Eun-Sung Chung

Development of spatial water resources vulnerability index considering climate change impacts

This study developed a new framework to quantify spatial vulnerability for sustainable water resources management. Four hydrologic vulnerability indices--potential flood damage (PFDC), potential drought damage (PDDC), potential water quality deterioration (PWQDC), and watershed evaluation index (WEIC)--were modified to quantify flood damage, drought damage, water quality deterioration, and overall watershed risk considering the impact of climate change, respectively. The concept of sustainability in the Driver-Pressure-State-Impact-Response (DPSIR) framework was applied in selecting all appropriate indicators (criteria) of climate change impacts. In the examination of climate change, future meteorological data was obtained using CGCM3 (Canadian Global Coupled Model) and SDSM (Statistical Downscaling Model), and future stream run-off and water quality were simulated using HSPF (Hydrological Simulation Program - Fortran). The four modified indices were then calculated using TOPSIS, a multi-attribute method of decision analysis. As a result, the ranking obtained can be changed in consideration of climate change impacts. This study represents a new attempt to quantify hydrologic vulnerability in a manner that takes into account both climate change impacts and the concept of sustainability.

Development of fuzzy multi-criteria approach to prioritize locations of treated wastewater use considering climate change scenarios

This study proposed a robust prioritization framework to identify the priorities of treated wastewater (TWW) use locations with consideration of various uncertainties inherent in the climate change scenarios and the decision-making process. First, a fuzzy concept was applied because future forecast precipitation and their hydrological impact analysis results displayed significant variances when considering various climate change scenarios and long periods (e.g., 2010-2099). Second, various multi-criteria decision making (MCDM) techniques including weighted sum method (WSM), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and fuzzy TOPSIS were introduced to robust prioritization because different MCDM methods use different decision philosophies. Third, decision making method under complete uncertainty (DMCU) including maximin, maximax, minimax regret, Hurwicz, and equal likelihood were used to find robust final rankings. This framework is then applied to a Korean urban watershed. As a result, different rankings were obviously appeared between fuzzy TOPSIS and non-fuzzy MCDMs (e.g., WSM and TOPSIS) because the inter-annual variability in effectiveness was considered only with fuzzy TOPSIS. Then, robust prioritizations were derived based on 18 rankings from nine decadal periods of RCP4.5 and RCP8.5. For more robust rankings, five DMCU approaches using the rankings from fuzzy TOPSIS were derived. This framework combining fuzzy TOPSIS with DMCU approaches can be rendered less controversial among stakeholders under complete uncertainty of changing environments.

Robust spatial flood vulnerability assessment for Han River using fuzzy TOPSIS with α-cut level set

This study aims to improve the general flood vulnerability approach using fuzzy TOPSIS based on @a-cut level sets which can reduce the uncertainty inherent in even fuzzy multi-criteria decision making process. Since fuzzy TOPSIS leads to a crisp closeness for each alternative, it is frequently argued that fuzzy weights and fuzzy ratings should be in fuzzy relative closeness. Therefore, this study used a modified @a-cut level set based fuzzy TOPSIS to develop a spatial flood vulnerability approach for Han River in Korea, considering various uncertainties in weights derivation and crisp data aggregation. Two results from fuzzy TOPSIS and modified fuzzy TOPSIS were compared. Some regions which showed no or small ranking changes have their centro-symmetric distributions, while other regions whose rankings varied dynamically, have biased (anti-symmetric) distributions. It can be concluded that @a-cut level set based fuzzy TOPSIS produce more robust prioritization since more uncertainties can be considered. This method can be applied to robust spatial vulnerability or decision making in water resources management.

Assessing climate change vulnerability with group multi-criteria decision making approaches

This study developed an approach to assess the vulnerability to climate change and variability using various group multi-criteria decision-making (MCDM) methods and identified the sources of uncertainty in assessments. MCDM methods include the weighted sum method, one of the most common MCDM methods, the technique for order preference by similarity to ideal solution (TOPSIS), fuzzy-based TOPSIS, TOPSIS in a group-decision environment, and TOPSIS combined with the voting methods (Borda count and Copeland’s methods). The approach was applied to a water-resource system in South Korea, and the assessment was performed at the province level by categorizing water resources into water supply and conservation, flood control and water-quality sectors according to their management objectives. Key indicators for each category were profiled with the Delphi surveys, a series of questionnaires interspersed with controlled opinion feedback. The sectoral vulnerability scores were further aggregated into one composite score for water-resource vulnerability. Rankings among different MCDM methods varied in different degrees, but noticeable differences in the rankings from the fuzzy- and non-fuzzy-based methods suggested that the uncertainty with crisp data, rather widely used, should be acknowledged in vulnerability assessment. Also rankings from the voting-based methods did not differ much from those from non-voting-based (i.e., average-based) methods. Vulnerability rankings varied significantly among the different sectors of the water-resource systems, highlighting the need to assess the vulnerability of water-resource systems according to objectives, even though one composite index is often used for simplicity.

Development of Flood Vulnerability Index Considering Climate Change

This study aims to develop the Flood Vulnerability Index (FVI) and apply it to the Bukhan River Basin. A1B and A2 scenarios of CGCM3 of IPCC were adopted and SDSM (Statistical Downscaling Model) was used to downscale the original data to the daily data. Driver-Presure-State-Impact-Response (DPSIR) model was introduced to select all appropriate indicators for FVI and the daily rainfall-runoff model was simulated using HSPF (Hydrological Simulation Program-Fortran). Since FIV proposed in this study has a capability to quantify the potential flood vulnerability considering both present and future climate conditions, it is expected to be used for the comprehensive water resources and environmental planning.

Iterative Framework for Robust Reclaimed Wastewater Allocation in a Changing Environment Using Multi-Criteria Decision Making

In this study, an iterative framework for robust reclaimed wastewater allocation (IFRWA) was developed to consider multiple climate change scenarios using multi-criteria decision making (MCDM) methods. Each iteration begins with the assumption that an additional unit of water quantity is allocated to reclaimed wastewater (RWW) sites. Based on these allocation conditions, hydrologic simulations are performed and evaluated using the incremental alternative evaluation index (IAEI) to rank the best sites for each unit water quantity. The minimax regret strategy is employed to consider the uncertainty inherent in the climate change scenarios. The consequent robust ranking of the IAEIs is applied to determine the final allocation of the unit water quantity in a given iteration. This iteration continues until the total allocated water quantity satisfies the maximum available capacity of RWW for use in the studied watershed. Our results show that this incremental and robust framework can be used to determine the reasonable capacities of RWW at multiple sites within the watershed by considering various aspects of RWW use, including the water quantity and the socio-economic aspects of decision making. A choice and concentration strategy based on IAEIs should be employed to achieve the maximum utility considering the physical constraints (capacity and cost). If economic considerations, such as the cost of construction and management, are included, this framework can be applied to real problems.

Integrated assessment of climate change and urbanization impact on adaptation strategies: a case study in two small Korean watersheds

This study develops an integrated approach to assess climate change and urbanization impacts on adaptation strategies in watersheds. We considered the two adaptation strategies for two small watersheds in Korea: the redevelopment of an existing reservoir and the reuse of highly treated wastewater treatment plant (WWTP) effluent. Climate change scenarios were obtained by statistically downscaling the predicted precipitation and temperature with a global climate model (A1B and A2), and urbanization scenarios were derived by estimating the impervious area ratios with an impervious cover model. With the climate change and urbanization scenarios, we used the Hydrological Simulation Program-Fortran model to derive the flow and biochemical oxygen demand (BOD) concentration (conc.) duration curves, and calculate the numbers of days satisfying environmental requirement for instreamflow and the target BOD conc. Climate change reduced the effectiveness of the adaptation strategies with respect to low flow and BOD conc., whereas urbanization generally increased their effectiveness. Climate change had a greater impact on the effectiveness of the adaptation strategies for BOD conc. than for low flow, whereas urbanization had a greater impact on low flow. Comparing impacts of two strategies, a larger decrease in the effectiveness was observed for the WWTP effluent reuse strategy in response to climate change and urbanization. However, the consistent trends cannot be found with ease if climate change and urbanization happens jointly.

Fuzzy TOPSIS Approach to Flood Vulnerability Assessment in Korea

This study will be a new attempt to quantify flood vulnerability taking into account uncertainty. Information obtained from the real world has lots of uncertainties. Therefore, this study developed an approach to quantify spatial flood vulnerability of Korea using Fuzzy TOPSIS approach. Also, Fuzzy TOPSIS were compared with TOPSIS and weighted sum method. As a result, rankings of some areas were changed dramatically due to the uncertainty. Spearman rank correlation analysis indicated that the rankings of TOPSIS and weighted sum method were almost similar, but quite different from ranking of Fuzzy TOPSIS. In other words, because applying Fuzzy concept in regional vulnerability assessment may cause a significant change in priorities, the model presented in this study may be a method of vulnerability assessment.

Effects of Changes of Climate, Groundwater Withdrawal, and Landuse on Total Flow During Dry Period

In this study, the effects of variability in climate, groundwater withdrawal, and landuse on dry-weather streamflows were investigated by input sensitivity analysis using SWAT (Soil and Water Assessment Tool). Since only dry-period precipitation and daily average solar radiation among climate variables have high correlation coefficients to total flow (TF), sensitivity analyses of those were conducted. Furthermore, an equation was derived from simulation results for 30 years by multiple regression analysis. It may be used to estimate effects of various climatic variations (precipitation during the dry period, precipitation during the previous wet period, solar radiation, and maximum temperature). If daily average maximum temperatures increase, TFs during the dry period will decrease. Sensitivities of groundwater withdrawal and landuse were also conducted. Similarly, groundwater withdrawals strongly affect streamflow during the dry period. However, landuse changes (increasing urbanization) within the forested watershed do not appear to significantly affect TF during the dry period. Finally, a combined equation was derived that describes the relationship between the total runoff during the dry period and the climate, groundwater withdrawal and urban area proportion. The proposed equation will be useful to predict the water availability during the dry period in the future since it is dependent upon changes of temperature, precipitation, solar radiation, urban area ratio, and groundwater withdrawal.

Robustness, Uncertainty and Sensitivity Analyses of the TOPSIS Method for Quantitative Climate Change Vulnerability: a Case Study of Flood Damage

Multi-criteria decision making (MCDM) techniques have been used to evaluate and rank the spatial flood vulnerability to climate change. However, various sources of uncertainty, such as the determination of evaluation criteria, the assignment of criteria weights and performance values, exist in the application of MCDM methods. In this study, three existing methods were combined to quantify the risk and uncertainties inherent to the process of climate change vulnerability assessment, which is called the TOPSIS-based Robustness-Uncertainty-Sensitivity (RUS) approach. The A1B scenario was used to assess the vulnerability of seven metropolitan cities in South Korea to climate change. Twenty indicators that are closely related to the cause of and deterioration from the flood risk and the resulting damages were selected by two surveys of experts, and the weights of these factors were determined by using the Delphi technique, which can derive the subjective weights. Based on the derived weights, the vulnerability ranking was calculated using the TOPSIS method, one of the most popular MCDM methods. This TOPSIS-based RUS approach was used to analyze the robustness of the vulnerability rankings for the assessed cities, to derive the minimum changed weights of the single and multiple criteria that determine the rank equivalence (or reversal) between any two cities and to check the sensitivities of the performance values to the vulnerability rankings. This study showed the effectiveness of the RUS approach for assessing the vulnerability to climate change, demonstrating the application of flood vulnerability.