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Elements | Water flows | ||
---|---|---|---|
A | = area | P_atm | = precipitation |
atm | = atmosphere | E_atm | = evaporation |
PR | = paved roof | T_atm | = transpiration |
CP | = closed paved | R_up | = decoupled runoff |
OP | = open paved | R_ow | = runoff to open water |
UP | = unpaved | I_uz | = infiltration |
OW | = open water | P_gw | = percolation |
UZ | = unsaturated zone | D_ow | = drainage |
GW | = groundwater | S_out | = downward seepage |
MSS | = mixed sewer system | R_mss / R_swds | = runoff to sewer systems |
SWDS | = stormwater drainage system | SOF | = sewer overflow on street |
SO | = sewer overflow | Q_ow | = discharge to open water |
WWTP | = waste water treatment plant | Q_out | = discharge to outside / WWTP |
History
Originally the time step was 1 day. That way time series of more than 100-year rainfall and evaporation could be managed in EXCEL. A smaller time step could also be applied (1 hour, 15 minutes, 5 minutes). However, because of the limitations of EXCEL, a smaller time step implies much shorter time series. Transforming the water balance tool to a set of Python scripts solved this limitation. This set of Python scripts that has been combined in the Urbanwb model. This documentation describes the Urbanwb model.
Model purpose
This tool has been developed to determine the return periods of runoff events for relatively small urban areas in which the basic hydro(geo)logic conditions are assumed to be similar for the entire area. Determination of runoff return periods requires large time series of rainfall and evaporation, preferably at least 30 years.
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Figure 1 provides a schematic overview of Urbanwb model with its fundamental elements included. Under this conceptual framework, major hydrological dynamics in an urban water system can be quickly and indicatively modelled modeled to provide users with a general idea of the water quantity distribution and how the water system behaves under certain conditions.
Below you find a brief introduction of the major components of the Urbanwb model. Chapter 2 describes these components into much more detail.
1.2 Major components
In the Urbanwb, the land use area is divided into:
Notes
- The Urbanwb model is based on a Dutch urban area in a polder system (Figure 3) with a controlled target water level. However it can also be applied in other areas than polders. In those cases the target water level is the applied drainage water level of that area.
- The open water area is an essential part of the Urbanwb model. All excess water in the urban area first flows to the open water area, before it is discharged from the urban area (except for the water of the mixed sewer system that flow to the WWTP). Therefore the open water area size always has to be larger than 0.
- In case an urban area is modeled that contains no open water, an open water area has to be added to the model artificially (advised is to add in those cases an open water area size of a few percent of the total urban area).
1.2 Major components
In the Urbanwb, the land use area is divided into:
- Paved area above floor level
o Paved Roof (PR), i.e. buildings. - Paved area at floor level
o Closed Paved (CP), completely sealed.
o Open Paved (OP), allowing some infiltration. - Unpaved area at floor level
o Unpaved (UP). - Paved area above floor level
o Paved Roof (PR), i.e. buildings. - Paved area at floor level
o Closed Paved (CP), completely sealed.
o Open Paved (OP), allowing some infiltration. - Unpaved area at floor level
o Unpaved (UP). - Surface water at floor level
o Open Water (OW).
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class urbanwb.Unpaved.Unpaved(fin_intstor_up_t0, up_no_meas_area, up_meas_area, up_meas_inflow_area, intstorcap_up=20, infilcap_up=48, soiltype=2, croptype=1, **kwargs) [source]
Bases: object
Creates an instance of Unpaved class with given initial states and properties, iterates sol() function to compute states and fluxes of Unpaved at each time step.
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Figure 9 shows the schematic overview of the Unsaturated Zone. Two important definitions are recapped here. Field capacity is the amount of water that a well-drained soil can hold against gravitational forces. In the absence of water supply, the water content in the root zone decreases as result of water uptake by the crop. As water uptake progresses, the remaining water is held to the soil particles with greater force, lowering its potential energy and making it more difficult for the plant to extract it. Eventually, the so called wilting point is reached where the crop can no longer extract the remaining water in the soil and the water uptake becomes zero. The wilting point is the soil water content at which plants will permanently wilt.
Figure 9 Schematic overview of Unsaturated Zone (UZ) in Urbanwb
Figure 10 shows how the transpiration reduction factor is related to soil water pressure head h (i.e. root zone water potential). In the range between h3 (transpiration reduction point) and h2 (field capacity), root water uptake is optimal (maximal), so the transpiration reduction factor α= 1.
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The threshold pressure h3 increases with potential transpiration rates, i.e. daily crop-evaporation. For low potential transpiration rate, the threshold pressure h3l is lower than the threshold pressure h3h at high potential transpiration rate. Computational simplifications are made here to calculate daily crop-evaporation value. Evaporation data are often provided on daily basis. When the Urbanwb model is applied for smaller time steps (Δt), we derive the hourly values of h3 based on the daily evaporation values by divided by 2Δt, where Δt is expressed in days (e.g. Δt = 1 hour = 1/24 day). The factor 2 is applied, based on the assumptions that evapotranspiration mainly occurs during day time and that day time lasts on average 12 hours.
Figure 10 Transpiration reduction coefficient in Urbanwb (i.e. plant water stress factor) in relation to root zone water potential. Source: Dejongvanlier et al, 2008.
Some applied concepts regarding evapotranspiration based on literature are:
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The formula of groundwater level during current time step h(t) and its derivation are shown below (Figure 12 ). In this figure, P is percolation (assumed to be constant during a time step), qs is downward seepage to deep groundwater, qd is drainage to Open Water. All these water flows can get positive as well as negative values, negative meaning flow in the other direction. In Urbanwb all relevant levels are relative to the surface level, where the unit (m-SL) means meter below surface level.
Figure 12 Groundwater level h(t) calculation
Seepage: Drainage: Continuity:
Substitution results in:
Initial condition:
Figure 12 Groundwater level h(t) calculation
The basic applied formula is:
Seepage: Drainage: Continuity:
Example (check):
h(t) = 1 m –MV; PP = 1.5 m –MV; H = 2 m –MV; c = 1000 d; w = 50 d :
qs = (2 – 1) / 1000 = 0.001 m/d = 1 mm/d (downward)
qd = (1.5 – 1) / 50 = 0.01 m/d = 10 mm/d (outflow)
Two options for seepage are available.
In option 1 the seepage is dependent of the difference between the variable groundwater level and a user defined constant hydraulic head of the deep groundwater (H) over a hydraulic resistance (c) of the layer in-between.
In option 2 the seepage is defined as a constant water flow.
Important note: all parameters in these formulas are in meters and days. For different time step sizes water flows expressed in meter per time step need to be adapted.
Option 1. Seepage is groundwater level dependent
Substitution in continuity equation results in:
Rewritten:
Solving:
Initial condition:
Resulting in:
Drainage (qd) and seepage (qs) are automatically calculated in depth per day, because the sizes of both flow resistances (w and c) are expressed in days.
Percolation (P) is expressed in depth per time step, hence must be divided by the time step size (t [d])
Option 2. Seepage is constant
Substitution in continuity equation results in:
Rewritten:
Solving:
Initial condition:
Resulting in:
Drainage (qd) is automatically calculated in depth per day, because the size of the flow resistances (w) is expressed in day.
Seepage (qs) is defined as a constant flow, expressed in depth per day.
Percolation (P) is expressed in depth per time step, hence must be divided by the time step size (t [d])
2.6.1 Assumptions
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Return type: (dictionary)
2.8 Open Water (required area > 0)
Open Water in the Urbanwb model refers to all controlled Open Water bodies, e.g. ditches, canals and ponds. In the Urbanwb model the open water has a fixed target level. Above this level, water will be discharged to outside water, limited by a user defined discharge capacity. In the Urbanwb model, the minimum open water level is the defined target water level. If evaporation losses result in water level below the target level, water will be let in (with unlimited capacity) from outside water to maintain the target water level. Open Water can be deemed as an abstract term reflecting system storage capacity. By assumption, all runoff from Unpaved and all sewer overflow into the street flow directly to the Open Water. Also, sewer system outflow and groundwater drainage will recharge the Open Water. During simulation, under successive heavy rain events, Open Water level may exceed the target level due to insufficient storage capacity and discharge capacity, indicating there is excessive water that the urban water system cannot handle. This can represent all kinds of real urban flood phenomena. In the current version of the Urbanwb model water above surface elevation level cannot flow (directly) to the other surface areas and cause flooding in these areas. Hence the maximum water level in the Open Water is not limited. The storage height above the target Open Water level is calculated to understand the storage requirements of the water system. Maximum storage height on Open Water for a certain flood event multiplied with the Open Water area reflects the required storage capacity for the total study area for that event. To sum up, Open Water component is an abstract recipient water body that indicates the required storage capacity of the system. Figure 13 shows the schematic overview of the Open Water.
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Below some examples of how to conceptualize measures are provided:
- Blue roof
Blue roofs (without drainage) create extra water storage on buildings from where water can evaporate. A blue roof can be considered as a storage installation. In the Urbanwb model, it can be simulated with the basic model or with the Measure module. Simulating a blue roof with the basic model can be done by increasing the PR interception capacity. However, then interception capacity of the entire PR area increases. To simulate that in only part of the PR area blue roofs are applied, the Measure module can be used. A blue roof can be conceptualized as a 1-layer structure of which an interception layer with certain storage capacity is defined from where only evaporation is possible. Exceedance of the storage capacity results in overflow. Overflow from a blue roof is considered to be uncontrolled runoff and will be drained to the SWDS. - Wet pond:
Figure 15 shows the schematic view of how a wet pond is conceptualized. An artificial wet pond can be seen as a 2-layer structure, of which the interception layer is a pseudo layer that has no storage capacity and infinite infiltration capacity, allowing all water (precipitation and inflow runoff from contributing area) to flow directly into the bottom storage layer. A wet pond usually has a sealed concrete bottom to prevent it from falling dry thus percolation is defined not possible. The wet pond has a certain threshold (drainage level) above which the excess water is slowly drained. This runoff is called controlled runoff. The higher the water level in the pond above this threshold, the faster it drains. In addition, a drainage resistance has to be defined by the user to determine how fast it drains. Evaporation from the pool is possible and is limited by Penman evaporation. In case of very extreme rainfall events, incoming runoff may completely fill the storage capacity of wet pond, hence overflow from the wet pond occurs. Unlike controlled runoff from bottom storage layer, this overflow is an uncontrolled runoff, and will be drained eventually to SWDS.
Figure 15 Conceptualization of a wet pond. Source left figure: [LID].
- Bioswale and green roof
Figure 16 shows the schematic view of how a bioswale is conceptualized. A bioswale is an infiltration installation. An bioswale can be thought as a 3-layer structure, of which the surface vegetated soil is the interception layer that provides limited storage capacity and facilitates infiltration to the growing medium. The growing medium is the top storage layer where plant transpiration and soil evaporation occur. After evapotranspiration, excessive water infiltrates into the bottom drainage layer. Below the growing medium is the gravel drainage layer encouraging water percolating into the groundwater reservoir. Here the percolation flux can be modelled either as percolation to groundwater limited by saturated permeability of soil, or as a controlled runoff to groundwater dependent on predefined drainage level and resistance to mimic the water jamming. Evaporation from the bottom drainage layer is possible when potential evapotranspiration rate exceeds the transpiration from growing medium (top storage layer), to simulate that the plant roots can uptake water from drainage layer for further transpiration. Overflow from the bottom drainage layer and surface overflow from interception layer together form the uncontrolled runoff, which will be drained to the SWDS. Similar to a bioswale, a green roof is also modelled as a 3-layer structure. However, there are two major differences: 1. A green roof is installed on the building roof, thus controlled runoff directs to the SWDS instead of to GW; 2. The calculation formula for green roofs is specifically modified to make sure no surface submergence from green roof is possible because a normally functioning green roof should have no water logging on the surface.
Figure 16 Conceptualization of a bioswale. Source left figure: [LID].
2.9.1 Assumptions
- A measure can be defined as 3-layer. Even though the area of each layer of measure can be defined different, it is not recommended to do so because it has not been fully tested yet.
- The measure inflow area does not necessarily come from one source. For instance, if a measure is defined in the OP area, it is possible to define the measure inflow area not only in the OP area but also in the PR and the CP area. However, these possibilities have not been fully developed and tested yet. It’s users’ responsibility to pay attention to the boundary conditions of the model.
- Not all measures can be implemented with Measure module or implemented with the Urbanwb model. The user should understand the correct way of using this Urbanwb model and should be careful with the limitations of this model.
2.9.2 Calculation order
- Determine the rainfall on the measure for the current time step.
- Determine the runoff from the measure inflow area to the measure for the current time step.
- Determine the initial interception storage of measure. Initial interception water budge budget includes interception storage at the end of previous time step + rainfall + runoff from measure inflow area in case runoff is defined to flow to interception layer.
- Determine the evaporation from the interception layer of the measure, limited by Penman evaporation.
- Determine the downward infiltration from the interception layer. Downward infiltration from the interception layer is only possible when the measure structures contain at least 2 layers.
Note: Downward infiltration calculation for a green roof is separately defined. - Determine the surface overflow from the interception layer of the measure.
- Determine the final interception storage on the interception layer of the measure.
- Determine initial storage in top storage layer of measure. When measure structure contains only 2 layers. This storage is zeros (when 2 layer — no top storage layer is involved, all the variable related to top storage layer will be zero.) When 3 layer, initial storage in top storage layer of measure is storage at previous time step + downward infiltration from interception layer.
- Determine transpiration from top storage layer of measure, limited by water availability and Penman evaporation multiplied with a predefined reduction factor.
- Determine the percolation from the top storage layer of the measure to the bottom storage layer of the measure.
Note: This variable is separately defined for green roof type measures. - Determine the final storage in the top storage layer of the measure, limited by the predefined storage capacity of the top storage layer of the measure.
- Determine the initial storage in the bottom storage layer of the measure.
- Determine the evapotranspiration from the bottom storage layer of the measure. Transpiration from the bottom storage layer can only occur when defined possible and when the transpiration capacity exceeds the transpiration from the top storage layer in case of 3 layers.
- Determine the percolation from the bottom storage layer of the measure to the groundwater. Specify whether this percolation is limited by the groundwater level or not. If not, the limitation will only be the saturated permeability. It is recommended to specify percolation being not limited by the groundwater level.
- Determine the controlled runoff from the bottom storage level of the measure. The controlled runoff can be modelled as either a constant flux or as a dynamically-computed flux that depends on a user defined drainage level and resistance.
- Determine the final storage of the bottom storage layer of the measure.
- Determine the overflow from the bottom storage layer of the measure if the bottom layer is completely filled.
- Determine the outflow from the measure to OW, UZ, GW, SWDS, MSS, Out
2.9.3 Code and input arguments
class urbanwb.measure.Measure(tot_meas_area, runoff_to_stor_layer, intstor_meas_t0, EV_evaporation, num_stor_lvl, infilcap_int_meas, storcap_top_meas, storcap_btm_meas, stor_top_meas_t0, stor_btm_meas_t0, storcap_int_meas, top_meas_area, ET_transpiration, evaporation_factor_meas, IN_infiltration, infilcap_top_meas, btm_meas_area, btm_meas_transpiration, connection_to_gw, limited_by_gwl, k_sat_uz, btm_level_meas, btm_discharge_type, runoffcap_btm_meas, dischlvl_btm_meas, c_btm_meas, surf_runoff_meas_OW, ctrl_runoff_meas_OW, overflow_meas_OW, surf_runoff_meas_UZ, ctrl_runoff_meas_UZ, overflow_meas_UZ, surf_runoff_meas_GW, ctrl_runoff_meas_GW, overflow_meas_GW, surf_runoff_meas_SWDS, ctrl_runoff_meas_SWDS, overflow_meas_SWDS, surf_runoff_meas_MSS, ctrl_runoff_meas_MSS, overflow_meas_MSS, surf_runoff_meas_Out, ctrl_runoff_meas_Out, overflow_meas_Out, greenroof_type_measure, **kwargs) [source]
Bases: object
Creates an instance of Measure class with given initial states and properties, iterates sol() function to compute states and fluxes of measure at each time step.
Parameters:
- tot_meas_area (float) – total area of measure [m^2]
- num_stor_lvl (int) – predefined number of storage layers [1, 2 or 3]
- runoff_to_stor_layer (int) – predefined selection at which measure layer runoff from other area is stored, inflow runoff can only take place at interception layer (1) or at bottom storage layer (3) [1 or 3]
- Active processes (#) –
- EV_evaporation (int) – predefined selection if evaporation from measure interception layer is possible (1) or not (0) [0 or 1]
- ET_transpiration (int) – predefined selection if evapotranspiration from measure is possible (1) or not (0) [0 or 1]
- IN_infiltration (int) – predefined selection if infiltration from measure is possible (1) or not (0) [0 or 1]
- SD_delay (int) – predefined selection if slow drainage from measure is possible (1) or not (0) [0 or 1]
- FD_pumping (int) – predefined selection if fast drainage from measure is possible (1) or not (0) [0 or 1]
- RTC_realtime (#) – predefined selection if real- me-control release from measure is possible (1) or not (0) [0 or 1]
- Interception layer (#) –
- storcap_int_meas (float) – predefined storage capacity of interception layer of measure [mm]
- infilcap_int_meas (float) – predefined infiltration capacity of interception layer of measure [mm/d]
- stor_int_meas_t0 (float) – initial storage in interception layer of measure (at t=0) [mm]
- Top storage layer (#) –
- top_meas_area (float) – predefined area of top storage layer of measure [m^2]
- storcap_top_meas (float) – predefined storage capacity of top storage layer of measure [mm]
- infilcap_top_meas (float) – predefined infiltration capacity of top storage layer of measure [mm/d]
- stor_top_meas_t0 (float) – initial storage in top storage layer of measure (at t=0) [mm]
- Bottom storage layer (#) –
- btm_meas_area (float) – predefined area of bottom storage layer of measure [m^2]
- storcap_btm_meas (float) – predefined storage capacity of bottom storage layer of measure [mm]
- connection_to_gw (int) – predefined percolation (connection) from measure bottom storage layer to groundwater is possible (1) or not (0) [0 or 1]
- limited_by_gwl (int) – predefined limitation of percolation from measure to groundwater if groundwater level is below measure bottom level, limited (1) or unlimited (0) [0 or 1]
- btm_level_meas (float) – predefined bottom level of measure [m-SL]
- btm_meas_transpiration (int) – predefined selection if transpiration from bottom storage layer of measure is possible (1) or not (0) [0 or 1]
- btm_discharge_type (int) – predefined discharge type from bottom storage layer of measure [0:flux or 1:level]
- runoffcap_btm_meas (float) – predefined runoff capacity from bottom storage layer of measure [mm/d]
- dischlvl_btm_meas (float) – predefined discharge level from bottom storage layer of measure [mm]
- c_btm_meas (float) – predefined hydraulic resistance for level induced discharge from bottom storage layer of measure [d]
- k_sat_uz (float) – saturation permeability of soil [mm/d]
- evaporation_factor_meas (float) – predefined evaporation factor of measure [-]
- stor_btm_meas_t0 (float) – initial storage in bottom storage layer of measure (at t=0) [mm]
- Runoff from measure flows to (#) –
- surf_runoff_meas_OW (int) – predefined definition of surface runoff from measure storage 1 (interception level) to Open Water (0 = no, 1 = yes)
- ctrl_runoff_meas_OW (int) – predefined definition of controlled runoff from measure storage 3 (bottom level) to Open Water (0 = no, 1 = yes)
- overflow_meas_OW (int) – predefined definition of overflow from measure storage 3 (bottom level) to Open Water (0 = no, 1 = yes)
- surf_runoff_meas_UZ (int) – predefined definition of surface runoff from measure storage 1 (interception level) to Unsaturated Zone (0 = no, 1 = yes)
- ctrl_runoff_meas_UZ (int) – predefined definition of controlled runoff from measure to Unsaturated Zone (0 = no, 1 = yes)
- overflow_meas_UZ (int) – predefined definition of overflow from measure to Unsaturated Zone (0 = no, 1 = yes)
- surf_runoff_meas_GW (int) – predefined definition of surface runoff from measure to groundwater (0 = no, 1 = yes)
- ctrl_runoff_meas_GW (int) – predefined definition of controlled runoff from measure to groundwater (0 = no, 1 = yes)
- overflow_meas_GW (int) – predefined definition of overflow from measure to groundwater (0 = no, 1 = yes)
- surf_runoff_meas_SWDS (int) – predefined definition of surface runoff from measure to storm water drainage system (0 = no, 1 = yes)
- ctrl_runoff_meas_SWDS (int) – predefined definition of controlled runoff from measure to storm water drainage system (0 = no, 1 = yes)
- overflow_meas_SWDS (int) – predefined definition of overflow from measure to storm water drainage system (0 = no, 1 = yes)
- surf_runoff_meas_MSS (int) – predefined definition of surface runoff from measure to mixed sewer system (0 = no, 1 = yes)
- ctrl_runoff_meas_MSS (int) – predefined definition of controlled runoff from measure to mixed sewer system (0 = no, 1 = yes)
- overflow_meas_MSS (int) – predefined definition of overflow from measure to mixed sewer system (0 = no, 1 = yes)
- surf_runoff_meas_Out (int) – predefined definition of surface runoff from measure to outside water (0 = no, 1 = yes)
- ctrl_runoff_meas_Out (int) – predefined definition of controlled runoff from measure to outside water (0 = no, 1 = yes)
- overflow_meas_Out (int) – predefined definition of overflow from measure to outside water (0 = no, 1 = yes)
sol(p_atm, e_pot_ow, r_pr_meas, r_cp_meas, r_op_meas, r_up_meas, pr_no_meas_area, cp_no_meas_area, op_no_meas_area, up_no_meas_area, gw_no_meas_area, gwl_prevt, delta_t) [source]
Calculates states and fluxes in measure during current time step.
Parameters:
- p_atm (float) – rainfall during current time step [mm]
- e_pot_ow (float) – potential Open Water evaporation during current time step [mm]
- r_pr_meas (float) – runoff from Paved Roof to measure during current time step [mm]
- r_cp_meas (float) – runoff from Closed Paved to measure during current time step [mm]
- r_op_meas (float) – runoff from Open Paved to measure during current time step [mm]
- r_up_meas (float) – runoff from Unpaved to measure during current time step [mm]
- pr_no_meas_area (float) – area of Paved Roof without measure [m^2]
- cp_no_meas_area (float) – area of closed pave without measure [m^2]
- op_no_meas_area (float) – area of Open Paved without measure [m^2]
- up_no_meas_area (float) – area of Unpaved without measure [m^2]
- gw_no_meas_area (float) – area of groundwater without measure [m^2]
- gwl_prevt (float) – groundwater level at previous time step [m-SL]
- delta_t (float) – length of time step [d]
Returns: A dictionary of computed states and fluxes of measure during current time step:
- prec_meas – Direct rainfall on measure during current time step [mm]
- sum_r_meas – Total runoff from Paved Roof, Closed Paved, Open Paved, Unpaved to measure during current time step [mm]
- int_meas – Interception storage on interception layer of measure after rainfall at the beginning of current time step [mm]
- e_atm_meas – Evaporation form interception layer of measure during current time step [mm]
- interc_down_meas – Downward flow from interception layer of measure during current time step [mm]
- surf_runoff_meas – Surface runoff from interception layer of measure during current time step [mm]
- intstor_meas – Remaining interception storage on interception layer of measure during current time step [mm]
- ini_stor_top_meas – Storage in top storage layer of measure at the beginning of current time step [mm]
- t_atm_top_meas – Transpiration from top storage layer of measure during current time step [mm]
- perc_top_meas – Percolation from top layer of measure at the current time step [mm]
- fin_stor_top_meas – top layer storage at the end of current time step [mm]
- ini_stor_btm_meas – bottom layer storage at the beginning of current time step [mm]
- t_atm_btm_meas – transpiration from bottom layer of measure at the current time step [mm]
- p_gw_btm_meas – percolation from bottom layer of measure to groundwater during current time step [mm]
- runoff_btm_meas – runoff from the bottom layer of the measure during current time step [mm]
- fin_stor_btm_meas – bottom storage at the end of the current time step [mm]
- overflow_btm_meas – bottom storage overflow during current time step [mm]
- q_meas_ow – Measure outflow to Open Water during current time step [mm]
- q_meas_uz – Measure outflow to Unsaturated Zone during current time step [mm]
- q_meas_gw – Measure outflow to groundwater during current time step [mm]
- q_meas_swds – Measure outflow to storm water drainage system during current time step [mm]
- q_meas_mss – Measure outflow to mixed sewer system during current time step [mm]
- q_meas_out – Measure outflow to outside water during current time step [mm]
Return type: (dictionary)
3 FAQ
- What are area with measure, area without measure and measure inflow area?
Figure 17 Illustration of measure inflow area
- All individual areal components of the simulation model, PR, OP, etc., mentioned in the documentation, basically are all areas without applied measure. Figure 17 shows an example of applying a measure on OP. If the (green) measure area is 2 m2, and the total OP area is 10 m2, the (blue + grey) area of OP without measure is 10 – 2 = 8 m2.
- The measure inflow area (green + blue) should always be larger than (or equal to) the measure area (green) and limited by the total paved area (green + blue + grey). The total measure inflow area can be larger than the total OP area in the example, when also part of the PR and / or the CP area runoff is diverted to the measure inflow area in OP.
4 References for parameter estimations
- Penman, H. L. (1948). Natural evaporation from Open Water, bare soil and grass. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 193(1032), 120145.
- Monteith, J. L. (1965, July). Evaporation and environment. In Symp. Soc. Exp. Biol (Vol. 19, No. 205-23, p. 4).
- Feddes, R.A., Kowalik, P.J., Zaradny, H., (1978). Simulation of filed water use and crop yield. Simulation Monographs. Pudoc, Wageningen, 189pp
- DE JONG VAN LIER, Q., et al (2008). Macroscopic root water uptake distribution using a matric flux potential approach. Vadose Zone Journal, 2008, 7.3: 1065-1078.
- Allen, R.G., Pereira, L.S., Raes, D., and Smith, M. 1998. Crop evapotranspiration: Guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper No. 56, United Nations, FAO, Rome, Italy.
- STOWA, 2009 rapport 11. VERBETERING BEPALING ACTUELE VERDAMPING VOOR HET STRATEGISCH WATERBEHEER. isbn 978.90.5773.428.1
- Makkink, G. F. (1957). Testing the Penman formula by means of lysimeters. Journal of the Institution of Water Engineers, 11, 277-288.
- Susana, Urban pluvial flooding and climate change: London (UK), Rafina (Greece) and Coimbra (Portugal).
- Benedict, M. A., & McMahon, E. T. (2006). Green infrastructure. Island, Washington, DC.
- LID, Low impact development — a design manual for urban areas.
5 Running the model
5.1 Overview
The script model can be run from windows command prompt or with run.bat file. The latter choice is highly recommended.
For the time being, the most commonly used function is savecsv, batch-run-sdf and batch-run-measure
The running_sample folder in the Urbanwb package includes the sample of running the model for both basic model and model with measure.
Two sorts of input are necessary to start the Urbanwb model:
Dynamic input : The forcing — Hourly time series of Precipitation, potential Open Water evaporation and potential reference crop evapotranspiration. The user is responsible for data preprocessing — clean data, fill vacancy, remove unrealistic data and make sure the data is in float type. Make sure the column name is the same because the script uses the column name to index which data is precipitation and evaporation.
Static input : All the static input parameters are stored in the configuration file suffixed with .ini . Currently, two configuration files are indispensable for every function to use — one is neighbourhood configure file, the other is measure configuration file. If no measure is included in the modelling, please specify measure_applied=false in measure configuration file. Though the script will automatically do some checks after reading the configuration file to make it fool proof, for example it will update the measure-related area with zero if no measure is applied even if it is not zero due to the user’s carelessness, it is highly recommended that the user carefully deals with the configuration input. Besides, the user should modify the parameters according to the local context of his area of interest and expected setups. Be aware of not changing the parameter name, otherwise the model goes wrong. The descriptions of the parameters are in the configuration file, documentation and script docstrings for the user’s cross check.
5.2 Input time series and parameters
5.2.1 Time series (Dynamic input)
The forcing of Urbanwb model is the time series of:
- precipitation (only rainfall considered)
- potential Open Water evaporation (i.e. Penman evaporation – Penman, 1948)
- potential reference crop evapotranspiration (i.e. Penman-Monteith evaporation – Montheith, 1965 or Makkink evaporation – Makkink, 1957)
Note:
If Penman evaporation is not directly available, since it is not straightly measured, but (class-A) pan evaporation data are available, Pan evaporation can be multiplied by a factor 0.77 to convert to Penman evaporation (Linacre, 1994). The model assumes potential Open Water evaporation from actual interception evaporation on paved surfaces. Evapotranspiration for the unpaved areas (and reference crop grass) is assumed to be 0.8982 * Penman evaporation (Droogers, 2009).
Often hourly potential Open Water evaporation data are not available, or even daily evaporation time series are not available. Then assumptions and simplifications will be made on evaporation interpolation. For instance, when only monthly potential evaporation data and daily sunrise and sunset data are available, you can transform to hourly data by:
Hourly time series of precipitation (actually only rainfall) [mm] and potential evaporation of Open Water [mm]. (for grass, it is approximately 0.8982 * Penman evaporation – Droogers, 2009) Length should better be most recent 30 years. Atmosphere is the most crucial exchange to the model. 1. Format:
First, divide the monthly values by the number of days of these months. Second, assume zero evaporation during night hours and determine the hourly evaporation by dividing the daily values by the number of daily hours between sunrise and sunset.
All conversion required to retrieve hourly evaporation have to be done before entering these input data in the model.
The length of the time series of rainfall and evaporation is advised to be 30 years or more, preferably ending as recent as possible.
Regarding formats, CSV file format is preferred with corresponding column names. Check the data on vacancies and unrealistic values. Make sure the data is in float type.
5.2.2 Parameters (Static input)
Land use at or above surface level are divided into 5 components, namely Paved Roofs (buildings), Closed Paved (roads, etc.), Open Paved (pavements, parkings, etc.), Unpaved (grass land, etc.) and Open Water (ditches, canals, ponds, etc.). The fractions of the five land use types should sum up to 100%. The minimum required size of the open water area is larger than 0. In addition, the total area [m2] of the study area is required input. Besides, for paved areas (PR, CP, OP), three additional types of fractions have to be defined:
- disconnected fraction of three paved areas: “Part disconnected from sewer”: This disconnect fraction represents the percentage of each paved area that is disconnected from the sewer system. For instance if this fraction is 5% for Paved Roofs, it implies that 5% of the Paved Roofs (PR) is disconnected to sewer system. Consequently, 5% of the runoff from the Paved Roofs (PR) will not end in the sewer system but is assumed to flow to the Unpaved area.
- part of building above groundwater (GW): “part of buildings above GW”: This fraction means, in terms of Paved Roofs only, how much percentage of Paved Roofs (PR) has its bottom of foundation above the phreatic water table. This fraction in the model defines the total area size of the (shallow) groundwater (GW).
- part of Open Water above groundwater (GW): “Part of OW above GW”: This fraction is more or less similar to part of building above groundwater (GW). It affects the calculation of the size of the groundwater area. Say we have 300m2 Open Water. If this fraction is zero, then groundwater area is limited by this 300m2. If this fraction is 100%, then groundwater will also contain this 300m2 as all Open Water is assumed to be above the groundwater table.
To sum up, type 2 and type 3 fractions influence the total area of (shallow) groundwater (GW). This area is important since all the storage and fluxes in the model are calculated in depth [mm], so the conversion from one component to another component is dependent on the area ratio of these two components. Therefore, these two additional fractions (type 2 and type 3) are defined to determine the actual groundwater area in the model.
Runoff from paved surface to sewer systems only occurs when the surface interception storage capacity can no longer handle excessive rainfall. This runoff can flow to either of the two available sewer systems. The division is defined by the fraction (X%) flowing to the “Storm Water Drainage System”, the part of paved area that has a storm water drainage system. The rest of the paved runoff (100% – X%) is automatically defined to flow to the “Mixed Sewer System”, the part of paved area that has a combined sewer system.
Design standard / Design rainfall of sewer system.
In the Netherlands, the sewer overflow on the street is designed to occur once every two years. Hence 2 year is chosen as the design rainfall return period. Its corresponding rainfall intensity (16.8 mm/hour) is determined by rainfall statistics.
Consequently, for SWDS, the predefined hourly discharge capacity from SWDS to OW is determined by subtracting the interception capacity of the paved areas (1.6 mm) and the storage capacity of the SWDS (2 mm) from the T=2year rainfall intensity (16.8 mm), resulting in 13.2 mm/hr. This 13.2 mm/hour is the discharge capacity of SWDS to Open Water above which sewer water will overflow onto the street.
For the MSS the discharge capacity to the waste water treatment plant (WWTP) is calculated in a similar way. In the Netherlands the combined sewer overflow onto the Open Water is designed to occur approx. six times a year (T=1/6year). The corresponding rainfall intensity is 6.7 mm/hour. This will only occur when the discharge capacity of to the WWTP is exceeded. Hence the discharge capacity from MSS to WWTP is 6.7 – 1.6 (paved area interception) = 5.2 mm/hour.
The storage capacity of the MSS in the Netherlands is assumed to be 9 mm, hence MSS overflow onto street will occur above 16.8 – 1.6 – 9 = 6.2 mm/hour.
Please note that these values can (and have to be) adapted by the user dependent on the actual climate and sewer design of the study area.
5.3 Functions
5.3.1 save_to_csv
This function performs single run of the model. It can save all results or selected results in to an output csv file.
# save all results # module name func name timeseries name neighbourhood measure outputfile python -m urbanwb.main_with_measure save_to_csv timeseries.csv config1.ini config2.ini output.csv # save selected results # module name func name timeseries name neighbourhood measure outputfile variable to save save_all is False -> save selected python -m urbanwb.main_with_measure save_to_csv timeseries.csv config1.ini config2.ini output.csv owl r_pr_swds theta_uz --save_all=False |
5.3.2 batch_run_sdf
This function performs batch run on different pumping capacity to produce database which can be used to plot Storage-Discharge-Frequency (SDF) Curve
Running the model — urbanwb 0.1.0 documentation # mean daily rainfall as baseline q, batch run [4,5] # module name function ts.csv config1.ini config2.ini output.csv random number baseline q default python -m urbanwb.main_with_measure batch_run_sdf ep_ts.csv ep_neighbourhood.ini ep_measure.ini ep2_results.csv --q_list=[4,5] # 4 as baseline q, batch run [10,20] # module name function ts.csv config1.ini config2.ini output.csv random number baseline q predefined python -m urbanwb.main_with_measure batch_run_sdf ep_ts.csv ep_neighbourhood.ini ep_measure.ini ep2_results1.csv --q_list=[10,20] --baseline_q=4 # 3 as baseline q, batch run [min,max,steps] --- [4,8,3] # module name function ts.csv config1.ini config2.ini output.csv [min,max,steps] baseline q:predefined AP: True to enable [min,max,steps]. if False, then q_list random numbers python -m urbanwb.main_with_measure batch_run_sdf ep_ts.csv ep_neighbourhood.ini ep_measure.ini ep2_results2.csv --q_list=[4,8,3] --baseline_q=3 --arithmetic_progression=True |
...
Figure 20 The SDF curve for several return periods
5.3.3 batch_run_meas
This function performs batch run on measure. First do batch run with different (pairs of) values, then do baseline run (no measure). In the end, save the runoff time series into a csv file.
It can vary one parameter with a list of values or vary two parameters at the same time.
# module function ts.csv config1.ini config2.ini output.csv var to change value to update var corresp var value for corresp var baseline runoff measure runoff to save python -m urbanwb.main_with_measure batch_run_measure ep_ts.csv ep_neighbourhood.ini ep_measure.ini ep3_results.csv --varkey="storcap_btm_meas" --vararrlist1=[1050,1200] --correspvarkey=None -vararrlist2=None --baseline_variable="r_cp_swds" --variable_to_save="q_meas_swds" python -m urbanwb.main_with_measure batch_run_measure ep_ts.csv ep_neighbourhood.ini ep_measure.ini ep3_results.csv --varkey="storcap_btm_meas" --vararrlist1=[1050,1200] --correspvarkey="runoffcap_btm_meas" --vararrlist2=[30,40] --baseline_variable="r_cp_swds" --variable_to_save="q_meas_swds" python -m urbanwb.getconstants ep3_results.csv --num_year=30 |
5.4 References
- DROOGERS, P. Verbetering bepaling actuele verdamping voor het strategisch waterbeheer. Definitiestudie. STOWA, 2009.
- PENMAN, Howard Latimer. Natural evaporation from Open Water, bare soil and grass. Proc. R. Soc. Lond. A, 1948, 193.1032: 120-145.
- MONTEITH, John L., et al. Evaporation and environment. In: Symp. Soc. Exp. Biol. 1965. p. 4.
- LINACRE, Edward T. Estimating US Class A pan evaporation from few climate data. Water International, 1994, 19.1: 5-14.