One of the consequences of recent glacier recession in the Cordillera Blanca, Peru, is the risk of glacial lake outburst floods (GLOFs) from lakes that have formed at the base of retreating glaciers. GLOFs are often triggered by avalanches falling into glacial lakes, initiating a chain of processes that may culminate in significant inundation and destruction downstream. This paper presents simulations of all of the processes involved in a potential GLOF originating from Lake Palcacocha, the source of a previously catastrophic GLOF on 13 December 1941, killing about 1800 people in the city of Huaraz, Peru. The chain of processes simulated here includes (1) avalanches above the lake; (2) lake dynamics resulting from the avalanche impact, including wave generation, propagation, and run-up across lakes; (3) terminal moraine overtopping and dynamic moraine erosion simulations to determine the possibility of breaching; (4) flood propagation along downstream valleys; and (5) inundation of populated areas. The results of each process feed into simulations of subsequent processes in the chain, finally resulting in estimates of inundation in the city of Huaraz. The results of the inundation simulations were converted into flood intensity and preliminary hazard maps (based on an intensity-likelihood matrix) that may be useful for city planning and regulation. Three avalanche events with volumes ranging from 0.5 to 3 × 10⁶ m³ were simulated, and two scenarios of 15 and 30 m lake lowering were simulated to assess the potential of mitigating the hazard level in Huaraz. For all three avalanche events, three-dimensional hydrodynamic models show large waves generated in the lake from the impact resulting in overtopping of the damming moraine. Despite very high discharge rates (up to 63.4 × 10³ m³ s⁻¹), the erosion from the overtopping wave did not result in failure of the damming moraine when simulated with a hydro-morphodynamic model using excessively conservative soil characteristics that provide very little erosion resistance. With the current lake level, all three avalanche events result in inundation in Huaraz due to wave overtopping, and the resulting preliminary hazard map shows a total affected area of 2.01 km², most of which is in the high hazard category. Lowering the lake has the potential to reduce the affected area by up to 35 %, resulting in a smaller portion of the inundated area in the high hazard category.

The National Weather Service (NWS) forecasts floods at approximately 3,600 locations across the United States (U.S.). However, the river network, as defined by the 1:100,000 scale National Hydrography Dataset‐Plus (NHDPlus) dataset, consists of 2.7 million river segments. Through the National Flood Interoperability Experiment, a continental scale streamflow simulation and forecast system was implemented and continuously operated through the summer of 2015. This system leveraged the WRF‐Hydro framework, initialized on a 3‐km grid, the Routing Application for the Parallel Computation of Discharge river routing model, operating on the NHDPlus, and real‐time atmospheric forcing to continuously forecast streamflow. Although this system produced forecasts, this paper presents a study of the three‐month nowcast to demonstrate the capacity to seamlessly predict reach scale streamflow at the continental scale. In addition, this paper evaluates the impact of reservoirs, through a case study in Texas. Validation of the uncalibrated model using observed hourly streamflow at 5,701 U.S. Geological Survey gages shows 26% demonstrate PBias ≤ |25%|, 11% demonstrate Nash‐Sutcliffe Efficiency (NSE) ≥ 0.25, and 6% demonstrate both PBias ≤ |25%| and NSE ≥ 0.25. When evaluating the impact of reservoirs, the analysis shows when reservoirs are included, NSE ≥ 0.25 for 56% of the gages downstream while NSE ≥ 0.25 for 11% when they are not. The results presented here provide a benchmark for the evolving hydrology program within the NWS and supports their efforts to develop a reach scale flood forecasting system for the country.

Glacial-dominated areas pose unique challenges to downstream communities in adapting to recent and continuing global climate change, including increased threats of glacial lake outburst floods (GLOFs) that can increase risk due to flooding of downstream communities and cause substantial impacts on regional social, environmental and economic systems. The Imja glacial lake (or Imja Tsho) in Nepal, which has the potential to generate a GLOF, was studied using a two-dimensional debris-flow inundation model in order to evaluate the effectiveness of proposed measures to reduce possible flooding impacts to downstream communities by lowering the lake level. The results indicate that only minor flood impact reduction is achieved in the downstream community of Dingboche with modest (~3 m) lake lowering. Lowering the lake by 10 m shows a significant reduction in inundated area. However, lowering the lake by 20 m almost eliminates all flood impact at Dingboche. Further downstream at Phakding, the impact of the GLOF is significant and similar reductions in inundation are likely as a result of lake lowering.

Imja Tsho, located in the Sagarmatha (Everest) National Park of Nepal, is one of the most studied and rapidly growing lakes in the Himalayan range. Compared with previous studies, the results of our sonar bathymetric survey conducted in September of 2012 suggest that its maximum depth has increased from 90.5 to 116.3 ± 5.2 m since 2002, and that its estimated volume has grown from 35.8 ± 0.7 to 61.7 ± 3.7 million m3. Most of the expansion of the lake in recent years has taken place in the glacier terminus–lake interface on the eastern end of the lake, with the glacier receding at about 52 m yr−1 and the lake expanding in area by 0.04 km2 yr−1. A ground penetrating radar survey of the Imja–Lhotse Shar glacier just behind the glacier terminus shows that the ice is over 200 m thick in the center of the glacier. The volume of water that could be released from the lake in the event of a breach in the damming moraine on the western end of the lake has increased to 34.1 ± 1.08 million m3 from the 21 million m3 estimated in 2002.

This study assesses a large‐scale hydrologic modeling framework (WRF‐Hydro‐RAPID) in terms of its high‐resolution simulation of evapotranspiration (ET) and streamflow over Texas (drainage area: 464,135 km²). The reference observations used include eight‐day ET data from MODIS and FLUXNET, and daily river discharge data from 271 U.S. Geological Survey gauges located across a climate gradient. A recursive digital filter is applied to decompose the river discharge into surface runoff and base flow for comparison with the model counterparts. While the routing component of the model is pre‐calibrated, the land component is uncalibrated. Results show the model performance for ET and runoff is aridity‐dependent. ET is better predicted in a wet year than in a dry year. Streamflow is better predicted in wet regions with the highest efficiency ~0.7. In comparison, streamflow is most poorly predicted in dry regions with a large positive bias. Modeled ET bias is more strongly correlated with the base flow bias than surface runoff bias. These results complement previous evaluations by incorporating more spatial details. They also help identify potential processes for future model improvements. Indeed, improving the dry region streamflow simulation would require synergistic enhancements of ET, soil moisture and groundwater parameterizations in the current model configuration. Our assessments are important preliminary steps towards accurate large‐scale hydrologic forecasts.

The evaluation of potential landslides in mountain areas is a very complex process. Currently, event understanding is scarce due to information limitations. Identifying the whole chain of events is not a straightforward task, and the impacts of mass-wasting processes depend on the conditions downstream of the origin. In this paper, we present an example that illustrates the complexities in the evaluation of the chain of events that may lead to a natural disaster. On 16 December 2017, a landslide occurred in the Yelcho mountain range (southern Chile). In that event, 7 million m³ of rocks and soil fell on the Yelcho glacier, depositing 2 million m³ on the glacier terminal, and the rest continued downstream, triggering a mudflow that hit Villa Santa Lucía in Chilean Patagonia and killing 22 people. The complex event was anticipated in the region by the National Geological and Mining Survey (Sernageomin in Spanish). However, the effects of the terrain characteristics along the run-out area were more significant than anticipated. In this work, we evaluate the conditions that enabled the mudflow that hit Villa Santa Lucía. We used the information generated by Sernageomin's professionals after the mudflow. We carried out geotechnical tests to characterize the soil. We simulated the mudflow using two hydrodynamic programs (r.avaflow and Flo-2D) that can handle the rheology of the water–soil mixture. Our results indicate that the soil is classified as volcanic pumices. This type of soil can be susceptible to the collapse of the structure when subjected to shearing (molding), flowing as a viscous liquid. From the numerical modeling, we concluded that r.avaflow performs better than Flo-2D. The mudflow was satisfactorily simulated using a water content in the mixture ranging from 30 % to 40 %, which would have required a source of about 3 million m³ of water. Coupling the simulations and the soil tests that we performed, we estimated that in the area scoured by the mudflow, there were probably around 2 800 000 m³ of water within the soil. Therefore, the conditions of the valley were crucial to enhancing the impacts of the landslide. This result is relevant because it highlights the importance of evaluating the complete chain of events to map hazards. We suggest that in future hazard mapping, geotechnical studies in combination with hydrodynamic simulation should be included, in particular when human lives are at risk.