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SYSTEMS DYNAMICS SIMULATION IN WATERRESOURCES MANAGEMENT - LOVA RESERVOIR

CASE STUDYVladimir NIKOLIC

ABSTRACT: Selova reservoir was formed by damming the Toplica River. The dam is

located 18 km upstream of Kursumlija municipality, South Serbia. The reservoir was

designed as a multifunctional water resource management object with the principal idea

of spatial and temporal distribution of flow, while, in the same time, balancing and

capturing the full potential of the flow. Therefore, the accumulation mitigates potential

detrimental effects of flood waves, and increases the flow during the dry seasons. Finally,Selova reservoir is designed as a structural measure to provide water supplying for six

municipalities: Nis, Prokuplje, Kursumlija, Blace, Zitoradja, Merosina. In order to

illustrate a tool which facilitates integrated system approach to water resources

management process, by consolidating physical elements and socio-economic

environment, this paper presents an application of operational Selova reservoir model

developed using system dynamics VENSIM software package.

Key words: SDS, Simulation, Water Management, IWRM, Vensim

DINAMIKA SIMULACIJA U UPRAVLJANJUVODNIM RESURSIMA STUDIJA SLUAJAAKUMULACIJA SELOVA

Vladimir NIKOLIC

APSTRAKT:


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1. INTRODUCTION

Rapid development of human society in technological and scientific sense, during 20 th and

at the beginning of 21st century, has been mainly based on the perception of infinitenatural resources and indestructible environment. While having the motive to improve life

conditions for human kind, it has produced numerous scars on Earths ecosystem.

Economical and social development have emerged or accelerated numerous

environmental processes that critically affect the human kind well being and further

existence. Consequently, one of the top priority questions which directly affects human

life and living environment, and therefore defines the future human kind survival on this

planet, is a matter of potable water and its availability.

In addition to physical and biochemical destruction of the environment, human

population notes constant growth, having an increased water demand as a logical

consequence. According to Real Time Statistics Program, the current world population is

estimated on slightly more than 6.9 billions of habitants, which is significant increase

compared to 1.6 Billion in 1900. It is likely to expect that human population will exceed

the number of 7 billion inhabitants in period of next couple of years. On the other hand, in

spite of rapid technological and scientific development, more than one sixth of Earths

population still has no appropriate access to water of acceptable quality, meaning that the

human society has not succeeded to ensure reliable resource of clean water for more than

1.4 billion people (water.org). The statistics are more than alarming: four people across

the world die from a water-related disease each minute!

Along with persistently increasing water demand, one additional process

significantly pressures the availability of potable water natural and human induced

climate change. The results of this process are change of magnitude and frequency ofextreme climate and hydrological events, such as floods and droughts, which, naturally,

have great implications on water resources management. Having a continuous growth of

water demand on one side and, limited and greatly endangered water resources on the

other, the paradigm of Integrated Water Resources Management (IWRM) has been

proposed for facing this more than complex challenge, suggesting the systematic

approach in integration of multiple functions and purposes for each water resource.

UNESCO defines integrated water resources management as a step-by-step process

of managing water resources in harmonious and environmentally sustainable way by

gradually uniting stakeholders and involving them in planning and decision making,

while accounting for evolving social demands (UNESCO, 2010). More than a few

guiding principles for successful integrated water resources management can be derivedfrom the previous and current experience. Among the others, a few of them are especially

important in the context of approach discussed in this report. First, the necessity of taking

more comprehensive, wider perspective of problem analysis - systems view. Second,

more than often, responsibilities of water management practice are fragmented on

different levels (local, provincial, national, etc.), which requires both vertical (government

levels) and horizontal (agriculture, forestry, tourism, etc.) integration. Lastly, a

participation of all potential stakeholders supports the successful decision making. Having

that in mind, integrated water resources management can be also defined as a systematic

process of systematic development, allocation and monitoring of water resources in the

context of social, economic and environmental objectives (waterwiki.net).


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This paper will analyze in details one of the numerous existing methodologies and

tools for operational support of integrated water resources management. The theoretical

background of the specific approach will be detailed, and the major advantages will be

pointed out. Discussed systems approach methodology expands the scope of the problem,

from purely physical, to integrated physical and socio-economic. Methodology isdemonstrated through the simulation model development of the multi-functional reservoir

operation. The reservoir is designed during 1980s of the last century, according to the

regulations legitimate in that time. Since the project still has not been completed, while

the environmental and socio-economic context has been changed significantly, this paper

will examine the ability of reservoir to accommodate changes and successfully

accomplish the trusted goals.

2. PROBLEM FORMULATION

In order to illustrate a tool which facilitates integrated system approach in water resources

management process, by consolidating physical elements and socio-economic

environment, this paper will examine the operational Selova reservoir model, Serbia,

while developing the system dynamics model in VENSIMVENSIM software package. Basic

concepts and rationale of system dynamics approach will be detailed in following chapter.

Figure 1. River Toplica Catchment and Selova Reservoir (Googlemaps)

During 1980s, the construction of dam and reservoir was seen as a reasonable

solution for emerging water related problems in South-East Serbia. Selova reservoir was

planned to be formed by damming the Toplica River. The dam is located 18km upstream

of Kursumlija municipality, South Serbia. Toplica River is one of the most important

Juzna Moravas tributaries, Black Sea Basin, and its basin covers 2217 km 2. Selova

reservoir controls the area of 349 km2, or 16% of total river Toplica catchment area.

Based on 45 years of monitoring, the average flow at the cross section preceding the

reservoir is 3.7m3/s. The Selova Dam is designed as earth-fill embankment. The length of

the dam crest is 429.50 m, while the crest width is 8.00m. The crest elevation is 527.00

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meters above sea level, whereas the elevation of heel of the dam is 457.00 meters above

sea level. The reservoir total volume is 70 million m3. Dead space capacity is 7.0 Million

m3, the active capacity is estimated on 46.0 million m3, while the designed flood

protection capacity is 17.2 million m3 (for Q2% = 29 m3/s). Maximum water intake

capacity for water supplying is 2.70m3

/s.

Figure 2. Selova dam, downstream view (http://www.gradnis.net/forum/)

Planned as a multifunctional water resource management object, the most

significant task for Selova reservoir is spatial and temporal distribution of flow, while, in

the same time, the reservoir should balance and capture the full natural potential of the

flow. Therefore, the accumulation mitigates possible detrimental effects of flood waves,

and increases the flow during the dry seasons. In conclusion, Selova reservoir is designed

as a structural measure to provide: Domestic water supplying for six municipalities Nis, Prokuplje, Kursumlija,

Blace, Zitoradja, Merosina (Figure 1);

Downstream flood protection;

In-stream flow required for maintaining the life downstream from the dam;

Industry water demand;

Agriculture water demand;

Sediment deposition capacities;

Fishing; Tourism;

And, hydropower production.

3. SYSTEM DYNAMIC SIMULATION MODEL

Selova reservoir is a multifunctional water management structure, but the key function is

to secure the reliable source of water required for the domestic, industrial and agricultural

use. Water supplying systems of six counties are vastly dependent on the water resource

provided by this reservoir. Assumption is that the reservoir will be exposed to

considerable pressure to adequately response the assumed context change due to projected

demographic and economic growth: Inflow to the reservoir; Reservoir volume; Specific

consumption per capita; Domestic demand seasonal variation coefficient; Initial

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http://www.gradnis.net/forum/http://www.gradnis.net/forum/


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population; population growth prediction; Industry water demand; land dedicated to

agriculture; Seasonal agricultural demand variation coefficient; in stream flow -

biological minimum; spillway control, and, spillway discharge.

For the purpose of the model design and further problem analysis, following

information has been collected: Inflow [m3

/s]; Maximal probable flow [m3

/s]; Totalreservoir storage capacity [m3]; Active storage for water supplying and in-stream flow

[m3]; Available storage for flood protection [m3]; Dead storage [m3]; Water demands for

industry, agriculture, and domestic use [m3/s]; Demographic growth projections;

Reservoir operation regulations; Water Level Water Volume dependency.

Figure 3. Selova dam

Since the reservoir still has not been fully constructed and operated, the preliminary

structural and operational performances havent been verified. Therefore, the

development of reservoir simulation model will help us asses the capacity of reservoir to

successfully meet expected functions. Basically, the model tests the balance of the

reservoir volume regarding the change in water demand.

Process of variable identification involves definition of quantities fundamentally

important for model correctness. Since we have a rather simple differential equation to

solve, we have to define all system inputs and outputs, while calculating the reservoir

volume - Stock. System input is just simple time series of flow [m3/month] for years

1981 to 1985, while system output is defined as a sum of different water demands, as

presented in Figure 4.

Figure 4. Model key variables

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A rct

Municipality 1

Municipality 2

Municipality 3

Municipality 4

Municipality 5

Pop. demand

Industry

Pop. demand

Industry

Industry

Industry

Industry

Pop. demand

A rctSpillway

A rctReservoir volumeInflow Outflow

Pop. demandIn-streamflow

A rctPop. demand

A rctMunicipality 5 A rct

Pop. demand

Industry

Figure 5. Schematic diagram of Selova reservoir water balance

Causal diagram (Figure 5) is converted into mathematical form using VENSIM

Software package. Figure 6 shows the central water balance setup for Selova reservoir,while Figure 7 describes a typical water demand for one of the six municipalities. This

form is repeated for each of six municipalities.

Figure 6. VENSIM Model Reservoir Water Balance Sector

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Water Demand -Municipality 3

DomesticDemand 3

IndustryDemand 3

AgricultureDemand 3

Population3

Births 3

Deaths 3

Birth Rate 3

Death Rate 3+

+

+

+

+

+

Water Demand For 3

Municipality

(month/m3)

AgriculturalLand 3

+

(m3/month)

Auxiliary

(m3/month) Aux.

(m3/month)

Aux.

(Coeff.)

(Coeff.)

(Initial Value/Month)*

Birth Rate

(Initial

Value/Month)*

Death Rate

Specific Consumption *

Population (m3/month)

Agricultural Land

(ha)*Specific Demand

(m3/ha/month) - (m3/month)

Agricultural Land 3

Agr. Lande (ha) depending on local

policies

Seasonal WaterSupplying Coefficient

3+

Time dependant,

Montlhy, K= 0.7 - 2

AgriculturalSpecific Demand

3(m3/ha/month)

+

|*| Municipality 3: Merosina |*|

Figure 7. VENSIM Model - Municipal Water Demand Sector

Mathematically, the elementary process is described by following differential

equation:

Where: S [m3] reservoir storage, Inflow, Outflow [m3/s], So [m3] initial volume of the

reservoir

InflowInflow to the system (reservoir) is a five years monthly hydrograph [m3/month]in

period 1981-1985. This set is representative in hydrological sense for the whole period of

observations 1945 1991. Reservoir outflowReservoir outflow is defined as a sum of water quantities for

in-stream flow demand [m3/month], water demand for six municipalities (Nis, Prokuplje,

Kursumlija, Blace, Zitoradja, Merosina) [m3/month], and discharge through the spillway

if the water volume in the reservoir reaches 70 million m3:

Reservoir Outflow = Biological Minimum + Spillway Flow +

"Water Demand - Municipality 1" + "Water Demand -

Municipality 2" + "Water Demand - Municipality 3" + "WaterDemand - Municipality 4" + "Water Demand - Municipality 5" +

"Water Demand - Municipality 6" [m3/ month]

The sum of domestic, industrial and agricultural requirements defines water demand

for each municipality:

"Water Demand - Municipality X" = Agriculture Demand X +

Domestic Demand X + Industry Demand X [m3/ month]

Domestic water demand is a function of current population, specific water

consumption coefficient and seasonal variation coefficient:

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Domestic Demand X = Population X * Seasonal Water Supplying

Coefficient X* Specific Water Need X [m3/ month]

Population in a municipality depends on its initial value and augmentation

coefficient derived from the historical data:

Population X = Births X -Deaths X [Inhabitants]

Where:

Births X = Population X * Birth Rate X [Inhabitants]

And:

Deaths X = Population X * Death Rate X [Inhabitants]

On the other hand, Seasonal Water Supplying Coefficient X [dimensionless] is a

time dependent variable which depends on the season. Specific Water Demand is defined

by authorities and local governing acts, and it strongly depends on the current state of the

water supplying network. In our case, due to deteriorated networks over long period of

time,, Specific Water Demand parameter takes values in range between 350 [l/capita/day]

and 390 [l/capita/day]. Simple multiplication leads us to the total 10.675

[m3/capita/month] or 11.285[m3/capita/month].

The Industrial water demand [m3/month] is obtained through the available statistical

analysis of the region. Agricultural water demand is calculated by multiplying

Agricultural land [ha] and Agricultural Specific Demand [m3/ha/month], and it fully

depends on the time of the year:

Agriculture Demand X [m3/month] = Agricultural Land X [ha] *

Agricultural Specific Demand X [m3/month/ha]

Agricultural land X [ha] is total area dedicated to agricultural use, whereas

Agricultural Specific Demand X [dimensionless] is a coefficient that depends on the

season.

A number of operational rules are applied in reservoir management process. If total

volume of water stored in the reservoir becomes lower than 7.3 million cubic meters,

which presents the reservoir dead storage capacity, then the total water demand cannot bedistributed, and delivered amount of water becomes equal to zero. If water volume in

reservoir exceeds 53.3 million cubic meters, then the full capacity of conduit is exploited

to discharge additional amount of 5m3/s. The spillway is utilized to discharge additional

15m3/s in case that reservoir volume increases above 70.5 million of m 3.

4. THE MAIN OBJECTIVES OF THE MODEL SIMULATION

Recent analysis of social and economic tendencies discovers a significant increase of

water demand for the industry, domestic water supplying and agriculture, in period 1991

2020. According to the current design of water supplying systems Selova reservoir must

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be able to sustain considerable pressures within multiple constraints. Due to favorable

economical environment and incitement government subsidies, manifold international

companies have announced their plans to open new factories in the economic domains

that have not been yet shaped within this region. Consequently, significant migrations

from neighboring regions are expected. This model is planned to investigate if currentavailable water resource is ready to meet increased demand, and if designed operational

rules for reservoir management can still be applied in the case of greater industrial and

agricultural activities. The effects of newly shaped demographic and economical context

on reservoir operation will be assessed through six scenarios:

i. System performance (reservoir water balance) under initial conditions, year

1991 (table 1);

ii. Capacity of the reservoir to meet demand regarding tendency of statistical

demographic growth in period 1991 and 2020 (table 1);

iii. Examine further deterioration of the local water supplying network in period

1991-2020 (table 1);

iv. Inspect effects of eventual renewal of the water supplying network (table 1);v. Agriculture reforms introducing land use change (table 1);

vi. Check industry demand increase effects on water balance (table 1);

Table 1 presents specific values for each of the proposed scenarios.

Table 1. Scenario Values

No. Municipality

Municipality

Specific Demand(l/cap/day)

InhabitantsAgriculture

(ha)Industry

(l/s) Birth

Rate

Death

Rate19911991

20202020

iiiiii20202020

iviv19911991 20202020 19911991 20202020 19911991 20202020

1 Nis 390 300 41023545

2

34937

0 0 0 479 8000.015

2

0.010

2

2 Prokuplje 390 300 410 45164 59280 950 1300 64 1230.015

2

0.010

2

3 Merosina 350 250 390 16610 14700 450 500 2 60.015

2

0.010

2

4 Kursumlija 370 250 390 13909 28721 500 650 30 690.015

2

0.010

2

5 Blace 370 250 390 13903 14460 350 400 22 440.015

20.010

2

6 Zitoradja 370 250 390 18496 15853 550 650 8 120.015

2

0.010

2

Sum: 2800 3500

The question that remains unanswered concerns the model reliability. There are

several methods for model validation:

Behavior Replication Test

Behavior Sensitivity Test

Behavior Prediction Test

Each test confirms that the model response actually is equal to the observed system

responses, and if adequately validated, the model can be used for further system analysis.

However, in this case, since the reservoir still has not been in operation, and no data

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describing its performance is available, we cannot confidently verify the model

performance.

5. ANALYSIS OF THE RESULTS

i. System performance (reservoir water balance) under initial conditions, year 1991System performance (reservoir water balance) under initial conditions, year 1991;

Figure 8. System performance under different calculation time steps(t = 1.0, 0.5, 0.125)

Scenario 1 examines expected system behavior (reservoir water volume) under

magnitudes used for the design of the reservoir structural measures and operational rules.The result shows expected water volume variation within the active storage capacity. In

particular time steps, the reservoir volume exceeds the flood storage capacity; for this

reason, the exploitation of full in-stream conduit capacity and discharge through the

spillway is required. After reducing the time step, from t = 1, to t = 0.5, and t =

0.125, the graph presents an obvious improvement in accuracy for smaller time steps by

smoothing the resulting graph. This is directly related to the applied numerical method

used for solving the underlying differential equation. The noise observed on the

resulting graphs can be justified by regulations of reservoir management and increased

discharge throughout the conduit if the water level rises above the flooding storage

elevation.

ii.ii. Capacity of the reservoir to meet demand regarding tendency of statistical demographicCapacity of the reservoir to meet demand regarding tendency of statistical demographic

growth in period 1991 and 2020;growth in period 1991 and 2020;

Statistical analysis of demographic tendencies in the reservoir designing period presented

possible and significant population increase in the next 30 years. Scenario 2 compares the

reservoir water balance for current (1991) and predicted population (2020). Resulting

diagram shows that increased number of residents will increase the number of days when

water delivery is not possible due to lower water levels in the reservoir, Figure 9.

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Figure 9. System performance under demographic growth consideration

iii.iii. Examine further deterioration of the local water supplying network in period 1991-2020;Examine further deterioration of the local water supplying network in period 1991-2020;

Figure 10. System performance after WSN deterioration

Extremely high specific demand coefficients have been taken into account for

designing the domestic water demand, ranging from 350 390 [l/inhabitants/day], due to

devastated water distribution network. The network condition causes the enormous waste

of water and results in high water domestic demand rates. Currently there are no

presented plans for distribution network renewal, which can cause further deterioration of

the network and naturally create additional increase in water demand. According to the

table 1, Scenario 3 explores the reservoir water balance in case of increased waterdemand, Figure 10. The results show expected increase in number of days when the water

distribution from the reservoir is stopped.

iv. Inspect effects of the water supplying network revitalization;Inspect effects of the water supplying network revitalization;

In contrast to Scenario 3, Scenario 4 explores the effects of eventual distribution network

renewal, which consequently affects domestic water demand rates, Table 1. Figure 11

presents not drastic, but yet significant water savings, by lowering the number of days

when actual water distribution from the reservoir is possible.

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Figure 11. System performance after WSN deterioration

v. Effects of agricultural reforms introducing land use change;Effects of agricultural reforms introducing land use change;

Figure 12. System performance after conducted agricultural restructuring

Additional water demand pressure is a result of change in the total area of each

region which is dedicated to agriculture, Table 1. Scenario 5 investigates the reservoir

water volume behavior under applied agricultural water demand modification. The

resulting graph shows steeper reservoir emptying curve, and increased number of days

when the water level is actually below the dead space elevation.

vi. Assess effects of industry demand increase on water balance;Assess effects of industry demand increase on water balance;

Further industrial development of the region is expected in following years. Scenario 6

gives us an answer on proposed question whether the reservoir would be capable of

meeting the additional demand of increased industrial water demand, Table 1. Figure 12

presents the results of the simulation and suggests supplementary number of days when

the actual water level in the reservoir is below the desired level.

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Figure 11. System performance after introducing the increased industry demand

It is assumed that observed water stress, defined as a negative difference between

available quantities of water and water demand, can be avoided if the input information to

the model is more detailed and precise, such as detailed operational plans.

5. CONCLUSION

This paper presents an analysis of multiple scenarios, dynamic processes of reservoir filling and

emptying, depending on the river Toplica discharge, the conservation of biological requirements

of the river, while, at the same time, attempting to meet the needs of downstream users, such thecity of Nis and agriculture in the valley.

Implementation of all six scenarios has explored the behavior of the most important

systems element reservoir volume. Starting with year 1991, and water demand

characteristic for that period, based on population, agricultural and industrial conditions,

through the implementation of reasonable system evolution scenarios, model ends up with

conditions that are expected in year 2020, by statistical and legislation analysis.

As mentioned in previous chapters, simulation has been done for 5 years time

period, in monthly steps, for instance inflow to the reservoir is described in units

m3/month. This fact obviously brings a certain level of deviation from the real world

operational scenarios. Consequently, the Selova Reservoir simulation model can be

further enhanced by introducing the shorter time steps, such as m3/s or m3/h, which would

enable more detailed definition of managerial operations and would significantly improve

the precision of the calculation.

Additional hydrological, social and environmental parameters should be further

included in water balance equation. This model did not include obvious water losses, such

as evapotranspiration or infiltration. On the other hand, demographic variation has not

included important factors like migrations, or economic conditions.

More detailed operational rules, possibly provided by an experts, are also suggested

for the further model enhancement. In fact, this is one of the main ideas and advantages of

system dynamics simulation models comprehensive involvement of all concerned

parties in the model development process.

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6. REFERENCES

(1)M. Forester et al. (1996), Road Map: A Guide to Learning System Dynamics, MIT(2)S. P. Simonovic (2007), Managing water resources methods and tools for a System

Approach, UNESCO(3)VENTANA Systems (2003), Vensim 5 Reference Manual, Ventana Systems Inc. , Belmont,

MA

(4)VENTANA Systems (1995), Vensim 5 Users Guide, Ventana Systems Inc. , Belmont, MA(5)UNESCO (2010),IWRM Guidelines: Principles(6) www.waterwiki.net, Integrated Water Resources Management (accessed April, 2011)

(7) www.water.org, Water Statistics (accessed April, 2011)

(8)Energoprojekt Beograd, Maj 1986. g: Idejno reenje, Prethodni izvetaj: Analiza potreba uvodi, Dokumentacija u okviru formiranja Vodoprivrednog sistem za snabdevanje

podruja Toplice i Nia Selova

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