Multi-objective optimal design for flood risk management with resilience objectives

In flood risk management, the divergent concept of resilience of a flood defense system cannot be fully defined quantitatively by one indicator and multiple indicators need to be considered simultaneously. In this paper, a multi-objective optimization (MOO) design framework is developed to determine the optimal protection level of a levee system based on different resilience indicators that depend on the probabilistic features of the flood damage cost arising under the uncertain nature of rainfalls. An evolutionary-based MOO algorithm is used to find a set of non-dominated solutions, known as Pareto optimal solutions for the optimal protection level. The objective functions, specifically resilience indicators of severity, variability and graduality, that account for the uncertainty of rainfall can be evaluated by stochastic sampling of rainfall amount together with the model simulations of incurred flood damage estimation for the levee system. However, these model simulations which usually require detailed flood inundation simulation are computationally demanding. This hinders the wide application of MOO in flood risk management and is circumvented here via a surrogate flood damage modeling technique that is integrated into the MOO algorithm. The proposed optimal design framework is applied to a levee system in a central basin of flood-prone Jakarta, Indonesia. The results suggest that the proposed framework enables the application of MOO with resilience objectives for flood defense system design under uncertainty and solves the decision making problems efficiently by drastically reducing the required computational time.     

Environmental hazard analysis of a gypsum karst depression area with geophysical methods: a case study in Sivas (Turkey)

Because the mixture of seawater and freshwater in the Gyeongin-Ara Waterway in South Korea can lead to the intrusion of saline water into surrounding aquifers, systematic management through the establishment of a groundwater protection area is required. The analytic hierarchy process (AHP) model is used to delineate this protection area based on two primary factors and five secondary factors related to saline water intrusion. The study area is divided into 987 gridded cells with a unit size of 100 × 100 m, and the final evaluation score for each cell is calculated using the AHP model. Consequently, several artificial neural network models based on a multilayer perceptron are developed using the AHP’s secondary criteria and the evaluation score. Comparing the evaluation scores of ANN and AHP, more than 180 samples are required in the ANN model to insure high R2 between the original and estimated values. The ANN model is more consistent than the AHP model when determining groundwater protection area, because it can be re-constructed due to the changes in some secondary criteria and also changed due to a standardization process. The final evaluation score by the ANN model based on 300 samples, with the highest R2, is calculated and the regions with a score higher than 2.0 are selected as the groundwater protection area, accounting for 15% of the total cells. This area is similar to the range within approximately 200 m of the GA Waterway and also includes some changing sites in hydrogeochemistry and electric conductivity, which is produced by saline water intrusion. If the land-use type, groundwater levels, and some other criteria change at any cell, the ANN model can be re-executed to verify whether the cell belongs to a groundwater protection area. Considering that salinity of groundwater near the waterway can be affected by various factors including well depth, pumping conditions, and groundwater levels, the ANN model, which is a non-linear model, can be more effective for prediction than the AHP model.     

Adjustability of exposed elements by updating their capacity for resistance after a damaging event: application to an earthquake–tsunami cascade scenario

Natural Hazards - The 2011 Great East Japan earthquake and tsunami remind us once again that these types of cascade event can occur and cause considerable damage. The scientific community realizes...     

Relative quantification of wind erosion in argan woodlands in the Souss Basin,Morocco

The endemic argan woodlands cover large parts of South Morocco and create a characteristic landscape with areas of sparsely vegetated and bare soil surfaces between single trees. This unique ecosystem has been under extensive agrosilvopastoral management for centuries and is now at risk of degradation caused by overgrazing and increasing scarcity and variability of rainfall. To investigate susceptibility to wind erosion, we conducted an experimental–empirical study including wind tunnel tests and a drone-generated digital elevation model and quantified wind-erodible material on five different associated surface types by means of sediment catchers. The highest emission flux was measured on freshly ploughed surfaces (1875 g m^–2 h^–1), while older ploughed areas with a re-established crust produced a much lower emission flux (795 g m^–2 h^–1). Extensive tillage may have been a sustainable practice for generations, but increasing drought and uncertainty of rainfall now lead to an acute risk of severe soil erosion and dust production. The typical crusted surfaces characterized by residual rock fragment accumulation and wash processes produced the second highest emission flux (1,354 g m^–2 h^–1). Material collected from tree-shaded areas (933 g m^–2 h^–1) was revealed to be a considerable source of organic material, possibly affecting substrate conditions positively on a larger regional scale. The lowest flux was measured on rock fragment-covered surfaces (301 g m^–2 h^–1). The data show that open argan woodland may be a considerable source for wind erosion and dust production, depending on surface characteristics strongly related to management. An adapted management must include the conservation of argan trees to offer a promising approach to prevent severe wind erosion and dust production and mitigate possible impacts of land-use change and climate change related shifts in wind and rainfall patterns. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd     

Conceptualizing and measuring economic resilience of resource-based cities: Case study of Northeast China

This paper develops a conceptual model and an indicator system for measuring economic resilience of resource-based cities based on the theory of evolutionary resilience and the related concepts of persistence, adaptation, and transformation. Nineteen resource- based cities in Northeast China were analyzed using the indicator system. The results showed that Liaoning and Jilin provinces had higher economic resilience than Heilongjiang Province. Panjin, Benxi, and Anshan in Liaoning Province were the top three cities, while Shuangyashan and other coal-based cities in Heilongjiang Province ranked last. Metals- and petroleum-based cities had significantly higher resilience than coal-based cities. The differences in persistence, adaptability, transformation, and resilience among resource-based cities decreased since the introduction of the Northeast Revitalization Strategy in 2003. Forestry-based cities improved the most in terms of resilience, followed by metals-based and multiple-resource cities; however, resilience dropped for coal-based cities, and petroleum-based cities falling the most. The findings illustrate the importance and the way to develop a differentiated approach to improve resilience among resource-based cities.     

Evolution of landslide hotspots in Taiwan

Among the disasters facing Taiwan, earthquakes and typhoons incur the greatest monetary losses, and landslide disasters inflict the greatest damage in mountainous areas. The nationwide landslide susceptibility map gives an indication of where landslides are likely to occur in the future; however, there is no objective index indicating the location of landslide hotspots. In this study, we used statistical analysis to locate landslide hotspots in catchments in Taiwan. Global and local spatial autocorrelation analysis revealed the existence of landslide clusters between 2003 and 2012 and identified a concentration of landslide hotspots in the eastern part of Central Taiwan. The extreme rainfall brought by typhoon Morakot also led to the formation of new landslide hotspots in Southern Taiwan. This study provides a valuable reference explaining changes in landslide hotspots and identifying areas of high hotspot concentration to facilitate the formulation of strategies to deal with landslide risk.     

The characteristics of the seismic signals induced by landslides using a coupling of discrete element and finite difference methods

Landslide seismic signals support researchers to estimate magnitudes and locations of landslides. They can serve as a crucial data for landslide warning systems. However, the randomness of landslide locations makes the acquisition of landslide-induced seismic signals difficult and limits the number of available field data. The objectives of this study are to establish a numerical modeling approach to examine the characteristics of seismic signals induced by landslides and perform parametrical study. The two-dimensional particle flow code (PFC) and Fast Lagrangian Analysis of Continua (FLAC) are coupled to simulate the landslide process. The force and velocity data at the coupled interfaces of FLAC and PFC are transferred back and forth via a Socket I/O connection. Four locations were monitored for the induced vertical seismic signals, including velocity, acceleration, and stress histories. The signals were analyzed by Hilbert-Huang transform to obtain the time-frequency spectrograms for examining the characteristics of the signals. The particle size, wall friction, particle friction, and parallel bond of PFC input parameters were parametrically investigated. The Xiaolin landslide in 2009 was successfully simulated, and the characteristics of the seismic signals were studied and compared with the data from a broadband seismic station. These results demonstrate that terrain and transition in the movement type of a complex landslide do influence the seismic signals. A landslide with larger rock particles generates lower-frequency content seismic signals. Also, there can be approximately 40 s to escape before a large-scale landslide hits if seismic instrumentation is installed. The method proposed can be further applied for studies on many other large-scale rock avalanches to verify recorded signals and further correlate the signals with the landslide characteristics.     

Modelling wind-erosion risk in the Laghouat region (Algeria) using geomatics approach

Wind-erosion risk is a challenge that threatens land development in dry-land regions. Soil analysis, remote sensing, climatic, vegetal cover and topographic data were used in a geographic information system (GIS), using multi-criteria analysis (MCA) to map wind-erosion risk (R_we) in Laghouat, Algeria. The approach was based on modelling the risk and incorporating topographic and climatic effects. The maps were coded according to their sensitivity to wind erosion and to their socio-economic potential, from low to very high. By overlapping the effects of these layers, qualitative maps were drawn to reflect the potential sensitivity to wind erosion per unit area. The results indicated that severe wind erosion affects mainly all the southern parts and some parts in the north of Laghouat, where wind-erosion hazard (H_we) is very high in 43% of the total area, and which was affected mainly by natural parameters such as soil, topography and wind. The results also identified features vulnerable to R_we. The product of the hazard and the stake maps indicated the potential risk areas that need preventive measures; this was more than half of the study area, making it essential to undertake environmental management and land-use planning.     

Exploiting historical rainfall and landslide data in a spatial database for the derivation of critical rainfall thresholds

Critical rainfall thresholds for landslides are powerful tools for preventing landslide hazard. The thresholds are commonly estimated empirically starting from rainfall events that triggered landslides in the past. The creation of the appropriate rainfall–landslide database is one of the main efforts in this approach. In fact, an accurate agreement between the landslide and rainfall information, in terms of location and timing, is essential in order to correctly estimate the rainfall–landslide relationships. A further issue is taking into account the average moisture conditions prior the triggering event, which reasonably may be crucial in determining the sufficient amount of precipitation. In this context, the aim of this paper is exploiting historical landslide and rainfall data in a spatial database for the derivation of critical rainfall thresholds for landslide occurrence in Sicily, southern Italy. The hourly rainfall events that caused landslides occurred in the twentieth century were specifically identified and reconstructed. A procedure was proposed to automatically convert rain guages charts recorded on paper tape into digital format and then to provide the cumulative rainfall hyetograph in digital format. This procedure is based on a segmentation followed by signal recognition techniques which allow to digitalize and to recognize the hyetograph automatically. The role of rainfall prior to the landslide events was taken into account by including in the analysis the rainfall occurred 5, 15 and 30 days before each landslide. Finally, cumulated rainfall duration thresholds for different exceedance probability levels were determined. The obtained thresholds resulted in agreement with the regional curves proposed by other authors for the same area; antecedent rainfall turned out to be particularly important in triggering landslides.     

Climate change outlook for water resources management in a semiarid river basin: the effect of the environmental water demand

Iran is a developing country with arid and semiarid regions. Poor management of water resources combined with the effects of climate change is leading to the drying of several rivers and wetlands. Several planned water development projects, primarily for agricultural expansion, will be implemented in the coming years which could worsen impacts on vulnerable aquatic ecosystems. Proper water resources management is essential to meet present and future residential, environmental, industrial, and agricultural demands in semiarid regions. This paper presents projections of how the availability of water resources will change in the Karkheh river basin of Iran for the period 2010–2059 employing sustainability criteria in the form of time-based reliability, volumetric reliability, resiliency, and vulnerability. This paper’s results show that consideration of environmental receptors as a stakeholder of water use places limitations on agricultural development within the Karkheh river basin.