Study region: The study focuses on the Indus River Basin and southern Pakistan, severely affected by flooding in 2022. Study focus: This study assessed how land surface temperature, snow cover, soil moisture, and precipitation contributed to the deluge of 2022. This study mainly investigated MODIS-AIRS land surface temperature, MODIS snow cover (NDSI), SMAP soil moisture, and GPM IMERG precipitation accumulation. Furthermore, different flood visualization and mapping techniques were applied to delineate the flood extent map using Landsat 8-9, Sentinel-2 MSI, and Sentinel-1 SAR data. New hydrological insights for the region: The region experienced some of the most anomalous climatic events in 2022, such as prolonged heatwaves as observed with higher-than-average land surface temperatures and subsequent rapid decline in snow cover extent during the spring, increased soil moisture followed by an abnormal amount of extreme monsoon precipitation in the summer. The upper subbasins experienced more than 8 degrees C in positive temperature anomaly, indicating a warmer climate in spring. Subsequently, the snow cover declined by more than 25 % in the upper subbasins. Further, higher surface soil moisture values (> 0.3 m3/m3) were observed in the basin during the spring due to the rapid snow and ice melt. Furthermore, the basin received more than 200 mm of rainfall compared to the long-term average rainfall of about 98 mm, translating to about 300 % more rainfall than usual in July and August. The analysis helps understand the spatial and temporal variability within the basin and facilitates the understanding of factors and their intricate connections contributing to flooding.

Accurately understanding flood evolution and its attribution is crucial for watershed water resource management as well as disaster prevention and mitigation. The source region of the Yellow River (SRYR) has experienced several severe floods over the past few decades, but the driving factor influencing flood volume variation in the SRYR remains unclear. In this study, the Budyko framework was used to quantify the effects of climate change, vegetation growth, and permafrost degradation on flood volume variation in six basins of the SRYR. The results showed that the flood volume decreased before 2000 and increased after 2000, but the average value after 2000 remained lower than that before 2000. Flood volume is most sensitive to changes in precipitation, followed by changes in landscape in all basins. The decrease in flood volume was primarily influenced by changes in active layer thickness in permafrost-dominated basins, while it was mainly controlled by other landscape changes in non-permafrost-dominated basins. Meanwhile, the contributions of changes in potential evapotranspiration and water storage changes to the reduced flood volume were negative in all basins. Furthermore, the impact of vegetation growth on flood volume variation cannot be neglected due to its regulating role in the hydrological cycle. These findings can provide new insights into the evolution mechanism of floods in cryospheric basins and contribute to the development of strategies for flood control, disaster mitigation, and water resource management under a changing climate.

Soil microbes and enzymes mediate soil carbon-climate feedback, and their responses to increasing temperature partly affect soil carbon stability subjected to the effects of climate change. We performed a 50-month incubation experiment to determine the effect of long-term warming on soil microbes and enzymes involved in carbon cycling along permafrost peatland profile (0-150 cm) and investigated their response to water flooding in the active soil layer. Soil bacteria, fungi, and most enzymes were observed to be sensitive to changes in temperature and water in the permafrost peatland. Bacterial and fungal abundance decreased in the active layer soil but increased in the deepest permafrost layer under warming. The highest decrease in the ratio of soil bacteria to fungi was observed in the deepest permafrost layer under warming. These results indicated that long-term warming promotes recalcitrant carbon loss in permafrost because fungi are more efficient in decomposing high-molecular-weight compounds. Soil microbial catabolic activity measured using Biolog Ecoplates indicated a greater degree of average well color development at 15 degrees C than at 5 degrees C. The highest levels of microbial catabolic activity, functional diversity, and carbon substrate utilization were found in the permafrost boundary layer (60-80 cm). Soil polyphenol oxidase that degrades recalcitrant carbon was more sensitive to increases in temperature than 13-glucosidase, N-acetyl-13-glucosaminidase, and acid phosphatase, which degrade labile carbon. Increasing temperature and water flooding exerted a synergistic effect on the bacterial and fungal abundance and 13-glucosidase, acid phosphatase, and RubisCO activity in the topsoil. Structural equation modeling analysis indicated that soil enzyme activity significantly correlated with ratio of soil bacteria to fungi and microbial catabolic activity. Our results provide valuable insights into the linkage response of soil microorganisms, enzymes to climate change and their feedback to permafrost carbon loss.

China's Northwest Arid Region (NAR), with dry and cold climate conditions and glaciers widely developed in the high mountains, provides vital water resources for Asia. The consecutive cold, warm, dry and wet days have much higher impacts on the water cycle process in this region than extreme temperature and precipitation events with short durations but high intensities. Parametric and nonparametric trend analysis methods widely used in climatology and hydrology are employed to identify the temporal and spatial features of the changes in the consecutive cold, warm, dry and wet days in the NAR based on China's 0.5 degrees x 0.5 degrees meteorological grid datasets of daily temperature and precipitation from 1961 to 2018. This study found that (1) the consecutive cold days (Cold Spell Duration Indicator, CSDI), and the consecutive dry days (CDD) decreased, while the consecutive warm days (Warm Spell Duration Indicator, WSDI), and the consecutive wet days (CWD) increased from 1961 to 2018, (2) and the eastern Kunlun Mountains were the hot spots where all of these consecutive climate indices changed significantly, (3) and the changes in these consecutive climate indices were highly correlated with the rise in the Global Mean Land/Ocean Temperature Index. The results indicated that winters tended to warmer and dryer and summer became hotter and wetter during 1961-2018 in the NAR under the global warming, which can lead to the sustained glacier retreat and the increase in summer runoff in this region, and the eastern Kunlun Mountains are the area where could face high risks of water scarcity and floods if the changes in these climate indices continue in the future. Given the vulnerability of the socio-economic systems in the NAR to a water shortage and floods, it is most crucial to improve the strategies of water resources management, disaster prevention and risk management for this region under climate change.

The extreme floods of recent years underline the urgency of studying long-term changes of floods and their driving processes. This paper reports results on this issue obtained within the framework of subproject 6 of the DFG research group SPATE (Space-Time Dynamics of Extreme Floods). The analyses use an extensive dataset of flood observations at rivers and complementary information to determine and explain significant changes in flood probabilities. The data show that the flood-rich periods of the last 500 years in Europe have been significantly colder than usual. Over the last 60 years, the number of flood-rich periods in north-western Europe has increased. This increase is due to more intense precipitation. In medium-sized and large catchments of southern and eastern Europe, on the other hand, lower soil moisture and less snow cover have led to decreasing flood probabilities. These results are intended as a basis for more reliable design flood estimates in a changing world.

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.

This paper addresses the nexus of climate change and variability, soil moisture and surface runoff over the Lake Baikal catchment. Water level and distribution of dissolved and suspended matter over Lake Baikal are strongly affected by river inflow during rain-driven floods. In this study, we evaluate river flow changes at 44 streamflow gauges as well as related precipitation, evaporation, potential evaporation and soil moisture obtained from the ERA5-Land dataset. Based on Sen's slope trend estimator, Mann-Kendall non-parametric test, and using dominance analysis, we estimated the influence of meteorological parameters on river flow during 1979-2019. We found a significant correlation between the precipitation elasticity of river flow and catchment characteristics. Half of the gauges in the eastern part of the Selenga River basin showed a significant decreasing trend of average and maximum river flow (up to -2.9%/year). No changes in the central volume date of flood flow have been found. The reduction in rainfall amount explains more than 60% of runoff decrease. A decrease in evaporation is observed in areas where precipitation decrease is higher than 0.8%/year. Catchments, where the precipitation trends are not as substantial, are associated with increasing evaporation as a result of the increasing potential evaporation. Negative precipitation trends are accompanied by negative trends of soil moisture. Finally, the study reveals the sensitivity of catchments with steep slopes located in humid areas to precipitation change.

Alluvial fans are important paleoclimatic archives, thatmay record high-frequency climatic oscillations. However, climate signals may be overprinted or even be destroyed by autogenic processes caused by channel avulsion and lobe switching. Here we present new data from two different Late Pleistocene (MIS 3-2) alluvial fan systems in northern Germany and compare these systems to experimental alluvial fans and other field examples. The selected fan systems formed under similar climatic and tectonic conditions, but differ in size, type, and drainage area allowing to estimate the role of climate and autogenic controls on flow processes, facies architecture, and fan-stacking patterns. Luminescence dating is used to determine the timing of fan onset and aggradation. Fan onset occurred in response to climate change at the end of MIS 3 when temperatures decreased and periglacial climate conditions were established in northern central Europe. A related increase in sediment supply and strongly variable precipitation patterns probably promoted fan formation. The major period of fan aggradationwas approximately between 33 and 18 ka, followed by fan inactivity, abandonment, and incision during the Lateglacial. The highest aggradation rates occurred during the early stage of fan building, when up to 35 m thick sediment accumulated within a few thousand years. Sand-rich, sheetflood-dominated fans are related to larger, low-gradient fan catchments. Steep depositional fan slopes (5 degrees 17 degrees) and short-lived high-energy floods promoted supercritical flowconditions. Well sorted, sediment-laden, rapidly waning flows favored the deposition and preservation of supercritical bedforms and allowed for the aggradation of stable antidunes. Steep, dip-slope catchments enhanced stream gradients and promoted the transport of coarser sediments. These fans have lower gradient slopes (2-6 degrees) and are dominated by channelized flows, alternating with periods of unconfined sheetfloods. Meter-scale coarsening upward successions, characterized by sandy sheetflood deposits at the base, overlain by multilateral or smaller single-story gravelly channel fills may be related to highfrequency climatic fluctuations or seasonal fluctuations in water and sediment supply. These coarsening-upward successions are commonly bounded by a paleo-active layer, from which ice-wedge casts penetrate downwards. The comparison to experimental fans and other field examples implies that the recurrent pattern ofmultistory, multilateral and single-story channel bodieswith a lateral offset to vertical stacking patternmost probablywas controlled by autogenic switch in an avulsion-dominated system. The change in deposition from alluvial-dominated processes to aeolian sedimentation with minor alluvial influences during the Lateglacial records alternation of dry and ephemeral wetter phases that are related to rapid climatic variations. The main phase of aeolian sand-sheet deposition probably correlates with Heinrich event H1 between approximately 18-16 ka and reflects sedimentation in response to aridification and highmeanwind speeds.

The Karakoram mountain range is prone to natural disasters such as glacial surging and glacial lake outburst flood (GLOF) events. In this study, we aimed to document and reconstruct the sequence of events caused by glacial debris flows that dammed the Immit River in the Hindu Kush Karakoram Range on 17 July 2018. We used satellite remote sensing and field data to conduct the analyses. The order of the events in the disaster chain were determined as follows: glacial meltwater from the G2 glacier (ID: G074052E36491N) transported ice and debris that dammed the meltwater at the snout of the G1 glacier (ID: G074103E36480N), then the debris flow dammed the Immit River and caused Lake Badswat to expand. We surveyed the extent of these events using remote sensing imagery. We analyzed the glaciers' responses to this event chain and found that the glacial debris flow induced G1 to exhibit accelerating ice flow in parts of the region from 25 July 2018 to 4 August 2018. According to the records from reanalysis data and data from the automatic weather station located 75 km from Lake Badswat, the occurrence of this disaster chain was related to high temperatures recorded after 15 July 2018. The chains of events caused by glacially related disasters makes such hazards more complex and dangerous. Therefore, this study is useful not only for understanding the formation of glacial disaster chains, but also for framing mitigation plans to reduce the risks for vulnerable downstream/upstream residents.

Floods are a widespread natural disaster with substantial economic implications and far-reaching consequences. In Northern Pakistan, the Hunza-Nagar valley faces vulnerability to floods, posing significant challenges to its sustainable development. This study aimed to evaluate flood risk in the region by employing a GIS-based Multi-Criteria Decision Analysis (MCDA) approach and big climate data records. By using a comprehensive flood risk assessment model, a flood hazard map was developed by considering nine influential factors: rainfall, regional temperature variation, distance to the river, elevation, slope, Normalized difference vegetation index (NDVI), Topographic wetness index (TWI), land use/land cover (LULC), curvature, and soil type. The analytical hierarchy process (AHP) analysis assigned weights to each factor and integrated with geospatial data using a GIS to generate flood risk maps, classifying hazard levels into five categories. The study assigned higher importance to rainfall, distance to the river, elevation, and slope compared to NDVI, TWI, LULC, curvature, and soil type. The weighted overlay flood risk map obtained from the reclassified maps of nine influencing factors identified 6% of the total area as very high, 36% as high, 41% as moderate, 16% as low, and 1% as very low flood risk. The accuracy of the flood risk model was demonstrated through the Receiver Operating Characteristics-Area Under the Curve (ROC-AUC) analysis, yielding a commendable prediction accuracy of 0.773. This MCDA approach offers an efficient and direct means of flood risk modeling, utilizing fundamental GIS data. The model serves as a valuable tool for decision-makers, enhancing flood risk awareness and providing vital insights for disaster management authorities in the Hunza-Nagar Valley. As future developments unfold, this study remains an indispensable resource for disaster preparedness and management in the Hunza-Nagar Valley region.