Transportation infrastructure, such as highway embankment slopes and retaining walls, are often constructed using locally available fill materials. Slopes constructed with such fills can pose problems as those fills can be expansive and experience surficial failures due to significant strength reductions over the years from cyclic moisture ingress and egress. Repeated wetting and drying cycles often result in the formation of desiccation cracks, which, when compounded by rainfall events, lead to moisture infiltration in the cracks and cause surficial slope failures. This paper provides a forensic investigation conducted on one such collapsed highway embankment slope in Houston, Texas, employing exhaustive timeseries optical image analysis, site characterization, laboratory studies, and numerical modeling. In-situ investigations included determining the site properties using the Texas cone penetration test and retrieving augered soil specimens. Site characterization indicated that the embankment soil was expansive in nature and susceptible to moisture-induced distress. Subsequently, laboratory shear strength studies were performed, and it was determined that the loss in cohesion in the problematic clay during the fully softening stage was responsible for initiating slope failure. Shallow slope failure was often attributed to surficial cracking due to moisture migration and reduction in shear strength from peak to fullysoftened, and further aggravated by insufficient drainage along the slope and vegetation removal. Surficial soil treatment with a calcium-based stabilizer was determined as a potential mitigation method. Engineering studies and numerical analyses showed that soil stabilization using calcium-based stabilizers notably enhanced the mechanical strength properties and overall stability of the slope under future extreme precipitation conditions. Overall, the study emphasized the importance of moisture regulation and the inclusion of anticipated rainfall projections within numerical models along with suitable chemical stabilizers to stabilize problematic embankment subgrade conditions in order to ensure an adequate performance of transportation infrastructure for long-term serviceability.

Floods in India are recurring natural disasters resulting from extreme precipitation during the summer monsoon season (June-September). The recent flood in North India in July 2023 caused substantial damage to lives, agriculture, and infrastructure. However, what led to the 2023 North India flood and the role of atmospheric and land drivers still need to be examined. Using in situ observations, satellite data, and ERA5 reanalysis combined with hydrological and hydrodynamical modeling, we examine the role of land and atmospheric drivers in flood occurrence and its impacts. Extreme precipitation in a large region during 7-10 July 2023 created favorable conditions for the flood in the hilly terrains and plains of north India. More than 300 mm of precipitation fell in just 4 days, which was eight times higher than the long-term average (2001-2022). Anomalously high moisture transport over northern India was recorded on 7 July 2023, making atmospheric conditions favorable for intense landfall. Increased column water vapor and specific humidity at different pressure levels confirmed the continuous moisture presence before the extreme rainfall that caused floods in northern India from 7 to 12 July 2023. Atmospheric and land (high antecedent soil moisture) conditions contributed to a more than 200% rise in streamflow at several gauge stations. Satellite-based flood extent shows a considerable flood inundation that caused damage in the Sutlej and Yamuna River basins. Our findings highlight the crucial role of the favorable land and atmospheric conditions that caused floods and flash floods in north India in July 2023. In July 2023, North India experienced a severe flood that caused significant damage to lives, agriculture, and infrastructure. However, the exact causes of this flood have yet to be examined. Using in situ, satellite, and reanalysis data, we examined the drivers of the flood. Favorable atmospheric and land conditions created a unique situation that led to a significant flood in north India. For instance, extreme precipitation during 7-10 July enhanced antecedent soil moisture conditions in the hilly and plain regions. Anomalously high moisture transport caused intense rainfall, which, combined with high soil moisture, produced high runoff and streamflow conditions. Flood inundation caused damage to the Sutlaj and Yamuna river basins. Our findings show the need to monitor soil moisture and atmospheric processes for early warning of floods in hilly regions. The flood in North India in July 2023 caused substantial damage to lives, agriculture, and infrastructure Anomalously high moisture transport over northern India created atmospheric conditions favorable for intense landfall High antecedent soil moisture and extreme precipitation caused the north India flood in 2023

Debris flows can develop into mega catastrophes in semi-arid regions when the source materials come from landslides, and both snowmelt and precipitation are involved in increasing water discharge. In such environments, the formation of large-scale debris flows exhibits a distinguishable pattern, in which a multi-fold lower triggering rainfall threshold holds compared to humid regions. Previous research mainly focuses on mechanisms in humid environments or neglects variations across aridity classes. In this study, the formation and evolutionary mechanism of a debris flow occurring in a semi-arid context is investigated via field surveys, granularity measurement, terrain and climate analyses, and snow cover change detection. By examining the July 22, 2021, Xiao Dongsuo debris flow at Amidongsuo Park in the Qilian Ranges on the northeastern margin of the Tibetan Plateau, the mechanism of debris flows in semi-arid regions is revealed. The research finds that the large debris flow, whose course erosion scales up the disaster by 0.12 million m3, is primarily supplied by landslide deposits of 1.16 million m3. The debris flow is empowered by the integrated flow of extreme precipitation and extreme heat-stimulated snowmelt. However, the precipitation required to trigger the debris flow is much lower than that of precipitation-dominated ones and those in humid regions. In semi-arid mountains, prolonged extreme heat tends to increase soil moisture in areas covered by snow or permafrost. This reduces slope stability and induces slope failures, amplifying the disaster magnitude and raising disaster risks through extended deterioration. Hence, this study inspects the failure mechanism associated with debris flows in semi-arid regions for a more comprehensive understanding to constitute viable control plans for analogous disasters.

Nitrous oxide (N2O) is the third most important greenhouse gas, and can damage the atmospheric ozone layer, with associated threats to terrestrial ecosystems. However, to date it is unclear how extreme precipitation and nitrogen (N) input will affect N2O emissions in temperate desert steppe ecosystems. Therefore, we conducted an in -situ in a temperate desert steppe in the northwest of Inner Mongolia, China between 2018 and 2021, in which N inputs were combined with natural extreme precipitation events, with the aim of better understanding the mechanism of any interactive effects on N2O emission. The study result showed that N2O emission in this desert steppe was relatively small and did not show significant seasonal change. The annual N2O emission increased in a non-linear trend with increasing N input, with a much greater effect of N input in a wet year (2019) than in a dry year (2021). This was mainly due to the fact that the boost effect of high N input (on June 17th 2019) on N2O emission was greatly amplified by nearly 17-46 times by an extreme precipitation event on June 24th 2019. In contrast, this greatly promoting effect of high N input on N2O emission was not observed on September 26th 2019 by a similar extreme precipitation event. Further analysis showed that soil NH4+-N content and the abundance of ammonia oxidizing bacteria (amoA (AOB)) were the most critical factors affecting N2O emission. Soil moisture played an important indirect role in regulating N2O emission, mainly by influencing the abundance of amoA (AOB) and de-nitrification functional microorganisms (nosZ gene). In conclusion, the effect of extreme precipitation events on N2O emission was greatly increased by high N input. Furthermore, in this desert steppe, annual N2O flux is co-managed through soil nitrification substrate concentration (NH4+-N), the abundance of soil N transformation functional microorganisms and soil moisture. Overall, it was worth noting that an increase in extreme precipitation coupled with increasing N input may significantly increase future N2O emissions from desert steppes.

Extreme precipitation events (EPEs) are projected to become more frequent and intense due to global warming. Understanding how coastal groundwater levels respond to and recover from these severe events is important for estuarine ecosystems to adapt to global change. Numerical model and non-EPE scenario simulation were used to examine groundwater level recovery time (RT) after Super Typhoon Lekima, which triggered EPEs that resulted in groundwater rise and widespread flooding in the Yellow River Delta (YRD). The three-day rainfall during Lekima totaled 290.9 mm, equivalent to 50 % of the annual rainfall for 2019 (581.5 mm), leading to a general rise in groundwater levels. Groundwater recovery to EPE can be divided into two types: inland and coastal. The RT of groundwater levels in monitoring wells in inland areas ranged from 12 to 89 days, with an average of 56.2 days, and there was spatial variation. However, groundwater levels in monitoring wells close to the coast may not recover. Differences in recovery are reflected in the land-sea gradient, with RT gradually increasing from inland highlands to coastal depressions and lowlands. The results showed that inland aquifers were more resistant to EPEs, while coastal aquifers were less resistant. In addition, EPE can cause groundwater flooding, and areas at lower altitude and close to the sea are more sensitive to flooding. Estuarine groundwater and the ecological processes on which it depends are profoundly affected by the direct and legacy effects of EPEs, including salt contamination, widespread flooding, crop damage, and reduced biodiversity. The study of this event provides case support for the response of estuarine groundwater to EPEs, while highlighting the importance of continuous monitoring.

The risk of floods has increased in South Asia due to high vulnerability and exposure. The August 2022 Pakistan flood shows a glimpse of the enormity and devastation that can further rise under the warming climate. The deluge caused by the floods in 2022, which badly hit the country's southern provinces, is incomparable to any recent events in terms of the vast spatial and temporal scale. The flood event is ranked second in human mortality, while this was the top event that displaced about 33 million people in Pakistan. Using observations and climate projections, we examine the causes and implications of the 2022 flood in Pakistan. Multiday (& SIM;15 days) extreme precipitation on wet antecedent soil moisture conditions was the primary driver of the flood in August 2022. The extreme precipitation in August was caused by two atmospheric rivers that passed over southern Pakistan. Streamflow simulations from the multiple hydrological models show that multiday extreme precipitation was the primary driver of floods. Several flood-affected stations experienced anomalously higher flow than the upstream stations. The 2022 Pakistan flood highlights the adaptation challenges South Asia is facing along with the substantial need for climate mitigation to reduce the risk of such events. Plain Language Summary The Pakistan flood of 2022 received a considerable attention. However, the causes and implications of the events have not been examined. Using observations, satellite data, and reanalysis products, we show that the event was caused by multiday extreme rainfall on wet antecedent conditions. The extreme rainfall was associated with the two atmospheric rivers that transported significant moisture from the Arabian Sea. The flood was primarily driven by the extreme precipitation and other factors (glacier-melt) played a secondary role. Extreme precipitation is projected to increase in a warming climate, which highlight the strong need of adaptation and mitigation.

Despite the importance of the Yellow River to China, climate change for the middle reaches of the Yellow River Basin (YRB) has been investigated far less than for other regions. This work focuses on future changes in mean and extreme climate of the YRB for the near-term (2021-2040), mid-term (2041-2060), and far-term (2081-2100) future, and assesses these with respect to the reference period (1986-2005) using the latest REgional MOdel (REMO) simulations, driven by three global climate models (GCMs) and assuming historical and future [Representative Concentration Pathway (RCP) 2.6 and 8.5] forcing scenarios, over the CORDEX East Asia domain at 0.22 degrees horizontal resolution. The results show that REMO reproduces the historical mean climate state and selected extreme climate indices reasonably well, although some cold and wet biases exist. Increases in mean temperature are strongest for the far-term in winter, with an average increase of 5.6 degrees C under RCP 8.5. As expected, the future temperatures of the warmest day (TXx) and coldest night (TNn) increase and the number of frost days (FD) declines considerably. Changes to mean temperature and FD depend on elevation, which could be explained by the snow-albedo feedback. A substantial increase in precipitation (34%) occurs in winter under RCP 8.5 for the far-term. Interannual variability in precipitation is projected to increase, indicating a future climate with more extreme events compared to that of today. Future daily precipitation intensity and maximum 5-day precipitation would increase and the number of consecutive dry days would decline under RCP 8.5. The results highlight that pronounced warming at high altitudes and more intense rainfall could cause increased future flood risk in the YRB, if a high GHG emission pathway is realized.

Heavy precipitation events are increasingly concerned because their significant contribution to annual precipitation in the Northwestern China, which might be related to invasion of summer monsoon moisture. It is interest whether or not the same is Jade Pass as being outside the control of the Asian summer monsoon. In this work, six heavy precipitation events were selected based on the 95 percentiles of the daily precipitation at the 12 weather stations around the Jade Pass from 1970-2000, with consideration of the influences of elevation. The event on June 19th, 2013 was chosen for a detailed examination due to the fact that the day has a large-scale precipitation as revealed by a gridded precipitation dataset over a large region. Using a Weather Research and Forecasting Model (WRF) simulation with high spatiotemporal resolution and in situ isotopic tracing (delta O-18, delta D), under a large-scale heavy precipitation event, this study provides ambitious view at the synoptic scale. A dramatic decrease in the delta O-18, delta D and deuterium (d)-excess of precipitation, very high relative humidity (98%), and reduced air temperature indicate that the precipitation was a result of long-distance-transported monsoon vapor. In addition, the slope of the local water meteoric line (LWML) of the precipitation for this event was very close to that of the global meteoric water line (GWML), indicating the source of moisture was from the ocean. Meanwhile, the WRF simulation confirms that the precipitation at the Jade Pass was not caused by local convection, but by summer monsoon. Both WRF simulation and isotopic tracing support the view that the monsoon moisture could invade Jade Pass at the synoptic scale and impact on precipitation, which need be further investigated.

Accurate estimates of extreme precipitation events play an important role in climate change studies and natural disaster risk assessments. This study aimed to evaluate the capability of the China Meteorological Forcing Dataset (CMFD), Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), and Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) to detect the spatiotemporal patterns of extreme precipitation events over the Qinghai-Tibet Plateau (QTP) in China, from 1981 to 2014. Compared to the gauge-based precipitation dataset obtained from 101 stations across the region, 12 indices of extreme precipitation were employed and classified into three categories: fixed threshold, station-related threshold, and non-threshold indices. Correlation coefficient (CC), root mean square error (RMSE), mean absolute error (MAE), and Kling-Gupta efficiency (KGE), were used to assess the accuracy of extreme precipitation estimation; indices including probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) were adopted to evaluate the ability of gridded products' to detect rain occurrences. The results indicated that all three gridded datasets showed acceptable representation of the extreme precipitation events over the QTP. CMFD and APHRODITE tended to slightly underestimate extreme precipitation indices (except for consecutive wet days), whereas CHIRPS overestimated most indices. Overall, CMFD outperformed the other datasets for capturing the spatiotemporal pattern of most extreme precipitation indices over the QTP. Although CHIRPS had lower levels of accuracy, the generated data had a higher spatial resolution, and with correction, it may be considered for small-scale studies in future research.

Investigation of extreme precipitation events in arid and semiarid regions, especially for occurrence time and the associated circulation mechanisms, is vital to support the forecasting of and the advanced response to resultant disasters. In this study, the spatiotemporal pattern of occurrence time of extreme precipitation and atmospheric circulation mechanisms in the Arid Region of Northwest China (ARNC) were analyzed using two indicators (precipitation concentration degree and period) and the climate diagnosis method. Results showed that the significant scattered pattern of extreme precipitation occurrence time (EPOT) in Northern Xinjiang and the postponed pattern of maximum extreme precipitation occurrence (MEPO) from southern to northern Xinjiang are consistent with the input pathway of the Arctic air mass. During the anomaly dispersion year of EPOT and the anomaly delay year of MEPO, the Arctic air mass carried sufficient water vapor is transported to ARNC for triggering extreme precipitation events. Meanwhile, the pattern of concentration-dispersion-concentration in eastern ARNC demonstrates interaction between the westerlies and the summer monsoon. Sufficient water vapor is transported to southwestern ARNC by the southwest monsoon during the anomaly delay year of MEPO and the anomaly concentration year of EPOT. The findings of this study suggest that invasion of the Arctic air mass and the summer monsoon could influence extreme precipitation in ARNC.