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The rapid and ongoing expansion of urbanised impervious areas could lead to more frequent flood inundation in urban flood-prone regions. Nowadays, urban flood inundation induced by rainstorm is an expensive natural disaster in many countries. In order to reduce the flooding risk, eco-roof systems (or green roof systems) could be considered as an effective mechanism of mitigating flooding disasters through their rainwater retention capability. However, there is still a lack of examining the stormwater management tool. The purpose of this paper is to evaluate the effects on flooding disaster from extensive green roofs.

Based on geographical information system (GIS) simulation, this research presents a frame of assessing eco-roof impacts on urban flash floods. The approach addresses both urban rainfall-runoff and underground hydrologic models for traditional impervious and green roofs. Deakin University’s Geelong Waurn Ponds campus is chosen as a study case. GIS technologies are then utilised to visualise and analyse the effects on flood inundation from surface properties of building roofs.

The results reveal that the eco-roof systems generate varying degrees of mitigation of urban flood inundation with different return period storms.

Although the eco-roof technology is considered as an effective stormwater management tool, it is not commonly adopted and examined in urban floods. This study will bring benefits to urban planners for raising awareness of hazard impacts and to construction technicians for considering disaster mitigation via roof technologies. The approach proposed here could be used for the disaster mitigation in future urban planning.

This study aims to use porous concrete and mineral adsorbents (additives) for reducing the quantity and improving the quality of urban runoff.

The effects of adding mineral adsorbents and fine grains to porous concrete is tested for increasing its performance in improving the quality of urban runoff. Two levels of sand (10 and 20 per cent) and 5, 10 and 15 per cent of zeolite, perlite, LECA and pumice were added to the porous concrete. Unconfined compressive strength, hydraulic conductivity (permeability) and porosity of the porous concrete specimens were measured. Some of the best specimens were selected for testing the improvement of runoff quality. A rainfall simulator was designed and the quality of the runoff was investigated for changes in electrical conductivity (EC), total suspended solids (TSS), total dissolved solids (TDS) and chemical oxygen demand (COD).

The results of this study showed that compressive strength of the porous concrete was increased by adding fine grains to the concrete mixture. Fine grains decreased the permeability and porosity of the samples. Zeolite had the highest compressive strength. Samples having pumice own maximum permeability. Samples which had perlite, had the least compressive strength and permeability. Because of the fast flow of runoff water in the porous slab and its low thickness, sufficient time was not provided for effective functioning of the additives, and the removal percentage of the pollution parameters was low.

Porous concrete can ameliorate both quantity and quality of the urban runoff.

Golestan province in the northern part of Iran has been affected by devastating floods. There has been a significant change in the pattern of rainfall in Golestan province based on an analysis of the seven heaviest rainfall events in recent decades. Climate change appears to be a significant contributing factor to destructive floods. Thus, this paper aims to assess the susceptibility of this area to flash floods in case of heavy downpours.

This paper uses a variety of computational approaches. Following the collection of data, spatial analyses have been conducted and validated. The layers of information are then weighted, and a final risk map is created. Fuzzy analytical hierarchy process, geographic information system and frequency ratio have been used for data analysis. In the final step, a flood risk map is prepared and discussed.

Due to the complex interaction between thermal fluctuations and precipitation, the situation in the area is further complicated by climate change and the variations in its patterns and intensities. According to the study results, coastal areas of the Caspian Sea, the Gorganrood Basin and the southern regions of the province are predicted to experience flash floods in the future. The research criteria are generalizable and can be used for decision-making in areas exposed to flash flood risk.

The unique feature of this paper is that it evaluates flash flood risks and predicts flood-prone areas in the northern part of Iran. Furthermore, some interventions (e.g. remapping land use and urban zoning) are provided based on the socioeconomic characteristics of the region to reduce flood risk. Based on the generated risk map, a practical suggestion would be to install and operate an integrated rapid flood warning system in high-risk zones.

An efficient and adequate environmental monitoring plan is essential to any integrated coastal zone management (ICZM) program. The purpose of this paper is to apply an environmental diagnostic study to a coastal lagoon using anthropogenic markers as a decision support tool to aid the development of coastal environmental management policies.

Specifically, environmental status and anthropogenic sources were determined as part of a coastal environmental management plan; a study of human occupation and use was conducted to determine the predominant human activities around the lagoon; an environmental diagnostic study was conducted to determine the occurrence, levels and distribution of markers; and the results of the environmental diagnostic study were compared to indicators stipulated in Brazilian legislation.

Land use study revealed both urban and rural activities around the lagoon, as evidenced by the existence of residences, restaurants as well as poultry and livestock activities. The environmental diagnostic study revealed the input of human sewage (treated and raw) and runoff from animal husbandry activities.

The information produced using anthropogenic markers showed the influence of less studied rural activities, such as livestock and poultry farming, thereby providing a more reliable environmental status compared to the use of classic indicators employed in laws issued by international and Brazilian agencies.

The present results show that classic indicators used by environmental agencies are insufficient for an accurate diagnosis of coastal zones with multiple anthropogenic activities. Thus, the modernization of the environmental monitoring plan of the ICZM program is urgently needed for a more accurate assessment of coastal environments.

The primary objective of this study is to develop a predictive model that will predict the swimmability of certain areas of a brackish water body (Lake Pontchartrain) based on physicochemical and meteorological conditions.

Samples were collected and analyzed for bacteria indicator organisms at 13 sites along and adjacent to Lincoln Beach for four years. Physicochemical parameters and meteorological data were also recorded. A logistic regression model and an artificial neural networks (ANNs) model were both used to predict whether a lake condition is “safe to swim” or “not safe to swim”, given only physicochemical and meteorological parameters.

Both models predicted very well the results observed when lake conditions were “safe to swim” (97.7 percent of time the statistical model predicted correctly and an average >99.5 percent of the time for the ANNs model). However, for conditions under which the lake water quality was “not safe to swim”, the statistical model predicted correctly only 5.6 percent of the time. The ANNs model successfully predicted the “not safe to swim” conditions for an average 98.5 percent of the time. However, this percentage decreases to 53.9 percent when ANNs is used for forecasting “not safe to swim” conditions.

The poorer performance of both models for “not safe to swim” conditions is probably due to the fact that most data (84.5 percent) were collected during “safe to swim” conditions. The limited database for “not safe to swim” conditions resulted in a poorer forecasting success rate.

The ANNs model might serve as a useful tool for public beach management with increased data on “not safe to swim” conditions.

The purpose of this paper is to build a support vector machine (SVM) model to evaluate the city air quality level, using the three main air pollutants selected as evaluation index.

PM₁₀, SO₂, NO₂ are the most important three air pollutants and their concentration data are selected as the influencing factor. And the SVM model is build and used to evaluate the air quality level of 29 major cities in China 2011. The cross-validation is adopted to select optimal penalty parameters and optimal kernel function, and the classification accuracies achieved under different normalization methods and kernel functions are compared in the end.

The study found, the parameters and kernel functions chosen by the SVM model have influence on the model's prediction accuracy. Through continuous optimization of model parameters, finally it is found that the model performs better with [0, 1] normalization method and RBF kernel function. It proves that SVM classification model is effective in dealing with the problem of city air quality evaluation.

The result of this study shows that the SVM classification model can be well applied to predict the city air quality level by using air pollutants concentration data as evaluation index. It can help the government and relevant department issue corresponding environmental policy and environmental protection measures.

The qualitative and quantitative study method are combined in this paper, on the basis of predecessors’ research results, as well as careful analysis to select evaluation index. The SVM classification model build is simulated by using Matlab technique, beyond comparing the accuracy, its outcomes and its efficiency in classification are demonstrated.

The purpose of this paper is to examine the role of high intensity precipitation events in increasing the vulnerability to floods in Mediterranean Spain. Precipitation intensity in this area appears to have augmented in the last two decades in association with warming trends of the Mediterranean Sea. At the same time, intense urbanization processes, occupying and transforming flood prone land, have produced an important increase in exposure. The main objective is to assess whether higher intensity precipitation and changing patterns in exposure aggravate vulnerability to floods.

In this paper, vulnerability is understood as the result of the interrelationships between exposure, sensitivity, impacts and adaptive capacity. Consequently, methods used involved the compilation and analysis of published and unpublished precipitation data, population and land use data, data on insurance claims, and media sources related to those variables.

Changes toward episodes of more intense precipitation in the expanding urban areas of Mediterranean Spain increase exposure but not necessarily vulnerability, at least in terms of human deaths. However, adaptative capacity needs to be formulated. Actions that attempt to absorb and eventually reuse flood flows (as the flood park in Alicante) appear to be more effective than traditional hydraulic solutions (as in Majorca).

The paper provides a systematic and coherent approach to vulnerability analysis taking into account the changing dynamics of its components. Especially, it signals the limits of current adaptive approaches to flooding and advocates for changes toward a more circular and less linear approach to urban drainage.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

The purpose is to study the possible environmental impact from a supercenter construction on a 313,643‐m² land by the Bayou Bartholomew.

The sources of information were field work, flood maps, flood models, 100 years of rainfall data, soil quality, water infiltration rate, and traffic flows in the areas around the supercenter. Rainfall data were used to find the frequency of flashfloods under different flood models. The supercenter center obstructs the virgin drainage of water down the bayou. Bernoulli's equation was used to estimate delays in the flashflood drainage following the constricted flow after the construction of the supercenter. Overloads of traffic flows on selected city roads in the event of submergence of the main road were studied.

A total of eight major flashfloods per century occur. Bernoulli's theorem predicts flooding over wider areas and of longer duration. About 32,248 m³ of recharging of groundwater will be affected. Traffic loads will increase by about three times on the state highway 15 beside the supercenter. Rain‐drained automobile engine oil drips will cause bayou's water quality to deteriorate.

Prediction needs to be checked during flashfloods occurrences. Water quality in the bayou upstream and downstream of the supercenter needs to be monitored.

Policy makers in the city government and urban development will benefit from the findings.

The paper upholds the multifarious environmental problems and as such it is of interest to urban planners, farmers, water quality monitors, groundwater hydrologists, and businessmen who would like to serve the community.

The prediction of soil erosion by the action of water has been based largely on the universal soil loss equation and its variations, derived from data collected from agricultural land in the USA. Open pit mining creates waste rock or spoil dumps at the angle of repose of the material (typically 35° to 40°). Even after regrading these slopes, relatively steep slope angles will remain, typically steeper than 6° to 8°. Topsoiling is generally required to facilitate revegetation, but bare topsoil is particularly prone to erosion. Mine slopes are therefore quite unlike the agricultural slopes on which the predictive tools for erosion by water were based. The paper discusses the prediction of erosion from steep mine waste slopes in the light of some erosion data collected from laboratory flume and field studies for open pit coal and gold mining situations in Queensland, Australia. Alternative interpretations of the data are presented, which result in different trends when the data are extrapolated up to angle of repose slopes. The effectiveness of both coarse‐grained riprap on the surface and revegetation in limiting erosion are highlighted.