Over the past decades, China has experienced severe compound natural disasters, such as extreme rainfalls, which have led to significant losses. In response to the challenges posed by the lack of a clear investigation process and inadequate comprehensiveness in evaluating the natural disaster chains, this study proposes a comprehensive retrospective simulation strategy for emergency investigation and simulation of heavy rainstorm–flash flood–debris flow chain disasters at the county–town level. The primary aim is to avert potential new chain disasters and alleviate subsequent disasters. This study combines emergency investigation efforts with hydrodynamic models to digitally simulate and analyze compound chain disasters triggered by an extreme rainfall event in the Haihe River regional area, specifically Gaoyakou Valley, Liucun Town, Changping District, Beijing, in July 2023, along with potential new disasters in adjacent regions. The findings indicate that the heavy rainstorm chain disaster on “7.29” resulted from a complex interplay of interrelated natural phenomena, including flash floods, debris flows, urban floodings, and river overflows. Hantai Village has experienced flash flood and debris flow events at different times in this area. Should the rainfall volume experienced in Liucun Town be replicated in the Ming Tombs Town area, approximately 6.2 km² of land would be inundated, leading to damages to 458 residences and impacting around 240 ha of agricultural land. The anticipated release of floodwater from the reservoir would lead to significant impacts on downstream residents and roads. Our research can improve the efficacy of emergency investigations and assessments, which in turn can help with the management and reduction of disaster risks at the grassroots level.

The essence of post-disaster reconstruction is the restoration and rebirth of the affected areas. The earthquake hitting Jiuzhaigou was the first earthquake that had its epicenter in the World Natural Heritage located in China. Ecological restoration and landscape reconstruction are essential for the sustainable development of tourism. This study uses high-resolution remote sensing images to monitor and evaluate the post-disaster restoration and reconstruction process of the leading lakes in Jiuzhaigou. It was found that the lake water quality, vegetation, and road facilities have undergone moderate reconstruction. However, the restoration and reconstruction still faced severe challenges. The ecological environment’s stability and balance are prerequisites for the sustainable development of the World Natural Heritage sites. This paper combines the “Build Back Better” concept that advocates risk reduction, scenic spot restoration, and efficient implementation to ensure Jiuzhaigou’s restoration and sustainable development. It comes up with specific measures for the resilience development of Jiuzhaigou from the eight principles of overall planning, structural resilience, disaster prevention and mitigation, landscape facilities, social psychology, management mechanisms, policies and regulations, and monitoring and evaluation to provide a reference for the sustainable development of tourism.

Post-disaster rapid recovery and reconstruction, along with the evaluation of these efforts, are crucial for affected areas. They not only facilitate the swift repair of vulnerable systems but also reflect whether the recovery work has enhanced regional coordinated development. This is vital for achieving sustainable development post-reconstruction. This study addresses two main questions: (1) How effective were the recovery and reconstruction efforts in Mianyang, Deyang, and Guangyuan post-Wenchuan earthquake from a socio-economic–ecological system perspective? (2) What are the temporal and spatial changes in the Coordinated Development Index (CDI) of key affected counties? By constructing a framework to assess post-disaster coordinated development, this study utilized the entropy weight method and mean-variance method for the comprehensive weighting of evaluation indicators. The gray system prediction model G(1,1) was used to forecast the coordinated development levels of the three cities from 2019 to 2025. The findings reveal the following: (1) From 2005 to 2018, the CDI of Deyang, Guangyuan, and Mianyang showed a significant upward trend. Post-earthquake reconstruction measures like land planning and ecological restoration notably enhanced regional resilience and promoted coordinated development among social, economic, and ecological systems. (2) Despite overall success in reconstruction, disparities in development levels persist among Mianyang, Deyang, and Guangyuan. Predictions suggest that Deyang, Mianyang, and Guangyuan will achieve high-quality coordinated development in the next 5, 2, and 1 years, respectively. (3) Although significant achievements have been made through industrial restructuring, land reuse planning, and ecological restoration, more precise disaster prevention and mitigation strategies are needed to foster coordinated development among social, economic, and ecological systems. In summary, this study evaluates the post-disaster recovery effects in the hardest-hit areas of the Wenchuan earthquake and forecasts future development, providing a reference for similar post-disaster reconstruction areas in assessing and predicting coordinated development.

The study of geography is centered on the regional system of the human-land relationship, and the core of the study of the geographical system of the human-land relationship is land use change. Land use is the most direct manifestation of human activities, accompanied by changes in land cover. This is the most appropriate entry point to reveal the evolution of human-land relationships. The past 300 years have been the most intense period of social change in China and the United States. In this study, we investigated the differences and evolution of human-land relations between China and the United States from the perspective of land cover change. We found: (1) Cultivated land, forest land, and grassland areas in China and the United States have changed significantly in the past 300 years. The cultivated land area has generally increased, and the extent of forest land and grassland has declined. According to the speed of land cover change, it can be roughly divided into three different stages. The change in cultivated land in China is mainly based on the enhancement of cultivation intensity. The change in cultivated land in the United States is mainly based on expansion of cultivated land. (2) The difference in land cover change between China and the United States in the past 300 years is mainly caused by the difference in social development, interpreting human-land relationships with honest feedback and social feedback. In general, with the continuous development of land, environmental issues have become increasingly prominent, and people’s awareness of environmental protection has also increased. (3) The evolution of human-land relations in China and the United States has been influenced by natural and social factors for nearly 300 years. China is dominated by population, whereas the United States is dominated by technology. The relationship between humans and land differs between the two countries in some respects, with similarities in other areas. In both countries, this relationship can be characterized by the stages of relying on the environment, understanding the environment, transforming the environment, and protecting the environment. This evolution is in line with the law of social development, according to which human beings constantly recognize, utilize, and adapt to nature.

The highly stochastic nature of rainfall presents significant challenges for the accurate prediction of its time series. To enhance the prediction performance of non-stationary rainfall time series, this study proposes a hybrid deep learning forecasting framework—VMD-IWMA-BiLSTM—that integrates Variational Mode Decomposition (VMD), Improved Whale Migration Algorithm (IWMA), and Bidirectional Long Short-Term Memory network (BiLSTM). Firstly, VMD is employed to decompose the original rainfall series into multiple modes, extracting Intrinsic Mode Functions (IMFs) with more stable frequency characteristics. Secondly, IWMA is utilized to globally optimize multiple hyperparameters of the BiLSTM model, enhancing its ability to capture complex nonlinear relationships and long-term dependencies. Finally, experimental validation is conducted using daily rainfall data from 2020 to 2024 at the Xinzheng National Meteorological Observatory. The results demonstrate that the proposed framework outperforms traditional models such as LSTM, ARIMA, SVM, and LSSVM in terms of prediction accuracy. This research provides new insights and effective technical pathways for improving rainfall time series prediction accuracy and addressing the challenges posed by high randomness.

Metaheuristic algorithms have become effective tools for solving complex engineering optimization problems. The Parrot Optimization (PO) algorithm is a recently proposed method with promising performance; however, it still suffers from premature convergence and slow convergence when handling complex tasks. To address these issues, this paper proposes an improved variant termed the Elite Cauchy Multi-scale Multi-directional Parrot Optimization algorithm (ECMPO). The proposed ECMPO incorporates three coordinated strategies. First, an elite learning strategy is introduced before the behavioral update phase to guide the population toward promising regions and accelerate convergence. Second, after the behavioral update, individuals are adaptively processed based on their fitness: elite individuals perform a multi-scale multi-directional search to enhance local exploitation. Third, non-elite individuals undergo Cauchy mutation to increase population diversity and strengthen global exploration. These strategies enable ECMPO to achieve a better balance between exploration and exploitation. To evaluate its performance, ECMPO is examined through ablation studies on the CEC2017 benchmark functions and further compared with eleven algorithms on the CEC2020–2022 benchmark suites. Finally, it is applied to six constrained engineering design problems. The results demonstrate that ECMPO exhibits superior performance compared with competitive algorithms. ECMPO shows strong robustness and applicability in practical engineering optimization tasks.