2.2 Applicability of WEAP in water resource management
WEAP stands for Water Evaluation and Planning System, it is a digital hydrological model supporting water resource assessment and planning, developed and established by Stockholm Environment Institute
WEAP can synthetize issues related to water resource (source distribution, environmental quality and policies related to sustainable exploitation of water resource) into a practical tool for water resource planning.
WEAP operates on the basic principle of water balance, which is applicable to urban and agricultural systems, single basin or transboundary river systems complex. Two key features of the model are (Sieber, J et al., 2005):
- Simulation of hydrological processes in the basin (including evaporation, runoff and absorbency), thereby enabling to assess the water potential of the basin.
- Simulation of human activities on water resources (including water consumption needs and without water consumption), thereby assessing the impact of domestic demand on water resources of the basin, as well as influence from mining activities on water quality.
In WEAP, the water users are divided into groups (Demand sites) and every user could be separated further (e.g. user using drinking water can be divided into sub-groups to use water in rural and sub-groups in urban). Modelers can define an unlimited number of user groups of water user depending on available data. Between the supply sources and users connected by the links provided and regressed. Policy priorities for each household to use and water selection rights (in case an user supplied by various sources) is represented by a set of "rules of priority"
For regression source at a demand node, WEAP allows the creation of regression points with different ratios allowing regression to evaluate the effects of waste source to water quality. In addition, with the capacity of fast developing scenarios, WEAP is suitable to develop the variety of forecasting scenarios which are the base for the researchers and the planers to develop an optimal method for achieving water quality goals, which means that it can solve the inverse problem (proposed water quality objectives), based on these to develop plans for quality control wastewater. Thus in the content of water resources protection, WEAP model can be applied in step 5 and step 6, detailed in the following diagram:
Figure 2. Implementation Steps in water resource protection
However, WEAP is one-dimensional model, therefore the model application in forecasting water quality will have difficulty in cases of studying in tidal affected areas and estuaries.
2.3 Input data
The input data include: data of meteorological and hydrological stations data on people's livelihood, economic and social data, discharge of wastewater into water sources, water treatment plants, data on substances water quality
2.3.1 Hydro-meteorological data
To ensure the accuracy and the consistency of the simulating model during the calculation process, the meteorological and hydrological stations were chosen to have the data long enough and have to be delegates. (40 years of data from 1960 to 2010 was collected at the national meteorological and hydrological center). Data calculated from rain – flow model.
Table 1. Rainfall and meteorological stations representing sub-basin
|
No |
River Basin |
Area (km2) |
Rainfal Station |
Meteorological stations |
|
1 |
Tich |
1330 |
Ba Vi |
Son Tay |
|
2 |
Thanh Ha |
271 |
My Đuc |
Ba Vi |
|
3 |
Đay |
1818 |
Thach That |
Son Tay |
|
4 |
Nhue |
1070 |
Ha Noi |
Ha Noi |
|
5 |
Hoang Long |
1550 |
Kim Boi |
Kim Boi |
|
6 |
Chau Giang |
368 |
Phu Ly |
Phu Ly |
|
7 |
Đao |
185 |
Nam Đinh |
Nam Đinh |
2.3.2 Water demand data
Calculated from documents such as the provincial statistical yearbooks, status and orientation of socio-economic development, status and development orientation of the sectors, status and orientation of land use structure in basin.
2.3.3 Water quality data
Data was collected from the General Department of the Environment (the results of water quality monitoring in Nhue-Day river in 2005-2010). The data is used to provide input data on water quality of water sources as well as to test the model's accuracy
2.3.4 Discharge and Water treatment plant data
The data is used to develop the scenarios of sewage control plan. The data was derived from the planning of sewer and wastewater treatment in residential areas, industrial zones in Nhue - Day River basin to 2030 – Ministry of Construction.
2.4 Modelling and Verification
In this study we use WEAP model to calculate and forecast the trend in the variation of water quality on mainstream of Day River section from Day dam to the end of Ha Nam Province (the segments less affected by tide) with 4 basic parameters of DO, COD, BOD, TSS based on the scenarios of discharging waste water into watercourse. The specific steps to be carried out as follows:
- Modelling calculation diagram in WEAP
- Calibration and verification of flows at nodes
- Calibration and verification of water quality
- Water quality change trend forecasting with scenarios of waste source controlling
After calculation determined the parameters of the model, the forecasting of water quality trend based on the scenarios of discharging wastewater into water sources was conducted.
Define border
Within the scope of this study, the upper boundary of the model was selected at the Day dam with Q, H time series at the outlet of Day dam. Lower boundary is defined at Gian Khau hydrological station.
Middle joint boundary was determined by rain-flow model MIKE NAM integrated into module in WEAP.
The discharge waste source boundaries for the model are calculated based on the plans of the provinces in the basin by 2015 and 2020, taken from Nhue-Day basin environmental protection planning.
2.4.1 Simulating Diagram
The diagram is set up includes: 8 water sources, 36 water demand nodes, 7 rain flow simulation nodes, 75 input nodes, 134 regression nodes, 2 flow stations, 8 wastewater treatment plants.
Figure 3. Simulating diagram in Nhue – Day River Basin
2.4.2 Calibration
The process of calibration is one of the most important steps in running models. Calibration will be an important contribution for assessing the practical of the model. This process involves calibrate the flow at nodes as well as water quality parameters based on flow regression.
2.4.3 Verification
Model verification results are assessed by Nash-Sutcliffe index for monitored and calculated data:
Where:
is observed flow at time i
is simulated flow at time i
is Average observed flow
n is number of observed point of flow process
The more Nash-Sutcliffe index is, the more close the calculated results are with observed data and the model parameters are identified with high confidence level. Normally if Nash-Sutcliffe index is greater than 0.7, then the model parameters are considered as acceptable.
