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Soil erosion in agricultural landscapes reduces crop yields, leads to loss of ecosystem services, and influences the global carbon cycle. Despite decades of soil erosion research, the magnitude of historical soil loss remains poorly quantified across large agricultural regions because preagricultural soil data are rare, and it is challenging to extrapolate local-scale erosion observations across time and space. Here we focus on the Corn Belt of the midwestern United States and use a remote-sensing method to map areas in agricultural fields that have no remaining organic carbon-rich A-horizon. We use satellite and LiDAR data to develop a relationship between A-horizon loss and topographic curvature and then use topographic data to scale-up soil loss predictions across 3.9 × 10⁵km²of the Corn Belt. Our results indicate that 35 ± 11% of the cultivated area has lost A-horizon soil and that prior estimates of soil degradation from soil survey-based methods have significantly underestimated A-horizon soil loss. Convex hilltops throughout the region are often completely denuded of A-horizon soil. The association between soil loss and convex topography indicates that tillage-induced erosion is an important driver of soil loss, yet tillage erosion is not simulated in models used to assess nationwide soil loss trends in the United States. We estimate that A-horizon loss decreases crop yields by 6 ± 2%, causing $2.8 ± $0.9 billion in annual economic losses. Regionally, we estimate 1.4 ± 0.5 Pg of carbon have been removed from hillslopes by erosion of the A-horizon, much of which likely remains buried in depositional areas within the fields.

 

The planform rearrangement of river basins is recognized as an important process for landscape evolution. The boundaries of river basins can shift either through gradual drainage divide migration or discrete river captures, but the methods for identifying these processes often rely on topographic evidence that remains otherwise untested. Moreover, efforts to understand the relative importance of either process are hampered by a lack of age constraints on river captures. We use¹⁰Be‐derived erosion rates to test whether, and how, divide motion is occurring at three locations along the Blue Ridge Escarpment in the Appalachian Mountains. In the Pee Dee River basin, we find that the escarpment is migrating inland up to 45 m/Myr, consistent with topographic evidence for gradual divide migration. In the Dan River basin, erosion rates support the topographic evidence for river capture, and we use a forward model of river incision to estimate that the capture likely occurred in the past 12.5 Myr. In the South Fork Roanoke River basin, where the presence of a knickzone has been interpreted as evidence that a river capture initiated a pulse of faster erosion, we instead measure nearly uniform tributary erosion rates above and within the mainstem knickzone. Simulations show that river incision into a more erodible layer of rock, with or without a river capture, could produce the observed topography and erosion rates in the South Fork Roanoke River. Our results show how multiple lines of evidence can illuminate the rates and mechanisms of river basin reorganization.

 

In May 2012, a sediment‐laden flood along the Seti Khola (= river) caused 72 fatalities and widespread devastation for > 40 km in Pokhara, Nepal's second largest city. The flood was the terminal phase of a hazard cascade that likely began with a major rock‐slope collapse in the Annapurna Massif upstream, followed by intermittent ponding of meltwater and subsequent outburst flooding. Similar hazard cascades have been reported in other mountain belts, but peak discharges for these events have rarely been quantified. We use two hydrodynamic models to simulate the extent and geomorphic impacts of the 2012 flood and attempt to reconstruct the likely water discharge linked to even larger medieval sediment pulses. The latter are reported to have deposited several cubic kilometres of sediment in the Pokhara Valley. The process behind these sediment pulses is debated. We traced evidence of aggradation along the Seti Khola during field surveys and from RapidEye satellite images. We use two steady‐state flood models, HEC‐RAS and ANUGA, and high‐resolution topographic data, to constrain the initial flood discharge with the lowest mismatch between observed and predicted flood extents. We explore the physically plausible range of simplified flood scenarios, from meteorological (1000 m³ s⁻¹) to cataclysmic outburst floods (600,000 m³ s⁻¹). We find that the 2012 flood most likely had a peak discharge of 3700 m³ s⁻¹in the upper Seti Khola and attenuated to 500 m³s⁻¹when arriving in Pokhara city. Simulations of larger outburst floods produce extensive backwater effects in tributary valleys that match with the locations of upstream‐dipping medieval‐age slackwater sediments in several tributaries of the Seti Khola. Our findings are consistent with the notion that the medieval sediment pulses were linked to outburst floods with peak discharges of >50,000 m³ s⁻¹, though discharge may have been an order of magnitude higher.

 

Cosmogenic nuclide surface exposure dating and erosion rate measurements in basaltic landscapes rely primarily on measurement of 3He in olivine or pyroxene. However, geochemical investigations using 3He have been impossible in the substantial fraction of basalts that lack separable olivine or pyroxene crystals, or where such crystals were present, but have been chemically weathered. Fine-textured basalts often contain small grains of ilmenite, a weathering-resistant mineral that is a target for cosmogenic 3He production with good He retention and straightforward mineral separation, but with a poorly constrained production rate. Here we empirically calibrate the cosmogenic 3He production rate in ilmenite by measuring 3He concentrations in basalts with fine-grained (~20 lm cross-section) ilmenite and co-existing pyroxene or olivine from the Columbia River and Snake River Plain basalt provinces in the western United States. The concentration ratio of ilmenite to pyroxene and olivine is 0.78 ± 0.02, yielding an apparent cosmogenic 3He production rate of 93.6 ± 7.7 atom g-1 yr-1 that is 20–30% greater than expected from prior theoretical and empirical estimates for compositionally similar minerals. The production rate discrepancy arises from the high energy with which cosmic ray spallation reactions emit tritium and 3He and the associated long stopping distances that cause them to redistribute within a rock. Fine-grained phases with low cosmogenic 3He production rates, like ilmenite, will have anomalously high production rates owing to net implantation of 3He from the surrounding, higher 3He production rate, matrix. Semi-quantitative modeling indicates implantation of spallation 3He increases with decreasing ilmenite grain size, leading to production rates that exceed those in a large grain by ~10% when grain radii are <150 lm. The modeling predicts that for the ilmenite grain size in our samples, implantation causes production rates to be ~20% greater than expected for a large grain, and within uncertainty resolves the discrepancy between our calibrated production rate, theory, and rates from previous work. The redistribution effect is maximized when the host rock and crystals differ substantially in mean atomic number, as they do between whole-rock basalt and ilmenite. 

Soil erosion diminishes agricultural productivity by driving the loss of soil organic carbon (SOC). The ability to predict SOC redistribution is important for guiding sustainable agricultural practices and determining the influence of soil erosion on the carbon cycle. Here, we develop a landscape evolution model that couples soil mixing and transport to predict soil loss and SOC patterns within agricultural fields. Our reduced complexity numerical model requires the specification of only two physical parameters: a plow mixing depth,L_p, and a hillslope diffusion coefficient,D. Using topography as an input, the model predicts spatial patterns of surficial SOC concentrations and complex 3D SOC pedostratigraphy. We use soil cores from native prairies to determine initial SOC‐depth relations and the spatial pattern of remote sensing‐derived SOC in adjacent agricultural fields to evaluate the model predictions. The model reproduces spatial patterns of soil loss comparable to those observed in satellite images. Our results indicate that the distribution of soil erosion and SOC in agricultural fields can be predicted using a simple geomorphic model where hillslope diffusion plays a dominant role. Such predictions can aid estimates of carbon burial and evaluate the potential for future soil loss in agricultural landscapes.