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Hyporheic exchange transports solutes into the subsurface where they can undergo biogeochemical transformations, affecting fluvial water quality and ecology. A three-dimensional numerical model of a natural in-stream gravel bar (20 m x 6 m) is presented. Multiple steady state streamflow is simulated with a computational fluid dynamics code that is sequentially coupled to a reactive transport groundwater model via the hydraulic head distribution at the streambed. Ambient groundwater flow is considered by scenarios of neutral, gaining, and losing conditions. The transformation of oxygen, nitrate, and dissolved organic carbon by aerobic respiration and denitrification in the hyporheic zone are modeled, as is the denitrification of groundwater-borne nitrate when mixed with stream-sourced carbon. In contrast to fully submerged structures, hyporheic exchange flux decreases with increasing stream discharge, due to decreasing hydraulic head gradients across the partially submerged structure. Hyporheic residence time distributions are skewed in the log-space with medians of up to 8 h and shift to symmetric distributions with increasing level of submergence. Solute turnover is mainly controlled by residence times and the extent of the hyporheic exchange flow, which defines the potential reaction area. Although streamflow is the primary driver of hyporheic exchange, its impact on hyporheic exchange flux, residence times, and solute turnover is small, as these quantities exponentially decrease under losing and gaining conditions. Hence, highest reaction potential exists under neutral conditions, when the capacity for denitrification in the partially submerged structure can be orders of magnitude higher than in fully submerged structures.
Cosmic-Ray neutron sensing (CRS) is a unique approach to measure soil moisture at field scale filling the gap of current methodologies. However, CRS signal is affected by all the hydrogen pools on the land surface and understanding their relative importance plays an important role for the application of the method e.g., validation of remote sensing products and data assimilation. In this study, a soil moisture scaling approach is proposed to estimate directly the correct CRS soil moisture based on the soil moisture profile measured at least in one position within the field. The approach has the advantage to avoid the need to introduce one correction for each hydrogen contribution and to estimate indirectly all the related time-varying hydrogen pools. Based on the data collected in three crop seasons, the scaling approach shows its ability to identify and to quantify the seasonal biomass water equivalent. Additionally, the analysis conducted at sub-daily time resolution is able to quantify the daily vertical redistribution of the water biomass and the rainfall interception, showing promising applications of the CRS method also for these types of measurements. Overall, the study underlines how not only soil moisture but all the specific hydrological processes in the soil-plant-atmosphere continuum should be considered for a proper evaluation of the CRS signal. For this scope, the scaling approach reveals to be a simple and pragmatic analysis that can be easily extended to other experimental sites. (C) 2015 Elsevier B.V. All rights reserved.
Sediments in rivers record the dynamics of erosion processes. While bulk sediment fluxes are easily and routinely obtained, sediment caliber remains underexplored when inferring erosion mechanisms. Yet sediment grain size distributions may be the key to discriminating their origin. We have studied grain size-specific suspended sediment fluxes in the Kali Gandaki, a major trans-Himalayan river. Two strategically located gauging stations enable tracing of sediment caliber on either side of the Himalayan orographic barrier. The data show that fine sediment input into the northern headwaters is persistent, while coarse sediment comes from the High Himalayas during the summer monsoon. A temporally matching landslide inventory similarly indicates the prominence of monsoon-driven hillslope mass wasting. Thus, mechanisms of sediment supply can leave strong traces in the fluvial caliber, which could project well beyond the mountain front and add to the variability of the sedimentary record of orogen erosion.
Earthquakes impart an impressive force on epicentral landscapes, with immediate catastrophic hillslope response. However, their legacy on geomorphic process rates remains poorly constrained. We have determined the evolution of landslide rates in the epicentral areas of four intermediate to large earthquakes (M-w, 6.6-7.6). In each area, landsliding correlates with the cumulative precipitation during a given interval. Normalizing for this meteorological forcing, landslide rates have been found to peak after an earthquake and decay to background values in 1-4 yr, with the decay time scale probably proportional to the earthquake magnitude. The transient pulse of landsliding is not related to external forcing such as rainfall or aftershocks, and we tentatively attribute it to the reduction and subsequent recovery of ground strength. Observed geomorphic trends are not linked with groundwater level changes or root system damage, both of which could affect substrate strength. We propose that they are caused by reversible damage of rock mass and/or loosening of regolith. Qualitative accounts of ground cracking due to strong ground motion abound, and our observations are circumstantial evidence of its potential importance in setting landscape sensitivity to meteorological forcing after large earthquakes.
We study distributed-order time fractional diffusion equations characterized by multifractal memory kernels, in contrast to the simple power-law kernel of common time fractional diffusion equations. Based on the physical approach to anomalous diffusion provided by the seminal Scher-Montroll-Weiss continuous time random walk, we analyze both natural and modified-form distributed-order time fractional diffusion equations and compare the two approaches. The mean squared displacement is obtained and its limiting behavior analyzed. We derive the connection between the Wiener process, described by the conventional Langevin equation and the dynamics encoded by the distributed-order time fractional diffusion equation in terms of a generalized subordination of time. A detailed analysis of the multifractal properties of distributed-order diffusion equations is provided.
Non-invasive imaging techniques to study O-2 micro-patterns around pesticide treated lupine roots
(2015)
The soil root interface is a highly heterogeneous system, e.g. in terms of O-2 and pH distribution. The destructive character of conventional methods disturbs the natural conditions of those biogeochemical gradients. Therefore, experiments aiming to control these influences and study pesticide kinetics under given O-2 and pH conditions suffer from a large uncertainty of the "real" O-2/pH at a certain position. Our approach with two different imaging techniques will examine the soil-root interface as well as the dissipation of the applied pesticide at a high spatial resolution.
The obtained outcomes show directly that the pH has an influence on enantioselective dissipation of the acetanilide fungicide metalaxyl. In areas with high pH from an applied racemic mixture, the R-enantiomer dissipates faster than the S-enantiomer. Moreover, we found significantly reduced oxygen values in the bulk soil and vicinity of metalaxyl treated roots compared to control plant roots. The combination of matrix-assisted laser desorption/ionization mass spectrometry (MALDI) and fluorescence imaging indicated the oxygen-dependent behavior of metalaxyl at the root surface.
The results presented here underline the great potential of combining different imaging methods to examine the soil-root interfaces as well as the dissipation of organic pollutants in small soil compartments. (C) 2014 Elsevier B.V. All rights reserved.
Inventories of individually delineated landslides are a key to understanding landslide physics and mitigating their impact. They permit assessment of area-frequency distributions and landslide volumes, and testing of statistical correlations between landslides and physical parameters such as topographic gradient or seismic strong motion. Amalgamation, i.e. the mapping of several adjacent landslides as a single polygon, can lead to potentially severe distortion of the statistics of these inventories. This problem can be especially severe in data sets produced by automated mapping. We present five inventories of earthquake-induced landslides mapped with different materials and techniques and affected by varying degrees of amalgamation. Errors on the total landslide volume and power-law exponent of the area-frequency distribution, resulting from amalgamation, may be up to 200 and 50 %, respectively. We present an algorithm based on image and digital elevation model (DEM) analysis, for automatic identification of amalgamated polygons. On a set of about 2000 polygons larger than 1000 m(2), tracing landslides triggered by the 1994 Northridge earthquake, the algorithm performs well, with only 2.7-3.6% incorrectly amalgamated landslides missed and 3.9-4.8% correct polygons incorrectly identified as amalgams. This algorithm can be used broadly to check landslide inventories and allow faster correction by automating the identification of amalgamation.
Flood risk analyses are often estimated assuming the same flood intensity along the river reach under study, i.e. discharges are calculated for a number of return periods T, e.g. 10 or 100 years, at several streamflow gauges. T-year discharges are regionalised and then transferred into T-year water levels, inundated areas and impacts. This approach assumes that (1) flood scenarios are homogeneous throughout a river basin, and (2) the T-year damage corresponds to the T-year discharge. Using a reach at the river Rhine, this homogeneous approach is compared with an approach that is based on four flood types with different spatial discharge patterns. For each type, a regression model was created and used in a Monte-Carlo framework to derive heterogeneous scenarios. Per scenario, four cumulative impact indicators were calculated: (1) the total inundated area, (2) the exposed settlement and industrial areas, (3) the exposed population and 4) the potential building loss. Their frequency curves were used to establish a ranking of eight past flood events according to their severity. The investigation revealed that the two assumptions of the homogeneous approach do not hold. It tends to overestimate event probabilities in large areas. Therefore, the generation of heterogeneous scenarios should receive more attention.