Xiao Li^*, Junxiang Liu, Weinan Fan, Shiying Xu

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.1, pp. 1-2, 2025, DOI:10.32604/icces.2025.012284

Abstract Flooding is one of the most common types of natural hazards leading to wide-spread disturbances and damages to human communities and natural environment across the world. Flood forecasting is an effective means to provide timely hazard information to relevant government decision-makers and practitioners as well as those residents at risk, which plays an important role in flood risk reduction. A complete flood forecasting system normally includes at least two components, that is precipitation predictions and a hydrological or hydraulic model for flooding processes simulation. However, the current flood forecasting especially for urban floods face obvious… More >

Muazu Dantala Zakari^1,2,*, Md. Rowshon Kamal^1,*, Norulhuda Mohamed Ramli¹, Balqis Mohamed Rehan³, Mohd Syazwan Faisal Bin Mohd⁴

Revue Internationale de Géomatique, Vol.34, pp. 487-511, 2025, DOI:10.32604/rig.2025.065835 - 29 July 2025

Abstract Understanding trends in rainfall and temperature projections is critical for assessing climate change impacts, managing water resources, mitigating disaster risks, and guiding sustainable agricultural and infrastructure planning. This study investigates projected changes in temperature and rainfall in the Upper Bernam River Basin (UBRB), Malaysia, using ten Global Climate Models (GCMs) from CMIP6 across four scenarios (SSP126, SSP245, SSP370, and SSP585). Downscaling was conducted with the Climate-Smart Decision Support System (CSDSS) for the baseline period (1985–2014) and for future periods: 2020s, 2040s, 2060s, and 2080s. Results indicate a consistent warming trend, with maximum temperatures projected to… More >

Shanshan Tang^1,2,*, Zhanbin Li^3,4, Xubin Zhu^1,2, Peng Li³, Zhaoyang Feng^1,2, Guoliang Yang^1,2, Huake Chang^1,2, Zefeng Che^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.4, pp. 819-831, 2025, DOI:10.32604/fdmp.2025.057605 - 06 May 2025

Abstract The particle size distribution plays a crucial role in the transportation and deposition of eroded sediments. Gaining insights into the related sorting mechanism can significantly enhance our understanding of such processes. In this study, sand-covered slopes were examined. A controlled indoor rainfall simulation was conducted on loess slopes with a 12° incline and a rainfall intensity of 1.5 mm/min. These slopes were then covered with sand layers of varying thicknesses—0.5, 1.0, and 1.5 cm—to observe their effects. The findings have revealed that as the thickness of the sand cover increases, the content of sediment particles… More >

Ramya Nemani¹, G. Jose Moses², Fayadh Alenezi³, K. Vijaya Kumar⁴, Seifedine Kadry^5,6,7,*, Jungeun Kim⁸, Keejun Han⁹

Computer Systems Science and Engineering, Vol.47, No.1, pp. 919-935, 2023, DOI:10.32604/csse.2023.034213 - 26 May 2023

Abstract Statistics are most crucial than ever due to the accessibility of huge counts of data from several domains such as finance, medicine, science, engineering, and so on. Statistical data mining (SDM) is an interdisciplinary domain that examines huge existing databases to discover patterns and connections from the data. It varies in classical statistics on the size of datasets and on the detail that the data could not primarily be gathered based on some experimental strategy but conversely for other resolves. Thus, this paper introduces an effective statistical Data Mining for Intelligent Rainfall Prediction using Slime… More >

El-Sayed M. El-kenawy¹, Abdelaziz A. Abdelhamid^2,3, Fadwa Alrowais^4,*, Mostafa Abotaleb⁵, Abdelhameed Ibrahim⁶, Doaa Sami Khafaga⁴

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2885-2899, 2023, DOI:10.32604/csse.2023.034206 - 21 December 2022

Abstract Rainfall plays a significant role in managing the water level in the reservoir. The unpredictable amount of rainfall due to the climate change can cause either overflow or dry in the reservoir. Many individuals, especially those in the agricultural sector, rely on rain forecasts. Forecasting rainfall is challenging because of the changing nature of the weather. The area of Jimma in southwest Oromia, Ethiopia is the subject of this research, which aims to develop a rainfall forecasting model. To estimate Jimma’s daily rainfall, we propose a novel approach based on optimizing the parameters of long… More >

Shaojie Feng^*, Leipeng Liu, Chen Gao, Hang Hu

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.5, pp. 1189-1201, 2023, DOI:10.32604/fdmp.2023.023637 - 30 November 2022

Abstract The present study considers the damage mechanisms and the rainfall infiltration process responsible for landslide phenomena which originate from accumulation slopes. Accordingly, a physical test model is developed for different slopes and different rainfall conditions. Moreover, a three-dimensional laser scanner and a camera are used to monitor the slope erosion and the landslide dynamic evolution. Using this approach, the time variation curves of volumetric water content, pore water pressure, soil pressure, slope deformation, and damage are determined. The results show that under similar conditions, similar trends of the pore water pressure are achieved for different More > Graphic Abstract

Mohammad Alamgeer¹, Amal Al-Rasheed², Ahmad Alhindi³, Manar Ahmed Hamza^4,*, Abdelwahed Motwakel⁴, Mohamed I. Eldesouki⁵

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2725-2738, 2023, DOI:10.32604/cmc.2023.029163 - 31 October 2022

Abstract Data mining process involves a number of steps from data collection to visualization to identify useful data from massive data set. the same time, the recent advances of machine learning (ML) and deep learning (DL) models can be utilized for effectual rainfall prediction. With this motivation, this article develops a novel comprehensive oppositional moth flame optimization with deep learning for rainfall prediction (COMFO-DLRP) Technique. The proposed CMFO-DLRP model mainly intends to predict the rainfall and thereby determine the environmental changes. Primarily, data pre-processing and correlation matrix (CM) based feature selection processes are carried out. In More >

Wen Zhang^1,2, Wei Fang^1,3,*, Xuelei Jia^1,2, Victor S. Sheng⁴

Journal of Quantum Computing, Vol.4, No.1, pp. 23-37, 2022, DOI:10.32604/jqc.2022.026975 - 12 August 2022

Abstract In order to solve the rainfall estimation error caused by various noise factors such as clutter, super refraction, and raindrops during the detection process of Doppler weather radar. This paper proposes to improve the rainfall estimation model of radar combined with rain gauge which calibrated by common Kalman filter. After data preprocessing, the radar data should be classified according to the precipitation intensity. And then, they are respectively substituted into the improved filter for calibration. The state noise variance and the measurement noise variance can be adaptively calculated and updated according to the input observation More >

Mahmoud Ragab^1,2,3,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 4143-4155, 2022, DOI:10.32604/cmc.2022.027075 - 29 March 2022

Abstract Rainfall prediction becomes popular in real time environment due to the developments of recent technologies. Accurate and fast rainfall predictive models can be designed by the use of machine learning (ML), statistical models, etc. Besides, feature selection approaches can be derived for eliminating the curse of dimensionality problems. In this aspect, this paper presents a novel chaotic spider money optimization with optimal kernel ridge regression (CSMO-OKRR) model for accurate rainfall prediction. The goal of the CSMO-OKRR technique is to properly predict the rainfall using the weather data. The proposed CSMO-OKRR technique encompasses three major processes More >

Ganapathy Pattukandan Ganapathy¹, Kathiravan Srinivasan², Debajit Datta², Chuan-Yu Chang^3,4,*, Om Purohit⁵, Vladislav Zaalishvili⁶, Olga Burdzieva⁶

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6333-6350, 2022, DOI:10.32604/cmc.2022.023254 - 14 January 2022

Abstract A substantial amount of the Indian economy depends solely on agriculture. Rainfall, on the other hand, plays a significant role in agriculture–while an adequate amount of rainfall can be considered as a blessing, if the amount is inordinate or scant, it can ruin the entire hard work of the farmers. In this work, the rainfall dataset of the Vellore region, of Tamil Nadu, India, in the years 2021 and 2022 is forecasted using several machine learning algorithms. Feature engineering has been performed in this work in order to generate new features that remove all sorts… More >