A multicriteria spatial decision support system for solving emergency service station location problems

Earthquakes occurring in urban areas constitute an important concern for emergency management and rescue services. Emergency service location problems may be formulated in discrete space or by restricting the potential location(s) to a specified finite set of points in continuous space. We propose a Multicriteria Spatial Decision Support System to identify shelters and emergency service locations in urban evacuation planning. The proposed system has emerged as an integration of the geographical information systems (GIS) and the multicriteria Decision-Making method of Preference Ranking Organization Method for Enrichment Evaluation IV (PROMETHEE IV). This system incorporates multiple and often conflicting criteria and decision-makers’ preferences into a spatial decision model. We consider three standard structural attributes (i.e., durability density, population density, and oldness density) in the form of spatial maps to determine the zones most vulnerable to an earthquake. The information on these spatial maps is then entered into the ArcGIS software to define the relevant scores for each point with regards to the aforementioned attributes. These scores will be used to compute the preference functions in PROMETHEE IV, whose net flow outranking for each alternative will be inputted in ArcGIS to determine the zones that are most vulnerable to an earthquake. The final scores obtained are integrated into a mathematical programming model designed to find the most suitable locations for the construction of emergency service stations. We demonstrate the applicability of the proposed method and the efficacy of the procedures and algorithms in an earthquake emergency service station planning case study in the city of Tehran.     

Analysis of recharge conceptualization in inverse groundwater modelling

ABSTRACT

This study presents a systematic illustration quantifying how misleading the calibration results of a groundwater simulation model can be when recharge rates are considered as the model parameters to be estimated by inverse modelling. Three approaches to recharge estimation are compared: autocalibration (Model 1), the empirical return coefficient method (Model 2), and distributed hydrological modelling using the Soil and Water Assessment Tool, SWAT (Model 3). The methodology was applied in the Dehloran Plain, western Iran, using the MODFLOW modular flow simulator and the PEST method for autocalibration. The results indicate that, although Model 1 performed the best in simulating water levels at observation wells in the calibration stage, it did not perform satisfactorily in real future scenarios. Model 3, with SWAT-based recharge rates, performed better than the other models in the validation stage. By not evaluating the model performance solely on calibration results, we demonstrate the relative significance of using more accurate recharge estimates when calibrating groundwater simulation models.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR M. Besbes     

A fast joint seismic data reconstruction by sparsity‐promoting inversion

Seismic field data are often irregularly or coarsely sampled in space due to acquisition limits. However, complete and regular data need to be acquired in most conventional seismic processing and imaging algorithms. We have developed a fast joint curvelet‐domain seismic data reconstruction method by sparsity‐promoting inversion based on compressive sensing. We have made an attempt to seek a sparse representation of incomplete seismic data by curvelet coefficients and solve sparsity‐promoting problems through an iterative thresholding process to reconstruct the missing data. In conventional iterative thresholding algorithms, the updated reconstruction result of each iteration is obtained by adding the gradient to the previous result and thresholding it. The algorithm is stable and accurate but always requires sufficient iterations. The linearised Bregman method can accelerate the convergence by replacing the previous result with that before thresholding, thus promoting the effective coefficients added to the result. The method is faster than conventional one, but it can cause artefacts near the missing traces while reconstructing small‐amplitude coefficients because some coefficients in the unthresholded results wrongly represent the residual of the data. The key process in the joint curvelet‐domain reconstruction method is that we use both the previous results of the conventional method and the linearised Bregman method to stabilise the reconstruction quality and accelerate the recovery for a while. The acceleration rate is controlled through weighting to adjust the contribution of the acceleration term and the stable term. A fierce acceleration could be performed for the recovery of comparatively small gaps, whereas a mild acceleration is more appropriate when the incomplete data has a large gap of high‐amplitude events. Finally, we carry out a fast and stable recovery using the trade‐off algorithm. Synthetic and field data tests verified that the joint curvelet‐domain reconstruction method can effectively and quickly reconstruct seismic data with missing traces.     

Wind energy potential assessment using Weibull distribution with various numerical estimation methods: a case study in Mersing and Port Dickson,Malaysia

Theoretical and Applied Climatology - In this study, the Weibull distribution with various numerical estimation methods is utilized for the assessment of wind energy potential in Mersing and Port...     

Forecasting of meteorological drought using Wavelet-ANFIS hybrid model for different time steps (case study: southeastern part of east Azerbaijan province, Iran)

Drought is accounted as one of the most natural hazards. Studying on drought is important for designing and managing of water resources systems. This research is carried out to evaluate the ability of Wavelet-ANN and adaptive neuro-fuzzy inference system (ANFIS) techniques for meteorological drought forecasting in southeastern part of East Azerbaijan province, Iran. The Wavelet-ANN and ANFIS models were first trained using the observed data recorded from 1952 to 1992 and then used to predict meteorological drought over the test period extending from 1992 to 2011. The performances of the different models were evaluated by comparing the corresponding values of root mean squared error coefficient of determination (R ²) and Nash–Sutcliffe model efficiency coefficient. In this study, more than 1,000 model structures including artificial neural network (ANN), adaptive neural-fuzzy inference system (ANFIS) and Wavelet-ANN models were tested in order to assess their ability to forecast the meteorological drought for one, two, and three time steps (6 months) ahead. It was demonstrated that wavelet transform can improve meteorological drought modeling. It was also shown that ANFIS models provided more accurate predictions than ANN models. This study confirmed that the optimum number of neurons in the hidden layer could not be always determined using specific formulas; hence, it should be determined using a trial-and-error method. Also, decomposition level in wavelet transform should be delineated according to the periodicity and seasonality of data series. The order of models with regard to their accuracy is as following: Wavelet-ANFIS, Wavelet-ANN, ANFIS, and ANN, respectively. To the best of our knowledge, no research has been published that explores coupling wavelet analysis with ANFIS for meteorological drought and no research has tested the efficiency of these models to forecast the meteorological drought in different time scales as of yet.     

Initiation and evolution of fault-controlled slope-parallel submarine channels: Miocene eastern slope of Yinggehai Basin,South China Sea

Submarine channels act as the main conduits for the transport of sediment to deep-water basins by sediment gravity flows. The interplay between fault-related deformation and the initiation and development of the channels is poorly known. Here, we present the identification, formation and evolution of the Miocene slope-parallel channel by employing 3D seismic reflection, wireline-log and core data in the eastern slope of Yinggehai Basin, South China Sea. Based on the lengths and plan-view shapes, a total of three different types of fault-associated slope-parallel depressions have been identified. The depressions were formed in the fault zone and controlled by the reactivation of the underlying older faults. Among them, Type-1 depressions are short (<20 km) oval or circle shaped possessing only one depocenter. Type-2 depressions are elongated (25–70 km), and usually have multiple depocenters. Type-3 depressions, which are usually connected by slope-perpendicular channels in the head and middle, are longer (more than 190 km) and connect shallow and deep-water basins. The analysis of morphology, erosivity and material transport shows that Type-3 depressions are fully fledged channels. Type-1 and Type-2 depressions are channel precursors representing the initial stage of channel evolution. With this motive, a model for the initiation and evolution of slope-parallel submarine channels controlled by strike-slip-extensional faults is presented. Unlike the previous investigations which suggest that erosion takes place at the inception of submarine channel formation, the fault-controlled slope-parallel channel is mainly controlled by faulting and has no initial erosive base and does not develop levees. The depressions are extended and elongated by the continuous fault activity. It was not until the slope-parallel depression connected with large-scale slope-perpendicular channels transporting materials into the depression via erosive turbidity currents that it evolved into a channel-levee system. This study is of global importance for understanding submarine channel generation and evolution since the fault-controlled slope-parallel channels have been found in tectonic active basins worldwide.     

Soil loss and displacement by heavy equipment in forest road subgrading projects

Forest soil is an important component of the natural environment, and is a primary medium for many biological activities. In this study, soil loss and displacement by excavator and bulldozer （heavy equipments） were measured on cut and fills slopes of forest roads located in Mazandaran province, lran. The volumes of soil losses were estimated by prismoidal analyses of cut and fill slopes deformation between two time treatments （under subgrading and two years later） in slope classes of 30-50% and 50-70%. Weights of soil losses were calculated by multiplying the volumes of soil losses （cm^3） to the general bulk density （1.3g/cm^3）. Soil displaced area by heavy equipment was evaluated according to earth working width. Results indicated that heavy equipment has significant effect on deformation of cut slope gradient and fill slope length （p〈0.0001）. During the two-year period, the cut （p〈0.0002） and fill （p〈0.0001） slope gradients were significantly deformed in different slope classes. The average soil loss by excavator and bulldozer were 160.35 t/ha·yr and 429.09 t/ha·yr, respectively. Moreover, the soil displaced area during the subgrading process by bulldozer was greater than excavator in both two slope classes （p〈0.05）. Soil loss and displacement in forest roads can be rednced by applying powerful excavators in subgrading project, especially in steep terrains.     

Impact of downstream lakes on dam break wave attenuation

In this study, the effect of downstream lakes or ponds on dam break flow was investigated. To do this, a robust finite volume method with Harten-Lax-van Leer contact surface Riemann’s solver technique for flux evaluation has been used. For space discretization, a triangular mesh grid was used and a complete software with mesh generator was developed. A reservoir with a long downstream channel was assumed, and many scenarios such as a single lake with various lengths, widths and positions along the channel and multiple consecutive lakes as symmetric and non-symmetric with respect to the channel centerline were considered. The numerical modeling of dam break flow along the channel showed that the downstream lake can decrease the speed and depth of the dam break wave front and the amount of this wave attenuation was very dependent on the storage volume of the lake and vortexes which were established in the lake.