N.F. Fang

Using biomarkers as fingerprint properties to identify sediment sources in a small catchment

Traditional fingerprinting methods are limited in their ability to identify soil erosion sources where geologic variations are small or where different land uses span geological boundaries. In this study, a new biomarker for fingerprinting, specifically, n-alkanes, was used in a small catchment to identify sediment sources. The n-alkanes were based on land uses, could provide vegetation information, and were relatively resistant to diagenetic modifications and decomposition. This study used a composite fingerprinting method that was based on two types of fingerprint factors (27 biomarker properties and 45 geochemical properties) with 60 source samples (i.e., gully, grassland, forest, and cropland) and nine soil profiles. Genetic algorithm (GA) optimization has been deployed to find the optimal source contribution to sediments. The biomarker results demonstrated that young forest is the main sediment source in this catchment, contributing 50.5%, whereas cropland, grassland and gully contributed 25.6%, 14.4% and 9.5%, respectively; the geochemistry results were similar to the biomarkers. The forest and grassland contributions gradually increased from upstream to downstream, and the sediment contributions of cropland gradually decreased in the direction of the runoff pathway at the check dam. In a comparison of biomarker and geochemical fingerprinting data, the latter may have overestimated the forest inputs to the catchment sediment yields because of a mixed land use history (i.e., forest and grassland). The geochemical fingerprint approach limits its ability to fully discriminate sources based on land management regimes, but the biomarker (individual n-alkanes) displayed the potential to discriminate between a greater number and different types of sediment sources and to provide greater detail regarding sediment sources.

Sediment source analysis using the fingerprinting method in a small catchment of the Loess Plateau, China

PurposeThis paper aims to use the composite fingerprinting method to reconstruct the environmental history after the Grain-for-Green Project and to provide effective sediment management and soil erosion-control strategies.Materials and methodsThis study used a composite fingerprinting method based on 45 geochemical properties and a mixing model to investigate sediment core changes in the sediment source in an agricultural catchment with little native vegetation. The samples consisted of 77 source samples (i.e., gully, grassland, forest, cropland, and fallow land) and five sediment cores. Genetic algorithm (GA) optimization has been recently used to find the best optimum source contribution to sediments.Results and discussionThe results demonstrate that gully is the main sediment source in this catchment, constituting 34.7xa0%, followed by cropland (28.2xa0%), forest (21.5xa0%), grassland (12.7xa0%), and fallow land (2.9xa0%). However, the relative contribution of each source type was variable in all five sediment cores. The sediment that derived from grassland was relatively stable in the five cores. The relative contribution of forest was higher in the downstream portion of the check dam and lower in the upstream portion and gradually increased in the direction of the runoff pathway. As the forest matured, the sediment that derived from the forest gradually decreased. Changes in the hydro-ecological environment would lead to the leaf litter and understory being poorly developed and the soil being bare in the forest, making it more vulnerable to erosion.ConclusionsReforestation and fallow are the key ecological strategies for reducing soil erosion. However, at the beginning of the Grain-for-Green Project, the young forest contributed 21.5xa0% of the sediment, indicating that natural fallow may be a better-designed sediment management and soil erosion-control strategy.

Hydrological response of a large-scale mountainous watershed to rainstorm spatial patterns and reforestation in subtropical China

This paper aims to investigate the hydrological response of a large-scale (8973u202fkm2) mountainous watershed to different rainstorm spatial patterns and reforestation. Based on 32u202fyears of observations, measurements of 184 rainstorm events and 125 sediment-producing events with complete hydrographs were analyzed. The K-means clustering method was used to classify the spatial patterns of rainstorm events in accordance with their event-based spatial rainfall characteristics. The 184 rainstorm events were classified into four spatial patterns, among which the spatial features differ significantly: (I) Spatial Pattern I (SPI) includes rainstorms with a low amount of cumulative areal rainfall (27.4u202fmm), the highest spatial variability (0.986), and the highest frequency; (II) Spatial Pattern II (SPII) includes rainstorms of high spatial variability (0.759) and the largest amount of local maximum daily rainfall (106.8u202fmm); (III) Spatial Pattern III (SPIII) includes rainstorms with a medium amount of cumulative areal rainfall (58.7u202fmm) and low spatial variability (0.362); and (IV) Spatial Pattern IV (SPIV) includes rainstorms with the largest amount of cumulative areal rainfall (117.2u202fmm) and the lowest spatial variability (0.313). Vegetation cover in the upper Du watershed was significantly improved after the implementation of the Grain-for-Green project. The average area-specific sediment yields (SSY) for the four SPs were 15.4, 65.5, 55.8, and 286.2u202ftu202fkm-2 before reforestation and decreased to 6.0, 59.3, 43.7 and 89.9u202ftu202fkm-2, respectively, after reforestation. ANOVA (analysis of variance) indicated that reforestation resulted in a significant reduction in runoff coefficient under SPIII and SPIV and a significant reduction in SSY under SPI and SPIV. A hysteresis analysis suggested that the proportion of events with a clockwise loop increased from 64.9% before reforestation to 82.1% after reforestation and that complex loops became less common during 2000-2010 under SPIV, thereby implying a reduced sediment supply.