Medium-term Time Scales Research Articles

Wind turbine gearbox multi-scale condition monitoring through operational data

Since wind is expected to play a crucial role on the worldwide electricity production scenario, the reliability of the turbines is attracting attention of both industry and academia. New techniques for efficient condition monitoring of key components can be fundamental to optimising the performance and maintenance of a large fleet of turbines. The gearbox and bearings are the most critical mechanical components as they are responsible for a large proportion of the downtime of a wind turbine over its lifetime. However, the monitoring of wind turbine gearboxes is challenging due to the non-stationary nature of the operation and the lack of noise-free vibration measurements. In the present work, a new approach for efficient long to short term monitoring of wind turbine gearboxes has been developed based on real data. An turbine drivetrain failure was used as a test case to develop a new approach based on the use of multi-scale data sources. On the one hand, SCADA (Supervisory Control And Data Acquisition) data were used for general monitoring of the condition of the machine component on long to medium term time scales, while on the other hand, high resolution, triggered event data collected by a CMS (Condition Monitoring System) were used to refine the diagnosis and prognosis of the fault on a shorter time scale. Even though triggered spot events are very difficult to manage, the results show that the use of multi-scale high resolution CMS data can be fast and useful in fault diagnosis to classify a target machine with a healthy reference one. In the present work, the one-class SVM (Support Vector Method) was used for novelty detection. The approach, when applied to all available time scales, can be very precise in detecting the faulty machine and can therefore be proposed as a fast detection approach requiring less data compared to the classical data-driven regression normal behaviour model developed with continuously available SCADA data.

Future of mobility in Jakarta Metropolitan Area: A Multi-Stakeholder scenario planning

The growth of the urban population and their mobility, added with the COVID-19 pandemic and its impacts, requires the capability to anticipate uncertainties. As a developing country, Indonesia has progressed with many developments in urban mobility, but at the same time, challenges still may affect its future, particularly in a metropolitan like Jakarta. Despite the widely understood challenges faced by the metropolitan, there has been limited understanding about its possible futures of mobility and the ways to go in its respective future. A multi-stakeholder scenario planning was used to develop future scenarios of urban mobility in Jakarta Metropolitan Area (JMA), utilizing stakeholders’ point of views regarding the driving forces and critical uncertainties that may shape the future of mobility to create action-oriented strategies to achieve the desired future. A medium-term time scale of ten years (2021–2030) was used to give viable and practical recommendations. Four scenarios were developed, which consisted of: 1) one seamless ecosystem, 2) the culture of public transportation, 3) the exclusive green community, and 4) the social dilemma of public versus private transportation, which emphasized the forms of mobility that would dominate in the next ten years. With implications of each scenario explained from several aspects, six efforts should be considered to direct the future of mobility in Jakarta Metropolitan Area: vehicle electrification, limitation of fossil fuel vehicles and broader use of public transportation, implementation of MaaS and TOD, commuters’ behavior changes with push and pull policies, and boosting funding for mobility facilities.

On the co-orbital asteroids in the solar system: medium-term timescale analysis of the quasi-coplanar objects

The focus of this work is the current distribution of asteroids in co-orbital motion with Venus, Earth and Jupiter, under a quasi-coplanar configuration and for a medium-term timescale of the order of 900 years. A co-orbital trajectory is a heliocentric orbit trapped in a 1:1 mean-motion resonance with a given planet. As such, to model it this work considers the Restricted Three-Body Problem in the planar circular case with the help of averaging techniques. The domain of each co-orbital regime, that is, the quasi-satellite motion, the horseshoe motion and the tadpole motion, can be neatly defined by means of an integrable model and a simple two-dimensional map, that is invariant with respect to the mass parameter of the planet, and turns out to be a remarkable tool to investigate the distribution of the co-orbitals objects of interest. The study is based on the data corresponding to the ephemerides computed by the JPL Horizons system for asteroids with a sufficient low orbital inclination with respect to the Sun–planet orbital plane. These objects are cataloged according to their current dynamics, together with the transitions that occur in the given time frame from a given type of co-orbital motion to another. The results provide a general catalog of co-orbital asteroids in the solar system, the first one to our knowledge, and an efficient mean to study transitions.

Coastal dune dynamics in embayed settings with sea-level rise – Examples from the exposed and macrotidal north coast of SW England

Coastal dune systems are natural forms of coastal defence, but are expected to exhibit increased erosion rates due to climate change impacts, notably sea-level rise and, potentially, increased storminess. This is especially the case in embayed coastal settings, i.e., where there are no significant sediment inputs into the beach/dune system from longshore sources. Dune development is closely linked to that of beaches that lie seaward, but their temporal dynamics tend to be asynchronous. So, whereas beaches are generally highly variable over a short- to medium-term (event–decadal) time scales, potentially obscuring a longer-term (decadal–centennial) sea-level signal, dunes display a low-pass filtered response which may contain a sea-level signal.In this study, we investigate the decadal-scale, inter-annual dynamics of 25 embayed coastal dune systems along the exposed and macrotidal north coast of SW England. We then compare the observed behaviour with that hindcasted from simple parametric models and forecast future dune retreat rates due to sea-level rise. We show that practically all exposed dune systems show retreat with a regionally-averaged retreat rate of the dune foot of 0.5 m yr−1. The majority of retreat occurred over a small number of especially energetic winters and it was found that dune retreat is not automatically linked to dune volumetric change. Many of the retreating dune systems display so called ‘dune roll-over’, characterised by removal of sediment from the dune face and deposition at the dune top. Observed dune retreat rates were 2–3 times larger than predicted using simple parametric retreat models forced by sea-level rise. This suggests that the retreat models are inappropriate and/or that sea-level rise in itself may be insufficient to explain the observed retreat and that increased winter storminess may be implicated.A key factor in driving dune retreat is considered to be the number of hours that waves reach the dune foot or the excess runup energy present at the dune foot elevation. Both sea-level rise and enhanced storminess will increase exposure of the dune foot to energetic wave action and this is expected to accelerate dune retreat rates in these settings. Application of parametric shoreline retreat models that account for the acceleration in rate of sea-level rise predicts c. 40 m of dune retreat by 2100 with a considerable range in retreat (20–75 m), resulting from uncertainty in model choice and parameterisation. Simply extrapolating the current dune retreat rate also results in c. 40 m of dune retreat by 2100, but this approach ignores the potential acceleration in dune retreat rate due to an increase in the rate of sea-level rise.The combination of analysis of multi-annual coastal dune morphological change along with application of dune retreat models can provide useful insights into future dune evolution for coastal planners and managers.

The price relationship between main-byproduct metals from a multiscale nonlinear Granger causality perspective

Basing on the relationship of joint production, we take lead-bismuth, lead-selenium, zinc-cadmium, and zinc-germanium as examples to study the nonlinear Granger causal relationship between the prices of main-byproduct metal pairs. The price relationship between the main metal and byproduct metal is nonlinear and varies with the time scales. Therefore, we use an Ensemble Empirical Modal Decomposition method (EEMD) to break down the price series of the main metals and byproduct metals into different frequency bands, and then test these different frequency bands for nonlinear Granger causality. The results show that a two-way nonlinear Granger causal relationship exists between the prices of the main metals and byproduct metals, and this nonlinear Granger causal relationship is reflected primarily in the short- and medium-term time scales. Moreover, the effect of the main metal price on the price of the byproduct metal is not as significant as previously thought, and the influence of the byproduct metal price on the main metal price has been previously underestimated.

Distilling actionable insights from big travel demand datasets for city planning

Working towards a more data-informed land use, amenities and infrastructure planning process, the Singapore Urban Redevelopment Authority (URA) harnesses big data and spatial analytics to deepen its understanding of urban activity and mobility patterns. Big travel demand datasets from public transport and ride-hailing services enable planners to observe mobility patterns at a high level of detail for large numbers of users, trips, and trip types. Since August 2018, the URA has been working with leading technology company and ride-hailing operator Grab to understand how daily commute patterns vary between existing and new transport modes, and how the volume of activities in each area evolves across different times of day. This paper describes the novel dataset and analytical techniques utilised to study the relationship between urban activity and mobility. It will also report how spatiotemporal characteristics of the urban environment, such as land use mix, location accessibility, and peak-hour travel demand, influence commutes by different modes in each area. By studying mobility over a range of travel modes, this method of analysis will provide city planners with richer insights to better assess infrastructure requirements for new developments. The findings are also useful for emerging transport providers, who can improve service delivery across short- and medium-term time scales.

Responses to the preparation of strong Kamchatka earth-quakes in the lithosphere–atmosphere–ionosphere system, based on new data from integrated ground and iono-spheric monitoring

The experience of short-term forecasting of Kamchatka earthquakes based on complex well measurements at the Petropavlovsk-Kamchatsky geody-namic polygon (PGP) shows that, as a rule, the preparation of strong Kamchatka earthquakes is fairly reliable in the medium-term time scale (months or years be-fore the earthquake). However the determination of the stage beginning imme-diately preceding an earthquake (weeks or days before the main event) is a very difficult task. At present time, the solution of this problem is largely associated with the involvement in the preparation of forecast conclusions of data from continuous monitoring of the ionosphere, carried out by ground-based means of vertical radiosonding and measurements of total electronic content (TEC) using the global navigation satellite system GLONASS and GPS. This is due to the fact that significant changes in a number of ionospheric parameters occur mainly 1-5 days before the Kamchatka earthquakes. The results of the compar-ison of the data of daily monitoring of the ionosphere, including information on TEC, with the data integrated downhole measurements showed a rather high correlation of occurrence of anomalies in the ionosphere before strong earth-quakes with changes in the complex parameters in borehole measurements. As one example, the report presents the results of ionospheric and borehole monitoring obtained in the time neighborhood of the strong (MW= 7.5) the earth-quake that occurred on March 25, 2020 in the area of the Northern Kurils. The results show a high correlation between changes in the specific electrical resis-tivity of the Geospace in the area of the PGP with variations in the TEC and the formation of a number of other anomalies in the ionosphere a few days be-fore the earthquake. These results indicate that it is possible to determine fairly reliably the beginning of the final stage of preparation for a strong earthquake. Currently, methods based on atmospheric parameters monitoring are used quite successfully for predictive estimates of the epicenter and magnitude of an earth-quake: the method of chemical potential corrections for measurements at an altitude of ∼ 100 m, as well as data from measurements of outgoing long-wave infrared radiation (OLR) at the level of the upper edge of clouds (heights of 10 -15 km).

Evaluation of Cross-Shore Profile Behavior in Medium-Term Timescales Using XBeach: A Case Study of Zarabad Fishery Harbor, Iran

Among the numerous problems that decrease the capability of a harbor in the country, seasonal sedimentation is identified as a major problem for many fishery harbors. In 2007, Zarabad Fishery Harbor conditions were also identified as critical due to the large volume of sand accumulation and consequent closure of its entrance. Numerical modeling of coastal bed level change was implemented to provide insight into the typical response of the Zarabad beach to regular wave attacks, and to obtain an operational and validated model for the site. Advanced numerical models employed to predict coastal evolution at a variety of time and spatial scales usually include many free parameters that require calibration to the available field data. The XBeach numerical model was selected for its capacity to accurately model hydrodynamic and morphological processes over a two-dimensional domain. It comprises about 250 model settings that approximately 150 of these settings relate to physical and numerical Behavior and the other 100 are case-specific parameters. In this research, 11 parameters are adopted to optimize the model prediction efficiency for Zarabad Fishery Harbor area. For calibration and validation stages, two cross-shore profiles and two medium-term time periods are selected. The model showed great promise in predicting the evolution of cross-shore profiles under water, but as expected, the dry part results showed major errors. XBeach proved to be an operational tool to predict cross-shore profiles in the area, in such timescales. Although, more tests are needed to utilize the model in longer time periods with regard to the duration of simulations.

Are We Doing ‘Systems’ Research? An Assessment of Methods for Climate Change Adaptation to Hydrohazards in a Complex World

Climate change is a product of the Anthropocene, and the human–nature system in which we live. Effective climate change adaptation requires that we acknowledge this complexity. Theoretical literature on sustainability transitions has highlighted this and called for deeper acknowledgment of systems complexity in our research practices. Are we heeding these calls for ‘systems’ research? We used hydrohazards (floods and droughts) as an example research area to explore this question. We first distilled existing challenges for complex human–nature systems into six central concepts: Uncertainty, multiple spatial scales, multiple time scales, multimethod approaches, human–nature dimensions, and interactions. We then performed a systematic assessment of 737 articles to examine patterns in what methods are used and how these cover the complexity concepts. In general, results showed that many papers do not reference any of the complexity concepts, and no existing approach addresses all six. We used the detailed results to guide advancement from theoretical calls for action to specific next steps. Future research priorities include the development of methods for consideration of multiple hazards; for the study of interactions, particularly in linking the short- to medium-term time scales; to reduce data-intensivity; and to better integrate bottom–up and top–down approaches in a way that connects local context with higher-level decision-making. Overall this paper serves to build a shared conceptualisation of human–nature system complexity, map current practice, and navigate a complexity-smart trajectory for future research.

Exploring the drivers of energy consumption-related CO2 emissions in China: a multiscale analysis

The exploration and modeling of the drivers of CO2 emissions can help make effective CO2 emission reduction policies. In this study, we examine the drivers of energy consumption-related CO2 emissions in China during 1978–2014 from a multiscale perspective. Firstly, we use the multivariate empirical mode decomposition model to simultaneously decompose the CO2 emissions and 17 drivers into several groups of intrinsic mode functions and one group of residues at different timescales. Secondly, we employ the stepwise regression analysis to explore and model the key drivers of CO2 emissions at different timescales without multicollinearity. The empirical results show that China’s CO2 emissions have obvious timescales of 6.17 years, 9.25 years, 18.5 years, 37.0 years, and long-term trend. At the short-term timescales, fuel structure and economic structure have significant impacts on CO2 emissions. At the medium-term timescales, urban population and fuel structure are the major contributors to CO2 emissions. At the long-term timescale, only per capita GDP has a positive effect on CO2 emissions. Finally, we propose the policy implications at the short, medium, and long timescales.

Dynamic Correlation and Risk Contagion Between “Black” Futures in China: A Multi-scale Variational Mode Decomposition Approach

This paper explores the dynamic correlation and risk contagion between “black” futures in China at various time horizons. We employ the DCC-GARCH-t model and Granger causality in risk test jointly with variational modal decomposition. Our study covers the period from October 2013, to January 2018. The paper’s three key findings are as follows: first, a positive dynamic correlation exists between “black” futures across most sample period at each time scale. Secondly, dynamic correlation differs between “black” futures, which is largest during the medium-term time scale. What’s more, the correlation of coking coal futures and coke futures is consistently higher than other pairs at each time scale. Thirdly, the direction and the time lag of risk contagion varies across different time scales. The complexity of contagion will increase as the length of the time scale increases. We have also discovered some synchronic contagions between “black” futures.

The relationship between regional natural gas markets and crude oil markets from a multi-scale nonlinear Granger causality perspective

This study first decomposes the daily returns of regional gas and crude oil at different time scales, using the ensemble empirical mode decomposition (EEMD) method. It then investigates the causality relationship between each pair of components at the different time scales, by employing the linear and nonlinear Granger causality tests. For the original returns series, this study finds that unidirectional linear Granger causality exists from crude oil markets to North American and European gas markets. However, for nonlinear characteristics, the crude oil and regional gas markets exhibit bidirectional nonlinear Granger causality. On the medium-term time scale, a bidirectional nonlinear spillover effect is found between the markets. The long-term trends for the markets suggest a significant linear relationship; however, no nonlinear spillover effect is found between the crude oil and regional gas markets.

The driving forces of landscape change in Europe: A systematic review of the evidence

Over the past decades, landscapes worldwide have experienced changes (e.g., urbanization, agricultural intensification, expansion of renewable energy uses) at magnitudes that put their sustainability at risk. The understanding of the drivers of these landscape changes remains challenging, partly because landscape research is spread across many domains and disciplines. We here provide a systematic synthesis of 144 studies that identify the proximate and underlying drivers of landscape change across Europe. First, we categorize how driving forces have been addressed and find that most studies consider medium-term time scales and local spatial scales. Most studies assessed only one case study area, one spatial scale, and less than four points in time. Second, we analyze geographical coverage of studies and reveal that countries with a non-European Union/European Free Trade Association membership; low Gross Domestic Product; boreal, steppic, and arctic landscapes; as well as forestland systems are underrepresented in the literature. Third, our review shows that land abandonment/extensification is the most prominent (62% of cases) among multiple proximate drivers of landscape change. Fourthly, we find that distinct combinations of mainly political/institutional, cultural, and natural/spatial underlying drivers are determining landscape change, rather than single key drivers. Our systematic review indicates knowledge gaps that can be filled by: (a) expanding the scope of studies to include underrepresented landscapes; (b) clarifying the identification and role of actors in landscape change; (c) deploying more robust tools and methods to quantitatively assess the causalities of landscape change; (d) setting up long-term studies that go beyond mapping land-cover change only; (e) strengthening cross-site and cross-country comparisons of landscape drivers; (f) designing multi-scale studies that consider teleconnections; (g) considering subtle and novel processes of landscape change.

A dataset of future daily weather data for crop modelling over Europe derived from climate change scenarios

Coupled atmosphere-ocean general circulation models (GCMs) simulate different realizations of possible future climates at global scale under contrasting scenarios of land-use and greenhouse gas emissions. Such data require several additional processing steps before it can be used to drive impact models. Spatial downscaling, typically by regional climate models (RCM), and bias-correction are two such steps that have already been addressed for Europe. Yet, the errors in resulting daily meteorological variables may be too large for specific model applications. Crop simulation models are particularly sensitive to these inconsistencies and thus require further processing of GCM-RCM outputs. Moreover, crop models are often run in a stochastic manner by using various plausible weather time series (often generated using stochastic weather generators) to represent climate time scale for a period of interest (e.g. 2000 ± 15 years), while GCM simulations typically provide a single time series for a given emission scenario. To inform agricultural policy-making, data on near- and medium-term decadal time scale is mostly requested, e.g. 2020 or 2030. Taking a sample of multiple years from these unique time series to represent time horizons in the near future is particularly problematic because selecting overlapping years may lead to spurious trends, creating artefacts in the results of the impact model simulations. This paper presents a database of consolidated and coherent future daily weather data for Europe that addresses these problems. Input data consist of daily temperature and precipitation from three dynamically downscaled and bias-corrected regional climate simulations of the IPCC A1B emission scenario created within the ENSEMBLES project. Solar radiation is estimated from temperature based on an auto-calibration procedure. Wind speed and relative air humidity are collected from historical series. From these variables, reference evapotranspiration and vapour pressure deficit are estimated ensuring consistency within daily records. The weather generator ClimGen is then used to create 30 synthetic years of all variables to characterize the time horizons of 2000, 2020 and 2030, which can readily be used for crop modelling studies.

Phonon creation by gravitational waves

We show that gravitational waves create phonons in a Bose–Einstein condensate (BEC). A traveling spacetime distortion produces particle creation resonances that correspond to the dynamical Casimir effect in a BEC phononic field contained in a cavity-type trap. We propose to use this effect to detect gravitational waves. The amplitude of the wave can be estimated applying recently developed relativistic quantum metrology techniques. We provide the optimal precision bound on the estimation of the waveʼs amplitude. Finally, we show that the parameter regime required to detect gravitational waves with this technique could be, in principle, within experimental reach in a medium-term timescale.

Redox interactions of technetium with iron-bearing minerals

AbstractIron minerals influence the environmental redox behaviour and mobility of metals including the long-lived radionuclide technetium. Technetium is highly mobile in its oxidized form pertechnetate (Tc(VII)O4–), however, when it is reduced to Tc(IV) it immobilizes readily via precipitation or sorption. In low concentration tracer experiments, and in higher concentration XAS experiments, pertechnetate was added to samples of biogenic and abiotically synthesized Fe(II)-bearing minerals (bio-magnetite, bio-vivianite, bio-siderite and an abiotically precipitated Fe(II) gel). Each mineral scavenged different quantities of Tc(VII) from solution with essentially complete removal in Fe(II)-gel and bio-magnetite systems and with 84±4% removal onto bio-siderite and 68±5% removal onto bio-vivianite over 45 days. In select, higher concentration, Tc XAS experiments, XANES spectra showed reductive precipitation to Tc(IV) in all samples. Furthermore, EXAFS spectra for bio-siderite, bio-vivianite and Fe(II)-gel showed that Tc(IV) was present as short range ordered hydrous Tc(IV)O2-like phases in the minerals and for some systems suggested possible incorporation in an octahedral coordination environment. Low concentration reoxidation experiments with air-, and in the case of the Fe(II) gel, nitrate-oxidation of the Tc(IV)-labelled samples resulted in only partial remobilization of Tc. Upon exposure to air, the Tc bound to the Fe-minerals was resistant to oxidative remobilization with a maximum of ∼15% Tc remobilized in the bio-vivianite system after 45 days of air exposure. Nitrate mediated oxidation of Fe(II)-gel inoculated with a stable consortium of nitrate-reducing, Fe(II)-oxidizing bacteria showed only 3.8±0.4% remobilization of reduced Tc(IV), again highlighting the recalcitrance of Tc(IV) to oxidative remobilization in Fe-bearing systems. The resultant XANES spectra of the reoxidized minerals showed Tc(IV)-like spectra in the reoxidized Fe-phases. Overall, this study highlights the role that Fe-bearing biogenic mineral phases have in controlling reductive scavenging of Tc(VII) to hydrous TcO2-like phases onto a range of Fe(II)-bearing minerals. In addition, it suggests that on reoxidation of these phases, Fe-bound Tc(IV) may be octahedrally coordinated and is largely recalcitrant to reoxidation over medium-term timescales. This has implications when considering remediation approaches and in predictions of the long-term fate of Tc in the nuclear legacy.

Six-qubit two-photon hyperentangled cluster states: Characterization and application to quantum computation

Six-qubit cluster states built on the simultaneous entanglement of two photons in three independent degrees of freedom, i.e. polarization and a double longitudinal momentum, have been recently demonstrated. We present here the peculiar entanglement properties of the linear cluster state $\LCtilde$ related to the three degrees of freedom. This state has been adopted to realize various kinds of Controlled NOT (CNOT) gates, obtaining in all the cases high values of the gate fidelity. Our results demonstrate that a number of qubits $\leq$10 in cluster states of two photons entangled in multiple degrees of freedom is achievable. Furthermore, these states represent a promising approach towards scalable quantum computation in a medium term time scale. The future perspectives of a hybrid approach to one-way quantum computing based on multi-degree of freedom and multi-photon cluster states are also discussed in the conclusions of this paper.

Applying a simple methodology to assess historical soil erosion in olive orchards

Although soil erosion is a well-known problem in olive orchards, causing both on-site soil degradation and off-site environmental pollution, quantitative field measurements of soil erosion are scarce. This situation has restrained the development of a reliable, predictive soil erosion model for this land use. This study applies a simple and inexpensive technique to measure soil losses in olive orchards over a medium-term time scale. The methodology is based on measuring the size of small mounds that form around individual trees. The resulting historical soil loss rate, averaged for seven sites and over a period between 55–100 years, was 95 Mg ha − 1 yr − 1 . Locally, the historical soil loss rate amounted up to 184 Mg ha − 1 yr − 1 . The measurement of actual erosion by water yielded a soil loss rate between 70–100 Mg ha − 1 yr − 1 . This difference illustrates the important contribution of tillage translocation. Our approach provides novel insights into the intensity and processes of soil erosion in olive orchards. It also provides valuable input for model calibration and validation.

Using Fallout Lead-210 Measurements to Estimate Soil Erosion in Three Small Catchments in Southern Italy

Soil erosion and associated off-site environmental impacts have attracted increasing attention in recent decades, and there is a growing need for reliable information on rates of soil loss. The potential for using 137Cs fallout to quantify rates and patterns of soil redistribution over medium-term timescales (ca. 45 years) has been successfully demonstrated in a wide range of environments around the world. The similar behaviour of fallout 210Pb in soils offers potential for its use as an alternative to 137Cs, in areas where 137Cs inventories are low or are complicated by additional fallout from the Chernobyl accident. There have, however, to date been few attempts to validate the use of fallout 210Pb measurements for assessing erosion rates. This paper reports an attempt to explore the use of fallout 210Pb to estimate rates of water-induced soil erosion on uncultivated land. It focuses on three small forest/rangeland catchments located in Calabria, southern Italy, for which measurements of sediment output are available. Comparison of the estimates of net soil loss from the catchments derived from 210Pb measurements with the measured sediment output, confirmed the validity of the 210Pb approach. The soil redistribution rates estimated using 210Pb measurements were also consistent with equivalent estimates obtained for the same study catchments using 137Cs measurements.

A preliminary assessment of the potential for using 210Pb ex measurement to estimate soil redistribution rates on cultivated slopes in the Sichuan Hilly Basin of China

In order to assess its potential for estimating soil redistribution rates, the naturally occurring fallout radionuclide 210Pb ex has been used in parallel with 137Cs, derived from the atmospheric testing of nuclear weapon testing in the 1950s to 1970s, to estimate rates of soil redistribution on a sloping field with traditional erosion control measures located near Jiajia Village, Jianyang County, in the Sichuan Hilly Basin of China. The local 210Pb ex reference inventory of 12,860 Bq m − 2 is higher than those reported for many other areas of the world and may reflect the influence of cloudy weather in preventing 210Pb released to the atmosphere across the local region moving up into the upper troposphere, where is would be more widely dispersed. The mean 210Pb ex and 137Cs inventories measured in cores collected from the upper part of the field with an average slope of 10° were 8028 Bq m − 2 and 993 Bq m − 2 , respectively, and the equivalent values for the lower part of the field, where the slopes are steeper (20°) were 11,388 Bq m − 2 and 1299 Bq m − 2 . The pattern of post-fallout 210Pb ex and 137Cs redistribution on the sloping field reflects not only the effects of water erosion and redistribution by tillage, but also the local traditional practice of “Tiaoshamiantu”, whereby sediment trapped in the ditches is returned to the fields by the farmer. The estimates of annual rates of soil loss provided by the 210Pb ex measurement are closely comparable with those derived from the 137Cs measurements and are consistent with existing knowledge for the study area. The results obtained from this study confirm the potential for using 210Pb ex measurement to estimate soil erosion rates over medium-term timescale of 50–100 years. By combining the estimates of erosion rates provided by the 210Pb ex and 137Cs measurements, the weighted mean net soil loss was estimated to be 48.7 t ha − 1 year − 1 from the upper subfield and 16.9 t ha − 1 year − 1 from the lower subfield. These rates are considerably lower than the erosion rates obtained from runoff plot measurements in the local area. It is suggested that the traditional erosion control practices and the practice of “Tiaoshamiantu” have a significant effect in reducing soil loss and conserving valuable cultivated soil on sloping fields in the Sichuan Hilly Basin.