Taipei has been ranked as the most vulnerable city to a wider combination of risks. Although the Special Education Law addresses the consideration of disaster preparedness for students with disabilities enrolling in Special Education Schools, more attention needs to be given to the far larger number of students with disabilities enrolling in normal schools. These schools need to consider the care for students with different types and severe degrees of disabilities. The aim of the research is to investigate challenges of earthquake preparation and response for students with different severe degrees of disabilities who enrol in the special education classes in general primary schools. The objectives of the research include the following: (1) investigating the challenges and requirements for support of students with different severe degrees of disabilities; (2) examining the need and support for students with different degrees of disabilities during the earthquake response process; and (3) exploring the best practice in the curriculum building for students with different severity of disabilities. The purposive sampling was used to select four primary schools in Taipei as participant groups in the research. The research team used semi-structured interviews to interview eight participants: one special education class teacher and one administrator of each school were invited. Findings include the following: (1) ensuring the appropriate design of physical environment for earthquake response in schools, including rapid response, evacuation, and assembly points for students with different severe degrees of disabilities; (2) proposing suitable staff to student ratio to be planned for the response phase; (3) identifying the appropriate individualised curriculum and learning objectives to suit students with different severe degrees of disabilities.

The relationship between Taiwan’s groundwater resources recharge strategy and flood disasters is significant. The adaptation strategies of traditional urbanization areas simulate the spatial distribution of permeable pavements under different rainfall intensities that affect surface runoff and infiltration. Since there are many parameters of the Stormwater Management Model set in different low-impact development modules, this study refers to transform the inundation to groundwater recharge. In this study, we simulated the spatial distribution multi-advantages of the JW ecological technology under short-duration intense rainfall events. The results show that the application of JW ecological technology can effectively increase groundwater resources by 64.1% through infiltration and reduce economic losses by about NTD 1.25 million under the rainfall event of 112 mm/1 h. The infiltration replenishment amount was about 61%, which could reduce the economic loss of NTD 4.4 million under the rainfall event of 350 mm/6 h. Thus, applying JW ecological technology in a highly developed urbanization area can effectively reduce surface runoff and economic losses. At the same time, the issue of water resources was adapted by the groundwater recharge.

This study proposes a hybrid grey model for forecasting annual maximum daily rainfall in order to determine long-term hydrological system trends. The proposed model uses an integral form of background value to improve accuracy, and applies two residual operators, the Fourier series and the exponential smoothing technique, to correct periodic and stochastic errors. The annual maximum daily rainfall measured by 5 stations around Taiwan are used to validation the proposed model. The performance of the proposed hybrid grey model is compared with those of the autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) models. By evaluation of different indicators, it is shown that the proposed model outperforms both compared models. With more precise information, the proposed model will allow government officials and civil engineering-related industries to better prepare for heavy rainfall, averting potential disasters.

Predicting the effects of changes in dissolved input concentration on the variability of discharge concentration at the outlet of the catchment is essential to improve our ability to address the problem of surface water quality. The goal of this study is therefore dedicated to the stochastic quantification of temporal variability of concentration fields in outflow from a catchment system that exhibits linearity and time invariance. A convolution integral is used to determine the output of a linear time-invariant system from knowledge of the input and the transfer function. This work considers that the nonstationary input concentration time series of an inert solute to the catchment system can be characterized completely by the Langevin equation. The closed-form expressions for the variances of inflow and outflow concentrations at the catchment scale are derived using the Fourier–Stieltjes representation approach. The variance is viewed as an index of temporal variability. The closed-form expressions therefore allow to evaluate the impacts of the controlling parameters on the temporal variability of outflow concentration.

In large-scale seismic scenarios, the operational continuity of evacuation shelters is frequently compromised by limited governmental capacity, necessitating the strategic integration of Disaster Relief Volunteers (DRVs). Traditional assessments often rely on coarse regional aggregates, overlooking the critical spatial mismatch between volunteer availability and localized demand. In this study, a high-resolution, spatially explicit framework was developed to evaluate urban operational resilience in New Taipei City. Utilizing the TERIA platform, a nocturnal magnitude 6.8 Shanjiao Fault rupture was simulated, identifying that approximately 460,000 individuals would be affected, with shelter demand reaching 300,000—double the current capacity. Service areas were delineated using ArcGIS Network Analyst (Dijkstra’s algorithm) based on an 800 m walking threshold, further refined by a secondary assignment rule to redistribute “shadow demand” from peripheral populations. Quantitative analysis of the newly introduced “DRV shortfall” metric reveals that 74% of shelters (148/200) face concurrent spatial and manpower saturation. Notably, 42 analysis units lack resident volunteers entirely, with the most severe shortfall magnitude reaching 361 DRVs at a single “high-risk convergence node”. These results uncover a profound deficiency in urban disaster resilience driven by significant spatial mismatch. This research contributes a three-fold advancement: (i) the high-resolution coupling of volunteer residential data with dynamic demand patterns; (ii) the formalization of the DRV shortfall as a standardized metric for resource adequacy; and (iii) the formulation of a strategic policy framework for multi-shelter activation sequencing, “Support Hub” designation, and resource synchronization in hyper-dense urban environments.