Geographic Information System Model Research Articles

Searching for Situational Patterns in Cannabis Dealing, Possession and Use in a Scandinavian Context

Although cannabis is the most frequent illicit drug consumed in Sweden, little is known about the situations in which cannabis trade, possession and use occur. Following a recent strand of international research on the effect of recreational drugs on crime, this study uses a unique specially tailored database, Geographical Information Systems (GIS) and regression models, to investigate the situational conditions of cannabis offenses as they are detected in Stockholm, Sweden. Cannabis coincides with the location of drug markets initially delimited by the police but also extends over to locations far from the radar of the police, such as private residences (comfort places). Modeling results indicate that several land uses (convergent public places) have significant predictive value of the geography of cannabis offenses after controlling for other neighborhood characteristics. The article finishes by stating new research questions and making recommendations for practice.

Flood hazard potential evaluation using decision tree state-of-the-art models.

Floods occur frequently in Romania and throughout the world and are one of the most devastating natural disasters that impact people's lives. Therefore, in order to reduce the potential damages, an accurate identification of surfaces susceptible to flood phenomena is mandatory. In this regard, the quantitative calculation of flood susceptibility has become a very popular practice in the scientific research. With the development of modern computerized methods such as geographic information system and machine learning models, and as a result of the possibility of combining them, the determination of areas susceptible to floods has become increasingly accurate, and the algorithms used are increasingly varied. Some of the most used and highly accurate machine learning algorithms are the decision tree models. Therefore, in the present study focusing on flood susceptibility zonation mapping in the Trotus River basin, the following algorithms were applied: forest by penalizing attribute-weights of evidence (forest-PA-WOE), best first decision tree-WOE, alternating decision tree-WOE, and logistic regression-WOE. The best performant, characterized by a maximum accuracy of 0.981, proved to be forest-PA-WOE, whereas in terms of flood exposure, an area of over 16.22% of the Trotus basin is exposed to high and very high floods susceptibility. The performances applied models in the present work are higher than the models applied in the previous studies in the same study area. Moreover, it should be noted that the accuracy of the models is similar with the accuracies of the decision tree models achieved in the studies focused on other areas across the world. Therefore, we can state that the models applied in the present research can be successfully used in by the researchers in other case studies. The findings of this research may substantially map the flood risk areas and further aid watershed managers in limiting and remediating flood damage in the data-scarce regions. Moreover, the results of this study can be a very useful for the hazard management and planning authorities.

Inclusive Development Strategy Based on Regional Excellent Potential Mapping through Business Clusters in Supporting MSME Marketing Development: Penta Helix Approach

The MSME sector has become a pillar of the Magelang City economy with a contribution to the economy of 60%. The MSME sector in Magelang City is currently experiencing a decline due to two factors including the Covid-19 pandemic and the characteristics of the MSME business itself. Thus, it is necessary to map the potential of MSMEs based on business cluster-based superior potential so as to support the accelerated development of MSMEs in Magelang City, as well as encourage the creation of strategic policies in responding to shocks that occur in the economy quickly and purposefully. This study uses the Geographic Information System (GIS) model. This analysis discusses the characteristics of MSMEs in Magelang City. Structural Equation Modeling (SEM) is a multivariate technique that combines aspects of multiple regression (testing dependency relationships) and factor analysis (describing concepts that cannot be measured factors with multiple variables), and the Analytical Hierarchy Process (AHP) method arranges a priority as well as the purpose of the various options using several criteria. Based on the analysis result of marketing capabilities through social media and marketing performance directly have a significant influence on competitive advantage. Based on AHP analysis, the most prioritized criterion in developing the MSME marketing network in Magelang City is government policy.

Application of RMMF-Based GIS Model for Soil Erosion Assessment in Andaman Ecosystem

Water erosion is one of the major land degradation problems all over the globe, and its accurate quantification in different land use contexts is required in order to propose suitable conservation measures and curtail related hazards. In the Andaman and Nicobar (A&N) Islands, the land use changes due to faster urbanization and deforestation practices have led to accelerated erosion at many points around the inhabited Islands. Moreover, agricultural land uses in the A&N Islands are vulnerable to severe soil erosion, mainly due to cultivation practices along the steep slopes and mono-cropping culture. A study was conducted by establishing runoff plots in areas with different land uses to measure soil and nutrient losses and to estimate soil erosion using a semi-process-based soil erosion model, i.e., Revised Morgan Morgan and Finney (RMMF). The RMMF model was calibrated using primary data from runoff plots for the years 2019–21, validated for the year 2022, and applied in a Geographical Information System (GIS) to estimate soil erosion spatially over the Andaman ecosystem. The RMMF model simulated soil erosion during validation with a coefficient determination (R2) greater than 0.87 as compared to measured soil erosion from the runoff plots. The study revealed that annual N, P, and K losses of 41–81%, 42–95%, and 7–23%, respectively, due to runoff from various land uses. The land use land classification analysis of the Andaman Islands revealed that about 88% of the total geographical area is under the forest and mangrove land uses, which exhibited very slight soil erosion of <5 t/ha. This 88% of forest and mangrove areas requires suitable conservation measures such as afforestation and rehabilitation/restoration of mangroves. Moreover, 6% of cultivated areas need terracing, bunding, intercropping, etc., at the highest priority in order to conserve a sustainable Andaman ecosystem. On average, the annual soil loss from the Andaman Islands is 3.13 t/ha. About 6% of the study area exceeds the soil tolerance limit of 2.5–12.5 t/ha/year, which needs suitable soil and water conservation measures at the lowest priority due to economic implications.

Seascape Visual Characterization: Combining Viewing Geometry and Physical Features to Quantify the Perception of Seascape

The visual impacts of marine-based economic activities on seascape quality and its inherent value for different user groups are considered to be a highly contentious issue and difficult to quantify. In recent years, with the growth of the blue economy, the need to better understand the visual perceptions of seascapes has become essential when seeking societal support for new development. This article presents a unique method for assessing and quantifying seascape perception by characterizing a person viewing the geometry of seascape views both from the land and the sea. The method first utilizes a geographic information system (GIS) model to deconstruct the viewing geometry of a seascape view into five geometric elements, including (1) area of viewshed, (2) length of the visible coastline, (3) horizontal extent of the view, (4) vertical extent of the view, and (5) distance to the view. These geometric elements in the second step were reconstructed through an analytical hierarchical process (AHP) to determine the visual quality perception of participants. The results showed a significant improvement in the visual characterization of the seascape and its visual quality perception in comparison with conventional visual characterization methods. The findings indicate that the model promotes multiple perceptual perspectives by facilitating constructive discussions about social acceptance of the visual impact of a specific marine-based development.

Landfill Site Suitability Assessment Using Geographic Information System (GIS) and Analytic Hierarchy Process (AHP) in Butuan City, Philippines

Landfilling is one of the most effective and responsible ways to dispose of municipal solid waste (MSW). Identifying landfill sites, however, is a challenging and complex undertaking because it depends on social, environmental, technical, economic, and legal issues. This study aims to map the optimal sites that were environmentally suitable for locating a landfill site in Butuan City, Philippines. With reference to the policy requirements from DENR Section I, Landfill Site Identification Criteria and Screening Guidelines of National Solid Waste Management Commission, the integration of a Geographic Information System (GIS) model builder and Analytical Hierarchy Process (AHP) has been used in this study to address the aforementioned challenges related to the landfill site suitability analysis. Based on the generated sanitary landfill suitability map, results showed that Barangay Tungao (1131.42967 ha) and Florida (518.48 ha) were able to meet and consider the three (3) main components, namely economic, environmental, and physical criteria, and are highly suitable as landfill site locations in Butuan City. It is recommended that there will conduct a geotechnical evaluation, involving rigorous geological and hydrogeological assessment employing a combination of site investigation and laboratory techniques. In addition, additional specific social, ecological, climatic, and economic factors need to be considered (i.e. including impact on humans, flora, fauna, soil, water, air, climate, and landscape).

Deforestation patterns and stages of the Southern Amazon agricultural frontier

From 1980 to 2020, the Paciá River Drainage Basin (BHRP – Bacia Hidrográfica do Rio Paciá), located in the Southern Amazon agricultural frontier, underwent an accelerated process of change in human land use and occupation. This study aimed to identify and analyze deforestation patterns, relating them to landscape metrics and the stages of expansion of the agricultural frontier. The methodology was based on the following phases: 1) organizational structure of GIS (Geographic Information System) modeling; 2) mapping and classification of deforestation patterns; 3) mapping of the expansion stages of the agricultural frontier. Diffuse and geometric patterns represented 72.5% of the polygons analyzed, corresponding to 15.64% of deforestation. However, linear and consolidated patterns, which referred to 12.5% of the polygons, represented 65.5% of the deforested areas in the BHRP. The spatial arrangements of deforestation polygons are associated with two evolutionary stages of the Amazon agricultural frontier: permanent/consolidated, which is located along the Transamazon highway, and pioneer/diffuse, located along the banks of rural roads and the main course of the Paciá River.

Environmental risk assessment based on the allergenicity of urban green infrastructure: Case study of an urban park

It is essential to study the air quality of modern urban areas to improve the tolerance to health issues related to allergenicity in cities. The objective of this study was to develop a methodology for representing allergenicity by applying the Urban Green Zone Allergenicity Index (IUGZA) to urban environments and producing 3D maps. This study is based on an inventory of green infrastructure with information obtained through fieldwork and from accurate images of the actual conditions such as orthophotos and Light Detection and Ranging (LiDAR) clouds of points, which were used in the production of 3D maps. The inventory data were stored and georeferenced in a Geographic Information System (GIS) model, which was also used to extract geometrical information for the IUGZA index calculation. The allergenicity results from the index application are represented in the GIS model and exported to the Google Earth map system. The developed methodology was applied to a park (25 ha of surface) on the right margin of the Guadiana River in Badajoz (Spain). An IUGZA value of 0.093 was obtained for the inventory index calculation and 0.063 for the calculation method developed using GIS. Furthermore, two reduction-of-exposure simulations were performed to recalculate the IUGZA values, and successful results were obtained. The results showed that the proposed methodology provides an effective technique of representing potential allergenicity in 3D maps as an eco-design to reduce exposure to urban green infrastructure and to build a healthier environment in construction engineering.

Integrating GIS, Statistical, Hydrogeochemical Modeling and Graphical Approaches for Hydrogeochemical Evaluation of Ad-Dawadmi Ground Water, Saudi Arabia: Status and Implications of Evaporation and Rock–Water Interactions

Ensuring sustainability of groundwater (GW) resources requires understanding the interplaying factors in the hydrogeochemical evolution of the system (cause and effect relationships), which is the subject of the current work concerning the groundwater resource in a hyperarid region, namely, AdDawadmi, Saudi Arabia. Integration of geographical information system (GIS), statistical, graphical, and geochemical modeling approaches are adopted to achieve the study’s design intentions. Slicing the study area on a spatial basis helped yield insights into major constituents’ variation trends using the graphical methods that lack spatial representation capabilities, such as Piper, radial, and Durov plots. Localities of higher salinities, NO3−, SO42−, Cl−, Na+, and Ca2+ are remarkable, indicating the effects of localized and point source activities and evaporation-driven concentrating processes rather than lithology supported by the largest regression and correlation coefficients for Cl−, Na+, and SO42. Many interacting processes are identified: evaporation, vicious salinization cycle (VSC), rock weathering, ion exchange, and geomorphological-driven flow. Hydrogeochemical modeling using the Visual MINTEQ program concludes that concentration-driven evaporation might lead to the precipitation of significant SO42− and Ca2+ along with CaCO3 saturation. Such processes, coupled with the ion exchange, would greatly impact the GW chemical composition and affect the aquifer and soil properties such as permeability. Human activities impact the GW system, necessitating remediation plans and protection policies to prevent overexploitation and brook the VSC. Finally, the integration of the adopted approaches was found useful, constraining the findings of one approach, reducing the associated uncertainties, enhancing the confidence level and reliability of the obtained conclusions, and obtaining useful information, enabling understanding of the internally interacting processes otherwise hidden.

Abstract P3-04-02: Population level access to diagnostic mammography and ultrasound guided breast biopsy in Nigeria: a geospatial analysis

Abstract Introduction: Breast cancer is the most common cause of cancer-related mortality among women in Nigeria. Physical proximity to a diagnostic center is an important component of access, which has direct implication on the cost and timeliness of diagnosis and treatment. Beyond diagnostic mammography, ultrasound (US)-guided biopsy is an essential tool in the diagnostic pathway for suspicious lesions of the breast and is recommended by the Whole Health Organization Breast Health Global Initiative for LMICs. Unfortunately, there is a dearth of data on the population level access to mammography and US-guided breast biopsy in Nigeria and little is known about the geospatial inequities in access that targeted programming or investment could potentially address. This study undertook a comprehensive evaluation of breast imaging and diagnostic services in Nigeria and using a previously validated geographic information system (GIS) model, evaluated geospatial access to diagnostic mammography and US-guided breast biopsy in Nigeria. Methods: A comprehensive list of public and private facilities offering diagnostic mammography and/or US-guided breast biopsy was compiled using publicly available facility data from the Nigerian Ministry of Health, a survey administered to members of the Breast Imaging Society of Nigeria (BISON) as well as key stakeholder interviews from each of the countries six geopolitical zones. A novel survey was delivered to BISON members to identify additional/new facilities not captured by the latest Nigerian Ministry of Health data. Facility location, administration (public vs. private) and duration of service delivery were elicited from respondents and paired with the Ministry of Health facility dataset. Data on provider training and volume were also captured in the survey. All facilities were geolocated using Google Earth™ (Google, Mountain View, CA). A previously described cost-distance model, that uses open-source population density data to 100m2 (GeoData Institute) and road network data (OpenStreetMap) was used to estimate population level travel time to the nearest diagnostic center. Any portion of a route that included travel over terrain without roads was assigned a walking speed of 5 kmh-1. Geospatial access was calculated for mammography and US-guided biopsy separately and as well as by geopolitical zone. This study was approved by the research ethics board at Obafemi Awolowo University. Results: In addition to publicly available data from the Ministry of Health, facility and practice data was obtained from 63 Nigerian Radiologists from across the country. In total, 124 centers were identified that offer diagnostic mammography, of which 78 (63%) are privately administered. Nine of the countries 36 states did not have a center offering this service. Across the country, 33 centers offer US-guided breast biopsy, of which the majority (72.7%) are public. At a population level, 83.1% of the population has access within 120 minutes of continuous one-way travel to a center with diagnostic mammogram or US. At 240 minutes of continuous one-way travel, which corresponds to a full day of travel round-trip, 80.8% of the population has access to US-guided breast biopsy. However, there are differences in access between geopolitical zones. Just 68.7% of the population in the North East geopolitical zone has access to US-guided biopsy within a day’s travel (i.e. 240 minutes one-way). The remaining five geopolitical zones have population level access to this service of ≥80%. Conclusions: This is the first comprehensive evaluation of breast cancer imaging and diagnostic services in Nigeria. Our results, demonstrate that the majority of the population in Nigeria has reasonable geospatial access to basic breast cancer imaging services. However, there are inequalities in access between states and geopolitical zones in the north and south of the country, which may have an impact on timely diagnosis and care. Citation Format: Adeleye Omisore, Elizabeth J. Sutton, Gavin Tansley, Rachael Adeyanju AKINOLA, Gregory Knapp. Population level access to diagnostic mammography and ultrasound guided breast biopsy in Nigeria: a geospatial analysis [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-04-02.

Analysis of the Effects of Climate Change on Cotton Production in Maharashtra State of India Using Statistical Model and GIS Mapping

Cotton is a prominent cash crop cultivated for fiber, edible oil and oil cake. A global environmental issue, like climate change, alters weather parameters necessary for the healthy growth and development of cotton plants, affecting fiber quality and economic yield. The study aims to illustrate the evidence of climate change in Maharashtra and assess its impact on the production of cotton in this region. The study was conducted in the state of Maharashtra, India. Geographic information system (GIS)-based models were created based on the vector data (geopolitical boundaries of the state of Maharashtra and its districts) and the corresponding raster attributes (meteorological data) to examine the changes in the patterns of distribution of temperature, rainfall and severity of drought (Standardized Precipitation Index-SPI) over the study period (1990 to 2015). Further, a statistical multiple linear regression model was developed using district-wise data on yield and climatic parameters obtained from International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) to estimate the relationship between the dependent variable (yield of cotton) and the independent variables (annual rainfall and annual mean temperature). GIS modeling and mapping provide evidence of changes in the spatial distribution of rainfall and temperature. Although the regression analysis seems weak, it is acceptable for natural systems because natural systems are complex and often highly variable, making it difficult to create a perfect model. The multiple linear regression model shows that such changes in climatic parameters have a significant negative impact on the economic yield of cotton.

Delineation of Ground Water Potential Zoning Using GIS and Remote Sensing by AHP of Sunsari District (Koshi Basin) Area of Nepal

This study assesses the groundwater potential in Sunsari district of Nepal by using a multi-criteria decision analysis tool along with remote sensing and geographic information system (GIS).The study has taken precipitation, Land use/cover (LULC), slope, geology, drainage density, lineament density, soil, and canal density as key influencing factors for determining the groundwater potential of the study area. The Analytical Hierarchical Process (AHP) technique was adopted in deriving the relative weights of these criteria and sub-criteria based on a review of the literature according to their relative importance in recharging the groundwater. The final thematic map of groundwater potential zones was prepared based on a groundwater potential index computed by aggregating the selected thematic layer with appropriate weights. The groundwater potential zones are classified into three zones based on the score of the groundwater potential index. The generated groundwater potential zones were further validated with ground truth data using a confusion matrix with a kappa coefficient and analysis of the receiver operating curve (ROC). The validation indicated fair predictability of groundwater potential zone with the AHP and GIS model. The areas under “Poor”, “Moderate” and “Good” are 13.6%, 36.0%, and 50.4% of the study area, respectively. The areas under the “Good” potential category are concentrated in the lower southern and western parts of the study area, while the east central part with highly dense built-up area falls under the “Poor” potential category. Also, the area just north of the central part is under the “Moderate” zone. There is a good coherence of precipitation and LULC with groundwater potential zones and less coherence of other factors.

Spatiotemporal change analysis of land use/land cover in NCT of Delhi, India using geospatial technology

Increasing anthropological and economic activity has transformed human–environment connections. Using remote sensing and geographic information system (GIS), severe issues connected to rapid growth, such as supplemental infrastructure, informal residents, demolition of ecological construction, shortage of natural resources, and environmental contamination, have been studied for a fast-growing metropolis like Delhi. Industrialization accelerates urbanization, resulting in land transformations, which are one of the major uses of natural resources. In a fast-growing city like Delhi, the development has been rapid, and it is important to investigate the factors behind these shifts. For the present study, remote sensing and GIS models are used for land use and land cover (LULC) change detection. The applied model in the study uses the satellite datasets of two different satellites, i.e., Landsat 5 (TM) of 2010 and Landsat 8 (OLI) of 2021, from November with little or no cloud cover, which could block the LULC features. The study compares the temporal LULC map and analyzes the change and increase in urbanization for two periods, 2010 and 2021. In the study, it is revealed that urbanization causes constant shifts in vegetation, built-up area ratio, and land-use patterns. To confirm the same, indices like the normalized difference vegetation index and the normalized difference building index are also studied. Inequitable land use is a major contributor to environmental degradation. The spatial datasets from two time periods used in the study and the database results are helpful in extensive LULC investigations, land use planning, spatial growth, and urbanization patterns in the NCT of Delhi. Further, the change detection model used in the study was supported by the standard accuracy assessment of the Kappa coefficient. Overall accuracy in 2010 was 89.52% with a Kappa statistic of 0.863 and 89.92% with a Kappa statistic of 0.868 in 2021. Such studies using remote sensing and GIS are extremely helpful in understanding and monitoring urban sprawl patterns.

Geographic information systems applications in India's public health are we moving towards the right direction?

Governments worldwide focus particularly on digital healthcare sensors for leveraging data and technology like Geographic Information Systems (GIS) to improve governance and service delivery. Geoinformatics technology can help with epidemiological research and outbreak response, minimizing the health consequences in communities beforehand, during, and then after epidemic episodes. We can all agree that location and time play a crucial role in carrying out an efficient public health response. Since location information is essential for every stage of planning, response, and recovery, GIS helps the location-based support of public health preparedness programmes like support for decisions, resource allocation, communication and collaboration, and civic participation. GIS scales to situations ranging from adverse weather to pandemics. Public health professionals can coordinate their efforts with those of other organizations and external stakeholders due to maps and apps. The public health preparedness community may achieve significant strides by incorporating GIS data, models, communication and engagement centres, and location-centric apps. GIS technology can help with this efficient method for gathering data, performing analysis, where they are most needed, interacting with decision-makers, and finally achieving health equity can be created with the aid of a location-based strategy. During COVID-19, this reality was disseminated more extensively through the news media and the national, state, and local governments. This paper evaluates the application of GIS in the Indian public health system and the various aspects of public health where GIS may emerge as a game-changer for future policy decisions.

Identification of small-scale hydropower potential sites using geographic information system and hydrologic modeling technique: Awata river, Genale Dawa basin, Ethiopia

Small-scale hydropower is a significant source of renewable and inexpensive energy. This study was carried out to identify suitable potential sites for small-scale hydropower for the generation of electricity along the Awata River in Ethiopia. Primary and secondary data collected from various sources were used in the present study to achieve its objective. After the consistency of rainfall was checked and areal rainfall was estimated using the Theissen polygon method, the rainfall–runoff​ relationship was simulated using HEC-HMS. The head of each identified site was estimated by using GIS to overlay the DEM and stream network starting at the outlet. To estimate the discharge, the flow duration curve was developed. HEC-HMS performance was evaluated using Nash–Sutcliffe efficiency (NSE), Mean Absolute Error (MAE), Percent Bias (PBIAS), and coefficient of determination (R2). During calibration, the values were 0.82, 4.39, −2.93, and 0.83, and during validation, the values were 0.76, 5.35, 6.25, and 0.76. The identified sites were ranked using an analytical hierarchy process based on a ratio of five criteria. There are twenty-eight sites identified, with estimated power output and energy output of 45.26 MW and 198.79 GWh at 50% and 6.74 MW and 53.23 GWh at 90%, respectively. The overall rank indicated that the selected site code 29 is ranked first and can be used for the implementation of a small hydropower plant. As a result, the design of all the components of small hydropower plants will be required to implement and generate energy for rural areas in future development.

Modeling on Urban Land Use Characteristics and Urban System of the Traditional Chinese Era (1930s) Based on the Historical Military Topographic Map

The quantitative urban system structure in historical periods and the long time-scale urban land area grid dataset with spatial attributes are important for land use and land cover change (LUCC) research. In this study, we aimed to measure the area of county level and above cities in mainland China in the 1930s, also known as the traditional Chinese era (TCE), using a geographic information system (GIS) model and 1:50,000 military topographic maps. Furthermore, we aimed to identify the structure and characteristics of the urban system in the TCE according to the administrative area division using methods such as the rank size law. The results of this study revealed that 1265 county level and above cities existed in the TCE, including 25 provincial level or above cities, 179 prefectural level cities, and 1061 county level cities. The total land area of all of the cities was 1396.48 km2, with a mean value of 1.1 km2 and a standard deviation of 2.37 km2. The rank-size analysis indicated that the urban system in TCE was characterized by large cities with insignificant development (q = 0.829 < 1, R2 = 0.905). The results of the Lorenz curve and Moran analyses showed that the spatial distribution of the urban systems in China during the traditional period exhibited nonuniform agglomeration. Large-scale military topographic maps of historical periods have proven to be a good source for land use reconstruction. The 1° × 1° grid urban land area dataset constructed based on a GIS model in the TCE is important for future research on historical LUCC and can provide basic data for climate change models, urban economic history, and other disciplines.

Sensitivity Analysis of Parameters of U-Net Model for Semantic Segmentation of Silt Storage Dams from Remote Sensing Images

Building silt storage dams is an important measure to control soil erosion. Sensitivity analysis of the parameters in a deep learning model is the premise of extracting high-precision silt storage dams from high-resolution remote sensing (RS) images. In this study, watershed features of Hulu River and Lanni River in the Loess Plateau, China, are extracted using a geographic information system and digital elevation model. The detection of silt storage dams using the U-Net model considered three high-resolution RS image datasets to evaluate the effect of different input sizes, batch sizes, and sample sizes on accuracies of silt storage dams. The results show that a large input size, batch size, and sample size can improve the accuracy of silt storage dams extracted by U-Net. U-Net with Dataset 3, input size of 576 × 576, and batch size of 4 achieved an overall accuracy of 96.26%, F1 score of 70.61%, mean intersection over union of 75.33%, training time of 485 ms/step, minimum noises and shadow, and clear outlines of silt storage dams. This study provides theoretical and practical decision-making for the planning, construction, and maintenance of silt storage dams, as well as ecological protection and high-quality development of the Yellow River Basin.

Зонирование малых городов Иркутской области по степени опасности затопления

Methods of flooding zones identification using as satellite space images as digital elevation model in the QGIS geographic information system are considered. It has been determined that the digital elevation model is most effective method. It allows to more accurately identify the flooding zone boundary according to the elevation marks of the highest water level at the hydrological station. For studying the floods risk the small towns in the Angara River basin in Irkutsk region were selected (Tulun, Nizhneudinsk and Biryusinsk), which located on the floodplain areas of the Iya, Uda and Biryusa Rivers. Biryusinsk is subject to less flooding and consequences due to the location of the town on elevated areas of the right-bank terraces of the Biryusa River valley. Zoning of “Tulun town”, “Nizhneudinsk town” and “Biryusinsk town” according to the flood risk degree was carried out. According to relief elevation marks the four zones have been defined for each territory, which characterized by different degrees of flooding hazard (high hazard, medium hazard, low hazard and no hazard zone). An analysis of the main causes, as well as the structure of the flood zone during the catastrophic rain flood of 2019 in the cities of Tulun and Nizhneudinsk was carried out. He showed that, along with hydroclimatic factors (intense and abundant rainfall, high previous moisture content of watersheds), a significant role in the formation of great damage from floods was played by high population, economic development and development features of flooding areas of the Iya and Uda river valleys. The floods damage in Biryusinsk is less, despite the frequent observation of water levels above the critical level due to the city location on elevated area of the right-bank terraces of the Biryusa river.

Mercury pollution in the soil and river water of the Ratai watershed by artisanal and small-scale gold mining activities in Pesawaran District, Lampung, Indonesia

<p>The high risk of mercury pollution in the Ratai watershed due to artisanal and small-scale gold mine activities in Pesawaran District, Lampung, Indonesia, was evaluated. Studies are needed to improve the understanding of the effect of heavy metal pollution, especially mercury (Hg), in soil and river water along the watershed because of erosion. The Universal Soil Loss Equation (USLE) integrated with Geographic Information Systems (GIS) model was used to analyze the transport of mercury (Hg) from nonpoint source pollution loads to the Way Ratai River using rainfall-based erosion. Soils and river water samplings were conducted in 2020. Biophysical conditions, the land cover, and the rainfall data of the Ratai watershed were also taken into account. The results indicated that Hg concentrations in the soil and the river water were high, ranging from 0.26-28.9 mg L<sup>-1</sup> and from 0.08-14.1 mg L<sup>-1</sup>, respectively. The reason for the high Hg contents in the soils and the river waters was the high erosion rate in the watershed. As the study area was characterized by high rainfall erosivity and low to high soil erodibility, the erosion-caused Hg contamination in soil and water can be significant if no conservation strategies are developed.</p>

Calibration and Validation of CN Values for Watershed Hydrological Response

The amount of rainfall can be used to estimate the runoff that enters a reservoir. Runoff is influenced by land use, and soil type greatly affects the amount of runoff that will occur. This study discusses the development of a hydrological model with the application of the Hydrologic Engineering Center (HEC-HMS) in the Karangmumus watershed using soil data that has been verified in the field and divided into soil zones based on soil permeability testing in the laboratory. With the help of Geographic Information System (GIS) and Geospatial Hydrological Model (HEC-GeoHMS) applications, it is possible to identify the flow of the Karangmumus watershed and the Lempake Dam in Kalimantan by simulating the rain runoff process. The hydrological model was developed in the HEC-HMS by recording daily rainfall events from 2009 to 2019. With a daily period, then, the zoning soil type data was entered based on the results of soil permeability testing with the help of the application of the soil conservation curve method (SCS-CN), then discharge transformation, and calculation of water loss, including routing with Muskingum and SCS-Hydrograph applications. Based on the distribution of the CN value, the theoretical runoff is calculated and then calibrated with the observed discharge in 2017 and 2018, and then validated with the observed discharge in 2019, showing good results with a coefficient of determination between 0.89 to 0.92. Doi: 10.28991/CEJ-2023-09-01-06 Full Text: PDF