•Stormwater drainage system as infrastructure protecting cities from heavy rainfall.•Problems in designing stormwater drainage due to limited short-term rainfall data.•The STORAGE model as an ...effective tool for determining short-duration rainfall.•The STORAGE model as a tool supporting the determination of urban flood areas.•Application the STORAGE model for the urban landscape planning.
In this investigation, we evaluated the applicability of the Stochastic Rainfall Generator (STORAGE) as a data source for deriving design hydrographs in urban catchments. This assessment involved a comparison with design rainfall calculated using Intensity-Duration-Frequency (IDF) curves derived from observed time-series data. The resulting design rainfall values from both methods were incorporated into a hydrodynamic model of the storm sewer network. To simulate peak discharge and flood areas, the Storm Water Management Model (SWMM) program was employed in conjunction with SCALGO. Our findings indicate that design rainfall values obtained from the STORAGE model exceeded those derived from the observed time-series, with a more pronounced difference for shorter rainfall durations. Simulations further revealed that peak runoff disparities between the two approaches were most evident at a 0.10 probability of exceedance compared to a 0.01 probability. Hydrodynamic simulations demonstrated that the flooding volume induced by design rainfall based on the STORAGE model surpassed that resulting from observed rainfall. Across all events, both the flooding volume and area from STORAGE were consistently greater than those derived from IDF curves. The integration of the SWMM model with the SCALGO application introduced a novel functionality for dynamic visualization of flooding, offering valuable insights for effective flood management in urban areas.
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Geomorphic Flood Area is a plugin used to classify flood-prone areas using a linear binary classifier method based on Geomorphic Flood Index. However, key determinant data in this classification are ...geographic data like Digital Elevation Model. But other determinant factors are neglected in the Geomorphic Flood Area plugin. For example, land cover data. The purpose of this research is to develop the Geomorphic Flood Area by adding land cover as a determinant factor. This research was conducted by finding the runoff coefficient value based on land cover, then adding the runoff coefficient value to the Geomorphic Flood Index calculation. The result shows there is an increase between F1-score of the Geomorphic Flood Area plugin and F1-score of the Geomorphic and Land Cover Flood Area plugin. The conclusion of this research is F1-score of the Geomorphic and Land Cover Flood Area plugin is more accurate in flood-prone area classification because if flow accumulation data that is used in Geomorphic Flood Index calculation, multiplied by runoff coefficient value, flow accumulation data becomes more accurate.
•A novel EICP-lignin treatment for soil was proposed for the modification of silt in the Yellow River flood area.•The optimum lignin content was approximately 5% for the EICP-lignin treatment of ...soil.•The relationships between the strength parameters and the lignin level in the treatment were investigated.
A novel method that combines enzyme-induced carbonate precipitation (EICP) and lignin was proposed to improve the mechanical properties of silt in the Yellow River flood area. The silt in this area is characterized by poor particle gradation, weak cohesion and low strength. It is essential to focus on the modification of silt by environmentally friendly methods. The work described in this paper investigated the unconfined compressive strength (UCS), elastic modulus, cohesion, internal friction angle and microstructure of EICP-lignin treated silt. A series of laboratory experiments was conducted, including the unconfined compressive strength (UCS) test and consolidated undrained (CU) triaxial test. The results proved that the EICP-lignin treatment enhanced silt obtained from the Yellow River flood area. All the strength parameters increased and then decreased with increasing lignin content, and their values were optimum for approximately 5% lignin. Specifically, the optimum UCS strength, cohesion and internal friction angle improved to approximately 5, 10, and 3 times those of untreated silt. In addition, the strength parameters gradually increased with curing time. Microstructure analyses were used to illustrate the physical basis for the improvement in strength with increasing aggregation of lignin and calcite.
The diversity of soil types in Indonesia causes the design of development to have to adjust its planning carefully in accordance with the type of soil, so that it is necessary to test the mechanical ...properties such as porosity, pore number, and density. In the city of Padang, there are several areas often flooded (flood). This associative study was conducted to reveal the relationship of the influence of porosity and permeability of the soil which is often inundated in the city of Padang. This research was conducted in May-June 2018 in the Soil Mechanics Labor Department of Civil Engineering FT UNP with soil samples in the area of Kampung Jambak Lubuk Buaya, Padang City. The analysis technique used the Microsoft Excel application to present data into simpler information and analyze the relationship using the Pearson Product Moment formula. The results of the study obtained soil porosity values of 63.53% (large porosity). Soil permeability value is 0.0000633 cm/second or 0.23 cm/hour (very slow). The effect of porosity on soil permeability in the Kampung Jambak Lubuk Buaya Padang City is 3.37% with t-count smaller than t-table or 0.324 <3.182 or insignificant.
Deep learning algorithms show good prospects for remote sensing flood monitoring. They mostly rely on huge amounts of labeled data. However, there is a lack of available labeled data in actual needs. ...In this paper, we propose a high-resolution multi-source remote sensing dataset for flood area extraction: GF-FloodNet. GF-FloodNet contains 13388 samples from Gaofen-3 (GF-3) and Gaofen-2 (GF-2) images. We use a multi-level sample selection and interactive annotation strategy based on active learning to construct it. Compare with other flood-related datasets, GF-FloodNet not only has a spatial resolution of up to 1.5 m and provides pixel-level labels, but also consists of multi-source remote sensing data. We thoroughly validate and evaluate the dataset using several deep learning models, including quantitative analysis, qualitative analysis, and validation on large-scale remote sensing data in real scenes. Experimental results reveal that GF-FloodNet has significant advantages by multi-source data. It can support different deep learning models for training to extract flood areas. There should be a potential optimal boundary for model training in any deep learning dataset. The boundary seems close to 4824 samples in GF-FloodNet. We provide GF-FloodNet at
https://www.kaggle.com/datasets/pengliuair/gf-floodnet
and
https://pan.baidu.com/s/1vdUCGNAfFwG5UjZ9RLLFMQ?pwd=8v6o
.
The risk of flooding has become more significant in many parts of the world due to climate change and increased urbanization. Flood has devastating effects on infrastructure, and communities, causing ...damage to property and loss of life. Simulation of flood extent in a particular area is done by using various mathematical models, hydrologic‐hydraulic models, and datasets. Flood modeling using hydraulic‐hydrological models has many errors due to the lack of hydraulic‐hydrologic data and insufficient statistical period length. This study demonstrates the fact that the geomorphological index (GI) method, which is based on the digital elevation model and requires little hydraulic‐hydrologic data, is an effective method for flood modeling. Flood zoning based on GI was performed within the Kashafroud basin with 25, 100, and 200‐year return periods by using geomorphic flood area (GFA) plugin in QGIS software. The true positive rates were 0.985, 0.989, and 0.992, respectively, which showed the high accuracy of flood zoning based on the GI method. Here proposed method showed that using the GFA plugin offers a good way for the flood risk assessment in a basin with the lack of measured data as an alternative to the hydraulic‐hydrological methods.
In recent years, super-long and super-large diameter pipe piles have been gradually applied to the foundation in the Yellow River flood area. However, its bearing mechanism is not clear, especially ...the unclear bearing characteristics of the pile under the eccentric state, which limits its application and development. In this regard, this paper uses the method of combining field test and numerical simulation to analyze the bearing characteristics of super-long and super-large diameter pipe piles under different pile lengths, different pile diameters, different diameter-thickness ratios, and different offsets. Combined with the specific deviation form of the pipe pile, the calculation formula of the vertical ultimate bearing capacity of the super-long and super-long diameter pipe pile in the Yellow River flooding area under the influence of the construction effect is modified. The results show that when the length of the pipe pile changes, the vertical bearing capacity changes the most, and the vertical ultimate bearing capacity of the pipe pile increases linearly with the increase of the length of the pipe pile. When the wall thickness of the pipe pile increases, the vertical bearing capacity increases approximately linearly, but the reduction of the pile displacement decreases exponentially. The greater the deflection of the pipe pile, the smaller the vertical ultimate bearing capacity. When the deflection of the pipe pile is greater than 0.35°, the vertical ultimate bearing capacity decreases rapidly with the increase of the deflection. On the basis of the traditional formula, considering the deviation form of the pipe pile, the reduction coefficient of the bearing capacity correction formula of the super-long and super-large diameter pipe pile is proposed, and the correction formula is compared with the field example. It is proved that the formula can accurately calculate the bearing capacity of the super-long and super-large diameter pipe pile. The research results of this paper are of great significance to the application and promotion of super-long and super-large diameter pipe piles in the Yellow River flood area and the evaluation of vertical ultimate bearing capacity. At the same time, the research results of this paper can also provide a reference for the study of bearing characteristics of super-long and super-large diameter pipe piles in other foundations.
Abstract
Building architecture in urban areas is very important, especially for settlements that are at risk of flooding. Architechnopreneurship is a residential architectural design concept that can ...provide comfort even in a flooded area, has a concept that utilizes technology, provides insight into entrepreneurial values and provides education for residents in mitigating flood risk. This study aims to obtain an overview of the Jakarta society’s perspectives on architechnopreneurship design. The research method used is the Neuroresearch method, a mixed method which has three stages of research, namely exploratory, explanatory, and confirmatory research. The results showed that the Architechnopreneur building design concept presented was still not in accordance with the views of the people of Jakarta significantly at α <0.05. These results provide input for changes and improvements to architechnopreneurship design in accordance with community expectations.
Population growth and tourism exert tremendous pressures on the lakeshore habitats of Lake Constance. However, great efforts have been put into shore restoration measures over the last few decades to ...generate a more natural state. These activities, and the importance of the littoral zone as a UNESCO world cultural heritage, increase the need for comprehensive shore typology data to provide a decision base for littoral zone management. Our approach comprises the delineation and classification of different regions of the littoral zone based on morphological features as a first step towards a comprehensive shore typology. We applied a combination of spatial and statistical analyses to classify the Lake Constance shore, based on width and slopes at different depths. We classified ten different hydro-morphological shore types, each representing homogenous areas in the littoral zone separated into sublittoral zones and potential flood areas. Validation of the typology revealed that the shorelines with steep inclinations or embankments were the shore types most likely to erode. Our findings show that the typology based on morphological features can be a useful predictor and method to link the structures and processes that interact in the shore area with the shore morphology.
Synthetic aperture radar (SAR) satellite has been widely applied in real-time flood monitoring as that they are not affected by extreme weather conditions. However, there is no automatic method to ...quickly and accurately extract flood areas with SAR satellite images. In this article, a UNet combined with the attention mechanism (UNet-CBAM) method has been proposed for extracting flood submerged areas, and both Longgan Lake and Dahuchi in Poyang Lake Basin are selected as the test sites. Based on the polarization characteristics of two Sentinel-1A data of Poyang Lake, both UNet and UNet-CBAM extraction methods are utilized to extract the flood areas, respectively. Compared with traditional SAR image water extraction methods, simulation results demonstrate that UNet can obtain more satisfactory results in recall, precision, and <inline-formula><tex-math notation="LaTeX">{F}_1</tex-math></inline-formula>-parameter, but it has no capability to guarantee continuity in edges and small bodies of water. Moreover, our proposed UNet-CBAM method can further improve recall, precision, and <inline-formula><tex-math notation="LaTeX">{F}_1</tex-math></inline-formula>-parameter, respectively. Specifically, when compared with UNet, its recall is increased by 0.8% and 1.2% while <inline-formula><tex-math notation="LaTeX">{F}_1</tex-math></inline-formula>-parameter is improved by 0.6% and 0.8%, respectively, in the two test sites.
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