The `dynatop`

package represents an implementation of the concepts behind a dynamic TOPMODEL.
One of the underlying principles of dynamic TOPMODEL is that the landscape can be broken up into
hydrologically similar regions, or Hydrological Response Units (HRUs), where
all the area within a HRU behaves in a hydrologically similar fashion.

While a Hydrological Response Unit (HRU) has typically been thought of as an area of hill slope with, for example, similar topographic, soil and upslope area characteristics the idea may be generalised. In doing this a catchments is conceptualised as a collection of HRUs of different type (e.g. hill slope, channel, lake) which exchange fluxes at specified levels (e.g. saturated zone, surface)

As well as the exchange of fluxes this documents considers two types of HRU. The first termed “hillslope” solves the surface, root, unsaturated and saturated zones for ‘similar’ areas of hill slope the catchment a each time step. The second termed “channel” represents a length of river channel in a simplified manner allowing the extraction of the inflow from the hill slope. The solutions for each of these HRU types are presented in the hillslope and channel vignettes.

The aim of this document is to outline

- the computational sequence and linking the HRUs
- conventions for the input data
- other miscellaneous information that may help developers

Each HRU has a unique reference number in the `id`

variable. In principle the HRUs are
solved in reverse order of `id`

; that is from the largest `id`

value to the
smallest. Currently this not strictly enforced since the C++ code used for the
computation first solves the hillslope HRUs then the channel HRUs, but this
should not be relied upon and may change in future releases.

Fluxes between the HRUs are represented as occurring at two levels, the surface and the saturated zones. For the \(i\)th HRU the outflow in \(m^3/s\) at time \(t+\Delta t\) is \(\left.q_{sf}^{\left[i\right]}\right\rvert_{t+\Delta t}\) at the surface and \(\left.q_{sz}^{\left[i\right]}\right\rvert_{t+\Delta t}\) in the saturated zone.

The fraction of outflow going from the \(i\) th to the \(j\) th HRU is \(f_{i,j}\). The redistribution is conservative as does not vary in time so \[ \sum\limits_{j} f_{i,j} = 1 \] Since there is no exchange between the surface and saturated zones during redistribution the inflows at time \(t+\Delta t\) to the \(k\)th HRU can be computed as \[ \sum\limits_{i>k} f_{i,k}\left.q_{sf}^{\left[i\right]}\right\rvert_{t+\Delta t} \] and \[ \sum\limits_{i>k} f_{i,k}\left.q_{sz}^{\left[i\right]}\right\rvert_{t+\Delta t} \]

The values of \(f_{i,j}\) are specified in the `flow_direction`

data.frame of
the model.

It is expected that the precipitation and potential evapotranspiration inputs series are given in \(m\) accrued over the proceeding time step. So if the data has a time step \(\Delta t\) the value given at \(t+\Delta t\) is accrued in the interval between time \(t\) and time \(t+\Delta t\).

The data series for the diffuse and point inputs used in the channel routing should be in \(m^3/s\). In the channel HRU solution the value given at time \(t+\Delta t\) is presumed to be constant over the interval \(t\) to \(t+\Delta t\).

To aid the readability of the code the variables are labelled consistently with regards to the vignettes. For example:

- Single subscript: \(l_{sz}\) becomes
`l_sz`

, \(s_{uz}\) becomes`s_uz`

etc. - Directional variables: \(q_{rz \rightarrow uz}\) becomes
`q_rz_uz`

, etc. - Greek letters are spelt: \(\lambda\) becomes
`lambda`

However the notation used in the vignettes for intermediate values of fluxes or states (e.g. ) is dropped from the code where it can be inferred from the computational sequence (or comments)

Currently the code uses a purely implicit scheme for the solution of the
hillslope HRUs. This requires a solving a *zero finding* problem for each HRU
at each (sub)time step. Currently a simple bisection algorithm is used with a
user specified tolerance and maximum number of iterations. The tolerance is
defined as the difference between the upper and lower limits of the interval
containing the zero point. Notionally faster algorithms (such as the TOMS-748
algorithm) could be used.