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Soil respiration that releases CO 2 into the atmosphere roughly balances the net primary productivity and varies widely in space and time. However, predicting its spatial variability, particularly in intensively managed landscapes, is challenging due to a lack of understanding of the roles of soil organic carbon (SOC) redistribution resulting from accelerated soil erosion. Here we simulate the heterotrophic carbon loss (HCL)—defined as microbial decomposition of SOC—with soil transport, SOC surface redistribution, and biogeochemical transformation in an agricultural field. The results show that accelerated soil erosion extends the spatial variation of the HCL, and the mechanical-mixing due to tillage further accentuates the contrast. The peak values of HCL occur in areas where soil transport rates are relatively small. Moreover, HCL has a strong correlation with the SOC redistribution rate rather than the soil transport rate. This work characterizes the roles of soil and SOC transport in restructuring the spatial variability of HCL at high spatio-temporal resolution.

Massive gully land consolidation projects, launched in China’s Loess Plateau, aim to restore 2667$$\mathrm{km}^2$$${\mathrm{km}}^2$agricultural lands in total by consolidating 2026 highly eroded gullies. This effort represents a social engineering project where the economic development and livelihood of the farming families are closely tied to the ability of these emergent landscapes to provide agricultural services. Whether these ‘time zero’ landscapes have the resilience to provide a sustainable soil condition such as soil organic carbon (SOC) content remains unknown. By studying two watersheds, one of which is a control site, we show that the consolidated gully serves as an enhanced carbon sink, where the magnitude of SOC increase rate (1.0$$\mathrm{g\,C}/\mathrm{m}^2/\mathrm{year}$$$gC/m^2/\mathrm{year}$) is about twice that of the SOC decrease rate (− 0.5$$\mathrm{g\,C}/\mathrm{m}^2/\mathrm{year}$$$gC/m^2/\mathrm{year}$) in the surrounding natural watershed. Over a 50-year co-evolution of landscape and SOC turnover, we find that the dominant mechanisms that determine the carbon cycling are different between the consolidated gully and natural watersheds. In natural watersheds, the flux of SOC transformation is mainly driven by the flux of SOC transport; but in the consolidated gully, the transport has little impact on the transformation. Furthermore, we find that extending the surface carbon residence time has the potential to efficiently enhance carbon sequestrationmore »from the atmosphere with a rate as high as 8$$\mathrm{g\,C}/\mathrm{m}^2/\mathrm{year}$$$gC/m^2/\mathrm{year}$compared to the current 0.4$$\mathrm{g\,C}/\mathrm{m}^2/\mathrm{year}$$$gC/m^2/\mathrm{year}$. The success for the completion of all gully consolidation would lead to as high as 26.67$$\mathrm{Gg\,C}/\mathrm{year}$$$\mathrm{Gg}C/\mathrm{year}$sequestrated into soils. This work, therefore, not only provides an assessment and guidance of the long-term sustainability of the ‘time zero’ landscapes but also a solution for sequestration$$\hbox {CO}_2$$${\text{CO}}_2$into soils.

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Evapotranspiration is arguably the least quantified component of the hydrologic cycle. We propose two complementary strategies for estimation of evapotranspiration rates and root water uptake profiles from soil‐moisture sensor‐array data. One is our implementation of ensemble Kalman filter (EnKF); it treats the evapotranspiration sink term in the Richards equation, rather than soil moisture, as the observable to update. The other is a maximum likelihood estimator (MLE) applied to the same observable; it is supplemented with the Fisher information matrix to quantify uncertainty in its predictions. We use numerical experiments to demonstrate the accuracy and computational efficiency of these techniques. We found our EnKF implementation to be two orders of magnitude faster than either the standard EnKF or MLE, and our MLE procedure to require an order of magnitude fewer iterations to converge than its counterpart applied to soil moisture. These findings render our methodologies a viable and practical tool for estimation of the root water uptake profiles and evaporation rates, with the MLE technique to be used when the prior knowledge about evapotranspiration at the site is elusive.

Soil organic carbon (SOC) is going through rapid reorganization due to anthropogenic influences. Understanding how biogeochemical transformation and erosion‐induced SOC redistribution influence SOC profiles and stocks is critical to our food security and adaptation to climate change. The important roles of erosion and deposition on SOC dynamics have drawn increasing attention in the past decades, but quantifying such dynamics is still challenging. Here we develop a process‐based quasi 3‐D model that couples surface runoff, soil moisture dynamics, biogeochemical transformation, and landscape evolution. We apply this model to a subcatchment in Iowa to understand how natural forcing and farming practices affect the SOC dynamics in the critical zone. The net soil thickness and SOC stock change rates are −0.336 (mm/yr) and −1.9 (g C/m²/year), respectively. Our model shows that in a fast transport landscape, SOC transport is the dominant control on SOC dynamics compared to biogeochemical transformation. The SOC profiles have “noses” below the surface at depositional sites, which are consistent with cores sampled at the same site. Generally, erosional sites are local net atmospheric carbon sinks and vice versa for depositional sites, but exceptions exist as seen in the simulation results. Furthermore, the mechanical soil mixing arising from tillage enhancesmore »SOC stock at erosional sites and reduces it at depositional ones. This study not only helps us understand the evolution of SOC stock and profiles in a watershed but can also serve as an instrument to develop practical means for protecting carbon loss due to human activities.

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