A Simplified Equation for Modeling Sediment Transport Capacity

Sediment transport capacity for shallow overland flow was represented as a quadratic function of downslope distance using the assumption of a linear increase in overland flow discharge with downslope distance and an approximation to the Yalin equation for sediment transport capacity. The simplified equation for sediment transport applies to complex topography having uniform soil and management characteristics. The simplified equation accurately approximated the Yalin equation when calibrated using the average of the hydraulic shear stresses at the end of a constant slope reference profile and the end of the actual profile. The simplified equation is useful in deriving closed-form solutions to the governing erosion equations for steady state conditions and reduces the computational time when numerical solutions are required

A Simplified Equation for Modeling Sediment Transport Capacity

Sediment transport capacity for shallow overland flow was represented as a quadratic function of downslope distance using the assumption of a linear increase in overland flow discharge with downslope distance and an approximation to the Yalin equation for sediment transport capacity. The simplified equation for sediment transport applies to complex topography having uniform soil and management characteristics. The simplified equation accurately approximated the Yalin equation when calibrated using the average of the hydraulic shear stresses at the end of a constant slope reference profile and the end of the actual profile. The simplified equation is useful in deriving closed-form solutions to the governing erosion equations for steady state conditions and reduces the computational time when numerical solutions are required

A ranking of hydrological signatures based on their predictability in space

Hydrological signatures are now used for a wide range of purposes, including catchment classification, process exploration and hydrological model calibration. The recent boost in the popularity and number of signatures has however not been accompanied by the development of clear guidance on signature selection. Here we propose that exploring the predictability of signatures in space provides important insights into their drivers, their sensitivity to data uncertainties, and is hence useful for signature selection. We use three complementary approaches to compare and rank 15 commonly‐used signatures, which we evaluate in 671 US catchments from the CAMELS data set (Catchment Attributes and MEteorology for Large‐sample Studies). Firstly, we employ machine learning (random forests) to explore how attributes characterizing the climatic conditions, topography, land cover, soil and geology influence (or not) the signatures. Secondly, we use simulations of a conceptual hydrological model (Sacramento) to benchmark the random forest predictions. Thirdly, we take advantage of the large sample of CAMELS catchments to characterize the spatial auto‐correlation (using Moran's I) of the signature field. These three approaches lead to remarkably similar rankings of the signatures. We show i) that signatures with the noisiest spatial pattern tend to be poorly captured by hydrological simulations, ii) that their relationship to catchments attributes are elusive (in particular they are not correlated to climatic indices) and iii) that they are particularly sensitive to discharge uncertainties. We suggest that a better understanding of their drivers and better characterization of their uncertainties would increase their value in hydrological studies

Impact of an Extreme Storm Event on River Corridor Bank Erosion and Phosphorus Mobilization in a Mountainous Watershed in the Northeastern United States

Movement of sediment, and associated phosphorus, from stream banks to freshwater lakes is predicted to increase with greater frequency of extreme precipitation events. This higher phosphorus load may accelerate harmful algal blooms in affected water bodies, such as Lake Champlain in Vermont, New York, and Québec. In the Mad River, a subwatershed in central Vermont\u27s Lake Champlain Basin, extreme flooding from Tropical Storm Irene in 2011 caused extensive erosion. We measured stream channel change along the main stem between 2008 and 2011 by digitizing available prestorm and poststorm aerial imagery. Soils were sampled post Irene at six active stream erosion sites, using an experimental design to measure differences in soil texture and phosphorus both with depth (90 cm) and distance from the stream. In addition to total phosphorus (TP), we determined bioavailable (soil test) phosphorus (STP) and the degree of phosphorus saturation (DPS). The six sites represented a 0.87-km length of stream bank that contributed an estimated 17.6 × 10 3 Mg of sediment and 15.8 Mg of TP, roughly the same as average annual watershed export estimates. At four sites, the STP and DPS were low and suggested little potential for short-term phosphorus release. At two agricultural sites where the lateral extent of erosion was high, imagery showed a clear loss of well-established riparian buffer. Present-day near-stream soils were elevated in STP and DPS. An increase in these extreme events will clearly increase sediment loads. There will also be increasing concentration of sediment phosphorus if stream banks continue to erode into actively managed agricultural fields

The water balance components of undisturbed tropical woodlands in the Brazilian cerrado

Deforestation of the Brazilian cerrado region has caused major changes in hydrological processes. These changes in water balance components are still poorly understood but are important for making land management decisions in this region. To better understand pre-deforestation conditions, we determined the main components of the water balance for an undisturbed tropical woodland classified as "cerrado sensu stricto denso". We developed an empirical model to estimate actual evapotranspiration (ET) by using flux tower measurements and vegetation conditions inferred from the enhanced vegetation index and reference evapotranspiration. Canopy interception, throughfall, stemflow, surface runoff, and water table level were assessed from ground measurements. We used data from two cerrado sites, Pé de Gigante (PDG) and Instituto Arruda Botelho (IAB). Flux tower data from the PDG site collected from 2001 to 2003 were used to develop the empirical model to estimate ET. The other hydrological processes were measured at the field scale between 2011 and 2014 at the IAB site. The empirical model showed significant agreement (<i>R</i>² = 0.73) with observed ET at the daily timescale. The average values of estimated ET at the IAB site ranged from 1.91 to 2.60 mm day⁻¹ for the dry and wet seasons, respectively. Canopy interception ranged from 4 to 20 % and stemflow values were approximately 1 % of the gross precipitation. The average runoff coefficient was less than 1 %, while cerrado deforestation has the potential to increase that amount up to 20-fold. As relatively little excess water runs off (either by surface water or groundwater), the water storage may be estimated by the difference between precipitation and evapotranspiration. Our results provide benchmark values of water balance dynamics in the undisturbed cerrado that will be useful to evaluate past and future land-cover and land-use changes for this region

Atrial septum fat deposition and atrial anatomy assessed by cardiac magnetic resonance: relationship to atrial electrophysiology

To assess the prevalence of fat deposition in the atrial septum with and its relationship with 12-lead electrocardiogram (ECG) atrial parameters (PR interval, P wave duration) and the presence of atrial fibrillation

Estimating Conservation Needs for Rangelands Using USDA National Resources Inventory Assessments

This study presents (1) the overall concept of assessing non-federal western rangeland soil loss rates at a national scale for determining areas of vulnerability for accelerated soil loss using USDA Natural Resources Conservation Service (NRCS) National Resources Inventory (NRI) data and the Rangeland Hydrology and Erosion Model (RHEM) and (2) the evaluation of a risk-based vulnerability approach as an alternative to the conventional average annual soil loss tolerance (T) for assessment of rangeland sustainability. RHEM was used to estimate runoff and soil loss at the hillslope scale for over 10,000 NRCS NRI sample points in 17 western states on non-federal rangelands. The national average annual soil loss rate on non-federal rangeland is estimated to be 1.4 ton ha⁻¹ year⁻¹. Nationally, 20% of non-federal rangelands generate more than 50% of the average annual soil loss. Over 29.2 × 10⁶ ha (18%) of the non-federal rangelands might benefit from treatment to reduce 1559-1570 soil loss to below 2.2 ton ha⁻¹ year⁻¹. National average annual soil loss rates combine areas with low and accelerated soil loss. Evaluating data in this manner can misrepresent the magnitude of the soil loss problem on rangelands. Between 23% and 29% of U.S. non-federal rangelands are vulnerable to accelerated soil loss (≥ 2.2 ton ha⁻¹ event⁻¹) if assessed as a function of vulnerability to a runoff event with a return period of ≥ 25 years. The NRCS has not evaluated potential soil loss risk in national reports in the past, and adaptation of this technique will allow the USDA and its partners to be proactive in preventing accelerated soil loss on rangelands.Keywords: Soil erosion, Rangeland Hydrology and Erosion Model, Non-federal rangelands, Conservation Effects Assessment Project, Soil loss tolerance, Soil and water conservation, National resources inventor

Soil erosion modelling: A bibliometric analysis

Soil erosion can present a major threat to agriculture due to loss of soil, nutrients, and organic carbon. Therefore, soil erosion modelling is one of the steps used to plan suitable soil protection measures and detect erosion hotspots. A bibliometric analysis of this topic can reveal research patterns and soil erosion modelling characteristics that can help identify steps needed to enhance the research conducted in this field. Therefore, a detailed bibliometric analysis, including investigation of collaboration networks and citation patterns, should be conducted. The updated version of the Global Applications of Soil Erosion Modelling Tracker (GASEMT) database contains information about citation characteristics and publication type. Here, we investigated the impact of the number of authors, the publication type and the selected journal on the number of citations. Generalized boosted regression tree (BRT) modelling was used to evaluate the most relevant variables related to soil erosion modelling. Additionally, bibliometric networks were analysed and visualized. This study revealed that the selection of the soil erosion model has the largest impact on the number of publication citations, followed by the modelling scale and the publication\u27s CiteScore. Some of the other GASEMT database attributes such as model calibration and validation have negligible influence on the number of citations according to the BRT model. Although it is true that studies that conduct calibration, on average, received around 30% more citations, than studies where calibration was not performed. Moreover, the bibliographic coupling and citation networks show a clear continental pattern, although the co-authorship network does not show the same characteristics. Therefore, soil erosion modellers should conduct even more comprehensive review of past studies and focus not just on the research conducted in the same country or continent. Moreover, when evaluating soil erosion models, an additional focus should be given to field measurements, model calibration, performance assessment and uncertainty of modelling results. The results of this study indicate that these GASEMT database attributes had smaller impact on the number of citations, according to the BRT model, than anticipated, which could suggest that these attributes should be given additional attention by the soil erosion modelling community. This study provides a kind of bibliographic benchmark for soil erosion modelling research papers as modellers can estimate the influence of their paper

Soil erosion modelling: A global review and statistical analysis

To gain a better understanding of the global application of soil erosion prediction models, we comprehensivelyreviewed relevant peer-reviewed research literature on soil-erosion modelling published between 1994 and2017. We aimed to identify (i) the processes and models most frequently addressed in the literature, (ii) the re-gions within which models are primarily applied, (iii) the regions which remain unaddressed and why, and (iv)how frequently studies are conducted to validate/evaluate model outcomes relative to measured data. To per-form this task, we combined the collective knowledge of 67 soil-erosion scientists from 25 countries. Theresulting database, named‘Global Applications of Soil Erosion Modelling Tracker (GASEMT)’, includes 3030 indi-vidual modelling records from 126 countries, encompassing all continents (except Antarctica). Out of the 8471articles identified as potentially relevant, we reviewed 1697 appropriate articles and systematically evaluatedand transferred 42 relevant attributes into the database. This GASEMT database provides comprehensive insightsinto the state-of-the-art of soil- erosion models and model applications worldwide. This database intends to sup-port the upcoming country-based United Nations global soil-erosion assessment in addition to helping to informsoil erosion research priorities by building a foundation for future targeted, in-depth analyses. GASEMT is anopen-source database available to the entire user-community to develop research, rectify errors, andmakefutureexpansion

Surface Energy Budgets of Arctic Tundra During Growing Season

This study analyzed summer observations of diurnal and seasonal surface energy budgets across several monitoring sites within the Arctic tundra underlain by permafrost. In these areas, latent and sensible heat fluxes have comparable magnitudes, and ground heat flux enters the subsurface during short summer intervals of the growing period, leading to seasonal thaw. The maximum entropy production (MEP) model was tested as an input and parameter parsimonious model of surface heat fluxes for the simulation of energy budgets of these permafrost‐underlain environments. Using net radiation, surface temperature, and a single parameter characterizing the thermal inertia of the heat exchanging surface, the MEP model estimates latent, sensible, and ground heat fluxes that agree closely with observations at five sites for which detailed flux data are available. The MEP potential evapotranspiration model reproduces estimates of the Penman‐Monteith potential evapotranspiration model that requires at least five input meteorological variables (net radiation, ground heat flux, air temperature, air humidity, and wind speed) and empirical parameters of surface resistance. The potential and challenges of MEP model application in sparsely monitored areas of the Arctic are discussed, highlighting the need for accurate measurements and constraints of ground heat flux.Plain Language SummaryGrowing season latent and sensible heat fluxes are nearly equal over the Arctic permafrost tundra regions. Persistent ground heat flux into the subsurface layer leads to seasonal thaw of the top permafrost layer. The maximum energy production model accurately estimates the latent, sensible, and ground heat flux of the surface energy budget of the Arctic permafrost regions.Key PointThe MEP model is parsimonious and well suited to modeling surface energy budget in data‐sparse permafrost environmentsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150560/1/jgrd55584.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150560/2/jgrd55584_am.pd