Impact assessment of land cover changes on the runoff changes on the extreme flood events in the Kelantan River basin

In the current years, changing the land cover/land use had serious hydrological impacts affecting the flood events in the Kelantan River basin. The flood events at the east coast of the peninsular Malaysia got highly affected in the recent decades due to several factors like urbanisation, rapid changes in the utilisation of land and lack of meteorological (i.e. change in climate) and developmental monitoring and planning. The Kelantan River basin has been highly influenced due to a rapid change in land use during 1984 to 2013, which occurred in the form of transformation of agricultural area and deforestation (logging activities). In order to evaluate the influence of the modifications in land cover on the flood events, two hydrological regional models of rainfall-induced runoff event, the Hydrologic Engineering Center (HEC)-Hydrologic Modeling System (HMS) model and improved transient rainfall infiltration and grid-based regional model (Improved TRIGRS), were employed in this study. The responses of land cover changes on the peak flow and runoff volume were investigated using 10 days of hourly rainfall events from 20 December to the end of December 2014 at the study area. The usage of two hydrological models defined that the changes in land use/land cover caused momentous changes in hydrological response towards water flow. The outcomes also revealed that the increase of severe water flow at the study area is a function of urbanisation and deforestation, particularly in the conversion of the forest area to the less canopy coverage, for example, oil palm, mixed agriculture and rubber. The monsoon season floods and runoff escalate in the cleared land or low-density vegetation area, while the normal flow gets the contribution from interflow generated from secondary jungle and forested areas.     

Retrieving of Land Surface Temperature Using Thermal Remote Sensing and GIS Techniques in Kandaihimmat Watershed,Hoshangabad, Madhya Pradesh

Remotely sensed thermal infrared (TIR) data have been widely used to retrieve land surface temperature (LST). LST is an important parameter in the studies of urban thermal environment and dynamics. In the study, an attempt has been made using LANDSAT 8 thermal imagery to compute LST and the associated land cover parameters viz; land surface emissivity (LSE), normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI) and normalized difference water index (NDWI). Landsat 8 TIRS band 10 & 11 (thermal bands) during 21 Oct. 2016, 22 Nov.2016, 24 Dec. 2016 and 09 Jan. 2017 were processed for LST analysis. However, band 5 & band 4 of the imagery was processed for NDVI, band 6 & band 5 for NDBI and band 2 & band 5 for NDWI analysis. LST has been derived from both the bands 10 &11 and validated by in-situ observations on the date and time of satellite overpass from the study area. Band 10 derived LST have shown much temperature difference while comparing with the in-situ observations. However, LST derived from band 11 found similar & close to the in-situ measurements. Relationship between band 11 results and in-situ observed measurements were developed, which has showing a strong correlation with (r² = 0.991). Land surface emissivity were also evaluated which shows variation in different land cover surfaces like vegetation, settlement, forest cover and water body. The study has proven that land surface temperature derived from satellite band 11 is the actual surface temperature of the study area.     

Probabilistic Analysis of Ground Surface Vibration Due to Train Movement, a Case Study on Tehran Metro Line 4

Ground surface vibration produced by moving train is one of the most important aspects in urban areas. The purpose of this study is the probabilistic analysis of ground surface vibration, which is generated by metro transportations. For this reason, Tehran metro line 4 is considered as a case study. In this paper, at first, a new procedure is used to simulate train dynamic load. In the second step, based on the variation of geomechanical properties and train characteristics in Tehran metro line 4, more than 60 numerical models are simulated. The results of numerical simulations are analyzed by multivariate statistical technique and an equation for prediction of peak particle velocity (PPV) in the ground surface is presented. In the next step, probabilistic analysis is done using Monte Carlo Simulation (MCS). Finally, sensitivity of input data on ground surface vibration is discussed and the impact of geomechanical properties and train characteristics on the surface vibration is considered. Based on the probabilistic analysis, PPV in the surface region of Tehran metro line 4 is <2.76?mm/s with 95?% probability.     

Wave data assimilation using a hybrid approach in the Persian Gulf

The main goal of this study is to develop an efficient approach for the assimilation of the hindcasted wave parameters in the Persian Gulf. Hence, the third generation SWAN model was employed for wave modeling forced by the 6-h ECMWF wind data with a resolution of 0.5°. In situ wave measurements at two stations were utilized to evaluate the assimilation approaches. It was found that since the model errors are not the same for wave height and period, adaptation of model parameter does not result in simultaneous and comprehensive improvement of them. Therefore, an approach based on the error prediction and updating of output variables was employed to modify wave height and period. In this approach, artificial neural networks (ANNs) were used to estimate the deviations between the simulated and measured wave parameters. The results showed that updating of output variables leads to significant improvement in a wide range of the predicted wave characteristics. It was revealed that the best input parameters for error prediction networks are mean wind speed, mean wind direction, wind duration, and the wave parameters. In addition, combination of the ANN estimated error with numerically modeled wave parameters leads to further improvement in the predicted wave parameters in contrast to direct estimation of the parameters by ANN.     

Modelling and predicting the spatial dispersion of skin cancer considering environmental and socio-economic factors using a digital earth approach

ABSTRACT

Almost all causative factors of diseases depend on location. The Digital Earth approach is suitable for studying diseases globally. Geospatial information systems integrated with statistical models can be used to model the relationship between a disease and its causative factors. Through modelling, the most important causative factors can be extracted and the epidemiology of the disease can be observed. In this paper, skin cancer (the most common type of cancer) has been modelled based on its causative factors, including climate factors, people's occupations, nutrition habits, socio-economic factors, and usage of chemical fertiliser. To fit the model, a data framework was first designed, and then data were gathered and processed. Finally, the disease was modelled using Generalised Linear Models (GLM), a statistical model based on the location of the factors. The results of this study identify the most important causative factors together with their relative priority. Furthermore, a model was used to predict the change in skin cancer occurrences caused by a change in one of its causative factors. This work illustrates the ability of the model to predict disease occurrence. Thus, by using this Digital Earth approach, skincancer can be studied in all the key countries around the world.     

Transient analysis of wave propagation in non‐homogeneous elastic unbounded domains by using the scaled boundary finite‐element method

The scaled boundary finite‐element method has been developed for the dynamic analysis of unbounded domains. In this method only the boundary is discretized resulting in a reduction of the spatial dimension by one. Like the finite‐element method no fundamental solution is required. This paper extends the scaled boundary finite‐element method to simulate the transient response of non‐homogeneous unbounded domains with the elasticity modulus and mass density varying as power functions of spatial coordinates. To reduce the number of degrees of freedom and the computational cost, the technique of reduced set of base functions is applied. The scaled boundary finite‐element equation for an unbounded domain is reformulated in generalized coordinates. The resulting acceleration unit‐impulse response matrix is obtained and assembled with the equation of motion of standard finite elements. Numerical examples of non‐homogeneous isotropic and transversely isotropic unbounded domains demonstrate the accuracy of the scaled boundary finite‐element method. Copyright © 2006 John Wiley & Sons, Ltd.