Geographic Information System Techniques Research Articles

Assessment of soil erosion and sediment yield in the Peddavagu watershed, India, using a revised universal soil loss equation model (RUSLE) and GIS techniques

ABSTRACT The present investigation was carried out within the Peddavagu watershed, which is located in India. The necessary datasets, including soil, land use land cover, rainfall, and digital elevation model, were processed and analysed within a Geographic Information System framework. To evaluate soil loss within the watershed, the present investigation employed the revised universal soil loss equation (RUSLE) model. Subsequently, the sediment yield is estimated based on the sediment delivery ratio (SDR). The average annual soil loss was estimated at 17.91 tonnes/hectare/year, which is high soil erosion risk. The RUSLE model's accuracy is 82.1%. Moreover, the findings revealed that sub-watersheds (SW) 9 and SW 3 exhibited the maximum and minimum average annual soil loss. The Peddavagu watershed's SDR was 0.210. Annually, 3.76 tonnes/hectare/year of sediment were transported to the Peddavagu watershed outlet. The findings revealed that SW 9 and SW 5 exhibited the maximum and minimum average annual sediment yield. The model's performance was evaluated by comparing its predictions with gauge data for validation. The observed actual data indicated a yield of 3.66 tonnes/hectare/year, while the model predicted a yield of 3.76 tonnes/hectare/year. This resource offers significant insights for policymakers and decision-makers on sustainable watershed management techniques.

Delineation of groundwater potential zones in coastal alluvial region using remote sensing, geographic information system and analytical hierarchy process techniques

Delineation of groundwater potential zone in coastal region is a challenging task. One of the reasons for that is lack of understanding of the geogenic factors in the coastal alluvial areas such as geomorphology, lithology etc. These factors can influence the locations of the groundwater potential zones over the coastal alluvial terrains. The present study is an attempt to analyse the multiple factors to delineate groundwater potential zones in the coastal region of Contai Sub-division, West Bengal, India. In this study, remote sensing, geographic information system (GIS) and multi-criteria decision analysis (MCDA) techniques have been utilized to delineate the groundwater potential zones. Weights were assigned to the parameters using the analytical hierarchical process (AHP) and different classes within each parameter have been ranked on the basis of their relative importance regarding groundwater potentiality. The results of the study were validated by water yield data, water level fluctuation data and geophysical survey. The outcome of validation reveals that a strong correlation (80%) exists between water yield data and groundwater potential zones. Similarly, a good relation occurs for the water level fluctuation data and groundwater potential zones, where the overall accuracy and kappa coefficients are 84.2% and 0.76 respectively. The output of the study reveals that geomorphologically older deltaic plain, older alluvial plain and older coastal plain are good indicators of high groundwater potential regions. Furthermore, the outcome of the study also unveils that lithologically the well sorted medium grained sand is important feature to delineate high groundwater potential regions in coastal alluvial areas. The findings, thus, could establish that present methodology using GIS and AHP techniques has a better potential to identify and map the groundwater potential zones more realistically and can be applied for future planning of groundwater resource management and groundwater exploration in wider coastal alluvial terrain.

Evaluating Shoreline Changes at Ayvacık Reservoir (Çanakkale, Türkiye) Through Remote Sensing and Geographic Information System Techniques: A Twelve-Year Assessment

This study aims to determine the spatial and temporal changes occurring along the shoreline of the Ayvacık Reservoir in Çanakkale, Türkiye. Landsat 8 OLI/TIRS and Landsat 7 ETM+ satellite images were analyzed using remote sensing and geographic information system techniques. The dataset used in the study covers the period between the completion of the dam construction in 2008 and 2019. Preprocessing of the remote sensing satellite images and digital image processing analyses were carried out using ENVI and ArcGIS software. The shoreline was determined through manual digitization. Consequently, it was found that the shoreline length was 14.994 km in 2008 and increased to 22.293 km in 2019. These values represent the observed minimum and maximum shoreline lengths, respectively. The study period revealed an increase in shoreline length. Given that this study is the first to elucidate shoreline changes occurring at the Ayvacık Reservoir, it is anticipated to provide essential insights for water resource managers by contributing significantly to the literature.

Prioritization of sub-watersheds based on quantitative morphometric analysis of the Narmada River, India, using SRTM-DEM and GIS techniques

Investigating the contribution of basin to the cycle of hydrological and the area's size, shape, and creation through quantitative analysis of these characteristics of the local scenery. Additionally, estimates of the denudation rate and hypsometric analysis were made in order to comprehend the sub-basin's quantitative geomorphological properties. The link between the morphometric parameters shows that the local geological and geomorphological features significantly influence the drainage system. On a less elevated surface with a moderate slope, stream geometry displays a pattern as semi-dendritic in greater stream order flow. On mountainous terrain surfaces, main-order streams display a dendritic drainage pattern combined with a coarse texture of drainage. The center zone of the Narmada River basin's sub-watersheds area (9461 km2) underwent morphometric investigation utilizing geographical information systems (GIS) with remote sensing methods. It highlights the usefulness of using Shuttle Radar Topographic Mission – Digital Elevation Model (SRTM-DEM) and satellite images to enhance basin management to evaluate and comprehend many geo-hydrological aspects, like topographic & drainage analyses. ArcGIS hydrological modeling has been used to identify and study basins utilizing SRTM-DEM having 10 m resolution. For the micro-level research of its physiographic characteristics and flow structural control along with runoff, using morphometric parameters like relief, aerial, and linear is also beneficial. This may assist in predicting floods, their extent, and their severity.

Urban Pedestrian Routes' Accessibility Assessment Using Geographic Information System Processing and Deep Learning-Based Object Detection.

The need to establish safe, accessible, and inclusive pedestrian routes is considered one of the European Union's main priorities. We have developed a method of assessing pedestrian mobility in the surroundings of urban public buildings to evaluate the level of accessibility and inclusion, especially for people with reduced mobility. In the first stage of assessment, artificial intelligence algorithms were used to identify pedestrian crossings and the precise geographical location was determined by deep learning-based object detection with satellite or aerial orthoimagery. In the second stage, Geographic Information System techniques were used to create network models. This approach enabled the verification of the level of accessibility for wheelchair users in the selected study area and the identification of the most suitable route for wheelchair transit between two points of interest. The data obtained were verified using inertial sensors to corroborate the horizontal continuity of the routes. The study findings are of direct benefit to the users of these routes and are also valuable for the entities responsible for ensuring and maintaining the accessibility of pedestrian routes.

Resilience Assessment and Enhancement Strategies for Urban Transportation Infrastructure to Cope with Extreme Rainfalls

As climate change intensifies, urban transportation infrastructure faces unprecedented challenges from extreme weather events, such as floods. This study investigates the resilience and vulnerability of such infrastructure under extreme rainfall conditions in Changchun City. Utilizing Multi-Criteria Decision-Making Analysis (MCDM) and Geographic Information System (GIS) techniques, we comprehensively assess the physical, functional, and service vulnerabilities of the transportation network. Our analysis reveals that only 3.57% of the area is classified as highly resilient, demonstrating effective flood management capabilities. In contrast, a significant 61.73% of the area exhibits very low resilience, highlighting substantial vulnerabilities that could impact urban operations. Based on our findings, we propose specific strategies to enhance resilience, including optimizing drainage systems, upgrading infrastructure standards, implementing green infrastructure initiatives, and integrating disaster risk factors into urban planning. These strategies and insights provide valuable references for global cities facing similar climatic challenges.

Utilizing Landsat, Sentinel Image to Estimate Snow Cover Duration in Gara Mountain

The study area is considered a mountainous environment with climatic characteristics that suit the nature of this study. It is located in the northern part of the Kurdistan Region of Iraq, and it is part of a complex mountainous region according to the physiographic division of the surface of Iraq. On the other hand, it’s one of the most significant in terms of snow cover region in winter and spring season. No study has been done on this subject in the study area. In this study, Landsat data and geographic information system (GIS) techniques were used to analyze the duration of snow cover. After apply these technologies, snow cover duration maps (SCDM) for the duration (1989 – 1990) and (2022 – 2023) were extracted and analyzed. The maps show how long snow remains in each cell during these periods. This study suggested that there is an effect of terrain on snow cover duration, and this is due to the increase in air temperature.

Detection of mainland Kedah’s shoreline changes (2013-2020); a case study

Abstract Shoreline erosion and accretion are natural processes that involve the gradual change in the shape and position of coastlines due to the movement of water, sediment, and geological factors. These processes have significant implications for coastal environments, ecosystems, and human activities. Therefore, it is essential to frequently assess the shoreline changes for effective coastal management, sustainable development, and safeguarding valuable ecosystems. In the present study, shoreline condition along mainland Kedah (109 km) was investigated through remote sensing and geographical information system (GIS) techniques. The assessment was performed over the period of 7 years (2013 and 2020) by analysing the satellite images captured by Landsat-8 satellite Operational Land Imager (OLI) at 15 m resolution. Preprocessing was established by performing image geometric correction and registration. Next, the Support Vector Machines (SVMs) toolbox was used for image classification to define the water and non-water fields. Later, the shoreline was extracted from the classified images and overlaid in a geodetic base in ArcGIS software to detect shoreline changes. The results showed that the majority of mainland Kedah’s shoreline did not experience extensive erosion or accretion at which 54% of the shoreline (58.8 km) was found to be stable. Erosion was observed at 6 locations with a total length of 10.1 km (9% of the total shoreline length) which was mainly concentrated in the non-protected areas. On the other hand, shoreline accretion was observed at 19 locations with a total length of 40.1 km (37% of the total length). It is worth highlighting that the erosion areas were concentrated in the southern part of the coastline, while the accretion areas were distributed between the middle part and the north side of mainland Kedah’s shoreline.

STRATEGIES FOR WATERSHED MANAGEMENT AND PLANNING: A BIBLIOMETRIC ANALYSIS

In the twentieth century, governance approaches to watershed planning evolved in response to environmental challenges. The paper highlights the importance of watersheds and explores methodologies used in global watershed planning over the last decade, focusing on popular methods and their rationale. Through a systematic literature review of 10,154 publications, using ENDNOTE X9 for citation management (Bramer, 2018), and VOSviewer ver.1.6.18 software (Van Eck and Waltman, 2018) to prioritize publications, the study identified the most cited publications related to "Watershed", "Planning", and "Management". From these, publications aligning with study objectives underwent comprehensive review, totaling 270. Commonly used methods, such as "Integrated Watershed Management Planning" and geographic information systems techniques like morphometric indices, overlap weighting, and Analytic Hierarchy Process (AHP), emerged as prevalent findings.

Restoration of degraded waterlogged saline soil through subsurface drainage: Spatiotemporal soil salinity assessment using electromagnetic induction (EMI) and geographic information system (GIS) techniques

AbstractReduction in soil salinity in the entire project area is a key indicator of proper functioning of the implemented subsurface drainage (SSD) projects. Electromagnetic induction (EMI) surveys were carried out to facilitate spatiotemporal assessment of soil salinity of a SSD project site in Kahni, Haryana (India). The surveys were conducted in two time frames: immediately after the start of SSD project in 2019 and after 2 years of successful operation in 2021. The collected data of 2 surveys was used to derive a depth‐specific calibrated correlation between the observed salinity (ECe) of collected soil samples and surveyed apparent electrical conductivity (ECa) observations in vertical (ECav) and horizontal (ECah) modes. Spatiotemporal analysis of soil salinity revealed notable changes in areas under different salinity classes over a period of 2 years, indicating the impact of SSD on soil desalinization. During the course of 2 years (2019–2021) of SSD operation, area under moderate salinity (4–8 dS m−1) in the top 0–0.15 m soil increased by 54.5% while it decreased by 40% and 6.6% under high (8–12 dS m−1) and very high (12–16 dS m−1) salinity classes. The rice and wheat yields were also enhanced by 24% and 7% respectively after 2 years operation of SSD in hitherto severally waterlogged saline soils. Overall findings of this study reinforce the scope of using EMI approach to quickly and effectively assess the efficacy of subsurface drainage. Creation of measurable soil salinity maps by proposed EMI and GIS techniques can help in planning and implementing site‐specific management strategies in saline soil reclamation projects.

A GIS-based Approach to Spatially Explicit Mean Monthly Areal Rainfall Estimation of Krishna District, Andhra Pradesh, India

Rainfall analysis is pivotal for understanding hydrological systems, crucial for effective water resource management. In this study spatial rainfall analysis is carried out for Krishna District of Andhra Pradesh using ArcGIS software. Rainfall data for a period of 30 years (1992-2021) was collected from the Directorate of Economics and Statistics, Vijayawada, Andhra Pradesh. Utilizing the spatial interpolation techniques in Geographic Information System (GIS) software, mean monthly areal rainfall was found using the three methods viz., Arithmetic mean, Thiessen’s polygon and isohyet method. This study utilized Geographic Information Systems (GIS) to visualize spatial patterns of rainfall across Krishna district. To account for missing data in the rainfall record, the normal ratio method was implemented. Spatial maps were generated to depict mean monthly areal rainfall variations. The analysis yielded mean monthly areal rainfall for Krishna district as 84.72 mm, 85.22 mm and 83.97 mm using the arithmetic mean, Thiessen polygon and Isohyet methods, respectively. Isohyet method is considered to be more accurate and rainfall is the basic data required for all hydrological analysis as an input layer for runoff generation, water resources planning, evapotranspiration studies, crop planning, flood estimation and water budget estimations etc.

Mapping Longitudinal and Transverse Displacements of a Dam Crest Based on the Synergy of High-Precision Remote Sensing

Reservoirs are highly relevant infrastructure assets, and now, more than ever, they play an essential role in society’s welfare and national security. Their importance is related to regional socioeconomic development due to their capacity to store water for different uses, such as human consumption, agricultural irrigation, flood control, and hydroelectric energy production, among other important services. However, many reservoirs are reaching the end of their period of life, and others are showing undesired displacements and cracking. Four 3D surveys were conducted on a reservoir that serves the Metropolitan Area of Monterrey City in Mexico. These surveys were carried out over a period of 5 years using GNSS observation to assist in understanding the actual dam kinematics, i.e., the behavior of its longitudinal and transversal displacements and the possible correlation with the reservoir level. The high-precision leveling and close-range remote sensing data were assessed and then mapped. The high-precision geodetic and leveling techniques allowed us to locate and measure 84 established permanent control points with errors of about ± 0.003 m. The mapping of displacements was made possible by modeling the positive and negative translations. The highest uplifts (11 mm) occurred at the left riverbank, and the highest subsidences (−5 mm) occurred along the downstream piers from the middle of the dam crest to the right riverbank. A ground laser scanner (GLS) produced 3D digital models with geometrical and radiometric characteristics, detecting displacements among the dam crest elements. The synergy of GNSS and high-leveling techniques allows the possibility to measure displacements, while the use of geographical information system (GIS) and geomatic techniques allows a better visualization through 2D and 3D maps validated using traditional topographical methods.

Quantifying land change dynamics, resilience and feedback: A comparative analysis of the lake Chad basin in Africa and Aral Sea basin in Central Asia

The intricate interaction of natural and anthropogenic factors drives changes in land and water in response to societal demands and climate change. However, there has been insufficient information on the feedback effects in dryland hotspots altered by land change dynamics. This research compared two transboundary inland lakes, the Lake Chad basin (LCB) in Africa and the Aral Sea basin (ASB) in Central Asia, using remote sensing and geographic information system techniques to analyze and quantify present and future land cover dynamics, resilience, and their feedback effects. The study integrated Cellular Automata, Markov Chain, and Multilayer Perceptron models to predict LULC changes up to 2030. Descriptive statistics, ordinary least squares regression, hotspot Gi-Bin, trend analysis, and advanced geostatistical methods were utilized to identify relationships, patterns, magnitudes, and directions of observed changes in the feedback effects. From 2000 to 2030, the analysis unveils intriguing trends, including an increase in cropland from 48% to 51% and a decrease in shrubland from 18% to 15% in the LCB. The grassland increased from 21% to 22%, and the settlement expanded from 0.10 to 0.60% in the ASB. Water bodies remained stable at 1.60 % in LCB, while in ASB, it declined from 3% to 2%. These changes were significantly influenced by population, elevation, and temperature in both basins, with irrigation also playing a significant role in the ASB and slope in LCB. The study further revealed discernible shifts in normalized difference vegetation index, temperature, and precipitation linked to specific land cover conversions, suggesting alterations in surface properties and vegetation health. This study underscores the complex interplay between land cover dynamics, resilience, climate variability, and feedback mechanisms in LCB and ASB.

Estimate of the Surface Evaporation from the Tharthar Lake (Buhayrat Tharthar) in Iraq, Based on Remote Sensing Data and Techniques of Geographic Information Systems GIS

Tharthar is the largest water reservoir in Iraq. It is Giving the circumstances of drought and water crisis in Iraq, which is considered a semi-arid region, along with significantly feverish temperatures, especially in the summer. It is expected that evaporation rates will increase. Therefore, it was necessary to determine the water loss due to evaporation from Lake Tharthar. Due to the lack of ground measurement stations providing such data, the study relied on remote sensing data, specifically satellite imagery from Landsat 8 and Landsat 9. These images were used to extract temperature values for Lake Tharthar for the hydrological year extending from October 2022 to September 2023. This was done in conjunction with geographic information system (GIS) software and using ArcMap to calculate the annual evaporation rate and volume of the lake. Spatial modeling of evaporation was conducted for each month using the modified Lambert equation, adapted from the Penman-Cridle equation, which is most suitable for the climatic conditions of Iraq. Using this methodology saved time, effort, and cost, and yielded satisfactory results compared to field measurements of nearby water bodies. Temperature and evaporation rates were calculated at the level of each image pixel (30×30 meters). The research concluded many important findings, including that the total annual evaporation from the lake is estimated at 1881.16 millimeters (2.930 billion cubic meters per year). Accordingly, the annual loss per square kilometer from Lake Tharthar is estimated at 188 million cubic meters. This means that when Lake Tharthar reaches its maximum capacity, expanding the area to 2710 square kilometers, the evaporation loss will increase to 5.089 billion cubic meters per year. This necessitates relevant authorities to take necessary measures to reduce the annual evaporation loss from the lake surface. The study recommends adopting this method in cases where data is not available for locations lacking weather stations or when there is a data shortage.

Incorporating mitigation strategies in machine learning for landslide susceptibility prediction

This study proposes an approach that considers mitigation strategies in predicting landslide susceptibility through machine learning (ML) and geographic information system (GIS) techniques. ML models, such as random forest (RF), logistic regression (LR), and support vector classification (SVC) are incorporated into GIS to predict landslide susceptibilities in Hong Kong. To consider the effect of mitigation strategies on landslide susceptibility, non-landslide samples were produced in the upgraded area and added to randomly created samples to serve as ML models in training datasets. Two scenarios were created to compare and demonstrate the efficiency of the proposed approach; Scenario I does not considering landslide control while Scenario II considers mitigation strategies for landslide control. The largest landslide susceptibilities are 0.967 (from RF), followed by 0.936 (from LR) and 0.902 (from SVC) in Scenario II; in Scenario I, they are 0.986 (from RF), 0.955 (from LR) and 0.947 (from SVC). This proves that the ML models considering mitigation strategies can decrease the current landslide susceptibilities. The comparison between the different ML models shows that RF performed better than LR and SVC, and provides the best prediction of the spatial distribution of landslide susceptibilities.

Simulating Future Exposure to Coastal Urban Flooding Using a Neural Network–Markov Model

Urbanization and climate change are two major challenges of the 21st century, and the effects of climate change, combined with the urbanization of coastal areas, increase the frequency of coastal flooding and the area exposed to it, resulting in increased risk of flooding and larger numbers of people and properties being vulnerable. An urban growth modeling system was used to simulate future growth scenarios along the coast of the Vendée region in western France, and the potential exposure to flooding with each scenario was evaluated. The model used was an Artificial Neural Network combined with a Markov Chain, using data obtained by the remote sensing and geographic information system techniques to predict three future urban growth scenarios: business as usual, environmental protection, and strategic urban planning. High-risk flood areas and future sea level projections from the Sixth Assessment Report of the Intergovernmental Panel on Climate Change were then used to assess future flood risk under each growth scenario in the study area. According to the results, the different growth scenarios are associated with different development patterns, and the strategic urban planning scenario significantly reduces the risk of flooding compared to the other two scenarios. However, the rise in sea level considerably expands the areas vulnerable to flooding. Finally, the methodology adopted can be used to prepare for the impact of climate change and develop strategies to mitigate the risk of flooding in the future.

Integrating fuzzy-AHP and GIS for solid waste disposal site selection in Kenitra province, NW Morocco.

Selecting an optimal solid waste disposal site is one of the decisive waste management issues because unsuitable sites cause serious environmental and public health problems. In Kenitra province, northwest Morocco, sustainable disposal sites have become a major challenge due to rapid urbanization and population growth. In addition, the existing disposal sites are traditional and inappropriate. The objective of this study is to suggest potential suitable disposal sites using fuzzy logic and analytical hierarchy process (fuzzy-AHP) method integrated with geographic information system (GIS) techniques. For this purpose, thirteen factors affecting the selection process were involved. The results showed that 5% of the studied area is considered extremely suitable and scattered in the central-eastern parts, while 9% is considered almost unsuitable and distributed in the northern and southern parts. Thereafter, these results were validated using the area under the curve (AUC) of the receiver operating characteristics (ROC). The AUC found was 57.1%, which is a moderate prediction's accuracy because the existing sites used in the validation's process were randomly selected. These results can assist relevant authorities and stakeholders for setting new solid waste disposal sites in Kenitra province.

Spatio-temporal pattern analysis of coastal zone in Nansha based on remote sensing technology

Among the most important and active areas of coastal cities is the coastal zone. Examining the changes in the coastal zone of Nansha District is helpful in identifying the spatiotemporal evolution pattern and driving force of this area, as well as serving as a guide for the preservation and exploitation of its resources. This is due to the fact that remote sensing's ability to collect and analyze coastlines can show minute variations in the way the water and land interact. The article uses drone orthophotos and Landsat and Quickbird paired with eight different sceneries from 1987 to 2021 to extract the coastline using remote sensing (RS) and geographic information system (GIS) techniques. The spatiotemporal features of the evolution of the Nansha shoreline are examined in order to guarantee correctness. and the motivating elements are talked about. The findings indicate that: 1) Over the previous 30 years, there has been a consistent upward tendency along Nansha District's shoreline. Among these, the percentage of artificial shoreline is growing annually, growing by about 56%, while the natural coastline is decreasing annually, decreasing by 70%. 2) There is a shift in the type of shoreline from natural to sea-reclamation, engineering construction, and aquaculture. 3) The modifications to the coastline have occurred in three phases: the first was the agricultural phase; the second was the port petrochemical phase; and the third was the reasonable restraint phase (quality construction). Wanqingsha, Longxue Island, and Nansha Bay's coastlines are all close to significant expansion areas of coastline. 4) The primary causes of the changes in the Nansha District shoreline are human activity, regional policy, and natural elements.

GIS-based groundwater potential zonation and assessment of groundwater quality and suitability for drinking and irrigation purposes in the Shanmughanadhi river basin, south India

To develop a specific watershed scenario, the quantity and quality of groundwater resources must be assessed and monitored locally. In the present study, an attempt has been made to identify possible groundwater potential zones, determine the quality of groundwater resources in this region, and evaluate their suitability for drinking and irrigation purposes. This goal has been achieved with the combined use of the weighted index overlay analysis (WIOA), groundwater quality index (GWQI), Remote Sensing (RS), and Geographic Information System (GIS) techniques. The proposed study area, Shanmuganadhi, is marked with superior rainfall, oscillating temperature, and runoff with litho-units encompassing charnockite (CHK) and hornblende biotite gneiss (HBG). Over-abstraction of groundwater and intensive agricultural practices have resulted in declining and degrading water quantity and quality in this area. The resulting integrated thematic map has been classified into five groundwater potential zones, namely poor, low, moderate, high, and very high, covering 3.2, 45.49, 15.3, 27.9, and 8.1% area, respectively. Sixty groundwater samples were collected during the pre-monsoon (PRM) and analyzed for major Physico-chemical parameters. From the water quality index assessment, over 28.0% of the samples fall within the “excellent,” 8.0% “good” and 4.0% “poor” in CHK, followed by 5.71% “excellent,” 48.57% “good,” 37.14% “poor,” 5.71% “very poor” and 2.87% “unsuitable” for drinking purposes in HBG terrain of this region. Irrigation indices also demonstrated that most of the groundwater samples in the CHK and HBG exposed zones exhibited good classes for irrigation purposes, as evidenced by the SAR and %Na+. The outcome, which shows the research area's groundwater potential zones, is beneficial for improved groundwater resource planning and management. It is concluded that for larger-scale groundwater-quality investigation and assessment, the groundwater quality index-making approach (GWQI) is more practical and dependable. Water planners and decision-makers may find it helpful in effectively controlling and monitoring groundwater quality at the basin or watershed scale. Reducing urban land use and natural runoff from farms can help prevent water contamination in some regions. To ensure the safe use of groundwater, long-term monitoring of these groundwater was suggested.

Multi-Scale Analysis of Lyme Disease Ecology

Multi-Scale Analysis of Lyme Disease Ecology