System-Dynamics Approach to Evaluate Climate ...

World Environmental and Water Resources Congress 2014: Water without Borders © ASCE 2014

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A System Dynamics Approach to Evaluate Climate Change Adaptation Strategies for Iran’s Zayandeh-Rud Water System Alireza Gohari1, Kaveh Madani2, Ali Mirchi3, Alireza Massah Bavani4 1

Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816, USA; email: [email protected] 2 Centre for Environmental Policy, Imperial College London, London SW7 1NA, UK; email: [email protected] 3 Department of Civil & Environmental Engineering, Michigan Technological University, Houghton, MI 49931, USA; email: [email protected] 4 Department of Irrigation and Drainage Engineering, College of Abureyhan, University of Tehran, Pakdasht, Iran; email: [email protected] ABSTRACT This study aims to evaluate climate change adaptation strategies for the ZayandehRud water system located in central Iran. A probabilistic multi-model ensemble scenario is used to characterize uncertainties in climate change projections for the study period (2015–2044). The Zayandeh-Rud Watershed Management and Sustainability Model (ZRW-MSM) is run under an ensemble scenario with different uncertainty levels to evaluate the effects of climate change on the Zayandeh-Rud water system and to identify effective adaptation strategies to minimize these effects. ZRW-MSM is a system dynamics model that captures the interrelations between the basin’s hydrologic, socioeconomic, and agricultural sub-systems. This model can provide insights about the behavior trends of the basin’s sub-systems under climate change impacts. If current water management policies hold into the future, GavKhouni Marsh, an important ecosystem will severely degrade because of the lack of environmental flows, which will likely aggravate with climate change. Results indicate that supply oriented strategies (water transfer) alone are not effective in mitigating climate change impacts on different use sectors. Nevertheless, when combined with effective water demand management, these measures can alleviate climate change-related anthropogenic water stress in the basin. 1. INTRODUCTION Zayandeh-Rud River Basin is one of the most important basins in central Iran due to its socioeconomic status and ecological resources. Population growth as a result of socioeconomic development and urbanization, coupled with occurrence of severe droughts has significantly intensified the basin’s water stress in the recent decades (Madani and Mariño, 2009). Projection of climate change has indicated that this basin with the semi-arid Mediterranean climate will face warmer and drier conditions in the near-term future (2015–2044) (Gohari et al., 2013a). In the absence of timely

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adaptation actions, the basin will be highly vulnerable to climate change due to the expected continuous watershed development and growing water demand (Gohari et al., in press). Climate change may lead to more severe water scarcity, exacerbating conflict over water in the basin. The specific objectives of this study include: (1) evaluating the impacts of climate change on the Zayandeh-Rud River basin system and its subsystems; and (2) examining the effectiveness of adaptation strategies for minimizing the undesirable effects of climate change on the basin. 2. METHOD A probabilistic multi-model framework suggested by Gohari et al. (2013a) is used to generate climate change scenarios for the study area. This framework incorporates the uncertainties of General Circulation Models (GCMs), greenhouse gas emission scenarios, and climate variability of daily time series to improve the reliability of the climate change impact assessment. A system dynamics model, ZRW-MSM 2.0 (Gohari et al., 2013b) is used to explore the impacts of global warming on the Zayandeh-Rud Watershed system, providing insights into the most effective adaptation policies to improve water resources management under climate change. 2.1. Climate change scenarios The climate change scenarios used in this study were developed by Gohari et al. (2013a). In their study, daily time series of precipitation (mm), and maximum and minimum temperatures (ºC) were generated under climate change scenarios for the 2015-2044 period. A multi-model ensemble scenario framework was developed to project climate change effects, capturing various sources of uncertainties, namely GCM models, emission scenarios and climate variability of daily time series. In the first step, monthly change fields of precipitation, maximum and minimum temperatures were calculated as the difference between model-simulated in the future time period (2015-2044) and the baseline period (1971-2000) extracted from 10 GCMs under two emission scenarios (A2 and B1).The high levels of uncertainty in outputs of GCMs affect the confidence in the impact assessment results. Here, a bounded range with known probability distribution was developed to deal with the uncertainties of the 10 GCMs. Each of the 10 GCMs was weighted based on the Mean Observed Temperature-Precipitation (MOTP) method (Massah Bavani and Morid, 2005) based on their ability to simulate the observed climate variables for the baseline period. In the next step, Probability Distribution Functions (PDFs) of the change field scenarios were developed for each month. These PDFs relate the 30-year monthly average of temperature and precipitation changes to the weight of corresponding GCMs. Gamma distribution function with two parameters was then used to convert discrete probability distributions of change field scenarios to continuous probability distributions. Cumulative Distribution Functions (CDFs) were then developed based on the projected continuous PDFs and climate scenarios corresponding to the 25th, 50th and 75th probability percentiles were extracted. This was followed by the use of LARS-WG to generate daily temperature and precipitation time series at extracted change field scenarios under the selected probability percentiles.


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2.2. Simulation of monthly runoff under climate change Monthly runoff in the study area under climate change was simulated in Gohari et al. (in press). The IHACRES model (Jackman and Hornberger, 1993) was used to simulate daily rainfall-runoff in the basin. This conceptual model uses a non-linear loss module to estimate effective rainfall amount based on the temperature and rainfall. The estimated effective rainfall converts to runoff hydrograph by using a linear unit hydrograph module. The IHACRES model generated the monthly runoff time series based on the temperature and precipitation time series under climate change for the future 2015–2044 period. 2.3. Climate change impacts on agricultural water demand The study area’s agricultural water demand under climate change during the study period was estimated in Gohari et al. (2013a). They used the Agro-Ecological Zones (AEZ) method, developed by the Food and Agriculture Organization (FAO) and International Institute for Applied Systems Analysis (IIASA), to estimate the irrigation water demand of various crops under climate change scenarios. This framework uses a crop-specific soil water balance model developed by Tao et al. (2003) to calculate irrigation water demand. The major crops cultivated in the study area include wheat, barley, potato, rice, onion, alfalfa, corn, garden products, vegetables, and cereal, and legume. 2.4. System dynamics model A system dynamics model, Zayandeh-Rud Watershed Management and Sustainability Model 2.0 (ZRW-MSM 2.0) (Gohari et al., 2013b), was used to evaluate the efficiency of climate change adaptation strategies in the basin. The ZRW-MSM 2.0 model (Figure 1) comprises hydrologic, socioeconomic, and agricultural sub-systems, incorporating different drivers of the water resources development. This model provides a high-level illustration of the interactions between water resources system. The hydrological sub-system captures the regional elements of hydrologic cycle, water supply, and Gav-Khouni Marsh as the main ecosystem resource in the basin. As illustrated in Figure 1, the regional climatologic and hydrologic attributes (i.e., temperature, precipitation, evapotranspiration, runoff, natural flows, and groundwater recharge), groundwater and inter-basin transferred inflow govern the basin’s water balance. The socioeconomic sub-system captures the state of socioeconomic development, water demand of various users, and residents’ utility in the basin. In this sub-system, the basin’s economic development is used as a proxy for residents’ utility and their satisfaction from the available job opportunities, services, and goods, driving inmigration from neighboring basins. It is assumed that a combination of per capita water use, added value from water use, national economic growth rate, and the watershed’s Gross Domestic Product (GDP) relative to neighboring basins, determines the residents’ utility. The agricultural sub-system includes ten main crops of the basin. Figure 1 presents the agricultural sub-system for two hypothetical crops. In this sub-system, decision making about crop production levels and crop-based


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agricultural land use are based on income-maximizing behavior of the farmers. The land area for each crop is a function of its net benefit in the previous year. Expected land area for each crop determines the farmer’s preferred land area for each crop to achieve the maximum economic benefit. More detailed information on this model may be found in Gohari et al. (2013b).

Figure 1. The stock and flow diagram of the ZRW-MSM 2.0 2.4. Assessment of adaptation strategies Different water resources management strategies were examined to develop effective adaptation policies in response to climate change. To understand the effects of selected strategies on the water resources system, the ZRW-MSM 2.0 model was run for different combinations of seven hydrologic scenarios and water demand scenarios projected under climate change impacts. Seven scenarios have been considered, including Business as Usual (B.a.U), and climate projections under two emission scenarios of A2 and B1. Under B.a.U. agricultural water demand and hydrological parameters (i.e., temperature, precipitation, runoff, and reservoir inflow) are assumed to be similar to 1971-2000 baseline period. Other scenarios were constructed by projecting agricultural water demand and hydrological parameters at 25%, 50%, and 75% probability percentile of climate change under A2 and B1 emission scenarios. The 25% probability percentile indicates a low temperature change scenario and the wettest condition while the 75% probability percentile captures the warmest and driest condition. Four adaptation metrics were used to evaluate the performance of different policies for adapting the Zayandeh-Rud water resources system to climate change. These


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indices include the reliability, vulnerability, maximum deficit, and sustainability of water supply system for each water user (i.e., agricultural, urban, industrial and environmental) as suggested by Sandoval-Solis et al. (2011). The reliability index is defined as the probability that water resources system can supply sufficient water for the demands during the simulation period (Hashimoto et al., 1982): ReI =

Number of years with D = 0 N

(1)

where D is the water deficit for ith water user and N is the length of the simulation period. The vulnerability index is defined as the average annual deficit divided by average annual demand for the ith water user in the deficit period (Hashimoto et al., 1982): VuI =

(∑

)⁄Number of years with D > 0

(2)

Water demand

The maximum deficit index indicates the maximum annual deficit for each water user: Max. Def =

) max(D Water demand

(3)

The sustainability index is an aggregate index to facilitate the evaluation and comparison of water resources management policies. Here, the sustainability index (SI) is defined as a product of the three aforementioned performance criteria, namely reliability, vulnerability and maximum deficit indices for each water user (SandovalSolis et al., 2011): SI = ReI × (1 − VuI ) × (1 − Max. Def )

(4)

3. RESULTS 3.1. Climate change impacts on the water resources system The ZRW-MSM model was run under different climate change probability percentiles under two emission scenarios to assess the effects on the water resources system during 2015-2044. Figure 2 shows the behavior of selected model variables. Results indicate that global warming is expected to intensify the current environmental and agricultural water shortage in the basin. Increasing temperature generally raises evapotranspiration rates and consequently agricultural water demand, leading to more groundwater extraction to irrigate farmlands. If current humancentered management policies hold into the future, Gav-Khouni Marsh will not receive any water during 2015-2044 period under different climate change scenarios. The expected agricultural and environmental water stress is larger under B1 emission scenario than under the A2 scenario due to more rapid population growth and


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Domestic water demand (MCM) Industrial water demand (MCM) Watershed water shortage (MCM) Population (Million capita) Agricultural water demand (MCM) Agricultural water use (MCM)

Figure 2. Behavior of selected model variables under climate change scenarios Compared to B.a.U. scenario, intensified water shortage under climate change scenarios declines the residents’ satisfaction from services and goods, leading to the lower rates of in-migration from neighboring basins. Therefore, the negative effects of water stress on the residents’ utility reduce the growth rates of population, industrial and domestic water demands under climate change. The expected values of population, industrial and domestic water demands growth rates as well as residents’ utility are lower under the B1 emission scenario than the A2 emission scenario. The lowest levels of residents’ utility are estimated for 75% probability percentile under B1 emission scenario (high-development warm dry scenario). Climate change


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socioeconomic expansion in the near future. The most severe agricultural and environmental water shortages are expected for 75% probability percentile under B1 emission scenario (high-development warm dry scenario) throughout the simulation period.



impacts produce a limiting condition for the watershed development, leading to lower growth in urban and industrial areas. While agricultural and environmental sector will experience more severe water shortage due to the lack of sufficient water supply as well as increasing water demand under global warming. Proper planning and management of agricultural water use as the main water user can mitigate water tension effects in the basin under a changing climate. In this study, a number of water supply and demand management policies were analyzed to develop effective climate change adaptation policies. Each adaptation policy package is defined by changing one or more exogenous parameter(s) of the model to represent, for example, likely changes in the leakage of water supply networks, agricultural water use efficiency, cropping pattern, and water withdrawals from surface and groundwater resources. These adaptation policy packages are presented in Table 1. The system dynamics model was run under these adaptation policy packages and different climate change scenarios to evaluate their effectiveness and flexibility. Table 1: Description of climate change adaptation policies Policy package

Description Agricultural water use efficiency

leakage of water supply networks

Agricultural water demand

(Business as Usual)

45%

20%

All crops are cultivated in the basin

The increase of 300 MCM in surface water supply through inter-basin water transfers

2

45%

20%

All crops are cultivated in the basin


3

70%

15%

Removing alfalfa and rice from the cropping pattern


1

Water supply

The simulation results for the B.a.U. policy package are given to provide insights into climate change impacts on the Zayandeh-Rud’s water resources system. Table 2 summarizes the values of selected performance evaluation indices under the policy package 1. To better understand the climate change effects on each water sector, these indices have been separately calculated for each sector. Given that domestic and industrial water demands are fully satisfied under all scenarios due to high priority, the corresponding index values are not reported here. Results indicate that climate change will intensify the current agricultural and environmental water shortages throughout the simulation period. Severe agricultural and environmental water shortages are expected due to high agricultural water demand, which will cut off the flow to the Gav-Khouni Marsh, a valuable ecosystem in the most downstream point of the basin. The negative effects of climate change on water resources availability lead to lower levels of residents’ utility. In comparison to the historical period, the lower levels of residents’ utility in the basin reduce the growth rates of watershed population, industrial and domestic water demands.


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Table 2: Adaptation metrics under the policy package 1 Hydrologic and water demand scenario B.a.U. A2-25% A2-50% A2-75% B1-25% B1-50% B1-75%

Environment

Agriculture

Re Index

Vul Index

Max. Deficit

SI Index

Re Index

Vul Index

Max. Deficit

SI Index

0.00 0.00 0.00 0.00 0.00 0.00 0.00

1.00 1.00 1.00 1.00 1.00 1.00 1.00

1.00 1.00 1.00 1.00 1.00 1.00 1.00

0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.21 0.17 0.27 0.33 0.25 0.25 0.39

0.29 0.25 0.35 0.41 0.33 0.33 0.44

0.00 0.00 0.00 0.00 0.00 0.00 0.00

Implementation of water transfer projects (policy package 2) increases surface water supply in order to reduce water shortage in the study area. Table 3 summarizes the values of selected performance evaluation indices under the policy package 2. According to the calculated reliability index, water transfer projects will not supply sufficient water for agricultural activities under B.a.U. and climate change hydrologic and water demand scenario. The high values vulnerability indexes indicate that the agricultural water deliveries are highly unreliable under other climate change scenarios. Table 3: Adaptation metric under the policy packages 2 and 3 Policy Package

Policy Package 2

Policy Package 3

Hydrologic and water demand scenario

Re Index

Vul Index

Max. Deficit

SI Index

Re Index

Vul Index

Max. Deficit

SI Index

B.a.U. A2-25% A2-50% A2-75% B1-25% B1-50% B1-75% B.a.U. A2-25% A2-50% A2-75% B1-25% B1-50% B1-75%

0.47 0.43 0.29 0.14 0.31 0.17 0.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

0.50 0.68 0.88 0.89 0.84 0.95 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.57 1.00 1.00 1.00 1.00 1.00 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.47 0.00 0.00 0.00 0.00 0.00 0.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00 1.00 1.00 0.98 1.00 1.00 0.95

0.13 0.17 0.20 0.20 0.19 0.24 0.26 0.00 0.00 0.00 0.07 0.00 0.00 0.10

0.17 0.20 0.21 0.27 0.22 0.26 0.29 0.00 0.00 0.00 0.05 0.00 0.00 0.08

0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00 1.00 1.00 0.95 1.00 1.00 0.92

Environment

Agriculture

Gav-Khouni Marsh receives sufficient water about 31-43% and 17-29% of the simulation period respectively for 25% and 50% probability percentiles of climate change under policy package 2. Despite reducing environmental vulnerability in response to 25% probability percentile climate change scenario, the minimum SI values of 0 indicate that implementation of water transfer projects does not have any moderating effects on the expected environmental stress under different climate change scenarios. According to the SI and Re values of 0, supplying more water through inter-basin water transfer alone cannot provide sufficient water for increasing


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agricultural and environmental water demands during the simulation period, indicating potential inadequacy of policy package 2. Implementation of water transfer projects along with changing cropping pattern, and improving irrigation efficiency under policy package 3 can reduce water shortage by increasing surface water supply and raising agricultural water use productivity The values of selected adaptation evaluation performance indices under the policy package 3 are summarized in Table 3. This policy package can help meet minimum environmental flow requirements of the Gav-Khouni Marsh under various climate change scenarios (reliability and vulnerability indices for the environmental water sector are 1 and 0, respectively). The maximum SI value of 1 is expected for environmental sector indicating that this policy package will be an effective strategy for adaptation to various expected climate change scenarios. The water resources system under policy package 3 will supply sufficient agricultural water in the whole period under four out of the six considered climate change scenarios. 4. CONCLUSIONS The results indicate that climate change impacts will intensify water shortage through reducing water availability as well as increasing water demand, with potential to restricting watershed development and population growth. Increased agricultural water demand due to temperature rise will lead to more groundwater extraction to supply farmlands’ water uses under climate change. If current human-centered water management policies are not reformed, Gav-Khouni Marsh, the basin’s main ecological resource, will not receive any water during 2015-2044 period under medium-and high-development cold wet and warm dry climate change scenarios. The intensified water shortage under climate change declines the residents’ satisfaction from services and goods and consequently the in-migration rate from neighboring basins, lowering growth rates of population, industrial and domestic water demands in the basin. According to the expected limiting role of climate change in urban and industrial development, the regional water management efforts should focus on effective planning and management of agricultural water use as the main water user to adapt the basin’s water resources system to climate change. Analysis of different adaptation policies indicates that supplying more water through implementation of water transfer projects increases water availability, providing potential for socioeconomic development in the basin, eventually resulting in higher water demand. Therefore, implementation of a supply-oriented adaptation policy alone will not effectively mitigate the expected climate change effects on water availability in the basin. Supply-oriented strategies driving watershed development, lead to water resources system vulnerability to climate change in the long run. Given the strategic importance of water availability in the basin for ecosystem health and food security, adaptation strategies must be accurately identified to mitigate the impacts of projected climate and socio-economic changes on the basin’s water resources system. Effective adaptation decisions should simultaneously focus on the water supply and demand management in the basin to enhance climate change adaptation capacity.


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