A Case Study on Integrated Urban Water Modelling using Aquacycle NTUA, 2007
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1 A Case Study on Integrated Urban Water Modelling using Aquacycle NTUA, 2007
2 Contents Motivation Input Data Requirements Case Study - Greater Athens Area Model calibration and validation Formulation and simulation of urban water management scenarios Recommendations 2
3 Why Integrated modelling? Integration of water use and natural processes Respect of all water sources in the water cycle Integration of all components of the water system Sustainable and equitable use of all water resources 3
4 Why Integrated modelling using Aquacycle? Holistic view of the urban water cycle through a conceptual representation of system components: Water uses Water supply Wastewater treatment Integration of: Rainfall-stormwater runoff network Potable supplywastewater network 4
5 Aquacycle Features Not geographically explicit but it can handle spatial and temporal patterns for the various urban water uses Ability to simulate decentralized water and wastewater management Quantitative estimates of water use, stormwater and wastewater production Performance assessment for the entire system and alternative schemes ( what-if scenarios) 5
6 Structure of the Aquacycle Model
7 A daily urban water balance model Indoor water usage Climate Meteorology Site characteristics Daily urban water balance model Unit block scale operations Indoor water consumption Garden irrigation Stonnwater runoff Wastewater discharge On-site stonnwater and wastewater use Output Cluster scale operations Daily iterations for each cluster Road runoff Public open space irrigation and runoff Inflow and infiltration Leakage of imported water Groundwater recharge and base flow Community stormwater and wastewater use 7
8 Temporal and spatial scale Temporal Daily time step Monthly and annual estimates through the aggregation of daily data Spatial Unit Block: e.g. single household, industrial site, public building, commercial unit Cluster: Group of uniform Unit Blocks (e.g. local neighborhood, suburb) + roads + public open space Catchment: Group of Clusters (possibly of different characteristics) Garden Roof Road Unit Block Cluster 2 Pavement Open Space Cluster 1 Unit Block Cluster Catchment Cluster 3 Catchment 8
9 Data Requirements
10 Input Data 1. Indoor water use profile For the different water uses in a house (kitchen, laundry, bathroom, toilet) and household occupancy Prediction of the total water used in indoor activities 2. Meteorological data series Daily precipitation Daily potential evapotranspiration The length of available record data defines the maximum modelling period 10
11 Input Data 3. Unit Block, Cluster & Catchment description data (measured parameters) Related to physical catchment characteristics Values are determined through measurement, observation or local experience 11
12 Input Data 4. Calibrated parameters for stormwater, wastewater and water use User should provide initial values Values should be adjusted for fitting observed data on water supply, wastewater and stomrwater flows 5. Characteristics of applied technical options (e.g. stormwater and wastewater reuse methods) 12
13 Case study: Greater Athens Area
14 Case study: Greater Athens Area Overview Capital of Greece Population of 3,894,573 inhabitants(2001), accounts for 30% of country s total population It is about 400km 2 divided into 4 prefectures Athens has a typical Mediterranean climate Mean annual temperature 18.5 o C Mean annual precipitation 388mm Serviced by water supply network (1,700,000 metered connections) Wastewater network Separate approximately 95-98% Combined stormwater and sewer system in the city centre It is served by a WWTP 14
15 Case study: Greater Athens Area Athens water supply system includes: Surface water 4 reservoirs The Mornos reservoir and the Yliki lake hold 88,5% of the overall storage capacity (equal to 1400 hm 3 ) Groundwater resources More than 100 boreholes 350 km of main aqueducts 15 pumping stations 4 Water Treatment Plants The Athens water supply system 15
16 Modelling Indoor Water Water consumption per capita per day approx. 220 lt (literature) Usage Indoor water usage profile based on literature 10% kitchen 35% bathroom 31% toilet 24% laundry Average household occupancy: 2.6 persons 16
17 Precipitation data & Evapotranspiration estimation Precipitation Data for mean daily precipitation Average mean values from 2 meteorological stations in Athens (Hellenic National Meteorological Service) Evapotranspiration Data Daily mean temperature Mean monthly values for: Relevant humidity Wind velocity Solar radiation Estimation of mean monthly ETp according to the Penman-Monteith method Temperature (oc) mean Temperature ºC mean Temperature ºC 0 Jan-05 Feb-05 Mar-05 Apr-05 May-05 Jun-05 Jul-05 Aug-05 Sep-05 Oct-05 Nov-05 Dec-05 time (days) 17
18 Modelling site characteristics Athens Greater Area 1. Road length 2. Number of road lines 3. Pavement length 4. Road area 5. Pavement area 6. Cluster area 7. Catchment area GIS Data 1. Population 2. Household occupancy Census Data 1. Area of residential block 2. Surface of total roof area in a residential block 3. Garden and Open Space area 4. Number of buildings per residential block Satellite images 18
19 Clusters & Unit Blocks Division into 5 clusters According to different structural characteristics & geography The schematization of unit blocks metered connections total number of Unit Blocks Flat of a multifamily house or Single family house Catchment information Catchment area: 357 km 2 Total road area: 70 km 2 Pavement area: 28 km 2 Open space and garden space area: 147 km 2 Total roof area: 112 km 2 19
20 20 Clusters characteristics Total Area (km²) (5%) 1 20% 11.2 (20%) 3.8 (10%) 10.2 (20%) Road area (km²) 1,300,000 31,000 1,200, , ,000 Population 28 (50%) 5.6 (10%) 11.2 (20%) 3 Semidetached % 0.35 (7%) 3.5 (70%) 4 Industrial 62.1 (30%) (5%) (60%) 5 Detached houses 22.8 (60%) 3.8 (10%) 7.6 (20%) 2 Semidetached 5.1 (10%) 5.1 (10%) 30.6 (60%) 1 Detached Roof area (km²) Pavement area (km²) Garden & Open Space (km²) Cluster ID
21 Measured parameters 21
22 Calibrated parameters Effective impervious area % High trigger-toirrigate ratio 22
23 Technical Options No recycle or reuse methods are presently applied Irrigation requirements are covered only by imported water 23
24 Model Calibration
25 Testing the performance of Imported water is given by: I=IWU+IR+LD IWU: Indoor water use IR: Irrigation requirements LD: Leakage depth Aquacycle (1/2) Equation is highly dependent on: Parameter trigger to irrigate Percentage of open space and garden irrigated Meteorological conditions Precipitation (irrigation is defined as the amount of water required, supplementary to precipitation) Evapotranspiration Calibration results Annual simulated/recorded data = 0.95 Sum of squares of differences (SDOF) = 2 25
26 Testing the performance of Aquacycle (2/2) Wastewater discharge: Rw=IWU+INF+ISI Rw: Wastewater discharge IWU: Indoor water use INF: Infiltration into the wastewater system ISI: Inflow of stormwater into the wastewater system Dependence on network type (separate or combined sewerage system) Surface runoff inflow into the wastewater system Calibration results Annual simulated/recorded data = 0.95 Sum of squares of differences (SDOF) = 1 26
27 Formulation & Simulation of Scenarios
28 Options for stormwater & wastewater reuse Unit Block Cluster Sub-surface irrigation with grey water Rain Tank On-site wastewater treatment unit Wastewater treatment & storage Stormwater storage Aquifer storage & recovery Unit Block Irrigation Kitchen, Laundry, Bathroom, Toilet, Unit Block Irrigation Toilet, Unit Block Irrigation Toilet, Unit Block Irrigation Public open space Irrigation Aquifer recharge with stormwater Catchment Stormwater store Wastewater treatment & storage Toilet, Unit Block Irrigation Public open space Irrigation 28
29 Development of scenarios Baseline Scenario: Water demands are covered only by reticulated water No recycle-reuse methods Scenario 1: Rainwater use (rain tanks) on site Scenario 2: Wastewater reuse (on site waste water treatment and reuse for toilet flushing and irrigation) Scenario 3: Subsurface greywater irrigation (on site use) 29
30 Performance indicators Reduction in the volumes of imported water Minimize freshwater withdrawals Reduction in stormwater run-off Minimize the cost of wastewater treatment in combined networks Minimize pollution to the receiving water body Possibly reduce flood risk Reduction in wastewater discharge Minimize wastewater treatment costs Minimize environmental impacts from untreated wastewater flows 30
31 Scenario 1: Rainwater use Rain tanks Sources of water: Roof runoff Uses: Indoor water use (kitchen, laundry, bathroom, toilet) Outdoor water use (garden irrigation) Rainwater supplies kitchen, laundry, bathroom, toilet uses and garden irrigation Precipitation (Roof runoff) Evaporation Storage volume Indoor water uses (kitchen, laundry, bathroom, toilet) Outdoor water uses (irrigation) 31
32 Scenario 1: Performance Million m³/yr % 14% (Cluster 1) 25% (Clusters 1,2) 41% (Clusters 1,2,3) 42% (Clusters 1,2,3,4) 100% Area of Application Imported water Stormwater run-off Wastewater Discharge 32
33 Scenario 2: On-site wastewater treatment On-site wastewater treatment units: Sources of water: wastewater flows (kitchen, laundry, bathroom, toilet) Uses: Unit block toilet flushing Irrigation Wastewater sources (kitchen, bathroom, laundry, toilet) Treatment Unit Evaporation Storage volume Indoor water uses (toilet flushing) Outdoor water uses (irrigation) 33
34 Scenario 2: Performance Million m³/yr % 14% (Cluster 1) 25% (Clusters 1,2) 41% (Clusters 1,2,3) 42% (Clusters 1,2,3,4) 100% Area of Application Imported water Stormwater run-off Wastewater Discharge 34
35 Scenario 3: Subsurface irrigation with greywater in Unit Blocks Sources: Kitchen, bathroom, laundry, toilet Uses: Garden irrigation in unit blocks Million m³/yr Performance. 0 0% 14% (Cluster 1) 25% (Clusters 1,2) 41% (Clusters 1,2,3) Area of Application 42% (Clusters 1,2,3,4) 100% Imported water Stormwater run-off Wastewater Discharge 35
36 Reduction in imported water volumes Million m³/yr Scenario 1 (Rainwater use) Scenario 2 (On-site WW treatment) Scanario 3 (Sub-surface irrigation with greywater) 0 0% 14% (Cluster 1) 25% (Clusters 1,2) 41% (Clusters 1,2,3) 42% (Clusters 1,2,3,4) 100% Area of Application 36
37 Reduction in stormwater runoff Million m³/yr Scenario 1 (Rainwater use) Scenario 2 (On-site WW treatment) Scanario 3 (Sub-surface irrigation with greywater) 0 0% 14% (Cluster 1) 25% (Clusters 1,2) 41% (Clusters 1,2,3) 42% (Clusters 1,2,3,4) 100% Area of Application 37
38 Reduction in wastewater discharge Million m³/yr Scenario 1 (Rainwater use) Scenario 2 (On-site WW treatment) Scanario 3 (Sub-surface irrigation with greywater) 0 0% 14% (Cluster 1) 25% (Clusters 1,2) 41% (Clusters 1,2,3) 42% (Clusters 1,2,3,4) 100% Area of Application 38
39 Performance overview Imported water (m 3 /yr) Stormwater runoff (m 3 /yr) Wastewater discharge (m 3 /yr) Baseline Scenario No interventions 394,800, ,750, ,190,000 Scenario 1 Rainwater use 359,142,000 (-9%) 82,110,000 (-27%) 237,762,000 (-1%) Scenario 2 On-site wastewater treatment 234,906,000 (-41%) 100,674,000 (-10%) 109,956,000 (-54%) Scenario 3 Subsurface irrigation with greywater 326,298,000 (-17%) 107,100,000 (-4%) 184,212,000 (-23%) 39
40 Recommendations
41 Aquacycle limitations (1/2) The model does not address short-term changes in water use, which in turn affect water supply requirements and wastewater production Does not provide for population changes (e.g. during the summer and holiday seasons) Does not provide for temporal variation in the profile for indoor water usage (e.g. increased washing and showering during the summer season) It is not an event-based model Estimates the total (daily) quantity moved through the urban water cycle Does not estimate peak flows or produce event hydrographs 41
42 Aquacycle limitations (2/2) Long-term simulation The model does not include the possibility to develop scenarios for urban expansion/population growth Water needs are always covered by imported (fresh)water - Simulation under water shortage conditions and water cuts? Indoor water use The typical unit block of a cluster (and therefore the entire cluster) can have only one indoor water usage profile Indoor water usage profiles are differentiated only according to the average household occupancy and not per cluster The model does not take into account technology improvements that result in water saving (e.g. high-efficiency washing machines, lowpressure taps, dual-flush toilets etc.) Technology applications On-site technologies are applied at the household level, implying that each household is a single house Block flats? Cost and water quality estimations are not included in the package 42
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