Landslide susceptibility assessment along the southern coast of the Caspian Sea,Iran

China is a disaster-prone country, and these disasters have diverse characteristics, a wide scope of distribution, high frequency, and large losses. China has advanced community-based disaster management (CBDM) capacity. Community is the bottom unit of the society, and CBDM is the foundation of the entire society’s disaster management system. A series of domestic major emergency incidents and disasters and international disaster reduction activities have promoted the formation of the CBDM concept, the implementation of capacity building activities, and the improvement of policy and laws. Thus far, the CBDM system has been preliminarily formed in China, and relevant rules and regulations have been promulgated and implemented. Furthermore, disaster reduction activities, such as the construction of the national comprehensive disaster reduction community and national safe community, have been promoted nationwide. As a result, China’s disaster-resistance capacity has largely improved. However, it is only in the initial phase of CBDM implementation, which remains plagued by several challenges and problems, such as the deficiency of community resident participation, management organizations, disaster risk assessment methods, NGO development, and safety culture cultivation.     

Generating non-stationary random fields of auto-correlated,normally distributed CPT profile by matrix decomposition method

This paper emphasises the true realisation of Cone Penetration Test (CPT) profiles considering non-stationary nature of the data. Formulation of stationary random field theory has been modified and adapted to non-stationary state in order to take into account the mean and variance variability for soil properties. Multi-variance correlation matrix along with the Cholesky decomposition technique was employed to produce realisations of non-homogenous and non-stationary random fields of CPT profiles. A piecewise and segmental data realisation according to the lithology and site class specifications acquired directly from CPT data is adopted in this study so as to render an accurate data simulation. For validation of proposed method 8 CPT test profiles collected from Urmia Lake site have been introduced and simulated by the stationary and non-stationary algorithms. The mean correlation coefficient between the actual CPT data profiles and related realisations along with some other important statistical parameters and their coefficients of variation strongly demonstrate that non-stationary random field generation technique gives quite better accuracy, by comparison to the conventional stationary random field generation scheme.     

Modeling and assessing the effects of land use changes on runoff generation with the CLUE-s and WetSpa models

Theoretical and Applied Climatology - Land use change is an important determinant of hydrological processes and is known to affect hydrological parameters such as runoff volume, flood frequency,...     

Optimal water and waste load allocation in reservoir–river systems: a case study

In this paper, a new methodology is developed for optimization of water and waste load allocation in reservoir–river systems considering the existing uncertainties in reservoir inflow, waste loads and water demands. A stochastic dynamic programming (SDP) model is used to optimize reservoir operation considering the inflow uncertainty, and another model called PSO-SA is developed and linked with the SDP model for optimizing water and waste load allocation in downstream river. In the PSO-SA model, a particle swarm optimization technique with a dynamic penalty function for handling the constraints is used to optimize water and waste load allocation policies. Also, a simulated annealing technique is utilized for determining the upper and lower bounds of constraints and objective function considering the existing uncertainties. As the proposed water and waste load allocation model has a considerable run-time, some powerful soft computing techniques, namely, Regression tree Induction (named M5P), fuzzy K-nearest neighbor, Bayesian network, support vector regression and an adaptive neuro-fuzzy inference system, are trained and validated using the results of the proposed methodology to develop real-time water and waste load allocation rules. To examine the efficiency and applicability of the methodology, it is applied to the Dez reservoir–river system in the south-western part of Iran.     

Mixed precision parallel preconditioner and linear solver for compositional reservoir simulation

Reservoir simulation role in value creation and strategic management decisions cannot be over emphasized. Simulation of complex challenging reservoirs with millions of grid blocks especially in compositional mode is very time-consuming even with fast modern computers. On the other hand, high price of cluster supercomputers prevents them for being commonly used for fast simulation of such reservoirs. In recent years, the development of many-core processors like cell processors, DSPs, and graphical processing units (GPUs) has provided a very cost-effective hardware platform for fast computational operations. However, programming for such processors is much more difficult than conventional CPUs, and new parallel algorithm design and special parallel implementation methods are needed. Using the computational power of CPUs, GPUs, and/or any other processing unit, Open Computing Language (OpenCL) provides a framework for programming for heterogeneous platforms. In this paper, OpenCL is used to employ the computational power of a GPU to build a preconditioner and solve the linear system arising from compositional formulation of multiphase flow in porous media. The proposed parallel preconditioner is proved to be quite effective, even in heterogeneous porous media. Using data-parallel modules on GPU, the preconditioner/solver runtime reduced at least 1 order of magnitude compared to their serial implementation on CPU.     

Three-dimensional discontinuous deformation analysis (3-D DDA) using a new contact resolution algorithm

This paper presents a new contact calculating algorithm for contacts between two polyhedra with planar boundaries in the three-dimensional discontinuous deformation analysis (3-D DDA). In this algorithm, all six type contacts in 3-D (vertex-to-face, vertex-to-edge, vertex-to-vertex, face-to-face, edge-to-edge, and edge-to-face) are simply transformed into the form of point-to-face contacts. The presented algorithm is a simple and efficient method and it can be easily coded into a computer program. In this paper, formulations of normal contact, shear contact and frictional force submatrices based on the new method are derived and the algorithm has been programmed in VC⁺⁺. Examples are provided to demonstrate the new contact rule between two blocks.     

Location of Areas Prone to Flood Spreading Using GIS (Ilam Province,Iran)

Water Resources - The present study aimed to locate the areas prone to flood spreading in order to manage surface water resources. Therefore, the information layers of slope, land capability,...     

An investigation of trends in precipitation volume for the last three decades in different regions of Fars province, Iran

Under condition of climate changes as global warming, monitoring and detecting trend of precipitation volume is essential and will be useful for agricultural sections. Considering the fact that there were not enough research related to precipitation volume, this study aimed to determine trends in precipitation volume, monthly and annually in different regions of Fars province for the last three decades (33?years period; 1978–2010). Fars province is located in arid and semi-arid regions of Iran, and it plays an important role in agricultural production. Inverse distance weighting interpolation method was used to provide precipitation data for all regions. To analyze the trends of precipitation volume, Mann–Kendall test, Sen’s slope estimator, and 10-year moving average low-pass filter (within time series) were used. The negative trends were identified by the Sen’s slope estimator as well as Mann–Kendall test. However, all the trends were insignificant at the surveyed confidence level (95%). With regards to the application of 10-year moving average low-pass filter, a considerable decreasing trend was observed after around year 1994. Since one of the most important restrictions in agricultural development of the Fars province is lack of sufficient water resources, any changes onward to lack of sufficient precipitation impose impressive pressure and stress on valuable resources and subsequently agricultural production.     

A study of differentiation pattern and rare earth elements migration in geochemical and hydrogeochemical environments of Airekan and Cheshmeh Shotori areas (Central Iran)

The Airekan and Cheshmeh Shotori areas are located about 60 km northeast of Khour, in Isfahan province from Central Iran. Research on characteristics and rare earth elements (REE) pattern in hydrogeochemical environments of these areas suggests the same origin for the elements dissolved in groundwater in these areas. Investigation of migration pattern of REE in hydrogeochemical environments shows that the migration and transportation of REE has occurred through chloride complexes. REEs, leached by water/rock interaction from the Airekan granite, are transported by groundwater and then precipitated in the Cheshmeh Shotori area. Study of the Cheshmeh Shotori sediments shows the presence of a sequence of red oxidized and dark layers. Geochemical characteristics of these sediments reveal that their REE characteristics are mainly inherited from the Airekan granite. Changes in the REE pattern of these sediments with depth show that changes in oxidation and reduction process have not played a significant role in controlling their behavior. It is crucial to note that adsorption of REEs dissolved in water by hydrosilicate increases these elements in depth. The REE behavior shows water/rock interaction between the granitic rocks and groundwater as the main factor of solution, migration and precipitation of REEs in the Cheshmeh Shotori area.     

Geochemical Prospectivity Mapping Through a Feature Extraction–Selection Classification Scheme

Natural Resources Research - Machine learning (ML) schemes can enhance success in geochemical prospectivity mapping. This study has examined the effectiveness of several feature extraction or...