Integrated knowledge- and data-driven approaches for groundwater potential zoning using GIS and multi-criteria decision making techniques on hard-rock terrain of Ahar catchment, Rajasthan, India

2014 ◽  
Vol 73 (4) ◽  
pp. 1871-1892 ◽  
Author(s):  
Deepesh Machiwal ◽  
Nishtha Rangi ◽  
Arun Sharma
Keyword(s):  
Decision Making ◽  
Hard Rock ◽  
Groundwater Potential ◽  
Data Driven ◽  
Multi Criteria Decision Making ◽  
Hard Rock Terrain ◽  
Integrated Knowledge

The framework of data-driven and multi-criteria decision-making for detecting unbalanced bidding

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huimin Li ◽  
Limin Su ◽  
Jian Zuo ◽  
Xiaowei An ◽  
Guanghua Dong ◽  
...  
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Public Procurement ◽  
Unit Price ◽  
Data Driven ◽  
Relative Distance ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Content Type ◽  
The Government

PurposeUnbalanced bidding can seriously imposed the government from obtaining the best value for the taxpayers' money in public procurement since it increases the owner's cost and decreases the fairness of the competitive bidding process. How to detect an unbalanced bid is a challenging task faced by theoretical researchers and practical actors. This study aims to develop an identification method of unbalanced bidding in the construction industry.Design/methodology/approachThe identification of unbalanced bidding is considered as a multi-criteria decision-making (MCDM) problem. A data-driven unit price database from the historical bidding document is built to present the reference unit prices as benchmarks. According to the proposed extended TOPSIS method, the data-driven unit price is chosen as the positive ideal solution, and the unit price that has the furthest absolute distance measure as the negative ideal solution. The concept of relative distance is introduced to measure the distances between positive and negative ideal solutions and each bidding unit price. The unbalanced bidding degree is ranked by means of relative distance.FindingsThe proposed model can be used for the quantitative evaluation of unbalanced bidding from a decision-making perspective. The identification process is developed according to the decision-making process. The finding shows that the model will support owners to efficiently and effectively identify unbalanced bidding in the bid evaluation stage.Originality/valueThe data-driven reference unit prices improve the accuracy of the benchmark to evaluate the unbalanced bidding. The extended TOPSIS model is applied to identify unbalanced bidding; the owners can undertake objective decision-making to identify and prevent unbalanced bidding at the stage of procurement.

scholarly journals Use of Earth Observation Images and GIS Techniques for Groundwater Exploration in Hard Rock Terrain

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
P. MOHANA ◽  
S Muthusamy
Keyword(s):  
Remote Sensing ◽  
Water Resources ◽  
Ground Water ◽  
Hard Rock ◽  
Groundwater Potential ◽  
Groundwater Exploration ◽  
Scientific Data ◽  
Srtm Dem ◽  
Regional Patterns ◽  
Hard Rock Terrain

Prolonged drought and improper maintenance of water resources increased the demands on ground-water supplies resulting are focuses for the need to evaluate ground-water resources in the hard rock terrain. In recent years, Remote-Sensing methods have been increasingly recognized as a means of obtaining crucial geo-scientific data for both regional and site-specific investigations. This work aims to develop and apply integrated methods combining the information obtained by geo-hydrological field mapping and those obtained by analyzing multi-source remotely sensed data in a GIS environment for better understanding the Groundwater condition in hard rock terrain. In this study, digitally enhanced Landsat ETM+ data was used to extract information on geology, geomorphology. Hill-Shading techniques are applied to SRTM DEM data to enhance terrain perspective views and to extract Geomorphological features and morphologically defined structures through the means of lineament analysis. A combination of Spectral information from Landsat ETM+ data plus spatial information from SRTM-DEM data is used to address the groundwater potential of alluvium, colluvium and fractured crystalline rocks in study area. The spatial distribution of groundwater potential zones shows regional patterns related to lithologies, lineaments, drainage systems and landforms. High yielding wells and springs are often related to large lineaments and corresponding structural features such as dykes. The results demonstrate that the integration of remote sensing, GIS, traditional fieldwork and models provide a powerful tool in the assessment and management of water resources and development of groundwater exploration plans.

scholarly journals Multi-Criteria Decision Making and Dempster-Shafer Model Based Delineation of Groundwater Prospect Zones From A Semi-Arid Environment

2021 ◽  
Author(s):  
Hemant Kumar Pandey ◽  
Vishal Kumar Singh ◽  
Sudhir Kumar Singh
Keyword(s):  
Decision Making ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Groundwater Potential Zone ◽  
Groundwater Prospect ◽  
Potential Zone ◽  
Multi Criteria Decision Making ◽  
Groundwater Potential Zones ◽  
Ahp Model ◽  
The North

Abstract The present study illustrates the delineation of the groundwater potential zones in one of the most critical and drought affected areas under Bundelkhand region of Uttar Pradesh. Hydrological evaluations were carried out in district Mahoba using GIS tools and remote sensing data which ultimately yielded several thematic maps, such as lineament density, land use/land cover, drainage density, lithology, slope, geomorphology, wetness index (WTI), altitude and soil. CartoDEM data which have spatial resolution of 30m i.e. equivalent to one arc second were used to create digital elevation model, drainage density, altitude, WTI and slope. The thematic layers were assigned relative weightages as per their groundwater potential prospects under multi-criteria decision making (MCDM) method through analytical hierarchy process (AHP). To recognize the groundwater potential zone, weighted overlay analysis was performed using ArcMap software. Additionally, for testing of the Dempster-Shafer model, 16 borewells in high potential areas have been selected. Based on the probability of the groundwater occurrence, the belief factor was equated. Further combining the weighted layers, groundwater potential zones were obtained. The groundwater potential maps illustrate five zones having different potential in the Mahoba district. According to the AHP model the north-west side of the study area is characterized with very good potential zones whereas the north-east and south-east region constitute medium and poor groundwater potential zones respectively. It reflects that more than 50% of the area is having medium groundwater potential while 30 percent of the area falls under low potential zone. 10% of the study area falls under very good groundwater potential zones. According to the DS model, very high groundwater zones constitute only 7% and the remaining area falls under poor potential. Overall accuracy of the DS model was higher than AHP model.

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