Value of uncertain streamflow observations for hydrological modelling

Etter, Simon; Strobl, Barbara; Seibert, Jan; Meerveld, Ilja van

doi:10.5194/hess-22-5243-2018

Cited by 25 publications

(38 citation statements)

References 44 publications

(59 reference statements)

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“…We, therefore, used synthetic data (cf. Etter et al, 2018;Seibert & Vis, 2016;van Meerveld et al, 2017), which is an efficient approach to assess data requirements before making considerable efforts to collect the data (Christophersen et al, 1993;Pool et al, 2019). First, we converted the water level time series for four Swiss catchments into WLclass time series.…”

Section: Methodsmentioning

confidence: 99%

Value of Crowd‐Based Water Level Class Observations for Hydrological Model Calibration

Etter

Strobl

Seibert

et al. 2020

Water Resources Research

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While hydrological models generally rely on continuous streamflow data for calibration, previous studies have shown that a few measurements can be sufficient to constrain model parameters. Other studies have shown that continuous water level or water level class (WL‐class) data can be informative for model calibration. In this study, we combined these approaches and explored the potential value of a limited number of WL‐class observations for calibration of a bucket‐type runoff model (HBV) for four catchments in Switzerland. We generated synthetic data to represent citizen science data and examined the effects of the temporal resolution of the observations, the numbers of WL‐classes, and the magnitude of the errors in the WL‐class observations on the model validation performance. Our results indicate that on average one observation per week for a 1‐year period can significantly improve model performance compared to the situation without any streamflow data. Furthermore, the validation performance for model parameters calibrated with WL‐class observations was similar to the performance of the calibration with precise water level measurements. The number of WL‐classes did not influence the validation performance noticeably when at least four WL‐classes were used. The impact of typical errors for citizen science‐based estimates of WL‐classes on the model performance was small. These results are encouraging for citizen science projects where citizens observe water levels for otherwise ungauged streams using virtual or physical staff gauges.

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Section: Methodsmentioning

confidence: 99%

Value of Crowd‐Based Water Level Class Observations for Hydrological Model Calibration

Etter

Strobl

Seibert

et al. 2020

Water Resources Research

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“…However, these approaches require significant funding, equipment, and expertise and are often difficult to maintain, and even more so to scale (Davids et al, 2017). Consequently, despite growing demand, the amount of streamflow data being collected continues to decline in several parts of the world, especially in Africa, Latin America, Asia, and even North America (Hannah et al, 2011;Van de Giesen et al, 2014;Feki et al, 2017;Tauro et al, 2018). Specifically, there is an acute shortage of streamflow data in headwater catchments (Kirchner, 2006) and developing regions (Mulligan, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Despite the promising nature of these technologies, we could not find any specific studies evaluating the strengths and weaknesses of citizen scientists applying these technologies directly in the field themselves. Etter et al (2018) evaluated the error structure of simple "stick method" streamflow estimates (similar to what we later refer to as the float method) from 136 participants from four streams in Switzerland. Participants estimated crosssectional area with visual estimates of stream width and depth.…”

Section: Introductionmentioning

confidence: 99%

Citizen science flow – an assessment of simple streamflow measurement methods

Davids

Rutten

Pandey³

et al. 2019

Hydrol. Earth Syst. Sci.

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Abstract. Wise management of water resources requires data. Nevertheless, the amount of streamflow data being collected globally continues to decline. Generating hydrologic data together with citizen scientists can help fill this growing hydrological data gap. Our aim herein was to (1) perform an initial evaluation of three simple streamflow measurement methods (i.e., float, salt dilution, and Bernoulli run-up), (2) evaluate the same three methods with citizen scientists, and (3) apply the preferred method at more sites with more people. For computing errors, we used midsection measurements from an acoustic Doppler velocimeter as reference flows. First, we (authors) performed 20 evaluation measurements in headwater catchments of the Kathmandu Valley, Nepal. Reference flows ranged from 6.4 to 240 L s−1. Absolute errors averaged 23 %, 15 %, and 37 % with average biases of 8 %, 6 %, and 26 % for float, salt dilution, and Bernoulli methods, respectively. Second, we evaluated the same three methods at 15 sites in two watersheds within the Kathmandu Valley with 10 groups of citizen scientists (three to four members each) and one “expert” group (authors). At each site, each group performed three simple methods; experts also performed SonTek FlowTracker midsection reference measurements (ranging from 4.2 to 896 L s−1). For float, salt dilution, and Bernoulli methods, absolute errors averaged 41 %, 21 %, and 43 % for experts and 63 %, 28 %, and 131 % for citizen scientists, while biases averaged 41 %, 19 %, and 40 % for experts and 52 %, 7 %, and 127 % for citizen scientists, respectively. Based on these results, we selected salt dilution as the preferred method. Finally, we performed larger-scale pilot testing in week-long pre- and post-monsoon Citizen Science Flow campaigns involving 25 and 37 citizen scientists, respectively. Observed flows (n=131 pre-monsoon; n=133 post-monsoon) were distributed among the 10 headwater catchments of the Kathmandu Valley and ranged from 0.4 to 425 L s−1 and from 1.1 to 1804 L s−1 in pre- and post-monsoon, respectively. Future work should further evaluate uncertainties of citizen science salt dilution measurements, the feasibility of their application to larger regions, and the information content of additional streamflow data.

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“…This would imply artificially re-sampling a higher-frequency isotopic time series using various strategies (e.g. Pool et al, 2017;Etter et al, 2018) and re-calibrating the model many times, which would come with an exorbitant computational price.…”

Section: Age Information Contents Of Stable and Radioactive Isotopesmentioning

confidence: 99%

Testing the truncation of travel times with StorAge Selection functions using deuterium and tritium as tracers

Rodriguez

Pfister

Zehe

et al. 2019

Preprint

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Abstract. Catchment travel time distributions (TTDs) are an efficient concept to summarize the time-varying 3-dimensional transport of water and solutes to an outlet in a single function of water age and to estimate catchment storage by leveraging information contained in tracer data (e.g. 2H and 3H). It is argued that the increasing use of the stable isotopes of O and H compared to tritium as tracers has truncated our vision of streamflow TTDs, meaning that the long tails associated with old water are neglected. However, the reasons for the truncation of the TTD tails are still obscured by methodological and data limitations. In this study, we went beyond these limitations and tested the hypothesis that streamflow TTDs calculated using only deuterium (2H) or only tritium (3H) are different. We similarly tested if the mobile catchment storage (derived from the TTDs) associated with each tracer is different. For this we additionally constrained a model successfully developed to simulate high-frequency stream deuterium measurements with about 30 stream tritium measurements over the same period (2015–2017). We used data from the forested headwater Weierbach catchment (42 ha) in Luxembourg. The streamflow TTDs were estimated in unsteady conditions by using both tracers coherently within a framework based on StorAge Selection (SAS) functions. We found equal TTDs and equal mobile storage between the 2H- and 3H-derived estimates. The truncation hypothesis was thus rejected. The small differences we found could be explained by the calculation uncertainties and by a limited sampling frequency for tritium. Using both stable and radioactive isotopes of H as tracers reduced the age and storage uncertainties. Although tritium and stable isotopes had redundant information about younger water, using both tracers better exploited the more specific information about longer ages that 3H inherently contains, and it could be even better in the next decades. The two tracers thus had overall different information contents. Tritium was however slightly more informative and cost-effective than stable isotopes for travel time analysis. We thus reiterate the call of Stewart et al. (2012) to measure tritium in the streams for travel time analysis, and emphasize the need for high-frequency tritium sampling in future studies to match the resolution in stable isotopes.

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Value of uncertain streamflow observations for hydrological modelling

Cited by 25 publications

References 44 publications

Value of Crowd‐Based Water Level Class Observations for Hydrological Model Calibration

Value of Crowd‐Based Water Level Class Observations for Hydrological Model Calibration

Citizen science flow – an assessment of simple streamflow measurement methods

Testing the truncation of travel times with StorAge Selection functions using deuterium and tritium as tracers

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