Research -> Processes  -> Spatio/temporal Variability

Spatio/Temporal Variability

Catchments are “… complex systems with some degree of organization” (Dooge, 1986:48).

How can we "capture" this variability and interpret it in terms of dominant process mechanisms? Why not also consider "soft" data as valuable information?


  • Boots & Trousers Method
  • Soft Soil Moisture Sensing - Africa
  • Hydrochemical Fingerprints

Rinderer et al., (2016)

Boots & Trousers Method

Sensing with boots and trousers – qualitative field observations of shallow soil moisture patterns

Soil moisture patterns can be interesting traits to investigate spatio-temporal heterogeneity of catchments. However many existing methods to capture spatial patterns are time-consuming, expensive or need site-specific calibration. We present a quick and inexpensive supplementary field method for classifying soil wetness in wet environments. The seven wetness classes are based on qualitative indicators, which one can touch, hear or see on the soil surface. To counter critics that such qualitative methods are considerably affected by subjectivity, we performed systematic testing of the method by taking qualitative measurements in the field with 20 non-expert raters, analyzed these in terms of degree of agreement and assessed the results against gravimetric sampling and Time Domain Reflectometry (TDR) measurements.

In 70% of all classifications, raters agreed on the wetness class assigned to the marked sampling locations and in 95% they were not off by more than one wetness class. The seven quantitative wetness classes agreed with gravimetric and TDR measurements although intermediate to wet classes showed an overlap of their range whereas the driest classes showed considerable spread. Despite some potential to optimize the method, it has been shown to be a reliable supplement to existing quantitative techniques for assessing soil moisture patterns in wet environments.


Rinderer et al., (2012)



J. Seibert, (University of Zurich, CH)

I. van Meerveld (University of Zurich, CH)

M. Stähli (Swiss Federal Research Institute WSL, CH)

Soft Soil Moisture Sensing - Africa

Qualitative soil moisture assessment in semi-arid Africa - The role of experience and training on inter-rater reliability

Soil moisture differences are important indicators of the soil water deficit and have traditionally been used for allocating water resources among farmers of village communities in rural Africa. We adapted the Boots & Trousers Method (Rinderer et al., 2012) to incorporate the local farmers’ tacit knowledge and the soil properties of the study site near Arusha, Tanzania. The qualitative indicators to distinguish between the seven wetness classes are related to moisture conditions for seeding plants and brick making in this semi-arid environment.

The scheme was tested twice in 2014 with farmers, students and experts (April: 40 persons, June: 25 persons) for inter-rater reliability, bias of individuals and the importance of training how to apply the method.

During the test in June in 66% of all classifications farmers assigned the same wetness class and were off by not more than one wetness class in 90%. However it was important to organize the group in small  sub-groups and to provide them with good instructions. Students who had been trained in how to apply the method gained higher inter-rater reliability than their colleagues with only a basic introduction. This study demonstrates that a wetness classification scheme based on qualitative indicators can be a robust tool for capturing soil moisture variability.


Rinderer et al., (2015)



H. Komakech, (Nelson Mandela African Institution of Science and Technology, TZ)

D. Müller, (University of Zurich, CH)

G. L. B. Wiesenberg, (University of Zurich, CH)

J. Seibert, (University of Zurich, CH)


Funded by:

Swiss Agency for Development and Cooperation (SDC)

(Rinderer et al., 2015)

Hydrochemical Fingerprints

Contributing sources to baseflow in pre-alpine headwaters using spatial snapshot sampling

Mountainous headwaters consist of different landscape units including forests, meadows and wetlands. In these headwaters it is unclear which landscape units contribute what percentage to baseflow. In this study, we analysed spatiotemporal differences in baseflow isotope and hydrochemistry to identify catchment-scale runoff contribution. Three baseflow snapshot sampling campaigns were performed in the Swiss pre-alpine headwater catchment of the Zwäckentobel (4.25 km2) and six of its adjacent subcatchments. The spatial and temporal variability of δ2H, Ca, DOC, AT, pH, SO4, Mg and H4SiO4 of streamflow, groundwater and spring water samples was analysed and related to catchment area and wetland percentage using bi-variate and multi-variate methods. Our study found that in the six subcatchments, with variable arrangements of landscape units, the inter- and intra catchment variability of isotopic and hydrochemical compositions was small and generally not significant. Stream samples were distinctly different from shallow groundwater. An upper spring zone located near the water divide above 1,400 m and a larger wetland were identified by their distinct spatial isotopic and hydrochemical composition. The upstream wetland percentage was not correlated to the hydrochemical streamflow composition, suggesting that wetlands are less connected and act as passive features with a negligible contribution to baseflow runoff. The isotopic and hydrochemical composition of baseflow changed slightly from the upper spring zone towards the subcatchment outlets and corresponded to the signature of deep groundwater. Our results confirm the need and benefits of spatially distributed snapshot sampling to derive process understanding of heterogeneous headwaters during baseflow.


Fischer et al., (2015)

in collaboration with

B. Fischer (first author)

P. Schneider

T. Ewen

J. Seibert