scholarly journals A Comprehensive Review of Low Impact Development Models for Research, Conceptual, Preliminary and Detailed Design Applications

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1541 ◽  
Author(s):  
Sahereh Kaykhosravi ◽  
Usman Khan ◽  
Amaneh Jadidi
Keyword(s):  
Spatial Data ◽  
Spatial Scales ◽  
Low Impact Development ◽  
Model Development ◽  
Point Of View ◽  
Tree Canopy ◽  
Balance Model ◽  
Runoff Generation ◽  
Development Models ◽  
Model Features

This review compares and evaluates eleven Low Impact Development (LID) models on the basis of: (i) general model features including the model application, the temporal resolution, the spatial data visualization, the method of placing LID within catchments; (ii) hydrological modelling aspects including: the type of inbuilt LIDs, water balance model, runoff generation and infiltration; and (iii) hydraulic modelling methods with a focus on the flow routing method. Results show that despite the recent updates of existing LID models, several important features are still missing and need improvement. These features include the ability to model: multi-layer subsurface media, tree canopy and processes associated with vegetation, different spatial scales, snowmelt and runoff calculations. This review provides in-depth insight into existing LID models from a hydrological and hydraulic point of view, which will facilitate in selecting the best-suited model. Recommendations on further studies and LID model development are also presented.

scholarly journals Future large hydropower dams impact global freshwater megafauna

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Christiane Zarfl ◽  
Jürgen Berlekamp ◽  
Fengzhi He ◽  
Sonja C. Jähnig ◽  
William Darwall ◽  
...  
Keyword(s):  
Spatial Scales ◽  
Point Of View ◽  
Ecological Impacts ◽  
Climate Mitigation ◽  
Threat Status ◽  
Hydropower Dams ◽  
Balkan Region ◽  
America South ◽  
Freshwater Management ◽  
Major Attention

AbstractDam construction comes with severe social, economic and ecological impacts. From an ecological point of view, habitat types are altered and biodiversity is lost. Thus, to identify areas that deserve major attention for conservation, existing and planned locations for (hydropower) dams were overlapped, at global extent, with the contemporary distribution of freshwater megafauna species with consideration of their respective threat status. Hydropower development will disproportionately impact areas of high freshwater megafauna richness in South America, South and East Asia, and the Balkan region. Sub-catchments with a high share of threatened species are considered to be most vulnerable; these are located in Central America, Southeast Asia and in the regions of the Black and Caspian Sea. Based on this approach, planned dam locations are classified according to their potential impact on freshwater megafauna species at different spatial scales, attention to potential conflicts between climate mitigation and biodiversity conservation are highlighted, and priorities for freshwater management are recommended.

Mapping wildlife: integrating stakeholder knowledge with modelled patterns of deer abundance by using participatory GIS

2009 ◽  
Vol 36 (7) ◽  
pp. 553 ◽  
Author(s):  
Z. Austin ◽  
S. Cinderby ◽  
J. C. R. Smart ◽  
D. Raffaelli ◽  
P. C. L. White
Keyword(s):  
Community Involvement ◽  
Spatial Data ◽  
Spatial Scales ◽  
Stakeholder Participation ◽  
Landscape Scale ◽  
Scientific Data ◽  
Future Research ◽  
Economic Damage ◽  
Participatory Gis ◽  
Wild Deer

Context. Some species that are perceived by certain stakeholders as a valuable resource can also cause ecological or economic damage, leading to contrasting management objectives and subsequent conflict between stakeholder groups. There is increasing recognition that the integration of stakeholder knowledge with formal scientific data can enhance the information available for use in management. This is especially true where scientific understanding is incomplete, as is frequently the case for wide-ranging species, which can be difficult to monitor directly at the landscape scale. Aims. The aim of the research was to incorporate stakeholder knowledge with data derived from formal quantitative models to modify predictions of wildlife distribution and abundance, using wild deer in the UK as an example. Methods. We use selected predictor variables from a deer–vehicle collision model to estimate deer densities at the 10-km square level throughout the East of England. With these predictions as a baseline, we illustrate the use of participatory GIS as a methodological framework for enabling stakeholder participation in the refinement of landscape-scale deer abundance maps. Key results. Stakeholder participation resulted in modifications to modelled abundance patterns for all wild deer species present in the East of England, although the modifications were minor and there was a high degree of consistency among stakeholders in the adjustments made. For muntjac, roe and fallow deer, the majority of stakeholder changes represented an increase in density, suggesting that populations of these species are increasing in the region. Conclusions. Our results show that participatory GIS is a useful technique for enabling stakeholders to contribute to incomplete scientific knowledge, especially where up-to-date species distribution and abundance data are needed to inform wildlife research and management. Implications. The results of the present study will serve as a valuable information base for future research on deer management in the region. The flexibility of the approach makes it applicable to a range of species at different spatial scales and other wildlife conflict issues. These may include the management of invasive species or the conservation of threatened species, where accurate spatial data and enhanced community involvement are necessary in order to facilitate effective management.

scholarly journals Distributed snow and rock temperature modelling in steep rock walls using Alpine3D

2017 ◽  
Vol 11 (1) ◽  
pp. 585-607 ◽  
Author(s):  
Anna Haberkorn ◽  
Nander Wever ◽  
Martin Hoelzle ◽  
Marcia Phillips ◽  
Robert Kenner ◽  
...  
Keyword(s):  
Energy Balance ◽  
Snow Cover ◽  
Snow Depth ◽  
Spatial Scales ◽  
Swiss Alps ◽  
Balance Model ◽  
Near Surface ◽  
Surface Rock ◽  
Depth Data ◽  
Rock Temperature

Abstract. In this study we modelled the influence of the spatially and temporally heterogeneous snow cover on the surface energy balance and thus on rock temperatures in two rugged, steep rock walls on the Gemsstock ridge in the central Swiss Alps. The heterogeneous snow depth distribution in the rock walls was introduced to the distributed, process-based energy balance model Alpine3D with a precipitation scaling method based on snow depth data measured by terrestrial laser scanning. The influence of the snow cover on rock temperatures was investigated by comparing a snow-covered model scenario (precipitation input provided by precipitation scaling) with a snow-free (zero precipitation input) one. Model uncertainties are discussed and evaluated at both the point and spatial scales against 22 near-surface rock temperature measurements and high-resolution snow depth data from winter terrestrial laser scans.In the rough rock walls, the heterogeneously distributed snow cover was moderately well reproduced by Alpine3D with mean absolute errors ranging between 0.31 and 0.81 m. However, snow cover duration was reproduced well and, consequently, near-surface rock temperatures were modelled convincingly. Uncertainties in rock temperature modelling were found to be around 1.6 °C. Errors in snow cover modelling and hence in rock temperature simulations are explained by inadequate snow settlement due to linear precipitation scaling, missing lateral heat fluxes in the rock, and by errors caused by interpolation of shortwave radiation, wind and air temperature into the rock walls.Mean annual near-surface rock temperature increases were both measured and modelled in the steep rock walls as a consequence of a thick, long-lasting snow cover. Rock temperatures were 1.3–2.5 °C higher in the shaded and sunny rock walls, while comparing snow-covered to snow-free simulations. This helps to assess the potential error made in ground temperature modelling when neglecting snow in steep bedrock.

scholarly journals Olomouc - Possibilities of Geovisualization of the Historical City

2011 ◽  
Vol 6 ◽  
pp. 267-274
Author(s):  
Stanislav Popelka ◽  
Alžběta Brychtová
Keyword(s):  
Spatial Data ◽  
Large Scale ◽  
18Th Century ◽  
3D Visualization ◽  
3D Models ◽  
Google Earth ◽  
Point Of View ◽  
World Heritage Site ◽  
Historical Maps ◽  
The City

Olomouc, nowadays a city with 100,000 inhabitants, has always been considered as one of the most prominent Czech cities. It is a social and economical centre, which history started just about the 11th century. The present appearance of the city has its roots in the 18th century, when the city was almost razed to the ground after the Thirty years’ war and a great fire in 1709. After that, the city was rebuilt to a baroque military fortress against Prussia army. At the beginning of the 20th century the majority of the fortress was demolished. Character of the town is dominated by the large number of churches, burgher’s houses and other architecturally significant buildings, like a Holy Trinity Column, a UNESCO World Heritage Site. Aim of this project was to state the most suitable methods of visualization of spatial-temporal change in historical build-up area from the tourist’s point of view, and to design and evaluate possibilities of spatial data acquisition. There are many methods of 2D and 3D visualization which are suitable for depiction of historical and contemporary situation. In the article four approaches are discussed comparison of historical and recent pictures or photos, overlaying historical maps over the orthophoto, enhanced visualization of historical map in large scale using the third dimension and photorealistic 3D models of the same area in different ages. All mentioned methods were geolocalizated using the Google Earth environment and multimedia features were added to enhance the impression of perception. Possibilities of visualization, which were outlined above, were realized on a case study of the Olomouc city. As a source of historical data were used rapport plans of the bastion fortress from the 17th century. The accuracy of historical maps was confirmed by cartometric methods with use of the MapAnalyst software. Registration of the spatial-temporal changes information has a great potential in urban planning or realization of reconstruction and particularly in the propagation of the region and increasing the knowledge of citizens about the history of Olomouc.

scholarly journals Hotspot analysis: a first prototype Python plugin enabling exploratory spatial data analysis into QGIS

2016 ◽  
Author(s):  
Daniele Oxoli ◽  
Mayra A Zurbarán ◽  
Stanly Shaji ◽  
Arun K Muthusamy
Keyword(s):  
Data Analysis ◽  
Spatial Data ◽  
Point Of View ◽  
Geospatial Data ◽  
Spatial Data Analysis ◽  
Exploratory Spatial Data Analysis ◽  
Software Environment ◽  
Hotspot Analysis ◽  
Computational Procedures ◽  
Gis Software

The growing popularity of Free and Open Source (FOSS) GIS software is without doubts due to the possibility to build and customize geospatial applications to meet specific requirements for any users. From this point of view, QGIS is one of the most flexible as well as fashionable GIS software environment which enables users to develop powerful geospatial applications using Python. Exploiting this feature, we present here a first prototype plugin for QGIS dedicated to Hotspot analysis, one of the techniques included in the Exploratory Spatial Data Analysis (ESDA). These statistics aim to perform analysis of geospatial data when spatial autocorrelation is not neglectable and they are available inside different Python libraries, but still not integrated within the QGIS core functionalities. The main plugin features, including installation requirements and computational procedures, are described together with an example of the possible applications of the Hotspot analysis.

scholarly journals Application of a revised Water Poverty Index to target the water poor

2011 ◽  
Vol 63 (6) ◽  
pp. 1099-1110 ◽  
Author(s):  
R. Giné Garriga ◽  
A. Pérez Foguet
Keyword(s):  
Water Resources ◽  
Policy Making ◽  
Spatial Scales ◽  
Point Of View ◽  
Poverty Index ◽  
Index Construction ◽  
Policy Tool ◽  
Water Poverty Index ◽  
Decision Making Processes

The Water Poverty Index (WPI) has been recognized as a useful tool in policy analysis. The index integrates various physical, social and environmental aspects to enable more holistic assessment of water resources. However, soundness of this tool relies on two complementary aspects: (i) inadequate techniques employed in index construction would produce unreliable results, and (ii) poor dissemination of final outcome would reduce applicability of the index to influence policy-making. From a methodological point of view, a revised alternative to calculate the index was developed in a previous study. This paper is therefore concerned not with the method employed in index construction, but with how the composite can be applied to support decision-making processes. In particular, the paper examines different approaches to exploit the index as a policy tool. A number of alternatives to disseminate achieved results are presented. The implications of applying the composite at different spatial scales are highlighted. Turkana District, in Kenya has been selected as initial case study to test the applicability and validity of the index. The paper concludes that the WPI approach provides a relevant tool for guiding appropriate action and policy-making towards more equitable allocation of water resources.

Mapping arsenic vulnerability at different spatial scales using statistical and machine learning models 

2021 ◽  
Author(s):  
Sonal Bindal
Keyword(s):  
Spatial Resolution ◽  
Spatial Data ◽  
Fuzzy Inference ◽  
Spatial Scales ◽  
Fuzzy Model ◽  
Fuzzy Regression ◽  
Percentage Error ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Predictive Algorithms

<p>In the recent years, prediction modelling techniques have been widely used for modelling groundwater arsenic contamination. Determining the accuracy, performance and suitability of these different algorithms such as univariate regression (UR), fuzzy model, adaptive fuzzy regression (AFR), logistic regression (LR), adaptive neuro-fuzzy inference system (ANFIS), and hybrid random forest (HRF) models still remains a challenging task. The spatial data which are available at different scales with different cell sizes. In the current study we have tried to optimize the spatial resolution for best performance of the model selecting the best spatial resolution by testing various predictive algorithms. The model’s performance was evaluated based of the values of determination coefficient (R<sup>2</sup>), mean absolute percentage error (MAPE) and root mean square error (RMSE). The outcomes of the study indicate that using 100m × 100m spatial resolution gives best performance in most of the models. The results also state HRF model performs the best than the commonly used ANFIS and LR models.</p>

Identifying Potential Zones of Crime Commitment against Tourists in a Park: Conceptual and Logical Spatial Data Modeling

2014 ◽  
Vol 3 (9) ◽  
pp. 114-123
Author(s):  
Mozhdeh Shahbazi
Keyword(s):  
Spatial Data ◽  
Data Modeling ◽  
Research Topic ◽  
Point Of View ◽  
Complex Nature ◽  
Crime Mapping ◽  
Spatial Point ◽  
Suitability Maps ◽  
Gis Software

Location is considered as an important element in studying tourism security. Therefore, mapping crime hotspots has recently been an interesting research topic in tourism development. In order to identify crime patterns and hotspots, it is essential to create a database containing the required spatial data. It should also be integrated with additional qualitative/quantitative attributes affecting criminal actions. Designing a geographic information system (GIS) can be considered as the most efficient way to deal with this problem considering the complex nature of tourism security. This paper presents the theoretical scheme of spatial data modeling with the purpose of indentifying potential crime zones within a developed park. From the spatial point of view, the factors and the constraints, which make a location vulnerable, are defined. The entities are identified by their attributes and characterized by their relationships. Finally, the conceptual and the logical models to create the crime suitability maps are generated. The models provided in this paper are designed in an explicit way; therefore, they can be easily modified or generalized for any specific case study. The presented data modeling procedure can be applied to generate essential databases for crime mapping via any GIS software.

Thermal-Mechanical Effects and Near-Critical Fluid Dynamic Behaviors in Micro-Scale

2021 ◽  
pp. 55-111
Author(s):  
Lin Chen
Keyword(s):  
Fluid Dynamic ◽  
Spatial Scales ◽  
Small Time ◽  
Point Of View ◽  
Dynamic Responses ◽  
Chemical Extraction ◽  
Scaling Effects ◽  
Mechanical Process ◽  
Micro Scale ◽  
Leading Role

Supercritical CO2 fluid has been widely used in chemical extraction, chemical synthesis, micro-manufacturing, and heat transfer apparatus, and so forth. The current chapter deals with near-critical CO2 micro-scale thermal convective flow and the effects of thermal-mechanical process. When the scale becomes smaller, new, and detailed figures of near-critical thermal effects emerges. To explore this new area, theoretical developments and numerical investigations are discussed and explained in this chapter. From a theoretical point of view, the thermal-mechanical nature of near-critical fluid would play a leading role in small time and spatial scales. This effect is found dominant to the thermal dynamic responses and convective structures of micro-scale fluid behaviors. The scaling effects, boundary thermal-mechanical process, instability evolutions, mixing flows and characteristics, possible extensions, and applications are also discussed in this chapter.

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