality has been the subject of numerous studies in the last two decades. However, the problem of linking results and models at different scales remains to be solved. A case study has been performed in the Fichtelgebirge region in South-East Germany. Data from this case study has been used to analyse scale dependences of spatial variance, autocorrelation lengths, and the interdependence of soil hydrological and soil chemical parameters. For soil suction, spatial variability increases stepwise with scale. Three different sources of variation could be identified, predominating at different ranges of scale, making a deterministic mapping feasible. Local SO4 deposition explained much of the spatial pattern of SO4 concentration in soil solution and in catchment runoff observed at different scales. This is mainly due to the fact that the sorption capacity of the soils in this region has been exceeded. Decreasing SO4 deposition in the long term run is likely to enhance the influence of the soil, and reduces the correlation between deposition and soil solution concentration. NO3 showed minimum variation at the county scale. This seems to be a reasonable representative elementary area for mapping regional NO3 concentration patterns. For protons and CI, neither observed spatial patterns nor the scale dependence of spatial heterogeneity could be explained adequately.

Original languageEnglish
Pages (from-to)109-118
Number of pages10
JournalNutrient Cycling in Agroecosystems
Volume50
Issue number1-3
DOIs
StatePublished - 1998
Externally publishedYes

Keywords

  • Deterministic length scale
  • Hydrology
  • Representative elementary volume
  • Soil chemistry
  • Spatial correlation
  • Spatial variance

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