Technical note: Calculation scripts for ensemble hydrograph separation

Kirchner, James W.; Knapp, Julia L. A.

doi:10.5194/hess-2020-330

Cited by 6 publications

(8 citation statements)

References 7 publications

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“…For example, public availability of water age simulations for various research catchments would enable their use to test physically based model results based on particle tracking. With regard to software, many codes are already freely accessible and well documented (Benettin & Bertuzzo, 2018; Harman, 2015; Harman & Fei Xu, 2022; Kirchner & Knapp, 2020). There are currently many initiatives to enhance the exchange among scientists working at different research catchments (see Brantley et al., 2017).…”

Section: Going Forwardmentioning

confidence: 99%

“…Both new water fractions and TTDs can be expressed as “backward” fractions of streamflow, or “forward” fractions of precipitation, with or without volume‐weighting. The calculations are conceptually straightforward but may be somewhat tricky to implement correctly, so user‐friendly scripts are available for both R and Matlab (Kirchner & Knapp, 2020). Perhaps most importantly, the methods have been extensively benchmark tested (Kirchner, 2019), and demonstrated with chloride and isotope data from Plynlimon, in a proof‐of‐concept illustration of how F new values and TTDs vary seasonally, with flow regime, and under varying precipitation intensity (Knapp et al., 2019).…”

Section: New Ttd Framework (2006–2022)mentioning

confidence: 99%

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Transit Time Estimation in Catchments: Recent Developments and Future Directions

Benettin

Rodriguez

Sprenger

et al. 2022

Water Resources Research

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The transit time of water in catchments is a fundamental descriptor of catchment behavior. If we think of "age" as a label that is attached to any water particle resident within a hydrologic system (e.g., a catchment) and that tracks the time elapsed since arrival (e.g., as precipitation), the transit time is the particle's age when it leaves the system (e.g., as discharge or evapotranspiration). While slow to gain ground as a standard metric, transit times and their analyses now abound in the literature due in part to the increased availability of tracer data used to estimate water transit times. As a result, transit time is now a common means to improve process representation in models and a strong test of model output realism. Once, the review presented in McGuire and McDonnell (2006) was the starting point for newcomers interested in getting to grips with catchment transit time modeling. However, the explosion of the transit time literature since the mid-2000s-with new studies, terminology, theory, and mathematical approaches-means a newcomer to the field now is met with the challenge of absorbing these developments and harmonizing them with earlier approaches.Over the last ∼15 yr, there have indeed been departures and advancements beyond what was summarized by McGuire and McDonnell (2006). That review provided the first "evaluation and review of the transit time literature in the context of catchments and water transit time estimation". It was motivated by "new and emerging interests in transit time estimation in catchment hydrology and the need to distinguish approaches and assumptions used in groundwater applications from catchment applications". At that time, hydrologists were mainly using time-invariant, lumped parameter transit time approaches largely focused on low temporal resolution

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Section: Going Forwardmentioning

confidence: 99%

Section: New Ttd Framework (2006–2022)mentioning

confidence: 99%

Transit Time Estimation in Catchments: Recent Developments and Future Directions

Benettin

Rodriguez

Sprenger

et al. 2022

Water Resources Research

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“…Recently, Kirchner (2016b, 2016a) introduced the “young water” concept since mean transit time (MTT) estimates can suffer from large spatial aggregation errors in heterogeneous catchments. The EHS method allows the determination of water ages and young water fraction thresholds directly from observed input–output tracer series, correlating tracer fluctuations overcoming the need of stationary end‐member signatures (Kirchner, 2019; Kirchner & Knapp, 2020).…”

Section: Introductionmentioning

confidence: 99%

Tracer‐aided modelling reveals quick runoff generation and young streamflow ages in a tropical rainforest catchment

Mayer‐Anhalt¹,

Birkel

Sánchez‐Murillo

et al. 2022

Hydrological Processes

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There is still limited understanding of where stream water originates, their flow paths, how water sources mix, and for how long water transits montane tropical catchments. Here, we used a simple gamma convolution integral model (GM), ensemble hydrograph separation (EHS) and a tracer‐aided model (TAM) to assess runoff generation, mixing processes and water ages in the pristine tropical rainforest Quebrada Grande catchment in Costa Rica. Model simulations are based on a four‐year record (2016–2019) of continuous hydrometric and stable isotope observations. Comparative model tests included multi‐objective calibration (2017–2019) and validation (2016) using stream discharge and isotope data as well as an independent model evaluation using groundwater and soil water isotope data. GM and TAM agreed on the dominance of young water in streamflow that was less than 95 days old for 75% of the study period. The EHS suggested a young water fraction threshold of 12 ± 2 days with a transit time distribution that approximates the best‐fit GM. These short water ages are the result of high annual rainfall even during drier years such as 2019 with 4300 mm/a and consistent quick near‐surface runoff generation with limited mixing. A supra‐regional loss (~55%) of likely older groundwater was detected. The TAM‐based hydrograph separation (streamflow KGE > 0.78, δ2H KGE > 0.90) suggested an average near‐surface water contribution of more than 60% to streamflow emphasizing the dominance of quick flow paths. This tropical rainforest represents one of the quickest streamflow responses of mostly young water of pristine catchments globally.

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“…First, the manual selection of recessions from a curved plot on a semi‐logarithmic scale limited the ability to use larger pool of catchments and this can be improved to yield better results. Newer techniques (e.g., Dralle et al, 2017; McMahon & Nathan, 2021; Sujono et al, 2004) preferably with coding (e.g., Kirchner & Knapp, 2020), will indeed improve the efficiency in larger sample studies. Additionally, recessional analyses should be taken over a longer period of time where consistency of similar recessional behaviour is maintained; in order to properly capture the inter‐annual variation of streamflow events within a catchment.…”

Section: Discussionmentioning

confidence: 99%

“…Additionally, recessional analyses should be taken over a longer period of time where consistency of similar recessional behaviour is maintained; in order to properly capture the inter‐annual variation of streamflow events within a catchment. Furthermore, literature has indicated the existence of several techniques developed to improve hydrograph separation methods (e.g., Blume et al, 2007; Kirchner & Knapp, 2020; Sujono et al, 2004) which presumably could improve the annual and seasonal recessional analysis. Lastly, we suggest that improvements to the approach should use hourly timescales, to reduce the impact of averaging daily streamflow predictions on the FDC.…”

Section: Discussionmentioning

confidence: 99%

A multiple hydrograph separation technique for identifying hydrological model structures and an interpretation of dominant process controls on flow duration curves

Leong

Yokoo

2022

Hydrological Processes

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There has been significant progress made towards understanding the process controls that govern the shapes of flow duration curves (FDC). However, the transferability of the knowledge gained to large spatial scales is still lacking, partly due to the fixed representation of the model structures representing the unobserved underground layer. In the context of improving large scale applicability/transferability of FDC studies: (1) we propose a novel approach to transform/restructure the representation of the subsurface component in hydrological models to be flexible and adaptable in any environment and (2) provide a thorough interpretation of the dominant processes that impact the shape of FDCs. The flexible structure is designed from a series of multiple connected linear reservoirs that are developed from a unique multiple hydrograph separation procedure, to estimate the number of distinct hydrological processes at play. The main results are: (1) wet catchments have more complex model structures (more reservoirs) than arid catchments; indicating that subsurface processes are potentially more present in wet catchments than in drier ones. Dry catchments have more near surface occurring processes, thus have less complex model structures. However, more complexity is potentially required within the internal reservoirs of dry catchments. (2) The strength of interference in the intermediate reservoirs in controlling the dominant processes towards the bottom determined the shape of FDCs, and this increased with aridity. The novel finding is that a model structure can be determined by the catchment's ability to generate flows as well as the strength of low flow persistence. Hence, we propose a conceptual framework for the development of flexible model structures based on the shapes of FDCs. The transformation of models to be flexible in this research, should contribute to studies that seek the transferability of models over large spatial scales.

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Technical note: Calculation scripts for ensemble hydrograph separation

Cited by 6 publications

References 7 publications

Transit Time Estimation in Catchments: Recent Developments and Future Directions

Transit Time Estimation in Catchments: Recent Developments and Future Directions

Tracer‐aided modelling reveals quick runoff generation and young streamflow ages in a tropical rainforest catchment

A multiple hydrograph separation technique for identifying hydrological model structures and an interpretation of dominant process controls on flow duration curves

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