Search Results (28)

Climate change has intensified the melting of glaciers and permafrost in high-altitude cold regions, leading to more frequent extreme hydrological events. This has caused significant variations in the spatiotemporal distribution of meltwater runoff from the headwater cryosphere, posing a major challenge to regional water security. In this study, the HBV hydrological model was set up and driven by CMIP6 global climate model outputs to investigate the multi-scale temporal variations of runoff under different climate change scenarios in the Tuotuo River Basin (TRB) within the source region of the Yangtze River (SRYR). The results suggest that the TRB will undergo significant warming and wetting in the future, with increasing precipitation primarily occurring from May to October and a notable rise in annual temperature. Both temperature and precipitation trends intensify under more extreme climate scenarios. Under all climate scenarios, annual runoff generally exhibits an upward trend, except under the SSP1-2.6 scenario, where a slight decline in total runoff is projected for the late 21st century (2061–2090). The increase in total runoff is primarily concentrated between May and October, driven by enhanced rainfall and meltwater contributions, while snowmelt runoff also shows an increase, but accounts for a smaller percentage of the total runoff and has a smaller impact on the total runoff. Precipitation is the primary driver of annual runoff depth changes, with temperature effects varying by scenario and period. Under high emissions, intensified warming and glacier melt amplify runoff, while low emissions show stable warming with precipitation dominating runoff changes. Full article

Flash floods, typically triggered by natural events such as heavy rainfall, snowmelt, and dam failures, are characterized by abrupt onset, destructive power, unpredictability, and challenges in mitigation. This study investigates the spatial distribution patterns and driving mechanisms of rainstorm-induced flash flood disasters in the Yarlung Tsangpo River Basin (YTRB) by integrating topography, hydrometeorology, human activity data, and historical disaster records. Through a multi-method spatial analysis framework—including kernel density estimation, standard deviation ellipse, spatial autocorrelation (Moran’s I and Getis–Ord Gi*), and the optimal parameter geographic detector (OPGD) model (integrating univariate analysis and interaction detection)—we reveal multiscale disaster dynamics across county, township, and small catchment levels. Key findings indicate that finer spatial resolution (e.g., small catchment scale) enhances precision when identifying high-risk zones. Temporally, the number of rainstorm-induced flash floods increased significantly and disaster-affected areas expanded significantly from the 1980s to the 2010s, with a peak spatial dispersion observed during 2010–2019, reflecting a westward shift in disaster distribution. Spatial aggregation of flash floods persisted throughout the study period, concentrated in the central basin. Village density (TD) was identified as the predominant human activity factor, exhibiting nonlinear amplification through interactions with short-duration heavy rainfall (particularly 3 h [P3] and 6 h [P6] maximum precipitations) and GDP. These precipitation durations demonstrated compounding risk effects, where sustained rainfall intensity progressively heightened disaster potential. Topographic and ecological interactions, particularly between elevation (DEM) and vegetation type (VT), further modulate disaster intensity. These findings provide critical insights for risk zonation and targeted prevention strategies in high-altitude river basins. Full article

Stormwater runoff containing road deicing salts has led to the increasing salinization of surface waters in northern climates, and urban municipalities are increasingly being mandated to manage stormwater runoff to improve water quality. We assessed chloride concentrations in runoff from late-winter snowmelt and rainfall events flowing into an urban Minnesota, USA, lake during two different years, predicting that specific stormwater drainages with greater concentrations of roadways and parking lots would produce higher chloride loads during runoff than other drainages with fewer impervious surfaces. Chloride levels were measured in runoff draining into Lake Winona via 11 stormwater outfalls, a single channelized creek inlet, and two in-lake locations during each snowmelt or rainfall event from mid-February through early April in 2021 and 2023. In total, 33% of outfall runoff samples entering the lake collected over two years had chloride concentrations exceeding the 230 ppm chronic standard for aquatic life in USA surface waters, but no sample exceeded the 860 ppm acute standard. Chloride concentrations in outfall runoff (mean ± SD; 190 ± 191 ppm, n = 143) were significantly higher than in-lake concentrations (43 ± 14 ppm, n = 25), but chloride levels did not differ significantly between snowmelt and rainfall runoff events. Runoff from highway locations had higher chloride concentrations than runoff from residential areas. Site-specific chloride levels were highly variable both within and between years, with only a single monitored outfall displaying high chloride levels in both years. There are several possible avenues available within the city to reduce deicer use, capture and treat salt-laden runoff, and prevent or reduce the delivery of chlorides to the lake. Full article

In the context of rising temperatures and increasing humidity in Northwest China, substantial gaps remain in understanding the mechanisms of land–atmosphere cloud–precipitation coupling across the northeastern Tibetan Plateau (TP), Loess Plateau (LP), and Huangshui Valley (HV). This study addresses these gaps by investigating cloud properties and precipitation patterns utilizing the Fengyun-4 Satellite Quantitative Precipitation Estimation Product (FY4A-QPE) and ERA5 datasets. We specifically focus on Lanzhou, a pivotal city within the LP, and Xining, which epitomizes the HV. Our findings reveal that diurnal variations in precipitation are significantly less pronounced in the eastern regions compared to northeastern TP. This discrepancy is attributed to marked diurnal fluctuations in convective available potential energy (CAPE) and wind shear between 200 and 500 hPa. While both cities share similar wind shear patterns and moisture transport directions, Xining benefits from enhanced snowmelt and effective water retention in surrounding mountains, resulting in higher precipitation levels. Conversely, Lanzhou suffers from moisture deficits, with dry, hot winds exacerbating the situation. Notably, precipitation in Xining is strongly correlated with CAPE, influenced by diurnal variability, and intensified by valley and lake–land breezes, which drive afternoon convection. In contrast, Lanzhou’s precipitation exhibits a weak relationship with CAPE, as even elevated values fail to generate significant cloud formation due to insufficient moisture. The ongoing trends of warming and humidification may lead to improved precipitation patterns, especially in the HV, with potential ecological benefits. However, concentrated rainfall during summer afternoons and midnights raises concerns regarding extreme weather events, highlighting the susceptibility of the HV to geological hazards. This research underscores the need to further explore the uncertainties inherent in precipitation dynamics in these regions. Full article

The conventional measuring methods (runoff plots and soil morphological comparison) and models (WaTEM/SEDEM and regional model of Russian State Hydrological Institute (SHI)) were tested with regard to the Southern Cis-Ural region of Russia, along with data from rainfall simulation for assessing soil erosion. Compared with conventional methods, which require long-running field observations, using erosion models and rainfall simulation is less time-consuming and is found to be fairly accurate for assessing long-term average rates of soil erosion and deposition. In this context, ¹³⁷Cs can also be used as a marker of soil redistribution on the slope. The data of soil loss and sedimentation rates obtained by using conventional measuring methods were in agreement with the data based on the used contemporary modeling approaches. According to the erosion model calculations and data on the fallout of radionuclides in the Southern Cis-Ural (54°50–25′ N and 55°44–50′ E), the average long-term annual soil losses were ~1.3 t·ha⁻¹ yr⁻¹ in moderate (5°) arable slopes and ~0.2 t·ha⁻¹ yr⁻¹ in meadows. In forests, surface erosion is negligible, or its rates are similar to the rate of soil formation of clay–illuvial chernozems. The rates of soil erosion and sediment deposition on the arable land obtained using different methods were found to be very close. All the methods, including the WaTEM/SEDEM, allowed us to measure both soil erosion and intra-slope sedimentation. The regional SHI model fairly accurately assesses soil erosion in the years when erosion events occurred; however, soil erosion as a result of snowmelt did not occur every year, which should be taken into account when modeling. The concentrations of ¹³⁷Cs in the topsoil layer (0–20 cm) varied from 0.9 to 9.8 Bq·kg⁻¹, and the ¹³⁷Cs inventories were 1.6–5.1 kBq·m⁻², with the highest values found under the forest. The air dose rate in the forest was higher than in open areas and above the average of 0.12 μSv·h⁻¹ on the slope (0.1 μSv·h⁻¹ in the meadow and 0.08 μSv·h⁻¹ on the arable land), with the value increasing from the watershed to the lower part of the slope in all the areas. The γ-background level in the studied ecosystems did not exceed the maximum permissible levels. Full article

Debris flow, driven by natural events like heavy rainfall and snowmelt, involves sediment, rocks, and water, posing destructive threats to life and infrastructure. The accurate prediction of its activity range is crucial for prevention and mitigation efforts. Cellular automata circumvent is the cumbersome process of solving partial differential equations, thereby efficiently simulating complex dynamic systems. Given the anisotropic characteristics of square cells in the simulation of dynamic systems, this paper proposes a novel approach, utilizing a hexagonal cellular automaton for the numerical simulation of debris flows, where the direction judgment efficiency increased by 25%. Employing cubic interpolation, the model thereby determines the central elevation of each hexagonal cell. By modifying the flow direction function and stopping conditions, it achieves more accurate predictions of the debris flow run-out extent. This method was applied to the 2010 Yohutagawa debris flow event and the flume test. To evaluate the simulation’s accuracy, the $\mathsf{\Omega }$ value and $F\beta$ score were used. The $\mathsf{\Omega }$ value is a comprehensive evaluation factor that takes into account missed or misjudgment areas. On this basis, the $F\beta$ score emphasizes that the missed identification of debris flow areas will bring greater harm. Research indicates that the $\mathsf{\Omega }$ value showed improvements of 6.47% and 3.96%, respectively, while the $F\beta$ score improved by 3.10% and 4.61%. Full article

The continuous downward movement exhibited by the Lashagou landslide group in recent years poses a significant threat to the safety of both vehicles and pedestrians traversing the highway G310. By integrating geomorphological interpretation using multi-temporal optical images, interferometric synthetic aperture radar (InSAR) measurements, and continuous global navigation satellite system (GNSS) observations, this paper traced the formation period of the Lashagou landslide group, and explored its kinematic behavior under external drivers such as rainfall and snowmelt. The results indicate that the formation period can be specifically categorized into three periods: before, during, and after the construction of highway G310. The construction of highway G310 is the direct cause and prerequisite for the formation of the Lashagou landslide group, whereas summer precipitation and spring snowmelt are the external driving factors contributing to its continuous downward movement. Additionally, both the long-term seasonal downslope movement and transient acceleration events are strongly controlled by rainfall, and there is a time lag of approximately 1–2 days between the transient acceleration and heavy rainfall events. This study highlights the benefits of leveraging multi-source remote sensing data to investigate slow-moving landslides, which is advantageous for the implementation of effective control and engineering intervention to mitigate potential landslide disasters. Full article

The highly temporal variability of the hydrological response in Mediterranean areas affects the operation of hydropower systems, especially in run-of-river (RoR) plants located in mountainous areas. Here, the water flow regime strongly determines failure, defined as no operating days due to inflows below the minimum operating flow. A Bayesian dynamics stochastic model was developed with statistical modeling of both rainfall as the forcing agent and water inflows to the plants as the dependent variable using two approaches—parametric adjustments and non-parametric methods. Failure frequency analysis and its related operationality, along with their uncertainty associated with different time scales, were performed through 250 Monte Carlo stochastic replications of a 20-year period of daily rainfall. Finally, a scenario analysis was performed, including the effects of 3 and 30 days of water storage in a plant loading chamber to minimize the plant’s dependence on the river’s flow. The approach was applied to a mini-hydropower RoR plant in Poqueira (Southern Spain), located in a semi-arid Mediterranean alpine area. The results reveal that the influence of snow had greater operationality in the spring months when snowmelt was outstanding, with a 25% probability of having fewer than 2 days of failure in May and April, as opposed to 12 days in the winter months. Moreover, the effect of water storage was greater between June and November, when rainfall events are scarce, and snowmelt has almost finished with operationality levels of 0.04–0.74 for 15 days of failure without storage, which increased to 0.1–0.87 with 3 days of storage. The methodology proposed constitutes a simple and useful tool to assess uncertainty in the operationality of RoR plants in Mediterranean mountainous areas where rainfall constitutes the main source of uncertainty in river flows. Full article

Due to the changing climate, flash floods have been increasing recently and are expected to further increase in the future. Flash floods caused by heavy rainfall with snowmelt contribution due to sudden rises in temperature or rain-on-snow events have become common in autumn and winter in Norway. These events have caused widespread damage, closure of roads and bridges, and landslides, leading to evacuations in the affected areas. Hence, it is important to analyze such events. In this study, the rain-on-grid technique in the TELEMAC-2D hydrodynamic model was used for runoff modelling and routing using input of snowmelt, and precipitation partitioned on snow and rain was calculated via the hydrological model HBV. The results show the importance of including snowmelt for distributed runoff generation and how the rain-on-grid technique enables extracting flow hydrographs anywhere in the catchment. It is also possible to extract the flow velocities and water depth at each time step, revealing the critical locations in the catchment in terms of flooding and shear stresses. The rain-on-grid model works particularly well for single peak events, but the results indicate the need for a time-varying curve number for multiple peak flood events or the implementation of another infiltration model. Full article

This study aims to evaluate the potential of ERA5 precipitation and temperature reanalysis for snow water equivalent (SWE) simulation by considering the role of catchment spatial scale in controlling the errors obtained by comparison with corresponding SWE simulations from ground stations. This is obtained by exploiting a semi-distributed snowpack model (TOPMELT) implemented over the upper Adige River basin in the Eastern Italian Alps, where 16 sub-catchments of varying sizes are considered. The comparison is carried out from 1992 to 2019. The findings show that ERA5 precipitation overestimated low-intensity rainfall (drizzle problem) and underestimated high-intensity rainfall, while ERA5 temperature underestimated observations. The overestimation of low-intensity rainfall created fictitious low-intensity snowfall events, which, when combined with colder ERA5 temperature, resulted in delayed snowmelt and increased fictitious snow-cover days over the study area. The quantile mapping (QM) technique was used to remove errors in ERA5 variables. It was shown that ERA5 could struggle to resolve the orographic enhancement in precipitation, which may be particularly important during high-SWE years. This reduces the positive precipitation bias during those years, thus reducing comparatively the ability of the quantile mapping technique to correct for bias homogeneously during all years. This study highlighted the importance of temperature correction over precipitation correction in SWE simulation, particularly for smaller basins. Full article

Concern for the offsite impact of eroded sediment and the need to develop effective catchment sediment management strategies has directed attention to the need for an improved understanding of the primary sediment sources within catchments and the potential of sediment source fingerprinting techniques to provide such information. The study reported here was undertaken in the black soil region of Northeast China, where soil erosion is seen as a serious threat to the sustainable use of soil resources and offsite impacts of eroded soil are also concerned. The study applies source fingerprinting techniques to the evaluation of sediment sources in a small (3.46 km²) agricultural catchment. Sediment sources from five snowmelt and five rainfall events of varying magnitude were contrasted. Three key potential sediment sources were identified within the study catchment: gullies, cultivated topsoil and uncultivated topsoil. Geochemical properties of the source materials (Ti, Ga, Br and Ba) were used as composite fingerprints capable of discriminating between the three potential sources. A mixing model, optimized using a genetic algorithm and coupled with a Monte Carlo procedure to quantify the uncertainty associated with the resulting estimates, was used for source apportionment. The results indicated mean source contributions for the set of 10 events for cultivated topsoil, uncultivated topsoil and the gullies of ~30%, ~10% and ~60%, respectively. In general, snowmelt and rainfall events were characterized by increased contributions from gully sources and cultivated topsoil, respectively. The study is seen as demonstrating the potential for using source tracing techniques to investigate sediment sources in environments where strong seasonal contrasts between snowmelt and rainfall events exist. Full article

The fundamental assumption of flood frequency analysis is that flood samples are generated by the same flood generation mechanism (FGM). However, flood events are usually triggered by the interaction of meteorological factors and watershed properties, which results in different FMGs. To solve this problem, researchers have put forward traditional two-component mixture distributions (TCMD-T) without clearly linking each component distribution to an explicit FGM. In order to improve the physical meaning of mixture distributions in seasonal snow-covered areas, the ratio of rainfall to flood volume (referred to as rainfall–flood ratio, RF) method was used to classify distinct FGMs. Thus, the weighting coefficient of each component distribution was determined in advance in the rainfall–flood ratio based TCMD (TCMD-RF). TCMD-RF model was applied to 34 basins in Norway. The results showed that flood types can be clearly divided into rain-on-snow-induced flood, snowmelt-induced flood and rainfall-induced flood. Moreover, the design flood and associated uncertainties were also estimated. It is found that TCMD-RF model can reduce the uncertainties of design flood by 20% compared with TCMD-T. The superiority of TCMD-RF is attributed to its clear classification of FGMs, thus determining the weighting coefficients without optimization and simplifying the parameter estimation procedure of mixture distributions. Full article

The Gajevo landslide is located in a hilly area of northern Croatia, where numerous landslides endanger and damage houses, roads, water systems, and power lines. Nevertheless, available landslide data are relatively scarce. Therefore, the Gajevo landslide location was chosen for detailed research and the development of a typical landslide model for this area. During initial research, the geographical and geological settings were reviewed and historical orthophotos were analysed. Due to the complexity and vulnerability of the area, the location required detailed investigations and the integration of multi-level data: remote (based on high-resolution LiDAR data) and field landslide mapping were performed and a map of the landslide area was developed. Precipitation data were reviewed, while shallow boreholes with material sampling and geophysical measurements provided information on material characteristics and 3D (depth) insight. As a result, knowledge was gained about material resistivity and composition along with the depth of sliding surfaces, and an engineering geological map of the Gajevo landslide area with the landslide and directly endangered areas marked was developed to be used by the local community in landslide risk assessment. As it is reasonable to expect that an extreme rainfall event will occur in combination with snowmelt in the coming years, resulting in the reactivation of Gajevo landslide, further research and continuous landslide monitoring are recommended. Full article

Under global warming, the permafrost-underlain headwater catchments of the Tibetan Plateau have undergone extensive permafrost degradation and changes in precipitation characteristics, which may substantially alter the riverine suspended sediment and riverine solute fluxes. However, these fluxes and their influencing factors in such catchments are poorly understood. We studied the suspended sediment and solute fluxes in a permafrost-underlain headwater catchment on the northeastern Tibetan Plateau, based on comprehensive measurements of various water types in spring and summer in 2017. The daily flux of suspended sediment in spring was close to that in summer, but heavy rainfall events following a relatively long dry period made the largest contribution to the suspended sediment fluxes in summer. The riverine solute flux (in tons) was 12.6% and 27.8% of the suspended sediment flux (in tons) in spring and summer, indicating the dominating role of physical weathering in total material exportation. The snowmelt mobilized more suspended sediment fluxes and fewer solutes fluxes than summer rain, which may be due to the meltwater erosion and freeze–thaw processes in spring and the thicker thawed soil layer and better vegetation coverage in summer, and the longer contact time between the soil pore water and the soil and rock minerals after the thawing of frozen soil. The input of snowmelt driven by higher air temperatures in spring and the direct input of rainfall in summer would both act to dilute the stream water; however, the supra-permafrost water, with high solute contents, recharged the adjacent streamflow as frozen soil seeps and thus moderated the decrease in the riverine solute content during heavy snowmelt or rainfall events. With the permafrost degradation under future global warming, the solute fluxes in permafrost-underlain headwater catchments may increase, but the suspended sediment flux in spring may decrease due to the expansion of discontinuous permafrost areas and active layer thickness. Full article

The water level of the Urmia Lake Basin (ULB), located in the northwest of Iran, started to decline dramatically about two decades ago. As a result, the area has become the focus of increasing scientific research. In order to improve understanding of the connections between declining lake level and changing local drought conditions, three common drought indices are employed to analyze the period 1981–2018: The Standard Precipitation Index (SPI), the Standard Precipitation-Evaporation Index (SPEI), and the Standardized Snow Melt and Rain Index (SMRI). Although rainfall is a significant indicator of water availability, temperature is also a key factor since it determines rates of evapotranspiration and snowmelt. These different processes are captured by the three drought indices mentioned above to describe drought in the catchment. Therefore, the main objective of this paper is to provide a comparative analysis of drought over the ULB by incorporating different drought indices. Since there is not enough long-term observational data of sufficiently high density for the ULB region, ECMWF Reanalysis data version 5(ERA5) has been used to estimate SPI, SPEI, and SMRI drought indicators. These are shown to work well, with AUC-ROC > 0.9, in capturing different classes of basin drought characteristics. The results show a downward trend for SPEI and SMRI (but not for SPI), suggesting that both evaporation and lack of snowmelt exacerbate droughts. Owing to the increasing temperatures in the basin and the decrease in snowfall, drought events have become particularly pronounced in the SPEI and SMRI time series since 1995. No significant SMRI drought was detected prior to 1995, thus indicating that sufficient snowfall was available at the beginning of the study period. The study results also reveal that the decrease in lake water level from 2010 to 2018 was not only caused by changes in the water balance components, but also by unsustainable water management. Full article