An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia

Flooding is one of the most destructive natural hazards that cause damage to both life and property every year, and therefore the development of flood model to determine inundation area in watersheds is important for decision makers. In recent years, data mining approaches such as artificial neural network (ANN) techniques are being increasingly used for flood modeling. Previously, this ANN method was frequently used for hydrological and flood modeling by taking rainfall as input and runoff data as output, usually without taking into consideration of other flood causative factors. The specific objective of this study is to develop a flood model using various flood causative factors using ANN techniques and geographic information system (GIS) to modeling and simulate flood-prone areas in the southern part of Peninsular Malaysia. The ANN model for this study was developed in MATLAB using seven flood causative factors. Relevant thematic layers (including rainfall, slope, elevation, flow accumulation, soil, land use, and geology) are generated using GIS, remote sensing data, and field surveys. In the context of objective weight assignments, the ANN is used to directly produce water levels and then the flood map is constructed in GIS. To measure the performance of the model, four criteria performances, including a coefficient of determination (R ²), the sum squared error, the mean square error, and the root mean square error are used. The verification results showed satisfactory agreement between the predicted and the real hydrological records. The results of this study could be used to help local and national government plan for the future and develop appropriate (to the local environmental conditions) new infrastructure to protect the lives and property of the people of Johor.     

An Empirical Model for Significant Duration of the Ground Motions Containing Velocity Pulses

Izvestiya, Physics of the Solid Earth - ln this study, two relationships have been presented for predicting the significant duration values $$({{D}_{{s5 - 75}}}$$ and $${{D}_{{s5 - 95}}})~$$ of...     

A comparative study between sequential Gaussian simulation and kriging method grade modeling in open-pit mining

Grade estimation is very important in designing open pits. In the process of grade estimation, underestimation can result in loss of economic ore, whereas overestimation would unnecessarily increase stripping ratio. Normally, kriging method, which suffers from underestimation and/or overestimation due to smoothing effect, is used for grade estimation. To overcome drawbacks of the kriging method, more efficient techniques such as conditional simulation can be applied. In this paper, utilizing sequential Gaussian conditional simulation, grade models were constructed for Sungun copper deposit situated in the North West of Iran. According to the obtained results, it was observed that conditional simulation can effectively cope with the weakness of kriging method. Also, it was observed that as compared to the kriging method, grade distribution, resulted from the conditional simulation, is almost identical to that of the real exploration data. Accordingly, using conditional simulation, the amount of mineable ore was significantly increased, and also, average net present value as the mines’ most important economic indicator was improved by 40%.     

Different Irrigation Methods and Their Comparisons Based on the Parametric Evaluation Method in Khosouyeh Dam Subbasin,Iran

Today, the world's population is rising dramatically, and in line with this increase in the population of food and agricultural products, there must be an increasing in the number of problems associated with this process of agricultural land. Then it is necessary to use the maximum potential of this lands that product maximum yield without any damage. To reach this objective, land suitability evaluation is the most important way that can reach human to this objective. The main objective of this research was to compare different irrigation methods based on a parametric evaluation system in an area of 221402 ha in the Khosouyeh Subbasin of the Fars province, in the south of Iran. After preparing land unit map, 37 points were selected for sampling. Soil properties were evaluated and analyzed. Suitability maps for drop and gravity irrigation were generated using GIS technique. The results revealed land suitability of 98.42% of the case study was classified as permanently not suitable (N₂) and 1.52% currently not suitable (N₁) for gravity irrigation. On the other hand, land suitability of 77.73% of the case study was classified as permanently not suitability (N₂), 6.05% currently not suitable (N₁), 12.43% marginally suitable (S₃) and 3.79% moderately suitable (S₂) for drop irrigation. The limiting factors for both kinds of drop and gravity irrigation are soil depth and slope of land.     

Tunnel flexibility effect on the ground surface acceleration response

Flexibility of underground structures relative to the surrounding medium, referred to as the flexibility ratio, is an important factor that influences their dynamic interaction. This study investigates the flexibility effect of a box-shaped subway tunnel, resting directly on bedrock, on the ground surface acceleration response using a numerical model verified against dynamic centrifuge test results. A comparison of the ground surface acceleration response for tunnel models with different flexibility ratios revealed that the tunnels with different flexibility ratios influence the acceleration response at the ground surface in different ways. Tunnels with lower flexibility ratios have higher acceleration responses at short periods, whereas tunnels with higher flexibility ratios have higher acceleration responses at longer periods. The effect of the flexibility ratio on ground surface acceleration is more prominent in the high range of frequencies. Furthermore, as the flexibility ratio of the tunnel system increases, the acceleration response moves away from the free field response and shifts towards the longer periods. Therefore, the flexibility ratio of the underground tunnels influences the peak ground acceleration (PGA) at the ground surface, and may need to be considered in the seismic zonation of urban areas.     

Integrated rainfall–runoff and flood inundation modeling for flash flood risk assessment under data scarcity in arid regions: Wadi Fatimah basin case study,Saudi Arabia

This paper presents a proposed integrated approach for flood hazardous evaluation in arid and semi-arid areas. Wadi Fatimah in Saudi Arabia is utilized for implementation of such an approach. The approach consists of four stages. In the first stage, a statistical analysis of rainfall data is performed to determine the design storms at specified return periods. In the second stage, geological and geomorphologic analyses are followed to estimate the geomorphic parameters. The third stage concerned with land use and land cover analyses linked with hydrological analysis to estimate the hydrographs. The fourth stage is related to the delineation of the inundation area under two scenarios: the presence and absence of the dam. The statistical analysis proved that some rainfall stations do not follow a Gumbel distribution. The presence of the dam reduces the inundation depth by about 10 %. The reduction in the inundation area due the presence of the dam is about 25 %.     

Roadheader performance prediction using genetic programming (GP) and gene expression programming (GEP) techniques

Roadheading machines play a vital role in excavation operation in tunneling and mining industries notably when selective mining is required. Roadheaders are more effective in soft to medium rock formations due to a higher cutting rate in such strata. A precise prediction of machine’s performance is a crucial issue, as it has considerable effects on excavation planning, project’s cost estimation, machine specification selection as well as safety of the project. In this research, a database of machine performance and some geomechanical parameters of rock formations from Tabas coal mine project, the largest and fully mechanized coal mine in Iran, has been established, including instantaneous cutting rate (ICR), uniaxial compressive strength, Brazilian tensile strength, rock quality designation, influence of discontinuity orientation (Alpha angle) and specific energy. Afterward, the parameters were analyzed through genetic programming (GP) and gene expression programming (GEP) approaches to yield more accurate models to predict the performance of roadheaders. As statistical indices, coefficient of determination, root mean square error and variance account were used to evaluate the efficiency of the developed models. According to the obtained results, it was observed that developed models can effectively be implemented for prediction of roadheader performance. Moreover, it was concluded that performance of the GEP model is better than the GP model. A high conformity was observed between predicted and measured roadheader ICR for GEP model.     

Impacts of karst phenomena on engineering properties of limestone foundation bed,Ar Riyadh,Saudi Arabia

Evaluation of mechanical and petrophysical properties of the karst limestone became essential to avoid future risks in the construction of new urban cities built on limestones. Therefore, this study aims to evaluate the impact of karsts phenomena on engineering properties of limestone foundation bed at Ar Riyadh in Saudi Arabia. Three hundred core plugs were obtained by rotary drilling at depths ranging from the ground surface to 20 m collected from 24 boreholes in two sites: (1) karst limestone (KL) at Al Aziziyah district and (2) massive hard limestone (HL) at Hittin district in Ar Riyadh city, Saudi Arabia. Petrographic, SEM, EDX, and XRD analyses are used to identify the mineralogical composition and microstructures of limestone samples. The petrophysical properties included the ovendry density, P-wave, and porosity where the mechanical properties covered the uniaxial compressive strength (UCS), point load strength index (PLI), and rock quality designation (RQD) for the karst and hard limestone samples. KL is characterized by 17.11% total porosity, 14.71% water absorption, 32.1 MPa UCS, 1.70 g/cm³ ovendry density (γ dry), 51% weathered RQD, 5.49 MPa medium shear strength, and low modulus of deformation of the plate loading test. HL showed 11.63% total porosity, 9.45% water absorption 43.1 MPa UCS, 2.50 g/cm³ ovendry density (γ dry), 78% hard to fresh rock affinity RQD, and 9.93 MPa high strength and high modulus of deformation of the plate loading test. For the water absorption (%), KL at Al Aziziyah district showed a range of 12.85–17.80% averaged 14.71%. HL at Hittin district varied between 7.04 and 11.29% with an average of 9.45%. KL proved to be dense with ovendry density (γ dry) averaged at 1.70 g/cm³ while HL showed very dense affinity of 2.50 g/cm³. KL clarified a UCS range from 22.5 to 40.1 MPa and an average of 32.1 MPa while HL showed a range from 35.4 t o 48.1 MPa with an average of 43.1 MPa. KL is moderately weathered with RQD average of 51% while HL showed a hard to fresh rock affinity of 78%. Point load test clarified a medium shear strength with 5.49 MPa for KL and high strength of 9.93 MPa for HL. Plate loading tests indicated low and high modulus of deformation for KL and HL, respectively. Results of petrographical analyses and XED of limestone samples showed that the strength parameters of samples mostly composed of micrite (mudstone/wackestone) and dolomite in hard limestone of Hittin district. In Al Aziziyah district (KL), the samples mostly consist of foraminifera and high amount of calcite as in karst limestone (wackestone/packstone). Rock mechanical tests with combination of fabric analyses have shown that strength parameters depend not only on the amount of karst but also on the amount of allochem. Major geomechanical differences between the two types of limestone provide the proper base for prioritizing areas to alleviate future risks and sustainable urban planning for decision makers. The karstic limestone, therefore, is considered as an acceptable foundation bed for light engineering structures. However, for heavy structures and buildings, improving the foundation bed strength by grouting, cement injection, and mat foundations is necessary to avoid future failure risks.     

Risk assessment of water erosion for the Qareh Aghaj subbasin, southern Iran

South of the Zagros belt, the entire land of Southern Iran faces problems arising out of various types of land degradation of which water erosion forms a major type. A new model has been developed for assessing the risk of water erosion. Taking into consideration nine indicators of water erosion the model identifies areas with ‘Potential Risk’ (risky zones) and areas of ‘Actual Risk’ as well as projects the probability of the worse degradation in future. The Qareh Aghaj subbasin (1,265,000 ha), which covers the upper reaches of Mond River, has been chosen for a test risk assessment of this kind. The preparation of risk maps based on the GIS analysis of these indicators will be helpful for prioritizing the areas to initiate remedial measures. The different kinds of data for indicators of water erosion were gathered from the records and published reports of the governmental offices of Iran. By fixing the thresholds of severity classes of the nine indicators a hazard map for each indicator was first prepared in GIS. The risk classes were defined on the basis of risk scores arrived at by assigning the appropriate attributes to the indicators and the risk map was prepared by overlaying nine hazard maps in the GIS. Areas under potential risk have been found to be widespread (63%) in the basin and when classified into subclasses with different probability levels the model projects a statistical picture of the risk of land degradation.