Examination of deep root water uptake using anomalies of soil water stable isotopes, depth-controlled isotopic labeling and mixing models

•Drought-induced anomalies of soil water isotopes used to identify of deep uptake.•Acacia erioloba obtains 37% (median) from groundwater.•Isotopic labeling experiments used to constrain uptake depths.•Combined methods to assess the deep water uptake and source partitioning are needed.•We call for a...

Full description

Saved in:
Bibliographic Details
Published inJournal of hydrology (Amsterdam) Vol. 566; pp. 122 - 136
Main Authors Beyer, M., Hamutoko, J.T., Wanke, H., Gaj, M., Koeniger, P.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.11.2018
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:•Drought-induced anomalies of soil water isotopes used to identify of deep uptake.•Acacia erioloba obtains 37% (median) from groundwater.•Isotopic labeling experiments used to constrain uptake depths.•Combined methods to assess the deep water uptake and source partitioning are needed.•We call for a separation of lateral and deep roots in hydrological models. Knowledge on the water uptake depths of vegetation is crucial for understanding water transport processes of the soil-vegetation atmosphere continuum and relevant for many applications (e.g. the estimation of groundwater recharge, irrigation planning and the parameterization of (eco-) hydrological models). The identification and quantification of water uptake from deep soil layers and groundwater remain challenging. This study uses a combined framework based on natural abundances of stable water isotopes and isotopic labeling experiments with deuterium oxide (2H2O) to study root water uptake and identify uptake from deep soil in a semi-arid environment. Between 2013 and 2016, more than 1000 soil (isotope depth profiles); plant (xylem and transpiration) and water (precipitation and groundwater) samples for the analysis of isotope ratios were collected. Two experiments using isotopic labeling were carried out in order to assess root water uptake depths. Herein, we i) present series of deep soil water isotope depth profiles, interpret water transport dynamics and ecohydrological feedbacks; ii) examine the suitability of natural isotope depth profiles for identifying deep root water uptake; iii) apply the Bayesian mixing model MixSIAR to quantify deep root water uptake and iv) constrain water uptake depths using isotopic labeling experiments and derive an active root water uptake distribution. Our results show that the form of isotope depth profiles of soil in water-limited environments follows characteristic shapes for the end of the rainy and dry seasons, respectively. Isotope ratios in the upper 4 m of the soil are heavily dependent on the character of the respective rainy season. Under certain conditions – e.g. droughts or weak rainy seasons – the isotope depth profile displays an enrichment in heavy isotopes up to 4 m depth. Such pronounced anomalies provide an opportunity for studies on source water partitioning. In the present experiment, the studied individuals of Acacia erioloba were found to obtain 37% [24–52%] of their water from deep soil (>4 m) and groundwater at the end of the dry season of 2015. All other investigated trees (individuals of B. plurijuga, S. luebertii, T. sericea and C. collinum) mainly utilize water originating from 1 m to 2.5 m depth. Under “average” rainy season conditions, the similarity of isotope ratios of potential plant water sources hinders a conclusive identification of water uptake depths. Deep natural isotope depth profiles in dry environments can – under certain conditions – be used to identify and quantify access of vegetation to deep water resources. Isotopic labeling enables to determine active root distributions for the lateral root zone. Combined frameworks contribute to a better understanding of deep water uptake. A differentiated consideration of water uptake from the lateral root zone and deep, potentially groundwater-tapping roots is required in order to fully investigate ecohydrological feedbacks and for a proper parameterization of models.
ISSN:0022-1694
1879-2707
DOI:10.1016/j.jhydrol.2018.08.060