Cover crops and precipitation influence soluble reactive phosphorus losses via tile drain discharge in an agricultural watershed

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.     

Flexural deformation controls on Late Quaternary sediment dispersal in the Garo-Rajmahal Gap,NW Bengal Basin

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.     

Surficial and Deep Earth Material Prediction from Geochemical Compositions

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.

     

Modeling regional landslide susceptibility using dynamic soil moisture profiles

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.     

Extracting drainage networks and their connectivity using LiDAR data

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.     

Watershed-scale vegetation,water quantity,and water quality responses to wildfire in the southern Appalachian mountain region,United States

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.     

Environmental Monitoring and Peat Assessment Using Multivariate Analysis of Regional-Scale Geochemical Data

A compositional multivariate approach was used to analyse regional-scale soil geochemical data obtained as part of the Tellus Project generated by the Geological Survey of Northern Ireland. The multi-element total concentration data presented comprise X-ray fluorescence (XRF) analyses of 6862 rural soil samples collected at 20-cm depth on a non-aligned grid at one site per \(2\,\hbox {km}^{2}\). Censored data were imputed using published detection limits. Each soil sample site was assigned to the regional geology map, resulting in spatial data for one categorical variable and 35 continuous variables comprised of individual and amalgamated elements. This paper examines the extent to which soil geochemistry reflects the underlying geology or superficial deposits. Since the soil geochemistry is compositional, log-ratios were computed to adequately evaluate the data using multivariate statistical methods. Principal component analysis (PCA) and minimum/maximum autocorrelation factors (MAF) were used to carry out linear discriminant analysis (LDA) as a means to discover and validate processes related to the geologic assemblages coded as age bracket. Peat cover was introduced as an additional category to measure the ability to predict and monitor fragile ecosystems. Overall prediction accuracies for the age bracket categories were 68.4 % using PCA and 74.7 % using MAF. With inclusion of peat, the accuracy for LDA classification decreased to 65.0 and 69.9 %, respectively. The increase in misclassification due to the presence of peat may reflect degradation of peat-covered areas since the creation of superficial deposit classification.     

Conodont geothermometry in pyroclastic kimberlite: constraints on emplacement temperatures and cooling histories

Kimberlite pipes from Chidliak, Baffin Island, Nunavut, Canada host surface-derived Paleozoic carbonate xenoliths containing conodonts. Conodonts are phosphatic marine microfossils that experience progressive, cumulative and irreversible colour changes upon heating that are experimentally calibrated as a conodont colour alteration index (CAI). CAI values permit us to estimate the temperatures to which conodont-bearing rocks have been heated. Conodonts have been recovered from 118 samples from 89 carbonate xenoliths collected from 12 of the pipes and CAI values within individual carbonate xenoliths show four types of CAI distributions: (1) CAI values that are uniform throughout the xenolith; (2) lower CAIs in core of a xenolith than the rim; (3) CAIs that increase from one side of the xenolith to the other; and, (4) in one xenolith, higher CAIs in the xenolith core than at the rim. We have used thermal models for post-emplacement conductive cooling of kimberlite pipes and synchronous heating of conodont-bearing xenoliths to establish the temperature–time history of individual xenoliths within the kimberlite bodies. Model results suggest that the time-spans for xenoliths to reach the peak temperatures recorded by CAIs varies from hours for the smallest xenoliths to 2 or 3 years for the largest xenoliths. The thermal modelling shows the first three CAI patterns to be consistent with in situ conductive heating of the xenoliths coupled to the cooling host kimberlite. The fourth pattern remains an anomaly.

     

Sedimentology of the continental end‐Permian extinction event in the Sydney Basin,eastern Australia

Upper Permian to Lower Triassic coastal plain successions of the Sydney Basin in eastern Australia have been investigated in outcrop and continuous drillcores. The purpose of the investigation is to provide an assessment of palaeoenvironmental change at high southern palaeolatitudes in a continental margin context for the late Permian (Lopingian), across the end‐Permian Extinction interval, and into the Early Triassic. These basins were affected by explosive volcanic eruptions during the late Permian and, to a much lesser extent, during the Early Triassic, allowing high‐resolution age determination on the numerous tuff horizons. Palaeobotanical and radiogenic isotope data indicate that the end‐Permian Extinction occurs at the top of the uppermost coal bed, and the Permo‐Triassic boundary either within an immediately overlying mudrock succession or within a succeeding channel sandstone body, depending on locality due to lateral variation. Late Permian depositional environments were initially (during the Wuchiapingian) shallow marine and deltaic, but coastal plain fluvial environments with extensive coal‐forming mires became progressively established during the early late Permian, reflected in numerous preserved coal seams. The fluvial style of coastal plain channel deposits varies geographically. However, apart from the loss of peat‐forming mires, no significant long‐term change in depositional style (grain size, sediment‐body architecture, or sediment dispersal direction) was noted across the end‐Permian Extinction (pinpointed by turnover of the palaeoflora). There is no evidence for immediate aridification across the boundary despite a loss of coal from these successions. Rather, the end‐Permian Extinction marks the base of a long‐term, progressive trend towards better‐drained alluvial conditions into the Early Triassic. Indeed, the floral turnover was immediately followed by a flooding event in basinal depocentres, following which fluvial systems similar to those active prior to the end‐Permian Extinction were re‐established. The age of the floral extinction is constrained to 252.54 ± 0.08 to 252.10 ± 0.06 Ma by a suite of new Chemical Abrasion Isotope Dilution Thermal Ionization Mass Spectrometry U‐Pb ages on zircon grains. Another new age indicates that the return to fluvial sedimentation similar to that before the end‐Permian Extinction occurred in the basal Triassic (prior to 251.51 ± 0.14 Ma). The character of the surface separating coal‐bearing pre‐end‐Permian Extinction from coal‐barren post‐end‐Permian Extinction strata varies across the basins. In basin‐central locations, the contact varies from disconformable, where a fluvial channel body has cut down to the level of the top coal, to conformable where the top coal is overlain by mudrocks and interbedded sandstone–siltstone facies. In basin‐marginal locations, however, the contact is a pronounced erosional disconformity with coarse‐grained alluvial facies overlying older Permian rocks. There is no evidence that the contact is everywhere a disconformity or unconformity.