Application of Swat Hydrological Model with GIS Interface to Upper Bernam River Basin

Rising concern over the degradation of the environment due to rapid land development in recent years has created a need for watershed modeling. The Upper Bernam River Basin in South Perak and North Selangor, Malaysia was chosen for this study. This study was carried to evaluate the effectiveness of a GIS interface physically based hydrologic model (SWAT) in predicting surface runoff and sediment load from a basin scale watershed. The effects of land use changes on runoff and sediment loading rate were also studied. The data required for this study is the topographical, hydrometeorological, soil, and the land use data. All of them are integrated in a GIS in tabular, vector and grid formats. The land use data in this study were derived from Landsat TM images. These images were enhanced and classified using a combination of different classification strategies. The classified land use maps compares reasonably well with the map showing broad vegetation types of the river basin with an accuracy of 95%. Due to recent rapid land use changes, the model was run in a short term basis. The results from model application and statistical analysis show that SW AT generally does a good job in predicting both runoff flow and sediment load with a an average gap of 22% and 34% respectively between observed and predicted results. The exception is for those days with very heavy rainfall (> 35 mm/day), SWAT seriously overestimated runoff. Results from historical data, trend analysis, and calculated runoff rate and sediment loading rate due to open area have also shown the close relationship between surface runoff, sediment load and open area downstream of the upper river basin. It is found that the average increment of sediment loading rate for the study area ranges from 1.47 to 2.06 tonnes per millimeter of rainfall for each kilometer-square increase of open areas

Applications of GIS and remote sensing in the hydrological study of the Upper Bernam River Basin, Malaysia

Rising concern over the degradation of the environment, such as erosion and sediment loads, warrants the integration of the complex and dispersed geographical data sets. This paper describes the use of Geographic Information System (GIS) and remote sensing for assessing the impact of land use changes to water turbidity in multiple watersheds. In this study, necessary data sets representing land uses, hydrology, weather, soils, elevation, and surface characteristics were integrated in a GIS in tabular, vector and grid formats. The land use maps that were derived from Landsat-5 TM imagery using a combination of different classification strategies gave an average accuracy of 95 %. Results from data analysis had shown that there exists a close relationship existed between the extent of open area and sedimentation loading rate. However, the sediment loading rates were found to be non-linear ranging from 1.47 to 2.13 tonnes per millimeter of rainfall for each kilometer-square increase of open areas, depending on their location of open areas with respect to factors such as availability of sediment, soil type, slope length, and slope steepness etc

Ecological Sanitation, Sustainable Strategy as an Alternative Urban Water Source

Water supply is one of the basic infrastructure requirements. Water treatment and supply are often granted a much higher priority than wastewater collection and treatment, despite the fact that wastewater deserves a greater emphasis due to the impact of its poor management has on public health. A new commitment to give wastewater the same priority as water supply is a very positive development. A pilot project of greywater ecological treatment is established in Kuching city since 2003. Such treatment facility opens up an opportunity of wastewater reclamation for reuse as secondary sources of water for non-consumptive purposes. This paper aims in exploring the potential of the intended purposes in the newly developed ecological treatment project. By utilizing the Wallingford Software model, InfoWorks WS (Water Supply) is employed to carry out a hydraulic modeling of a hypothetical greywater recycling system as an integrated part of the Kuching urban water supply, where the greywater is treated, recycled and reused in the domestic environment. The modeling efforts had shown water saving of more than 50% from the investigated system reinstating that the system presents an alternative water source worth-investing in an urban environment

Modelling the flood vulnerability of deltaic Kuching City, Malaysia

The main objective of this writing is to present a practical way to envisage the flood vulnerability in deltaic region, particularly on the concern of sea level rise. Kuching city of Malaysia is established on banks of Sarawak River, 30 km from the sea. Therefore, it is subjected to fluvial and tidal floods. Kuching Bay experiences the highest King Tides in Southeast Asia region. These tide magnitudes could be a glimpse of future sea level rise. By means of modelling these tides, it provides an understanding and preparation for the impacts of sea level rise on the flood mitigation infrastructures and the city itself. The modelling efforts had created an illustration that a 10% rise in tide levels would result in increase of flooding areas up to 6% relative to existing tide levels

Applications of GIS and Remote Sensing In The Hydrological Study Of The Upper Bernam River Basin, Malaysia

Rising concern over the degradation of the environment, such as erosion and sediment loads, warrants the integration of the complex and dispersed geographical data sets. This paper describes the use of Geographic Information System (GIS) and remote sensing for assessing the impact of land use changes to water turbidity in multiple watersheds. In this study, necessary data sets representing land uses, hydrology, weather, soils, elevation, and surface characteristics were integrated in a GIS in tabular, vector and grid formats. The land use maps that were derived from Landsat-5 TM imagery using a combination of different classification strategies gave an average accuracy of 95 %. Results from data analysis had shown that there exists a close relationship existed between the extent of open area and sedimentation loading rate. However, the sediment loading rates were found to be non-linear ranging from 1.47 to 2.13 tonnes per millimeter of rainfall for each kilometer-square increase of open areas, depending on their location of open areas with respect to factors such as availability of sediment, soil type, slope length, and slope steepness etc

Application of artificial intelligence techniques for the verification of pile capacity at construction site: A review

In the construction industry, piling is part of foundation system that supports the constructed structures. There are various types of piles that can be designed and constructed such as bored piles, micropiles, spun piles, and pre-cast reinforced concrete square piles. Ground conditions and costs are two main factors to decide the piling system to adopt in the construction. Prior to the construction of piling, theoretical design of the piles is required to identify the capacity of pile based on the subsurface investigation works information

Applications of two neuro-based metaheuristic techniques in evaluating ground vibration resulting from tunnel blasting

Peak particle velocity (PPV) caused by blasting is an unfavorable environmental issue that can damage neighboring structures or equipment. Hence, a reliable prediction and minimization of PPV are essential for a blasting site. To estimate PPV caused by tunnel blasting, this paper proposes two neuro-based metaheuristic models: neuro-imperialism and neuro-swarm. The prediction was made based on extensive observation and data collecting from a tunnelling project that was concerned about the presence of a temple near the blasting operations and tunnel site. A detailed modeling procedure was conducted to estimate PPV values using both empirical methods and intelligence techniques. As a fair comparison, a base model considered a benchmark in intelligent modeling, artificial neural network (ANN), was also built to predict the same output. The developed models were evaluated using several calculated statistical indices, such as variance account for (VAF) and a-20 index. The empirical equation findings revealed that there is still room for improvement by implementing other techniques. This paper demonstrated this improvement by proposing the neuro-swarm, neuro-imperialism, and ANN models. The neuro-swarm model outperforms the others in terms of accuracy. VAF values of 90.318% and 90.606% and a-20 index values of 0.374 and 0.355 for training and testing sets, respectively, were obtained for the neuro-swarm model to predict PPV induced by blasting. The proposed neuro-based metaheuristic models in this investigation can be utilized to predict PPV values with an acceptable level of accuracy within the site conditions and input ranges used in this study

Deep learning model on rates of change for multi-step ahead streamflow forecasting

Water security and urban flooding have become major sustainability issues. This paper presents a novel method to introduce rates of change as the state-of-the-art approach in artificial intelligence model development for sustainability agenda. Multi-layer perceptron (MLP) and deep learning long short-term memory (LSTM) models were considered for flood forecasting. Historical rainfall data from 2008 to 2021 at 11 telemetry stations were obtained to predict flow at the confluence between Klang River and Ampang River. The initial results of MLP yielded poor performance beneath normal expectations, which was R ¼ 0.4465, MAE ¼ 3.7135, NSE ¼ 0.1994 and RMSE ¼ 8.8556. Meanwhile, the LSTM model generated a 45% improvement in its R-value up to 0.9055. Detailed investigations found that the redundancy of data input that yielded multiple target values had distorted the model performance. Qt was introduced into input parameters to solve this issue, while Qtþ0.5 was the target value. A significant improvement in the results was detected with R ¼ 0.9359, MAE ¼ 0.7722, NSE ¼ 0.8756 and RMSE ¼ 3.4911. When the rates of change were employed, an impressive improvement was seen for the plot of actual vs. forecasted flow. Findings showed that the rates of change could reduce forecast errors and were helpful as an additional layer of early flood detection

A deep dive into tunnel blasting studies between 2000 and 2023-A systematic review

Tunnel blasting is a common practice used to excavate rock formations. Many academic research articles have emerged and burgeoned in the field of tunnel blasting. These articles are dedicated to investigating objectives such as blasting vibration, rock damage, and vibration energy individually. However, no systematic analysis is conducted to consolidate and analyze the findings from the literature related to tunnel blasting. This study addresses this by offering a systematic review to explore the state of tunnel blasting research. A science mapping approach using bibliometric analysis is employed to examine 144 peer-reviewed journal articles. The review identified the most influential journals, institutions, researchers, and articles on tunnel blasting research, and it also summarizes the research hotspots of tunnel blasting according to the cluster analysis of research keywords. Findings in this review revealed the contribution of two leading journals, three leading institutions, and three leading researchers on the research of tunnel blasting. Moreover, four research keywords, i.e., blasting vibration, numerical simulation, rock damage, and overbreak, were identified as the research hotspots in 2018–2023. Finally, this review also speculated the future research directions/avenues of tunnel blasting, aiming to bring to light the deficiencies in the currently existing research and provide paths for future research

Optimal Design of Subsurface Conveyance System Based Bio-Ecological Drainage System Simulation

As urbanization grows in size, the problems of flash floods and water pollution are expected to worsen, so viable and cost-effective solutions are essential to reduce the impacts. The Bio-Ecological Drainage System (BIOECODS) was developed to demonstrate the use of ‘control at source’ approaches to urban stormwater management. This research attempts to analyse the optimal design of a subsurface conveyance system (modular conduit) that is available in a case study with a BIOECOD project. This modelling exercise uses a novel technique to merge the surface and online subsurface flow. Through the InfoWorks SD software, the BIOECODS model has been calibrated and validated using rainfall events with different intensities, rainfall amounts, and durations. The developed model was then further analysed to obtain the optimum design of online subsurface modular conduit in the BIOECODS project, according to different scenarios. The results show that the subsurface modular conduit in the study area has an optimal size of 0.45 m height and is capable of attenuating peak flow at the downstream outlet by more than 60%. It is expected that the innovative modelling technique and the optimum design of an online subsurface conveyance system can be of interest to the community