Copula-based interpretation of continuous rainfall–runoff simulations of a watershed in northern Iran

2012 ◽  
Vol 49 (5) ◽  
pp. 681-691 ◽  
Author(s):  
Saeed Golian ◽  
Bahram Saghafian ◽  
Ashkan Farokhnia
Keyword(s):  
Soil Moisture ◽  
Peak Discharge ◽  
Rainfall Runoff ◽  
Antecedent Soil Moisture ◽  
Rainfall Duration ◽  
Initial Soil Moisture ◽  
Hourly Rainfall ◽  
Copula Method ◽  
Initial Soil ◽  
Rainfall Depth

In the present work, the joint response of key hydrologic variables, including total precipitation depths and the corresponding simulated peak discharges, are investigated for different antecedent soil moisture conditions using the copula method. The procedure started with the calibration and validation of the soil moisture accounting (SMA) loss rate algorithm incorporated in the Hydrologic Engineering Center – hydrologic modeling system (HEC–HMS) model for the study watershed. A 1000 year long time series of hourly rainfall was then generated by the Neyman–Scott rectangular pulses (NSRP) rainfall generator, which was then transformed into the runoff rate by the HEC–HMS model. This long-term continuous hydrological simulation resulted in characterizing the response of the watershed for various input conditions such as initial soil moisture content (AMC), total rainfall depth, and rainfall duration. For each initial soil moisture class, the copula method was employed to determine the joint probability distribution of rainfall depth and peak discharge. For instance, for dry AMC condition and 1 h rainfall duration, the Joe family fitted best to the data, compared with six other one-parameter families of copulas. Results showed that the bivariate analysis of rainfall–runoff using the copula method can well characterize the watershed hydrological behavior. The derived offline curves could provide a probabilistic real-time peak discharge forecast.

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>

Assessment of initial soil moisture conditions for event-based rainfall–runoff modelling

2010 ◽  
Vol 387 (3-4) ◽  
pp. 176-187 ◽  
Author(s):  
Yves Tramblay ◽  
Christophe Bouvier ◽  
Claude Martin ◽  
Jean-François Didon-Lescot ◽  
Dragana Todorovik ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Rainfall Runoff ◽  
Initial Soil Moisture ◽  
Initial Soil ◽  
Moisture Conditions ◽  
Event Based

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

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 Impacts of Antecedent Soil moisture on the Rainfall–Runoff Transformation Process Based on High-Resolution Observations in Soil Tank Experiments

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 296 ◽  
Author(s):  
Shuang Song ◽  
Wen Wang
Keyword(s):  
Soil Moisture ◽  
Overland Flow ◽  
Response Times ◽  
Hysteretic Behavior ◽  
Rainfall Runoff ◽  
Moisture Index ◽  
Antecedent Soil Moisture ◽  
Non Linear ◽  
Subsurface Runoff ◽  
The Impact

An experimental soil tank (12 m long × 1.5 m wide × 1.5m deep) equipped with a spatially distributed instrument network was designed to conduct the artificial rainfall–runoff experiments. Soil moisture (SM), precipitation, surface runoff (SR) and subsurface runoff (SSR) were continuously monitored. A total of 32 rainfall–runoff events were analyzed to investigate the non-linear patterns of rainfall–runoff response and estimate the impact of antecedent soil moisture (ASM) on runoff formation. Results suggested that ASM had a significant impact on runoff at this plot scale, and a moisture threshold-like value which was close to field capacity existed in the relationship between soil water content and event-based runoff coefficient (φe), SSR and SSR/SR. A non-linear relationship between antecedent soil moisture index (ASI) that represented the initial storage capacity of the soil tank and total runoff was also observed. Response times of SR and SM to rainfall showed a marked variability under different conditions. Under wet conditions, SM at 10 cm started to increase prior to SR on average, whereas it responds slower than SR under dry conditions due to the effect of water repellency. The predominant contributor to SR generation for all events is the Hortonian overland flow (HOF). There is a hysteretic behavior between subsurface runoff flow and soil moisture with a switch in the hysteretic loop direction based on the wetness conditions prior to the event.

Sign in / Sign up

Export Citation Format

Share Document