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LLM - Digital Humanities 16

ERROR: type should be string, got "https://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n1\n\nValidating Plutonium-239+240 as novel soil redistribution tracer - a\n\n2\n\ncomparison to measured sediment yield\n\n3\n\nKatrin Meusburger1*, Paolo Porto2, Judith Kobler Waldis3, Christine Alewell3\n\n4\n5\n\n1\n\n6\n\nSwitzerland\n\n7\n\n2\n\n8\n\nItaly\n\n9\n\n3\n\nSwiss Federal Institute for Forest, Snow and Landscape Research WSL, CH-8903, Birmensdorf,\n\nDipartimento di Agraria, Università degli Studi Mediterranea di Reggio Calabria, Reggio Calabria,\n\nEnvironmental Geosciences, University of Basel, Switzerland\n\n10\n11\n\n*corresponding author: katrin.meusburger@wsl.ch\n\n12\n\n1\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n13\n\nAbstract\n\n14\n\nQuantifying soil redistribution rates is a global challenge addressed with direct sediment measurements\n\n15\n\n(e.g., traps), models and isotopic, geochemical and radiogenic tracers. The isotope of Plutonium, namely\n\n16\n\nPu-239+240, is a relatively new soil redistribution tracer in this challenge. Direct validation of Pu-\n\n17\n\n239+240 as soil redistribution is, however, still missing. We used a unique sediment yield time series\n\n18\n\nin Southern Italy, reaching back to the initial fallout of Pu-239+240 to verify Pu-239+240 as a soil\n\n19\n\nredistribution tracer. Distributed soil samples (n=55) were collected in the catchment, and at potential\n\n20\n\nundisturbed reference sites (n=22), Pu-239+240 was extracted, measured with ICP-MS and converted\n\n21\n\nto soil redistribution rates. Finally, we used a Generalized Additive model (GAM) to regionalize soil\n\n22\n\nredistribution estimates for the catchment. For the catchment sites, mean Pu-239+240 inventories were\n\n23\n\nsignificantly reduced (16.8 ± 10.2 Bq m-2) compared to the reference inventory (40.5 ± 3.5 Bq m-2,)\n\n24\n\nindicating the dominance of erosion. Converting these inventory losses into soil erosion rates resulted\n\n25\n\nin an average soil loss of 22.2 ± SD 7.2 t ha-1 yr-1. The uncertainties of the approach stemmed mainly\n\n26\n\nfrom the high measurement uncertainties of low-activity samples where samples have been bulked over\n\n27\n\ndepth. Therefore, we recommend taking incremental soil samples and extracting ~20g of soil. The\n\n28\n\ngeographic coordinates and the flow accumulation best described the spatial pattern of erosion rates in\n\n29\n\nthe GAM model. Using those predictors to upscale Pu-derived soil redistribution rates for the entire\n\n30\n\ncatchment resulted in an average on-site loss of 20.7 t ha-1 yr-1, which corresponds very well to the long-\n\n31\n\nterm average sediment yield of 18.7 t ha-1 yr-1 measured at the catchment outlet and to Cs-137 derived\n\n32\n\nsoil redistribution rates. Overall, this comparison of Pu-derived soil redistribution rates with measured\n\n33\n\nsediment yield data validates Pu-239+240 as a suitable retrospective soil redistribution tracer.\n\n34\n\nGraphical abstract\n\n2\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n35\n36\n\n3\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n37\n\n1\n\nIntroduction\n\n38\n\nSoil erosion endangers climate and food security and has considerable adverse off-site effects on\n\n39\n\nfreshwater systems (Reichstein et al., 2013; Amundson et al., 2015; Alewell et al., 2016; Panagos et al.,\n\n40\n\n2016; Borrelli et al., 2017; Alewell et al., 2020). Plutonium isotopes, with their previous hazardous\n\n41\n\nimpacts on the environment and released as a product of thermonuclear weapons testing and from\n\n42\n\nnuclear accidents (e.g. Chernobyl), may serve as a tool to quantify long-term soil loss (Alewell et al.,\n\n43\n\n2017).\n\n44\n\nThe approach to use Pu-239+240 as soil and sediment tracer is parallel to other fallout radionuclides\n\n45\n\n(FRN) (Xu et al., 2015; Meusburger et al., 2018). Once deposited on the ground, FRNs strongly bind\n\n46\n\nto soil particles and move across the landscape primarily through physical soil redistribution processes\n\n47\n\n(IAEA, 2014). In this way, fallout radionuclides provide an effective and retrospective (since the time\n\n48\n\nof the fallout) track of net soil and sediment redistribution (Zapata, 2003). However, Cs-137, the most\n\n49\n\ncommonly applied soil redistribution tracer, will reach its detection limit soon due to the successive\n\n50\n\ndecay (half-life = 30.17 years). Thus, alternative tracers like excess Pb-210 and Pu-239+240 have been\n\n51\n\nexplored (Wallbrink and Murray, 1996; Matisoff et al., 2002; Mabit et al., 2008; Kato et al., 2010; Porto\n\n52\n\net al., 2013; Teramage et al., 2015; Xu et al., 2015; Meusburger et al., 2018). While Pb-210 is associated\n\n53\n\nwith high uncertainties (Porto and Walling, 2012; Mabit et al., 2014; Meusburger et al., 2018), the\n\n54\n\ncharacteristics of Pu-239+240 seem more promising for soil tracing (Alewell et al., 2017).\n\n55\n\nThe advent of Pu-239+240 as a soil redistribution tracer was accelerated by the adoption of the less\n\n56\n\ntime-consuming (minutes instead of hours per sample) Inductively Coupled Plasma Mass spectrometry\n\n57\n\n(ICP-MS). It was a door opener for using Pu-239+240 as a soil erosion tracer. The application of Pu-\n\n58\n\n239+240 comes along with other advantages, such as i) reduced initial spatial variability at undisturbed,\n\n59\n\nso-called reference sites (Alewell et al., 2014; Meusburger et al., 2016), ii) less preferential uptake by\n\n60\n\nplants (Froehlich et al., 2016), iii) the possibility to assess the origin of the fallout by determining 240Pu\n\n61\n\nto\n\n62\n\nMeusburger et al., 2016; Meusburger et al., 2020), iv) considerably smaller soil sample volume needed\n\n63\n\nfor analysis, and v) no decline due to decay, which is of particular relevance for locations with low\n\n64\n\ninitial Cs-137 fallout such as the southern hemisphere (Tims et al., 2010). The potential of Pu-239+240\n\n65\n\nfurther convenes with the availability of the new conversion model \"Modelling Deposition and Erosion\n\n66\n\nrates with RadioNuclides (MODERN)\", suitable for estimating soil redistribution rates by comparing\n\n67\n\nreference with soil redistribution affected inventories with any FRN (Arata et al., 2016a; Arata et al.,\n\n68\n\n2016b).\n\n69\n\nSeveral studies (Schimmack et al., 2001; Tims et al., 2010; Hoo et al., 2011; Lal et al., 2013; Michelotti\n\n70\n\net al., 2013; Xu et al., 2013; Xu et al., 2015; Meusburger et al., 2018) have highlighted\n\n239\n\nPu atom ratios or Cs-137 to Pu-239+240 activity ratios (Ketterer et al., 2004; Xu et al., 2013;\n\n239+240\n\nPu's\n\n71\n\nsuitability as a soil redistribution tracer. However, to date, direct validation efforts to compare on-site\n\n72\n\nFRN-based soil erosion rates with off-site sediment yields have focused on other FRNs such as Cs-137\n4\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n73\n\nand excess 210Pb (Porto et al., 2001; Porto et al., 2003; Porto and Walling, 2012; Porto and Callegari,\n\n74\n\n2022). For 239+240Pu-derived soil redistribution rates, such a direct validation is not achieved yet, to the\n\n75\n\nbest of our knowledge. This study aims to fill this gap by validating 239+240Pu-derived soil redistribution\n\n76\n\nrates with a long-term time series of measured catchment suspended sediment yields.\n\n77\n\n2\n\n78\n\n2.1\n\nMaterials and Methods\nStudy site and soil sampling\n\n79\n\nThis study takes advantage of a unique long-term sediment yield monitoring catchment (W2, 1.38 ha)\n\n80\n\nlocated near Crotone in Calabria, Southern Italy (35 m a.s.l., 39°09′02″N, 17°08′10″E). The steep\n\n81\n\ncatchment with a mean average slope of ca. 35% is located in the ephemeral headwaters of the larger\n\n82\n\nCrepacuore basin (Fig. 1). The geology of this area consists of Upper Pliocene and Quaternary materials\n\n83\n\nand produced soils with a clay loam texture with 14.6%, 49.2%, and 36.2% of sand, silt, and clay,\n\n84\n\nrespectively. The catchment was never ploughed, but in 1968, Eucalyptus occidentalis Engl. was\n\n85\n\nplanted and cut again in 1978 and 1990. The tree cover is partly patchy, with about 20% of the area on\n\n86\n\nsouth-facing slopes having discontinuous tree and grass cover. The climate is Mediterranean, with a\n\n87\n\nmean annual precipitation of ~670 mm, predominantly occurring from October to March.\n\n5\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n88\n89\n90\n\nFig. 1 Location of the studied headwater catchment W2 within the Crepacuore Basin (lower panel\nindicated by a red dot), Calabria, Italy.\n\n91\n\nIn 2014, the collection of soil samples in the catchment was undertaken along an approximate 20 m ×\n\n92\n\n20 m grid with additional cores collected from areas characterized by marked variability of vegetation\n\n93\n\ncover or topography (Fig. 1). The samples were taken with a steel core tube (10 cm diameter) driven\n\n94\n\ninto the ground to a depth of 15 cm by a motorized percussion corer and subsequently extracted using\n\n95\n\na hand-operated winch. For each sampling point, two cores were taken, and they were bulked before\n\n96\n\nanalysis. This procedure provided a total of 55 composite bulk cores over the catchment area.\n\n97\n\nIn March 2021, a new sampling campaign was undertaken to obtain information at the reference area\n\n98\n\nto establish the baseline for 239+240Pu in the area. In this case, three depth profiles and nineteen additional\n\n99\n\nbulk reference soil cores were collected in adjacent undisturbed rangeland with some scattered oaks\n\n100\n\n(Quercus pubescens) at a similar altitude to the study catchment (see Porto and Callegari, 2022). The\n\n101\n\nsamples were collected using the same sampling device consisting of a motorized soil column cylinder\n\n6\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n102\n\nauger set in which a core tube (60 cm in length) with a larger internal diameter (11 cm) is\n\n103\n\naccommodated. The three depth profiles were sectioned into increments of 2 cm and were analyzed\n\n104\n\nseparately for 137Cs and 239+240Pu content. Before radiometric analyses, all samples were dried and sieved\n\n105\n\nto <2 mm. In a previous study, the soil samples collected within the catchment were analyzed for Cs-\n\n106\n\n137 using high-resolution HPGe detectors available at the Agraria Department at the University\n\n107\n\nMediterranea of Reggio Calabria, Italy (Porto et al., 2014). Counting times for the samples collected\n\n108\n\nduring that campaign were ca. 80,000 s, providing a precision of ca. ±10% at the 95% confidence level.\n\n109\n\nThe reference samples of 2021 were also analyzed for Cs-137 with the same detector settings. All Cs-\n\n110\n\n137 measurements were decay corrected to 01.01.2014 and used to calculate Pu-239+240 to Cs-137\n\n111\n\nactivity ratios.\n\n112\n\n2.2\n\nExtraction of Pu-239+240 and mass spectrometry for atom ratio and concentration\nmeasurements\n\n113\n114\n\nAll samples (5-10g) were oven-dried at 105°C for 48 h, mechanically disaggregated and dry-sieved to\n\n115\n\nrecover the <2 mm fraction. First, a representative sub-sample of this fraction was spiked with ~ 0.005\n\n116\n\nBq of a\n\n117\n\novernight at 80 °C and separated from the leach solution using a Pu-selective TEVA resin (Ketterer et\n\n118\n\nal., 2011). The isotope dilution calculations determined the masses of\n\n119\n\nsample and then converted them into the summed Pu-239+240 activity. The analysis was done with a\n\n120\n\nThermo X7 quadrupole ICP-MS system at Universidad de Cádiz. Please refer to Meusburger et al.\n\n121\n\n(2020) for details on the instrument method.\n\n122\n\n2.3\n\n123\n\nThe total inventory (Bq m-2) of each bulk soil core was calculated as the product of the measured Pu-\n\n124\n\n239+240 activity (Bq kg-1) and the dry mass of the <2 mm fraction of the bulk core (kg), divided by the\n\n125\n\nsurface area associated with the soil core (m2). The inventories were converted into soil redistribution\n\n126\n\nrates using the Profile Distribution model PDM (Walling et al., 2002; Walling et al., 2014) and the\n\n127\n\nmodel Modelling Deposition and Erosion rates with RadioNuclides (MODERN (Arata et al., 2016a;\n\n128\n\nArata et al., 2016b)). The profile distribution model is commonly employed to interpret the shape of an\n\n129\n\nFRN along the soil profile. It assumes an exponential depth distribution, and the depth of soil removed\n\n130\n\nby erosion is estimated by comparing the reduction in the FRN inventory with that related to the\n\n131\n\nreference site (see Porto et al., 2003). MODERN aligns the sampling site's total inventory to the\n\n132\n\nmeasured shape of the reference site's depth profile to estimate the thickness of soil losses/gains. The\n\n133\n\nintersection along the soil profile represents the solution of the model. We accounted for the uncertainty\n\n134\n\nin the conversion procedure by running both conversion models 100 times, sampling from the reference\n\n135\n\nand the erosion inventory within the uncertainty bounds and for the PDM in addition to the shape factor\n\n242\n\nPu yield tracer (licensed solution from NIST). Next, Pu was leached with 16M nitric acid\n239\n\nPu and\n\n240\n\nPu present in the\n\nConversion of Pu-239+240 activities to soil redistribution rates\n\n7\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n136\n\nh0. The sampling was done from normal distributions, defined by the mean measured value and the\n\n137\n\nstandard deviations (SD): i) of the repeated ICP-MS measurements for the erosional sites, ii) of the\n\n138\n\nreplicate reference inventories, iii) of the three depth profiles for the h0 factor (Supplementary Figure\n\n139\n\n1).\n\n140\n\n2.4\n\n141\n\nSince 1978, precipitation, runoff and sediment yield have been measured in the W2 catchment (Cantore\n\n142\n\net al., 1994). Precipitation was recorded using a tipping bucket rain gauge, and runoff was measured at\n\n143\n\nthe outlet using an H-flume structure equipped with a mechanical stage recorder. Below the H-flume,\n\nSediment yield measurements\n\n144\n\nthe sediment load was measured with a Coshocton wheel sampler (Porto et al., 2003). Sediment yield\n\n145\n\ndata used in this analysis is related to the period from 1978 to 1994 (Cantore et al., 1994) and from 2006\n\n146\n\nto 2013 (Fig. 2). However, due to the malfunctioning of the sediment sampling equipment in the\n\n147\n\ncatchment during some events, direct measurements of total annual sediment yield values are not\n\n148\n\navailable for all years. To account for these missing years, the corresponding sediment output was\n\n149\n\nestimated using the Arnoldus Index, for which long-term observations are available from the station of\n\n150\n\nCrotone located ca. 10 km distant from the study catchment (see Capra et al., 2017). These estimates\n\n151\n\nwere then incorporated into the annual record of sediment yield (Fig. 2), and the sediment yield data\n\n152\n\nwas extrapolated to cover the period 1963–2013, corresponding to the period captured by Pu-239+240\n\n153\n\nderived soil redistribution assessments.\n\n8\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n154\n155\n156\n157\n158\n\nFig. 2 Measured (orange) and predicted (blue) annual sediment yield (t ha-1 yr-1) of the headwater\ncatchment W2 (a). Predictions of sediment yields are based on a significant relation to Arnoldus\nerosivity index. In 1968, Eucalyptus occidentalis Engl. was planted in the catchment that was harvested\nin 1978 (b) (photo by M. Raglione, from Avolio et al., (1980)) and a second time in 1990 (c).\n\n159\n\n2.5\n\nSpatial extrapolation of Pu-239+240 derived estimates\n\n160\n\nRegionalization of the point erosion estimates was done to compare the sediment yields measured at\n\n161\n\nthe catchment's outlet with Pu-derived sediment yields. Therefore, generalized additive models (GAM)\n\n162\n\nwere fitted to the measured erosion estimates. GAMs can account for nonlinear relationships by\n\n163\n\ncoefficients that can be expanded as smooth functions of covariates. The smooth terms were modelled\n9\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n164\n\nby splines, and geographic coordinates (x and y) were modelled as a 2d spline. To prevent overfitting,\n\n165\n\nwe used the restricted maximum likelihood (REML) method with the R package mgcv (Wood, 2006).\n\n166\n\nAs spatial covariates, elevation, slope, aspect, flow accumulation, and scarce, discontinuous tree cover\n\n167\n\n(as 0 and 1 categorical variables, see Fig. 1) were tested. These covariates were derived from a DEM\n\n168\n\nwith 3m spatial resolution using the terrain function from the raster package. Because of the small\n\n169\n\nsample size of 55 sites, only a maximum of three covariables could be added to the model. For cross-\n\n170\n\nvalidation (n=50) of the spatial prediction, the data were randomly split into 80% training and 20%\n\n171\n\ntesting data.\n\n172\n\n3\n\n173\n\n3.1\n\n174\n\nThe mean measured\n\n175\n\nThese atom ratios corresponded to the atom ratio found for the global fallout (Kelley et al., 1999) and\n\n176\n\nconfirmed global fallout as the sole source of Pu in the catchment.\n\n177\n\nThe three reference depth profiles Pu-239+240 activity at the reference site showed different shapes\n\n178\n\nwith soil depth (Supplementary Figure 1). While profile 2 displays the expected exponential decline\n\n179\n\nwith soil depth, profile 1 shows signs typically expected from erosional processes and profile 3 of\n\n180\n\ndepositional processes (Supplementary Figure 1). Therefore, only profile 2 was assessed to be suitable\n\n181\n\nfor extracting the shape of the depth distribution for the conversion procedure (Fig. 3a). The penetration\n\n182\n\ndepth of Pu-239+240 reached 205 kg m-2, corresponding to 26 cm soil depth (Fig. 3b). With an\n\n183\n\nexponential model fit of the PDM, we derived an h0 at 94 kg m-2, representing the point where half of\n\n184\n\nthe activity is stored. The mean Pu-239+240 reference inventory was estimated at 42.3+-3.5 Bq m-2.\n\n185\n\nThe fitted surface soil (0 cm) concentration was 0.45 Bq kg-1 (Fig. 3a).\n\nResults and Discussion\nPu-239+240 distribution at the reference sites\n240\n\nPu to\n\n239\n\nPu atom ratios at the reference and sampling sites were 0.179±0.03.\n\n10\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n186\n187\n188\n189\n190\n191\n\nFig. 3 (a) Pu-239+240 activity with soil mass depth measured at the reference site (selected profile 2).\nInv corresponds to the total inventory of the soil, and h0 to the shape factor of the exponential fit\n(orange). (b) Pu-239+240 activity with soil depth (cm). (c) Relation between Pu reference inventories\nand precipitation for studies in the Alps, Southern Germany (Schimmack et al., 2001; Alewell et al.,\n2014; Meusburger et al., 2018).\n\n192\n\nThe Pu-239+240 measurements of the 19 bulk reference soil cores showed a bimodal distribution with\n\n193\n\nsix high inventories clustering at a mean of 40.2 +- 4.4 Bq m-2 and 13 low inventories of 15.0 +- 2.8 Bq\n\n194\n\nm-2. The Pu-239+240 activities of the bulk soil cores with low inventories had values <0.043 Bq kg-1,\n\n195\n\nclose to the detection limit, and the standard deviation of replicate measurement of these samples was\n\n196\n\nhigh. To verify the plausibility of these low inventories, we calculated the Pu to Cs activity ratios. For\n\n197\n\nEuropean soil samples, the activity ratio of Pu to Cs (with Cs being decay corrected to 2014) is expected\n\n198\n\nbetween 81 and 24 (Meusburger et al., 2020). However, the low inventory bulk cores had mean Pu/Cs\n\n199\n\nratios of 156, which is clearly outside this range. A possible explanation for these very low Pu values\n\n200\n\nin the reference site might be due to the mixing and dilution of deeper layers with no Pu activity into\n\n201\n\nthe bulk reference soil cores. Therefore, these low reference bulk samples were removed from further\n\n202\n\nanalysis. Bulking of Pu samples causing a dilution of the Pu activity should be avoided, particularly in\n\n203\n\nareas of high erosion or low initial fallout (Wilken et al., 2021). Here, we were able to resolve the\n\n204\n\ndilution problem due to the availability of Cs-137 data, as the Cs-137 to Pu-239+240 activity ratios\n\n205\n\nwere valuable in identifying the suitability of the reference samples. The plausibility of the Pu inventory\n\n206\n\nwas further underpinned when the inventory was related to the mean annual precipitation of other\n\n207\n\npublished European studies (Fig. 3c). The few published Pu inventories in Europe (Schimmack et al.,\n\n208\n\n2001; Alewell et al., 2014; Meusburger et al., 2018) show a linear relation to mean annual precipitation\n\n209\n\nwith 77, 67, 58 Bq m-2 for 1650, 1450, 950 mm of rainfall. The high inventory of this study of 40.2 Bq\n\n210\n\nm-2 plots on the linear relation (Fig. 3c), while the low inventory of 15 Bq m-2 is below the expected\n11\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n211\n\namount given the catchment's mean annual precipitation. Taking the depth distribution reference and\n\n212\n\nonly the six high inventories of bulk soil cores into account, the mean reference inventory of the soil\n\n213\n\nprofiles was 40.5 +- 3.5 Bq m-2 with a coefficient of variation of 8.6%.\n\n214\n\nAll in all, following the above-described procedure, the Pu-239+240 reference inventories had a small\n\n215\n\nspatial variability with a CV of <9%. For Cs-137, the CV was 11.6% in the same reference area (see\n\n216\n\nPorto and Callegari, 2022). The spatial variability of Pu in reference sites was comparable to previous\n\n217\n\nstudies (Alewell et al., 2014; Meusburger et al., 2016).\n\n218\n\n3.2\n\n219\n\nThe Pu-239+240 activities at the sampling sites ranged from 0.001 to 0.143 Bq kg-1 with a mean of\n\n220\n\n0.066 Bq kg-1. The uncertainties of repeated ICP-MS measurements increase with decreasing activities\n\n221\n\nfrom the smallest SD of 0.0004 Bq kg-1 to the largest of 0.067 Bq kg-1 corresponding to <1% to larger\n\n222\n\n>100% of the measured activity with a median of 20%.\n\n223\n\nThe respective mean Pu-239+240 inventories for all 55 sites were 16.8 Bq m-2 with a spatial SD of\n\n224\n\n±10.2 Bq m-2, thus less than half of the reference inventory. Given the uncertainty bounds, all\n\n225\n\ninventories, except for four sites, were significantly smaller than the reference inventory, indicating soil\n\nCatchment inventories and soil redistribution rates at sampling points\n\n226\n\nerosion (Fig. 4a). One site close to the catchment outlet had a very high Pu-239+240 inventory of 111\n\n227\n\nBq m-2 exceeding the reference inventory by almost three times (Fig. 4a). The Pu-239+240 inventories\n\n228\n\nare significantly (p<0.001) correlated to the Cs-137 inventories with 24.7 times more Bq m-2 for Cs-\n\n229\n\n137 (Fig. 4b). The Cs/Pu activity ratios of the catchment sites were at the lower range of the plausible\n\n230\n\nfallout range (between 23.9 = global and 81.3 = Chernobyl) with a mean value of 24.7. The activity\n\n231\n\nratios are significantly (p<0.005) decreasing with decreasing erosion rates even though Rsq of the\n\n232\n\nregression is with 0.15 very low (Fig. 4c).\n\n233\n\nThis depletion in Cs-137 pointed towards a preferential loss of Cs-137 during soil loss. A possible\n\n234\n\nexplanation might be that Cs-137 is transported with different soil particles as Pu, which are more\n\n235\n\nsusceptible to soil erosion. It is known that Pu-239+240 exhibits a different sorption behaviour to soil\n\n236\n\nparticles compared to, e.g. Cs-137. Pu is mainly associated with organic matter and sesquioxides in\n\n237\n\naddition to clay particles, whereas Cs-137 is predominantly bound to the fine mineral clay fraction\n\n238\n\n(Lujaniene et al., 2002; Qiao et al., 2012; Meusburger et al., 2016; Xu et al., 2017). As a consequence,\n\n239\n\nPu-239+240 is more exchangeable and might more easily migrate downward in soils (Schimmack et\n\n240\n\nal., 2001; Meusburger et al., 2016). This different sorption behaviour may result in different depth\n\n241\n\ndistributions, which have important implications for its use as a soil erosion tracer, e.g. regarding the\n\n242\n\nconversion of measured FRN inventory changes into soil redistribution rates. Further, it may also have\n\n243\n\nimplications regarding interpreting Cs-137 to Pu-239+240 activity ratios that may be shifted outside the\n\n244\n\nexpected ranges at sites affected by soil redistribution.\n12\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n245\n\n246\n247\n248\n249\n250\n251\n252\n253\n\nFig. 4 (a) Pu-239+240 inventories with measurement errors in relation to sample ID (points) and the\nreference inventory (orange line with ribbon). (b) Relation between Pu-239+240 and Cs-137 inventories\n(error bars indicate the measurement error for Pu) with a linear trend line. (c) Activity ratio of Cs to Pu\nversus erosion rate. (d) Measured sediment yield at catchment outlet (Yield), Pu-derived erosion rates\nbased on measured inventories within the catchment (siteY) and as a mean of the repeated conversion\nresults (meanY), and mean of regionalized catchment Pu-derived erosion rates (predY). Orange points\nand text show the mean values of each approach.\n\n254\n\n3.3\n\n255\n\nComparison of Pu-239+240 derived soil redistribution rates and sediment yield of\nthe catchment\n\n256\n\nWe produced three sets of Pu-derived soil redistribution rates using i) direct conversion of the site\n\n257\n\ninventories (siteY) and ii) the average of 100 Monte Carlo conversion models per site generated by\n\n258\n\nsampling within the uncertainty ranges of all input parameters (meanY) and iii) regionalized estimates\n13\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n259\n\nfor the catchment (predY). For the point estimates will refer to these meanY in the following because\n\n260\n\nthe uncertainty related to the entire procedure is included in this second set of redistribution rates.\n\n261\n\nSoil redistribution rates were highly variable within the catchment (Fig. 5). The highest soil loss with\n\n262\n\n43 ± 20 t ha-1 yr-1 occurred in the upper part with patchy tree cover. Generally, the sites with scarce tree\n\n263\n\ncover and adjacent sites showed the highest soil erosion rates. Downslope and towards the outlet of the\n\n264\n\ncatchment, the erosion rates decrease. Close to the outlet, soil deposition of 18.7 ± 2.0 t ha-1 yr-1 was\n\n265\n\nobserved in one measurement point (W2_29). The deposition rate is, however, difficult to quantify\n\n266\n\nwithout knowledge of the respective soil source area or a Pu depth profile in the deposition site. The\n\n267\n\naverage of all measured site redistribution rates (siteY) indicated erosion of -22.2 t ha-1 yr-1 with a spatial\n\n268\n\nstandard deviation of ± 21.1 t ha-1 yr-1. On average, the standard deviation, derived from repeated Monte\n\n269\n\nCarlo conversions, of these redistribution rates were 7.2 t ha-1 yr-1, with a slightly lower median of the\n\n270\n\nstandard deviations of 4.2 t ha-1 yr-1 corresponding to a mean CV of 45% and a median CV of 36%.\n\n271\n\nGenerally, higher erosion estimates are subject to higher standard deviations resulting from higher\n\n272\n\nuncertainties for measuring low Pu activities. Excluding these measurement uncertainties from the\n\n273\n\nMonte Carlo conversion reduced the CV of the erosion estimates to mean and median CVs of 19% and\n\n274\n\n13%, respectively.\n\n275\n\nThe XY-coordinates, elevation, and flow accumulation best explained the spatial pattern of soil\n\n276\n\nredistribution rates. The deviance explained with these two spatial covariates was 56.7%, with lower\n\n277\n\naccuracy of 24% for the cross-validation procedure. The spatial pattern of the predicted soil\n\n278\n\nredistribution rates showed erosion in most of the catchment (Fig. 5). Only in grid cells with high flow\n\n279\n\naccumulation deposition occurred. The average redistribution rate from the grid cells (predY) amounted\n\n280\n\nto -20.7 t ha-1 yr-1 (Fig 4d). Given the measured sediment yield at the outlet (Yield) of -18.2 t ha-1 yr-1,\n\n281\n\nthis corresponds to a 14% overestimation of soil loss by the Pu method (Fig 4d). The sediment yield\n\n282\n\n(Yield) corresponds to the off-site net erosion over time while the Pu-derived rates (siteY, meanY and\n\n283\n\npredY) to the on-site erosion over space. Their correspondence indicates that most of the on-site eroded\n\n284\n\nsediments are delivered to the outlet of the stream channel within the considered period.\n\n14\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n285\n286\n287\n288\n\nFig. 5 Soil redistribution rates assessed with Pu-derived soil redistribution rates (points) and spatial\nprediction of soil redistribution rates based on these point rates using XY-coordinates, elevation and\nflow accumulation as spatial covariates.\n\n289\n\nThe Pu-derived soil erosion rates in the catchment were very high, with maximum values <-40 t ha-1 yr-\n\n290\n\n1\n\n291\n\nexceptional rainfall events (Porto et al., 2018; Porto et al., 2022). The sediment yield time series reveals\n\n292\n\nthat besides the rainfall erosivity, particularly the second harvest of eucalyptus trees (1990), triggered\n\n293\n\nsoil erosion. The soil conservation effect of the eucalyptus trees was also revealed by the lower Pu\n\n294\n\ninventory and, therefore, higher soil losses in the catchment area with scarce tree cover. The protective\n\n295\n\neffect of trees (Sorriso-Valvo et al., 1995; Zhou et al., 2002) and vegetation cover, in general, was also\n\n296\n\nfound in other studies and reviewed by Zuazo and Pleguezuelo (2009). Flow accumulation, a proxy for\n\n297\n\nrunoff concentration in a catchment, was an important predictor of soil erosion patterns. Interestingly,\n\n298\n\nthe relationship was negative with lower soil losses and higher chances for deposition with increasing\n\n299\n\nflow accumulation. A reason for this was likely the collinearity between decreasing slopes with\n\n300\n\nincreasing flow accumulation, reducing the sediment transport capacity (Xiao et al., 2017). Still, flow\n\n301\n\naccumulation performed better than alternative GAM models, including slope.\n\n302\n\nMean Pu-239+240-based mean soil redistribution rates were -20.7 t ha-1 yr-1 and 14% higher as\n\n303\n\nmeasured sediment yields at the catchment outlet. Given both methods' uncertainties and variability,\n\n304\n\ncomparable magnitudes were achieved. In a recent study, Porto and Callegari (2022) found Cs-137\n\n305\n\nredistribution mean rates of -20.4 t ha-1 yr-1. The Cs-137 and Pu-239+240 derived soil redistribution\n\n306\n\nrates are in good agreement.\n\n. However, documented soil erosion peaks in this area can reach up to 100–150 t ha-1 yr-1 during\n\n15\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n307\n\n4\n\nConclusion\n\n308\n\nRecent measurements of Pu-239+240 in a catchment in Southern Italy provided essential insights into\n\n309\n\nthe suitability of the Pu-239+240 technique to estimate soil erosion rates. We also rigorously tested the\n\n310\n\nuncertainties involved in the approach. In our case study, the highest uncertainty resulted from the high\n\n311\n\nmeasurement uncertainty of low inventory samples, with a median CV of 21% and high measurement\n\n312\n\nuncertainty of <1% – 100%. This high uncertainty can, for future studies, be minimized by (i) taking\n\n313\n\nincremental soil depth samples, avoiding dilution with deeper horizons of low-activity soil and (ii)\n\n314\n\nextracting Pu on larger soil samples (~20g). Based on values with adequate measurement certainty, the\n\n315\n\nPu-239-240 technique showed a low spatial variability of the reference inventory (CV <9%) and the\n\n316\n\nshape of the Pu distribution within the soil profile proved stable adsorption to the topsoil. Patterns of\n\n317\n\ninventory loss were related to soil redistribution processes, with the best spatial predictors being tree\n\n318\n\ncover and flow accumulation. The Pu-assessed redistribution rates were in agreement with Cs-137-\n\n319\n\nderived rates and sediment yield measurements at the catchment outlet.\n\n320\n\nIncreasing climatic extremes associated with more intense farming practices endanger our soil\n\n321\n\nresources, and new tools to monitor soil losses are of utmost importance. So far, the tracer Cs-137 has\n\n322\n\nbeen a powerful approach to assess soil redistribution rates since its fallout. However, alternative tracers\n\n323\n\nare needed in light of the subsequent decay of Cs-137 approaching the detection limit. The Pu-239-240\n\n324\n\ntechnique works analogue to the Cs-137 technique. We conclude that Pu-239+240, with its considerably\n\n325\n\nlonger half-life, is a suitable and promising soil redistribution tracer.\n\n326\n\n16\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n327\n\nData availability\n\n328\n\nThe authors declare that all other data supporting the findings of this study are available within the\n\n329\n\narticle and its Supplementary Information files.\n\n330\n\nAcknowledgements\n\n331\n\nWe thank the University of Cadiz for the measurement of Pu-239+240 on the ICP-MS.\n\n332\n\nAuthor information\n\n333\n\nContributions\n\n334\n\nK.M., C.A, and P. P. conceptualized the study. P.P. collected the samples, J.K.-W. measured them and\n\n335\n\ncalculated the measurement uncertainties. K.M. and P.P. did the data analysis. K.M. wrote the\n\n336\n\nmanuscript, and all co-authors contributed to the writing process.\n\n337\n\nCompeting interests\n\n338\n\nThe authors declare no competing financial interests.\n\n339\n\n17\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n340\n\nAppendix\n\n341\n342\n343\n344\n345\n346\n\nFigure A1: Pu-239+240 activity with soil mass depth measured at three potential reference sites. Inv\ncorresponds to the total inventory of the soil, and h0 to the shape factor of the exponential fit (orange).\nProfile 3 was fitted with and without deposition layers. The standard deviation of the depth distribution\nand h0 factor of profiles 1, 2 and 3 (without deposition) was used for the uncertainty assessment in the\nconversion model.\n\n347\n\n18\n\n\fhttps://doi.org/10.5194/egusphere-2022-1359\nPreprint. Discussion started: 20 December 2022\nc Author(s) 2022. CC BY 4.0 License.\n\n348\n\nReferences\n\n349\n350\n351\n\nAlewell, C., Meusburger, K., Juretzko, G., Mabit, L., and Ketterer, M. 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