GIS Framework Research Articles

Выбор аналитической модели и количественных показателей для геоинформационного анализа устойчивого развития территориальных образований

Currently, there are no generally accepted algorithms for assessing, analyzing and forecasting the sustainable development of administrative-territorial units. The authors introduce the definition of this term, which implies the successful functioning of a human community over time carrying out economic activities without threats to its environment. Also, an analytical model for representation of its regional integrated indicator in the form of a vector with differential components, which characterize economic growth, environmental and social metrics, in a three-dimensional affine space, is proposed. Furthermore, we present a multiplicative criterion for assessing partial criteria of sustainable development efficiency and the basic expression for its parameters computation based on the set of economic, environmental and social ones, including such as the availability and quality of natural resources, regional labour resources, eco-factors, etc. The proposed vector model is based on the geoinformation approach and can be deployed within the framework of GIS of sustainable development for geo-analysis, modeling and mapping of natural resource potential and ecological state of intensively advancing territories, considering the dynamics of this process. Important properties of the geoinformation approach to assessing territorial entities’ forward growth, spatial and semantic scalability, are noted. In addition, the functional requirements and preliminary architecture of the core, modules, clients and layers of the related thematic geographic information system for the management, planning and forecasting the said indicator within the framework of digital economy are described

The GIS framework is used to assess Lucknow City's groundwater quality using the water quality index [WQI

Monitoring groundwater quality continuously is essential to reducing the dangers of geochemical pollutants through suitable treatment techniques and guaranteeing safe drinking and irrigation. Thus, this study's main goal was to evaluate the appropriateness of the groundwater that was collected, from India's Lucknow for irrigation as well as drinking. To assess the quality of the groundwater in the research area, ten samples were taken from various locations. Analysis was done on some parameters, including pH, total dissolved solids (TDS), electrical conductivity (EC), total hardness, total alkalinity, BOD, COD, nitrate, total nitrogen, E. Coli, and ammonia. The water quality index (WQI) has arithmetical weights. Using a critical grading system that shows overall quality, the water's quality was evaluated and categorized as very good, good, moderate, bad, and unfit for consumption. Increasing public understanding and decision-making to make informed choices about efficient care, management, and long-term, sustainable social growth is greatly aided by this classification. To find relationships between the different parameter values, a correlation matrix was created and examined. As a result, the results imply that the groundwater in the investigated region is secure and appropriate for irrigation and consumption.

Identifying seawater interaction with coastal aquifers using hydrochemical and GIS for Nagapattinam district, southeast coast of India

Groundwater chemistry of the two different seasons collected between 2020–2021 from the coastal areas of Nagapattinam, Mayiladuthurai and Karaikal in Tamil Nadu state of southeast India were evaluated for seawater intrusion into coastal aquifers. Groundwater types, its classification was evaluated to know the extension of seawater intrusions into coastal aquifers using the Groundwater Quality Indices (GQI) such as GQIPiper(mix), GQIPiper(dom), fsea, GQIfsea and GQISWI. Piper diagram grouped most samples (GQIPiper(mix) and GQIPiper(dom)) in domain-II, representing Na-Cl water type, followed by domain-IV, indicating mixed Ca-Mg-Cl water for both the seasons. As measured by the saltwater Intrusion as Groundwater Quality Index (GQISWI), about 62.5 % and 37.5 % of the pre-monsoon samples showed low saltwater intrusion and moderate seawater intrusion, respectively. In the post-monsoon samples, the low saltwater intrusion increased to around 82.5 % and the moderate seawater intrusion decreased to 17.5 % of the groundwater samples. The GIS framework was used to display the geographical distribution of groundwater types as well as the delineation of vulnerable zones from seawater intrusion.

Exploring the role of high-value crops to reduce agricultural greenhouse gas emissions in New Zealand

This study explores the potential benefits of transitioning from livestock farming to high-value alternative crops as a strategy for mitigating agricultural greenhouse gas (GHG) emissions in New Zealand. The government has set ambitious targets for reducing methane (CH4) emissions. However, since animal product exports play a crucial role in New Zealand’s economy, any shift in land use will have significant impacts on both the regional and national economy. We developed a GIS framework that integrated (i) growing requirements, (ii) GHG emissions and (iii) profitability for crops. Analysis of export market opportunities identified twelve high-value “alternative crops”. Availability of suitable land for crop expansion was not a limiting factor. Working with the Ministry for Primary Industries, we explored how land use change scenarios contributed to Government 2050 biogenic CH4 emission reduction targets. Doubling the area of alternative crops (a 195,000-ha increase) by reallocating land from livestock farming resulted in reducing biogenic CH4 emissions by 1.2 to 5.4% (0.35 to 1.57 Mt CO2-e) compared to 2017 baseline values, contributing to between 2.6 and 22.5% of the 2050 CH4 reduction targets, simultaneously increasing profitability by $NZ1.25 to 1.32 billion annually. While this approach demonstrates potential benefits of land use change, a deeper understanding of the complexity of land use decision-making is required to enable successful transitions. Addressing barriers to change requires collaborative efforts from land users, researchers and policy makers.

Delineation of groundwater vulnerable zone for sustainable development in the southwestern part of Bihar, India

In the face of the global groundwater crisis and climate change challenges, the groundwater potential (GWP) and quality (GWQ) assessment for tackling the depletion and contamination of aquifers are imperative for India's sustainable development of groundwater resources. This study explores the GWP and GWQ in the southwestern part of Bihar state, located in the declining groundwater of the lower Indo-Gangetic plain, where population growth, rapid urbanization, and escalating agricultural demands have strained aquifer systems. This study uses the Analytical Hierarchy Process and weighted average techniques in the GIS framework to assess groundwater vulnerability. Our results reveal that over 82% of the area exhibits good groundwater potential, except for the southern part. The presence of Vindhyan mountains in the southern part has different geology, elevation, and land use and land cover, leading to poor groundwater potential. Considering the desirable and acceptable limits by BIS (2012) and Who (2022), it has been found that 89% and 18% of the study area falls under the poor to unsuitable groundwater category, affecting a staggering 7.7 million and 1.6 million individuals, respectively despite substantial groundwater potential. Findings from this investigation indicate that groundwater contamination resulted from anthropogenic and geogenic factors; however, it remains suitable for agricultural purposes. Our research will assist policymakers in implementing sustainable management strategies to ensure a lasting and reliable supply for domestic and agricultural uses of groundwater.

ASSESSMENT OF THE SPATIAL APPROPRIATENESS OF THE FUTURE URBANIZATION OF THE CITY OF (AIN BEIDA, ALGERIA) USING GEOGRAPHIC INFORMATION SYSTEMS, THE ANALYTICAL HIERARCHY PROCESS, AND THE DELPHI METHOD

Spatial adequacy evaluation is a valuable tool for planning land use strategies. It provides planners with data and outcomes that can help them make informed decisions to ensure effective and secure utilization of land in future urbanization processes. The objective of this study is to analyze the urbanization patterns in the city of Ain El Beida to determine the most appropriate areas for urban development. The aim is to create self-sustaining growth centers that effectively support the city, while also helping decision-makers address current expansions and protect agricultural lands. The study utilized spatial analysis methodology to evaluate and map the suitability of expanding the city's future space. It proposed an integration strategy that combined modern methods and techniques of the Delphi methodology to establish criteria for appropriate land use. The influence of these criteria will be analyzed spatially by administering a questionnaire to a sample of specialists in urban planning and city geography, followed by the application of spatial analyst techniques. The user's text is straightforward and precise. within the GIS framework, integrated via the analytic hierarchy approach. The user's text is straightforward and precise. To evaluate the suitability of the spatial location, to determine the significance of the factors influencing the expansion process based on their relative importance, to ensure that the desired goals are achieved in a way that reflects the priority of the decision-making criteria, and to identify the most favorable options for urban development in the study area. The findings indicated that the optimal locations for the urban growth of Ein El-Baida were determined to be 239.57 hectares, which accounts for 26.31 per cent of the entire land area under investigation. These areas are situated on the northern side of the city along National Road 80 (Ain Beida Presh) and on the western side along National Road 10 (Oum el-Bouaghi Ain Beida). These locations have been identified as the most suitable areas for spatial expansion due to their numerous incentives for urban attraction. Firstly, there is a considerable distance from the fertile and generously compensated agricultural areas, which offer unoccupied and level terrain, as well as its proximity to the central area of the pristine city of Ein. The study also determined that integrating GIS with hierarchy is crucial for constructing spatial models that accurately represent physical reality through mathematical means. This integration aids planners in selecting the most appropriate alternatives for urbanization and achieving comprehensive development of the city.

Quantifying Morphostructural Evolution of the Eastern Algerian Saharan Atlas (NE, Algeria) Using GIS-based Surface Envelope Technique, Drainage Network Analysis, and Geological Features

This research work focuses on the morphostructural evolution of the eastern end of the Algerian Saharan atlas. The study employs a comprehensive methodology involving the utilization of the surface envelope technique, combined with an analysis of the hydrographic network and geological context. These techniques are integrated within a GIS framework to decipher the current relief characteristics. To interpret the current relief features, two ASTGTM v2 tiles were processed to extract morphometric data. The reconstruction of the original relief requires the generation of the summit level surface, the base level surface and the relief amount maps for 3 different grid sizes (4000m, 1000m and 250m). The respective different grid size maps has allowed determining the initial surface of the reliefs; first before any major vertical erosion, then after a phase of dismantling and finally the recent and sub current morphological aspect. The extraction of the hydrographic network and the elimination of lower than order 5 streams revealed the harmony of the latter with a raised shaped form (mega-horst) which represents the main morphostructural unit. This morphostructure is particularly characterized by outcrops from the Lower Cretaceous outcrops. The ramification of the hydrographic network along the main tectonic accidents has allowed the digging of wide valleys, often described as graben.

Groundwater quality evaluation using Water Quality Index (WQI) under GIS framework for Mandya City, Karnataka

Groundwater quality evaluation using Water Quality Index (WQI) under GIS framework for Mandya City, Karnataka

Glacial lakes of Sikkim Himalaya: their dynamics, trends, and likely fate—a timeseries analysis through cloud-based geocomputing, and machine learning

In the background of ongoing climate change, it is important to monitor the spatial and temporal changes of glacial lakes (GLs) since they influence snowmelt runoff, stream discharge, water resources, and glacial lake outburst flood (GLOF). However, accurate identification and mapping of GLs in the background of snow-clad mountains through visual interpretation of satellite data is a tedious and challenging assignment when multiyear time-series analysis is considered. To overcome this challenge, automated extraction of GLs in satellite images has been carried out in this study with the help of machine learning (ML). The novelty of this study is identification and tracking of GLs over three decades using ML and geospatial analysis using pixel-based image classification. For this, Random Forest Classifier (RFC) and Artificial Neural Network (ANN) were employed. The methodology is demonstrated here for the identification and mapping of GLs in the Sikkim Himalaya from 1987 to 2020 and for forecasting the possible fate of these GLs through time-series modelling. The geospatial time-series analysis using Google Earth Engine, ML classifiers, and GIS framework, has captured the dynamics of GLs in Sikkim and has revealed the spatial and temporal patterns in GLs’ dimensions as well as GLOF risk.

Ultrasonic-pretreated hydrothermal synthesis of less dense zeolite CHA from the transformation of zeolite T

Because of containing the same double 6-ring (D6R) building unit, the pure zeolite CHA with lower framework density (FDSi = 15.1 T/1000 Å3) has been transformed from zeolite T with higher framework density (FDSi = 16.1 T/1000 Å3) through ultrasonic-pretreated hydrothermal synthesis in MOH (KOH and NaOH) solution without adding organic template or seed crystals. Ultrasonic pretreatment facilitates the transformation rate and generates high-quality zeolite CHA. The ultrasound condition should be precisely controlled because that CHA phase is metastable, which is inclined to transform to other more stable phase. The ultrasonic conditions at 313 K and 333 K have been investigated in detail. In KOH solution, the ultrasonic treatment at 313 K can effectively restrain the generation of MER phase, however, it is hard to avoid the existence of MER phase when ultrasound temperature is 333 K. In NaOH solution, the samples with ultrasonic treatment of 313 K show the small particles size of about 1 μm, and the GIS framework topology starts to grow with the ultrasonic treatment of 333 K. The products prepared with the appropriate ultrasonic pretreatment represents smaller particles size, larger mesopore volume and higher CO2 adsorption capacity than the sample without the ultrasonic pretreatment. The structural evolution of interzeolite transformation has been explored by XRD, FT-IR and SEM observations. With the assistance of ultrasound, the parent zeolite T can quickly decompose into intermediate phase and then regenerate into CHA phase.

Spatial analysis of leisure land uses in Tehran: Assessing inequity using the MARCOS method within a GIS framework

This study focuses on the spatial analysis of leisure land uses in metropolitan Tehran, specifically examining spatial equality. The combination of the Measurement of Alternatives and Ranking according to Compromise Solution method and Geographic Information System is employed to evaluate leisure needs based on multiple criteria. These criteria encompass recreational, entertainment, tourism, social services, cultural services, religious, sports factors, as well as parks and green spaces. The objectives of this research are to draw attention to recreation-related challenges in Tehran, provide insights for urban planners, understand the city's spatial status, ensure equitable facility distribution, and propose solutions aligned with residents' preferences for improved service provisions. The final map resulting from the MARCOS method reveals significant disparities in leisure facility accessibility between privileged and deprived districts. Notably, residents in the northern and central districts experience better living conditions compared to other areas. This study highlights the diverse needs of residents across districts, underscoring the importance of tailored service provisions. The findings hold implications for the Ministry of Interior, the Management and Planning Organization, and the Municipality of Tehran, guiding their planning strategies to enhance recreational spaces and promote spatial equality. By utilizing the research outcomes, these organizations can contribute to the improvement of leisure facilities and the overall well-being of Tehran's residents.

A New Methodology for the Prioritization of Visual Inspections of Bridges and Viaducts

AbstractThe assessment of risk conditions of bridges and viaducts allows management authorities to ensure the safety of the users and the proper allocation of economic resources for maintenance and retrofitting interventions. A common circumstance in practice regards the lack of information as well as the need to update it, causing delays in the risk evaluation and, consequently, in the entire decision‐making process. Especially in the managing of large bridge assets, the retrieval/updating of information can be costly, both in terms of time and economic resources. In this regard, the execution of visual inspections to determine the defect level of bridges and viaducts is the most resource‐intensive operation on the part of the management authorities. In this paper, a new methodology to prioritize visual inspections of bridges according to their risk condition and operating costs is proposed and illustrated with a real case study. A novel aspect of the proposed methodology regards the use of information gain criteria to refine the outcomes from the risk assessment and prioritization process. Finally, the outcomes of the methodology are implemented in a GIS framework to ensure high interoperability and facilitate the construction of intuitive risk maps to assist inspection plans.

Assessment of Ground Water Quality of Lucknow City under GIS Framework Using Water Quality Index (WQI)

Continuous groundwater quality monitoring is crucial for ensuring safe drinking and irrigation by mitigating risks from geochemical contaminants through appropriate treatment methods. Therefore, the primary objective of this study was to assess the suitability of groundwater collected from Lucknow, India, for both drinking and irrigation. Forty samples were collected from different sites within the study area to evaluate groundwater quality. Various parameters such as pH, turbidity, total dissolved solids (TDS), chlorides (Cl−), total alkalinity, total hardness, sulphate (SO42−), nitrate (NO3−), fluorides (F−), iron (Fe), arsenic (As), magnesium (Mg2+), and calcium (Ca2+) were analyzed. The weighted arithmetic water quality index (WAWQI), a vital rating system representing overall water quality, was employed to classify the water into different categories, such as very good, good, moderate, poor, and unfit for drinking. This classification is invaluable for public awareness and decision-making to make informed decisions regarding effective management, treatment, and sustainable societal development on a broader scale. A correlation matrix was generated and analyzed to observe correlations between the various parameters. Additionally, spatial distribution maps for the analyzed parameters and WQI were prepared using the inverse distance weighted (IDW) method. The study found that WQI values in the area ranged from 2.64 to 168.68, indicating good water quality in most places except for the Kukrail region, where the water quality is unfit for drinking purposes. The water quality map shows that 86% of the area falls under the very good category, 14.63% under good to moderate quality, and 0.37% is categorized as unfit for drinking. Consequently, the findings suggest that the groundwater in the studied area is safe and suitable for drinking and irrigation purposes.

An ontology-based methodology to establish city information model of digital twin city by merging BIM, GIS and IoT

With the development of digital city and smart city construction, the City Information Model (CIM) has played a critical role as a container of spatial–temporal data to establish the Digital Twin City. For a digital twin city, a virtual high-fidelity CIM model that corresponds closely to the real physical world is the premise and cornerstone of its construction. Therefore, the integration of BIM, GIS and IoT has become the preferred topic for researchers and has received much more attention from a wide academic circle. However, traditional integration mainly focuses on the conversion of both IFC and CityGML, and IoT data are also often used as visualizations. More importantly, the underlying data formats of GIS, BIM and IoT are still independent of each other without a unified data structure expression, so real data-driven analysis and decision-making cannot be implemented. This study aims to establish a general CIM ontology to integrate heterogeneous BIM, GIS and IoT data. First, the related work of BIM, GIS and IoT integration is studied and analyzed. A comparison of three mainstream approaches, data conversion, standard extension and data linking, is conducted, and it illustrates the advantages of ontology techniques in solving data interoperability problems. Second, a technical framework of BIM, GIS and IoT data integration based on ontology technology is proposed. The approach is mainly divided into five steps: geometry processing, data instantiation, ontology construction, ontology mapping and querying application. On the basis of the CIM ontology, an application ontology is built for a specific application domain to illustrate rule-based mapping, querying and inferring. Finally, the case study shows that the Ontology-based methodology in this paper has contributed to establish a general pattern for CIM data integration by mapping and linking concepts from the semantic level. It avoids changes in the original data sources and the missing data problem.

A steady-state model reconstruction of the patagonian ice sheet during the last glacial maximum

During the Last Glacial Maximum (LGM), the Patagonian Ice Sheet (PIS) was the largest Quaternary ice mass in the Southern Hemisphere outside of Antarctica. Although the margins of the LGM ice sheet are now well established through end-moraine mapping and dating, apart from a few modelling and empirical studies, there remains a lack of constraint on its thickness and three-dimensional configuration. Here, we provide a high-resolution steady-state model reconstruction of the PIS at its maximum - LGM - extent applied using Nye's perfect-plastic ice rheology. The yield-strength parameter for the perfect-plastic flow model was calibrated against independent empirical reconstructions of the Lago Pueyrredón Glacier, where the former vertical extent of this major outlet glacier is well constrained by cosmogenically-dated trimlines and lateral and end-moraine limits. Using this derived yield-strength parameter, the perfect-plastic model is then applied to multiple flowlines demarking each outlet across the entirety of the PIS in a GIS framework. Our results reveal that the area of the PIS was ∼504,500 km2 (±8.5%) with a corresponding modelled ice volume of ∼554,500 km3 (±10%), equivalent to ∼1.38 m (±10%) of eustatic sea-level lowering at the LGM. Maximum surface elevation was at least 3500m asl although the majority of the ice sheet surface was below 2500 m asl. We find that our ice sheet reconstruction is in good general agreement with previous estimates of net PIS volume derived from transient modelling studies. We attribute the slightly lower aspect-ratio of our ice sheet (and its concomitant 5% reduction in volume and sea-level equivalent) to the lower yield strength applied, based on more temperate and dynamic ice sheet conditions.

Integration of High-Accuracy Geospatial Data and Machine Learning Approaches for Soil Erosion Susceptibility Mapping in the Mediterranean Region: A Case Study of the Macta Basin, Algeria

Erosion can have a negative impact on the agricultural sustainability and grazing lands in the Mediterranean area, especially in northern Algeria. It is useful to map the spatial occurrence of erosion and identify susceptible erodible areas on large scale. The main objective of this research was to compare the performance of four machine learning techniques: Categorical boosting, Adaptive boosting, Convolutional Neural Network, and stacking ensemble models to predict the occurrence of erosion in the Macta basin, northwestern Algeria. Several climatologic, morphologic, hydrological, and geological factors based on multi-sources data were elaborated in GIS environment to determine the erosion factors in the studied area. The conditioning factors encompassing rainfall erosivity, slope, aspect, elevation, LULC, topographic wetness index, distance from river, distance from roads, clay mineral ratio, lithology, and geology were derived via the integration of topographic attributes and remote sensing data including Landsat 8 and Sentinel 2 within a GIS framework. The inventory map of soil erosion was created by integrating data from the global positioning system to locate erosion sites, conducting extensive field surveys, and analyzing satellite images obtained from Google Earth through visual interpretation. The dataset was divided randomly into two sets with 60% for training and calibrating and 40% for testing the models. Statistical metrics including sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (ROC) were used to assess the validity of the proposed models. The results revealed that machine learning and deep learning, as well stacking ensemble techniques, showed outstanding performance with accuracy over 98% with sensitivity 0.98 and specificity 0.98. Policy makers and local authorities can utilize the predicted erosion susceptibility maps to promote sustainable use of water and soil conservation and safeguard agricultural activities against potential damage.

A GRASS GIS Scripting Framework for Monitoring Changes in the Ephemeral Salt Lakes of Chotts Melrhir and Merouane, Algeria

Automated classification of satellite images is a challenging task that enables the use of remote sensing data for environmental modeling of Earth’s landscapes. In this document, we implement a GRASS GIS-based framework for discriminating land cover types to identify changes in the endorheic basins of the ephemeral salt lakes Chott Melrhir and Chott Merouane, Algeria; we employ embedded algorithms for image processing. This study presents a dataset of the nine Landsat 8–9 OLI/TIRS satellite images obtained from the USGS for a 9-year period, from 2014 to 2022. The images were analyzed to detect changes in water levels in ephemeral lakes that experience temporal fluctuations; these lakes are dry most of the time and are fed with water during rainy periods. The unsupervised classification of images was performed using GRASS GIS algorithms through several modules: ‘i.cluster’ was used to generate image classes; ‘i.maxlik’ was used for classification using the maximal likelihood discriminant analysis, and auxiliary modules, such as ‘i.group’, ‘r.support’, ‘r.import’, etc., were used. This document includes technical descriptions of the scripts used for image processing with detailed comments on the functionalities of the GRASS GIS modules. The results include the identified variations in the ephemeral salt lakes within the Algerian part of the Sahara over a 9-year period (2014–2022), using a time series of Landsat OLI/TIRS multispectral images that were classified using GRASS GIS. The main strengths of the GRASS GIS framework are the high speed, accuracy, and effectiveness of the programming codes for image processing in environmental monitoring. The presented GitHub repository, which contains scripts used for the satellite image analysis, serves as a reference for the interpretation of remote sensing data for the environmental monitoring of arid and semi-arid areas of Africa.

Multi-Level Participatory GIS Framework to Assess Mobility Needs and Transport Barriers in Rural Areas: A Case Study of Rural Mumias East, a Sub-County of Kakamega, Kenya

In recent decades, there has been a growing interest in the application of GIS to community empowerment or new policy development through participatory design, information gathering and implementation. This study, therefore, aims to apply a multi-level participatory GIS (PGIS) framework to assess mobility needs and barriers in rural areas from different available transport modes. This assessment was applied to three sub-locations (Lusheya, Khaunga and Mahola) located in the sub-county of Mumias East, Kakamega, Kenya. The study brings two main contributions: (1) an overview of mobility needs and barriers in Sub-Saharan Africa (SSA) and (2) an introduction of a PGIS framework that integrates in-depth local knowledge of rural mobility needs and mobility barriers. This PGIS framework was applied to mobility issues based on three main dimensions: context, process and content. The context in the PGIS framework focuses on identifying the right stakeholders and putting on suitable structures for their training as well as the collection of data. The process considers the collection, analysis and visualization of rural mobility data. The content of the data collected are validated for accuracy in the form of maps and are evaluated for relevance by stakeholders. Local youths with GIS knowledge and digital tools were mobilized along with community people having a solid understanding of the local geographical contexts to collect geographically referenced data related to community resources, transport networks, and mobility barriers. The application of the multi-level PGIS framework has brought to the mainstream daily mobility challenges faced by rural communities in Sub-Saharan Africa. Community members, even those from remote areas, also have access to decision making, reversing the previous structure that strongly relied on often-irrelevant, top-down decision making.

Mapping and validation of groundwater dependent ecosystems (GDEs) in a drought-affected part of Bundelkhand region, India

The importance of groundwater in preserving the health of water resources such as rivers, lakes, streams, and associated vegetation is often ignored or underestimated, which shows a lack of groundwater management policies. Therefore, in order to manage and protect groundwater and groundwater-dependent ecosystems (GDEs), a complete framework is needed, which is necessary for accomplishing the sustainability aim. The present study utilized remote sensing-based input, in-situ data, and a GIS framework for mapping and validation of GDEs. The weights of the input layers were assigned using experts’ opinions. In the study area, GDEs are heterogeneous, and the impact of groundwater overdraft on its dependent ecosystems was also assessed using long-term in–situ groundwater level data. The results show a decreasing trend in groundwater storage; many wells have dried in recent years, whereas surface runoff through the natural streams is also reduced, which reduces the supply of water and the need to identify new well locations. The validation of GDEs shows an accuracy of 73.40% through the area under the curve method. Further, the GDEs map was categorized into five classes, and the moderate GDEs are the dominant in the area. The study shows an overall decrease in vegetation over the past two decades. Considering the risks of groundwater overdraft, the policy implications to support the conservation of GDEs within a sustainable withdrawal context have also been discussed in this work.

Traditional environmental knowledge and transport efficiency of a communal canal network, Tafilalt oasis, Morocco: A historical GIS analytics perspective

The provision of water in the arid Tafilalt – the largest natural oasis in Morocco – changed little over a span of centuries, though the network of surface canals and khettara (qanats) gradually expanded to yield more water to a growing oasis. The introduction of newer water technologies (pumped wells and dams) in the 1970s reduced the availability of water to the oasis but has not diminished reliance on the traditional canal network. All agriculture in this Sahara oasis is irrigated and most water is still distributed through an intricate system of earthen canals incrementally built over centuries and maintained to this day. Here, a traditional environmental knowledge (TEK) and transportation GIS framework is used to explore the efficacy of this common property canal network. Aerial photographic and field survey, interviews with users and managers of canal waters, and GIS network analysis were employed to examine the functional characteristics and communal issues inherent in the canal system, and to assess the efficiency and effectiveness of the traditional system as a water delivery network. GIS analytics employed to assess the distributive utility of the canal network include the Detour Index, Alpha Index, Beta Index, Gamma Index, and Network Density. The first four indices address the efficiency and connectivity of the complex canal network while Network Density assesses the effectiveness of the system in distributing water throughout the oasis. Results demonstrate the strength and adaptability of local TEK, revealing that the historic canal system was incrementally but not haphazardly constructed, and the system that evolved exhibits an efficiency of water distribution closely approximating the efficiency that could be obtained using advanced design and modern planning methods.