scholarly journals In situ measurements of post-fire debris flows in southern California: Comparisons of the timing and magnitude of 24 debris-flow events with rainfall and soil moisture conditions

2011 ◽  
Vol 116 (F4) ◽  
Author(s):  
Jason W. Kean ◽  
Dennis M. Staley ◽  
Susan H. Cannon
Keyword(s):  
Soil Moisture ◽  
Debris Flow ◽  
Debris Flows ◽  
Southern California ◽  
In Situ Measurements ◽  
Fire Debris ◽  
Moisture Conditions

scholarly journals Challenges in flood modelling over data scarce regions: how to exploit globally available soil moisture products to estimate antecedent soil wetness conditions in Morocco

2020 ◽  
Author(s):  
El Mahdi El Khalki ◽  
Yves Tramblay ◽  
Christian Massari ◽  
Luca Brocca ◽  
Mohamed El Mehdi Saidi
Keyword(s):  
Soil Moisture ◽  
In Situ Measurements ◽  
Time Step ◽  
Flood Modelling ◽  
Daily Time Step ◽  
Moisture Conditions ◽  
Scs Cn ◽  
Semi Arid ◽  
Daily Time

Abstract. The Mediterranean region is characterized by intense rainfall events giving rise to devastating floods. In Maghreb countries such as Morocco, there is a strong need for forecasting systems to reduce the impacts of floods. The development of such a system in the case of ungauged catchments is complicated but remote sensing products could overcome the lack of in-situ measurements. The soil moisture content can strongly modulate the magnitude of flood events and consequently is a crucial parameter to take into account for flood modeling. In this study, different soil moisture products (ESA-CCI, SMOS, SMOS-IC, ASCAT satellite products and ERA5 reanalysis) are compared to in-situ measurements and one continuous soil moisture accounting (SMA) model for basins located in the High-Atlas Mountains, upstream of the city of Marrakech. The results show that the SMOS-IC satellite product and the ERA5 reanalysis are best correlated with observed soil moisture and with the SMA model outputs. The different soil moisture datasets were also compared to estimate the initial soil moisture condition for an event-based hydrological model based on the Soil Conservation Service Curve Number (SCS-CN). The ASCAT, SMOS-IC and ERA5 products performed equally well in validation to simulate floods, outperforming daily in situ soil moisture measurements that may not be representative of the whole catchment soil moisture conditions. The results also indicated that the daily time step may not fully represent the saturation state before a flood event, due to the rapid decay of soil moisture after rainfall in these semi-arid environments. Indeed, at the hourly time step, ERA5 and in-situ measurements were found to better represent the initial soil moisture conditions of the SCS-CN model by comparison with the daily time step. The results of this work could be used to implement efficient flood modelling and forecasting systems in semi-arid regions where soil moisture measurements are lacking.

scholarly journals Challenges in flood modeling over data-scarce regions: how to exploit globally available soil moisture products to estimate antecedent soil wetness conditions in Morocco

2020 ◽  
Vol 20 (10) ◽  
pp. 2591-2607
Author(s):  
El Mahdi El Khalki ◽  
Yves Tramblay ◽  
Christian Massari ◽  
Luca Brocca ◽  
Vincent Simonneaux ◽  
...  
Keyword(s):  
Soil Moisture ◽  
In Situ Measurements ◽  
Flood Modeling ◽  
Time Step ◽  
Ocean Salinity ◽  
Daily Time Step ◽  
Moisture Conditions ◽  
Scs Cn ◽  
Daily Time

Abstract. The Mediterranean region is characterized by intense rainfall events giving rise to devastating floods. In Maghreb countries such as Morocco, there is a strong need for forecasting systems to reduce the impacts of floods. The development of such a system in the case of ungauged catchments is complicated, but remote-sensing products could overcome the lack of in situ measurements. The soil moisture content can strongly modulate the magnitude of flood events and consequently is a crucial parameter to take into account for flood modeling. In this study, different soil moisture products (European Space Agency Climate Change Initiative, ESA-CCI; Soil Moisture and Ocean Salinity, SMOS; Soil Moisture and Ocean Salinity by the Institut National de la Recherche Agronomique and Centre d'Etudes Spatiales de la Biosphère, SMOS-IC; Advanced Scatterometer, ASCAT; and ERA5 reanalysis) are compared to in situ measurements and one continuous soil-moisture-accounting (SMA) model for basins located in the High Atlas Mountains, upstream of the city of Marrakech. The results show that the SMOS-IC satellite product and the ERA5 reanalysis are best correlated with observed soil moisture and with the SMA model outputs. The different soil moisture datasets were also compared to estimate the initial soil moisture condition for an event-based hydrological model based on the Soil Conservation Service curve number (SCS-CN). The ASCAT, SMOS-IC, and ERA5 products performed equally well in validation to simulate floods, outperforming daily in situ soil moisture measurements that may not be representative of the whole catchment soil moisture conditions. The results also indicated that the daily time step may not fully represent the saturation state before a flood event due to the rapid decay of soil moisture after rainfall in these semiarid environments. Indeed, at the hourly time step, ERA5 and in situ measurements were found to better represent the initial soil moisture conditions of the SCS-CN model by comparison with the daily time step. The results of this work could be used to implement efficient flood modeling and forecasting systems in semiarid regions where soil moisture measurements are lacking.

scholarly journals Mapping High Spatiotemporal-Resolution Soil Moisture by Upscaling Sparse Ground-Based Observations Using a Bayesian Linear Regression Method for Comparison with Microwave Remotely Sensed Soil Moisture Products

2021 ◽  
Vol 13 (2) ◽  
pp. 228
Author(s):  
Jian Kang ◽  
Rui Jin ◽  
Xin Li ◽  
Yang Zhang
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
Spatial Scales ◽  
Microwave Remote Sensing ◽  
In Situ Measurements ◽  
Spatial Density ◽  
Linear Regression Method ◽  
Spatiotemporal Resolution ◽  
Pixel Scale

In recent decades, microwave remote sensing (RS) has been used to measure soil moisture (SM). Long-term and large-scale RS SM datasets derived from various microwave sensors have been used in environmental fields. Understanding the accuracies of RS SM products is essential for their proper applications. However, due to the mismatched spatial scale between the ground-based and RS observations, the truth at the pixel scale may not be accurately represented by ground-based observations, especially when the spatial density of in situ measurements is low. Because ground-based observations are often sparsely distributed, temporal upscaling was adopted to transform a few in situ measurements into SM values at a pixel scale of 1 km by introducing the temperature vegetation dryness index (TVDI) related to SM. The upscaled SM showed high consistency with in situ SM observations and could accurately capture rainfall events. The upscaled SM was considered as the reference data to evaluate RS SM products at different spatial scales. In regard to the validation results, in addition to the correlation coefficient (R) of the Soil Moisture Active Passive (SMAP) SM being slightly lower than that of the Climate Change Initiative (CCI) SM, SMAP had the best performance in terms of the root-mean-square error (RMSE), unbiased RMSE and bias, followed by the CCI. The Soil Moisture and Ocean Salinity (SMOS) products were in worse agreement with the upscaled SM and were inferior to the R value of the X-band SM of the Advanced Microwave Scanning Radiometer 2 (AMSR2). In conclusion, in the study area, the SMAP and CCI SM are more reliable, although both products were underestimated by 0.060 cm3 cm−3 and 0.077 cm3 cm−3, respectively. If the biases are corrected, then the improved SMAP with an RMSE of 0.043 cm3 cm−3 and the CCI with an RMSE of 0.039 cm3 cm−3 will hopefully reach the application requirement for an accuracy with an RMSE less than 0.040 cm3 cm−3.

Observations and Analyses of the 9 January 2018 Debris-Flow Disaster, Santa Barbara County, California

2021 ◽  
Vol 27 (1) ◽  
pp. 3-27
Author(s):  
Jeremy T. Lancaster ◽  
Brian J. Swanson ◽  
Stefani G. Lukashov ◽  
Nina S. Oakley ◽  
Jacob B. Lee ◽  
...  
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Extreme Rainfall ◽  
Atmospheric Conditions ◽  
Santa Barbara ◽  
Debris Removal ◽  
Fire Debris ◽  
Santa Barbara County ◽  
Coastal Land

ABSTRACT The post–Thomas Fire debris flows of 9 January 2018 killed 23 people, damaged 558 structures, and caused severe damage to infrastructure in Montecito and Carpinteria, CA. U.S. Highway 101 was closed for 13 days, significantly impacting transportation and commerce in the region. A narrow cold frontal rain band generated extreme rainfall rates within the western burn area, triggering runoff-driven debris flows that inundated 5.6 km2 of coastal land in eastern Santa Barbara County. Collectively, this series of debris flows is comparable in magnitude to the largest documented post-fire debris flows in the state and cost over a billion dollars in debris removal and damages to homes and infrastructure. This study summarizes observations and analyses on the extent and magnitude of inundation areas, debris-flow velocity and volume, and sources of debris-flow material on the south flank of the Santa Ynez Mountains. Additionally, we describe the atmospheric conditions that generated intense rainfall and use precipitation data to compare debris-flow source areas with spatially associated peak 15 minute rainfall amounts. We then couple the physical characterization of the event with a compilation of debris-flow damages to summarize economic impacts.

scholarly journals The temporally varying roles of rainfall, snowmelt and soil moisture for debris flow initiation in a snow-dominated system

2018 ◽  
Vol 22 (6) ◽  
pp. 3493-3513 ◽  
Author(s):  
Karin Mostbauer ◽  
Roland Kaitna ◽  
David Prenner ◽  
Markus Hrachowitz
Keyword(s):  
Soil Moisture ◽  
Debris Flow ◽  
High Intensity ◽  
Debris Flows ◽  
Regional Scale ◽  
Early Summer ◽  
Temporal Separation ◽  
Antecedent Soil Moisture ◽  
Trigger Mechanisms ◽  
Debris Flow Initiation

Abstract. Debris flows represent frequent hazards in mountain regions. Though significant effort has been made to predict such events, the trigger conditions as well as the hydrologic disposition of a watershed at the time of debris flow occurrence are not well understood. Traditional intensity-duration threshold techniques to establish trigger conditions generally do not account for distinct influences of rainfall, snowmelt, and antecedent moisture. To improve our knowledge on the connection between debris flow initiation and the hydrologic system at a regional scale, this study explores the use of a semi-distributed conceptual rainfall–runoff model, linking different system variables such as soil moisture, snowmelt, or runoff with documented debris flow events in the inner Pitztal watershed, Austria. The model was run on a daily basis between 1953 and 2012. Analysing a range of modelled system state and flux variables at days on which debris flows occurred, three distinct dominant trigger mechanisms could be clearly identified. While the results suggest that for 68 % (17 out of 25) of the observed debris flow events during the study period high-intensity rainfall was the dominant trigger, snowmelt was identified as the dominant trigger for 24 % (6 out of 25) of the observed debris flow events. In addition, 8 % (2 out of 25) of the debris flow events could be attributed to the combined effects of low-intensity, long-lasting rainfall and transient storage of this water, causing elevated antecedent soil moisture conditions. The results also suggest a relatively clear temporal separation between the distinct trigger mechanisms, with high-intensity rainfall as a trigger being limited to mid- and late summer. The dominant trigger in late spring/early summer is snowmelt. Based on the discrimination between different modelled system states and fluxes and, more specifically, their temporally varying importance relative to each other, this exploratory study demonstrates that already the use of a relatively simple hydrological model can prove useful to gain some more insight into the importance of distinct debris flow trigger mechanisms. This highlights in particular the relevance of snowmelt contributions and the switch between mechanisms during early to mid-summer in snow-dominated systems.

Towards an operationally capable satellite-based 0-100 cm soil moisture dataset from C3S

2021 ◽  
Author(s):  
Adam Pasik ◽  
Wolfgang Preimesberger ◽  
Bernhard Bauer-Marschallinger ◽  
Wouter Dorigo
Keyword(s):  
Soil Moisture ◽  
Soil Profile ◽  
Land Surface ◽  
Root Zone ◽  
Soil Layer ◽  
Land Surface Model ◽  
In Situ Measurements ◽  
Surface Model ◽  
T Values

<p>Multiple satellite-based global surface soil moisture (SSM) datasets are presently available, these however, address exclusively the top layer of the soil (0-5cm). Meanwhile, root-zone soil moisture cannot be directly quantified with remote sensing but can be estimated from SSM using a land surface model. Alternatively, soil water index (SWI; calculated from SSM as a function of time needed for infiltration) can be used as a simple approximation of root-zone conditions. SWI is a proxy for deeper layers of the soil profile which control evapotranspiration, and is hence especially important for studying hydrological processes over vegetation-covered areas and meteorological modelling.</p><p>Here we introduce the advances in our work on the first operationally capable SWI-based root-zone soil moisture dataset from C3S Soil Moisture v201912 COMBINED product, spanning the period 2002-2020. The uniqueness of this dataset lies in the fact that T-values (temporal lengths ruling the infiltration) characteristic of SWI were translated into particular soil depths making it much more intuitive, user-friendly and easily applicable. Available are volumetric soil moisture values for the top 1 m of the soil profile at 10 cm intervals, where the optimal T-value (T-best) for each soil layer is selected based on a range of correlation metrics with in situ measurements from the International Soil Moisture Network (ISMN) and the relevant soil and climatic parameters.<br>Additionally we present the results of an extensive global validation against in situ measurements (ISMN) as well as the results of investigations into the relationship between a range of soil and climate characteristics and the optimal T-values for particular soil depths.</p>

scholarly journals Inundation, flow dynamics, and damage in the 9 January 2018 Montecito debris-flow event, California, USA: Opportunities and challenges for post-wildfire risk assessment

Geosphere ◽  
2019 ◽  
Vol 15 (4) ◽  
pp. 1140-1163 ◽  
Author(s):  
J.W. Kean ◽  
D.M. Staley ◽  
J.T. Lancaster ◽  
F.K. Rengers ◽  
B.J. Swanson ◽  
...  
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Field Measurements ◽  
Economic Loss ◽  
Flow Dynamics ◽  
Dynamic Constraints ◽  
Fire Debris ◽  
Velocity Information ◽  
Intense Burst ◽  
Comprehensive Framework

Abstract Shortly before the beginning of the 2017–2018 winter rainy season, one of the largest fires in California (USA) history (Thomas fire) substantially increased the susceptibility of steep slopes in Santa Barbara and Ventura Counties to debris flows. On 9 January 2018, before the fire was fully contained, an intense burst of rain fell on the portion of the burn area above Montecito, California. The rainfall and associated runoff triggered a series of debris flows that mobilized ∼680,000 m3 of sediment (including boulders >6 m in diameter) at velocities up to 4 m/s down coalescing urbanized alluvial fans. The resulting destruction (including 23 fatalities, at least 167 injuries, and 408 damaged homes) underscores the need for improved understanding of debris-flow runout in the built environment, and the need for a comprehensive framework to assess the potential loss from debris flows following wildfire. We present observations of the inundation, debris-flow dynamics, and damage from the event. The data include field measurements of flow depth and deposit characteristics made within the first 12 days after the event (before ephemeral features of the deposits were lost to recovery operations); an inventory of building damage; estimates of flow velocity; information on flow timing; soil-hydrologic properties; and post-event imagery and lidar. Together, these data provide rare spatial and dynamic constraints for testing debris-flow runout models, which are needed for advancing post-fire debris-flow hazard assessments. Our analysis also outlines a framework for translating the results of these models into estimates of economic loss based on an adaptation of the U.S. Federal Emergency Management Agency’s Hazus model for tsunamis.

Objective definition of rainfall intensity–duration thresholds for the initiation of post-fire debris flows in southern California

Landslides ◽  
2012 ◽  
Vol 10 (5) ◽  
pp. 547-562 ◽  
Author(s):  
Dennis M. Staley ◽  
Jason W. Kean ◽  
Susan H. Cannon ◽  
Kevin M. Schmidt ◽  
Jayme L. Laber
Keyword(s):  
Debris Flows ◽  
Southern California ◽  
Rainfall Intensity ◽  
Fire Debris ◽  
Definition Of
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