Iranian Journal of Environmental Health, Science and Engineering Iranian Association of Environmental Health (IAEH) ISSN: 1735-1979 Vol. 4, Num. 2, 2007, pp. 99-106

Iranian Journal of Environmental Health Science & Engineering,Vol.
4, No. 2, 2007, pp. 99-106
DEVELOPING A WATER QUALITY MANAGEMENT MODEL FOR KARUN AND
DEZ RIVERS
 *1M. Afkhami, 2M. Shariat, 3N. Jaafarzadeh, 4H. Ghadiri, 5R. Nabizadeh
 1Islamic Azad University, Sciences and Research Branch, Ahvaz, Iran

  2Science and Research Campus, Islamic Azad University, Tehran, Iran

  3Ahvaz Jondishapoor Medical Sciences University, Ahvaz, Iran

  4Nathan Campus, Griffith University, Queensland, Australia

  5Department of Environmental Health Engineering, School of Public Health,Medical Sciences/University of Tehran, Tehran, Iran
*Corresponding author-Email: info@mehranafkhami.com Tel: +98 611 3365219,
Fax: +98 611 3388474 
 Received 10 January 2007; revised 30 February 2007; accepted 25 March 2007 
Code Number: se07015
Abstract
The Karun and Dez rivers basin are the largest rivers basin in Iran which
  are situated in the south west of
  the country. Karun River originates from Zagros mountain ranges and passing
  through Khuzestan plain,
  reaches the Persian Gulf. Several cities lie along its path of them the most
  important is Ahvaz, the center
  of Khuzestan province. To achieve water quality goals in Karun and Dez rivers,
  a water quality
  management model has been developed through the GIS approach and a mathematical
  water quality
  model. In Karun and Dez rivers, water quality has decreased due to heavy pollution
  loads from Khuzestan
  province cities and surrounding areas. In this survey, pollution sources, land
  use, geographic features an
  measured water quality data of the river basin were incorporated into the Arc-view
  geographic
  information system database. With the database, the model calculated management
  type and cost for each
  management project in the river basin. Until now, river management policy for
  polluted rivers in Iran has
  been first of all to get penalties from pollution sources and secondarily,
  to construct treatment plants for
  the pollution sources whose wastewater is released untreated and for which
  the wastewater quality goal of
  the Iranian Department of the Environment is not met. Different management
  projects with a time
  program were proposed and they were compared with the results of the river
  quality without any
  management approach. It became clear that the results based on the management
  approach were much
  better than those for the unmanaged condition from the viewpoint of the achievement
  of water quality
goals and cost optimization.
Key Words: Dez, Karun, management model, quality, river, water
INTRODUCTION 
More than one third of Iran's total surface 
  water of 94 billion m3 is flowing into the 
  Khuzestan province but ironically most of its inhabitants 
  are suffering from poor quality drinking water, especially during the summer months. More 
  than 70% of the four million population of the 
  khuzestan province, which includes the inhabitants of 
  the provincial capital city of Ahvaz and the two 
  major port cities of Abadan and Khoramshahr, are dependent on Karun river and its subsidiaries (KWPA, 2000 and 2001). According to the 
World Commission on Dam's report (WCD, 2000), Iran with 7.2 million hectares of land under 
irrigation agriculture is the largest in the Middle 
East, followed by Turkey (42 million ha) and Iraq 
(3.5 million ha). A large proportion of Iran's 
irrigated lands are in the Khuzestan province. Country 
wide 90% of Iran's freshwater needs are from groundwater sources and only 10% from 
rivers. In Khuzestan province however the opposite 
is true as 85% of its freshwater need is provided 
by rivers and only 15% taken from groundwater. Five rivers with the total annual capacity of 31 
billion m3/annum flow into the Khuzestan plain, 
among them, Karun, with 22 billion m3/annum being 
by far the largest and also the longest river (860 
km) in the province and in the country as a whole. 
The overall size of the Karun's catchments is 
65,230 km2. Karun originates from the Zagros 
mountain range on the western borders of Iran and 460 
km of its 860 km journey to the Persian Gulf is in Khuzestan's alluvial plain where 
irrigated agriculture has at least a 3000 years history. 
As shown in Fig. 1, for the last 60km of its 
journey, Karun joins Tigris and Euphrates which flow 
in from the Iraqi side of the border, to form a 
large shipping waterway called Arvand River 
(Shiva, 2002). In this study, a GIS based 
management model was introduced to take into account 
the characteristics of the water quality 
management projects and the cost function. To 
date, conventional mathematical programming such 
as linear programming, non-linear programming, dynamic program­ming and integer 
programming have been used to solve the problems for 
regional water quality management. Revelle et 
a1., (1968) developed a river Water Quality 
Management Model (WQMM) using linear programming. 
The principal constraints prevented violation of 
the dissolved oxygen standards and the results of 
the model were compared with those based on dynamic programming. While Liebman and 
Lynn (1966) and Klemetson and Grenny (1985) 
utilized dynamic programming, McNamara (1976) and Fujiwara (1990) developed a 
deterministic WQMM by non-linear programming. A 
WQMM was also developed with integer programming (Bishop and Grenny, 1976; Burn, 1989) 
using transfer coefficients to constitute 
constraint equations. Lohani and Thanh (1979) 
considered river flow as a random variable and a 
probabilistic WQMM was constructed using the 
DO-sag equation. Fujiwara et al. (1987) constructed 
an optimisation problem of linear programming 
using the Streeter-Phelps equation, Lee and Lin 
(2000), their recursive equation and a cumulative probability density function of river flow. 
Genetic Algorithms (Goldberg, 1989) imitate the 
genetic evolution process of creatures in nature in 
order to determine the global optimum in mathematical programming. Genetic algorithms (GA) have 
some practical advantages. First, the concept is 
very simple and easy to understand and it can be 
applied to many problems for which traditional mathematical programming techniques 
are intractable. Second, its searching strategy is 
very efficient and, according to the theory, it will 
finally find the global optimum solution. Chen and 
Chang (1998) did introduce a GA to solve a 
non-linear fuzzy multi-objective programming model, but 
they only considered Biologycal Oxygen Demand (BOD) and Dissolved Oxygen (DO) as 
water quality parameters and the water quality calculation was based on the 
Streeter-Phelps equation. The first objective of this research 
was to develop a WQMM to achieve specific water quality goals (Krenkel and Novotny, 1980) and 
the optimization of management projects costs. 
Most WQMMs can calculate BOD and DO as a standard. For the purpose of this study, 
nitrogen and phosphorus were included in the 
management model of this study as well as BOD and DO. 
With a management approach exact output from the mathematical water quality model can be used 
in this management model. The second objective was to apply this management model to the Karun 
and Dez river, which is heavily polluted, and 
identify whether the management approach 
out­performs other approaches. From the application result, 
a regional water quality management plan would be designed to improve the river water quality. 
Among various sources of pollutants, the focus was 
placed on the pollutants from domestic, agricultural 
and industrial wastes, which are the most 
important factors in the river basin.
MATERIALS AND METHODS 
This study has been done in Khuzestan 
  province, south west of Iran (Fig. 1). A literature 
  review was made through searching in books, journals 
  and different papers. 20 stations were selected at Karun and Dez rivers; then twelve samples 
  were collected monthly from each station. The 
  samples were transferred to the laboratory and 
  were prepared for analysis. The main reference for experimental issues was standard methods for 
  the examination of water and wastewater. SPSS and Minitab software were used to perform a statistical analysis of the results. 
A WQMM, in which water quality calculation results from 
the Qual2e model (Brown and Barnwell, 1987) were accurately reflected in the optimization 
problem whilst considering various water quality parameters such as BOD, DO, total nitrogen 
(TN) and total phosphorus (TP). The management model was applied to the Karun and Dez 
rivers where water quality is so poor that a comprehensive countermeasure for water 
quality restoration is necessary. The Arc-view 
geographic information system (GIS) was used to 
estimate pollution loads for the river basin.
At the end after developing a WQMM to 
  achieve specific water quality goals (Krenkel and 
  Novotny, 1980), introduction of management projects 
  and their cost optimization have been done.
RESULTS 
Salt in the soil profile and groundwater 
Alluvial deposits in Karun and Dez river 
  system, and three other smaller rivers, have resulted 
  in the formation of Khuzestan plain. The plain is 
  very flat and the rivers are prone to regular 
  flooding despite the fact that both Karun and Dez 
  are regulated by a number of large hydro-electric dams. The soil profile is very rich in salt 
  deposits and groundwater is both shallow and highly 
  saline (Ghadiri, 1985; Ghassemi et al., 1995). From 
  about 40km north of Ahvaz where the watertable is 
  less than 1.5m deep, salt accumulation on the soil surface is clearly visible on the surface. As 
  the groundwater table becomes even shallower 
  further south, soil salinity is further widespread. 
  (Afkhami, 2003). The 120 km distance between Ahvaz 
  and Khoramshahr consists almost entirely of highly saline soils with heavy texture and 
  high groundwater table of 0.60-1m. five new large sugar cane projects with the total area of 
  70000 hectares, have been planned for this region 
  (Fig. 1). Groundwater hydrology of the Khuzestan 
  plain also appears to have played a major part in 
  land degradation during the great Persian Empire of 
  2 to 3 thousand years ago. Remnants of irrigation canals from that era can still be seen in 
  regions around Ahvaz, an indication that the land was 
  being used for agriculture but rising ground water 
  and the salinization forced farmers to abandon the lands and move further north or towards 
Mesopotamia. Now after more than 2000 years, the 
government of Iran is trying to leach the salt out of the 
soil profile and resurrect agricultural activities to 
these salt affected lower regions of the Khuzestan 
plain, a very costly exercise with a very doubtful outcome. 
Agriculture 
Agriculture is by far the biggest consumer 
  and polluter of the Karun river. Table 1 shows the current and predicted water consumption by 
  the three main users of the Karun river. The total 
  water consumption of agriculture and fish farming activities is currently around 10 billion 
  m3/annum with plans to expand this amount by 
  approximately 80% over the next 10 years. In the 
  Agricultural sector, the main contributors to the 
  deterioration in water quality are large agro-business units 
  in Dezful region, large scale government owned sugar cane plantations with their modern 
  irrigation and drainage systems and private farms and 
  fish farms established along the Karun and Dez 
  river system itself. By far the biggest single 
  problem that the Karun river is facing is its rising level 
  of salinity which is already above the drinking 
  water limit (WHO, 2004) for several months of the year  for the two downstream cities of Abadan 
and Khoramshahr. Prior to growing sugar cane in 
these five new multi-million dollar projects, an 
elaborate and expensive drainage system has to be put 
in place and salt has to be washed down the soil profile and into the drainage system through 
the ponding technique.
Industrial effluents 
Khuzestan is the most industrialized province 
  of Iran and more than 25% of Iran's heavy 
  industries are located there. Most water polluting 
  industries of Iran such as the petroleum industry, gas 
  and sugar refineries, petrochemical factories, 
  paper mills, gas and petroleum based power plants, 
  steel plants and other heavy industries are built in 
  and around the provincial capital city of Ahvaz on 
  the banks of the Karun river. As well as using 
  Karun water for their needs, these industries release 
  their sewage effluent directly into this river 
  mostly without any treatment. Further downstream of 
  the river and near the twin port cities of Abadan 
  and Khoramshahr, where the Karun joins the 
  Euphrates and the Tigris rivers, large petrochemical 
  plants, petroleum refinery, soap factory and many 
  others further contribute to the degradation of 
  water quality in the Karun. In total, more than 315 
  million cubic meters of industrial sewage effluent 
  directly enters into Karun river annually. 
 Municipal effluent 
The majority of Khuzestan's population of 4 
  million is directly dependent upon Karun for their 
  drinking and sanitary water consumption. Municipal sewage from several large and small cities 
  such as Ahvaz, Abadan, Khoramshahr, Dezful, Shoushtar, Mahshahr, and Masjed-Soleiman 
  enters the river.  Table 2 shows the volume, flow 
  rate and the salinity (Electric Conductivity, EC) of 
  some of the sewage discharge entering Karun river 
  in an untreated form from these municipalities. 
Seawater intrusion 
The border river of Arvand Rood, which is 
  formed when the Karun and the two Iraqi rivers of 
  Tigris and Euphrates join together, as well as being 
  a major shipping waterway for both countries, irrigates the largest date palm plantation in 
  the world. In recent years both Iran and Iraq have significantly increased water uptake from 
  their respective rivers resulting in a decrease in the 
  flow rate in Arvand Rood. This has lead to an 
  increase in the distance upstream that sea water is 
  now capable of reaching during the high tides. 
  During the drought years of 1998-2001 sea water 
  backed up to the main pumping stations of the city 
  of Abadan severely contaminating its drinking 
  water supply. The date palm plantation industry 
  has already been damaged by the steady rise in 
  river salinity. Seawater intrusion, if it continues, 
  will ultimately destroy both countries' multi-million 
  dollar date export industry given time.
Water quality model and pollution load 
QUAL2E was chosen as the water quality 
  model for this study because it is a one dimensional 
  steady state model and it is easily applicable to this 
  type of management. Modeling was performed from the Shahid Abasspoor and Dez
  Dams, which  are located in the upper parts of the rivers, to 
  the estuary bank as shown in Fig. 1. The main 
  river channel was divided into 5 reaches. 
  Hydraulic calculations in the QUAL2E model were performed with the depth-flow
  and  velocity-flow equation (Brown and Barnwell, 1987). Initially, 
  the model was calibrated using the data set 
  observed at the Karun river in 1999 from Karun 
  river waterway project. Immediately after joining 
  the effluent flow of the Karun Dez river. However the calculated BOD and DO
  were lower  than those observed in 1999. Likewise, the water quality data for
  stations observed on different sampling dates were also compared with the
calculated values. Data sets of the model for 
verification including point source pollutant loads and 
stream flow were prepared based on conditions in 
October 2002 till September 2003. Unfortunately, as a 
large volume of water is needed for agricultural use 
in some special months, thus, the fluctuation of 
the river water quality is very high, and it was 
difficult to use the observed data for that particular 
date for verification. For BOD and DO, the 
calculated results show quite a good correspondence with the standards. To obtain
pollution load data from point sources and incremental inflows in the
model, the basin was divided into 5 sub-basins using  Arc-view spatial analyst
pollution loads from 
  each sub-basin were estimated using a 180m*180m 
  grid based database compiled from the pollution sources data. Based on the
unit load  approach, pollution loads from point sources and 
non-point sources were estimated using the Arc-view GIS. 
 
The pollutant removal rate of 
  management projectswere taken into account when 
  estimating the pollution loads from the WQMM with pollution loads of each reach
   calculated from delivery ratios (the ratio of the mass of pollutants delivered
   to
a stream divided by the mass of pollutants 
generated at the source (Novotny and Olem, 1994)). 
 
 Proposed management options 
In this section, the proposed management 
  options for water pollution control of the Karun-Dez basin are presented. These options have been 
identified and proposed through the cooperation of 
experts and the stakeholder organizations and agencies 
in the study area (Fig. 2). The proposed options, which should be implemented during a 10 
years timeframe, have been categorized into three groups, namely direct, indirect, and 
supporting projects. The general characteristics of 
these projects are presented below:
Direct projects 
Direct projects are those which can 
  directly improve the river water quality. The 
  direct projects are classified into industrial, domestic, and agricultural
  sectors as follows:
- Industrial Sector: The proposed direct 
  projects for the industrial sector have been 
  presented considering the following main categories: 
- point source reduction 
- improved solid waste disposal 
- reduction of water withdrawal from 
  Karun river and 
- control of miscellaneous polluter
As most of the industrial point loads are 
  violating the wastewater discharge standards of 
  Iranian Department of the Environment, point 
  source reduction will have significant effect on the 
  Karun river water quality.
- Domestic sector: The proposed direct 
  projects for the domestic sector have been 
  prepared considering source reduction as the main objective.The most important proposed 
  projects that can improve the river water quality 
  for the domestic sector are: 
- implementation or completion of 
  wastewater collection and treatment systems for cities 
  in the study area and 
- separation of biomedical wastewater of 
  hospitals located in the study area and surface 
  runoff management in urban areas.
- Agricultural and Agro industrial sector: 
  The direct water pollution reduction projects for agricultural and agro industrial sector 
  have been prepared considering source reduction as the main objective. These projects 
  are categorized into two sections, namely 
  pesticide and fertilizers pollution reduction, and deployment of modern irrigation projects 
  of agricultural return flows. The most important proposed projects for agricultural and 
  agro-industrial sector are:
- improvement and optimization of the 
  crop pattern and irrigation systems, 
- using the resistant and plentiful seeds, 
- reducing the application of pesticides 
  and chemical fertilizers in agricultural lands, 
- use of suitable pesticide and fertilizers 
  in agricultural networks, 
- transferring agricultural return flows, 
- recycling and reuse of agricultural wastewater, 
- watershed management 
 
- reduction of the pollution loads of the 
   hatchery projects.
 
Indirect projects 
 
Indirect projects are those which can 
   indirectly reduce the river water pollution. These 
   projects can also provide a long term stability in water 
   supply and demand and restore the ecological 
   condition of the system. The most important indirect 
   projects are proposed are:
 
- review of inter basin water transfer projects 
   to create balance between water supply and use, 
 
- development of the infrastructure needed 
   in the domestic sector such as improvement of the domestic water supply system, 
 
- improving the domestic water use pattern, 
 
- separation of drinking and non-drinking water 
 
- reducing water losses.
 
Supporting projects 
 
The supporting projects are aimed at providing 
   the basic information and research background 
   needed for the implementation, monitoring, and 
   evaluation of the master plan of water pollution reduction 
   of Karun river. The supporting projects have been proposed considering the following objectives:
 
- development of a water quality 
   monitoring network 
 
- man power capacity expansion and 
   behavioral improvement of existing institutional framework 
 
- Policies and rules scientific and research 
   based approaches.
 
Successful implementation of the 
   agricultural water pollution reduction projects will reduce 
   the concentration of pesticides and total 
   dissolved solids in agricultural return flows as well 
   as improving the irrigation efficiency by up to 20 percent. The pollution
   load reduction for each sector has been estimated using the
   hierarchical structure and the relative weights of water 
   quality variables. Based on the results of this study, 
   which are presented in Table 3, the water pollution 
   in agricultural, industrial, domestic, and 
   miscellaneous sectors can be reduced 45, 88, 30, and 65 
   percent respectively. Table 3 presents the share of 
   each sector in annual water use, pollution load, and the percentage of pollution
   reduction due to implementation of the proposed water pollution control projects.
   However, as evidenced in Table 3, the pollution load is not completely related to 
   water use. For example, the domestic sector that 
   uses only 4 percent of the total water use discharges 
   26 percent of the total pollution load of the 
   system. Table 3 also shows the range of variation of 
   the estimated share of each sector in pollution load 
   due to uncertainty in estimation of water use, and quantitative and qualitative
   characteristics of discharged wastewater. The estimated share for agricultural
   and miscellaneous sectors is less
   certain because of either insufficient or imprecise 
   data related to the assessment of pollution loads of 
   return flows, urban surface runoff,  leakage from land 
   fills, underground storage tanks, and pipes which 
   are used for storage or transfer of oil and 
   related products. (Afkhami, 2005). 
 
DISCUSSION 
 
One of the most important phases of this 
   study has been the need to determine an accurate timetable and budget for
   implementation of the projects. The projects with a higher
   effectiveness have been prioritized and budgetary spending 
   has been provided. These priority projects will be executed during the first
   few years of the water pollution reduction strategy. The share of
   this allocation from the total budget is very high because of the high cost
   of collection system. The allocated budgets to other sectors in this table
   also show the amount needed for a one percent reduction of water pollution
   in each sector.
   As demonstrated below, the unit reductions in 
   urban and industrial projects are more than 
   agricultural and miscellaneous sectors. In a 
   suggested framework for approving, monitoring, and evaluation of Karun pollution
   reduction projects, the Commission on Karun Environmental Protection will
   be the major overseer for
these activities. The representative of Khuzestan Environmental Protection Office
   will be the executive secretary of the commission. The commission will select
   the members of
urban, agricultural and agro-industrial and 
industrial committees. The main task of these 
committees will be to review and tentatively approve 
the suggested water pollution reduction projects 
and their associated budget requirements 
considering the overall framework for the master plan of 
Karun pollution reduction. These recommendations 
will then be passed to the Commission for final approval. The committees should
   request details of design, required budget, and the implementation timetable
   for different projects from all of
the involved organizations. Each committee should approve the above details based
   on the compatibility of each project with the master plan for
Karun pollution reduction, available amount of budget 
and time needed for implementation. Where budget restrictions affect the commencement
   and delivery of a project, then the affected projects should
be prioritized keeping in mind the overall 
framework and other "cause and effect" issues related to 
the overall implementation of the master plan. For 
this purpose, the projects are prioritized in this 
study based on their effectiveness in Karun river 
pollution reduction within the assessment limited 
time framework. As an example, in the agriculture 
and agro-industrial section that consumes 88.5% of 
the total water  and produce 48% of the 
contamination, development of modern methods of irrigation 
and increasing efficiency like treatment and reuse 
of drainages that needs five years time and 
100,000 million Rials, totally can reduce contamination 
by 10.5% with spending 447000 million Rials. The WQMM using pollution mitigation
projects developed in this study was applied to the
Karun and Dez rivers because of their very poor 
water quality. Pollution loads used in the model 
were calculated using Arc-view. The project type 
and cost of the projects in the river basin to simultaneously achieve the water
quality goals and pollution reduction cost optimization were calculated from
the model.
Nowdays, water quality management policy in Iran has 
focused mainly on wastewater treatment capacity expansion through the construction
of new WWTPs. However, from an economic viewpoint this is extremely ineffective
and therefore it
is necessary to establish a systematic water 
quality management plan that directly considers the 
cost of pollution mitigation projects. In the WQMM 
the results calculated using the QUAL2E model is directly used to check the water
quality goal. Accordingly, the WQMM has several advantages in that it can reflect
the non-linearity of
the mathematical water quality model, consider 
several water quality parameters and find the exact 
optimal solution to the cost optimization problem. 
According to the above mentioned results, some 
self-governing communities in the river basin 
would need to invest heavily in river quality 
management whilst other communities would contribute little 
and it is appreciated that mediating the profits 
and losses of the self-governing communities in 
the river basin is very difficult. Nonetheless, it 
is expected that the results of this study could 
be beneficial for the water quality management 
plan for comprehensive and cost-effective 
management of the Karun and Dez rivers in both the short 
and long term.
 
ACKNOWLEDGEMENTS 
 
The valuable contribution of the managers 
   and engineers of Khuzestan Environmental 
   Protection Agency and Khuzestan Water and Power 
   Authority for providing data and site maps as well as 
   the technical assistance are hereby acknowledged.
 
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