Using Improved TOPSIS and Best Worst Method in prioritizing management scenarios for the watershed management in arid and semi-arid environments

Alvandi, Ehsan; Soleimani-Sardo, Mojtaba; Meshram, Sarita Gajbhiye; Giglou, Behnam Farid; Ghaleno, Mohammad Reza Dahmardeh

doi:10.1007/s00500-021-05933-9

Cited by 19 publications

(9 citation statements)

References 41 publications

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“…A more considerable CC value indicates better water quality. In contrast, the lower the CC value, the higher the treatment priority rank of the location [26].…”

Section: Evaluate Treatment Priority Using the Technique Of Order Pre...mentioning

confidence: 95%

“…Furthermore, many mathematical methods have been applied to evaluate water quality and propose management solutions, such as the water quality index (entropy-weighted water quality index (EWQI), integrated water quality index (IWQI), modified water quality index (MWQI) [15,16], Set Pair Analysis (SPA) [17,18], Technique of Order Preference by Similarity to Ideal Solution (TOPSIS) [19,20], and other multivariate statistical analysis methods (Principal Component Analysis (PCA), Cluster Analysis (CA), Factor Analysis (FA), Discriminant Analysis (DA) [4,8,15,[21][22][23]. Among them, TOPSIS is commonly used in assessing water quality and identifying alternative solutions [19,[24][25][26][27]. In addition, the harmonic degree equation (HDE) is also used in water quality assessment studies [4,[28][29][30].…”

Section: Introductionmentioning

confidence: 99%

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Applying Harmony Degree Equation and TOPSIS Combined with Entropy Weights in Surface Water Classification

Le,

Nguyen

2024

Civ Eng J

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This study classified surface water quality in Can Tho city using the Eutrophication index, Harmony Degree Equation (HDE), and Technique of Order Preference by Similarity to Ideal Solution (TOPSIS). Water quality data were collected in two seasons at 38 locations with 18 parameters, including temperature, pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS), nitrite (N-NO2-), nitrate (N-NO3-), ammonium (N-NH4+), orthophosphate (P-PO43-), Fe, F-, Pb, As, Hg, coliform, chlorine-, and phosphorus-based pesticides. Water quality parameters are compared with national technical regulations on surface water quality (QCVN 08-MT:2015/BTNMT). The HDE method based on entropy weight has been applied to evaluate the comprehensive harmony degree of water quality for various purposes. In addition, the TOPSIS was also used to rank water quality at each location and determine the priority level that required mitigation and treatment solutions. Surface water quality in the study area had low dissolved oxygen content and was contaminated with TSS and coliform in both seasons. Water quality in the rainy season tends to decrease compared to the dry season. Based on HDE results, water quality in the study area in the dry season was assessed as suitable for domestic activities (needs treatment), irrigation, and navigation (HDII = 0.922), while the rainy season was suitable for irrigation and navigation (HDIII= 1.00). Moreover, surface water in the study area was in a state of potential eutrophication (EI > 0), in which eutrophication was higher during the dry season. The SW25 and SW28 were the most seriously eutrophic in the dry and rainy seasons, respectively. TOPSIS analysis indicated that SW22 and SW28 need treatment measures in both seasons; furthermore, SW2-SW4 (dry season) and SW23 (rainy season) also need appropriate management and impact mitigation solutions. SW4 was affected by the most significant seasonal impacts, which have high priority in the dry season and are lowest in the rainy season. Therefore, future studies are needed to identify specific sources of variation at these locations to reduce impacts. The study results provide helpful information for the decision-making process and water quality management. Doi: 10.28991/CEJ-2024-010-04-012 Full Text: PDF

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“…A more considerable CC value indicates better water quality. In contrast, the lower the CC value, the higher the treatment priority rank of the location [26].…”

Section: Evaluate Treatment Priority Using the Technique Of Order Pre...mentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Applying Harmony Degree Equation and TOPSIS Combined with Entropy Weights in Surface Water Classification

Le,

Nguyen

2024

Civ Eng J

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“…( 4) System dynamics approach The system dynamics approach, also known as the SD model, takes into account primarily social, economic and demographic factors. It focuses on factors that affect the system as a whole and uses system dynamics software to perform dynamic studies and analyses [11][12].…”

Section: Methods For Quantifying the Carrying Capacity Of The Water E...mentioning

confidence: 99%

A Neural Network-based Approach for Assessing the Energy Value of Regional Water Environment Pollution Losses and Its Application

2023

WPPCP

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With social development and population growth, people's demands for quality of life and quality of life are increasing, and higher requirements for drinking water safety have been put forward. Therefore, it is important to study and establish WE pollution loss assessment models for WE management work and reasonable economic policy formulation. However, most of the traditional models use a single factor as the input variable to assess the trend of pollutant concentration and the intensity of pollutant discharge; while the WE pollution loss assessment method based on energy value analysis theory uses a single factor as the input variable for energy value analysis to assess the intensity and concentration of pollutant discharge, but this method cannot handle multi-factor and multi-variable data, and can only use the fuzzy mathematics in However, this method cannot handle multi-factor and multi-variable data, and can only use fuzzy mathematics to evaluate and calculate the model; and it cannot deal with the non-linear relationship between multiple pollutants and single pollutant concentration at the same time. Therefore, in order to better solve the above problems, this paper proposes a neural network (NN) model based on the regional WE pollution loss energy assessment method; the method uses NNs to assess the energy value of a single factor; at the same time, the energy value of the regional pollution economic value is calculated to obtain the average energy value of the whole region; finally, the weighted average method is used to calculate the corresponding weighted average energy value of each unit and pollutant discharge intensity and other information. Finally, the weighted average method is used to calculate the weighted average energy value and the pollutant emission intensity of each unit. Compared with traditional methods, this method is not only better able to deal with multi-source data problems and non-linear relationships, but also more efficient in solving complex problems.

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“…TOPSIS is a common method in multi-objective decision analysis (Alvandi et al, 2021). It has a small amount of calculation, less information distortion, and intuitive geometric significance.…”

Section: Topsis Modelmentioning

confidence: 99%

Dynamic Evolution and Trend Analysis of the Coupling Coordination Between Sci-Tech Popularization and Sci-Tech Innovation in China

Wang,

Zhao,

Yang

et al. 2023

Sage Open

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Sci-Tech Popularization (STP) and Sci-Tech Innovation (STI) are two significant components to realize China’s innovation development. STI provides direction and content for STP, while STP creates an intense atmosphere for STI. By establishing two evaluation index systems of STP and STI, the STP index and the STI index of China and Chinese 31 provinces from 2010 to 2019 was calculated, and the STP index and the STI index from 2020 to 2024 were predicted. Finally, the relative development degree (RDD), the coupling coordination degree (CCD) and the dynamic degree of STP and STI were figured out. The results showed that: (1) From 2010 to 2024, the STP index and the STI index of China and Chinese 31 provinces showed a growing trend. The growth rate of STI was higher than that of STP, but the STP and the STI were low. (2) The RDD results showed that the development of STP lagged behind that of STI after 2018, and the gap between them showed a growing trend. (3) The CCD of STP and STI in China spanned three grades: moderate imbalance, slight imbalance, and approaching imbalance. The CCD in Chinese each province spanned five grades: severe imbalance, moderate imbalance, slight imbalance, approaching imbalance, reluctant coordination. The CCD was developing in a good direction, China and most Chinese provinces were still in an unbalanced level instead. Finally, suggestions on infrastructure, technical means, personnel, and social responsibility were put forward to promote the coordinated development between STP and STI in China.

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Using Improved TOPSIS and Best Worst Method in prioritizing management scenarios for the watershed management in arid and semi-arid environments

Cited by 19 publications

References 41 publications

Applying Harmony Degree Equation and TOPSIS Combined with Entropy Weights in Surface Water Classification

Applying Harmony Degree Equation and TOPSIS Combined with Entropy Weights in Surface Water Classification

A Neural Network-based Approach for Assessing the Energy Value of Regional Water Environment Pollution Losses and Its Application

Dynamic Evolution and Trend Analysis of the Coupling Coordination Between Sci-Tech Popularization and Sci-Tech Innovation in China

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