Initial soil moisture effects on flash flood generation – A comparison between basins of contrasting hydro-climatic conditions

2016 ◽  
Vol 541 ◽  
pp. 206-217 ◽  
Author(s):  
M.G. Grillakis ◽  
A.G. Koutroulis ◽  
J. Komma ◽  
I.K. Tsanis ◽  
W. Wagner ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Flash Flood ◽  
Climatic Conditions ◽  
Initial Soil Moisture ◽  
Moisture Effects ◽  
Initial Soil ◽  
Flood Generation

Which event produces the largest flash flood? Considering rainfall characteristics, initial soil moisture, retention and run-on infiltration

2020 ◽  
Author(s):  
Markus Weiler ◽  
Hannes Leistert ◽  
Andreas Steinbrich
Keyword(s):  
Soil Moisture ◽  
Return Period ◽  
Overland Flow ◽  
Flash Flood ◽  
Joint Probability ◽  
Flash Floods ◽  
Runoff Generation ◽  
Runoff Formation ◽  
Initial Soil Moisture ◽  
Initial Soil

<p>Local heavy precipitation regularly causes great damage resulting from flash floods in small catchments. Appropriate discharge records are usually unavailable to derive an extreme value statistics and regionalization approaches predicting peak discharge from discharge records of larger basins cannot consider the small-scale effects and local processes. In addition, forecasting flash floods from rainfall forecast requires to identify the event conditions under which a catchment is most prone to trigger flash floods. Therefore, factors influencing runoff formation and concentration need to be identified based on catchment characteristics in order to predict flood hydrographs, geomorphic processes and flood inundation.</p><p>We have developed a framework depending on the joint probability of soil moisture and rainfall and used the distributed, processed-based rainfall-runoff model RoGeR to predict the spatial explicit probability of soil moisture and linking this to overland-flow and subsurface flow generation assuming different scenarios of soil moisture and rainfall characteristics. Selected combinations result in a joint probability with a specified return period (e.g. 100 year), but are based on different probabilities for rainfall amount, duration and initial soil moisture. From this, the combination of a precipitation event and initial soil moisture condition can be determined which generates the largest runoff generation. In addition, we found, that accounting for the spatially and temporally controlled superimposition of runoff formation and runoff concentration, including the possible infiltration of overland flow (run-on infiltration) along the flow path and the retention in depression can have considerable influence on modelled peak discharge and discharge volume for a given catchment. For this purpose, various methods were developed and tested considering the effects of run-on infiltration and retention, from complex 2D hydraulic models coupled with RoGeR to simpler approaches considering run-on infiltration only locally or based on the difference between actual and potential infiltration. These approaches were tested in different catchments with different soils, geologies and land use. Also, the sensitiviy of surface roughness was considered.</p><p>We developed an interactive spatial explicit method, which combines the joint probability of soil moisture and rainfall for runoff formation with hydraulic assumptions to determine runoff concentration and thus the corresponding design hydrographs and the specific conditions a catchment can trigger flash floods. This information can on the one side help to generate flash flood risk maps, but should also be considered in order to provide adequate catchment specific information for heavy precipitation risk management. We could clearly demonstrate that only the combined consideration of factors affecting flood formation and concentration and its implementation into a statistical framework allows to predict floods for a specific return period (which is not equal to the return period of precipitation) for small catchments where different runoff generation mechanisms occur simultaneously.</p>

Initial soil moisture retrievals from the METOP-A Advanced Scatterometer (ASCAT)

2007 ◽  
Vol 34 (20) ◽  
Author(s):  
Zoltan Bartalis ◽  
Wolfgang Wagner ◽  
Vahid Naeimi ◽  
Stefan Hasenauer ◽  
Klaus Scipal ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Initial Soil Moisture ◽  
Initial Soil

Exploring the potential of soil moisture reanalysis data for improving the identification of regional landslide triggering thresholds

2021 ◽  
Author(s):  
Nunziarita Palazzolo ◽  
David J. Peres ◽  
Enrico Creaco ◽  
Antonino Cancelliere
Keyword(s):  
Soil Moisture ◽  
Rainfall Event ◽  
Rainfall Thresholds ◽  
Rainfall Duration ◽  
Soil Moisture Data ◽  
Initial Soil Moisture ◽  
Initial Soil ◽  
Different Depths ◽  
Moisture Conditions ◽  
Landslide Triggering

<p>Landslide triggering thresholds provide the rainfall conditions that are likely to trigger landslides, therefore their derivation is key for prediction purposes. Different variables can be considered for the identification of thresholds, which commonly are in the form of a power-law relationship linking rainfall event duration and intensity or cumulated event rainfall. The assessment of such rainfall thresholds generally neglects initial soil moisture conditions at each rainfall event, which are indeed a predisposing factor that can be crucial for the proper definition of the triggering scenario. Thus, more studies are needed to understand whether and the extent to which the integration of the initial soil moisture conditions with rainfall thresholds could improve the conventional precipitation-based approach. Although soil moisture data availability has hindered such type of studies, yet now this information is increasingly becoming available at the large scale, for instance as an output of meteorological reanalysis initiatives. In particular, in this study, we focus on the use of the ERA5-Land reanalysis soil moisture dataset. Climate reanalysis combines past observations with models in order to generate consistent time series and the ERA5-Land data actually provides the volume of water in soil layer at different depths and at global scale. Era5-Land project is, indeed, a global dataset at 9 km horizontal resolution in which atmospheric data are at an hourly scale from 1981 to present. Volumetric soil water data are available at four depths ranging from the surface level to 289 cm, namely 0-7 cm, 7-28 cm, 28-100 cm, and 100-289 cm. After collecting the rainfall and soil moisture data at the desired spatio-temporal resolution, together with the target data discriminating landslide and no-landslide events, we develop automatic triggering/non-triggering classifiers and test their performances via confusion matrix statistics. In particular, we compare the performances associated with the following set of precursors: a) event rainfall duration and depth (traditional approach), b) initial soil moisture at several soil depths, and c) event rainfall duration and depth and initial soil moisture at different depths. The approach is applied to the Oltrepò Pavese region (northern Italy), for which the historical observed landslides have been provided by the IFFI project (Italian landslides inventory). Results show that soil moisture may allow an improvement in the performances of the classifier, but that the quality of the landslide inventory is crucial.</p>

Soil Type, Soil Moisture, and Field Slope Influence the Horizontal Movement of Salmonella enterica and Citrobacter freundii from Floodwater through Soil

2016 ◽  
Vol 80 (1) ◽  
pp. 189-197 ◽  
Author(s):  
MARY THERESA CALLAHAN ◽  
SHIRLEY A. MICALLEF ◽  
ROBERT L. BUCHANAN
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Type ◽  
Soil Moisture Content ◽  
Clay Content ◽  
Horizontal Movement ◽  
Initial Soil Moisture ◽  
Salmonella Newport ◽  
Initial Soil ◽  
Rate Of Decline

ABSTRACT Pathogens in soil are readily mobilized by infiltrating water to travel downward through the soil. However, limited data are available on the horizontal movement of pathogens across a field. This study used a model system to evaluate the influence of soil type, initial soil moisture content, and field slope on the movement of Salmonella enterica serovar Newport across a horizontal plane of soil under flooding conditions. Three soil types of varying clay content were moistened to 40, 60, or 80% of their maximum water-holding capacities and flooded with water containing 6 log CFU/ml Salmonella Newport and Citrobacter freundii, the latter being evaluated as a potential surrogate for S. enterica in future field trials. A two-phase linear regression was used to analyze the microbial populations recovered from soil with increasing distance from the flood. This model reflected the presence of lag distances followed by a quantifiable linear decrease in the population of bacteria as a function of the distance from the site of flooding. The magnitude of the lag distance was significantly affected by the soil type, but this was not attributable to the soil clay content. The rate of the linear decline with distance from the flood zone was affected by soil type, initial soil moisture content, and soil incline. As the initial soil moisture content increased, the rate of decline in recovery decreased, indicating greater bacterial transport through soils. When flooding was simulated at the bottom of the soil incline, the rate of decline in recovery was much greater than when flooding was simulated at the top of the incline. There was no significant difference in recovery between Salmonella Newport and C. freundii, indicating that C. freundii may be a suitable surrogate for Salmonella Newport in future field studies.

scholarly journals Research on Occurrence and Development of Pasture Drought Events in Alpine Grassland using the Drought Threshold

2018 ◽  
Author(s):  
Tiaofeng Zhang ◽  
Lin Li ◽  
Hongbin Xiao ◽  
Hongmei Li
Keyword(s):  
Soil Moisture ◽  
Alpine Grassland ◽  
Soil Drought ◽  
Severe Drought ◽  
Drought Event ◽  
Drought Intensity ◽  
Quantitative Expression ◽  
Initial Soil Moisture ◽  
Initial Soil ◽  
The Relationship

Abstract. Pasture is vital to livestock husbandry development in Qinghai and even in North China. Drought is the primary meteorological disaster that affects pasture, but insufficient soil moisture is the most prominent cause of pasture drought. Timely and accurate determination of the soil moisture threshold of pasture is important for objective recognition and monitoring of the occurrence and development of pasture drought. This study aims at investigating pasture responses to soil drought as well as quantitative expression of soil drought degree and drought threshold. Test plots were selected from the pasture test station. Five testing groups were set according to coverage rate (0–100 %) at the initiation the pasture growth period. The impacts of profile moisture characteristics, drought threshold, and precipitation on duration of pasture drought were studied. Research results have demonstrated that moisture in the soil profile below 20 cm decreases slightly throughout drought events in alpine grassland. Changes of soil moisture in the 0–20 cm layer can generally reflect drought stress of the pasture. In the process of a drought event, the relationship between soil water storage and cumulative relative water loss can be expressed via a logarithmic linear equation. Quantitative expression of drought degree in grasslands can be realized by transforming the slope of this equation into the index D with an interval of [0, 1]. The occurrence rates of mild drought,moderate drought, and severe drought were 0.36, 0.45, and 0.70, respectively. The duration of severe drought was closely related with initial soil moisture. The relationship between duration of drought and the necessary minimum precipitation can be expressed by an exponential equation. Values of the D index can express soil drought intensity and pasture drought intensity. The durations for different grades of drought events were correlated with both initial soil moisture and previous precipitation. The conclusions of this study can provide scientific references for the objective understanding onoccurrence, development, monitoring, and early warning of pasture drought.

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