Analytical assessment and parameter estimation of a low-dimensional groundwater model

Rupp, David E.; Schmidt, Jochen; Woods, Ross; Bidwell, Vince J.

doi:10.1016/j.jhydrol.2009.08.018

Cited by 57 publications

(56 citation statements)

References 22 publications

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“…Fig. 7 of Rupp et al, 2009) shows similar spreads. If this spread is dominated by real variability rather than by measurement error or error arising from our approximation of each recession event as following a power law, then the mean recession timescales and storage amplitude may be some 10 %-40 % higher (e σ 2 −1) than estimated from the mean recession curve.…”

Section: Why Are Storage Amplitudes Inferred From the Recession Curvementioning

confidence: 59%

“…As we saw, assuming that a particular stream follows a single recession curve can be taken to imply that discharge for that stream is a single-valued function of basin water storage. While this assumption holds in analytical solution of some very simple aquifer models and for flow systems dominated by deep, homogenous aquifers (Brutsaert and Nieber, 1977;Dewandel et al, 2003;Rupp and Selker, 2006b), more complex watershed models show a clear dependence of flow rate on the time history of water input (rainfall or snowmelt), so that flow is not a single-valued function of basin storage and a recession curve plot will show systematic scatter (Sloan, 2000;Rupp et al, 2009). In such cases our approach to fitting a recession curve will produce averages of the rate of change in flowQ at given flow rates Q.…”

Section: Why Are Storage Amplitudes Inferred From the Recession Curvementioning

confidence: 99%

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Stream recession curves and storage variability in small watersheds

Krakauer

Temimi

2011

Hydrol. Earth Syst. Sci.

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Abstract. The pattern of streamflow recession after rain events offers clues about the relationship between watershed runoff (observable as river discharge) and water storage (not directly observable) and can help in water resource assessment and prediction. However, there have been few systematic assessments of how streamflow recession varies across flow rates and how it relates to independent assessments of terrestrial water storage. We characterized the streamflow recession pattern in 61 relatively undisturbed small watersheds (1-100 km 2 ) across the coterminous United States with multiyear records of hourly streamflow from automated gauges. We used the North American Regional Reanalysis to help identify periods where precipitation, snowmelt, and evaporation were small compared to streamflow. The order of magnitude of the recession timescale increases from 1 day at high flow rates (∼1 mm h −1 ) to 10 days at low flow rates (∼0.01 mm h −1 ), leveling off at low flow rates. There is significant variability in the recession timescale at a given flow rate between basins, which correlates with climate and geomorphic variables such as the ratio of mean streamflow to precipitation and soil water infiltration capacity. Stepwise multiple regression was used to construct a six-variable predictive model that explained some 80 % of the variance in recession timescale at high flow rates and 30-50 % at low flow rates. Seasonal and interannual variability in inferred storage shows similar time evolution to regional-scale water storage variability estimated from GRACE satellite gravity data and from land surface modeling forced by observed meteorology, but is up to a factor of 10 smaller. Study of this discrepancy in the inferred storage amplitude may provide clues to the range of validity of the recession curve approach to relating runoff and storage.

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Section: Why Are Storage Amplitudes Inferred From the Recession Curvementioning

confidence: 59%

Section: Why Are Storage Amplitudes Inferred From the Recession Curvementioning

confidence: 99%

Stream recession curves and storage variability in small watersheds

Krakauer

Temimi

2011

Hydrol. Earth Syst. Sci.

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“…A single linear reservoir is, however, too simple for describing the variability and non-linearity of hydrological response (Brutsaert and Nieber, 1977;Lindström et al, 1997). Some groundwater models conceptualise the stream-aquifer inter-4964 T. Skaugen and Z. Mengistu: Estimating catchment-scale groundwater dynamics from recession analysis actions as the drainage of an infinite number of independent linear reservoirs (Sloan, 2000;Pulido-Velasquez et al, 2005;Bidwell et al, 2008;Rupp et al, 2009). This comes as a result of solving the linearised Dupuit-Boussinesq equation for saturated flow as an eigenvalue and eigenfunction problem.…”

Section: Introductionmentioning

confidence: 99%

Estimating catchment-scale groundwater dynamics from recession analysis – enhanced constraining of hydrological models

Skaugen

Mengistu

2016

Hydrol. Earth Syst. Sci.

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Abstract. In this study, we propose a new formulation of subsurface water storage dynamics for use in rainfallrunoff models. Under the assumption of a strong relationship between storage and runoff, the temporal distribution of catchment-scale storage is considered to have the same shape as the distribution of observed recessions (measured as the difference between the log of runoff values). The mean subsurface storage is estimated as the storage at steady state, where moisture input equals the mean annual runoff. An important contribution of the new formulation is that its parameters are derived directly from observed recession data and the mean annual runoff. The parameters are hence estimated prior to model calibration against runoff. The new storage routine is implemented in the parameter parsimonious distance distribution dynamics (DDD) model and has been tested for 73 catchments in Norway of varying size, mean elevation and landscape type. Runoff simulations for the 73 catchments from two model structures (DDD with calibrated subsurface storage and DDD with the new estimated subsurface storage) were compared. Little loss in precision of runoff simulations was found using the new estimated storage routine. For the 73 catchments, an average of the Nash-Sutcliffe efficiency criterion of 0.73 was obtained using the new estimated storage routine compared with 0.75 using calibrated storage routine. The average Kling-Gupta efficiency criterion was 0.80 and 0.81 for the new and old storage routine, respectively. Runoff recessions are more realistically modelled using the new approach since the root mean square error between the mean of observed and simulated recession characteristics was reduced by almost 50 % using the new storage routine. The parameters of the proposed storage routine are found to be significantly correlated to catchment characteristics, which is potentially useful for predictions in ungauged basins.

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“…There are many other studies in which storage-discharge relations have been found by means of discharge (recession) analysis, but a more obvious approach, namely using storage data directly, is not known to the authors. However, local storage computed with a groundwater model has been used in direct storage-discharge fitting [Rupp et al, 2009]. Examples of studies in which solutions to the Boussinesq equation for sloping aquifers have been employed in order to investigate storage-discharge relations are Troch et al [1993], Brutsaert [1994], and Rupp and Selker [2006b].…”

Section: Introductionmentioning

confidence: 99%

Investigating storage‐discharge relations in a lowland catchment using hydrograph fitting, recession analysis, and soil moisture data

Brauer

Teuling

Torfs

et al. 2013

Water Resources Research

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[1] The relation between storage and discharge is an essential characteristic of many rainfall-runoff models. The simple dynamical systems approach, in which a rainfall-runoff model is constructed from a single storage-discharge relation, has been successfully applied to humid catchments. Here we investigate (1) if and when the less humid lowland Hupsel Brook catchment also behaves like a simple dynamical system by hydrograph fitting, and (2) if system parameters can be inferred from streamflow recession rates or more directly from soil moisture storage observations. Only 39% of the fitted monthly hydrographs yielded Nash-Sutcliffe efficiencies above 0.5, from which we can conclude that the Hupsel Brook catchment does not always behave like a simple dynamical system. Model results were especially poor in summer, when evapotranspiration is high and the thick unsaturated zone attenuates the rainfall input. Using soil moisture data to obtain system parameters is not trivial, mainly because there is a discrepancy between local and catchment storage. Parameters obtained with direct storage-discharge fitting led to a strong underestimation of the response of runoff to rainfall, while recession analysis leads to an overestimation.Citation: Brauer, C. C., A. J. Teuling, P. J. J. F. Torfs, and R. Uijlenhoet (2013), Investigating storage-discharge relations in a lowland catchment using hydrograph fitting, recession analysis, and soil moisture data, Water Resour. Res., 49,[4257][4258][4259][4260][4261][4262][4263][4264]

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Analytical assessment and parameter estimation of a low-dimensional groundwater model

Cited by 57 publications

References 22 publications

Stream recession curves and storage variability in small watersheds

Stream recession curves and storage variability in small watersheds

Estimating catchment-scale groundwater dynamics from recession analysis – enhanced constraining of hydrological models

Investigating storage‐discharge relations in a lowland catchment using hydrograph fitting, recession analysis, and soil moisture data

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