scholarly journals Multi-Criteria Evaluation and Sensitivity Analysis for the Optimal Location of Constructed Wetlands (METland) at Oceanic and Mediterranean Areas

2021 ◽  
Vol 18 (10) ◽  
pp. 5415
Author(s):  
Lorena Peñacoba-Antona ◽  
Montserrat Gómez-Delgado ◽  
Abraham Esteve-Núñez
Keyword(s):  
Sensitivity Analysis ◽  
Constructed Wetlands ◽  
Rural Areas ◽  
Geographical Information Systems ◽  
Removal Rate ◽  
Influential Factors ◽  
Pollutant Removal ◽  
Geographical Information ◽  
New Variety ◽  
Multi Criteria Evaluation

METland is a new variety of Constructed Wetland (CW) for treating wastewater where gravel is replaced by a biocompatible electroconductive material to stimulate the metabolism of electroactive bacteria. The system requires a remarkably low land footprint (0.4 m2/pe) compared to conventional CW, due to the high pollutant removal rate exhibited by such microorganisms. In order to predict the optimal locations for METland, a methodology based on Multi-Criteria Evaluation (MCE) techniques applied to Geographical Information Systems (GIS) has been proposed. Seven criteria were evaluated and weighted in the context of Analytical Hierarchy Process (AHP). Finally, a Global Sensitivity Analysis (GSA) was performed using the Sobol method for resource optimization. The model was tested in two locations, oceanic and Mediterranean, to prove its feasibility in different geographical, demographic and climate conditions. The GSA revealed as conclusion the most influential factors in the model: (i) land use, (ii) distance to population centers, and (iii) distance to river beds. Interestingly, the model could predict best suitable locations by reducing the number of analyzed factors to just such three key factors (responsible for 78% of the output variance). The proposed methodology will help decision-making stakeholders in implementing nature-based solutions, including constructed wetlands, for treating wastewater in rural areas.

Spatial Clusters of Diabetes and Physical Inactivity: Do Neighborhood Characteristics in High and Low Clusters Differ?

2019 ◽  
Vol 31 (7) ◽  
pp. 612-621
Author(s):  
Joanna Sara Valson ◽  
V. Raman Kutty ◽  
Biju Soman ◽  
V. T. Jissa
Keyword(s):  
Built Environment ◽  
Rural Areas ◽  
Physical Inactivity ◽  
Geographical Information Systems ◽  
Communicable Diseases ◽  
Geographical Information ◽  
Sample Population ◽  
Spatial Clusters ◽  
Non Communicable Diseases ◽  
Urban And Rural Areas

This study aims to find spatial clusters of diabetes and physical inactivity among a sample population in Kerala, India, and evaluate built environment characteristics within the high and low spatial clusters. Spatial clusters with a higher and lower likelihood of diabetes and physical inactivity were identified using spatial scan statistic at various radii. Built environment characteristics were captured at panchayat level and 1600 m buffer around participant location using Geographical Information Systems. Comparison of sociodemographic and built environment factors was carried out for participants within high and low spatial clusters using t tests. Ten high and 8 low spatial clusters of diabetes and 17 high and 23 low spatial clusters of physical inactivity were identified in urban and rural areas of Kerala. Significant differences in built environment characteristics were consistent for low spatial clusters of diabetes and physical inactivity in the urban scenario. Built environment characteristics were found to be relevant in both urban and rural areas of Kerala. There is an urgent call to explore spatial clustering of non-communicable diseases in Kerala and undo the one-size-fits-all approach for prevention and control of non-communicable diseases.

scholarly journals Multi-Criteria Evaluation (MCE) Method for the Management of Woodland Plantations in Floodplain Areas

2020 ◽  
Vol 9 (12) ◽  
pp. 725
Author(s):  
Christos Tzioutzios ◽  
Aristeidis Kastridis
Keyword(s):  
Spatial Analysis ◽  
Rural Areas ◽  
Flood Risk ◽  
Risk Mitigation ◽  
Low Cost ◽  
River System ◽  
Open Water ◽  
Geographical Information ◽  
Multi Criteria Evaluation ◽  
Total Study Area

The potential of woodland and floodplain woodland plantations in a wide area, of high flood risk, along the Spey River (Scotland) is investigated, to mitigate the floods’ catastrophic impact. The spatial analysis required various datasets to be overlaid, to define the suitable sites for woodland and floodplain woodland establishment. These datasets that concern the topography, the physical and technical characteristics (existing woodland, road system, urban and rural areas, river system and open water areas, railway) and the protected sites of the study area were obtained and merged using Geographical Information System (GIS) techniques. The most suitable and unsuitable areas within the region were identified, using multi-criteria evaluation methods (Boolean approach). In total, 13 constraints were created by expressing true/false statements for each factor, and were combined together using spatial analysis tools. The results revealed the high potential of woodland and floodplain woodland plantations to prevent floods, with 59.2% of the total study area (177.5 km2) determined to be appropriate for such practices’ application. The River Dulnain tributary demonstrated the highest potential for floodplain woodland planting, followed by Rivers Avon and Fiddich, and the southwestern and northeastern Spey River parts. The methodology proposed is simple and provides rapid and accurate results at low cost, while the datasets can be easily accessed and are available in convenient type/format. This useful methodology for researchers and authorities could be applied successfully to similar watersheds, contributing significantly to flood risk mitigation and the enhancement of the flood-preventative measures’ planning efficiency.

scholarly journals USING GIS FOR DEVELOPING SUSTAINABLE URBAN GROWTH CASE KYRENIA REGION

2018 ◽  
Vol XLII-3/W4 ◽  
pp. 263-268 ◽  
Author(s):  
C. Kara ◽  
N. Akçit
Keyword(s):  
Urban Development ◽  
Environmental Protection ◽  
Urban Growth ◽  
Geographical Information Systems ◽  
Planning Process ◽  
Central Zone ◽  
Geographical Information ◽  
Sustainable Urban Development ◽  
Soil Productivity ◽  
Multi Criteria Evaluation

<p><strong>Abstract.</strong> It is critical to develop urban layers for analysis sustainable urban development possibilities within planning process. Kyrenia Region has many physical, environmental or economic issues that may danger the growth possibilities in sustainable manner. From this point, this study uses different spatial layers such as slope, distance to roads, distance to central zone, vegetation, soil productivity, environmental protection zones, distance to open/green space, distance to education for supporting sustainable urban growth policies and define suitable areas for urban development within this perspective. The study tries to convert sustainable urban growth policies such as; compact growth, environmental protection, equal accessibility to basic services; into spatial layers and establish proper framework for multi criteria evaluation in Kyrenia Region within using geographical information systems. It shows suitability values for Kyrenia region and constraints zones at final section. It clearly presents the suitable areas for the sustainable urbanization and also unsuitable or risky areas for reducing the possible disasters and may happen in the future.</p>

Gradient Boosting Machine for Phosphorus Removal Prediction in Multi-Soil-Layering (MSL) system operated in a rural area 

2021 ◽  
Author(s):  
Sofyan Sbahi ◽  
Naaila Ouazzani ◽  
Abderrahmane Lahrouni ◽  
Abdessamed Hejjaj ◽  
Laila Mandi
Keyword(s):  
Rural Areas ◽  
Phosphorus Removal ◽  
Linear Models ◽  
Removal Rate ◽  
Pollutant Removal ◽  
Validation Dataset ◽  
Gradient Boosting ◽  
Feature Selection Technique ◽  
Gradient Boosting Machine ◽  
Soil Layering

&lt;p&gt;The quality of effluents from wastewater treatment plants still challenging especially in underprivileged rural areas where water resources are mostly affected by pollution, depletion and excessive exploitation. Thus, the prediction of phosphorus removal is one of the most important tasks in the management of wastewater effluent. Predictive model accuracy is crucial for safe reuse of treated water for public health and the environment. However, linear models that use a high dimensional dataset may be unable to build accurate and interpretable models. To address this complexity, the current study evaluates the effect of hydraulic retention time (HRT) on the removal of orthophosphates (PO&lt;sub&gt;4&lt;/sub&gt;&amp;#8211;P) and total phosphorus (TP) by the multi-soil-layering (MSL) eco-friendly technology. In addition, it attempts to predict this removal from domestic wastewater using a combined approach based on feature selection technique and gradient boosting machine algorithm (GBM). Sixteen physicochemical and bacterial indicators were monitored for a one-year period. The results show that the HRT impact significantly (p &lt; 0.01) the removal of phosphorus content by the MSL system. The HRT, pH, PO&lt;sub&gt;4&lt;/sub&gt;&amp;#8211;P and TP were suggested relevant for predicting the removal of TP, while HRT and PO&lt;sub&gt;4&lt;/sub&gt;&amp;#8211;P were sufficient for predicting the removal rate of PO&lt;sub&gt;4&lt;/sub&gt;&amp;#8211;P. The analysis of accuracy using the validation dataset demonstrates that GBM models have high credibility as they achieve an R&amp;#178; &gt; 0.92, while the analysis of sensitivity reveals that the HRT was the most important factor affecting phosphorus removal in the MSL system. In addition, the modeling results show that the GBM model has proven to be useful for predicting pollutant removal in the MSL technology and investigating its behavior.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

Reversing Clogging in Vertical-Flow Constructed Wetlands by Backwashing Treatment

2010 ◽  
Vol 129-131 ◽  
pp. 1064-1068
Author(s):  
Fei Ma ◽  
Li Jiang ◽  
Ting Zeng
Keyword(s):  
Waste Water ◽  
Hydraulic Conductivity ◽  
Constructed Wetlands ◽  
Constructed Wetland ◽  
Removal Rate ◽  
Pollutant Removal ◽  
Vertical Flow ◽  
Vertical Flow Constructed Wetlands ◽  
The World ◽  
Design Guidance

More and more constructed wetland CW) were used to treat waste water in the world for its advantage on cheaper and efficiency. CW would clog for improper design or imperfect management, so application for it was limited. The purpose of this paper is that using backwashing method resolve filter media clogging problem which is an intractable matter in constructed wetlands project. The effects of the backwashing treatment on pollutant removal, as well as the influence on characteristics of hydraulics of wetlands, were studied. The experimental results indicate that CW hydraulic conductivity, hydraulic resistance time and removal rate of COD increased after backwashing. This paper confirmed that backwashing method can reverse clogging in vertical-flow constructed wetlands, and provided design guidance for applying backwashing method to treat clogging vertical-flow constructed wetlands.

scholarly journals Quantitative Land Suitability Mapping for Crop Cultivation

2018 ◽  
Vol 20 (3) ◽  
pp. 77-83
Author(s):  
Svitlana Kokhan ◽  
Antonina Moskalenko ◽  
Oleg Drozdivskyi
Keyword(s):  
Knowledge Base ◽  
Geographical Information Systems ◽  
Climatic Conditions ◽  
Land Suitability ◽  
Geographical Information ◽  
Crop Cultivation ◽  
Suitability Assessment ◽  
Crop Suitability ◽  
Multi Criteria Evaluation ◽  
Gis Environment

Developing the structure of geodatabase and knowledge base to provide quantitative mapping of land suitability for cultivation the main crops has been shown in the research. The general model and catalogs of knowledge base were designed that are structuring and formalizing information for creating thematic and complex maps and geomodels. The real world spatial problems give rise to multi-criteria decision-making based on geographical information systems (GIS). The GIS environment provides both aggregation and spatial analysis of various georeferenced data. In this paper, the two approaches of multi-criteria evaluation (MCE) are represented - overlaying with the AND operation and the lowest score assignment on one criterion. An example of multi-attribute decision analysis is done using criteria for the crop suitability assessment. A comparison of those two approaches has been made, based on results of the land-use suitability mapping for the study crops - winter wheat, sunflower and corn. The results demonstrated that at certain locations, a range of criteria values, according to the AND operations had the lower applicability and less flexibility than according to the second approach, based on the lowest score assignment on one criterion. Designed maps characterize the threshold status of the soil quality to provide yields of studied crops on certain areas. A set of land suitability maps, designed as quantitative models of integration of environmental, soil and climatic conditions, would be very effective to manage the complex decisions under the crop cultivation.

scholarly journals Does access to health services influence the diagnostic pathway and outcome from cancer: analysis of a linked dataset.

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Melanie Turner ◽  
Shona Fielding ◽  
Peter Murchie
Keyword(s):  
Cancer Treatment ◽  
Rural Areas ◽  
Geographical Information Systems ◽  
Care Pathway ◽  
Geographical Information ◽  
Treatment Centre ◽  
One Year ◽  
The Uk ◽  
Diagnostic Centre ◽  
Timely Treatment

ABSTRACT ObjectivesTo determine whether cancer diagnostic pathways and survival are affected by access to GP practice, diagnostic centre and cancer treatment centre. Cancer treatment in the UK is generally delivered in large cancer centres within major cities. This could have a detrimental effect on outcomes for people from rural areas who develop cancer. Historical UK studies suggest distance from services affects cancer outcomes. In recent years several developments, such as cancer networks and suspected cancer referral pathways, have occurred within the UK NHS, which may have reduced earlier inequalities. It is currently unknown whether a persons’ geographical location within the UK has implications for the timeliness of their receipt of a diagnosis and treatment for cancer. ApproachRoutine clinical data from Scottish Morbidity Record (SMR) 01, Scottish Cancer Registry SMR 06, and Geographical Information Systems (GIS) derived measures of road distances and travelling times from key healthcare facilities have been linked to a clinical tracking database, NHS Grampian Cancer Care Pathway to form the Northeast and Aberdeen Scotland Cancer and Residence (NASCAR) database. This linkage provided a retrospective cohort of 13 702 people diagnosed with cancer since 2007. Logistic regression analyses have been conducted to determine the effect of distance from services on provider delays and survival at one year following diagnosis. ResultsOf the 13 702 patients included in the analysis the mean age was 67.4 ± 13 years and 45% were male. The highest proportion of patients lived within one mile of their GP practice (35.5%), less than five miles from their diagnostic centre (39.6%) and less than five miles from their cancer treatment centre (39.6%). Distance to GP practice or distance to diagnostic centre was not a significant predictor of timely treatment (treatment within 62 days of GP referral) or survival at one year following diagnosis. Increased distance to cancer treatment centre predicted shorter timely treatment intervals (5-9 miles [OR 1.50; CI 1.18-1.90], 10-29 miles [OR 1.09; CI0.90-1.31], 30-59 miles [OR 1.26; CI 1.05-1.52], > 60 miles [OR 1.72; CI 1.41-2.09]. Increased distance to treatment centre > 60 miles was associated with quicker times between diagnosis and receipt of treatment [OR 1.26; CI 1.12-1.42). ConclusionsIncreased distance to cancer treatment centre is associated with shorter treatment intervals. There was no association between likelihood of metastatic disease at diagnosis or survival at one year. Analysis is on-going into travelling times to services and may provide further insight.

The Relationship Between the Geographical Information Systems and Rural Development

2018 ◽  
pp. 167-188
Author(s):  
Hüseyin Çeken ◽  
Emine Yılmaz
Keyword(s):  
Rural Development ◽  
Rural Areas ◽  
Geographical Information Systems ◽  
Rural Tourism ◽  
Geographical Information ◽  
Data Systems ◽  
Tourism Planning ◽  
Income Sources ◽  
Sea Sand ◽  
The Relationship

Geographical data systems (GIS), which enable the creation of entities that are the subject of tourism, tourism planning, the identification of impact areas of tourism values, and the sustainable utilization of tourism entities, are data-collection and decision-making systems that can contribute to tourism planning and the development of tourism Recently, tourists' interests have shifted from sea-, sand-, and sun-focused tourism to alternative tourism types; one of which is rural tourism. With rural tourism, it is expected that economical and socio-cultural opportunities for people who live in rural areas can be improved. The realization of this provides the concept of rural development. Today, in Turkey, 36.40% of the whole population still live in rural areas and agricultural activities are the most important income sources. Therefore, it is possible to investigate rural tourism and rural development in the Turkish context. This chapter deals with suggestions in terms of rural tourism and rural development by using GIS.

Enhancing the removal of arsenic, boron and heavy metals in subsurface flow constructed wetlands using different supporting media

2011 ◽  
Vol 63 (11) ◽  
pp. 2612-2618 ◽  
Author(s):  
K. Lizama Allende ◽  
T. D. Fletcher ◽  
G. Sun
Keyword(s):  
Heavy Metals ◽  
Constructed Wetlands ◽  
Removal Rate ◽  
Subsurface Flow ◽  
Pollutant Removal ◽  
Synthetic Wastewater ◽  
Mass Rate ◽  
Toxicological Effects ◽  
Copper And Zinc ◽  
Subsurface Flow Constructed Wetlands

The presence of arsenic and heavy metals in drinking water sources poses a serious health risk due to chronic toxicological effects. Constructed wetlands have the potential to remove arsenic and heavy metals, but little is known about pollutant removal efficiency and reliability of wetlands for this task. This lab-scale study investigated the use of vertical subsurface flow constructed wetlands for removing arsenic, boron, copper, zinc, iron and manganese from synthetic wastewater. Gravel, limestone, zeolite and cocopeat were employed as wetland media. Conventional gravel media only showed limited capability in removing arsenic, iron, copper and zinc; and it showed virtually no capability in removing manganese and boron. In contrast, alternative wetland media: cocopeat, zeolite and limestone, demonstrated significant efficiencies – in terms of percentage removal and mass rate per m3 of wetland volume – for removing arsenic, iron, manganese, copper and zinc; their ability to remove boron, in terms of mass removal rate, was also higher than that of the gravel media. The overall results demonstrated the potential of using vertical flow wetlands to remove arsenic and metals from contaminated water, having cocopeat, zeolite or limestone as supporting media.

Development and spatial representation of synthetic indexes of outpatient mental health care in Andalusia (Spain)

2008 ◽  
Vol 17 (3) ◽  
pp. 192-200 ◽  
Author(s):  
Marco Garrido-Cumbrera ◽  
José Almenara-Barrios ◽  
Enrique López-Lara ◽  
Juan Luis Peralta-Sáez ◽  
Juan Carlos García-Gutierrez ◽  
...  
Keyword(s):  
Mental Health ◽  
Health Care ◽  
Information Systems ◽  
Mental Health Care ◽  
Rural Areas ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Case Load ◽  
Catchment Areas ◽  
Care Systems

SummaryIntroduction– There is a need to develop composite indicators to monitor mental health care in countries such as Spain, where there is wide variability of care systems in 17 different regions. The aim of this study is to generate and to test the usability of synthetic indexes in Andalusia (Southern Spain).Method– Seven mental health indicators were selected by expert opinion from a previous list of simple indicators used to compare mental health care systems across Spain (Psicost-74). A Geographical Information Systems (GIS) was used to delineate 71 sectors based on the catchment areas of the mental health centers in Andalusia. Synthetic indexes were obtained through linear combinations of simple indicators via Principal Components Analysis (PCA), using activity data from the Mental Health Information System of Andalusia (SISMA). Maps of these indexes were drawn for 71 catchment areas.Results– Two synthetic indexes were obtained and showed high consistency in the PCA. The Care Load Index (component 1) related to population size and total outpatient care provided within the area. The Case Load Index (component 2) related to assisted morbidity in relation to the population size. The care load index was higher in populated urban areas, whereas the case load was higher in rural areas.Discussion– Care and case load indexes show a different pattern in urban and rural areas. This may be related to a different underlying model of care related to the degree of urbanisation. Geographical Information Systems (GIS) improved recognition and assessment of the spatial phenomena related to the mental health care system, and support policy decision making process in mental health.Declaration of Interest:None.

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