Combined use of geochemistry and compound-specific stable isotopes for sediment fingerprinting and tracing.

Sediment fingerprinting has emerged as a valuable tool for elucidating soil erosion processes and assessing the sources of sediment and particle-bound chemicals. Due to its upward trend in popularity and the parallel advances in analytical methods, different types of tracers such as Compound-Specific Stable Isotopes (CSSIs) have been incorporated to identify the potential sources. However, the physical processes of CSSIs, usually characterised by the ratio of two stable isotopes, also depends on the isotopic content requiring specific fingerprinting models. For this reason, isotopic tracers have not been combined with classical tracers such as the elemental composition. In this context, we i) propose a simple physical model describing the mixing of isotopic tracers, ii) derive the conservative balance (CB) governing the isotopic ratio of the mixture, iii) demonstrate that previous models for isotopic tracers are approximations of the proposed formulation, and iv) obtain an exact transformation combining the isotopic ratio and the isotopic content into a virtual elemental tracer. The CB model was successfully validated and tested in three fingerprint datasets from published isotopic tracer studies, demonstrating the equivalence of the proposed transformation. Compared to previously reported methods, the CB has two advantages: the model enables the analysis of isotopic tracers using classical unmixing models and, at the same time, allows the combined use of isotopic and elemental tracers. Within the CB framework the Consensus and the Consistent Tracer Selection (CTS) methods can also be applied to isotopic tracers, which is critical for a correct fingerprinting analysis. The effect of combining both types of tracers is illustrated in a dataset composed of elemental and CSSI tracers. The results support its compatibility and reveal an increase in the discriminant capacity and better-defined results for the channel bank source when combining elemental and CSSI tracers.

Dating historical droughts from religious ceremonies, the international pro pluvia rogation database.

Climate proxy data are required for improved understanding of climate variability and change in the pre-instrumental period. We present the first international initiative to compile and share information on pro pluvia rogation ceremonies, which is a well-studied proxy of agricultural drought. Currently, the database has more than 3500 dates of celebration of rogation ceremonies, providing information for 153 locations across 11 countries spanning the period from 1333 to 1949. This product provides data for better understanding of the pre-instrumental drought variability, validating natural proxies and model simulations, and multi-proxy rainfall reconstructions, amongst other climatic exercises. The database is freely available and can be easily accessed and visualized via http://inpro.unizar.es/ .

A novel method for analysing consistency and unravelling multiple solutions in sediment fingerprinting.

Fingerprinting technique is a widely used tool to assess the sources of sediments and particle bound chemicals within a watershed, and the results obtained from unmixing models are becoming valuable data to support soil and water resources monitoring and conservation. Nowadays, numerous studies have used fingerprinting techniques to examine specific catchment management problems. Despite its shortcomings and the lack of standardization, the technique continues on an upward trend globally. This paper takes a new look at the utility of the mostly used tracer selection methods and their influence when using fingerprinting models. Furthermore, the increase in the analysis capabilities and the use of more tracers than n-1 tracers (where n is the number of sources) for unmixing leads to the possibility of mathematical inconsistency and the existence of multiple solutions in the analysis of a particular mixture, which is a possible source of errors that remains unexplored nowadays. Within the framework of these criteria, we have i) inspected if both types of models, Frequentist and Bayesian, are sensitive to tracers with erroneous information; ii) examined the most commonly used tracer selection methods; iii) tested the consistency and the existence of multiple solutions in over-determined systems and iv) devised a Consistent Tracer Selection (CTS) method to extract the solutions present in the dataset. The strength of this novel study lies in the valuable and useful tracer selection method that has been presented. Frequentist model such as FingerPro and a Bayesian model, MixSIAR, are implemented to test the method. Both models agreed on their solutions when selecting the tracers based on the new method, while both disagreed when selecting the tracers following previous methods. The new CTS method's ability to extract the multiple discriminant and consistent solutions inside fingerprinting datasets has no precedent in the literature.

Legacy of historic land cover changes on sediment provenance tracked with isotopic tracers in a Mediterranean agroforestry catchment.

A Compound Specific Stable Isotope (CSSI) sediment tracing approach is applied for the first time in a Mediterranean mountain agroforestry catchment subjected to intense land use changes in the past decades. Many Mediterranean mountain environments underwent conversion of rangelands into croplands during the previous centuries to increase agricultural production. Converted land has increased the risk of erosion and in some cases has led to loss of the entire fertile topsoil. After land abandonment the process was gradually reversed during the middle of the 20th century, allowing the recovery of natural land cover and reduction of soil erosion rates. The 13C abundance of long chain fatty acids was used as tracer to assess the contribution of soil under different vegetation covers in complex landscapes subjected to land use changes after land abandonment in a medium-sized Mediterranean catchment. A Bayesian mixing model (MixSIAR) was used for estimating the contribution of different land use types to suspended sediments. To this purpose, composite samples were collected over the four main land covers existing in the study area: cropland, Mediterranean forest, pine forest, scrubland, and two main geomorphic elements: highly disturbed areas such as exposed subsoil and channel banks. Suspended sediment traps were installed at three locations in the catchment to assess the variability of source contributions from the headwaters to the outlet of the catchment. At every sampling point three replicating traps integrated the suspended sediment per climatologic season during a one hydrological year. The fatty acids (FAs) content was significantly higher at the catchment outlet than at the headwaters. The δ13C signatures of the FAs were successful in discriminating between Mediterranean forest, scrubland, pine forest and both geomorphic elements. Overall, the model identified agricultural land as the largest contributing source for most of the sampled seasons. The inclusion of prior information with different informativeness produced variations in the model outputs and could represent an advantage as much as a disadvantage if priors are not used with caution and supported by robust evidence. The results of this study suggest that CSSI tracers are needed to correctly assess land use related sediment sources, while channel bank and subsoil contributions require geochemical tracers. The high agricultural apportionment despite its small coverage (16%) point out to the impact of human activities and the agriculture cycle on soil loss in these mountain agroforestry systems.

Variations in transport of suspended sediment and associated elements induced by rainfall and agricultural cycle in a Mediterranean agroforestry catchment.

Soil erosion and fine particle exports are two of the major concerns of soil nutrient loss and water quality decrease nowadays. In Mediterranean mountainous environments, agricultural practices during different cropland stages likely increase sediment supplies and the export of fertilisers and pesticides out into the drainage system. In this study, we attempt to evaluate the soil response to different agricultural practices implemented during the agricultural cycle by monitoring the bare soil cropland area through the use of remote sensing and applying the sediment fingerprinting technique together with the newly consensus-based tracer selection method. To this purpose, 128 source samples were distributed over the four main land use/land covers and geomorphic elements existing in the study area. To analyse the spatio-temporal variability of source contributions, three sampling stations were established along the catchment and collected during two hydrological years. The consensus method was used to show the individual messages of each tracer, revealing non-conservative and dissenting tracers, followed by a discriminant function analysis (DFA) to select the best set of tracers for each mixture. Overall, the unmixing model outputs displayed channel bank and agriculture as the main contributing sources for all the seasonal campaigns. Nevertheless, the agricultural contribution was higher during the periods when the soil surface in croplands had no plant cover protection. Certain elements such as As, Co, Li, Mn, Zn and 238U were above source ranges in the sediment mixtures. The enriched elements showed higher content in the sediment mixtures during sowing and after harvest periods. Besides, an enrichment of phosphorous during both agricultural practices periods points out to agricultural activities as the main cause of sediment and elements export to streams. Thus, in the subcatchment with less bare soil cropland area, the agriculture source contributed with the lowest percentages. Our results support the protection of croplands, especially in periods of vegetation cover absence to prevent the loss of fertile soil and the export of potential pollutants to downstream water bodies.

Geomorphological control of habitat distribution in an intermittent shallow saline lake, Gallocanta Lake, NE Spain.

The aim of the present study consists on the establishment of any relationship or interaction between geomorphological processes and vegetation/habitat distribution in an area with strong environmental gradients: an active saline lake in NE Spain. The resulting maps of the major geoforms and CORINE habitats within the lacustrine area were overlain to determine any significant relationships, taking into account the elevation derived from Lidar data. Whereas the geoforms resulted to have a roughly concentric distribution, the habitats appeared to be spread across different areas, and flooding frequency seemed not to be a determining factor in their altitudinal distribution. The correspondence matrix for geoforms and habitats underlined the coincidence between presently active morphodynamic units, flooding/salinity, and habitats typical of saline environments. Geomorphological units associated with the presently active shoreline dynamics host the habitats more typically related to frequent flooding and high salinity levels. The delay between geomorphological dynamics and vegetation changes, together with the opportunistic character of vegetation, promote the coexistence of different geomorphological processes and a great variety of plant communities and habitats. As a major conclusion, the present study provides a method through which a standard procedure may be set up to further determine the interaction between geomorphological processes and vegetation distribution, very useful for understanding vegetation patterns and conservation biodiversity, and the planning and managing of Natura 2000 sites.

Consensus ranking as a method to identify non-conservative and dissenting tracers in fingerprinting studies.

Soil erosion and fine particle transport are two of the major challenges in food security and water quality for the growing global population. Information of the areas prone to erosion is needed to prevent the release of pollutants and the loss of nutrients. Sediment fingerprinting is becoming a widely used tool to tackle this problem, allowing to identify the sources of sediments in a catchment. Methods in fingerprinting techniques are still under discussion with tracer selection at the centre of the debate. We propose a novel method, termed as consensus ranking (CR), that combines the predictions of single-tracer models to identify non-conservative tracers. In this context, a numerical procedure to quantify the predictions of individual tracers is first delivered. The scoring function to rank the tracers is based on several random debates between tracers in which the tracer that prevents consensus is discarded. Based on these results, a conservativeness index (CI) is presented along with a clustering method to identify groups of similar tracers. To illustrate the CI and CR procedures, an artificial mixture created with real soil to independently test the method is analysed. The results demonstrate the capability of our method to identify non-conservative tracers beyond the capability of currently used selection methods. Further, a real sediment sample from a Mediterranean mountain catchment is evaluated to emphasise its utility in complex natural environments. To test the utility of our method, it was decided to include the conservative and consensus-enforcing tracers extracted by this new approach with two different unmixing models. Furthermore, CR and CI procedures are displayed together with the most widespread statistical tests and the within-a-polygon approach used for tracer selection in fingerprinting studies. The new proposed method will enable the research community to homogenise results for replicability as well as allowing comparisons among study areas.

Fingerprinting changes in source contribution for evaluating soil response during an exceptional rainfall in Spanish pre-pyrenees.

In the Mediterranean region, floods are expected to increase as a result of climate change and knowledge of soil erosion hot spots during exceptional rainfalls is required to support mitigation measures. This study quantifies the main sediment sources during an exceptional rainfall event in 2012 (235 mm) at the outlet of two catchments located in NE Spain. To this purpose, suspended sediments were collected during the flood event, complemented with entrapped sediments in mat taken one year after the event. We used fingerprinting methodology and applied the FingerPro unmixing model to estimate the contribution from main sources. The selected tracers clearly distinguished agricultural, rangeland, subsoil and channel banks as the four potential sources in both catchments. In the Vandunchil catchment, the 8 time-integrated suspended sediment samples revealed changes in source contribution during the 2-h sampling sequence. There were relatively high contributions from rangeland, agriculture and subsoil at the beginning of the sampling, representing 30, 40 and 35% of the total source contributions, respectively. Our records captured the delivery of pulses of eroded surface soil transported by runoff with direct connectivity to the stream. The sequence was followed by a sharp increase in channel bank contribution (up to 90%) in comparison to the other sources, reflecting streambank erosion and landslide occurrence, which manifested during the flood. In contrast, in the La Reina catchment, agricultural soils contributed the most (65%) and, together with subsoils (32%), were the main sources. These results reflect the effect of the higher connectivity and slope gradient of these cultivated fields of the La Reina catchment in comparison with those of the Vandunchil catchment. We discuss the possibility of using different properties, such as radionuclides, geochemistry and magnetic measurements, as tracers to distinguish between potential sources during an exceptional event in upland Mediterranean catchments. Our results support the use of fingerprinting techniques to determine variations in source contribution and sediment provenance during flood events, as extreme rainfalls are main drivers of sediment mobilization and key factors in changing landscapes. This is essential in identifying vulnerable hot spots, in which early-stage interventions are needed, and for helping policy makers with management of soil and water resources.

Comparing catchment sediment fingerprinting procedures using an auto-evaluation approach with virtual sample mixtures.

Information on sediment sources in river catchments is required for effective sediment control strategies, to understand sediment, nutrient and pollutant transport, and for developing soil erosion management plans. Sediment fingerprinting procedures are employed to quantify sediment source contributions and have become a widely used tool. As fingerprinting procedures are naturally variable and locally dependant, there are different applications of the procedure. Here, the auto-evaluation of different fingerprinting procedures using virtual sample mixtures is proposed to support the selection of the fingerprinting procedure with the best capacity for source discrimination and apportionment. Surface samples from four land uses from a Central Spanish Pyrenean catchment were used i) as sources to generate the virtual sample mixtures and ii) to characterise the sources for the fingerprinting procedures. The auto-evaluation approach involved comparing fingerprinting procedures based on four optimum composite fingerprints selected by three statistical tests, three source characterisations (mean, median and corrected mean) and two types of objective functions for the mixing model. A total of 24 fingerprinting procedures were assessed by this new approach which were solved by Monte Carlo simulations and compared using the root mean squared error (RMSE) between known and assessed source ascriptions for the virtual sample mixtures. It was found that the source ascriptions with the highest accuracy were achieved using the corrected mean source characterisations for the composite fingerprints selected by the Kruskal Wallis H-test and principal components analysis. Based on the RMSE results, high goodness of fit (GOF) values were not always indicative of accurate source apportionment results, and care should be taken when using GOF to assess mixing model performance. The proposed approach to test different fingerprinting procedures using virtual sample mixtures provides an enhanced basis for selecting procedures that can deliver optimum source discrimination and apportionment.