scholarly journals Integration of Delphi Technique and Analytical Hierarchy Process Method in Assessment the Groundwater Potential Influence Criteria: A Case Study of the Ba River Basin

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Tuyet Minh DANG ◽  
Le Tung Duong NGUYEN
Keyword(s):  
Land Cover ◽  
River Basin ◽  
Weight Vector ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Sensitivity Analyses ◽  
Lineament Density ◽  
Analytic Hierarchy ◽  
Study Results ◽  
Hierarchy Process

Water is a boon for all living beings over the world and groundwater is considered one of theindispensable natural sources of potable water. It is necessary to assess and predict the groundwaterpotential to provide insights for decision-makers for proper planning and management of groundwater.The occurrence of groundwater depends on hydrological, ecological, climate, geological, andphysiographical criteria. The purpose of the present study is to choose and attribute scores to all variousfactors that affected groundwater prospects in the Ba river basin. Firstly, the Delphi method was appliedin the expert-based survey to choose six parameters that are considered as influencing factors, namely,lineament density, rainfall, slope, land cover, drainage density, and geology. Then, the weights for thevarious factors were generated using the Analytic Hierarchy Process (AHP) approach which allows thepairwise comparison of criteria influencing the potential areas. The consistency analyses show that thefindings were consistent with a previous study. The consistency and sensitivity analyses showed that theobtained results were coherent, providing the weight vector of the achievable criteria that affect thegroundwater prospect in the study area. The study reveals that lineament density and slope are criteriaaffecting the most prominent groundwater occurrence with 35.1% and 20.1%, respectively. However, theinfluence of other factors (rainfall, land cover, drainage density, and geology) is not visible. These criteriaare assigned to the small weights and do not have a significant influence on the groundwater potential.The study results provide baseline

scholarly journals ASSESSMENT OF FLOOD INFLUENCE CRITERIA IN THE LAM RIVER BASIN USING A COMBINED DELPHI-AHP METHOD

2021 ◽  
Vol 13 (3) ◽  
pp. 387-396
Author(s):  
Nguyen DUNG ◽  
◽  
Dang MINH ◽  
Keyword(s):  
Land Cover ◽  
River Basin ◽  
Flood Hazard ◽  
Drainage Density ◽  
Analytic Hierarchy ◽  
Slope Length ◽  
Study Results ◽  
Baseline Information ◽  
And Control ◽  
Relative Slope

Flood is represented as one of the most destructive natural hazards to humankind. Assessing and predicting floods hazard is necessary to offer appropriate solutions for flood mitigation and sustainable environmental management. It is only possible when the main criteria that contributed to creating the flood hazard are pointed out. The purpose of the current research was to choose and attribute scores to all various flood-causing factors in the Lam river basin. Firstly, the Delphi method was applied to the expertbased survey to choose six key parameters that led to the floods, including rainfall, slope, relative slope length, drainage density, land cover, and soil. Then, Analytic Hierarchy Process (AHP) approach is employed as an effective tool to obtain a better understanding of all the factors or indicator contributions in the flood process based on weight given to each of six flood influencing elements. The consistency analyses revealed that the findings were coherent and consistent with a previous study. It is also interesting to notice that rainfall and slope are the most prominent flood occurrence criteria with 45% and 25.5%, respectively. However, the influence of other factors (drainage density, relative slope length, land cover, and soil) is not visible. These parameters are assigned to the small weights and do not have a significant influence on the flood phenomenon. The study results provide baseline information, which needs to be taken into account to mitigate and control floods.

scholarly journals Integrated Geospatial Multi Influencing Factor Approach to Delineate and Identify Groundwater Potential Zones in Kabul Province, Afghanistan

2021 ◽  
Author(s):  
Muhammad Jamal Nasir ◽  
Sajjad Khan ◽  
Tehreem Ayaz ◽  
Amir Zeb Khan ◽  
Waqas Ahmad ◽  
...  
Keyword(s):  
Groundwater Resources ◽  
Influencing Factor ◽  
Relative Weight ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Land Use Land Cover ◽  
Groundwater Potential Zones ◽  
Lineament Density ◽  
Study Results ◽  
Groundwater Potentiality

Abstract This study was an attempt to evaluate the groundwater potentiality in Kabul province, Afghanistan using geospatial multi influencing factor (MIF) approach. The influencing parameters employed for the assessment of groundwater potential zones (GWPZ) includes slope, geology, soil, land use/land cover, lineament density, rainfall and drainage density. The sub-classes within each influencing parameter were sub-divided, based on their effectiveness in groundwater potentiality as major, minor and no effect, and subsequently assigned a score value. The combined score value of these parameters was used for calculating the relative weight. The delineated GWPZ were classified in four groups, i.e. poor, moderate, good and very good GWPZ. The study results revealed that very good GWPZ covered an area of 354.87km2 (2% of the total area), good 1523.86 km2 (20%), moderate 2250.99 km2 (73%) and poor 477.19 km2 (5%). The study concluded that geospatial assisted MIF approach was very useful and efficient techniques for the assessment of GWPZ and can be effectively employed to enhance the conceptual understanding of groundwater resources of Kabul Basin, Afghanistan.

Identification of Groundwater Potential Zones using AHP and Geospatial Techniques in Western Part of Cuddapah Basin, Andhra Pradesh, India

2020 ◽  
Vol 3 (2) ◽  
pp. 60-71
Author(s):  
Ramachandra M. ◽  
Raghu Babu K. ◽  
Rajasekhar M. ◽  
Pradeep Kumar B.
Keyword(s):  
Andhra Pradesh ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Water Levels ◽  
Geographical Information ◽  
Cuddapah Basin ◽  
Groundwater Potential Zones ◽  
Lineament Density ◽  
Geospatial Techniques ◽  
Hierarchy Process

Present study is carried out for delineation of Groundwater Potential Zones (GWPZ) in Western part of Cuddapah basin, Southern India using Remote Sensing (RS), Geographical Information System (GIS) and Analytical Hierarchy Process (AHP). Various categorized thematic maps: geology, geomorphology (GM), slope, soils, lineament density (LD), drainage density (DD) and gorundwater levels fluctuations (GWLF) were used for mapping and delineation of GWPZs. Suitable and normalized weights were assigned based on AHP to identify GWPZ. The GWPZ map was categorized into five GWPZs types: very poor, poor, moderate, good and very good. About 1.48% (6.05 km2) area is classified in ‘very good’, 25.95% (106.07 km2) in ‘good’, 47.11% (192.53 km2) in ‘moderate’, 22.12% (90.38 km2) in ‘poor’ and 3.34% (13.66 km2) in ‘very poor’ category. The acquired outcomes were validated with water levels fluctuations in pre- and post-monsoon seasons. GIS-based multi-criteria decision making approach is useful for preparation of precise and reliable data. The AHP approach, with the aptitudes of the geospatial data, various data bases can be combined to create conceptual model for identification and estimation of GWPZs.

scholarly journals Identification of Groundwater Potential Zones Using GIS and Multi-Criteria Decision-Making Techniques: A Case Study Upper Coruh River Basin (NE Turkey)

2021 ◽  
Vol 10 (6) ◽  
pp. 396
Author(s):  
Ümit Yıldırım
Keyword(s):  
Drainage Density ◽  
Groundwater Potential ◽  
High Potential ◽  
Groundwater Potential Zones ◽  
Topographic Wetness Index ◽  
Analytic Hierarchy ◽  
Soil Thickness ◽  
Çoruh River Basin ◽  
Basin Area ◽  
Very High

In this study, geographic information system (GIS)-based, analytic hierarchy process (AHP) techniques were used to identify groundwater potential zones to provide insight to decisionmakers and local authorities for present and future planning. Ten different geo-environmental factors, such as slope, topographic wetness index, geomorphology, drainage density, lithology, lineament density, rainfall, soil type, soil thickness, and land-use classes were selected as the decision criteria, and related GIS tools were used for creating, analysing and standardising the layers. The final groundwater potential zones map was delineated, using the weighted linear combination (WLC) aggregation method. The map was spatially classified into very high potential, high potential, moderate potential, low potential, and very low potential. The results showed that 21.5% of the basin area is characterised by high to very high groundwater potential. In comparison, the very low to low groundwater potential occupies 57.15%, and the moderate groundwater potential covers 21.4% of the basin area. Finally, the GWPZs map was investigated to validate the model, using discharges and depth to groundwater data related to 22 wells scattered over the basin. The validation results showed that GWPZs classes strongly overlap with the well discharges and groundwater depth located in the given area.

scholarly journals Weights of Factors Contributing to Flood Formation in the Lam River Basin, Vietnam

2020 ◽  
Vol 55 (2) ◽  
Author(s):  
Nguyen Ba Dung ◽  
Dang Tuyet Minh ◽  
Nguyen Quoc Long ◽  
Le Thi Thu Ha
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Analytic Hierarchy Process ◽  
River Basin ◽  
Flood Risk ◽  
Annual Rainfall ◽  
Soil Slope ◽  
Analytic Hierarchy ◽  
The Analytic Hierarchy Process ◽  
Hierarchy Process

There are many factors that influence the formation and development of floods, such as rainfall, soil, slope, land cover, drainage, and density. Therefore, a quantitative assessment of their importance is necessary, especially in the determination of flood risk zones, using the Analytic Hierarchy Process algorithm and Geographic Information System. In comparison with other methodologies, an obvious advantage of Analytic Hierarchy Process is the ability to solve multi-variable qualitative and quantitative problems with precise and trustworthy results. This paper presents the application of the Analytic Hierarchy Process algorithm in analyzing and evaluating the level at which various criteria affect flood risk in the Lam River basin. Some of the flood-causative factors considered in this paper are annual rainfall, soil, slope, land cover, drainage density, and relative slope length. These factors were chosen based on the physical conditions of the study area. The research results are the weight of different criteria. The higher the weight, the higher the effect of that criterion on flood risk. The computed weights show that annual rainfall and slope are the factors that contribute the most to flooding, based on decision-makers’ judgement. The results of this article can be used to construct a flood risk zoning map and flood susceptibility map for flood warnings in the Lam River basin, using the Analytic Hierarchy Process method and Geographic Information System technology. New research shows that Analytic Hierarchy Process can be trustworthy when assessing the level of influence of the different factors on determining flood-prone areas in the Lam River basin, as well as other basins.

scholarly journals Spatial Prediction of Groundwater Potentiality Mapping Using Machine Learning Algorithms

2021 ◽  
Author(s):  
Sunil Saha ◽  
Amiya Gayen ◽  
Kaustuv Mukherjee ◽  
Hamid Reza Pourghasemi ◽  
M. Santosh
Keyword(s):  
Machine Learning ◽  
Influencing Factors ◽  
Groundwater Resources ◽  
Learning Algorithms ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Machine Learning Algorithms ◽  
Lineament Density ◽  
Dug Wells ◽  
Groundwater Potentiality

Abstract Machine learning techniques offer powerful tools for the assessment and management of groundwater resources. Here, we evaluated the groundwater potential maps (GWPMs) in Md. Bazar Block of Birbhum District, India using four GIS-based machine-learning algorithms (MLA) such as predictive neural network (PNN), decision tree (DT), Naïve Bayes classifier (NBC), and random forest (RF). We used a database of 85 dug wells and one piezometer location identified using extensive field study, and employed 12 influencing factors (elevation, slope, drainage density (DD), topographical wetness index, geomorphology, lineament density, rainfall, geology, pond density, land use/land cover (LULC), geology, and soil texture) for evaluation through GIS. The 85 dug wells and 1 piezometer locations were sub-divided into two classes: 70:30 for training and model validation. The DT, RF, PNN, and NBC MLAs were implemented to analyse the relationship between the dug well locations and groundwater influencing factors to generate GWPMs. The results predict excellent groundwater potential areas (GPA) DT RF of 17.38%, 14.69%, 20.43%, and 13.97% of the study area, respectively. The prediction accuracy of each GWPM was determined using a receiver operating characteristic (ROC) curve. Using the 30% data sets (validation data), accuracies of 80.1%, 78.30%, 75.20%, and 69.2% were obtained for the PNN, RF, DT, and NBC models, respectively. The ROC values show that the four implemented models provide satisfactory and suitable results for GWP mapping in this region. In addition, the well-known mean decrease Gini (MDG) from the RF MLA was implemented to determine the relative importance of the variables for groundwater potentiality assessment. The MDG revealed that drainage density, lineament density, geomorphology, pond density, elevation, and stream junction frequency were the most useful determinants of GWPM. Our approach to delineate the GWPM can aid in the effective planning and management of groundwater resources in this region.

Ecosystem Health of the Beiyun River Basin (Beijing, China) as Evaluated by the Analytic Hierarchy Process Method

2021 ◽  
Author(s):  
Qianhui Yuan ◽  
Huihui Wu ◽  
Yunqiang Zhao ◽  
Yuhang Zhang ◽  
Ruihua Yao ◽  
...  
Keyword(s):  
Water Quality ◽  
Health Status ◽  
Analytic Hierarchy Process ◽  
River Basin ◽  
Ecosystem Health ◽  
Weak Links ◽  
Health Evaluation ◽  
Ecosystem Structure ◽  
Analytic Hierarchy ◽  
Hierarchy Process

Abstract Ecosystem services provided by river ecosystems rely on healthy ecosystem structure and ecological processes. The Beijing-Tianjin-Hebei urban is a typical water-deficient area. As an important part of the urban-rural integration construction, evaluating the health status of the Beiyun River Basin and discovering the weak links in the water environment is the basis for improving the health of the basin. In this study, Analytic Hierarchy Process was used to establish an evaluation index system for the Beiyun River Basin from 5 aspects including water quality, biology, habitat, hydrology, and social functions, and to assign weights to the index layer. The evaluation results showed that the health evaluation results of the Beiyun River Basin in 2019 are “sub-healthy”, and the overall health status is gradually worsening from northwest to southeast. In the middle reaches of the region, the evaluation result is "healthy", followed by the upstream, and the downstream is the worst. The results showed that areas with less human interference are in better health. The factors that affect the overall health evaluation status in the basin are the level of nutrition, biodiversity, and vegetation coverage. For the comprehensive management of the Beiyun River, the improvement of water quality and habitat ecological restoration is the key to the health of the upstream ecosystem health status. The improvement of the health status of the downstream should focus on equal emphasis on water quality and quantity, restoration of biodiversity, and improvement of the quality of the riparian ecological environment.

scholarly journals The Priority of Factors of Building Government as a Platform with Analytic Hierarchy Process Analysis

2020 ◽  
Vol 12 (14) ◽  
pp. 5615 ◽  
Author(s):  
Hyungjun Seo ◽  
Seunghwan Myeong
Keyword(s):  
Public Sector ◽  
Analytic Hierarchy Process ◽  
Process Analysis ◽  
Electronic Government ◽  
Data Driven ◽  
Analytic Hierarchy ◽  
The Public ◽  
Study Results ◽  
The Government ◽  
Hierarchy Process

Nowadays, the Government as a Platform (GaaP) based on cloud computing and network, has come to be considered a new structure to manage efficiently data-driven administration in the public sector. When the GaaP concept was first introduced, the ICT infrastructures that could underpin GaaP were not sufficiently developed. However, the recent digital transformation has transformed the previous electronic government, which was system- and architecture-oriented. As part of the next generation of government models, GaaP may reinvent the government at a lower cost but with better performance, similar to the case of electronic government two decades ago. This study attempted to determine the priority of factors of GaaP by using the analytic hierarchy process (AHP) methodology. Because of the GaaP characteristics, we drew the main components for building GaaP from previous studies and a group interview with experts. The study results show that experts tend to prefer publicness in terms of building GaaP. Most of the factors that the experts weighed with the highest importance are related to the public sector, which revealed that governments should focus on their primary duty, regardless of the origin and characteristics of the platform in GaaP. However, since GaaP allows governments to be more horizontal and innovative, the platform approach can fundamentally shift the existing processes and culture of the public sector. The enhanced activity of citizens with ICT can also accelerate the introduction of GaaP. Finally, the study showed that a data-driven GaaP is necessary to efficiently handle big data, contract services, and multiple levels of on-line and off-line channels. In this public platform, government, citizens, and private sector organizations can work cooperatively as partners to seamlessly govern the hyper-connected society.

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