Research and Realization of Non-traditional Water Resources
Optimal Allocation Model
Yating Gao
1
, Na Wei
1,
*, Xiaofeng Song
2
, Jiawei Gu
3
, Feng Yang
1
, Shaofei Zhang
1
and Shuni He
1
1
State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an, Shaanxi
710048, China
2
Hanjiang-to-Weihe River valley water diversion project construction CO.LTD., Shaanxi Province,
China
3
Powerchina Northwest Engineering Corporation Limited, Xi’an 710065, Shaanxi, China
Keywords: Non-traditional water resources, Regional water allocation, Water resource allocation system
Abstract: As the shortage of water resources becomes more and more obvious, it is imperative to incorporate non-
traditional water resources into the water supply system. The utilization of non-traditional water resources in
China is still in its infancy, and the research on the integration of non-traditional water resources into the water
resources allocation system still needs to be in-depth. This paper establishes a multi-objective water resources
allocation model, adopts the weighting method to convert multiple objectives into single objectives, solves
the problem by particle swarm algorithm, and builds a regional non-traditional water resources allocation
system by combining knowledge visualization integration platform, components, and knowledge maps.
Applying it to Tianjin Binhai New Area, a water resource optimization allocation system was established in
Binhai New Area, which realized the water availability of various water sources in the region, the water
demand of each user in the sub-region, the calculation of supply and demand balance, and the allocation of
water resources. The effect of the use of non-traditional water resources on alleviating regional water stress
and the feasibility of the algorithm for co-allocation of non-traditional water resources and traditional water
sources are verified, providing a basis for the allocation of non-traditional water resources.
1 INTRODUCTION
Water is one of the basic elements of human life, but
also to ensure the normal operation of all links of the
entire society indispensable important resources.
However, due to the rapid growth of the world
population and the development of modern industries,
the demand for water resources is increasing, while
the availability of water resources in many areas is
decreasing sharply. In addition, water pollution is
serious and water resources are wasted, making water
shortage an urgent problem to be solved worldwide
(Gao &
Yang, 2005). In order to solve the shortage of
water resources, in addition to conventional water-
saving measures, the development and utilization of
non-traditional water resources are gradually taken as
a breakthrough. Non-traditional water resources are
special water sources different from traditional
surface groundwater resources, mainly including sea
water, brackish water, reclaimed water and rainwater.
At present, the utilization modes of non-traditional
water resources at home and abroad mainly include
seawater desalination, direct use of seawater for
industrial cooling, rainwater collection and utilization,
brackish water irrigation and sewage recycling (Shao,
2017; Zhang, 2015). Due to the limitation of non-
traditional water resources users, they cannot be
allocated according to the traditional water resources
allocation mode, and the unreasonable allocation
leads to the waste and pollution of water resources.
Therefore, the urgent problem to be solved for the
utilization of non-traditional water resources is how
to use them rationally to play the biggest role.
The research on non-traditional water resources
utilization has a history of nearly 100 years and has
made many achievements. Due to the large difference
in water quality, non-traditional water resources have
more constraints in the configuration, and the target
users are relatively single, so they cannot be
configured like traditional water resources. Since the
21st century, with the development of intelligent
optimization algorithm theory and computer
technology, Genetic algorithm (Morshed &
Kaluarachchi, 2000), Ant colony algorithm (Minsker
Gao, Y., Wei, N., Song, X., Gu, J., Yang, F., Zhang, S. and He, S.
Research and Realization of Non-traditional Water Resources Optimal Allocation Model.
In Proceedings of the 7th International Conference on Water Resource and Environment (WRE 2021), pages 351-358
ISBN: 978-989-758-560-9; ISSN: 1755-1315
Copyright
c
2022 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
351
et al., 2000), Particle swarm optimization algorithm
(Mckinney & Cai, 2002), Large-scale system theory
and method (Perera et al., 2005)
and other intelligent
optimization algorithms have been used in the study
of water resource optimal allocation, and the study of
water resource optimal allocation has also developed
from the study of single objective to the study of
multi-objective water resource allocation. There is
still a lack of research on non-traditional water
resource allocation, so the utilization efficiency is not
high.
Like traditional water resources, the utilization of
non-traditional water resources also needs reasonable
allocation. However, due to the uneven quality of
non-traditional water resources, many factors, such as
water quantity and water quality, are often needed to
be considered when included in the overall regional
allocation. The water users are divided according to
the quality of non-traditional water resources, and the
combined allocation of water quality and quantity is
carried out to realize the maximum and optimal
utilization of resources. In this paper, the allocation of
non-traditional water resources was studied. Based on
particle swarm optimization algorithm, a multi-
objective water resources allocation model was
established. With the support of knowledge
visualization integration platform, component
development, knowledge visualization and other
technologies, a regional non-traditional water
resources allocation system was developed and
applied to Tianjin Binhai New Area. The solution of
water resources allocation scheme of Binhai New
Area and three administrative regions under its
jurisdiction is realized, which provides a basis for the
allocation of non-traditional water resources.
2 CONSTRUCTION OF WATER
RESOURCES ALLOCATION
MODEL
2.1 Configuration Model Building
2.1.1 Objective Function
(1) Economic objective: It is usually expressed in
terms of maximizing the net benefit of regional water
supply. The objective function is as follows:
𝑚𝑎𝑥𝑓
(
𝑥
)
=𝑚𝑎𝑥𝑥
𝛽
𝑏
−𝑐
(1)
Where:
𝑏
—The benefit coefficient of water supply from
source 𝑖 to user 𝑗 in sub-region 𝑘, yuan /m
3
;
𝑐
—The cost coefficient of unit water supply
from source 𝑖 to user 𝑗 in sub-region 𝑘, yuan /m
3
;
𝛽
—The water equity coefficient for user 𝑗 i n
sub-region 𝑘;
𝑥
—Decision variable: water supply from source
𝑖 to user 𝑗 in sub-region 𝑘: 10,000 m
3
.
(2) Social goal: The social goal is measured by the
minimum total water shortage in the region. The
objective function is as follows:
𝑚𝑎𝑥𝑓
(
𝑥
)
=−𝑚𝑖𝑛
∑∑
(𝐷
−
∑
𝑥
) (2)
Where:
𝐷
—The water requirement of user 𝑗 in sub-
region 𝑘, 10,000 m
3
.
(3) Ecological environment goal: to cause the least
damage to the environment as the goal. In this paper,
chemical oxygen demand (COD) is mainly taken as
the pollutant index, because it can reflect the pollution
degree more accurately and is relatively easy to
measure. COD discharge is taken as the reference of
pollution discharge, and the objective function is as
follows:
𝑚𝑎𝑥𝑓
(
𝑥
)
=−𝑚𝑖𝑛
∑∑
𝑑
𝑝
𝑥
(3)
Where:
𝑑
—COD concentration in wastewater
discharged by user 𝑗 in sub-region 𝑘, mg/L;
𝑝
—Sewage discharge coefficient of user 𝑗 i n
sub-region 𝑘.
2.1.2 Constraints
(1) Water supply capacity constraints. That is, the sum
of water supply to all users from source 𝑖 should not
be greater than its water supply:
∑
𝑥
≤𝑊
(4)
Where:
𝑊
—Water supply capacity from source 𝑖 ,
10,000 m
3
.
(2) Water constraints
𝐿
≤
∑
𝑥
≤𝐻
(5)
Where:
𝐿
—Upper limit of water demand of user 𝑗 i n
subregion 𝑘;
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352
𝐻
—Lower limit of water demand of user 𝑗 i n
subregion 𝑘.
（3）Non-negative constraint of variables:
𝑥
≥0 (6)
2.1.3 Setting of Decision Variables
(1) 𝑖 represents water source, and 𝑖 =1,2,3,4, and 5
respectively represent local surface water,
groundwater, externally transferred water, reclaimed
water and desalinated seawater.
(2) 𝑗 represents the water sector, and 𝑗 =1,2,3
represents life, production and ecology respectively.
(3) 𝑘 represents the water resources division.
Binhai New Area has three administrative regions
under its jurisdiction: k =1,2,3 are Hangu District,
Tanggu District and Dagang District respectively.
2.1.4 Algorithm Selection
In this paper, particle swarm optimization algorithm
is used to calculate the optimal configuration scheme.
The water users were divided into three categories,
the water supply households into five categories, and
the Binhai New Area was divided into three sub-
regions (Tanggu District, Hangu District, and Dagang
District). Thus, the decision-making variables
reached 45 dimensions. Floating-point coding is
adopted, with each gene in an individual represented
by one floating-point number.
2.2 Fitness Function Construction
Since water resource allocation is a multi-objective
problem, it is very complicated to directly use the
objective function to calculate, so it is considered to
construct the fitness function to transform the multi-
objective into a single objective to simplify the
calculation. As the indexes of each configuration
target are different in dimension and the optimization
criteria are not consistent, some values are better with
a larger value, while others are better with a smaller
value. Therefore, first of all, the optimization criteria
should be adjusted to be consistent. Among the three
objectives, the economic goal is the best when the
economic benefit is larger, the social goal is the best
when the regional water shortage is smaller, and the
environmental goal is the best when the COD
discharge is smaller. Secondly, the three objective
dimensions should be unified, so this paper makes the
following adaptive construction of the objective
function. Use the following interpolation formula to
calculate the standard value corresponding to the
target.
(1) Economic objectives:
𝑃
=
(7)
Where:
𝑃
—The adaptive structure of economic goals;
𝑓
—Value of economic objective function under a
configuration scheme;
𝑓
—The maximum of the economic objective
function.
(2) Social goals:
𝑃
=1−
(8)
Where:
𝑃
—The adaptive construction of social goals;
𝑓
—Value of social objective function under
certain configuration scheme;
𝑓
—The maximum social objective function.
(3) Ecological objectives:
𝑃
=1−
(9)
Where:
𝑃
—The adaptive structure of ecological goals;
𝑓
—Value of the ecological objective function for
a configuration.
𝑓
— Maximum value of the ecological
objective function.
After each target is converted into the standard
value between 0 and 1, the fitness function can be
constructed by weighting and summing these
standard values, i.e.
𝐹=
∑
𝑊
𝑃
(10)
Where:
𝐹—Fitness function;
2.3 Model Parameter Determination
2.3.1 Water Equity Coefficient
The water equity coefficient 𝛽
represents the
priority degree of water supply to users. According to
the importance degree of user, the water supply order
is domestic water supply, production water supply and
ecological water supply. The following formula can
be used to transform the priority degree of water use
into the water fairness coefficient.
𝛽
=
∑
(
)
(11)
Research and Realization of Non-traditional Water Resources Optimal Allocation Model
353
Where:
𝑛
—The sequence number of water user 𝑗 i n
sub-region 𝑘;
𝑛
—Number of all users in sub-region 𝑘.
2.3.2 Target Weight Coefficient
Target weight coefficient 𝑤
reflects the importance
of target 𝑖 in all targets sets in the target system. Both
the sub-region weight coefficient and the target
weight coefficient can be obtained by using the
analytic hierarchy process.
Component
Available groundw ater
in Tanggu District
Component
Available groundwater
in Hangu District
Component
Available groundwater
in Dagang District
Component
Available surface water in
Tanggu District
Component
Available surface water in
Hangu District
Component
Available surface water in
Dagang District
Component
Calculation of
available groundwater
Component
Calcul ation of
available surface water
Component
Statistics of water demand forecast
results in Tanggu District
Component
Water demand forecast
results
Component
Calculation result of
available water supply
Component
Statistics of water demand forecast
results in Hangu District
Component
Statis tics of water demand fo recast
results in Dagang District
Component
Available non-traditional
water resources
Component
Component
Component
Available non-traditional water
resources in Tanggu District
Available non-traditional water
res ources in H a n gu Distr ict
Available non-traditional water
resources in Dagang District
Component
Year selection
Component
Algorithm settings
Component
Parameter setting
Component
Supply and demand
Component
Water Resources Optimal
Allocation Model
Component
Water available for
transfer water
Component
Water available for
transfer water
Component
Water available for
transfer water
Component
Water resources allocation
plan in Tanggu District
Component
Water resources allocation
plan in Hangu District
Component
Water resources allocation
plan for Dagang District
Component
Water resources allocation
plan for Binhai New Area
Figure 1: Regional water resources configuration components.
3 REALIZATION OF REGIONAL
WATER RESOURCES
ALLOCATION MODEL
3.1 Technical Support for Model
Implementation
3.1.1 Knowledge Visualization Integration
Platform
Integrated platform based on SL538-2011 technical
standards for design, overall architecture includes
support layer, resource layer, information integrated
the four levels of layer and user layer, implemented
including discussion support environment, the human-
computer interaction interface, knowledge processing
and management, report generation and management
decision-making, communication and transmission
management, system maintenance, etc. In addition, the
platform makes the model method componentized. By
using components, Web services and other
technologies, each link of business application can be
realized by developing and encapsulating components.
When there are new requirements or businesses,
convenient and rapid modifications can be made, and
the required model can be flexibly built to realize
timely update of services.
3.1.2 Component Development Technology
Component is a unit of software with complete
semantics, correct syntax, and reusable value. It is a
system that can be clearly identified in the process of
software reuse. Structurally, it is a complex of
semantic description, generic interface, and
WRE 2021 - The International Conference on Water Resource and Environment
354
implementation code (Luo, 2009). A water component
is a simple encapsulation of water data and water
methods. It can have its own properties and methods.
Properties are simple visitors to the component data,
and methods are some simple and visible functions of
the component. The purpose of the design of water
conservancy components is to provide information
services for the construction of water conservancy
applications on the comprehensive integrated platform
and provide strong support for the expansion of water
conservancy business applications
(Mao, 2009).
3.1.3 Knowledge Visualization Technology
Visualization is the use of computer graphics and
image processing technology, data into graphics or
images displayed on the screen, and interactive
processing theory, method and technology. The
application of visualization technology in various
fields not only makes each process visually visible
and easy to understand, but also greatly improves the
work efficiency of various industries (Li et al., 2011).
3.2 Water Resources Allocation
Component Division
In order to realize the allocation of water resources,
it is necessary to forecast the water demand, calculate
the available water supply, establish the allocation
model, write the algorithm, set the parameters and
other steps to get the allocation scheme. Each step is
coded by computer and implemented in the form of
components. The components are logically divided
according to the calculation process, as shown in
Figure 1.
3.3 Water Resources Allocation
Components and Systems
Optimization allocation of water resources for the
allocation of water resources, for the area calculation
according to the section on the division of
components, optimized allocation of water resources
need to be work mainly includes the water requirement
of each area, regional supply amount calculation,
model structures and parameters setting, based on the
coupling relationship of components and system
function, the component is added to the mapping
relations with the node, Each node of the digital water
network has its corresponding data or description,
which realizes the function of water resources
optimization configuration at the business level.
4 MODEL APPLICATION
4.1 Research Area Overview
In this paper, the representative Binhai New Area of
Tianjin is selected as the research area. Binhai New
Area is named for its proximity to the Bohai Sea and
is located in the east of the center of Tianjin. The land
area is more than 2,000km
2
, the sea area is nearly
3,000 km
2
, and the coastline is as long as 153km.
Tanggu, Hangu and Dagang are three administrative
regions under its jurisdiction. It is one of the most
economically and technologically developed regions
in China and an important maritime gateway between
north China and the rest of the world. Binhai New
Area has a warm temperate subhumid continental
monsoon climate, with an average annual
precipitation of about 600mm, mainly in summer, up
to 80% of the annual rainfall, and annual evaporation
of 1469.1mm. All the rivers flowing into the sea of the
Haihe River flow into the Bohai Sea through the
Binhai New Area. The main rivers flowing through
Binhai New Area include Chaobai New River, Ji
Canal, Yongding New River, Dushu River, Haihe
River, Ziya New River and other first-grade channels;
There are 11 secondary river courses in Binhai New
Area, with a length of 220km. There is one large
reservoir, namely Beidagang reservoir, seven
medium-sized reservoirs and 23 small reservoirs, with
a total storage capacity of 732 million m
3
. This paper
mainly studies the allocation of non-traditional water
resources in Binhai New Area, and sets 2015 as the
current level year and 2030 as the planned level year.
4.2 Water Resources Allocation System
Application
Figure 2 shows the interface of optimal allocation of
water resources in Binhai New Area. The main water
system map of Binhai New Area is summarized and
various water sources are represented in the map.
Click the icon of the reservoir to view the basic
information of the reservoir. Click the groundwater
icon to view the recoverable amount of groundwater
in each sub-area; Click the icon of non-traditional
water resources to view the availability of non-
traditional water resources in each sub-region; Click
the external water transfer icon to view the water
supply of the corresponding water transfer project.
Research and Realization of Non-traditional Water Resources Optimal Allocation Model
355
Figure 2: Water resources configuration interface of Binhai New Area.
Click the area name node of each district to enter
the water resource configuration interface of the
corresponding district. Figure 3 shows the screenshots
of the water resource allocation system in each zone.
The granularity of water resource allocation can be
realized by the nesting of knowledge graph.
Figure 3: Water resources configuration page for a sub-region.
Click the parameter setting button to adjust the
model parameters of the optimal configuration
algorithm. In addition to the fact that some parameters
linked to the local basic situation have been written
into the components during programming, the weights
of the three configuration objectives, the number of
particle populations and the number of iterations need
to be set.
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356
4.3 Overall Allocation of Water
Resources in Binhai New Area
Click the clock button to select the horizontal year.
Due to space limitation, this paper only shows the
configuration results in 2030, as shown in Figure 4.
The configuration results show that the water
supply in Binhai New Area can basically meet the
demand, and the water shortage is mainly
concentrated on ecological water. The main reasons
are that the weight of ecological objectives in
parameter setting is small and the local surface water
is small, which mainly relies on external water
diversion, which is mainly used for production and
living.
Figure 4: Water resources allocation in Binhai New Area in 2030.
Figure 5: Results of non-traditional water resources allocation in Binhai New Area in 2030.
Research and Realization of Non-traditional Water Resources Optimal Allocation Model
357
4.4 Results of Non-traditional Water
Resources Allocation
Figure 5 shows the allocation of four types of non-
traditional water resources in 2030. It can be seen
from the configuration results that with the increase
of rainwater resource utilization, the available water
supply of domestic water increased significantly.
Through the analysis of the results of non-
traditional water resources allocation, the availability
of non-traditional water resources in Binhai New
Area is increasing. As for the allocation of non-
traditional water resources, the non-traditional water
resources in each region are mainly allocated for local
use, and there is no cross-regional allocation. Tanggu
District has the most non-traditional water resources.
Brackish water in Binhai New Area is used for
production; Rainwater users for life; Sea water is used
for living and production.
5 CONCLUSION
This paper mainly studies the model of incorporating
non-traditional water resources into regional water
resources allocation. The economy, society and
ecology are taken as the objective functions of the
allocation model, and the fitness function is selected
to simplify the multi-objective problem into a single
objective solution. The constraint conditions are
determined, the decision variables are set, the
regional water resource allocation model is
constructed, and the allocation scheme is solved by
particle swarm optimization algorithm. Through the
componentization of water demand prediction,
available water supply calculation, supply and
demand balance calculation and configuration model,
and the coupling of components and system
functions, the optimal allocation system of water
resources in Binhai New Area is established. To
realize the rational allocation of regional non-
traditional water resources, the research results
provide a reference for considering the allocation of
non-traditional water resources.
ACKNOWLEDGEMENTS
This research was funded by the Natural Science Basic
Research Program of Shaanxi Province (Grant No.
2017JQ5076, 2019JLZ-16), Science and Technology
Program of Shaanxi Province（Grant No.2019slkj-13,
2020slkj-16）, the Scientific Research Plan Program
of Educational Department Shaanxi Province (Grant
No.17JK0558) and the Program of Introducing
Talents to Universities (Grant Nos. 104-451016005
and 2016ZZKT-21). The authors thank the editor for
their comments and suggestions.
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