Subsurface tile drainage speeds water removal from agricultural fields that are historically prone to flooding. While managed drainage systems improve crop yields, they can also contribute tothe eutrophication of downstream ecosystems, as tile-drained systems are conduits for nutrients to adjacent waterways. The changing climate of the Midwestern US has already altered precipitation regimes which will likely continue into the future, with unknown effects on tile drain water and nutrient loss to waterways. Adding vegetative cover (i.e., as winter cover crops) is one approach that can retain water and nutrients on fields to minimize export via tile drains. In the current study, we evaluate the effect of cover crops on tile drain discharge and soluble reactive phosphorus (SRP) loads using bi-monthly measurements from 43 unique tile outlets draining fields with or without cover crops in two watersheds in northern Indiana. Using four water years of data (n = 844 measurements), we examined the role of short-term antecedent precipitation conditions and variation in soil biogeochemistry in mediating the effect of cover crops on tile drain flow and SRP loads. We observed significant effects of cover crops on both tile drain discharge and SRP loads, but these results were season and watershed specific. Cover crop effects were identified only in spring, where their presence reduced tile drain discharge in both watersheds and SRP loads in one watershed. Varying effects on SRP loads between watersheds were attributed to different soil biogeochemical characteristics, where soils with lower bioavailable P and higher P sorption capacity were less likely to have a cover crop effect. Antecedent precipitation was important in spring, and cover crop differences were still evident during periods of wet and dry antecedent precipitation conditions. Overall, we show that cover crops have the potential to significantly decrease spring tile drain P export, and these effects are resilient to a wide range of precipitation conditions. 相似文献
Subsurface deformation is a driver for river path selection when deformation rates become comparable to the autogenic mobility rate of rivers. Here we combine geomorphology, soil and sediment facies analyses, and geophysical data of the Late Quaternary sediments of the central Garo-Rajmahal Gap in Northwest Bengal to link subsurface deformation with surface processes. We show variable sedimentation characteristics, from slow rates (<0.8 mm/year) in the Tista megafan at the foot of the Himalaya to nondeposition at the exposed surface of the Barind Tract to the south, enabling the development of mature soils. Combined subsidence in the Tista fan and uplift of the Barind Tract are consistent with a N-S flexural response of the Indian plate to loading of the Himalaya Mountains given a low value of elastic thickness (15–25 km). Provenance analysis based on bulk strontium concentration suggests a dispersal of sediment consistent with this flexural deformation—in particular the abandonment of the Barind Tract by a Pleistocene Brahmaputra River and the current extents of the Tista megafan lobes. Overall, these results highlight the control by deeply rooted deformation patterns on the routing of sediment by large rivers in foreland settings. 相似文献
Prediction of true classes of surficial and deep earth materials using multivariate spatial data is a common challenge for geoscience modelers. Most geological processes leave a footprint that can be explored by geochemical data analysis. These footprints are normally complex statistical and spatial patterns buried deep in the high-dimensional compositional space. This paper proposes a spatial predictive model for classification of surficial and deep earth materials derived from the geochemical composition of surface regolith. The model is based on a combination of geostatistical simulation and machine learning approaches. A random forest predictive model is trained, and features are ranked based on their contribution to the predictive model. To generate potential and uncertainty maps, compositional data are simulated at unsampled locations via a chain of transformations (isometric log-ratio transformation followed by the flow anamorphosis) and geostatistical simulation. The simulated results are subsequently back-transformed to the original compositional space. The trained predictive model is used to estimate the probability of classes for simulated compositions. The proposed approach is illustrated through two case studies. In the first case study, the major crustal blocks of the Australian continent are predicted from the surface regolith geochemistry of the National Geochemical Survey of Australia project. The aim of the second case study is to discover the superficial deposits (peat) from the regional-scale soil geochemical data of the Tellus Project. The accuracy of the results in these two case studies confirms the usefulness of the proposed method for geological class prediction and geological process discovery.
The impacts of unconventional oil and gas production via high-volume hydraulic fracturing (HVHF) on water resources, such as water use, groundwater and surface water contamination, and disposal of produced waters, have received a great deal of attention over the past decade. Conventional oil and gas production (e.g., enhanced oil recovery [EOR]), which has been occurring for more than a century in some areas of North America, shares the same environmental concerns, but has received comparatively little attention. Here, we compare the amount of produced water versus saltwater disposal (SWD) and injection for EOR in several prolific hydrocarbon producing regions in the United States and Canada. The total volume of saline and fresh to brackish water injected into depleted oil fields and nonproductive formations is greater than the total volume of produced waters in most regions. The addition of fresh to brackish “makeup” water for EOR may account for the net gain of subsurface water. The total amount of water injected and produced for conventional oil and gas production is greater than that associated with HVHF and unconventional oil and gas production by well over a factor of 10. Reservoir pressure increases from EOR and SWD wells are low compared to injection of fluids for HVHF, however, the longer duration of injections could allow for greater solute transport distances and potential for contamination. Attention should be refocused from the subsurface environmental impacts of HVHF to the oil and gas industry as a whole. 相似文献
A landslide susceptibility mapping study was performed using dynamic hillslope hydrology. The modified infinite slope stability model that directly includes vadose zone soil moisture (SM) was applied at Cleveland Corral, California, US and Krishnabhir, Dhading, Nepal. The variable infiltration capacity (VIC-3L) model simulated vadose zone soil moisture and the wetness index hydrologic model simulated groundwater (GW). The GW model predictions had a 75% NASH-Sutcliffe efficiency when compared to California’s in-situ GW measurements. The model performed best during the wet season. Using predicted GW and VIC-3L vadose zone SM, the developed landslide susceptibility maps showed very good agreement with mapped landslides at each study region. Previous quasi-dynamic model predictions of Nepal’s hazardous areas during extreme rainfall events were enhanced to improve the spatial characterization and provide the timing of hazardous conditions. 相似文献
Enhanced production of unconventional hydrocarbons in the United States has driven interest in natural gas development globally, but simultaneously raised concerns regarding water quantity and quality impacts associated with hydrocarbon extraction. We conducted a pre‐development assessment of groundwater geochemistry in the critically water‐restricted Karoo Basin, South Africa. Twenty‐two springs and groundwater samples were analyzed for major dissolved ions, trace elements, water stable isotopes, strontium and boron isotopes, hydrocarbons and helium composition. The data revealed three end‐members: a deep, saline groundwater with a sodium‐chloride composition, an old, deep freshwater with a sodium‐bicarbonate‐chloride composition and a shallow, calcium‐bicarbonate freshwater. In a few cases, we identified direct mixing of the deep saline water and shallow groundwater. Stable water isotopes indicate that the shallow groundwater was controlled by evaporation in arid conditions, while the saline waters were diluted by apparently fossil meteoric water originated under wetter climatic conditions. These geochemical and isotopic data, in combination with elevated helium levels, suggest that exogenous fluids are the source of the saline groundwater and originated from remnant seawater prior to dilution by old meteoric water combined with further modification by water‐rock interactions. Samples with elevated methane concentrations (>14 ccSTP/kg) were strongly associated with the sodium‐chloride water located near dolerite intrusions, which likely provide a preferential pathway for vertical migration of deeply sourced hydrocarbon‐rich saline waters to the surface. This pre‐drill evaluation indicates that the natural migration of methane‐ and salt‐rich waters provides a source of geogenic contamination to shallow aquifers prior to shale gas development in the Karoo Basin. 相似文献
Policies, measures, and models geared towards flood prevention and managing surface waters benefit from high quality data on the presence and characteristics of drainage ditches. As a cost and labour effective alternative for acquiring such data through field surveys, we propose a method (a) to extract vector data representing ditch drainage networks based on local morphologic features derived from high resolution digital elevation models (DEM) and (b) to identify possible connections in the ditch network by calculating a probability of the connectivity using a logistic regression where the predictor variables are characteristics of the ditch centre lines or derived from the DEM. Using Light Detection and Ranging (LiDAR) derived DEMs with a 1 m resolution, the method was developed and tested for a mixed agricultural residential area in north‐eastern Belgium. The derived ditch segments had an error of omission of 8% and an error of commission of 5%. The original positional accuracy of the centre lines of the extracted ditches was 0.6 m and could be improved to 0.4 m by shifting each vertex to the position of the lowest LiDAR point located within a radius equal to the spatial resolution of the used DEM. About 69% of the false disconnections in the network were identified and corrected leading to a reduction of the unconnected parts of the ditch network by 71%. The extracted and connected network approximated the reference ditch network fairly well. 相似文献
Wildfires are landscape scale disturbances that can significantly affect hydrologic processes such as runoff generation and sediment and nutrient transport to streams. In Fall 2016, multiple large drought-related wildfires burned forests across the southern Appalachian Mountains. Immediately after the fires, we identified and instrumented eight 28.4–344 ha watersheds (four burned and four unburned) to measure vegetation, soil, water quantity, and water quality responses over the following two years. Within burned watersheds, plots varied in burn severity with up to 100% tree mortality and soil O-horizon loss. Watershed scale high burn severity extent ranged from 5% to 65% of total watershed area. Water quantity and quality responses among burned watersheds were closely related to the high burn severity extent. Total water yield (Q) was up to 39% greater in burned watersheds than unburned reference watersheds. Total suspended solids (TSS) concentration during storm events were up to 168 times greater in samples collected from the most severely burned watershed than from a corresponding unburned reference watershed, suggesting that there was elevated risk of localized erosion and sedimentation of streams. NO3-N concentration, export, and concentration dependence on streamflow were greater in burned watersheds and increased with increasing high burn severity extent. Mean NO3-N concentration in the most severely burned watershed increased from 0.087 mg L−1 in the first year to 0.363 mg L−1 (+317%) in the second year. These results suggest that the 2016 wildfires degraded forest condition, increased Q, and had negative effects on water quality particularly during storm events. 相似文献