diff --git a/hydrographdisaggregation/hydroparse.Rmd b/hydrographdisaggregation/hydroparse.md similarity index 97% rename from hydrographdisaggregation/hydroparse.Rmd rename to hydrographdisaggregation/hydroparse.md index 2000df6..2e0bcfe 100644 --- a/hydrographdisaggregation/hydroparse.Rmd +++ b/hydrographdisaggregation/hydroparse.md @@ -1,15 +1,12 @@ --- title: Automated hydrograph disaggregation -# author: Oak Ridges Moraine Groundwater Program -date: February, 2019 +author: Oak Ridges Moraine Groundwater Program output: html_document --- -# Hydrograph disaggregation - The hydrograph disaggregation algorithm is a means of categorizing the hydrograph into three primary constituent parts, namely: 1. the rising limb, diff --git a/hydrographdisaggregation/index.html b/hydrographdisaggregation/index.html deleted file mode 100644 index 2915e81..0000000 --- a/hydrographdisaggregation/index.html +++ /dev/null @@ -1,246 +0,0 @@ - - - - - - - - - - - - - -Automated hydrograph disaggregation - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Hydrograph disaggregation

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The hydrograph disaggregation algorithm is a means of categorizing the hydrograph into three primary constituent parts, namely:

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  1. the rising limb,
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  2. the falling limb, and
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  3. the baseflow recession component.
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The rising limb identifies the portion of the hydrograph that has been influenced by some forcing, typically a rainfall event, a snowmelt episode, and perhaps, some planned release of a significant volume of water from storage.

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The falling limb is subsequent to the rising limb and is likely indicative of the cessation of the forcing, and thus can be though of the excess precipitation that has yet to drain from the basin.

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The baseflow recession component should be though of that portion of the hydrograph that represents the slow release of water stored in the watershed. It is not uncommon to assume that this portion of the hydrograph is entirely composed of groundwater discharge, however there may be exceptions. The baseflow recession component is identified by locating portions of the hydrograph that closely follow the computer baseflow recession coefficient \((k)\) within a predefined degree of error.

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Hydrograph disaggregation can be useful to hydrologic modellers needing to identify model parameters that directly relate to specific portions of the hydrograph. The disaggregation also enables the ability to isolate stream flow volumes associated with specific events and thus can be used to convert a continuous hydrograph into a discrete form (see below).

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Hydrograph discretization

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A common challenge with the interpretation of hydrology is the comparison of stream flow response to a rainfall/snowmelt event. Complications arise since stream flow response can have a greater dependence on antecedent conditions over the amount of precipitation. In addition, snowmelt events can add further complication as they are rarely measured, yet has a significant impact on stream flow in Canadian watersheds. By assuming that initial flow prior to an event is a surrogate for antecedent state, one could isolate the portion of the hydrograph caused by that particular event. This method is an extension of the work of Reed et.al., (1975) who used the method to derive parameters for their rainfall-runoff model. Arnold and Allen (1999) also refer this to the ``recession curve displacement method.’’

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The algorithm locates the onset of a rising limb and projects stream flow recession from this point as if the event had never occurred (e.g., at points \(T`\) and \(T\) in the Figure above). This projected stream flow, termed “underlying flow” by Reed et.al. (1975), is subtracted from the total observed flow to determine the volume associated with the event. Comparing these event volumes with rainfall/snowmelt volumes can be used to calculate runoff coefficients but will also highlight non-linearities of watershed hydrology (see Beven et.al., 2011).

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In particular, events may be observed in the stream flow hydrograph that may have no corresponding rainfall event on record (or vice versa). This will be problematic during rainfall-runoff model calibration as this particular event will do nothing but hinder the fitness of the model as there will be no information (i.e., data) to drive the model. Identifying and eliminating these ``red herrings’’ (Bevin and Westerberg, 2011) from a calibration data set is a crucial step in preventing model over-fitting.

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References

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Arnold, J.G. and P.M. Allen, 1999. Automated Methods for Estimating Baseflow and Groundwater Recharge from Stream Flow Records Journal of American Water Resources Association 35(2): 411–424.

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Beven, K.J., P.J. Smith, A. Wood, 2011. On the colour and spin of epistemic error (and what we might do about it). Hydrology and Earth System Sciences 15: 3123-–3133.

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Bevin, K.J. and I. Westerberg, 2011. On red herrings and real herrings: disinformation and information in hydrological inference. Hydrological Processes 25: 1676–1680.

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Reed, D.W., P. Johnson, J.M. Firth, 1975. A Non-Linear Rainfall-Runoff Model, Providing for Variable Lag Time. Journal of Hydrology 25: 295–305.

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- - - - - - - - - - - - - - - diff --git a/hydrographseparation/index.md b/hydrographseparation/index.md index bf8d160..d409adf 100644 --- a/hydrographseparation/index.md +++ b/hydrographseparation/index.md @@ -5,7 +5,6 @@ output: html_document --- -# Hydrograph Separation > "Division of a hydrograph into direct and groundwater runoff as a basis for subsequent analysis is known as *hydrograph separation* or *hydrograph analysis*. Since there is no real basis for distinguishing between direct and groundwater flow in a stream at any instant, and since definitions of these two components are relatively arbitrary, the method of separation is usually equally arbitrary." - Linsley et.al., 1975 diff --git a/lumped/docs/Quinn Beven 1993 Spatial and temporal predictions of soil moisture dynamics runoff.pdf b/lumped/docs/Quinn Beven 1993 Spatial and temporal predictions of soil moisture dynamics runoff.pdf new file mode 100644 index 0000000..aa1be7e Binary files /dev/null and b/lumped/docs/Quinn Beven 1993 Spatial and temporal predictions of soil moisture dynamics runoff.pdf differ diff --git a/lumped/fig/DawdyODonnell.png b/lumped/fig/DawdyODonnell.png new file mode 100644 index 0000000..d975c2b Binary files /dev/null and b/lumped/fig/DawdyODonnell.png differ diff --git a/lumped/fig/Quinn.png b/lumped/fig/Quinn.png new file mode 100644 index 0000000..8952220 Binary files /dev/null and b/lumped/fig/Quinn.png differ diff --git a/lumped/index.md b/lumped/index.md index 6d74d9f..168e107 100644 --- a/lumped/index.md +++ b/lumped/index.md @@ -31,10 +31,11 @@ Below is a brief description of the model design. ## Dawdy and O'Donnell -The Dawdy and O'Donnell model is the classic bucket type model. +The Dawdy and O'Donnell (1965) model is the classic bucket type model. -![](fig/DawdyODonnellModel.png) +![](fig/DawdyODonnell.png) +*Schematic diagram of the overall model of the hydrological cycle (from Dooge and O'Kane, 2003).* ## GR4J @@ -70,6 +71,16 @@ A three layer model built to model Lysimeter water balances. Here a simple linea The Quinn model is the original land surface model used with TOPMODEL. When the Quinn model is used in isolation, a simple linear baseflow model is added to handle drainage. +Where the Quinn model differs is that it ca account for a shallow water table. + +![](fig/Quinn.png) + +*A simple version of the vertical storage element in the Quinn model. $S_i$ is the local gravity drainage storage deficit, $q_v$ is local recharge to the saturated zone and $\psi_o$ is the depth of the "capillary fringe" (Beven etal., 1995).* + +$$ + s_i = (\theta_s-\theta_\text{fc})(z_i-\psi_o)=\Delta\theta_1(z_i-\psi_o) +$$ + ## SIXPAR @@ -96,10 +107,14 @@ Bergström, S., 1976. Development and application of a conceptual runoff model f Bergström, S., 1992. The HBV model - its structure and applications. SMHI RH No 4. Norrköping. 35 pp. +Beven, K.J., R. Lamb, P.F. Quinn, R. Romanowicz, and J. Freer, 1995. TOPMODEL. In Singh V.P. editor, Computer Models of Watershed Hydrology. Water Resources Publications, Highland Ranch, CO: pp. 627—668. + Buytaert, W., and K. Beven, 2011. Models as multiple working hypotheses: hydrological simulation of tropical alpine. Hydrological Processes 25. pp. 1784–1799. Dawdy, D.R., and T. O'Donnell, 1965. Mathematical Models of Catchment Behavior. Journal of Hydraulics Division, ASCE, Vol. 91, No. HY4: 123-137. +Dooge, J.C.I., and O'Kane, P., 2003. Deterministic Methods in Systems Hydrology: IHE Delft Lecture Note Series (1st ed.). CRC Press. + Duan, Q., S. Sorooshian, V. Gupta, 1992. Effective and Efficient Global Optimization for Conceptual Rainfall-Runoff Models. Water Resources Research 28(4): 1015-1031. Gupta V.K., S. Sorooshian, 1983. Uniqueness and Observability of Conceptual Rainfall-Runoff Model Parameters: The Percolation Process Examined. Water Resources Research 19(1): 269-276.