KR20180116820A - Assessment of water use vulnerability in the unit watersheds using TOPSIS approach with subjective and objective weights - Google Patents

Abstract

In the present specification, selected is an indicator considering a situation of each watershed for assessing vulnerability of each small watershed. Indicator data is constructed by using national statistics and reports based on a current point of time and a SWAT model that can be simulated for each watershed. Also, multiple weights are applied by using subjective and objective weights. The vulnerability of each unit watershed by applying a TOPSIS method among multiple criteria decision methods. When assessing water resource vulnerability, a water resource is classified according to water quantity and water quality/aquatic ecology, thereby grasping a part with high vulnerability according to each watershed.

Description

[0002] The present invention relates to a method for evaluating water vulnerability of a unit watershed using multi-weighting and TOPSIS,

The present invention relates to a water vulnerability assessment method, and more particularly, to a multi-weighted estimation method and a water vulnerability evaluation method for each unit watershed using TOPSIS.

IPCC (2007) defined climate change vulnerability as a function of the nature, scale, speed, sensitivity to climate change, and adaptive capacity of climate change systems exposed to the system. The larger the impact of climate change and the less adaptive capacity, . The most vulnerable part of climate change impacts is the change in precipitation patterns and the change in available water resources, which will lead to water shortages in Asia by more than 1 billion people by 2050. Vulnerability issues due to climate change are constantly emerging, and it is therefore necessary to quantitatively assess vulnerability to water resources. Recently, studies using indicators have been conducted to identify the vulnerability and status of water resources. In case of using multiple indicators, weights are applied by various methods in order to secure the reliability of the weight calculation method that shows the importance of each indicator, but most of them are applied with a single weight. Weights are given using subjective or objective weighting methods. Subjective weights are weighted according to the decision-making process by conducting surveys. Objective weights are calculated by using data-based Entropy method and principal component analysis (PCA) . In addition, if there is no importance information on the indicator, the same weight is applied according to the neutral value judgment. In general, water vulnerability assessments have been conducted at the national level, and some vulnerability assessments have been conducted in some regions or by watersheds.

Korean Patent Publication No. 10-1665324

For the first purpose, in the previous research, most subjective or objective weights were calculated and the vulnerability was analyzed by applying a single weight. It is important to ensure the reliability of the estimation method since the weight represents the importance of the indicator. In this paper, we evaluated the vulnerabilities by applying subjective and objective weights and compared them to improve the reliability of the weighting method.

For the second purpose, previous studies have generally performed water vulnerability assessments at the national level. It is difficult to reflect regional characteristics, and recently some vulnerability assessments have been conducted by region or by watershed. However, in this specification, water vulnerability of small watershed is assessed and water vulnerability assessment is performed by unit watershed to reflect local characteristics.

As a third objective, in general, water vulnerability assessment tends to concentrate on water use in relation to water shortage, but in this specification, the term water / water ecology for efficient sustainable water use Were evaluated for vulnerability. By analyzing quantities and water / water ecological vulnerability, each vulnerable sector can be evaluated in more detail by unit watershed.

For the fourth purpose, in this specification, we used the results of SWAT (Long Run Rainfall-Runoff Model) as well as national statistical and observational data to construct indicator data for vulnerability assessment by geographical area. The SWAT model can simulate the drainage and water quality of the watershed considering the characteristics of the soil, land use, dams, and other water resources facilities, so that it is possible to provide land data that can not be obtained through observations. In addition, some of the national statistics and observation data used as indicator data were used as input data of SWAT to ensure consistency between indicators.

The solutions described herein are not limited to those mentioned above, and other solutions not mentioned may be clearly understood by those skilled in the art from the following description.

In this paper, we have selected indicators that take into account the situation of each watershed in order to assess the vulnerability of small watersheds. The indicator data were constructed by using national statistics and reports based on the current point of view and SWAT model that can be simulated by the watershed. We also applied multiple weights using subjective and objective weights and evaluated the vulnerability of each unit watershed by applying the TOPSIS method among multi - criteria decision methods. Water quality and water quality in the evaluation of vulnerability of water resources.

A vulnerability assessment method for unit watershed to address climate change has developed an indicator - based approach to assess the vulnerability of water resources to small - scale watersheds. In order to identify the vulnerability, we applied the objective weighted value calculated using the subjective weight and the data-based Entropy concept calculated through the questionnaire. Using the TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) And the vulnerability to unit watershed. In addition to the climate, social, economic, and environmental aspects were taken into account and the 16 indicators and 13 water / water ecological indicators were selected based on the indicators used in the existing vulnerability research. It is composed of exposure, sensitivity, and adaptive capacity according to the vulnerability assessment system. Among the indicators, the exposure is external factors such as climate and watershed environment. Sensitivity is an index that influences water use. It is composed of social, water supply and water use variables. In addition, adaptive capacity is an indicator to mitigate the instability of water use. It is composed of variables representing water supply, economy, and governance. Among the water quality / water ecological indicators, the exposure factors are external factors such as climate and pollution sources. Sensitivity is composed of variables related to watershed environment and water supply.

Adaptive capacity constituted representative variables of water supply, economy and governance. Each of the indicators is adapted to future climate change scenarios using the national statistical data and the simulated data of the SWAT (Soil and Water Assessment Tool) model. Through this specification, we could confirm the difference of vulnerability rankings and distributions by watershed, and it could be used for water resource planning and countermeasures planning in future watershed size.

The effects described in the present specification are not limited to those mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the following description.

1 is a flow chart schematically illustrating a method for evaluating a water vulnerability according to the present invention.
Fig. 2 is an illustration of a watershed under study.
FIG. 3 and FIG. 4 are diagrams illustrating the results of ranking vulnerabilities according to weights.
5 and 6 are comparative charts comparing the vulnerability indices of the detailed basin watersheds.

Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings so that those skilled in the art can easily carry out the present invention. It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the invention. Wherever possible, the same or similar parts are denoted using the same reference numerals in the drawings.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The singular forms as used herein include plural forms as long as the phrases do not expressly express the opposite meaning thereto.

Means that a particular feature, region, integer, step, operation, element and / or component is specified and that other specific features, regions, integers, steps, operations, elements, components, and / It does not exclude the existence or addition of a group.

All terms including technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Predefined terms are further interpreted as having a meaning consistent with the relevant technical literature and the present disclosure, and are not to be construed as ideal or very formal meanings unless defined otherwise.

Due to climate change, natural disasters such as droughts and floods are occurring all over the world. UNDP (2005) defined vulnerability as exposure sensitivity to climate change or stress exposure, coping, recovery, and adaptive capacity. IPCC (2007) defined climate change vulnerability as a function of the nature, scale, speed, sensitivity to climate change, and adaptive capacity of climate change systems exposed to the system. The larger the impact of climate change and the less adaptive capacity, . The most vulnerable part of climate change impacts is the change in precipitation pattern and the change in available water resources. As a result, more than 1 billion people in Asia will experience water shortage by 2050. (KEI, 2008; Kim et al., 2011), the vulnerability of water resources to climate change is increasing.

Recently, researches using indicators have been continuously conducted to evaluate the vulnerability and status of water resources. In addition to existing vulnerability assessment at the national level, studies are being conducted to evaluate vulnerability by region or watershed. In order to evaluate the vulnerability of climate change vulnerability, KEI (2008) evaluated the vulnerability of vulnerability according to regional scenarios by quantifying the vulnerability of flood damage by the watershed using the indicators (Jung et al., 2008) . Kim et al. (2012) used Fuzzy-TOPSIS (Technique for Order Performance) to select the location of reusing sewage treatment water in Anyangcheon watershed (Chung et al. The flood vulnerability was quantified using the weighted sum method and the correlation analysis was performed. Wang et al. (2012) collected major components of northern China and estimated water resource vulnerability by watershed. Kim and Chung (2014) used the weighted sum method and TOPSIS to quantify water quality and water quality vulnerability and developed an indicator-based decision framework that takes into account various climate change scenarios. Oh et al. (2014) developed a vulnerability assessment index for climate change considering the characteristics of coastal cities, assessing the vulnerability of 10 major coastal cities in Korea and evaluating the reliability of the indicators.

In addition, when multiple indicators are used, weights are applied in various ways in order to secure the reliability of the method of calculating the weight indicating the importance of each indicator. Baeck et al. (2011) compared and analyzed the results of the standardization and weighting methods of the previously developed flood risk index data. Kim et al. (2011) analyzed the vulnerability of climate change in domestic small and medium-sized rivers by calculating the weight through Delphi technique, and confirmed that vulnerabilities in water resources are affected by various variables in sensitivity field . Kong et al. (2014) used TOPSIS to evaluate the vulnerability of these dimensions, and analyzed the differences by applying subjective weighting and objective entropy weighting using the Delphi technique. Garg et al. (2015) applied the concept of entropy, calculated the weight, applied the Fuzzy-TOPSIS to evaluate the priority of the housing choice, and suggested that the weight is the most important to derive the optimal alternative. Lee et al. (2015) applied an objective analytical entropy weight to evaluate the vulnerability of air pollution, and Won et al. (2015) evaluated the vulnerability of water use in Korea by applying entropy weighting and TOPSIS.

Therefore, in this paper, TOPSIS was used as a multi-criteria decision technique to evaluate water resource vulnerability in the watershed and the water quality and water / water ecological vulnerability of the Han River watershed was evaluated. Indicators were selected based on socio-economic factors as well as hydrological factors and consisted of exposure, sensitivity, and adaptive ability. To evaluate the vulnerability according to the weighting method, the selected indexes were compared and analyzed by subjective weighting based on expert questionnaire and objective weighting of data base.

1 is a flow chart schematically illustrating a method for evaluating a water vulnerability according to the present invention.

Step 1 - The indicators were selected based on socio-economic factors as well as hydrological factors, and consisted of exposure, sensitivity, and adaptive ability. In addition, we applied Subjective weighting based on the questionnaire survey and Objective weighting based on the data to evaluate the vulnerability according to the weighting method.

Step 2 - Indicator data utilized socioeconomic data and SWAT simulation data as well as quantity, water quality, and watershed environmental data.

Step 3 - Subjective and objective weights were used to assess the water vulnerability of the watershed, and TOPSIS was used among multi - criteria decision - making methods.

Step 4 - Water quality and water quality / ecological vulnerability of the Han River basin were evaluated for each unit watershed.

Fig. 2 is an illustration of a watershed under study.

In the present specification, a total of 237 standard unit watersheds were constructed for the Han River basin, which includes Korea's capital city, Seoul, and relatively high population and industrial density. I did not consider it because it was not enough. The entire watershed was divided into four sub-basins (Imjin River, North River, Namhan River, and Han River) to evaluate the vulnerability of sub-basins.

Therefore, a total of 205 valid watersheds were analyzed for vulnerability and four watersheds (Imjin River, Bukang River, Namhan River, Han River) were considered in consideration of watershed characteristics. The entire watershed consists of 2 cities (Seoul, Incheon) and 4 (Gyeonggi Province, Gangwon Province, Chungcheongbuk-do, and Gyeongsangbuk-do).

Theoretical backgrounds are Subjective and Objective weights.

The weight is a measure of the importance of each indicator attribute, and it is important to assign an appropriate weight to achieve an efficient result. Therefore, the calculation process should be simple and easy to understand (Lee, 2003; Garg et al., 2015).

In this specification, weights of selected water quality and water quality / water quality indicators according to the vulnerability assessment system are calculated by subjective weights and objective weights, respectively. Expert questionnaires were conducted for each indicator to calculate subjective weights. In addition, the objective weighting is based on the entropy concept introduced by Shannon (1948), which is defined as the amount of information a signal has. The concept of entropy is relatively easy to identify the difference between given data, and reflects only quantitative characteristics, so it has an advantage that objective analysis is possible. The large entropy means that there is a large amount of information, so the uncertainty decreases (Lee, 2003; Kim and Chung, 2015; Won et al., 2015; Lee et al.

The TOPSIS (Technique for Order Performance by Similar Criteria to Ideal Solution) is based on the Multi Criteria Decision Making (MCDM), which measures the preference of each criterion when there are many evaluation criteria and many alternatives to consider. It means the best alternatives or ranking considering the importance of the research, and is used to evaluate alternatives in many studies.

TOPSIS was first introduced by Hwang and Yoon (1981) and is a reasonable alternative to the Positive Ideal Solution (PIS) and the Negative Ideal Solution (NIS). (Chung et al, 2012; Kim and Chung, 2014).

)는 두 변수의 순위간의 관계성을 나타낸다. 이는 Eq. (1)과 같이 계산되며, 결과 값의 범위는 -1에서 1사이이다. 두 변수의 순위가 완전히 일치하는 경우 1이며, 반대의 경우에는 -1이 된다. 변수의 분포와 상관성이 없으며, 선형관계가 없어도 관계성 분석이 가능하다.The rank correlation coefficient analysis is used when the data is an ordered scale, and the Spearman correlation coefficient,

) Represents the relationship between the ranking of two variables. This is because Eq. (1), and the range of the result is -1 to 1. If the rank of the two variables is completely equal, it is 1; otherwise, it is -1. There is no correlation with the distribution of variables, and it is possible to analyze the relationship without linear relationship.

Where D is the difference between x variable rank and u variable rank, and n is the total number of variables.

First of all, it is necessary to select an indicator.

In order to select the main indicators, substitution variables considering climate and socioeconomic factors were selected through previous studies such as domestic and foreign research reports. After that, 25 final indicators were selected considering the availability of indicator data. It is composed of exposure, sensitivity, and adaptation ability according to the vulnerability assessment system and classified into 16 water quality indicators and 13 water quality / water quality indicators (Tables 1 and 2).

Next, we need to construct a data base.

An example of this is shown in Fig. 7 and Fig.

Next, weights need to be determined.

In the case of subjective weights, the index was calculated by using the priority questionnaire for experts. In terms of vulnerability indicators, it was found that the effective rainfall (A1) was the most important in the order of exposure, the sensitivity was in the order of water use (A9) and population density (A5). In the adaptation ability, water supply rate (A12) was the highest. Among the water quality / water ecological indicators, the maximum value (B1), the forest area rate (B7) and the sewerage penetration rate (B8) were high in exposure and the water supply penetration rate (B10) was the highest in exposure.

In the case of objective weights, the entropy concept was applied and only the indicator data were used. In the vulnerability index, the effective precipitation (A1) was the highest at the exposures, but the weights of the cultivated area (A2) and the impervious layer (A3) were similar. The sensitivity of groundwater level (A8) was high and the adaptation capacity of water supply (A12) was high. Among the water / water ecological indicators, the exposure was higher in the order of phosphorus (B4), nitrogen (B3) and BOD (B6) loadings. Sensitivity was high in the forest area rate (B7) and water supply rate (B10) appear.

Next, data standardization.

Since the selected indicators have different units and ranges, standardization of each indicator has been carried out to integrate them. The distribution of raw data for all the indicators was confirmed, and the logarithmic function was used to standardize the maximum - minimum value. In addition, some indexes of exposure and sensitivity (total amount of effective rainfall, groundwater level, forest area rate, sewerage penetration rate) in the whole surface are standardized by matching the direction of the indicator value when estimating vulnerability because it shows low vulnerability when the value is high.

This can be used to identify water vulnerability rankings using the TOPSIS technique.

Subjective and objective weights were applied to each standardized index data and TOPSIS technique was applied to integrate the indicators according to quantity and water quality / water ecology. The vulnerability index was identified for each watershed and the water quality / water ecotypes.

FIG. 3 and FIG. 4 are diagrams illustrating the results of ranking vulnerabilities according to weights.

Figure 3 shows the results of water vulnerability rankings by unit watershed, and Figure 4 shows the results of water quality / water ecological vulnerability rankings by unit watershed. Each shows the difference in ranking according to subjective weighting result, objective weighting result, and weighting result.

According to the weighting method, the order of vulnerability rankings in some provinces such as Chungcheongbuk - do and Gangwon - do showed a similar distribution. Vulnerabilities were high in areas of Gangwon-do and Chungcheongbuk-do, where water leaks were high or water usage was high. In areas with high adaptive capacity index such as in the metropolitan area or in some parts of Gangwon-do, vulnerability decreased when water supply rate, effective rainfall, Results. Water quality / water ecological vulnerability rankings showed more differences according to the weighting method than water quantity vulnerability rankings, and most of them appeared in metropolitan area. When the subjective weight was applied, the vulnerability of the Seoul metropolitan area was high except for Seoul, but when the objective weight was applied, the vulnerability was high in Seoul and other metropolitan areas. . Most of the areas with high vulnerability such as the Seoul metropolitan area and central Gangwon province are expected to cause the deterioration of water quality and aquatic ecosystem due to the maximum number of days and the high temperature. Also, pollutant load was relatively high and sewerage penetration rate was low. The vulnerability was low in areas with high forest areas such as Chungcheongbuk-do and Gangwon-do, and in areas with low water use and high water supply.

5 and 6 are comparative charts comparing the vulnerability indices of the detailed basin watersheds.

Figure 5 shows that there was almost no difference in the index values according to weight application method due to the quantity vulnerability results, and in particular, the exposure index in the Han river basin (W4) was the largest. The watershed area (W2) is higher in the Han River basin (W4) than in the Han River basin (W4). Fig. 6 shows different results depending on the detailed watershed in water / water ecology. In case of water quality / water ecological vulnerability rankings in each watershed, the watershed of the North River (W2) was the highest in applying the subjective weighting, and the weakness of the Han River watershed (W4) was the highest in applying the objective weighting

The whole watershed was divided into four sub-basins (Imjin River, Bukang River, Namhan River, Han River) according to river flow. In the quantity sector, there was almost no difference in the index values according to the weighting method, especially in the Han river basin (W4). The exposure and sensitivity indices were higher in the subjective weighting and the exposure index was higher in the objective weighting. The watershed area (W2) is higher in the Han River basin (W4) than in the Han River basin (W4). Water quality / water ecology has different results depending on the detailed watershed. In most cases, the adaptive capacity index was high, but the Han area (W4) showed higher exposure index and lower sensitivity and adaptive capacity index than other watersheds. In the watershed excluding the Han river basin (W4), the exposure and sensitivity index values were lower when the objective weighting was applied. In case of water quality / water ecological vulnerability rankings in each watershed, the W2 was the highest in the North Korea River watershed when applying the subjective weighting, and the weakest in the Han River watershed (W4) was the highest in the objective weighting.

Finally, it is necessary to analyze the vulnerability correlation according to the weighting method.

In this paper, Spearman correlation coefficient analysis was performed to analyze the correlation of water vulnerability results according to weighting method. In case of quantity vulnerability, the index value and distribution were relatively similar, and the rank correlation analysis value was 0.80. However, in case of water / water ecological vulnerability, the correlation was relatively low and 0.51 was calculated. This is because the sensitivity index is weighted when the entropy is applied to the water / water ecological index and the correlation is low because the index with high value difference is included in the exposure and sensitivity classification. In addition, the difference according to the weighting method was larger than the quantity indicators, and the weight values of about half of the indicators showed a relatively large difference, indicating that the correlation was lowered.

In this paper, we attempted to evaluate each integrated vulnerability by classifying water quality and water quality / water ecological vulnerability in unit watershed scale for watershed water resource management. To integrate the indicators, TOPSIS was used among multi - criteria decision making methods to evaluate vulnerability by watershed and compare and analyze priorities. The weights of the evaluation indexes were divided into subjective weights based on the expert questionnaire and objective weights using the entropy concept based on the collected data.

As a result of the vulnerability assessment, watersheds with weak water quality were mostly used for water, sewage and agricultural use, and water leakage rate was high. However, vulnerability was low in areas with high effective precipitation and high water supply. The vulnerability rankings differed in some watersheds according to the weighting, but the correlation analysis showed that the correlation was very high as 0.80. In most regions where water quality / water ecological vulnerability is high, the maximum value and temperature of continuous rainy days are high. In areas where relatively low pollutant loads and river water use rates such as eastern part of Kangwon Province, high forest area rate and water supply rate, Low. The ranking of vulnerability according to weighting was relatively large compared to the quantity vulnerability, and showed a large difference mainly in the metropolitan area. As a result, the correlation was estimated to be 0.51, which is relatively low compared to the quantity vulnerability.

In this specification, quantity and water quality / water ecological vulnerability according to the weight calculation method were evaluated respectively, and the distribution and priority of the vulnerability were confirmed. Therefore, it is expected that more reliable vulnerability assessment results will be obtained through comparative study of various weighting methods in the future, and it will be possible to use water resources planning and countermeasure planning in the watershed scale.

The embodiments and the accompanying drawings described in the present specification are merely illustrative of some of the technical ideas included in the present invention. Accordingly, the embodiments disclosed herein are for the purpose of describing rather than limiting the technical spirit of the present invention, and it is apparent that the scope of the technical idea of the present invention is not limited by these embodiments. It will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (1)

(1) collecting indicator data through quantity, water quality, watershed environment, socioeconomic data and SWAT simulation data;
(2) Constructing indicators by applying subjective weight and data-based objective weights based on a questionnaire survey of the hydrological, socio-economic, exposure, sensitivity, and adaptation abilities;
(3) Evaluating water resource vulnerability in the watershed using TOPSIS among multi-criteria decision making methods; And
(4) evaluating the water quality and water quality / water ecological vulnerability of the unit watershed by the target watershed, respectively, and evaluating the water resource vulnerability of each unit watershed

Images