Detecting dominant changes in irregularly sampled multivariate water quality data sets

被引:2
|
作者
Lehr, Christian [1 ,2 ]
Dannowski, Ralf [1 ]
Kalettka, Thomas [1 ]
Merz, Christoph [1 ,3 ]
Schroeder, Boris [4 ,5 ]
Steidl, Joerg [1 ]
Lischeid, Gunnar [1 ,2 ]
机构
[1] Leibniz Ctr Agr Landscape Res ZALF, Muncheberg, Germany
[2] Univ Potsdam, Inst Earth & Environm Sci, Potsdam, Germany
[3] Free Univ Berlin, Inst Geol Sci, Workgrp Hydrogeol, Berlin, Germany
[4] Tech Univ Carolo Wilhelmina Braunschweig, Inst Geoecol, Landscape Ecol & Environm Syst Anal, Langer Kamp 19c, D-38106 Braunschweig, Germany
[5] Berlin Brandenburg Inst Adv Biodivers Res BBIB, Altensteinstr 6, D-14195 Berlin, Germany
关键词
NONLINEAR DIMENSIONALITY REDUCTION; LOCALLY WEIGHTED REGRESSION; TIME-SERIES ANALYSIS; HIGH-FREQUENCY WAVE; AGRICULTURAL CATCHMENTS; SOLUTE TRANSPORT; STREAM CHEMISTRY; GROUNDWATER; DYNAMICS; AQUIFER;
D O I
10.5194/hess-22-4401-2018
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Time series of groundwater and stream water quality often exhibit substantial temporal and spatial variability, whereas typical existing monitoring data sets, e.g. from environmental agencies, are usually characterized by relatively low sampling frequency and irregular sampling in space and/or time. This complicates the differentiation between anthropogenic influence and natural variability as well as the detection of changes in water quality which indicate changes in single drivers. We suggest the new term "dominant changes" for changes in multivariate water quality data which concern (1) multiple variables, (2) multiple sites and (3) long-term patterns and present an exploratory framework for the detection of such dominant changes in data sets with irregular sampling in space and time. Firstly, a non-linear dimension-reduction technique was used to summarize the dominant spatiotemporal dynamics in the multivariate water quality data set in a few components. Those were used to derive hypotheses on the dominant drivers influencing water quality. Secondly, different sampling sites were compared with respect to median component values. Thirdly, time series of the components at single sites were analysed for long-term patterns. We tested the approach with a joint stream water and groundwater data set quality consisting of 1572 samples, each comprising sixteen variables, sampled with a spatially and temporally irregular sampling scheme at 29 sites in northeast Germany from 1998 to 2009. The first four components were interpreted as (1) an agriculturally induced enhancement of the natural background level of solute concentration, (2) a redox sequence from reducing conditions in deep groundwater to post-oxic conditions in shallow groundwater and oxic conditions in stream water, (3) a mixing ratio of deep and shallow groundwater to the streamflow and (4) sporadic events of slurry application in the agricultural practice. Dominant changes were observed for the first two components. The changing intensity of the first component was interpreted as response to the temporal variability of the thickness of the unsaturated zone. A steady increase in the second component at most stream water sites pointed towards progressing depletion of the denitrification capacity of the deep aquifer.
引用
收藏
页码:4401 / 4424
页数:24
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