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Dalia Kirschbaum

Publications and source records attributed to Dalia Kirschbaum.

45 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

The NASA Aerosols, Clouds, Convection, and Precipitation (ACCP) Observing System

NASA’s new Earth System Observatory (ESO) will provide key information related to understanding climate change processes, mitigating natural hazards, fighting forest fires, and improving real-time agricultural processes. The ACCP observing system will address two of the five major focus areas: aerosols, which determine air quality and affect the global energy balance, a key source of uncertainty in predicting climate change; and clouds, convection, and precipitation, whose processes are also a large source of uncertainty in future projections of climate change as well as predictions of severe weather. ACCP, currently in the concept investigation phase, is made up of two projects, one in an inclined orbit and the other in a polar orbit, with both projects addressing synergistic A and CCP science. Suborbital science is also a significant element of ACCP. This talk will describe the science objectives of ACCP and their relationship to the 2017 NASA Earth Science Decadal Survey as well as summarize the orbital architecture and major science activities during the concept investigation phase.

Scott Braun↗
NASA NTRSDate not supplied

Landslide Susceptibility and Runout Assessment for the Arun Hydropower Cascade in Nepal Based on Multitemporal Landslide Inventory Developed Using Planet Imagery

The transboundary Pumqu/Arun River basin spreads across Nepal and Tibet. Nearly 95% of the basin lies in Tibet through which the Pumqu River flows forming the Arun River once it enters Nepal. The Arun River valley has about 3,163 MW in five large hydropower projects undergoing construction or planned for the future. Rainfall and earthquake-induced landslides, landslide dammed lakes and landslide-induced glacial lake outburst floods pose major risks to smooth operation of these projects. To safeguard upcoming hydropower projects, areas susceptible to landslides in the Arun River valley must be identified. We generated a multitemporal landslide inventory (2010-2020), modeled landslide susceptibility and runouts around the hydropower sites using Earth Observation (EO) techniques. We used high-resolution satellite imagery from Planet and open-source tool to establish a detailed and comprehensive multitemporal landslide inventory for the basin. The rigorous quality-controlled inventory represents yearly record of landslides from 2010 to 2020. To our knowledge this is one of the most comprehensive landslide inventories for the basin with yearly records of landslides.A data-driven approach was used to map areas susceptible to landslides within the Pumqu/Arun River basin. The multitemporal landslide inventory combined with other readily available EO-based variables were used to create a landslide susceptibility map. The highly susceptible areas delineated from the map was further used to characterize runouts near the hydropower sites. The susceptibility and runout analysis provide a valuable initial estimate of where landslides are likely to trigger and where the mobilized material is likely to end up.

Pukar Amatya↗
NASA NTRSDate not supplied

Landslide Runout Analysis Using Remote Sensing for Lower and Upper Barun Lakes

Landslides are recognized as common triggers of glacial lake outburst floods in high mountain regions, but the remoteness of dangerous glacial lakes makes monitoring and disaster management very difficult. Using a very high resolution digital elevation model produced from a series of stereo satellite images, we simulate debris flows and rock avalanche runout around two very dangerous lakes in high mountain Nepal. We constrain particularly likely sources of these slope failures to simulate 79,800 potential debris flows and rock avalanches of volumes ranging from 1,000 m3 to 1,000,000 m3. This allowed us to identify zones in and around dangerous glacial lakes that are most exposed to landslide runout hazards, along with the most frequent source areas that produced landslides that may run into either of the two glacial lakes. Although our empirical-statistical model presented limitations that numerical models attempt to overcome, our probabilistic approach combined with a very high resolution DEM may shed new light on how to identify sources and impact areas of debris flows and rock avalanches that may cascade into downstream disasters.

landslides↗
NASA NTRSDate not supplied

Satellite Based Precipitation Estimation in Orographic Regions within the Southwestern United States

Predicting precipitation-induced landslides requires accurate estimation of orographic precipitation. Many research studies have been done to estimate orographic precipitation using measurement/estimation methods that include rain gauges, ground-based radar, satellite-based estimates, and modeling. Each method has strengths and weaknesses, but none have been able to fully resolve orographic precipitation. The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Mission (IMERG) early run product provides precipitation estimates at a 0.1° spatial resolution, at half-hour time scales, with only a 4-hour latency. This product is currently used for the global landslide hazard assessment, but there are known issues in mountainous terrain that the IMERG algorithm has not been able to fully resolve; and the sparse gauge density in these regions makes it even more difficult. In this study, precipitation events were identified using high temporal resolution (5-15 minute) precipitation observations from rain gauges in mountainous terrain in the southwestern United States. The brightness temperature from several infrared (IR) bands from the Geostationary Operational Environmental Satellite (GOES) 16 satellite were used to estimate precipitation with a k-nearest neighbor machine learning model. Compared to IMERG, the IR estimates from GOES-16 performed better at predicting gauge-identified precipitation events. Additionally, the IR-only based estimates were able to estimate precipitation when IMERG failed to detect precipitation, false negative events. While additional analysis is needed, results indicate the need for better integration of IR observations for more accurate precipitation estimation in mountainous regions.

Jessica Sutton↗