Water demand and ecosystem services of Kenyir Lake

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International Journal of Civil Engineering and Technology (IJCIET)
Volume 10, Issue 02, February 2019, pp. 280-290, Article ID: IJCIET_10_02_031
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ISSN Print: 0976-6308 and ISSN Online: 0976-6316
© IAEME Publication Scopus Indexed
A REVIEW ON WATER DEMAND ANALYSES,
PROVISIONING SERVICE AND CULTURAL
SERVICE FROM ECOSYSTEM OF KENYIR
LAKE, TERENGGANU, MALAYSIA
N. N. I. M. Azlan
Department of Civil Engineering
Universiti Tenaga Nasional, Malaysia
M. A. Malek
Institute of Energy, Policy and Research (IEPRe)
Salina. D
College of Business, Management and Accounting
J. M. Salim
Institute of Tropical Biodiversity and Sustainable Development
Universiti Malaysia Terengganu, Malaysia
T. A. Mohammad
Department of Water Resources Engineering, College of Engineering
University of Baghdad, Iraq
ABSTRACT
This paper presents a synoptic survey on water demand estimation and the
literature review on provisioning services and cultural services that is applicable for
Kenyir Lake, Terengganu, Malaysia. A good water demand method serve as one of the
principal role in planning, operation and management of water supply system of an
area. The water demand methods consider geography of the region, weather and
community characteristics. Identification of ecosystem services namely provisioning
services and cultural services in relation to ecosystem of Kenyir Lake clarify the
contribution of those services in economy. This paper concludes that applicable water
demand estimation for Kenyir Lake is micro-component analysis method. Meanwhile

N. N. I. M. Azlan, M. A. Malek, Salina. D, J. M. Salim and T. A. Mohammad
for the provisioning service is aquaculture and the cultural services are recreation,
ecotourism and cultural heritage have been analysed from ecosystem of Kenyir Lake.
Key words: Water demand, Provisioning services, Cultural services, Micro-component
analysis.
Cite this Article: N. N. I. M. Azlan, M. A. Malek, Salina. D, J. M. Salim and T. A.
Mohammad, A Review on Water Demand Analyses, Provisioning Service and Cultural
Service From Ecosystem of Kenyir Lake, Terengganu, MalaysiaInternational Journal
of Civil Engineering and Technology, 10(02), 2019, pp. 280–290
http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=10&IType=02
1. INTRODUCTION
Insufficient supply of water is a significant issue around the world and it is closely related to
economic growth. When countries especially developing countries have well managed
economy, they are far from having such a problem. Besides that, water scarcities occur when
there is shortage in supply but high in demand. The changes in population growth and climate
change also a part of water depletion thus estimating water demand is a critical step in
governing water demand and supply [1]. There are many studies regarding water demand such
as water demand management and water demand calculation on residential, industrial,
agricultural and commercial water use. Babel and Shinde [2] worked on water demand
calculation using regression analysis and time series methods that resulted in surplus estimation
demand.
There are many factors affecting water demand such as population, water price, seasonal
variations, household demographics and other characteristics. The reliability of water demand
estimation depends on how much factors being considered in relation to the major socio-
economic and climatic factors affects water use [3]. Correspondingly, choosing the right
method in water demand calculation is also crucial. Information collected from any study
determines the suitable water demand method and model need to be picked. It is also important
for proper planning an implementation of water demand management by water providers [3].
Ecosystems of area like lakes also influence the water demand. As water controversy
increases, value of ecosystem services of a lake and any related ecosystem also increases [4].
Liu and Yang [5] clarified that ecosystem services is more significant compare to water demand
estimation. Ecosystem services in simple definition are benefits of ecosystem to human.
According to Millennium Ecosystem (MA) [6], ecosystem services includes, provisioning
services, regulating services, cultural services and supporting services.
Preferable meaning of ecosystem service units in a way that the procedure and financial are
uniform with the interpretation of goods and services used in standard income accounts [7].
Not only the unit of things such as car, house etc. that are bought or sold required to have a
value, but also the ecosystem services. Bear in mind that value and benefits of ecosystem is not
provided to people without the existence of people itself, their communities and built
environment [8].
This paper provide procedures of water demand calculation from broad method and models
for water demand study such as econometric method, micro-component analysis method, end
use methods, artificial neural networks and scenarios based methods with brief explanation on
variable and determinants on each methods. In this paper also presents the synoptic survey on
services and the value of ecosystem. Lastly, the method for water demand estimation and
ecosystem services are mend with current situation of Kenyir Lake, Terengganu, Malaysia for

A Review on Water Demand Analyses, Provisioning Service and Cultural Service From
Ecosystem of Kenyir Lake, Terengganu, Malaysia
future study. Brief explanation on overview of physical conditions and situations at Kenyir
Lake is in the ensuing sections.
2. OVERVIEW ON KENYIR LAKE, TERENGGANU, MALAYSIA
Kenyir Lake is situated in area of Hulu Terengganu and western region of Terengganu. A total
area of 209199 hectare covered Kenyir Lake that comprise of 171199 hectare of land and 38000
hectare of water body. After construction of Sultan Mahmud hydropower station, Kenyir Lake
was formed as South-East Asia’s biggest artificial lake with 369 square kilometres of artificial
lakes [9]. Initially in 1986, Kenyir Lake was inundated to generate hydroelectric power and
receive water from Terengganu River and Terengan River [10]. This man-made lake consist
on 340 islands, 14 waterfalls and plentiful of rivers.
Hakimi et al. [11] stated that ecotourists have high chance to experience Kenyir Lake’s
natural environments due to low density of development in there. Kenyir Lake is a promising
ecotourism destination with numerous natural resources and rich in diversity. The richness of
its forested land offer variety nature-based activities such as jungle trekking, fishing, camping,
visiting waterfalls and caves and also enjoying few parks around Kenyir Lake such as bird
park, orchid park, butterfly park and herbal park. Definition of ecotourism by Ceballos-
Lascurain [12] is visiting and travel that are within undisturbed natural areas and natural
resources, which bring joy and appreciation towards the surrounding nature, encourage
conservation, low tourist influence and benefit significantly for local people in socio economic
involvement.
3. FACTORS AFFECTING WATER DEMAND
Essential water needs in fulfilling human demands namely for showering and toilet use,
cleaning services and household necessities especially in preparing foods and drinks is a
minimum of 50 litres/person day (lpd) [13]. Nevertheless, not all countries are able to meet
such a demand of the basic needs of water mentioned. Worthington and Hoffman [14] verified
that cost per evaluation of water of any household linked to the billing frequency and level of
water consumption. As water consumption increase, the water bill also increases. Water
demand of any household depends on amount of water consumed. Therefore, factors
influencing water consumption also influence water demand. The trend of water consumption
or demand changes from country to country, depending on various factors including climate,
availability of resources, technological advancement, water price structure, incentives and
legislative provisions [15]. Some of the factors affecting water demand to focus in this paper
are population, water price, climate and other attributes.
Numbers of people whether it is big or small affect the water demand of any area. That is
why one factor that acts upon water demand is population. Generally, the number of people
and water demand increase simultaneously because high numbers of people tend to use more
water. However, in the study of Parliamentary Office of Science and Technology (POST) [16]
clarified a single person household consume higher volume of water by 40% than in two person
household. This shows that as the quantity of people increases in a family, they are thriftier in
consuming water. Kenyir Lake is known as ecotourism spot, so large contribution of movable
population is by tourists. It can be proved by Aznan et al. [17], since year 2006, more than
20,000 tourists were attracted to discover Kenyir Lake and enjoy the nature activities for
instance fishing, camping, bird watching, sight-seeing and jungle trekking. The number of
tourists visited Kenyir Lake keeps on increasing every year that is one of the factor to determine
water demand.

Water price is agreed through investigation and study of the water consumption of
consumers related to the economy and population of a country by water providers and
government. The water rate structure varies according the type of building whether it is
residential, commercial or industrial type. Increases and decreases of water demand also
depend on water price. In Singapore, as years goes by they imply a new water tariff and the
result showed decreased in water consumption per capita per day. These also become a notable
instrument to water demand management [18]. For Kenyir Lake, Pengkalan Gawi Jetty uses
water from the state’s water provider. The water provider, Syarikat Air Terengganu (SATU)
has confirmed that the water price structure in this area has not changed for the last 30 years.
Moreover, climate changes also influence the fluctuation of water demand. When
experiencing hot weather, people tend to consume more water for drinking, showering and
gardening. In Malaysia, we only experience dry and wet season and water demand is highly
affected when dry season as the water consumption also high. The importance of climate
change proven in the study of Howe and Lineweaver [19] determined sprinkling water demand
model precisely on summer precipitation and maximum day evapotranspiration. During wet
season, activities around Kenyir Lake are minimal. Boats being the only transportation
available are inconvenient during rainy days. Therefore, less water are consume during wet
season at the parks, chalets and resorts within Kenyir Lake.
Other attributes include access to appliances and household type. An example of access to
appliances is on water closet, whether it is single flush or dual flush. Nowadays, most of the
toilet use water closets with dual flush as it save more water than a single flush. The appliances
use by community of Kenyir Lake is likely of the basic common technology since the place
was open for public in year 1986. Barkatullah [20] also mentioned that other variables, access
to appliances and house size are applicable in affecting water demand. Bungalow house, terrace
house, apartments, and flat is household type that influence water demand. This characteristic
was studied by Russec et al. [21] and found that water demand in detached house was the
highest and vice versa for flat. Detached house is high in water demand, mainly because of
space available for appliances and large area of garden for watering.
4. METHODS USED FOR WATER DEMAND ESTIMATION
Researchers have developed large numbers of methods on water demand estimation. Choosing
the right method for water demand calculation is compulsory in order to achieve high
performance result to use in future water management and planning. Currently, many complete
water demand estimation are easily accessed online but the method is only applicable for
specific geographical regions and climate [3]. However, the application of the method can be
used in other ways with researchers own surveys and study of past literatures. Econometric
method, artificial neural network (ANN), end use method, scenarios based method and micro-
component analysis method is described briefly in next section. In addition, relevant method
of water demand estimation will be choose correspond to Kenyir Lake’s geographical
characteristics.
4.1. Econometric model
To perform econometric method, both models of demand and multivariate requirement need to
be included. According to Singh et al. [3], econometric model for water demand was expressed
by ordinary least square (OLS) multivariate linear regression techniques. The techniques derive
the model by precisely taking account on autocorrelation of error terms. The simple way to
comprehend the variables, model output and measure the elasticity value of econometric model
is using linear regression. In the study of Wang et al. [22], an OLS technique was used to

correlate with linear regression model. And one vital benefit of applying econometric method
in water demands estimation is to verify the individual explanatory variable in elasticity water
demand to changes in dependent variable.
Water scarcity always has close relationship with economic growth and become one of the
main reasons to re-evaluate the water price. This method is simple yet reliable in calculating
water demand. Moreover, it creates interest for water provider which they can use as guideline
to set for water price. Water providers have lack of information in consumer’s water usage such
as household characteristics, garden are, presence of swimming pool and pricing [23]. Study
of water demand using this method is resourceful for water provider as they do not have much
access to explore on micro-level data. Other parameters used in econometric model beside
water price are population, average water consumption and daily mean temperature.
4.2. Artificial neural network (ANN)
Since 90s era, Artificial Neural Network (ANN) has been introduced as effective tool in water
resources application specifically for forecasting and modelling. ANN model is progressively
developing in engineering practices. There are also few techniques of artificial neural networks
have been studied and applied for forecasting of water demand by numbers of researchers that
include Back-propagation, Delta-rule, generalized regression neural network (GRNN),
Kohonen neural network, feed forward neural network (FFNN), cascade correlation algorithm,
conjugate gradient algorithm and radial basis neural network (RBNN) [1,2, 24, 25].
Back propagation of ANN is practiced for the first time in Paris, France regarding hourly
and daily water demand of some communities there [26]. Based on the result of back
propagation ANN, comparison of the result and statistical model was drawn and the
performance of the technique is reliable. Generally, most water demand forecasting made by
researchers only applicable for specific area since many factor contribute in one place such as
meteorological condition, socio-economic variation and government policies. Babel and
Shinde [2] expressed it is mandatory to develop a city specific model in water demand
prediction. And the most accurate and relevant prediction of dynamic artificial neural network
model was using historical water demand as input variable [24, 27, 28].
4.3. Time series method
Direct water consumption estimation method without considering other influencing factor of
water consumption is time series method. This method uses an assumption of historical data in
water consumption and disintegration of various trends that affect water consumption over time
as a foundation for water demand forecasting. Time series method is a traditional approach to
predict water demand in future by multiplying the population per capita estimated in future and
it caused over estimation [29]. Other than that, this method does not take into consideration of
other factor clearly and the low in data accuracy for future reference.
Extrapolative and univariate time series method, exponential smoothing time series method
and box Jenkins autoregressive integrated moving average (ARIMA) or seasonal
autoregressive integrated moving average (SARIMA) model are all techniques of time series
method. The time series method can be used for limited variables is extrapolative while for
larger number of variables is univariate. Exponential smoothing time series method is broadly
used in short to medium term forecasting. While, Box-Jenkins ARIMA or SARIMA model is
suitable for complex profile of discrete-time or continuous-time formulation [30]. This forecast
is generally accurate for short term forecasting since least data required.
4.4. Hybrid method

Hybrid method is combination of two or more method to estimate water demand and aim for
broader verification on water demand calculation. A few combinations of ANNs built by
bootstrap sampling and wavelet analysis were delivered and being compared with
autoregressive integrated moving average (ARIMA), autoregressive integrated moving
average model and exogenous input variables (ARIMAX) and conventional ANNs [31]. The
performance of the combinations was analysed in daily, weekly and monthly and proven that
hybrid method more precise in water demand estimation than the conventional time series and
also ANN models. But the method is not broadly used for water demand forecasting because
extensive data need to be collected and it is costly.
4.3. Micro-component analysis method
Micro component analysis method or end-use method is statistically information collected from
the consumers and the end uses such as occupancy per household, consumer’s age, time taken
of water use in a time, frequency of flushing toilet, doing laundry, washing dish, washing hands
and more [32]. Every water use categories is being considered and added for water demand
calculation. All consumer’s activities and appliances used must be evaluated to avoid under
estimation of water demand.
In micro-component analysis, per capita consumption is calculated by adding up water
contributions for each appliances or activity in a household using the following Eq. (1) [33].
Total water consumption or water demand is a total of each appliances or activities.
= ∙ ∙ + 1
where pcc is per capita consumption, Oi is proportion of household using appliance or activity,
Fi is average frequency of use of appliance or activity, Vi is volume of water consume by
appliance or activity per use and pcr is per capita residual demand.
The change in appliance usage pattern is enough to quantify water demand using this
model. Memon and Butler [15] explained that this method does need significant and specify
data on appliances or activities characteristics. Historical data covering several years is useful
to support the calculated water demand forecasting. And the most accurate and relevant
prediction of dynamic artificial neural network model was using historical water demand as
input variable [24, 27, 28].
5. ECOSYSTEM SERVICES
Russell et al. [34] stated that people around the world hinge on the ecosystem for their living
and these include food, social relationship and spiritual needs. However, most of the main
ecosystems are damaged by human activities [35]. Ecosystem is becoming less valuable and
being ignored due to declining quality of ecosystem [36]. Communities expressing most of the
ecosystem services as ‘no charges’ and not commercialized, inclusive of emotional, cognitive,
and ethical preferences, demands or needs [37]. From that expression, people tend to take
ecosystem for granted. Therefore, to address a value of each ecosystem services, land planning
and decision making process need to be done [38].
Estimating value of ecosystem services has many positive outcome including ecosystem
understanding and concern, detailed guideline analysis, land use developing, and payment for
ecosystem services plans [8]. A variety of approaches applied from different sectors in order
to gain more community involvement in decision-making and valuation of ecosystem [35].
Payment for ecosystem services is the most reasonable method to overcome the degradation of

the ecosystem. There are several methods used, such as benefit transfer, market price, hedonic
price and travel cost.
The research on interactions between ecosystem services has recently gained numbers of
attention in the scientific community [39]. Provisioning, regulating and cultural services
instantly impacting people. However, supporting services need to balance other services.
D’Amato et al. [40] stated that ecosystem services aid in live of the local people in under-
developed areas include provisioning services, such as collection of raw materials; cultural
services, such as value of ecotourism and recreation in forests; and wider socioeconomic
benefits, such as employment, income and local development.
5.1 Provisioning services
The term provisioning means providing or making something available. These services include
food, fibre and fuel, biochemical, natural medicines and pharmaceuticals, genetic resources
and ornamental resources. Provisioning services are extensively known as essential to human
life such as nutrition, shelter and safety [41]. According to Castella et al. [42], some sector of
provisioning ecosystem services become household consumption so they tend to collect it in
their daily life. However, others choose to collect on seasonal time for other needs.
In addition, provisioning services are vital in economic growth and usually have well-
developed markets and valuation systems. In Finland, wood has large contribution in their
economy and the most crucial provisioning service there. Study by Wang et al. [43] also
showed that hydroelectricity provisioning of Daguan, Xizaikou and Tiangong is the most
beneficial to hydropower development which effects the irrigation, flood control, aquaculture
and more.
5.2 Regulating services
The content of regulating services as claimed by The Economics of Ecosystem and Biodiversity
(TEEB) [44], regulating services are the assistance that ecosystems contribute by acting as
regulators such as monitoring the quality of air and soil by disease control and providing flood.
Regulating services include air quality maintenance, bioremediation of waste, water
purification or detoxification, water regulation, natural hazard protection and climate
regulation
Regulating services are more complex than other services but now have caught public
attention by discussion of climate change and natural disaster [41]. Miles and Kapos [45]
discover that there is booming concern in regulating ecosystem services related to climate
change, such as carbon sequestration in different types of ecosystems, including opportunities
to protect carbon stocks in tropical forests, e.g. Reduction of Emissions from Deforestation and
forest Degradation (REDD). [24, 27, 28].
5.3 Cultural services
The Millennium Ecosystem Assessment [46] defines cultural services as non-material benefits
that people obtain from ecosystems. The list of cultural services is spiritual and religious
values, social relations, aesthetic values, cultural heritage values, recreation and ecotourism.
The value of cultural services slightly depends on ecosystems such as historic building and
paintings. All categories of ecosystem services including cultural services need to show
interaction between the ecosystem structures and functions as required in the biophysical
domain and fulfilment of human needs [41].
Gobster et al. [47] clarified that most cultural services are experienced directly, appreciated
naturally and often raise public support for protecting ecosystem. Besides that, most cultural

services are also delighted in “bundles” and can thus foster the orientation of ecosystem
services management toward multi functionality, which is a frequently expressed, but rarely
achieved desideratum in land-use science and policy [48]. From the study of Plieninger et al.
[48], cultural services was observed close to lakes, fishing ponds, settlements and the
campground with surrounding forest.
5.4 Supporting services
Ecosystem services are generated by ecosystem functions which in turn are underpinned by
biophysical structures and processes called ‘‘supporting services’’ by the Millennium
Ecosystem Assessment [6]. These services are necessary for the production of all other
ecosystem services. Soil formation and retention, nutrient cycling, primary production, water
cycling, production of atmospheric oxygen and provision of habitat are the supporting services.
Fundamental services to all other services is supporting services but their relationship to
one another can be indirect or complex [41]. Rodriguez et al. [49] stated that supporting
services are more likely to be “taken for granted”. The importance of supporting services
cannot be seen clearly by people so they tend to prioritize other services. Supporting services
need to get enough attention as it play an important role to other services.
6. CONCLUSIONS
Based on synoptic survey of water demand estimation from past studies, micro-component
analysis is the most suitable method in water demand estimation for Kenyir Lake. This is
because the information at Kenyir Lake is limited and its developments are not fully
dependable on water being supply by the water provider. Other sources of water were utilized
such as rainfall and lake. By conducting micro-component analyses of each appliances and
activities at Kenyir Lake, water demand can be estimated thoroughly. Apart from this, this
technique involves calculation and comparison from the actual billed water used at some parts
of Kenyir Lake.
Provisioning and cultural services are broad categories that need to be investigated at
Kenyir Lake. Provisioning services involve forest within Kenyir Lake such as wood, timber
and aquaculture. Sultan Mahmud Hydropower Dam located at Kenyir Lake also contributes to
provisioning services since it benefited the community by supplying electricity. Meanwhile,
cultural services are the activities currently taking place within Kenyir Lake. Since cultural
services consider aspects of recreation, ecotourism and cultural heritage, questionnaire and
actual ground data will be collected.
ACKNOWLEDGEMENTS
This study is financially funded by The Chair in Energy Economics (GCEE) Grant: Institute of
Energy Policy Research (IEPRe), Universiti Tenaga Nasional, Malaysia. Project code:
2018002KETST.
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