soil saturation
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2021 ◽  
Vol 25 (11) ◽  
pp. 5937-5950
Author(s):  
Elena Leonarduzzi ◽  
Brian W. McArdell ◽  
Peter Molnar

Abstract. Landslides are an impacting natural hazard in alpine regions, calling for effective forecasting and warning systems. Here we compare two methods (physically based and probabilistic) for the prediction of shallow rainfall-induced landslides in an application to Switzerland, with a specific focus on the value of antecedent soil wetness. First, we show that landslide susceptibility predicted by the factor of safety in the infinite slope model is strongly dependent on soil data inputs, limiting the hydrologically active range where landslides can occur to only ∼20 % of the country with typical soil parameters and soil depth models, not accounting for uncertainty. Second, we find the soil saturation estimate provided by a conceptual hydrological model (PREVAH) to be more informative for landslide prediction than that estimated by the physically based coarse-resolution model (TerrSysMP), which we attribute to the lack of temporal variability and coarse spatial resolution in the latter. Nevertheless, combining the soil water state estimates in TerrSysMP with the infinite slope approach improves the separation between landslide triggering and non-triggering rainfall events. Third, we demonstrate the added value of antecedent soil saturation in combination with rainfall thresholds. We propose a sequential threshold approach, where events are first split into dry and wet antecedent conditions by an N d (day) antecedent soil saturation threshold, and then two different total rainfall–duration threshold curves are estimated. This, among all different approaches explored, is found to be the most successful for landslide prediction.


Author(s):  
Ahmad Luthfi Gifari ◽  
Anggunmeka Luhur Prasasti ◽  
Casi Setianingsih

Eos ◽  
2021 ◽  
Vol 102 ◽  
Author(s):  
Ellis Avallone

The most complete hydrological data set for the African continent reveals a surprise: Soil moisture, not heavy precipitation, best explains the timing of Africa’s most severe floods.


2021 ◽  
Vol 20 (2) ◽  
Author(s):  
David C. Mercker ◽  
Michael H. Schiebout ◽  
Joshua S. Bowden ◽  
James R. Kerfoot

2021 ◽  
Vol 6 (1) ◽  
pp. 64
Author(s):  
Paul David Carchipulla-Morales ◽  
Xavier Zapata-Ríos

This study presents the spatio–temporal assessment of the Pugllohuma peatland’s soil saturation and water level variability. The Pugllohuma is a high elevation wetland located within the Sustainable Water Conservation Area Antisana in the northern Andes of Ecuador above 4100 m.a.s.l. This assessment provides information of the dry and wet seasons in the Pugllohuma peatland. The temporal variability was investigated considering variables such as: atmospheric pressure, rainfall, relative humidity, air temperature, wind speed and direction records of two near meteorological stations, while the spatial variability was investigated through images of the Sentinel-1 mission from 2017 to 2019, and terrain characteristics such as: elevation and slope. Image analysis and degree of soil saturation classification were carried out using the R programming language and Google Earth Engine, and the results were published in the UI service in Google Apps Script.


2021 ◽  
Vol 25 (3) ◽  
pp. 1425-1446
Author(s):  
Judith Eeckman ◽  
Hélène Roux ◽  
Audrey Douinot ◽  
Bertrand Bonan ◽  
Clément Albergel

Abstract. The MARINE (Model of Anticipation of Runoff and INundations for Extreme events) hydrological model is a distributed model dedicated to flash flood simulation. Recent developments of the MARINE model are explored in this work. On one hand, transfers of water through the subsurface, formerly relying on water height, now take place in a homogeneous soil column based on the soil saturation degree (SSF model). On the other hand, the soil column is divided into two layers, which represent, respectively, the upper soil layer and the deep weathered rocks (SSF–DWF model). The aim of the present work is to assess the accuracy of these new representations for the simulation of soil moisture during flash flood events. An exploration of the various products available in the literature for soil moisture estimation is performed. The efficiency of the models for soil saturation degree simulation is estimated with respect to several products either at the local scale or spatially distributed: (i) the gridded soil moisture product provided by the operational modeling chain SAFRAN-ISBA-MODCOU; (ii) the gridded soil moisture product provided by the LDAS-Monde assimilation chain, which is based on the ISBA-A-gs land surface model and assimilating satellite derived data; (iii) the upper soil water content hourly measurements taken from the SMOSMANIA observation network; and (iv) the Soil Water Index provided by the Copernicus Global Land Service (CGLS), which is derived from Sentinel-1 C-SAR and ASCAT satellite data. The case study is performed over two French Mediterranean catchments impacted by flash flood events over the 2017–2019 period. The local comparison of the MARINE outputs with the SMOSMANIA measurements, as well as the comparison at the basin scale of the MARINE outputs with the gridded LDAS-Monde and CGLS data, lead to the following conclusion: both the dynamics and the amplitudes of the soil saturation degree simulated with the SSF and SSF–DWF models are better correlated with both the SMOSMANIA measurements and the LDAS-Monde data than the outputs of the base model. Finally, the soil saturation degree simulated by the two-layers model for the deep layer is compared to the soil saturation degree provided by the LDAS-Monde product at corresponding depths. In conclusion, the developments presented for the representation of subsurface flow in the MARINE model enhance the soil saturation degree simulation during flash floods with respect to both gridded data and local soil moisture measurements.


2021 ◽  
Author(s):  
Hannah Lieberman ◽  
Christian von Sperber ◽  
Maia Rothman ◽  
Cynthia Kallenbach

<p>With climate change, much of the world will experience devastating shifts in weather patterns like increased flooding, intensifying periods of soil saturation. Soil carbon (C), nitrogen (N) and phosphorus (P) cycles are sensitive to changes in soil saturation, where exchange between the mineral-bound and the soluble bioavailable pools can occur with increases in moisture content. With soil saturation, C, N, and P may be mobilized either through greater diffusion or reduced conditions that cause desorption of mineral-bound C, N and P into their respective soluble pools. De-sorption, resorption and diffusion dynamics of C, N, and P may or may not reflect the stoichiometry of the mineral bound pool. Changes in bioavailable soluble C, N and P that could occur with soil saturation and drying may cause unknown consequences for microbial biomass C:N:P. With increases in soil moisture, simultaneous changes in both substrate stoichiometry and microbial growth may occur that impact microbial biomass stoichiometry.  Such changes in microbial stoichiometry and microbial retention of C, N, and P may affect the post-flood fate of soluble C, N, and P. Understanding how releases in mineral bound C, N and P alter the bioavailable C:N:P and how this in turn impacts microbial activity and accumulation of these substrates can inform predictions of retention or losses of C, N and P following soil saturation events.</p><p>To determine if mineral-bound, soluble and microbial biomass stoichiometry is maintained or altered during and after soil saturation events, we used a laboratory incubation approach with manipulated soil saturation and duration. Soil incubations were maintained at three water-holding capacity (WHC) levels: 20% (control), 50%, (moderate) and 100% (severe). We maintained the moderate and severe water-logging treatments for  0.5 h, 24 h, 1 week, followed by air-drying to 20% WHC to examine the influence of flood duration. To understand the exchanges of C, N and P between different pools during flooding, we compared changes in soluble and mineral bound soil C, N and P and impacts on microbial C, N, and P exo-cellular enzymes, and microbial biomass C:N:P. Preliminary results indicate that greater soil moisture content increases soluble P and that the 24 hour flood period captures shifts in the mineral bound P pool that do not remain for the longer flood period (1 week). Enzyme activity similarly reflects an increase in microbial activity in the soil held at 50% and 100% moisture content for 24 hours. We also discuss how soil moisture levels and flood duration impact soluble and mineral bound C relative to P, and how microbial biomass C:N:P tracks these fractions. By exploring the combined response of mineral-bound and soluble C, N, and P to variation in soil saturation, we can better understand how different flood scenarios will impact soil C, N and P retention.</p>


2021 ◽  
Author(s):  
Hyeonji Song ◽  
Snowie Galgo ◽  
Ronley Canatoy ◽  
Hogyeong Chae ◽  
Pil Joo Kim

<p>Soil C sequestration is widely regarded as the most reasonable way to mitigate global warming. Traditionally, a high amount of organic carbon (OC) input is strongly recommended to increase soil organic carbon (SOC) stocks in croplands. However, according to the whole-soil saturation theory, stable SOC (mineral-associated SOC) accumulation can be limited at a certain point, relying on silt and clay contents. Most studies based on the theory were conducted in aerobic soil condition. This relationship is still uncertain in a rice paddy that makes up 10.8% of total arable land and has an anaerobic soil environment. In this study, we investigated high OC addition can enhance soil C sequestration in a rice paddy. We added different OC levels (0.5, 2.0, 2.9, and 4.6 Mg C ha<sup>-1</sup> yr<sup>-1</sup>) in rice paddy by incorporating cover crop biomass for nine years. SOC stock and soil saturation degree were determined. Unprotected, sand-associated, silt-associated, and clay-associated SOC were separated via density and size fractionation. Respired C losses (CO<sub>2</sub>-C and CH<sub>4</sub>-C) were monitored using the static closed chamber method. SOC stock did not linearly increase with higher amount of OC input. The carbon sequestration efficiency (i.e. the increase of SOC per unit of OC input) decreases with the amount OC added. Higher OM input significantly increased unprotected labile SOC content. Unprotected SOC (<1.85 g cm<sup>-3</sup>) exponentially increased as the SOC saturation degree was higher. On the other hand, stable SOC content did not exhibit a linear relationship with the SOC saturation degree. The higher OC addition level exponentially increased respired C loss. In particular, C loss via CH<sub>4</sub> was more sensitive to high OC addition. We conclude that higher OC addition in rice paddy without consideration in terms of SOC stock saturation point can accelerate global warming by increasing labile SOC accumulation and CH<sub>4</sub> emission.</p>


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