•Review of methods applied and key findings from a large number of studies in Europe.•Observations and climate model projections show an increase in extreme precipitation.•Hydrological projections of ...floods show large impacts in many areas.•Snowmelt-dominated catchments show a decrease in flood magnitude.•Few countries in Europe have developed guidelines for incorporating climate change.
This paper presents a review of trend analysis of extreme precipitation and hydrological floods in Europe based on observations and future climate projections. The review summaries methods and methodologies applied and key findings from a large number of studies. Reported analyses of observed extreme precipitation and flood records show that there is some evidence of a general increase in extreme precipitation, whereas there are no clear indications of significant trends at large-scale regional or national level of extreme streamflow. Several studies from regions dominated by snowmelt-induced peak flows report decreases in extreme streamflow and earlier spring snowmelt peak flows, likely caused by increasing temperature. The review of likely future changes based on climate projections indicates a general increase in extreme precipitation under a future climate, which is consistent with the observed trends. Hydrological projections of peak flows show large impacts in many areas with both positive and negative changes. A general decrease in flood magnitude and earlier spring floods are projected for catchments with snowmelt-dominated peak flows, which is consistent with the observed trends. Finally, existing guidelines in Europe on design flood and design rainfall estimation are reviewed. The review shows that only few countries have developed guidelines that incorporate a consideration of climate change impacts.
•Backcasting storm runoff response using novel method for generating historical LUC.•Increased peak flow and reduced response time following peri-urban development.•Attribution of flashy response ...using impervious cover plus storm drainage.•Increased impervious cover has greater impact on rural peak flows than urban.•Drainage more important determinant of storm response than land use type.
This paper investigates changes in storm runoff resulting from the transformation of previously rural landscapes into peri-urban areas. Two adjacent catchments (∼5km2) located within the town of Swindon in the United Kingdom were monitored during 2011 and 2012 providing continuous records of rainfall, runoff and actual evaporation. One catchment is highly urbanized and the other is a recently developed peri-urban area containing two distinct areas of drainage: one with mixed natural and storm drainage pathways, the other entirely storm drainage. Comparison of observed storm hydrographs showed that the degree of area serviced by storm drainage was a stronger determinant of storm runoff response than either impervious area or development type and that little distinction in hydrological response exists between urban and peri-urban developments of similar impervious cover when no significant hydraulic alteration is present. Historical levels of urbanization and impervious cover were mapped from the 1960s to the 2010s based on digitized historical topographic maps and were combined with a hydrological model to enable backcasting of the present day storm runoff response to that of the catchments in their earlier states. Results from the peri-urban catchment showed an increase in impervious cover from 11% in the 1960s to 44% in 2010s, and introduction of a large-scale storm drainage system in the early 2000s, was accompanied by a 50% reduction in the Muskingum routing parameter k, reducing the characteristic flood duration by over 50% while increasing peak flow by over 400%. Comparisons with changes in storm runoff response in the more urban area suggest that the relative increase in peak flows and reduction in flood duration and response time of a catchment is greatest at low levels of urbanization and that the introduction of storm water conveyance systems significantly increases the flashiness of storm runoff above that attributed to impervious area alone.
This study demonstrates that careful consideration is required when using impervious cover data within hydrological models and when designing flood mitigation measures, particularly in peri-urban areas where a widespread loss in pervious surfaces and alteration of drainage pathways can significantly alter the storm runoff response. Recommendations include utilizing more refined urban land use typologies that can better represent physical alteration of hydrological pathways.
•A novel ensemble SVM and WoE method was used for flood susceptibility mapping.•Four SVM kernel types: LN, PL, RBF, and SIG were used in the ensemble model.•Cross validation was used to measure the ...most accurate SVM parameters.•The derived ensemble methods were compared with individual WoE and SVM methods.•The proposed ensemble method could improve flood modeling by 29%.
Flood is one of the most devastating natural disasters that occur frequently in Terengganu, Malaysia. Recently, ensemble based techniques are getting extremely popular in flood modeling. In this paper, weights-of-evidence (WoE) model was utilized first, to assess the impact of classes of each conditioning factor on flooding through bivariate statistical analysis (BSA). Then, these factors were reclassified using the acquired weights and entered into the support vector machine (SVM) model to evaluate the correlation between flood occurrence and each conditioning factor. Through this integration, the weak point of WoE can be solved and the performance of the SVM will be enhanced. The spatial database included flood inventory, slope, stream power index (SPI), topographic wetness index (TWI), altitude, curvature, distance from the river, geology, rainfall, land use/cover (LULC), and soil type. Four kernel types of SVM (linear kernel (LN), polynomial kernel (PL), radial basis function kernel (RBF), and sigmoid kernel (SIG)) were used to investigate the performance of each kernel type. The efficiency of the new ensemble WoE and SVM method was tested using area under curve (AUC) which measured the prediction and success rates. The validation results proved the strength and efficiency of the ensemble method over the individual methods. The best results were obtained from RBF kernel when compared with the other kernel types. Success rate and prediction rate for ensemble WoE and RBF-SVM method were 96.48% and 95.67% respectively. The proposed ensemble flood susceptibility mapping method could assist researchers and local governments in flood mitigation strategies.
•Decision tree (DT) machine learning algorithm was used to map the flood susceptible areas in Kelantan, Malaysia.•We used an ensemble frequency ratio (FR) and logistic regression (LR) model in order ...to overcome weak points of the LR.•Combined method of FR and LR was used to map the susceptible areas in Kelantan, Malaysia.•Results of both methods were compared and their efficiency was assessed.•Most influencing conditioning factors on flooding were recognized.
Flood is one of the natural hazards which occur all over the world and it is critical to be controlled through proper management. Severe flood events in Kelantan, Malaysia cause damage to both life and property every year, and therefore the development of flood model to recognize the susceptible areas in watersheds is important for decision makers. Remote sensing (RS) and geographic information system (GIS) techniques could be useful in hydrological studies while they are able to fulfill all the requirements for comprehensive, rapid and accurate analysis. The aim of the current research is to compare the prediction performances of two different approaches such as rule-based decision tree (DT) and combination of frequency ratio (FR) and logistic regression (LR) statistical methods for flood susceptibility mapping at Kelantan, Malaysia. DT is based on the rules which are created precisely and strongly by considering all the characteristics of the variables which can enhance the performance of the flood susceptibility mapping. On the other hand, LR as multivariate statistical analysis (MSA) has some weak points. For that reason, FR was used to analyze the impact of classes of each variable on flood occurrence and overcome the weakness of LR. At first, flood inventory map with a total of 155 flood locations was extracted from various sources over the part of the Kelantan. Then the flood inventory data was randomly divided into a testing dataset 70% (115 flood locations) for training the models and the remaining 30% (40 flood locations) was used for validation purpose. The spatial database includes digital elevation model (DEM), curvature, geology, river, stream power index (SPI), rainfall, land use/cover (LULC), soil type, topographic wetness index (TWI) and slope. For validation both success and prediction rate curves were performed. The validation results showed that, area under the curve for the results of DT and integrated method of FR and LR was 87% and 90% for success rate and 82% and 83% for prediction rate respectively.
Floods are among the most destructive natural disasters, which are highly complex to model. The research on the advancement of flood prediction models contributed to risk reduction, policy ...suggestion, minimization of the loss of human life, and reduction of the property damage associated with floods. To mimic the complex mathematical expressions of physical processes of floods, during the past two decades, machine learning (ML) methods contributed highly in the advancement of prediction systems providing better performance and cost-effective solutions. Due to the vast benefits and potential of ML, its popularity dramatically increased among hydrologists. Researchers through introducing novel ML methods and hybridizing of the existing ones aim at discovering more accurate and efficient prediction models. The main contribution of this paper is to demonstrate the state of the art of ML models in flood prediction and to give insight into the most suitable models. In this paper, the literature where ML models were benchmarked through a qualitative analysis of robustness, accuracy, effectiveness, and speed are particularly investigated to provide an extensive overview on the various ML algorithms used in the field. The performance comparison of ML models presents an in-depth understanding of the different techniques within the framework of a comprehensive evaluation and discussion. As a result, this paper introduces the most promising prediction methods for both long-term and short-term floods. Furthermore, the major trends in improving the quality of the flood prediction models are investigated. Among them, hybridization, data decomposition, algorithm ensemble, and model optimization are reported as the most effective strategies for the improvement of ML methods. This survey can be used as a guideline for hydrologists as well as climate scientists in choosing the proper ML method according to the prediction task.
China’s macroeconomic policy framework has been determined to ensure steady growth, adjust the industrial structure and advance the socioeconomic reforms in recent years. And urbanization is supposed ...to be one of the most important socioeconomic reform directions. Meanwhile, China also committed to reduce carbon emissions intensity by 2020, then it should be noted that what kind of impact of these policy orientations on carbon emission intensity. Therefore, based on the historical data from 1978 to 2011, this paper quantitatively studies the impact of China’s economic growth, industrial structure and urbanization on carbon emission intensity. The results indicate that, first, there is long-term cointegrating relationship between carbon emission intensity and other factors. And the increase in the share of tertiary industry i.e., the ratio of tertiary industry value added to gross domestic product (GDP) and economic growth (here we use the real GDP per capita) play significant roles in curbing carbon emission intensity, while the promotion of population urbanization (i.e., the share of population living in the urban regions of total population) may lead to carbon emission intensity growth. Second, there exists significant one-way causality running from the urbanization rate and economic growth to carbon emission intensity, respectively. Third, among the three drivers, economic growth proves the main influencing factor of carbon emission intensity changes during the sample period.
Current use of land surface curvatures (LSCs) is in a confused state as a large gap has opened up between applications and theoretical work. LSCs exercise important control on changes of gravity ...potential energy and the equilibrium of the surface, and they are increasingly used in geosciences but they are not consistently defined. This paper offers a comprehensive theoretical framework for definition, classification and interpretation of LSCs. Systematization of known and newly derived relationships between LSCs is followed by extension of the traditional scheme for interpretation. A new comprehensive system of LSCs starts with the basic trio: profile, plan and twisting curvatures, and includes their slope-dependent sub-forms, combinations and imitations. Analysis of their influence on changes of gravitational potential energy available for mass flows is crucial for their understanding, and leads to a new interpretation of difference curvature. The systematic evaluation of LSCs as expressions of slope disequilibrium offers a further interpretation: zero values of LSCs can be considered as important theoretical attractors of landform development. LSCs are increasingly employed for analyses of landslide, flood, snow avalanche, forest fire, soil erosion, mass balance, ground water, digital soil mapping, individual landform identification and land surface segmentation, modelling of landscape development, classification of LIDAR data and visualization of terrain features. Important improvement of LSC use in all these spheres is possible. They are mostly computed in geographical information systems with limited capabilities: the performance of ArcGIS, SAGA, GRASS, LandSerf, Surfer and MICRODEM is compared here. The important interrelations of DEM resolution, accuracy and generalization are demonstrated in relation to the nested hierarchy of land forms and processes. The best interpretable LSCs, and challenges of future progress, are specified at the close of the paper.
•Flash floods and debris flows escape conventional hydrometeorological monitoring.•Further development of radar-based rainfall estimation and nowcasting in complex orography is key.•Effective risk ...management requires consolidating physical and social datasets of these events.•Further research should focus on methods for multiple-hazard warning.
Flash floods and debris flows develop at space and time scales that conventional observation systems for rainfall, streamflow and sediment discharge are not able to monitor. Consequently, the atmospheric, hydrological and geomorphic controls on these hydrogeomorphic processes are poorly understood, leading to highly uncertain warning and risk management. On the other hand, remote sensing of precipitation and numerical weather predictions have become the basis of several flood forecasting systems, enabling increasingly accurate detection of hazardous events. The objective of this paper is to provide a review on current European and international research on early warning systems for flash floods and debris flows. We expand upon these themes by identifying: (a) the state of the art; (b) knowledge gaps; and (c) suggested research directions to advance warning capabilities for extreme hydrogeomorphic processes. We also suggest three areas in which advancements in science will have immediate and important practical consequence, namely development of rainfall estimation and nowcasting schemes suited to the specific space–time scales, consolidating physical, engineering and social datasets of flash floods and debris-flows, integration of methods for multiple hydrogeomorphic hazard warning.
INTRODUCTION: Nature's fury Grocholski, Brent; Coontz, Robert
Science (American Association for the Advancement of Science),
07/2016, Letnik:
353, Številka:
6296
Journal Article
This article reviews current drought effects on environmental systems. It stresses the need for considering environmental drought as a relevant type to be included in drought classifications. Here we ...illustrate that drought has complex environmental effects and affects many different systems (e.g., soils, air, vegetation, and forests, aquatic systems and wildlife). Droughts can affect the quality, structure, and diversity of these systems. However, we find that most environmental systems show strong resistance and resilience to drought events, and the effects of drought are usually temporary. Structural effects of environmental droughts tend to only occur in areas that are perturbed or in communities near their distribution limits. There are few long-term experimental studies that quantify possible trends in drought effects on environmental systems. Nevertheless, existing studies of forests that are based on tree-ring chronologies or forest inventories indicate increased drought-related effects on environmental systems. Future climate change scenarios suggest increased drought severity worldwide, which could alter the vulnerability of different environmental systems and increase the number of structural drought effects.
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