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River blocking caused by landslide dams is a common geological disaster in mountainous regions worldwide, threatening the safety of human lives and infrastructure. However, studies on the formation process of landslide dams and the criteria of river blockage are still at an early stage. This paper built a laboratory-scale experimental apparatus for simulating the formation and evolution process of landslide dams, and then carried out a total of 29 experiments. It analyzed the common evolution stages of river blocking, including landslides, dam formation, and dam breaching in detail. Then, we investigated the influences of the landslide volume, the landslide discharge, and the water flow rate on a criterion and the time length of river blockage. The experimental results suggest that the formation condition of a landslide dam is related to the ratio of the landslide discharge to the water flow rate. Based on this understanding, we proposed a dimensionless River Blockage Criterion (RBC) to judge the formation of landslide dams. The criterion indicates that when RBC > 1.5, a landslide dam may form; otherwise, a landslide dam may not form. Additionally, the time length of river blockage was found to be related to the landslide volume and the water flow rate. Subsequently, we proposed a model for predicting the time length of river blockage and verified it by the 29 experimental results. The Baige River-blocking event, which occurred on the Jinsha River, China, in 2018, was used as a case study to further verify the RBC and the proposed model. The results show that the proposed RBC agreed well with reality, and the percentage difference between the calculated and the actual time length of river blockage was 11%. The findings of this study could contribute to the early warning and emergency response of river-blocking disasters.

The territory of Azad Jammu and Kashmir (AJK) is vulnerable to different natural hazards because of its proximity to a geo-dynamically active zone and its tropical and monsoonal climatic pattern. Both factors operate in various combinations and result in the occurrence of disasters generated by natural hazards like floods, earthquakes, and landslides at different intervals. There are numerous landslides in the study area, out of which the Donga Kass landslide has been selected for study due to its ongoing activity which poses a significant risk to the nearby community and infrastructure. Therefore, assessment of two possible triggering factors (i.e., earthquake and rainfall) for this landslide was conducted through the laboratory testing using the DPRI-5 Ring shear simulator. Undrained cyclic loading tests were performed to simulate the dynamic loading and earthquake-induced landslides, while pore pressure control tests simulated the rise of groundwater level during rainfall for rainfall-induced landslides. Based on the laboratory test results, a critical seismic acceleration and a critical pore pressure ratio are suggested for Donga Kass landslide. Using these values and combining with rainfall data and monitored pore water pressure in bore holes, early warning system can be activated to reduce any potential landslide risk in the future.

Shallow landslides have posed significant threats to humans around the world. In order to reduce landslide disaster risk, the effectiveness of early warning systems and hazard zonation work needs to be improved. This research attempted to couple a landslide simulation model (LS-RAPID model) and a hydrological model (Rainfall-Runoff-Inundation (RRI) model) to exploit the advantages of each model for simulating and predicting landslide hazard (location and timing). The pilot area is a small catchment where a shallow landslide happened in July 2015 after 2 days of heavy rain. The landslide buried 3 houses and killed 8 people in Cao Thang Ward, Halong City, Vietnam. A soil sample was collected from the sliding surface and tested using an undrained ring-shear apparatus ICL-2 in the undrained condition. A thickness map of the potential sliding material was interpolated from the relationship between the depth of sandy soil layer and slope (based on 12 soil drill locations) and updated through field surveys in the study area. Different pore water pressure ratio scenarios were applied in the LS-RAPID model to simulate in 3D the initiation and motion of the rapid shallow landslide to create different hazard maps. The subsurface water level was monitored at two locations on the top of the shallow landslide. Based on the observed subsurface water and rainfall data, the RRI model was calibrated and then integrated with the LS-RAPID scenarios to generate Risk Index maps. The simulation results from the newly proposed coupled hydrological-geotechnical framework were compared with those from the observed landslide hazard and showed the reliability to predict the spatial and temporal occurrence of landslide hazard. This could be very useful for supporting decision-makers in rainfall-induced landslide hazard early warning and land use planning.

Flash floods have long been common in Asian cities, with recent increases in urbanization and extreme rainfall driving increasingly severe and frequent events. Floods in urban areas cause significant damage to infrastructure, communities and the environment. Numerical modelling of flood inundation offers detailed information necessary for managing flood risk in such contexts. This study presents a calibrated flood inundation model using referenced photos, an assessment of the influence of four extreme rainfall events on water depth and inundation area in the Hanoi central area. Four types of historical and extreme rainfall were input into the inundation model. The modeled results for a 2008 flood event with 9 referenced stations resulted in an R 2 of 0.6 compared to observations. The water depth at the different locations was simulated under the four extreme rainfall types. The flood inundation under the Probable Maximum Precipitation presents the highest risk in terms of water depth and inundation area. These results provide insights into managing flood risk, designing flood prevention measures, and appropriately locating pump stations.

Apple cultivation is one of the most important sources of livelihood in Indian side of the Himalayas. The present study focuses on the apple orchards of Himachal Pradesh, a state within the Himalayan Mountains, a major apple producers of India. In the study, it is found that the optimum apple growing conditions in the region have been consistently shifting and farmers are shifting their orchards to the higher altitudes. For example, orchards have shifted to 1500–2500 meters in the 2000s compared to the cultivated elevation of 1200–1500 meters during 1980s. As of 2014, apples are being cultivated at an elevation of more than 3500 meters, for example, the newly developed orchards of Leo village in upper Kinnaur and Keylong area of Lahul and Spiti districts. Chilling hours for different districts are calculated. The trend of temperature during the growth period, winter session and annual rainfall have been analysed using Mann-Kendall and Sen’s slope test. Data catalogued from different time periods indicates that the northward shift (towards higher altitude) is due to changes in chilling hours, total annual rainfall and mean surface temperature during the apple growing season. The mean surface temperature in all the districts has increased by almost 0.5°C during last 2000–2014. These changes are directly related to global warming. While the changing climate is reducing the apple production in low altitudinal regions of the state, it is creating new opportunities for apple cultivation in higher altitudes as conditions are getting more favourable for apple growth in those higher regions. The associated socio-economic changes are posing new societal issues for the local farmers.

Precipitation, as a primary hydrological variable in the water cycle plays an important role in hydrological modeling. The reliability of hydrological modeling is highly related to the quality of precipitation data. Accurate long-term gauged precipitation in the Mekong River Basin, however, is limited. Therefore, the main objective of this study is to assess the performances of various gridded precipitation datasets in rainfall-runoff and flood-inundation modeling of the whole basin. Firstly, the performance of the Rainfall-Runoff-Inundation (RRI) model in this basin was evaluated using the gauged rainfall. The calibration (2000-2003) and validation (2004-2007) results indicated that the RRI model had acceptable performance in the Mekong River Basin. In addition, five gridded precipitation datasets including APHRODITE, GPCC, PERSIANN-CDR, GSMaP (RNL), and TRMM (3B42V7) from 2000 to 2007 were applied as the input to the calibrated model. The results of the simulated river discharge indicated that TRMM, GPCC, and APHRODITE performed better than other datasets. The statistical index of the annual maximum inundated area indicated similar conclusions. Thus, APHRODITE, TRMM, and GPCC precipitation datasets were considered suitable for rainfall-runoff and flood inundation modeling in the Mekong River Basin. This study provides useful guidance for the application of gridded precipitation in hydrological modeling in the Mekong River basin.

The wave energy resources in the Indian Ocean can be considered as a potential alternative to fossil fuels. However, the wave energy resources are subject to short-term fluctuations and long-term changes due to climate change. Hence, considering sustainable development goals, it is necessary to assess both short-term (intra-annual) variation and long-term change. For this purpose, the simulated wave characteristics were utilized, and the wave power and its variation and change were analyzed in the whole domain and nearshore areas. The short-term fluctuation was investigated in terms of monthly and seasonal variations and the future change was discussed based on absolute and relative changes. Both analyses show that the Southern Indian Ocean, despite experiencing extreme events and having higher wave energy potential, is more stable in terms of both short and long-term variation and change. The assessment of the total and exploitable storages of wave energy and their future change revealed the higher potential and higher stability of the nearshores of the Southern Indian Ocean. It can be concluded that based on various factors, the south of Sri Lanka, Horn of Africa, southeast Africa, south of Madagascar and Reunion and Mauritius islands are the most suitable areas for wave energy extraction.

The Himalayas have become synonymous with the hydropower developments for larger electricity demands of India’s energy sector. In the Himachal Himalayas though, there are only three large storage dams with more than 1000 megawatts (hereafter MW) capacity that have very serious environmental issues. However, hundreds of small runoff-river hydropower plants across the Himachal Himalayas are a serious threat to the river regimes and Himalayan biota. There are 965 identified hydropower projects (hereafter HPPs) having a potential capacity of 27,436 MW in the Himachal Pradesh as of December 2019 as per the Directorate of Energy of the state. Out of the 965 identified, 216 are commissioned, including less than 5 MW plants, with an installed capacity of 10,596 MW, and were operational by December 2019. Only 58 projects are under construction among the identified with an installed capacity of 2351 MW, 640 projects are in various stages of clearance and investigation with an installed capacity 9260 MW, 30 projects are to be allotted with 1304 MW installed capacity, and merely four projects are disputed/cancelled with installed capacity of 50.50 MW. The large number of HPPs are sanctioned without proper consideration of negative environmental and geohazard impacts on the Himalayan terrestrial biota. In this work, our focus was on the hydropower and climate change impact on the Himalayan river regimes of the Chenab, the Ravi, the Beas, the Satluj, and the Yamuna river basins. We analyzed basin-wise rainfall, temperature, and soil moisture data from 1955 to 2019 to see the trend by applying the Mann–Kendall test, the linear regression model, and Sen’s slope test. A basin-wise hazard zonation map has been drawn to assess the disaster vulnerability, and 12 hydropower sites have been covered through the primary survey for first-hand information of local perceptions and responses owing to hydropower plants.

Evidence for climate change impacts on the hydro-climatology of Japan is plentiful. The objective of the present study was to evaluate the impacts of possible future climate change scenarios on the hydro-climatology of the upper Ishikari River basin, Hokkaido, Japan. The Soil and Water Assessment Tool was set up, calibrated, and validated for the hydrological modeling of the study area. The Statistical DownScaling Model version 4.2 was used to downscale the large-scale Hadley Centre Climate Model 3 Global Circulation Model A2 and B2 scenarios data into finer scale resolution. After model calibration and testing of the downscaling procedure, the SDSM-downscaled climate outputs were used as an input to run the calibrated SWAT model for the three future periods: 2030s (2020–2039), 2060s (2050–2069), and 2090s (2080–2099). The period 1981–2000 was taken as the baseline period against which comparison was made. Results showed that the average annual maximum temperature might increase by 1.80 and 2.01, 3.41 and 3.12, and 5.69 and 3.76 °C, the average annual minimum temperature might increase by 1.41 and 1.49, 2.60 and 2.34, and 4.20 and 2.93 °C, and the average annual precipitation might decrease by 5.78 and 8.08, 10.18 and 12.89, and 17.92 and 11.23% in 2030s, 2060s, and 2090s for A2a and B2a emission scenarios, respectively. The annual mean streamflow may increase for the all three future periods except the 2090s under the A2a scenario. Among them, the largest increase is possibly observed in the 2030s for A2a scenario, up to approximately 7.56%. Uncertainties were found within the GCM, the downscaling method, and the hydrological model itself, which were probably enlarged because only one single GCM (HaDCM3) was used in this study.

The COVID-19 pandemic, coupled with more frequent and stronger heatwaves, has introduced a novel confluence of challenges. In Japan, emergency medical transport staffs are facing increasing difficulty in distinguishing between COVID-19 and heat stroke at the scene because they share some similar symptoms. This study explored the impacts of the COVID-19 pandemic on heat-related ambulance calls and identifies the challenges faced by local fire departments in the Kansai region of Japan over 2020–2022. Both historical data analysis and an online questionnaire survey were used in this study. We utilized a heat-related ambulance calls prediction model developed in our previous research based on the historical data (2008–2019) to project the expected number of heat-related ambulance calls from 2020 to 2022. Subsequently, we compared expected number and the actual number of daily heat-related ambulance calls to examine the variations of heat-related ambulance calls across six prefectures in the Kansai region. Our findings reveal a significant decrease in the number of heat-related ambulance calls during the COVID-19 pandemic across all Kansai prefectures, ranging from 3.2% to 22.9%. The decline in heat-related ambulance calls can be attributed to shifts in daily routines, such as the increase of remote work and decrease of outdoor exercise. However, it may also be influenced by the strain on the emergency medical resource. Furthermore, this study has also highlighted substantial pressures on local fire departments and emergency medical transport systems during the pandemic. A primary challenge for local fire departments was securing available medical facilities for patients. Improving the efficiency of the emergency medical transport system and enhancing the coordination between emergency medical services and healthcare facilities may offer a more resilient response in future crises.