Spatial Multi-criteria Analysis Research Articles

Integrating spatial data and multi-criteria analysis for wind farm suitability mapping in eastern Saudi Arabia

Wind energy offers significant potential for Saudi Arabia's energy future. This framework integrates wind farm suitability analysis with spatially explicit groundwater potential mapping. So, revealing prospective windy sites as optimal zones for wind farm installation has become a vital issue for wind farms in Saudi Arabia's Eastern Province. To power clean energy and groundwater pumping, we deployed a unique blend of multi-criteria decision-making and spatial analysis. Several suitability criteria (17 factors) were used, including wind power density, land cover, and infrastructure, via a two-pronged approach. Five key factors were analyzed through a decision-making process, while the remaining 12 received suitability modeling. The resulting map reveals extensive areas with high wind farm potential. "Very high," "high," and "moderate" suitability zones cover a combined 211,943 ha, compared to a mere 1459 ha with "low" and "very low" potential. Interestingly, "sands" emerged as the surface with the highest concentration of "very high" suitability, while "fallow land" offered the most extensive suitable area overall. Wind power density proved to be the driving force behind these rankings. The study recommends further research to understand how wind power density correlates with wind speed at different altitudes. This could refine wind farm placement and maximize its effectiveness.

Identification of appropriate sites for solar-based green hydrogen production using a combination of density-based clustering, Best-Worst Method, and Spatial GIS

Hydrogen is a relatively new source of sustainable energy resources; presently, its usage ranges from direct energy generation in mixed-cycle thermal power plants to its usage in the internal combustion engine. If the generation of hydrogen is coupled with renewable energy resources, the use of hydrocarbons can be substantially reduced in both energy generation and transportation. In this paper, we conducted a national-level assessment to identify the hydrogen generation capacity of Pakistan. The methodology used in this study is a combination of spatial multi-criteria analysis and density-based clustering in a geographical information systems environment. Based on the analysis, the national clusters capable of producing green hydrogen were identified. The results shows that the hydrogen generation capacity for Pakistan is approximately 7 million tons per year using solar photovoltaic energy. The Surab-Gwadar alignment, N-25 national highway, and Quetta-to-D-I-Khan alignment offer potential hydrogen generation sites with water resources. Most of the identified sites for the production of hydrogen in the country were found to be near the national electricity transmission networks. The Best-Worst Method was further employed to provide policymakers with a road map for prioritizing the development of these capacities based on their proximity to the national networks, their terrain suitability, and their generation capacities.

Mapping Residential Land Suitability Using a WEB-GIS-Based Multi-Criteria Spatial Analysis Approach: Integration of AHP and WPM Methods

Along with the rise in population and the acceleration of economic expansion, there has been a concomitant rise in the urgent requirement for additional property that can serve as a venue for a wide variety of community activities. It is not uncommon for large cities that are the epicenter of urbanization, such as the city of Surabaya, to experience a sharp uptick in the demand for land. One of the regions that has excellent accessibility is the Sidoarjo Regency, which is comparable to the City of Surabaya in this regard. The goal of this research is to use Web-GIS to conduct an analysis of spatial data in order to identify the land functions that are most suitable for use in residential areas. The Analytic Hierarchy Process (AHP) and the Weighted Product Model (WPM) are two of the methodologies that are included in the spatial data modeling method that uses multi-criteria decision making (MCDM). The characteristics parameters that are employed are derived from data such as the distance to the city center, the distance to the market, the distance to the hospital, the distance to public transit, the slope, the kind of soil, and the amount of rainfall. The outcomes of spatial data modeling categorize the suitability of new residential land into categories of land that is not suitable for residential use and land that is acceptable for residential use. A K value of 0.27 is the outcome of the comparison test that was run between the two MCDM approaches using Cohen's Kappa coefficients.

Spatial multi-criteria analysis for prioritising forest management zones to prevent large forest fires in Catalonia (NE Spain)

Large forest fires are one of the most common environmental issues in the Mediterranean region. In this study, we defined a set of indicators and criteria based on available spatial data to assess and prioritize management zones for preventing large forest fires in Catalonia (NE Spain). In total, 22 indicators were defined and grouped into 5 criteria. The process involved geospatial modelling using a Geographical Information System (GIS) and the Multi-Attribute Utility Theory (MAUT) analysis. The conducted MAUT analysis resulted in the development of rules for a more standardized assessment of priority management areas. This assessment is based on participatory evaluation and introduces a utility-function-based hierarchical spatial model. Within the model, each of the 5 criteria contains relevant information, including fuel hazard, potential fire behaviour, fire extinction accessibility, valuable resources at risk, and historical fire data, serving as the foundation for a comprehensive analysis of fire prevention measures. During the assessment, two distinct sets of weights were applied: one based on expert evaluation and another using equal weights. These weights describe the relative importance of the indicators within each criterion in the assessment of fire prevention measures. Our results reveal noticeable differences between the two applied approaches. In general terms, management priority levels showcase certain spatial aggregation patterns and spatial polarization characteristics. Our study underscores the importance of participatory planning for prioritizing forest management areas to reduce fire impacts and presents a methodological framework that facilitates such spatial assessments, utilizing tools that combine expert knowledge and scientific expertise. Therefore, the main focus of this study is not on the obtained results, but on the novel methodological framework used, which consists in combining geospatial modelling with MAUT and the participatory workshops for generating the utility rules. This framework allows participation of stakeholders which at the same time enlarges credibility and acceptance of the methodology and results.

Landslide Susceptibility Assessment in Nuwakot: An Examination of Methods to Mapping

The highest re-occurring hazard incident in Nepal in 2022 is reported to be fi re and landslides. A comprehensive study on understanding and identifying landslide susceptible areas and planning accordingly is perhaps one approach to disaster preparedness. In this context, landslide susceptibility assessment (LSA), plays a key role as a preparedness and mitigation tool at the local level. Landslide susceptibility, theoretically, denotes a geographic location of potential reoccurrence of landslide in an area based on several causative factors. I have conducted this study to explore landslide occurrence in Nepal based on secondary data, and map landslide susceptibility in Nuwakot district by using spatial multi-criteria analysis, SMCA and frequency ratio (FR) method. Then, I have evaluated the results which will support preliminary landslide risk level identification at the local level. Existing secondary data and landslide inventory extracted using satellite imageries were major data sources. Landslides in Nuwakot are concentrated within the range of 1000-1500-meter elevation of 15-25-degree convex slope with gneisses/schists formation. A result using SCMA methodology shows 47% area of Nuwakot under landslide susceptibility, of which 13.6% is highly susceptible whereas FR method resulted 27% area under high susceptible zone. The variation in susceptibility level and area between SCMA and FR methods can be attributed to differential calculated weight factor to geological factors, such as fault, lineament, and lithology. This study concludes that irrespective of methods adopted, landslide susceptibility maps and output data provide useful tools for landslide hazard risk identification and management. The necessity of robust and commonly applicable guidelines at different geographic scales is also obvious.

Spatial multi-criteria decision analysis for site selection of wind power plants: a case study

ABSTRACT Site selection for wind power plant (WPP) installation is a complex process that includes not only technical requirements but also physical, economic, social, and environmental sanctions. This study was carried out to determine optimal sites for WPP installation within the borders of Çanakkale province using spatial multi-criteria decision analysis (MCDA). Within the scope of the study, sites with a high level of suitability where a WPP can be established were determined by the geographic information system (GIS) and the analytical hierarchy process (AHP). The results were examined in two ways: by excluding and not excluding forest areas. After creating the two separate suitability maps, the annual electrical power generation potential (GP) map of the study area was generated. The results show that for the case where the forest areas were excluded, 67.26% of the study area is restricted and 29.94% is highly suitable, and for the case where the forest areas were not excluded, 58.94% is restricted and 36.25% is highly suitable. The total GP value of the highly suitable sites is 104,061.61 GWh/year. When the locations of existing WPPs were examined for control purposes, it was seen that the majority of them were located inside the areas with high suitability and outside the non-installable areas, but some of them were established in forested areas.

Measuring the Transit-Oriented Development (TOD) Levels of Pakistani Megacities for TOD Application: A Case Study of Lahore

The urbanization challenges in the megacities of Pakistan necessitate the implementation of comprehensive sustainable development practices to effectively address contemporary urban issues. Transit-oriented development (TOD) is a globally accepted device in achieving sustainable urban development through transport and land use integration. Evaluating the levels of TOD built in present conditions is essential for productive TOD planning, as it enables the prioritization of development interferences. In this context, we utilized a methodology to evaluate the levels of TOD (TOD-ness) present near transportation nodes through a TOD index. It utilizes ArcGIS and spatial multi-criteria analysis (SMCA) to determine the extent of TOD-supporting qualities around a transit node and identifies areas for potential improvements in transit orientation. The methodology was executed in the megacity of Lahore, situated in Pakistan. A TOD index was computed for areas surrounding the 26 LRT and 27 BRT stations along two existing corridors. The findings suggest that the TOD concept is feasible for Pakistani megacities, and urban decision makers can utilize the TOD index results to facilitate urban- or regional-level planning, funding, and investment policies. Furthermore, these findings offer valuable insights into the transportation obstacles and potential opportunities in similar developing cities in South Asia.

Community gardens for inclusive urban planning in Padua (Italy): implementing a participatory spatial multicriteria decision-making analysis to explore the social meanings of urban agriculture

Urban agriculture is recognized as a worthy resource to support a growing population as well as to provide other positive effects on urban ecosystems and their citizens. In this context, community gardens are considered key topics in terms of food production and food security, in both developing and developed countries, as well as in terms of social inclusion and participation. The general aim of this study was to assess the main spatial criteria recognized and shared by stakeholders to identify suitable and inclusive areas for community gardens by testing and developing a participatory process. Because of its size, population, and urban fabric, Padua (northeast Italy) was selected as a representative and emblematic case study for mid-sized cities in Europe. The methodology was based on field surveys of key informants and spatial multicriteria decision-making analysis in the open-source geographic information system environment of QGIS. The results identified neighborhoods to be prioritized in the design of new community gardens according to three scenarios: the distance index, the social index, and the combination of the two (overall index). To conclude, this study highlighted the importance of adopting a decision-making methodology to support local policymakers and municipal agencies that are interested in implementing other community gardens in Padua. The case study and the methodology adopted could also serve as important guides for cities by providing step-by-step processes that can be directly applied.

Evaluating Industrial Areas with Spatial Multicriteria Analysis (SMCA)

The assessment of industrial areas stands as a pivotal challenge, increasingly recognized for its urgency across various regions. The industrial sector is a cornerstone of national economic development, contributing significantly to growth and enhancing community welfare. Nonetheless, the establishment of industries also poses environmental and societal risks, primarily due to potential pollution. This study focuses on evaluating the suitability of industrial zones in East Cikarang District, Bekasi Regency, through spatial analysis, benchmarking findings against government-regulated industrial areas as outlined in the Bekasi Regency spatial plan for 2011-2031. Employing Spatial Multicriteria Analysis (SMCA) via ILWIS software, this research aims to deliver a comprehensive assessment of industrial locations by considering variables such as proximity to roads, rivers, settlements, land slope, and alignment with designated industrial zones in the regional spatial plan. The analysis reveals a nuanced classification of industrial suitability, with 48.55% of the area deemed highly suitable, indicating a substantial portion of East Cikarang District is favorable for industrial development. Conversely, a smaller segment falls into the less suitable or unsuitable categories. Overall, the study concludes that 55% of the region qualifies as suitable for industrial purposes based on the SMCA-derived spatial model, with 98.1% of the assessed area aligning with the criteria for designated industrial zones. These insights are intended to guide industrial planning and environmental management strategies, fostering sustainable development within the region.

Mapping areas suitable for agriculture and their accessibility: The case of the centre region of Cameroon

Given the pressure on land in the Central Region due to economic development and the search for opportunities, the best land for agriculture needs to be identified, so as to preserve it from urbanization, the expansion of mining areas, infrastructure and other occupations. It is in this context that the issue of mapping to identify agricultural zones and assess their accessibility was raised. This is an opportune moment to feed reflections on planning, agricultural production and natural resource management in the Center Region of Cameroon. GIS-based multi-criteria spatial analysis of data on land use, hydrographic network, slopes, soils and their suitability for cultivation provided precise, geolocalized information on land potentially suitable for agriculture in general. Following the analyses, we were able to establish and highlight the areas suitable for agriculture and accessible, which amounted to 8%, or 5662.42 km2 for high-potential and accessible areas. This was followed by 56%, or 37144.95 km2 for medium-potential and accessible zones, and finally 6%, or 4238.93 km2 for low-potential and accessible zones. Once the accessible areas had been removed, 5% or 3028.27 km2 of high-potential inaccessible areas remained, 19%, that is 14639.46 km2 of medium-potential inaccessible areas and 2% that is 967.12km2 of low-potential inaccessible areas.

Landslide susceptibility assessment along the Red Sea Coast in Egypt, based on multi-criteria spatial analysis and GIS techniques

The Egyptian Red Sea coast, a mountainous coastal region, is periodically exposed to landslide that cause severe man and economic losses. That is due to its geological, hydrogeomorphological, and seismological nature. This research aims to map landslide susceptibility in the study area using a multi-criteria overlay analysis approach. Slopes, elevations, aspects, curvature, lineaments, faults, earthquakes, rainfall, stream network, and rock units are the factors used to derive the landslide's susceptibility map. The data were obtained from research organizations and open-source geospatial platforms. The landslide susceptibility map of the area under investigation ranges from low to high as follows: 1) low (23 %), 2) moderate (43 %), and 3) high (34 %) from total area. The used model is validated using direct field check and statistical analysis by Receiver operating characteristic (ROC) curve test 40 landslides events. Based on ROC, the multi-criteria overlay analysis approach can predict landslides by 82 % at a 95 % confidence level. The leading causes of landslides are geological, topographical, hydrogeomorphological, and seismological. For long-term development, the study's findings would assist decision-makers in lowering the risks connected with landslides in the areas. To reduce the chance of landslides, the study recommended it is important to take into account the rugged topography of zones where landslides are likely to occur and implement rockfall protection systems like barriers, embankments, or mesh.

Spatial multi-criteria decision analysis for the selection of sentinel regions in tick-borne disease surveillance

BackgroundThe implementation of cost-effective surveillance systems is essential for tracking the emerging risk of tick-borne diseases. In Canada, where Lyme disease is a growing public health concern, a national sentinel surveillance network was designed to follow the epidemiological portrait of this tick-borne disease across the country. The surveillance network consists of sentinel regions, with active drag sampling carried out annually in all regions to assess the density of Ixodes spp. ticks and prevalence of various tick-borne pathogens in the tick population. The aim of the present study was to prioritize sentinel regions by integrating different spatial criteria relevant to the surveillance goals.MethodsWe used spatially-explicit multi-criteria decision analyses (MCDA) to map priority areas for surveillance across Canada, and to evaluate different scenarios using sensitivity analyses. Results were shared with stakeholders to support their decision making for the selection of priority areas to survey during active surveillance activities.ResultsWeights attributed to criteria by decision-makers were overall consistent. Sensitivity analyses showed that the population criterion had the most impact on rankings. Thirty-seven sentinel regions were identified across Canada using this systematic and transparent approach.ConclusionThis novel application of spatial MCDA to surveillance network design favors inclusivity of nationwide partners. We propose that such an approach can support the standardized planning of spatial design of sentinel surveillance not only for vector-borne disease BDs, but more broadly for infectious disease surveillance where spatial design is an important component.

A Spatial Multicriteria Analysis for a Regional Assessment of Eligible Areas for Sustainable Agrivoltaic Systems in Italy

Agrivoltaics’ share of renewable generation is relevant for countries to achieve their energy transition targets. Agrivoltaics is the dual and synergistic use of the land by agricultural crop production and photovoltaic (PV) systems. For their development around a country, a fundamental step is to determine which areas are suitable. This research work has developed a methodological framework for a reliable agrivoltaic land eligibility analysis at regional scale based on a spatial multicriteria analysis (i.e., GIS/MCDM-AHP). The challenging step has been to select a set of relevant criteria, also based on experts’ knowledge, able to capture the factors that can affect both the solar PV potential and agriculture-oriented factors. On the basis of these criteria, properly weighted, a 30 m-resolution land eligibility map for agrivoltaic systems has been generated for the NUTS-2 regions of Italy. We have found that Italy has an eligible area of 10.7 million hectares and a capacity potential of 6435 GW, assuming an installed power density of 0.6 MW/ha. Thus, a land coverage of only 1.24% of this area would allow to reach the national 80 GW target of new renewable capacity to achieve the country’s decarbonisation and energy transition objectives by 2030. The potential of installed capacity results at GW scale for the main land categories of arable land and permanent crops if they are just covered by only 5% with agrivoltaic systems. Thus, the impact of agrivoltaic systems development on land occupation can be considered marginal especially in relation to benefits generated for both the energy and agricultural sectors. Such a method is essentially targeted to regional authorities for planning the sustainable development of agrivoltaic systems at the local level.

Location of agricultural warehouses based on spatial multicriteria analysis

Resumo O agronegócio brasileiro avança em busca de tecnologias e novas áreas agricultáveis. Muitas vezes, a expansão das áreas agrícolas ocorre sem planejamento integrado com os atores do sistema logístico, especialmente em regiões de fronteira agrícola, como a região do MATOPIBA. O planejamento da localização de novos armazéns graneleiros contribui para a melhoria do processo de tomada de decisão para investimentos. Além disso, possibilita um processo virtuoso que permite a incorporação de aspectos para fomentar a intermodalidade e a preservação ambiental. Assim, o objetivo deste artigo é avaliar se uma combinação de critérios locacionais que considerem aspectos ambientais e de intermodalidade pode identificar regiões mais adequadas para a instalação de armazéns graneleiros do tipo subterminal. A metodologia utilizada agrega a Análise Hierárquica de Processos (AHP) e técnicas de geoprocessamento. A aplicação dos métodos permitiu classificar as regiões candidatas para a instalação de armazéns. Os resultados indicaram três grandes áreas adequadas para a armazenagem de grãos, que juntas representam 12% da área de estudo. A conclusão da pesquisa foi que, além de aspectos econômicos, a inclusão de fatores ambientais e de infraestrutura logística na análise espacial da localização promove uma rede de armazenagem mais sustentável, com armazéns bem posicionados e com menor competição.

Participatory mapping of local stakeholders’ perceptions of nature’s contributions to people in an intensified agricultural area in the Colombian Andes

ABSTRACT Intensification of agricultural land use in traditional Andean production landscapes has led to changes in the provision of nature’s contributions to people (NCP) that can threaten people’s wellbeing. Understanding local stakeholders’ valuation of these NCP is crucial for improving land use decisions. We implemented a spatially explicit and participatory NCP valuation method, using semi-structured interviews and participatory mapping, followed by a spatial multi-criteria decision analysis, to identify priority areas for NCP provision in a highly intensified production landscape in the Colombian Andes. We considered multiple value types, ecological, economical and sociocultural, and the points of view of different actors, orienting this towards decision-making on land use. Our results show that local actors can identify and value a wide range of NCP. However, there are also significant differences between actors. Environmentalists attached special importance to regulating NCP, while agricultural laborers focused more on agriculture-related material NCP. As we expected, tourism entrepreneurs especially valued non-material NCP related to their business experiences. Small-scale farmers tended to put more importance on regulating and non-material NCP than big farmers did. Although there was a consensus between actors as to the importance of natural ecosystems for NCP provision, agricultural actors tended to attach more importance to material NCP in areas deemed important for regulating and non-material NCP by other actors. Our main results confirm the importance of involving different stakeholders in spatial NCP valuation exercises, recognizing their different points of view to help identify possible trade-offs and synergies related to land use.

Spatial multicriteria framework for sustainable wind-farm planning – Accounting for conflicts

Considerable pressure is placed on wind power in Sweden due to the country's goal of generating 100% of its electricity from fossil free resources. The aim was to develop the REWIND methodological framework to support wind power planning, built on spatial multi-criteria analysis (SMCA). In addition, the purpose was to develop a conflict score as a novel component of this framework, for handling goal conflicts. This framework includes the scoping, design and evaluation stages. It was applied in a case study of Västernorrland County with extensive involvement of stakeholders throughout the process.The conflict score allows a separate analysis of trade-offs between factors, highlighting potential conflicts across the landscape to increase transparency. Thus, users are allowed to decide on a threshold on how much conflict among factors should be allowed for areas to qualify as planning alternatives. Critical issues that will need further attention concern quality and availability of data, creation of representative spatial indicators for the factors, weighting methods, and uncertainty analysis. The REWIND framework is open-ended and allows for further development to provide planning support that gives more control of factors and conflicts to be acceptable in real-world planning. Capacity building involving stakeholders in the design of planning alternatives are crucial. In Sweden, it can promote a more proactive planning process in the municipalities, supported by the regional actors, leading to a more predictable permitting process for developers. This will be useful for inclusive wind power planning in any country, since it is applicable on different scales.

Harmonization Approach to Spatial and Social Techniques to Define Landscape Restoration Areas in a Colombian Andes Complex Landscape

Landscape restoration activities must be conducted through a transdisciplinary process, integrating social, economic, environmental, and governance aspects. Combining visions from the natural and social sciences is a challenge in highly complex territories, where unique ecosystem characteristics, economic processes, stakeholders of diverse nature, and different normativity converge. The harmonization of multiple techniques, such as multicriteria spatial analysis, expert knowledge elicitation, and social mapping, allows for an approach to defining landscape restoration areas in complex regions. This paper employs multiple techniques to define ecosystem restoration areas in a complex Colombian Andes landscape, integrating ecological and social components for sustainable development. We observed that areas of high and very high feasibility for ecological restoration, encompassing 179.5 hectares (4.84% of the study area), are predominantly located near primary forests. Although some areas have a low feasibility for conservation processes, they should not be disregarded as they still require protection. Landowners prioritize watershed and soil restoration as the most important landscape restoration activity due to their interest in improving water-related ecosystem services. This proposal enables the identification of areas with a higher restoration potential at the property level, facilitating prioritization and investment allocation for future implementation.

Spatial Multi-Criteria Analysis for Discovering Nature-Based Solutions Location for Urban Flood Mitigation in Accra

In recent years, Nature-Based Solutions (NBS) have become instrumental in restoring ecosystems and reducing the negative effects of hard surface developments. Existing studies have shown the potential of NBS in mitigating urban floods and reducing overall hydrogeological risks, especially in high-income areas. However, there is limited knowledge on area-specific NBS implementation and the locational suitability of areas to support different NBS for urban flood mitigation in medium to low-income regions. A methodology based on Spatial Multi-Criteria Analysis (SMCA) has the potential to spatially combine and synthesize information to elicit spatially-specific opportunities for NBS implementation. However, an SMCA tool to determine suitable locations for different NBS measures for urban flood mitigation does not yet exist. In order to address this research gap, this study developed an SMCA methodology to identify different target areas where specific urban flood-related NBS measures can be implemented to minimize urban flood occurrence in Accra, Ghana. The study revealed different locations where urban flood-related NBS measures could be applied. It also demonstrated how specific NBS measures could be tailored to the characteristics of different areas in Accra to ensure effective urban flood mitigation. The suggested methodological approach provides a spatial knowledge base for flood management institutions to integrate NBS into flood management schemes. The approach has application potential for other geographic contexts facing urban flood risks. Future research could focus on possible ways of integrating NBS into the spatial development of cities.

Spatial Analysis of Built-Up Land Suitability in Ternate Island

The population of Ternate City which is increasing every year can certainly cause the need for land as a space for their activities to increase and will lead to a kind of competition to get a suitable space and in accordance with the various interests and needs of the community there. This study aims to spatially analyze the suitability of built-up land on Ternate Island, North Maluku Province. This research uses Spatial Multi Criteria Analysis method using variables of terrain shape, slope, distance from road, distance from river, distance from economic activity center, and disaster prone area of Mount Gamalama. The results showed that 49.12% of the Ternate Island area was in the suitable area, 29.57% of the research area was in the less suitable class and the unsuitable class had an area of 21.31% of the total research area. The results of this study are expected to be a reference and input for the evaluation of the Ternate City RTRW in the future.

Insights from a comparative GIS-MCDA groundwater vulnerability assessment in a granitic and metasedimentary fractured rock media

This work proposes a comprehensive methodology for evaluating fissured hard-rock groundwater resources through an integrative approach based on fieldwork techniques, Geographic Information System (GIS)-based mapping, geospatial analysis and multiple-criteria decision analysis (MCDA). The study sites comprise distinct geological settings and geographic contexts, i.e. granitic rocks (NW Portugal) and metasedimentary rocks (SW Spain). A similar methodological approach was used in both areas to compare and assess the methodological approaches’ effectiveness. The cartographic, field, and laboratory data were analysed through GIS overlay and multi-criteria spatial analysis. This GIS-integrated analysis allowed the calculation of the Infiltration Potential Index (IPI) and groundwater vulnerability indexes: GOD-S, DRASTIC-Fm, SI and DISCO, as well as the development and improvement of the hydrogeological conceptual models. At the Entre-os-Rios site (NW Portugal), the IPI index showed that the most favourable areas for infiltration are the fractured granitic regions, where the slope has the lowest values, combined with forest areas. The recharge values are around 70 to 90 mm/year. Considering hydraulic connection with the borehole data, the DISCO index identified the geostructures with the most important trending to NNE-SSW, NE-SW and WNW-ESE in the area. The highest IPI values were identified in the regional aquifer quartzite unit at Herrera del Duque (SW Spain). The recharge values are around 60 to 80 mm/year. The DISCO index identified zones where discontinuities have a higher hydraulic connection to the borehole, mainly trending NW-SE and NE-SW. The models developed could be helpful for decision-making and sustainable water resources management regarding the planning of hydrogeological investigations, delineating potential contamination areas, and the definition of catchment protection areas.