Medical and Dental Students’ Perception of Online Learning across Pakistan in the COVID Pandemic Era: A Review Article

The widespread lockdowns due to the COVID pandemic led to an abrupt shift in the medical education sector from a conventional to an online education system. The aim of this study was to determine the perception of medical and dental students regarding the acceptance of e-learning in Pakistan. A thorough literature search was conducted on PubMed and Google Scholar; six articles were included in this review. Perceptions of students regarding online medical learning were compiled. These perceptions were related to both non-clinical subjects as well as the attainment of clinical skills through online education. This review also highlights online educational challenges such as the level of student-teacher interaction, internet connectivity issues, and perception of fairness in online assessments. Online learning during COVID pandemic has not been a successful mode of learning for undergraduate medical and dental students across Pakistan. This specifically stands true for the learning of clinical and laboratory skills

Flood damage analysis for Kg. Datuk Dagang, Klang / Maureen Neging, Assoc. Prof. Dr. Wardah Tahir and Lydia Dundun Francis

Geographical Information System (GIS) application in flood management are largely utilised by the authorities around the world. GIS operations improve the efficiency of flood disaster monitoring and management in tropical countries like Malaysia. In this study, Geographic Information System (GIS) method is selected over other approaches namely; Penning-Rowsell & Chatterton and Narabeen Lagoon Floodplain Risk Management Plan. The study area, Kg. Datuk Dagang is located in area of South Klang. This area is near to the Klang River and has high potential of flooding. The focus of this study is to estimate flood damage at Kg. Datuk Dagang, Selangor on buildings and roads using Geographic Information System (GIS). This study has managed to quantify for flood damage costs for the lengths of inundation of 100 m through 300 m from the river. It is proven that the damage costs increase proportionally with the increase of the lengths of inundation

Coupling of Cellular Automata Urban Growth Model and HEC-HMS to Predict Future Flood Extents in the Upper Klang Ampang Catchment

Urban areas in tropical regions have higher flood risks due to the more frequent occurrence of intense convective rainfalls. The rising urbanization process have caused more surfaces to be covered with impervious materials, resulting in increased runoff. Modelling urban growth and its impact on urban hydrology is essential to ensure informed decision in the sustainable management and planning of cities in developing country like Malaysia. The aim of this research is to develop an integrated system for simulating future flood extents by coupling flood and urban growth models for the Upper Klang Ampang catchment which includes Kuala Lumpur capital city. HEC-HMS was used for flood modelling while SLEUTH cellular automata model was employed to analyse urban growth in the catchment. The results indicate that using historical satellite images from 1990, 2000, 2010 and 2016 as input data layers along with slope, land use, hill shade, road and restricted area layers, a slight increase in urban growth from 2020 until 2050 is predicted which can cause the peak discharge to increase by about 11-15%. The integrated flood estimation-urban growth system can be used as an effective tool in urban planning and management for the city

Coupling of Cellular Automata Urban Growth Model and HEC-HMS to Predict Future Flood Extents in the Upper Klang Ampang Catchment

Urban areas in tropical regions have higher flood risks due to the more frequent occurrence of intense convective rainfalls. The rising urbanization process have caused more surfaces to be covered with impervious materials, resulting in increased runoff. Modelling urban growth and its impact on urban hydrology is essential to ensure informed decision in the sustainable management and planning of cities in developing country like Malaysia. The aim of this research is to develop an integrated system for simulating future flood extents by coupling flood and urban growth models for the Upper Klang Ampang catchment which includes Kuala Lumpur capital city. HEC-HMS was used for flood modelling while SLEUTH cellular automata model was employed to analyse urban growth in the catchment. The results indicate that using historical satellite images from 1990, 2000, 2010 and 2016 as input data layers along with slope, land use, hill shade, road and restricted area layers, a slight increase in urban growth from 2020 until 2050 is predicted which can cause the peak discharge to increase by about 11-15%. The integrated flood estimation-urban growth system can be used as an effective tool in urban planning and management for the city

Analysis on the effect of land use changes on flooding using SCS method and GIS / Janmaizatulriah Jani, Wardah Tahir and Marfiah Abd. Wahid

The research investigated the effect of land use changes on flood estimation by focusing on a widely used method developed by the US Soil Conservation Services, namely SCS Curve Number method. This method was developed to estimate the peak flow and flood hydrograph based on several parameters, one of it is known as the Curve Number (CN). The CN which can be measured effectively using GIS is an indirect measure of soil potential storage and is dependent on the land use. The research explored the feasibility of the method to Malaysian catchments by firstly, analysed the CN in a small urban catchment of UiTM campus at Shah Alam and secondly compared the hydrograph calculated by the method with the observed ones. The results indicated a close proximity of the CN values obtained from the observed rainfall runoff and the values published by the US SCS (around 8 % difference). In addition, comparison between observed unit hydrographs and SCS unit hydrographs for the same rainfall duration indicated that the estimated values of peak discharge from the synthetic method were not very far from the observed values. Finally, it was shown that changes in land use especially during urbanization process would increase the peak flow, hence increase the possibility of flooding

Development of Rainfall Model using Meteorological Data for Hydrological Use

Abstract At present, research on forecasting unpredictable weather such as heavy rainfall is one of the most important challenges for equipped meteorological center. In addition, the incidence of significant weather events is estimated to rise in the near future due to climate change, and this situation inspires more studies to be done. This study introduces a rainfall model that has been developed using selected rainfall parameters with the aim to recognize rainfall depth in a catchment area. This study proposes a rainfall model that utilizes the amount of rainfall, temperature, humidity and pressure records taken from selected stations in Peninsular Malaysia and they are analyzed using SPSS multiple regression model. Seven meteorological stations are selected for data collection from 1997 until 2007 in Peninsular Malaysia which are Senai, Kuantan, Melaka, Subang, Ipoh, Bayan Lepas, and Chuping. Multiple Regression analysis in Statistical Package for Social Science (SPSS) software has been used to analyze a set of eleven years (1997 – 2007) meteorological data. Senai rainfall model gives an accurate result compared to observation rainfall data and this model were validating with data from Kota Tinggi station. The analysis shows that the selected meteorological parameters influence the rainfall development. As a result, the rainfall model developed for Senai proves that it can be used in Kota Tinggi catchment area within the limit boundaries, as the two stations are close from one another. Then, the amounts of rainfall at the Senai and Kota Tinggi stations are compared and the calibration analysis shows that the proposed rainfall model can be used in both areas.&nbsp

Hydro-meteorological flood simulation integrating radar rainfall with infoworks RS™ and GIS analysis / Zaizatul Zafflina Mohd Zaki, Wardah Tahir and Zuraisah Dollah

Thunderstorms and incessant monsoon rainfalls are the cause of many natural disasters including floods in Malaysia. The damages and losses due to floods are so immense that billions of ringgit has been spent for salvages and recoveries. Even though the government has provided various flood mitigation measures but flooding still occur frequently especially if the systems related are not designed properly. A non structural measure strategy is proposed to help to reduce these damages. Identification of flood prone areas would assist the relevant agencies in issuing a timely warning to victims in the affecting areas. In addition, for an integrated flood monitoring measure, the use of alternative rainfall measurement system such as weather radar is considered crucial to complement areas inaccessible to rain-gauges. In addition, by using develop model flood occurrence can be monitored more closely

Prognostic equation based on artificial neural network for quantitative rainfall forecast using numerical weather prediction model products / Wardah Tahir … [et al.]

In Malaysia, there are two types of flood that normally occur namely, monsoon flood and flash flood. Floods associated with the monsoonal rainfall events are common occurrences on the eastern coast of Peninsular Malaysia during the northeast monsoon season. Every year tropical monsoon storms result in severe flooding and causes enormous economic damage, social disruption, and sometimes loss of lives. Extreme monsoon storm weather phenomenon is the most destructive natural disaster afflicting Malaysia with respect to the cost, damages to properties and the area of extent (Keizrul and Chong, 2002). Given the sparseness of ground based observations, missing records and uneven distribution of the existing raingauge network, there is no adequate and timely information about rainfall pattern in Malaysia. An alternative source of quantitative precipitation information is from the Numerical Weather Prediction (NWP) model products. However, the accuracy of quantitative precipitation forecast produced by the Malaysian Meteorological Department (MMD) is still lacking even though significant progress has been made on the technical aspects (Low, 2006) . The study examined the effectiveness of two high resolution Numerical Weather Prediction (NWP) models namely the Fifth Generation Penn State/NCAR Mesoscale (MM5) and Weather Research and Forecasting (WRF) in predicting Quantitative Precipitation Forecast (QPF) over a tropical region. In this study, Kelantan River Basin has been selected as the case study to evaluate the performance and accuracy of precipitation forecast produced by the NWP models for monsoon flood events in the catchment area. Hourly and daily total rainfall data in year 2009 had been analysed. The rainfall events were further classified into low, moderate and heavy rainfall by using Drainage and Irrigation Department (DID) Malaysia standard. The performance and accuracy of the NWP model outputs against rainfall amount was verified using Root Mean Square Error (RMSE) and correlation (r). Notably, the statistical verification shows that there is quite strong correlation for 24 hourly rainfall forecast and the RMSE values are smaller for short range forecast (hourly up to 24 hourly). It is also noted that the longer the rainfall forecast duration, the higher probability of detection (POD) and the lesser probability of the false alarm ratio (FAR)

Mean Field Bias Correction to Radar QPE as Input to Flood Modeling for Malaysian River Basins

The occurrence of unprecedented flood events has increased in Malaysia recently. To mitigate the impact of the disaster, the National Flood Forecasting and Warning System (NaFFWS) has endeavored to improve the system so as to produce more accurate and reliable early warning to the public. The paper describes the use of radar composites from the radar network in Peninsular Malaysia to produce quantitative precipitation estimates (QPE) as input to the NaFFWS flood model. The processing of the raw radar data and the conversion of rain rate are described. The comparison between radar QPE and gauge rainfall shows that radar QPE underestimates the gauge rainfall, and the results are better at the western parts of Peninsular Malaysia compared to the eastern parts of Peninsular Malaysia. The comparison between Marshall Palmer (MP) and Rosenfeld (RF) conversion equations shows that there is not much difference in performance between the two equations. Both underestimate the rainfall, although RF estimates higher radar QPE for high rainfall intensity. The underestimated radar QPE is improved by calibration process via the Mean Field Bias (MFB) correction technique. The study introduced zoning into smaller regions for the MFB factors derivation.  Results indicated that the radar QPE is much improved after the calibration process. Simulation of flood event in December 2021 for the case study of Langat River basin indicates the improvement of correlation coefficient from 0.67 to 0.99 after the calibration process via MFB for smaller zones

Mean Field Bias Correction to Radar QPE as Input to Flood Modeling for Malaysian River Basins

The occurrence of unprecedented flood events has increased in Malaysia recently. To mitigate the impact of the disaster, the National Flood Forecasting and Warning System (NaFFWS) has endeavored to improve the system so as to produce more accurate and reliable early warning to the public. The paper describes the use of radar composites from the radar network in Peninsular Malaysia to produce quantitative precipitation estimates (QPE) as input to the NaFFWS flood model. The processing of the raw radar data and the conversion of rain rate are described. The comparison between radar QPE and gauge rainfall shows that radar QPE underestimates the gauge rainfall, and the results are better at the western parts of Peninsular Malaysia compared to the eastern parts of Peninsular Malaysia. The comparison between Marshall Palmer (MP) and Rosenfeld (RF) conversion equations shows that there is not much difference in performance between the two equations. Both underestimate the rainfall, although RF estimates higher radar QPE for high rainfall intensity. The underestimated radar QPE is improved by calibration process via the Mean Field Bias (MFB) correction technique. The study introduced zoning into smaller regions for the MFB factors derivation.  Results indicated that the radar QPE is much improved after the calibration process. Simulation of flood event in December 2021 for the case study of Langat River basin indicates the improvement of correlation coefficient from 0.67 to 0.99 after the calibration process via MFB for smaller zones