Naturally-occurring colloids, particles of diameter < 10μm, are ubiquitous in geo-environments and can potentially facilitate transport of numerous contaminants in soil including heavy metals, pesticides, pathogens etc. via Colloid-Facilitated Transport (CFT). The CFT of contaminants to groundwater is still an underrepresented transport domain and may lead to significant environmental and health problems related to groundwater contamination. Colloid mobilization, transport and CFT in various geomedia are highly sensitive to physico-chemical perturbations. This study investigated colloid transport and colloid-facilitated heavy metal transport in saturated porous media with a series of column experiments using soil colloids extracted from two areas affected by Chronic Kidney Disease of Unknown Etiology (CKDu) in North Central Province of Sri Lanka. Colloid breakthrough curves were obtained from the column studies to observe the colloid transport under different flow rates (0.5±0.05, 1.65±0.05, 4.10±0.05 cm3/s) and ionic strengths (NaCl - 0.01 M, 0.05 M, 0.1 M). The CFT was studied using Cadmium (Cd(II)) as a model contaminant together with colloidal suspension under selected scenarios for high colloid deposition. Elevated colloid concentrations were observed in high CKDu affected area compared to the low endemic area. The experimental results were numerically simulated on an advection-diffusion/dispersion modelling framework coupled with first-order attachment, detachment and straining parameters inversely estimated using HYDRUS 1D software. Experimental and simulated colloid breakthrough curves showed a good agreement, and recognized colloid attachment as the key mechanism for colloid immobilization in selected soil. Both colloids and CFT of Cd(II) showed pronounced deposition under low flow rate and high ionic strength.
Rooting depth is an ecosystem trait that determines the extent of soil development and carbon (C) and water cycling. Recent hypotheses propose that human-induced changes to Earth’s biogeochemical cycles propagate deeply due to rooting depth changes from agricultural and climate-induced land cover changes. Yet, the lack of a global-scale quantification of rooting depth responses to human activity limits knowledge of hydrosphere-atmosphere-lithosphere feedbacks in the Anthropocene. Here we use land cover datasets to demonstrate that root depth distributions are changing globally as a consequence of agricultural expansion truncating depths above which 99% of root biomass occurs (D99) by ~60 cm, and woody encroachment linked to anthropogenic climate change extending D99 in other regions by ~38 cm. The net result of these two opposing drivers is a global reduction of D99 by 5%, or ~8 cm, representing a loss of ~11,600 km3 of rooted volume. Projected land cover scenarios in 2100 suggest additional future D99 shallowing of up to 30 cm, generating further losses of rooted volume of ~43,500 km3, values exceeding root losses experienced to date and suggesting that the pace of root shallowing will quicken in the coming century. Losses of Earth’s deepest roots — soil-forming agents — suggest unanticipated changes in fluxes of water, solutes, and C. Two important messages emerge from our analyses: dynamic, human-modified root distributions should be incorporated into earth systems models, and a significant gap in deep root research inhibits accurate projections of future root distributions and their biogeochemical consequences.
Hillslopes are responsible for the production and transport of sediments within a landscape (Gilbert 1877). Since the hillslope gradient and morphology tend to vary across a landscape, it is expected that the erosion and sediment delivery would also be non-uniform. In this study, we explore the probability of the flux at a particular point in the catchment reaching the river mouth using connectivity and the Revised Universal Soil Loss Equation (RUSLE) in the Pranmati river catchment (a small 3rd order Himalayan river catchment within the Ganga River system). Methodology involves characterising the hillslopes of Pranmati river catchment centered on land use and land cover units. Using RUSLE, the sediment yielding capacity of various land cover units are estimated based on which potential source areas are marked. The sediment connectivity within the basin is also calculated by generating a sediment connectivity map of the area using method given by Borcelli et al. (2008). The catchment is categorized into four classes – (A) Highly connected zones with high sediment yielding capacity (B) highly connected zones but low yielding capacity (C) poorly connected zones but high yielding capacity (D) poorly connected zones and low yielding capacity. The area is then mapped on the basis of the defined classes and potential areas of erosion and storage are identified. Our results show that about 62% of the catchment area has low connectivity implying sediment flux generated in these zones have a low probability of leaving the catchment. Only 11% of the catchment area has sediment yield greater than the mean yield per hectare. The sediment generated from this small area of the catchment contributes 93% of the total sediment production of the catchment. References Borselli, L., Cassi, P., & Torri, D. (2008). Prolegomena to sediment and flow connectivity in the landscape: a GIS and field numerical assessment. Catena, 75(3), 268-277. Gilbert, G. K. (1877). Geology of the Henry mountains (pp. i-160). Government Printing Office.
Rain gardens are green stormwater infrastructure that are designed to leverage natural processes to mitigate the impacts of urban stormwater through capturing, infiltrating, and filtering run off. Overtime these systems have the potential to buildup fines and nutrients, impacting their sustainable function. A rain garden’s performance depends on its ability to infiltrate runoff which can be reduced by clogging. Another concern is the potential transport of contaminants from rain gardens to groundwater through deep drainage. This study analyses the spatial and temporal distribution of fines and nutrients in three rain gardens through comprehensive field tests, laboratory testing, and computation analysis. Geomorphic studies were performed by integrating the digital elevation models, derived from Lidar surveys, with the FastMech solver within International River Interface Cooperative (iRIC) software, to model shear stress distribution and sediment transport relative to spatial observations of soil texture and nutrient concentrations within the rain garden. The soil properties were also used in creating models of water infiltration and nutrient sorption using Hydrus 1D. Results show that shear stresses in localized sections of each rain garden can be correlated with fines and nutrient distributions, allowing for prioritizing locations for maintenance. To conclude, LiDAR scans, flow and shear stress models, infiltration and nutrient transport models, field and laboratory soil tests can help us understand the surface dynamics and soil attributes, and gradually gain insight into the GSI performance with time.
Some of the Earth system data products such as those from NASA airborne and field investigations (a.k.a. campaigns), are highly heterogeneous and cross-disciplinary, making the data extremely challenging to manage. For example, airborne and field campaign measurements tend to be sporadic over a period of time, with large gaps. Data products generated are of various processing levels and utilized for a wide range of inter- and cross-disciplinary research and applications. Data and derived products have been historically stored in a variety of domain-specific standard (and some non-standard) formats and in various locations such as NASA Distributed Active Archive Centers (DAACs), NASA airborne science facilities, field archives, or even individual scientists’ computer hard drives. As a result, airborne and field campaign data products have often been managed and represented differently, making it onerous for data users to find, access, and utilize campaign data. Some difficulties in discovering and accessing the campaign data originate from the incomplete data product and contextual metadata that may contain details relevant to the campaign (e.g. campaign acronym and instrument deployment locations), but tend to lack other significant information needed to understand conditions surrounding the data. Such details can be burdensome to locate after the conclusion of a campaign. Utilizing consistent terminology, essential for improved discovery and reuse, is also challenging due to the variety of involved disciplines. To help address the aforementioned challenges faced by many repositories and data managers handling airborne and field data, this presentation will describe stewardship practices developed by the Airborne Data Management Group (ADMG) within the Interagency Implementation and Advanced Concepts Team (IMPACT) under the NASA’s Earth Science Data systems (ESDS) Program.
We study how ground frost affects the ambient seismic wavefield recorded by a three-component broadband sensor. By applying machine learning algorithms on continuous seismic data, we can retrieve the seismic signature of the continuous freeze and thaw process at the surface of the ground. The retrieved signature reveals that the presence of ground frost imprints the amplitude of the ambient seismic wavefield, and the energy ratio between horizontal and vertical components (H/V). A regression model can even predict diurnal freeze and thaw patterns based on the seismic data. Thus, we assume that slight changes in the physical properties of the frozen surface, such as the thickness, alter the seismic wavefield. Models of the subsurface with different properties of the ground frost agree with the observations from the field. The penetration depth of the ground frost, the temperature of the frozen ground, and the presence of different modes in the wavefield determine how the seismic wavefield is changing. The findings of this study show the potential of a single seismic station for monitoring frozen bodies near the surface, such as permafrosts.
The uncontrolled rapid population growth in our regions and strong industrialization are putting pressure on natural resources, accelerating climate change and desertification. This study aims to follow the evolution of land use in the N’ZI watershed. Three images from Landsat 4 & 5 (1986), Landsat 7 (2000), and Landsat 8 (2020) made it possible to carry out this study. Remote sensing and geographic information systems (GIS) have been used to monitor land cover as a whole. The software Envi 5.1 and ArcGIS 10.4.1 have made it possible to do various treatments. The supervised classification method was used in this work in addition to the calculation of the spectral indices. The land-use analysis showed the changes that took place during the periods 1986-2000, 2000-2020, and 1986-2020. The results of this analysis showed regression of water surfaces (-64.95% and-52.47%) over the period (2000-2020 and 1986-2020) on the other hand, there is a great increase in bare-ground dwellings (373.63%) and low-cover soils (10.60%). These progressions are at the expense in particular of forests (-86.93%), savannas (-3.97%), and agricultural areas (-9.30%) between 1986-2020.
The dissolution and mobilization of non-aqueous phase liquids (NAPL) blobs in Surfactant-Enhanced Aquifer Remediation (SEAR) processes are upscaled using dynamic pore network modelling of three-dimensional and unstructured networks. We considered corner flow and micro-flow mechanisms including snap-off and piston-like movement for two-phase flow. Moreover, NAPL entrapment and remobilization were evaluated using force analysis to develop capillary desaturation curve (CDC) and predict the onset of remobilization and complete removal of entrapped NAPL blobs. The corner diffusion mechanism was also applied in the modeling of interphase mass transfer to represent NAPL dissolution as the dominant mass transfer process. Our model showed that although surfactants enhance NAPL recovery during two-phase flow, surfactant-enhanced remediation of residual NAPL through dissolution is highly dependent on surfactant type. When sodium dodecyl sulfate (SDS), as a surfactant with high critical micelle concentration (CMC) and low micelle partition coefficient ( ) was injected into a NAPL contaminated site, reduction in mass transfer rate coefficient (due to considerable changes in interface chemical potentials) significantly reduced NAPL recovery after the end of two-phase flow. However, Triton X-100 (with low CMC and high ) improved NAPL recovery. This is because by enhancing solubility at surfactant concentrations greater than CMC, Triton X-100 overcompensates the interphase mass transfer reduction.