Searching for useful non-systematic tree-ring data sources for flood hazard analysis using GIS tools

This report provides techniques and procedures for estimating the probable magnitude and frequency of floods at ungaged sites on Iowa streams. Physiographic characteristics were used to define the boundaries of five hydrologic regions. Regional regression equations that relate the size of the drainage area to flood magnitude are defined for estimating peak discharges having specified recurrence intervals of 2, 5, 10, 25, 50, and 100 years. Regional regression equations are applicable to sites on streams that have drainage areas ranging from 0.04-to 5,150 square miles provided that the streams are not affected significantly by regulation upstream from the sites and that the drainage areas upstream from the sites are not mostly urban areas.

A study was conducted that updated methods for estimating the magnitude and frequency of floods in ungaged urban basins in Georgia that are not substantially affected by regulation or tidal fluctuations. Annual peak-flow data for urban streams from September 2008 were analyzed for 50 streamgaging stations (streamgages) in Georgia and 6 streamgages on adjacent urban streams in Florida and South Carolina having 10 or more years of data. Flood-frequency estimates were computed for the 56 urban streamgages by fitting logarithms of annual peak flows for each streamgage to a Pearson Type III distribution. Additionally, basin characteristics for the streamgages were computed by using a geographical information system and computer algorithms. Regional regression analysis, using generalized least-squares regression, was used to develop a set of equations for estimating flows with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities for ungaged urban basins in Georgia. In addition to the 56 urban streamgages, 171 rural streamgages were included in the regression analysis to maintain continuity between flood estimates for urban and rural basins as the basin characteristics pertaining to urbanization approach zero. Because 21 of the rural streamgages have drainage areas less than 1 square mile, the set of equations developed for this study can also be used for estimating small ungaged rural streams in Georgia. Flood-frequency estimates and basin characteristics for 227 streamgages were combined to form the final database used in the regional regression analysis. Four hydrologic regions were developed for Georgia. The final equations are functions of drainage area and percentage of impervious area for three of the regions and drainage area, percentage of developed land, and mean basin slope for the fourth region. Average standard errors of prediction for these regression equations range from 20.0 to 74.5 percent.

The ongoing global population growth and the corresponding rise in energy demand have contributed to increased greenhouse gas (GHG) emissions. The integration of alternative, locally sourced energy solutions such as biogas presents a promising strategy to partially offset conventional energy consumption. In this context, countries like Colombia—characterized by a high availability of organic waste such as palm oil mill effluent (POME), rice straw, and pig manure—have the potential to harness these residues for biogas production. This study integrates experimental assays of anaerobic co-digestion tests with the spatial analysis of substrate distribution through GIS tools, enabling the identification of optimal regions for biogas production. Methane yields reached 412 mL CH4/g VS, comparable or superior to those reported in similar studies. In addition to laboratory assays, Geographic Information System (GIS) tools were used to generate a weighted heatmap index based on feedstock availability (POME, rice straw, pig manure) across 40 municipalities in Colombia. This integrated approach supports decentralized renewable energy planning and helps identify optimal locations for biogas plant development.

A geographical information system (GIS) was used to develop a regression model designed to predict flood magnitudes in the Sandy and Clackamas river basins in Oregon. Manual methods of data assembly, input, storage, manipulation and analysis traditionally used to estimate basin characteristics were replaced with automated techniques using GIS-based computer hardware and software components. Separate GIS data layers representing (1) stream gage locations, (2) drainage basin boundaries, (3) hydrography, (4) water bodies, (5) precipitation, (6) landuse/land cover, (7) elevation and (8) soils were created and stored in a GIS data base. Several GIS computer programs were written to automate the spatial analysis process needed in the estimation of basin characteristic values using the various GIS data layers. Twelve basin characteristic data parameters were computed and used as independent variables in the regression model. Streamflow data from 19 gaged sites in the Sandy and Clackamas basins were used in a log Pearson Type III analysis to define flood magnitudes at 2-, 5-, 10-, 25-, 50- and 100-year recurrence intervals. Flood magnitudes were used as dependent variables and regressed against different sets of basin characteristics (independent variables) to determine the most significant independent variables used to explain peak discharge. Drainage area, average annual precipitation and percent area above 5000 feet proved to be the most significant explanatory variables for defining peak discharge characteristics in the Sandy and Clackamas river basins. The study demonstrated that a GIS can be successfully applied in the development of basin characteristics for a flood frequency analysis and can achieve the same level of accuracy as manual methods. Use of GIS technology reduced the time and cost associated with manual methods and allowed for more in-depth development and calibration of the regression model. With the development of GIS data layers and the use of GIS-based computer programs to automate the calculation of explanatory variables, regression equations can be developed and applied more quickly and easily. GIS proved to be ideally suited for flood frequency modeling applications by providing advanced computerized techniques for spatial analysis and data base management.

The survey of extensive and topographically irregular landscapes is not easy. Survey teams often must be creative to cover the largest area possible, in a short time, with limited budgets, without losing quality and effectiveness in their work. The use of techniques employing geographic information system (GIS) tools has tremendously improved the efficiency and quality of the surveys. Such techniques were employed in the Jabal al‐Yamh and Ḥattā Valley (Emirate of Dubai, UAE), and their methodology, implementation and effectiveness are discussed in this paper. The Jabal al‐Yamh Research Project, which began in 2018 to survey, excavate, restore and research the prehistoric tombs in the Jabal al‐Yamh and the surrounding Ḥattā Valley, thus used primarily GIS tools employing remote sensing and probabilistic analysis to identify a large number of tombs in this rugged topography, delimitating areas more likely to contain tombs. On the other hand, identifying tomb distribution and orientation patterns through GIS data queries also allowed us to answer several sociocultural questions posed during the development of this project. This paper will thus discuss two primary purposes of this project's survey: methods for identifying new tombs for further excavation and protection, on the one hand, and the interpretation of those same tombs' emplacement, attending to their distribution and orientation pattern, on the other, thus developing a theoretical and predictive model of the distribution of prehistoric tombs in the area.

The rapid advances in Information and Communication Technologies (ICT) contribute to the creation of ‘Smart Cities'/‘Knowledge Precincts' that use data, information and technologies to enable innovative business models. This contributes to the nations' development. For smart cities/knowledge precincts to realize the planned social and economic impact; they have to be well-located and planned. Creating connections among cities also contributes to their smartness. This, calls for concepts of inter and intra smartness contributed in this chapter. The question is: a) how to locate the components of the smart city internally and b) how to locate the smart cities relative to each other and to their communities. Location problems are tackled with optimization and Geographic Information Systems (GIS) tools. This chapter starts by giving definitions on the topic and then presents a survey on the ‘Smart Cities'/‘Knowledge Precincts' location problems that use optimization and GIS tools and concludes with avenues for future research.

The rapid advances in Information and Communication Technologies (ICT) contribute to the creation of ‘Smart Cities'/‘Knowledge Precincts' that use data, information and technologies to enable innovative business models. This contributes to the nations' development. For smart cities/knowledge precincts to realize the planned social and economic impact; they have to be well-located and planned. Creating connections among cities also contributes to their smartness. This, calls for concepts of inter and intra smartness contributed in this chapter. The question is: a) how to locate the components of the smart city internally and b) how to locate the smart cities relative to each other and to their communities. Location problems are tackled with optimization and Geographic Information Systems (GIS) tools. This chapter starts by giving definitions on the topic and then presents a survey on the ‘Smart Cities'/‘Knowledge Precincts' location problems that use optimization and GIS tools and concludes with avenues for future research.

Geographic Information System (GIS) is a technology that deals with location to support better representations and decision making. It has a long tradition in several planning areas, such as urbanism, environment, riskiness, transportation, archeology or tourism. In academics context higher education has followed that evolution. Despite of their potentialities in education, GIS technologies at the elementary and secondary have been underused. Empowering graduates to learn with GIS and to manipulate spatial data can effectively facilitate the teaching of critical thinking. Likewise it has been recognized that GIS tools can be incorporated as an interdisciplinary pedagogical tool. Nevertheless more practical examples on how GIS tools can enhance teaching and learning process, namely to promote interdisciplinary approaches. The proposed paper presents some results obtained from the project “Each thing in its place: the science in time and space”. This project results from the effort of three professors of Geography, History and Natural Sciences in the context of Didactics of World Knowledge curricular unit to enhance interdisciplinarity through Geographic Information Technologies (GIT). Implemented during the last three years this action-research project developed the research practice using GIS to create an interdisciplinary attitude in the future primary education teachers. More than teaching GIS the authors were focused on teaching with GIS to create an integrated vision where spatial data representation linked the space, the time and natural sciences. Accumulated experience reveals that those technologies can motivate students to learn and facilitating teacher’s interdisciplinary work.

Geographic Information System (GIS) are now recognized broadly as a valuable tool for managing, analyzing and displaying large set of data relevant many local and regional planning and analyzing activities. The complex nature of Airport site suitability issues can be sorted it out using GIS tools. This research will discuss some potential of GIS application in site suitability analyzing considering factors that can affect to the Airports for entire Sri Lanka (considering forest area, tanks, airborne restricted area, and streams) and closer study for Polonnaruwa district, as there is a higher tourist attraction for historical and ancient cities. Anuradhapura and Polonnaruwa districts give considerable amount of contribution for that. Therefore Polonnaruwa district will be closely analyzed considering all the factors that will affect the selection of area for Airports. In this study, the factors considered, will lead to generate areas which are not suitable for local airports in Sri Lanka. Hence using Erase tool under GIS tool box overlay function erase all those areas as not suitable areas for local Airports. Rest can be defined as suitable areas for local airports. Also the buffering tool can be used to identify the most suitable areas by considering land use patterns, road and railway networks.

The rapid advances in Information and Communication Technologies (ICT) contribute to the creation of ‘Smart Cities'/‘Knowledge Precincts' that use data, information and technologies to enable innovative business models. This contributes to the nations' development. For smart cities/knowledge precincts to realize the planned social and economic impact; they have to be well-located and planned. Creating connections among cities also contributes to their smartness. This, calls for concepts of inter and intra smartness contributed in this chapter. The question is: a) how to locate the components of the smart city internally and b) how to locate the smart cities relative to each other and to their communities. Location problems are tackled with optimization and Geographic Information Systems (GIS) tools. This chapter starts by giving definitions on the topic and then presents a survey on the ‘Smart Cities'/‘Knowledge Precincts' location problems that use optimization and GIS tools and concludes with avenues for future research.

In recent years, the analysis of social vulnerability to floods became an integrated part of the flood risk management process, the strategies and policies developed focusing on risk reduction methods that increase the resilience of vulnerable communities. Therefore, reliable and robust social vulnerability approaches are needed, which is also highlighted by the increasing socio-economic growth and climate change related effects that can lead to unpredictable consequences. The use of vulnerability indices is the most widespread methodology that allows the identification of the most vulnerable communities and the understanding of the factors that increase vulnerability to floods. However, due to the lack of a standard procedure, the existing studies are often characterized by uncertainties related to subjective selection of indicators, lack of inclusion of all vulnerability dimensions, equal or subjective weighting methods, and reduced number of variables due to data unavailability. The present paper is addressing these gaps by developing a comprehensive methodology approach which: includes a large set of indicators that are selected considering the local socio-economic context, includes the hazard dimension in the analysis considering flood related variables, and applies objective weighting methods based on the Principal Component Analysis (PCA) method. Furthermore, flood vulnerability maps are developed using Geographic Information System (GIS) tools, to provide a rapid and easy way to identify highly vulnerable areas. The results showed that the integration of statistical methods and GIS tools in the social vulnerability index construction provides a better understanding of the factors that increase the social vulnerability and offers an overview of the mitigation and adaptation measures that must be implemented by authorities in order to improve the flood risk management.

Drought occurrence is influenced by a complex interplay of natural and anthropogenic factors, with human activities significantly shaping the frequency and severity of such events. Among these, land use change is a critical driver, as it alters the geographical and environmental characteristics that determine regional drought vulnerability. This study focuses on land use as a manageable and controllable factor in spatial development, with implications for minimizing the adverse impacts of human-induced environmental change. The research assesses the impact of land use transitions on drought vulnerability in the Lam Ta Kong watershed, emphasizing projected changes over the next decade. Drought vulnerability was evaluated using the Analytical Hierarchy Process, while future land use for 2032 was simulated using the Cellular Automata-Markov model, integrated with Geographic Information System tools. The projection was grounded in historical land use dynamics from 2000 to 2021, which revealed substantial shifts due to socio-economic growth. The transition was characterized by a decline in agricultural and forested land and a significant expansion of built-up areas. By 2032, urban areas are projected to expand by 33.11%, predominantly encroaching upon agricultural and forested lands. Current assessments indicate that 35.09% of the watershed is highly vulnerable to drought, with this figure anticipated to rise by 10.55% under future land use scenarios. High vulnerability zones are primarily concentrated in the midstream region of the watershed. These findings underscore the substantial influence of land use change on drought risk and highlight the urgent need to integrate land use planning into comprehensive drought mitigation strategies. Graphical Abstract This graphical abstract illustrates an assessment of the impacts of land use conversion on drought vulnerability in the Lam Ta Kong Watershed. The study employed spatial transition analysis using Geographic Information System (GIS) tools to identify historical land use change patterns. Building on this, the CA-Markov model was applied to project land use distribution for the year 2032. The projected scenario served as a basis for evaluating future drought vulnerability, integrating ten critical drought-related criteria, which are grouped into four factors, through the Analytical Hierarchy Process (AHP) within a GIS framework. This approach generated a spatially explicit drought vulnerability map, revealing that land use conversion substantially increases susceptibility to drought. The results underscore the urgent need for integrated land use planning and sustainable water resource management to mitigate escalating drought risks in the region.

The Oil Program Center at the U.S. Environmental Protection Agency (EPA) Headquarters is developing geographic information system (GIS) standards to aid EPA's 10 regions in developing and implementing GIS. GIS can support spill response, contingency planning, risk analysis, training and exercises, inspections and enforcement actions, reporting, incident analysis, cost recovery, and outreach. By developing and promoting standards, the Oil Program Center hopes to ensure that GIS development is targeted at the broadest practical user base and considers all aspects of EPA's oil program. In addition, GIS standards will promote consistency between EPA regions, promote data sharing, reduce duplication of effort, and focus attention on using GIS as an analytical tool rather than just as a mapping tool. The standards also may promote greater consistency between the Oil Program Center and other offices within EPA; for example, standards promote watershed-based analysis, which is consistent with other offices' use of watersheds as units of analysis. The standards address the following issues: Minimum essential data elements Data verification and accuracy standards Standard symbols and icons System design and data structure Because the specific needs of regions differ, the GIS tools that they develop will reflect these differences. GIS data standards, however, will promote compatibility across the regions to facilitate collaboration and expand prevention, preparedness, response, and outreach capabilities.

This study evaluates the suitability of Geographic Information Systems ( GIS ) for analysing Roman communication routes. We will use the Itinerarium Antonini Augusti Route XIX between Lucus Augusti and Asturica Augusta , as a case study. It questions the effectiveness of GIS in reconstructing historical road networks and proposes a methodology to address observed challenges. Applying this methodology reveals new issues and errors, highlighting limitations inherent in GIS tools and the available data. These findings emphasise the complexity of studying historical landscapes and the importance of integrating GIS with interdisciplinary methods. The research contributes to understanding Route XIX , while encouraging critical reflection on GIS ’s broader application in historical studies. Although GIS offers powerful spatial modelling and visualisation tools, its use for studying ancient roadways requires caution and methodological support. The study identifies its constraints as opportunities for refining GIS integration into historical landscape analysis and Roman route studies, fostering further research and critical evaluations.

The first step of a risk assessment analysis is the evaluation of flood-prone areas. Its importance is considered for both managing and planning emergency activities, such as hydraulic risk reduction management, and also town planning. Nowadays, using Geographic Information System (GIS) technology for risk assessment analysis is very common. However, it is not widely used for defining inundated areas. LiDAR data, such as digital elevation models (DEM), makes GIS numerical models attractive methods for obtaining a flooded area automatically. Using GIS tools is beneficial for effective processing and accuracy assessment in comparison to traditional methods which are based on topographic maps and field surveys. A first approach (Federici & Sguerso, Bollettino SIFET 4:25–42, 2007; Marzocchi, 2009) uses a GIS module in order to simulate perifluvial flood maps, having as prerequisites (i) the conformation of the river floodplain by a high-resolution DEM and (ii) a water surface profile along the river axis calculated for a given water discharge through a generic one-dimensional (1D) hydraulic model (HEC-RAS, Basement, MIKE 11, etc.). On the other hand, a second approach uses a GIS-embedded two-dimensional (2D) model in order to simulate flooded areas due to a dam break (Cannata & Marzocchi, Nat Hazards 61(3):1143–1159, 2012). This module solves the conservative form of the 2D shallow water equations (SWE) using a finite volume method (FVM). The intercell flux is computed by a one-side upwind conservative scheme extended to a 2D problem (Ying et al., J hydraul eng-ASCE 10:977–98, 2004). The newly developed GIS module gives as output maximum intensity maps which can be directly used in a risk assessment process. Both models have been implemented in geographic resources analysis support system (GRASS)-GIS software (Neteler et al., Environ Model Softw 31:124–130, 2012; GRASS, 2013) and two new commands (r.inund.fluv and r.damflood) have been created. Both are available on the official GRASS addons website and are distributed under the terms of the GNU General Public License (GPL). In this work we present a comparison between the two models mentioned above. We analyse the possibility of integrating these two approaches. We intend to use the 1D model, GIS embedded if possible, to calculate the water surface profile along the river axis and the 2D numerical one to analyse inundation beside the river levees.