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Sichuan-Tibet Railway spans several watersheds such as Jinsha River and Yalong River, and Potential landslides are frequent along the route, which poses serious hazards to the normal construction and operation of the railroad. The traditional time-series InSAR technology is limited by the number of images and other restrictions, and has a long solution time, making it difficult to obtain information on short-term occurrence of deformation and unable to perform wide-area potential landslides monitor quickly. In this paper, taking a geological hazard-prone area in the Jinsha River basin (or a section of the Sichuan-Tibet line) as an example, based on the Sentinel-1 satellite SAR data provided by the Copernicus program of ESA, the model corrects the interferometric superposition deformation results obtained from a small number of SAR images (less than 7), decodes the corrected rate results, and identifies a total of 13 areas where deformation obviously occurs A total of 13 typical areas with significant deformation were identified. The identified typical areas were time-series solved and their deformation was traced. The method provides a new idea for identification and monitor of Potential landslides in a wide area and further promotes the development of disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

In order to deeply analyze the drought and flood disaster response patterns of Tuojiang River Basin under the background of climate anomalies, this paper reconstructs the time series of drought and flood disaster of Tuojiang River Basin in the Qing Dynasty, and analyzed its related data with mathematical statistics, mutation test, power spectrum cycle analysis, ADF and Granger causality test, etc., to explore the occurrence patterns of drought and flood disasters in the Tuojiang River Basin in the Qing Dynasty and its climate driving force factors. The results show that, during the Qing Dynasty, 208 drought and flood disaster occurred in the Tuojiang River Basin, with an average of one drought and flood disasters occurring every 1.29 years. There were more flood disasters than drought disasters, with a total of 21 persistent flood and drought disasters and an overall high level of severity of disasters. Drought and flood disasters were interspersed frequently, and there were also drought and flood disasters coexisting during the same year. Drought and flood disasters were concentrated in a chain-like distribution from 1800 to 1910.The number of disasters peaked in the middle of the Qing Dynasty, and mega-disasters were concentrated in the middle and late Qing Dynasty. The year 1863 was an important mutation point for drought and flood disasters, after which the number of disasters increased significantly. Drought and flood disasters in the Qing Dynasty were significantly correlated with the average annual sunspot number, and continuous disaster events were more frequent around sunspot extreme years.The change cycle of drought and flood disasters is about 2.5 a, which is strongly consistent with the ENSO cycle. The number of drought and flood disasters in the Tuo River Basin was significantly higher during ENSO event years. With a lag period of 1a, sunspot activity and ENSO events are the main climatic triggers of drought and flood disasters changes. The research results not only fill the research gap of drought and flood disasters mechanism in the Tuojiang River Basin under climate change, but also enrich the knowledge of spatial and temporal distribution pattern and regularity of drought and flood disasters in the Yangtze River Basin. It provides a useful reference for strengthening the scientific use of water resources and disaster prevention and mitigation, and also provides an important reference for the flood and drought prevention and ecological civilization construction in the Tuojiang River Basin. [ABSTRACT FROM AUTHOR]

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Climate warming increases the intensity of extreme precipitation. Studying extreme precipitation patterns and changes is vital to reducing risk. This paper investigates thresholds, changes and timescales for extreme precipitation using sub-daily records from meteorological stations in the Ganjiang River basin. We use the gamma distribution and select the L-moment method to estimate the parameters α and β. Results show that (1) continuous precipitation events of 36 h contributed the most precipitation to the total but with lower frequency, which would be key events for flood monitoring; (2) the intensity and the occasional probability of extreme precipitation will increase in spring in the future in stations like Yifeng, Zhangshu and Ningdu, which will in turn increase the risk of storm floods; and (3) spatial distribution of extreme precipitation risk shows that the risk increases as elevation increases in the northern lowland and the Jitai Basin in the midstream region, while the risk in the southern mountainous region decreases as elevation increases. These findings will facilitate emergency preparedness, including risk management and disaster assistance, in the study areas. [ABSTRACT FROM AUTHOR]

A wide range of nature‐based solutions for flood hazard management work by storing and slowing flow within catchments, and therefore, there is a need to identify the optimal locations for implementing these solutions. This paper presents a relative scoring‐based mapping of the likely locations that contribute to the flood peak. Targeting flow reduction and attenuating mitigation actions in these locations can be an effective way to reduce flood damages at impact points downstream. The presented tool, SCIMAP‐Flood, uses information on land cover, hydrological connectivity, flood generating rainfall patterns and hydrological travel time distributions to impacted communities to find the potential source areas of flood waters. The importance of each location in the catchment is weighted based on its contribution to the flood hazard at each of the downstream impact points. In the example application, SCIMAP‐Flood is applied at a 5‐m grid resolution for the River Eden catchment, Cumbria, England, to provide sub‐field scale information at the landscape extent. Therefore, the tool can identify sub‐catchments where more detailed work can test different mitigation measures. [ABSTRACT FROM AUTHOR]

Nature-based solutions (NbS) are currently a priority of international institutions (UN and EU) to improve urban resilience to hydro-climatic risks. However, responsible institutions, such as river basin authorities and local governments, while still prioritizing gray infrastructure, often present resistance to these strategies. This paper analyzes this issue in the case of Seville (Spain). We identify historical and recent institutional practices related to the development of gray infrastructure and the experience of citizens' movements that demand the implementation of green infrastructure and the naturalization of urban space. Based on the theoretical framework of the sustainability transition, the article contributes to the identification of the factors that hinder or trigger the processes of change, drawing from the results of a case with a long tradition in hydro-climatic disaster management. The research has included an in-depth review of risk planning in the city of Seville, semi-structured interviews with 24 social and institutional actors, and participant observation of both urban planning processes and the practices of citizen movements. Our results show that the generation of shared visions clashes, first with conflicting perceptions of the city's strengths and weaknesses regarding risks; second, with contradictions between institutional discourses and practices, and finally, with the operational limitations of public participation processes. [ABSTRACT FROM AUTHOR]

Arid area is very sensitive to global warming and are extremely vulnerable to climate change. Moreover, the water resources system in the arid area is fragile and will undergo tremendous changes with climate change. Therefore, the interaction of climate and hydrology in arid area has an important impact on the formation of regional microclimate and hydrological changes. Daihai Lake is a typical closed inland lake in arid area of China, and a key area for ecological protection in North China. In this paper, WRF-Hydro model is used to simulate the climate hydrological coupling situation of Daihai Basin from 1980 to 2020, and the coupling results are verified and calibrated by meteorological statistics, runoff calculation and remote sensing analysis. Based on the synopsis of climate and hydrology in the past 40 years, the causes and future trends of the hydrological elements in Daihai Basin are analyzed. Through the analysis, it is found that the interannual variation of precipitation in Daihai Basin is sharp, with 401.75 mm as the average from 1980 to 1994; and drastic fluctuations from 1995 to 2011, with a difference of nearly 400 mm between the interannual maximum and minimum; From 2012 to 2020, the fluctuation is small. Although the interannual variation of evaporation fluctuated, it showed an upward trend with a slope of 8.855 mm/year. The annual average temperature showed an obvious upward trend with a slope of 0.040 °C/year. From 1980 to 2020, the inflow of Daihai Lake shows a downward trend; Since 2013, the runoff into the lake has tended to be flat. Climate change and human activities are the decisive factors leading to the change of water quantity in Daihai, among which human activities play a greater role. Cultivated land irrigation and industrial water use are highly correlated with the lake discharge, and these two factors have a great influence on the lake discharge. If the current agricultural and industrial water consumption does not increase, Daihai still has a lifespan of nearly 120 years. If human activities do not change and any protective measures are not taken in time, under the background of global climate change, the flow of the Daihai Lake into the lake will be reduced to zero in 2025, and the Daihai Lake will completely dry up in 2031–2033. The study of climate hydrological coupling of long time series in Daihai Basin can not only make up for the lack of runoff data, but also provide the basis for water resources management, disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

To explore the possible impact of climate change on the hydrometeorologicalprocesses and provide the reference for flood prevention and disaster reduction in Yuanjiang River Basin, this paper obtains the outputs of five GCMs announced by CMIP6 from 2041 to 2100. Then, monthly precipitation and temperature under SSP126, SSP245, SSP370 and SSP585 paths are generated through the M-BCSD down- scaling method. Moreover, the impact of climate change on the runoff at the basin outlet is forecasted by back-propagation neural network (BPNN) with cross validation skill. The results indicate that the M-BCSD method has better applicability in Yuanjiang River Basin and the BPNN is able to predict the monthly runoff effectively. In general, the mean annual rainfall, temperature and runoff have an increasing trend within the periods of 2041-2100 with the maximum increase of 24.6%, 20.4% and 10.2% respectively. As for the seasonal scale, the runoff decreases in spring and increases in fall. As for the monthly scale, the runoff decreases in April and increases in November. Under different path scenarios, the changes of the hydrometeorological elements are basically consistent but their amplitudes are different. [ABSTRACT FROM AUTHOR]

Flash floods are an increasing hazard to human infrastructure and life. Effective disaster management and mitigation require accurate and fast predictions for decision-making. The Flood Inundation Parallel Computation (FIP) software presented in this paper shows how to fully exploit the tremendous computational capabilities of graphics processing units (GPUs) to accelerate shallow water solvers beyond the current state-of-the-art. The time efficient explicit shallow water scheme for structured grids RMG, is introduced and implemented in FIP. The optimized GPU implementation of FIP achieves balanced memory- and instruction throughputs of up to 80%. Validation and performance tests using laboratory and historical flood cases are presented that demonstrate the accuracy and effectiveness of FIP in predicting flood inundation. Our implementation achieves a fourfold speedup in comparison to state-of-the-art approaches. It enables faster-than real-time simulations of areas of over 600 km2 at 1 m resolution on consumer-grade GPUs. • Efficient, mass-preserving shallow water solver. • Future-proof CUDA implementation with nearly fourfold speedup compared to state of the art approaches. • Validation and performance tests on historical flooding events. • Computations with high resolution terrain data of complete river catchments and flood forecasts. [ABSTRACT FROM AUTHOR]

Climate warming increases flooding risk and the intensity of extreme precipitation. Studying changes and trends of extreme precipitation events is key in term of reducing flood risk and disaster loss. This paper investigates the thresholds, changes and time scales of extreme precipitation using sub-daily records in meteorological stations in the Ganjiang river basin. We use Gamma distribution and choose L-moment method to estimate parameters. Results show that (1) precipitation events with very long duration occur rarely and have minimal contribution to the total precipitation; (2) Extreme precipitations have the characteristics of occasional but sudden occurrence in summer and spring and the intensity and occasional probability will increase in spring in the future in Yifeng, Zhangshu and Ningdu; (3) Risks were positively correlated with elevation in the northern plain and Jitai Basin in the midstream area while risks in the southern hilly area were negatively correlated with elevation. These findings should be helpful in adjusting regional land use planning and for emergency preparedness including risk management and relief operations in high-risk areas in the future. [ABSTRACT FROM AUTHOR]

Frequent drought disasters have significant impacts on socio-economic and ecosystems, and it is crucial to explore the propagation characteristics of drought for disaster prevention and mitigation. In this paper, based on 0.25° × 0.25° grid-point Meteorological hydrological and large-scale climate factor data, the start-to-start, peak-to-peak, and end-to-end drought propagation times, and the periods and rates of drought development and recovery were estimated for 11 regions in the Luanhe River Basin under stationary and non-stationary conditions. The Generalized Additive Model for Location, Scale and Shape (GAMLSS) framework was used to construct stationary and non-stationary models to capture the stationary and non-stationary drought characteristics respectively, and then the drought development and recovery patterns, and drought propagation times were assessed. The results showed that under the influence of climate factors, severe drought events occurred in most study areas, the duration of meteorological drought was prolonged by 0.1–0.6 months, and the peak intensity was increased by about 0.05. The severity of hydrological drought increased by 0.2–0.8, and the peak intensity decreased by 0.1–0.2. The rate of development and recovery of hydrological drought was accelerated by 0.1–0.2 per month. The propagation time of start-to-start was shortened by 0.2 months, and the propagation time of end-to-end was extended by 1–2 months. These mean that water resource control authorities need to propose responses to droughts more quickly. • The non-stationary drought indices considering climatic factors were constructed. • The drought propagation time was calculated from start to start, peak to peak, and end to end. • Quantification of the effects of climate change on drought propagation [ABSTRACT FROM AUTHOR]

In drinking water catchments, exploiting ecosystem services provided by stream buffers has the potential to complement conventional engineering solutions such as water treatment and reduce the overall public health risks to consumers. These stream buffers interrupt the movement of contaminants and sediments from non-point source sources, such as agricultural land, to surface waters. Effectively managing stream buffers can be challenging due to the complexity and diversity of factors that can directly and indirectly impact efficacy. This study uses System Theoretic Process Analysis (STPA) and Early Warning Signal Analysis based on STPA (EWaSAP) methodology to systematically examine the sociotechnical structures for managing stream buffers in surface water catchments using a theoretical scenario representative of typical surface water supplies. The combination of STPA and EWaSAP provides a practical approach for developing requirements for stream buffers in drinking water catchments, focusing on hazard assessment and management measures. The evaluation considers the complex management arrangements for land uses within catchment areas. The performance and effectiveness of these actions can be tracked through the selected sensors and early warning measures. As a practical matter, this approach would help specify requirements for catchment management and drinking water source protection that can be systematically integrated into relevant management strategies. [ABSTRACT FROM AUTHOR]

Glaciers and snow are critical components of the hydrological cycle in the Himalayan region, and they play a vital role in river runoff. Therefore, it is crucial to monitor the glaciers and snow cover on a spatiotemporal basis to better understand the changes in their dynamics and their impact on river runoff. A significant amount of data is necessary to comprehend the dynamics of snow. Yet, the absence of weather stations in inaccessible locations and high elevation present multiple challenges for researchers through field surveys. However, the advancements made in remote sensing have become an effective tool for studying snow. In this article, the snow cover area (SCA) was analysed over the Beas River basin, Western Himalayas for the period 2003 to 2018. Moreover, its sensitivity towards temperature and precipitation was also analysed. To perform the analysis, two datasets, i.e., MODIS-based MOYDGL06 products for SCA estimation and the European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis of the Global Climate (ERA5) for climate data were utilized. Results showed an average SCA of ~56% of its total area, with the highest annual SCA recorded in 2014 at ~61.84%. Conversely, the lowest annual SCA occurred in 2016, reaching ~49.2%. Notably, fluctuations in SCA are highly influenced by temperature, as evidenced by the strong connection between annual and seasonal SCA and temperature. The present study findings can have significant applications in fields such as water resource management, climate studies, and disaster management. [ABSTRACT FROM AUTHOR]

This study reviewed some of the challenges faced by local authorities in disaster management, especially flood disasters that occurred in Malaysia. Flood disasters are the most frequent disasters in Malaysia, especially during the monsoon seasons. The hard structure developed by Malaysia's National Security Council (MKN) under 'Directive 20' is used to manage disasters in the country. Although Malaysia has become more skillful in managing flood disasters, the frequent climate changes along with weakness in implementing flood risk management plans resulted in much losses and damages throughout the country. Therefore, this study explored the gaps and weaknesses in flood risk management (FRM) in Malaysia by reviewing the available literature to recommend better flood management. This study revealed four main issues which are weaknesses in terms of (i) coordination and communication, (ii) manpower and assets, (iii) public awareness, and (iv) power and authority among local authorities to implement flood management plans. The capacity of local authorities and individuals in charge of disaster management is inadequate, especially for flood risk preparedness and management. Hence, responsible individuals are also in a vulnerable situation to implement management plans or rescue operations when flood disasters occur since they are also flood victims. Thus, the National Disaster Management Agency (NADMA) which acts as the main coordinator of disaster management in Malaysia should re-examine the flood management plan to ensure that it can be implemented efficiently and effectively, especially at the local level as they are the first respondents on the scene when the disaster occurs. The combination of both structural and non-structural measures might require in many cases the management of flood disasters; however, the disaster risk preparedness and management of individuals via customized training is a must to prevent flood disasters as well as minimize their impact. The flood management plan should also incorporate natural-based approaches at the whole-river-basin level for the long-term solution and sustainable development, not only focusing to manage the localized flood problem at the specific area. [ABSTRACT FROM AUTHOR]

Identifying the response of runoff changes to extreme climate evolution was of great scientific significance for the rational regulation of watershed water resources and the prevention of hydrological disasters. However, the time–frequency response relationships were not clear. The Yinjiang River watershed, a typical watershed with karst trough valley areas, was chosen to identify the impact of different climatic driving factors on runoff changes from 1984 to 2015. Continuous wavelet transform (CWT), cross-wavelet transform (XWT), and wavelet coherence transform (WTC) were performed to study the response relationship and time–frequency effect between runoff changes and extreme climate change at different time scales. The main results showed that: (1) Twelve extreme climate indices (ECIs) were detected to have a significant impact on runoff changes, mainly on a 6-year time scale; (2) The R10 and Rx1day in extreme precipitation index and SU34.4 and TNx in the extreme temperature index were the main driving factors of runoff changes, which had relatively large impacts on runoff changes in high and low energy vibration regions. However, the remaining eight ECIs that passed the 0.05 confidence level showed relatively large impacts on runoff changes only in low energy vibration regions; (3) The transition of the interaction between ECIs and runoff changes in high and low time–frequency scales was related to the abrupt change characteristics of the ECIs. The correlation of abrupt change was an important reason for the emergence of highly correlated regions that trigger high and low energy vibrations; (4) As a whole, the extreme precipitation events were ahead of runoff changes at the high time–frequency scale and exhibited small lag effects at the low time–frequency scale, while extreme temperature events were mainly ahead of runoff changes. This study has effectively revealed the impact of climate factors at different scales on runoff changes, and provides a theoretical understanding for regulating and managing water resources in karst basins. [ABSTRACT FROM AUTHOR]

The analysis of precipitation, snow cover, and temperature based on measured data is important for many applications in hydrology, meteorology, climatology, disaster management, and human activities. In this study, we used long-term historical datasets from the Varzob River Basin (VRB) in Tajikistan to evaluate the trend and magnitudinal changes in temperature, precipitation, and snow cover area in the Anzob (upstream), Maykhura (midstream), and Hushyori (downstream) regions of the VRB using the original Mann–Kendall test, modified Mann–Kendall test, Sen's slope test, and Pettitt test. The results revealed a decreasing trend in the mean monthly air temperature at Anzob station in the upstream region for all months except January, February, and December between 1960 and 2018 and 1991 to 2018. In each of the three regions, the mean annual temperature indicated a clear upward trend. Seasonal precipitation indicated a large increasing trend in January and February at the Anzob station from 1960 to 2018, but a significant downward trend in April in the upstream, midstream, and downstream regions between 1960 and 1990 and from 1991 to and 2018. In the VRB, almost all stations exhibited a downward trend in annual precipitation across all periods, whereas the upstream region showed a non-significant upward trend between 1960 and 1990. The monthly analysis of snow cover in the VRB based on ground data showed that the maximum increase in snow cover occurs in April at the Anzob station (178 cm) and in March at Maykhura (138 cm) and Hushyori stations (54 cm). The Mann–Kendall test, based on MODIS data, revealed that the monthly snow cover in the VRB increased in April and July while a decrease was recorded in February, September, November, and December from 2001 to 2022. The trend's stable pattern was observed in March, May, August, and October. [ABSTRACT FROM AUTHOR]

The present initiative study has been planned to develop a conceptual model for watershed resilience for which rare documents have been reported yet, particularly in developing countries where such studies are necessary. In this vein, different ecological, social, economic, and infrastructural and cultural key domains were applied for the modeling processes of watershed resilience for the Shazand Watershed in Iran. To this end, watershed resilience was firstly conceptualized according to the prevailing conditions for three periods 1986–1998, 1999–2008, and 2009–2016. Accordingly, the watershed health index was used for the ecological dimension, and 13, 8, and 13 criteria were consequently considered for social, economic, and infrastructural and cultural dimensions, respectively. The whole data required for the last three dimensions were collected through the distribution of questionnaires among the stockholders of the Shazand Watershed. The principal component analysis (PCA) method was used to weighting and prioritize the criteria and dimensions. The overall resilience index was ultimately calculated by aggregating all four dimensions using a geometric mean. The effect of each dimension on resilience was also assessed by applying multivariable regression. According to the resilience map of the period 2009–2016, 40%, 9%, 34%, and 17% of the Shazand Watershed has been classified as very low and low resilience, moderate, high, and very high resilience. This study showed that the resilience of the Shazand Watershed has improved over time. The necessity of resilience modeling for practical and integrated management of watersheds was also confirmed during the present research. Recommendations for Resource Managers: Application of resilience zoning results in explaining management strategies.Monitoring the changes in resilience status in certain periods.Improving the level of stakeholders' awareness in dealing with disasters adaptive management. [ABSTRACT FROM AUTHOR]

Owning to the nature of flood events, near-real-time flood detection and mapping is essential for disaster prevention, relief, and mitigation. In recent years, the rapid advancement of deep learning has brought endless possibilities to the field of flood detection. However, deep learning relies heavily on training samples and the availability of high-quality flood datasets is rather limited. The present study collected 16 flood events in the Yangtze River Basin and divided them into three categories for different purpose: training, testing, and application. An efficient methodology of dataset-generation for training, testing, and application was proposed. Eight flood events were used to generate strong label datasets with 5296 tiles as flood training samples along with two testing datasets. The performances of several classic convolutional neural network models were evaluated with those obtained datasets, and the results suggested that the efficiencies and accuracies of convolutional neural network models were obviously higher than that of the threshold method. The effects of VH polarization, VV polarization, and the involvement of auxiliary DEM on flood detection were investigated, which indicated that VH polarization was more conducive to flood detection, while the involvement of DEM has a limited effect on flood detection in the Yangtze River Basin. Convolutional neural network trained by strong datasets were used in near-real-time flood detection and mapping for the remaining eight flood events, and weak label datasets were generated to expand the flood training samples to evaluate the possible effects on deep learning models in terms of flood detection and mapping. The experiments obtained conclusions consistent with those previously made on experiments with strong datasets. [ABSTRACT FROM AUTHOR]

This study evaluated multiple aspects of flood risks and effects on the Cinan Feizuo flood protection area in the Huaihe River basin. Flooding remains a leading problem for infrastructure, especially in urban, residential areas of the region. Effective flood modeling for urbanized floodplains is challenging, but MIKE (ID-2D) is paramount for analyzing and quantifying the risk in the vulnerable region. The Saint-Venant equation and a one-dimensional (1D) MIKE 11 model were used to understand the flood dynamics in the Huaihe River, and a two-dimensional (2D) MIKE 21 model was applied to assess the risk in the Cinan Feizuo flood protection area. The finite volume method (FVM) was used for discrete grid problems, and the models were coupled through the weir equation to find the flow volume from the 1D domain to the 2D domain to investigate water level changes. Flood inundation maps were generated for the flood protection area. The maximum discharge, velocity, and submerged depth for 50- and 100-year flood events were assessed with flood risk. Chenbei indicated a high flood risk level in 50 to 100 years in which the water level exceeds a high level and inundates the maximum area with minimum time. Conversely, the 100-year flood inundation in the flood protection area was comparatively higher than the 50-year flood, with a lower time step. The risk analysis identified significant damage caused by the flood over the target regions. The findings of this study provide technical support for flood risk analysis and loss assessment within the flood protection area and have important reference values for regional flood control, disaster reduction decision making, and constructive planning. [ABSTRACT FROM AUTHOR]

Monitoring for mass flows on volcanoes can be challenging due to the ever-changing landscape along the flow path, which can drastically transform the properties and dynamics of the flow. These changes to the flows require the need for detection strategies and risk assessments that are tailored not only between different volcanoes but at different distances along flow paths as well. Being able to understand how a flow event may transform in time and space along the channel is of utmost importance for hazard management. While visual observations and simple measuring devices in the past have shown how volcanic mass flows transform along the flow path, these same features for the most part have not been described using seismological methods. On 18 March 2007, Mt. Ruapehu produced the biggest lahar in Aotearoa / New Zealand in over 100 years. At 23:18 UTC the tephra dam holding the Crater Lake water back collapsed causing 1.3×106 m3 of water to flow out and rush down the Whangaehu channel. We describe here the seismic signature of a lake-breakout lahar over the course of 83 km along the Whangaehu River system using three three-component broadband seismometers installed <10 m from the channel at 7.4, 28, and 83 km from the Crater Lake source. Examination of three-component seismic amplitudes, frequency content, and directionality, combined with video imagery and sediment concentration data, was carried out. The seismic data show the evolution of the lahar as it transformed from a highly turbulent out-burst flood (high peak frequency throughout), to a fully bulked-up multi-phase hyperconcentrated flow (varying frequency patterns depending on the lahar phase), to a slurry flow (bedload dominant). Estimated directionality ratios show the elongation of the lahar with distance down the channel, where each recording station depicts a similar pattern but for differing lengths of time. Furthermore, using directionality ratios shows extraordinary promise for lahar monitoring and detection systems where streamflow is present in the channel. [ABSTRACT FROM AUTHOR]

Droughts have severely affected Afghanistan over the last four decades, leading to critical food shortages where two-thirds of the country's population are in a food crisis. Long years of conflict have lowered the country's ability to deal with hazards such as drought which can rapidly escalate into disasters. Understanding the spatial and temporal distribution of droughts is needed to be able to respond effectively to disasters and plan for future occurrences. This study used Standardized Precipitation Evapotranspiration Index (SPEI) at monthly, seasonal and annual temporal scales to map the spatiotemporal change dynamics of drought characteristics (distribution, frequency, duration and severity) in Afghanistan. SPEI indices were mapped for river basins, disaggregated into 189 sub-catchments, using monthly precipitation and potential evapotranspiration derived from temperature station observations from 1980 to 2017. The results show these multi-dimensional drought characteristics vary along different years, change among sub-catchments, and differ across temporal scales. During the 38 years, the driest decade and period are 2000s and 1999–2022, respectively. The 2000–01 water year is the driest with the whole country experiencing 'severe' to 'extreme' drought, more than 53% (87 sub-catchments) suffering the worst drought in history, and about 58% (94 sub-catchments) having 'very frequent' drought (7 to 8 months) or 'extremely frequent' drought (9 to 10 months). The estimated seasonal duration and severity present significant variations across the study area and among the study period. The nation also suffers from recurring droughts with varying length and intensity in 2004, 2006, 2008 and most recently 2011. There is a trend towards increasing drought with longer duration and higher severity extending all over sub-catchments from southeast to north and central regions. These datasets and maps help to fill the knowledge gap on detailed sub-catchment scale meteorological drought characteristics in Afghanistan. The study findings improve our understanding of the influences of climate change on the drought dynamics and can guide catchment planning for reliable adaptation to and mitigation against future droughts. [ABSTRACT FROM AUTHOR]

The existence of glacial lakes in the southeastern Tibetan Plateau (SETP) is a potential hazard to downstream regions, as the outburst of such lakes has the potential to result in disastrous glacial lake outburst floods (GLOFs). In the present study, we conducted a comprehensive investigation of Bienong Co, a moraine-dammed glacial lake in the SETP. First, the lake basin morphology was determined, and the lake volume was estimated, showing that the maximum lake depth is ∼181 m and the lake volume is ∼102.3×106 m 3. These scenarios included the possibility of GLOFs being triggered by ice avalanches (Scenarios A1–3) from the mother glacier or by landslides from the lateral moraines (Scenarios B1–3 and C1–3). Avalanche volumes of the nine trigger scenarios were obtained from the Rapid Mass Movement Simulation (RAMMS) modeling results. Next, the Basic Simulation Environment for Computation of Environmental Flow and Natural Hazard Simulation (BASEMENT) model was used to simulate the generation and propagation of the avalanche-induced displacement waves in the lake. With the model, the overtopping flows and erosion on the moraine dam and the subsequent downstream floods were also simulated. The results indicate that the ice avalanche scenario may cause the largest mass volume entering the lake, resulting in a displacement wave up to 25.2 m in amplitude (Scenario A3) near the moraine dam. Landslide scenarios with smaller volumes entering the lake result in smaller displacement waves. Scenarios A1, A2, and A3 result in released water volumes from the lake of 24.1×106 , 25.3×106 , and 26.4×106 m 3 , respectively. Corresponding peak discharges at the moraine dam are 4996, 7817, and 13 078 m 3 s -1 , respectively. These high discharges cause erosion of the moraine dam, resulting in breach widths of 295, 339, and 368 m, respectively, with the generally similar breach depth of approximately 19 m. In landslide scenarios, only overtopping flows generated by Scenarios B3 and C3 cause erosion on the moraine dam, with breach depths of 6.5 and 7.9 m and breach widths of 153 and 169 m, respectively. According to our simulations, GLOFs generated by Scenarios A1–3 all flow through 18 settlements downstream in 20 h, threatening more than half of them. Both Scenarios B3 and C3 produce GLOFs that flow through the first eight settlements downstream in 20 h and have a relatively small impact on them. Comparisons of the area, depth, and volume of glacial lakes for which the bathymetry data are available show that Bienong Co is the deepest known glacial lake with the same surface area on the Tibetan Plateau. This study could provide a new insight into moraine-dammed glacial lakes in the SETP and be a valuable reference for GLOF disaster prevention for the local government. [ABSTRACT FROM AUTHOR]

Regular monitoring of drought events, watershed characterization, management, and development efforts is crucial for future disaster predictions and mitigation strategies. The drought susceptibility investigation has been carried out in the Ken River Basin of Bundelkhand region, one of the most drought‐prone areas in India. Proxies used in the present study are long‐term climatological data (rainfall, standardized precipitation index, and aridity index), satellite data (slope, drainage density [DD], distance to river, and normalized difference vegetation index), lithology, lineament density, and groundwater depth. By the analytical hierarchy process, weightage of each factor is assigned according to its importance. Study shows that nearly 48% of the area of the basin experiences moderate to severe drought conditions. In the last five decades, there have been 22 years of extreme drought, with the most extended period being 1972–1974 and the driest year being 2006–2007. Sensitivity analysis reveals that lithology, slope, and DD are the most significant parameters in the susceptibility analysis. Model validation through an artificial neural network demonstrates the model's high accuracy (0.9) and sensitivity with minor errors. An integrated study of drought susceptibility and morphometry is useful for identifying the drought risk hotspots in the basin. The investigation will be helpful in river basin management and disaster management strategies. [ABSTRACT FROM AUTHOR]

This research evaluates the applicability of different types of hydrological models to simulate discharge behavior scenarios in a northern Moroccan watershed, Oued Laou Watershed (OLW). In this context, an improved understanding of the runoff mechanisms through hydrological modeling of the OLW can assist in the hazard risk management and facilitate the effective planning of water resources. For that end, a multitude of hydrological models were used to perform a very efficient modelling, and a comparative approach was adopted. Comparison of the models allowed the determination of potential sources of uncertainty in hydrological modelling of a subhumid watershed. Three models (ATelier Hydrologique Spatialisé (ATHYS), Hydrologic Modeling System (HEC-HMS), and Soil and Water Assessment Tool (SWAT)) with different characteristics were employed for a continuous modelling approach. The models were calibrated and validated using observed daily rainfall and streamflow data for 4 years (2004–2008) and 3 years (2009–2011), respectively. The multi-criteria model comparison (R², NSE, RSR, and PBIAS) showed that all three models are capable of reproducing the observed flows. The SWAT model performed well over both periods (NSE = 0.76 for calibration), with an improvement in validation (NSE = 0.84). A good agreement was also observed in the HEC-HMS model outputs, with an approximately stable NSE of 0.77 and 0.78 for calibration and validation phases, respectively. The ATHYS model showed a NSE value of 0.67 during the calibration, with a decrease of 0.06 towards the validation period. The other performance criteria confirmed these findings. Additionally, results suggest that semi-distributed and conceptual hydrological models are particularly suitable for the OLW given their physical heterogeneity. Generally, the integration of these models may be suitable for water resources assessment in OLW. [ABSTRACT FROM AUTHOR]

Rivers play a major role within ecosystems and society, including for domestic, industrial, and agricultural uses, and in power generation. Forecasting of suspended sediment yield (SSY) is critical for design, management, planning, and disaster prevention in river basin systems. It is difficult to forecast the SSY using conventional methods because these approaches cannot handle complicated non-stationarity and non-linearity. Artificial intelligence techniques have gained popularity in water resources due to handling complex problems of SSY. In this study, a fully automated generalized single hybrid intelligent artificial neural network (ANN)-based genetic algorithm (GA) forecasting model was developed using water discharge, temperature, rainfall, SSY, rock type, relief, and catchment area data of eleven gauging stations for forecasting the SSY. It is applied at individual gauging stations for SSY forecasting in the Mahanadi River which is one of India's largest peninsular rivers. All parameters of the ANN are optimized automatically and simultaneously using the GA. The multi-objective algorithm was applied to optimize the two conflicting objective functions (error variance and bias). The mean square error objective function was considered for the single-objective optimization model. Single and multi-objective GA-based ANN, autoregressive and multivariate autoregressive models were compared to each other. It was found that the single-objective GA-based ANN model provided the best accuracy among all comparative models, and it is the most suitable substitute for forecasting SSY. If the measurement of SSY is unavailable, then single-objective GA-based ANN modeling approaches can be recommended for forecasting SSY due to comparatively superior performance and simplicity of implementation. [ABSTRACT FROM AUTHOR]

Flooding is a major natural hazard that can cause significant damage to socioeconomic and ecological systems. This study presents an approach to producing the maximum flood inundation and flood duration maps over the Chao Phraya River Basin (CPRB), Thailand. An integrated numerical model and spatial analysis tool were utilized in this study. The Rainfall-Runoff-Inundation (RRI) model was first used to simulate both river discharge and inundation depth. Then, the maximum flood inundation and flood duration maps with different return periods were estimated using a Geographical Information System (GIS) tool. The results illustrate that the flood inundation areas were spread out, starting from Nakhon Sawan Province, which is located in the central part of the basin. The maximum flood inundation depth could reach up to approximately 7.71, 8.28, and 8.78 m for the flood return periods of 50, 100, and 200 years, respectively. The results also indicate that the inundation areas over the CPRB could cover approximately 21,837, 23,392, and 24,533 km2 for flood return periods of 50, 100, and 200 years, respectively. The longest flood durations for return periods of 50, 100, and 200 years were approximately 159, 177, and 198 days, respectively. The longest flood duration occurred in the vicinity of the Nakhon Sawan. This study suggests that flood inundation areas and duration mapping could provide supporting information regarding the impacts caused by varying degrees of flood hazards and can be used to enhance comprehensive disaster risk management planning. [ABSTRACT FROM AUTHOR]

Much attention has recently been devoted to the qualitative relationship between climate factors and drought; however, the influences of climate variability, land-use/cover changes (LUCC), and other human activities on drought have rarely been quantitatively assessed. Based on the Soil and Water Assessment Tool (SWAT) model and the Palmer drought severity index (PDSI), this study presents a framework to quantify drought changes in an attribution study, and quantifies the effects of climate factors, LUCC, and other human activities on drought in a typical basin (Yihe River) in eastern China from 1980 to 2019. (1) The SWAT–PDSI results revealed a slight decreasing trend from 1980 to 2019, indicating that the degree of drought increased—especially in the middle of the basin. (2) The precipitation in the basin exhibited a downward trend (−2.7 mm/10 a), while the temperature exhibited a significant increasing trend (0.13 °C/10 a, p < 0.05). Over the past 40 years, LUCC in the Yihe River Basin was mainly characterized by a reduction in the dryland area (149 km2) and an increase in the built-up area (135 km2), which changed by −1.77% and 18.96%, respectively. (3) Climate fluctuation was the main driving factor of drought change, with a contribution rate ranging from 68 to 84%, and the contribution to drought gradually increased. Among the various factors, the contribution of temperature exceeded that of precipitation from 2010 to 2019, suggesting that temperature has become the most important climate factor affecting drought. The contribution rates of LUCC to drought changes over the periods 1990–1999, 2000–2009, and 2010–2019 were 7.8%, 18%, and 12.6%, respectively. This indicates that the relative contributions of other human activities to drought changes gradually decreased. This study refines the drought attribution framework, which could provide scientific support for the quantitative attribution of drought and the formulation of disaster prevention and reduction strategies. [ABSTRACT FROM AUTHOR]

The construction of refuge spaces in rapidly urbanizing historic cities is a challenging task owing to their complex urban form, unique urban fabric, and historic preservation requirements. Refuge green space (RGS) is a green space that can serve as an emergency shelter in cities, providing a flexible means to increase the emergency shelter capacity for rapidly urbanized historic cities. After major earthquakes, spatial accessibility to GRSs is a critical planning strategy for disaster prevention and emergency response in historic cities. To match the RGS planning with the emergency service demand, we must examine the spatial disparity in access to existing RGSs. In this study, the urban area of Nanjing was selected as the target region to analyze the spatial disparity in access to RGSs using the Gaussian two-step floating catchment area method at four evacuation times (10, 20, 30, and 60 min). The results showed that the spatial accessibility exhibited clustering characteristics, where high-accessibility spaces were mainly distributed in the northern and southern regions of Nanjing. The increase in the evacuation time improved accessibility to RGSs, but the existing RGSs still could not sufficiently satisfy the emergency shelter needs of citizens. Based on the bivariate local Moran's I analysis of the RGS accessibility and population density, the spatial mismatch regions were dominant in the center of the urban area. These findings not only are expected to assist emergency planners by improving their strategic plans for emergency shelter investment in Nanjing and their ability to respond to catastrophic earthquakes, but also provide a strong reference for the construction of a safe environment in other rapidly developing historic cities that face earthquake threats. [ABSTRACT FROM AUTHOR]

Glacial till is a special soil in alpine mountainous areas, which often induces geohazards such as debris flows and landslides due to the influence of special geological environmental conditions in alpine mountainous areas. The change in the structure of glacial till is the main cause of geohazards. Glacial till structure is one of the important factors affecting the mechanical properties of soil. It can explain the mechanical phenomena of soil engineering and establish the quantitative relationship between soil structure and macro–mechanical properties. However, there are few systematic research results on its structure. For this reason, the intact glacial till in the Moxi River Basin, South of Kangding City, Tibetan Autonomous Prefecture of Garzê, Sichuan Province was taken as the research object, and the meso-structure and micro-structure of intact glacial till were studied using CT scanning and scanning electron microscopy (SEM). The meso-structure and micro-structure images of the interior of intact glacial till were obtained and the porosity, particle shape, directivity and structural unit were analyzed. The results show that: (1) the average porosity of longitudinal and transverse sections of intact glacial till are 24.92% and 24.35%, respectively, and the difference is not significant; (2) the average circularity of the particles in the longitudinal and transverse sections is 0.836 and 0.802, respectively, and the average aspect ratio is 2.5 and 3.7, respectively. The shape of the particles in the longitudinal section is more circular than in the transverse section, and the orientation of the particles in the transverse sectional direction is more obvious; (3) the main mineral components of the glacial till sample are mica, feldspar and quartz. In the process of transportation and deposition, the mineral particles undergo different degrees of grinding, crushing and dissolution. The particles are mainly formed by calcareous cementation, and the cementation is dense. The structure is mainly a skeleton structure composed of fine particles that are wrapped or filled. These findings provide the scientific basis for highway-, railway- and hydro-power-station construction and disaster prevention and mitigation in the alpine mountainous area. [ABSTRACT FROM AUTHOR]

In this study, an alternative solution for flood risk management in complex cross-border regions is presented. In these cases, due to different flood risk management legislative approaches, there is a lack of joint cooperation between the involved countries. As a main consequence, LiDAR-derived digital elevation models and accurate flood hazard maps obtained by means of hydrological and hydraulic modeling are missing or are incomplete. This is also the case for the Prut River, which acts as a natural boundary between European Union (EU) member Romania and non-EU countries Ukraine and Republic of Moldova. Here, flood hazard maps were developed under the European Floods Directive (2007/60/EC) only for the Romanian territory and only for the 1% exceeding probability (respectively floods that can occur once every 100 years). For this reason, in order to improve the flood hazard management in the area and consider all cross-border territories, a fully remote sensing approach was considered. Using open-source SAR Sentinel-1 and Sentinel-2 data characterized by an improved temporal resolution, we managed to capture the maximum spatial extent of a flood event that took place in the aforementioned river sector (middle Prut River course) during the 24 and 27 June 2020. Moreover, by means of flood frequency analysis, the development of a transboundary flood hazard map with an assigned probability, specific to the maximum flow rate recorded during the event, was realized. [ABSTRACT FROM AUTHOR]

In this study, the standardized precipitation index (SPI) data in Hunan Province from 1961 to 2020 is adopted. Based on the critical slowing down theory, the moving t-test is firstly used to determine the time of drought-flood state transition in the Dongting Lake basin. Afterwards, by means of the variance and autocorrelation coefficient that characterize the phenomenon of critical slowing down, the early-warning signals indicating the drought-flood state in the Dongting Lake basin are explored. The results show that an obvious drought-to-flood (flood-to-drought) event occurred around 1993 (2003) in the Dongting Lake basin in recent 60 years. The critical slowing down phenomena of the increases in the variance and autocorrelation coefficient, which are detected 5–10 years in advance, can be considered as early-warning signals indicating the drought-flood state transition. Through the studies on the drought-flood state and related early-warning signals for the Dongting Lake basin, the reliabilities of the variance and autocorrelation coefficient-based early-warning signals for abrupt changes are demonstrated. It is expected that the wide application of this method could provide important scientific and technological support for disaster prevention and mitigation in the Dongting Lake basin, and even in the middle and lower reaches of the Yangtze River. [ABSTRACT FROM AUTHOR]