Early season remote sensing of wheat nitrogen status using a green scanning laser

In-season, spatially variable nitrogen (N) fertilizer applications in agricultural systems can help to maximize crop N use efficiency and minimize N losses via hydrological leaching, runoff, and atmospheric volatilization. N fertilizer management often relies upon measurements of crop spectral reflectance using ground-based optical on-the-go sensors or hand-held chlorophyll meters. However, soil background reflectance can confound on-the-go sensing, especially during early crop growth stages, and hand-held chlorophyll meters are impractical for spatially explicit mapping at the field scale. Scanning laser technology is available that measures the intensity of the reflected laser light plus height information within a mm-scale ground instantaneous field of view at a very high sampling rate (up to 50,000 points s⁻¹ in this study). We examined the ability to quantify foliar N status of spring wheat (Triticum aestivum L.) using a green (532 nm) terrestrial laser scanner during an early stem extension growth stage (Zadoks growth stage 3.2). Laser data were processed by (1) removing soil background returns based on laser-determined height information, (2) standardizing green laser intensity based on white-reference panel readings, and (3) filtering noisy laser returns from leaf edges based on a laser return intensity threshold value. The return intensity of the reflected green laser light more accurately (r² = 0.68, RMSE = 0.30 μg g⁻¹) predicted foliar N concentration than conventional chlorophyll meter readings (r² = 0.36, RMSE = 0.41 μg g⁻¹) and spectral indices measured by a ground optical on-the-go sensor (r² < 0.41, RMSE > 0.39 μg g⁻¹). The results indicate that laser scanners are useful for measuring the N status of wheat during early growth stages, and provide justification for incorporating laser scanner based measurements into developing spatially-explicit estimates of foliar N during this critical growth period. Further research is needed to evaluate the operational practicality of a green scanning laser from a moving platform.     

Phosphorus and iron erosion from non-vegetated sites in a post-mining landscape,Lusatia, Germany: Impact on aborning mining lakes

Particulate phosphorus (P) can be transported via soil erosion in overland flow to waters, where it provides a long-term source of P for aquatic biota, and can accelerate freshwater eutrophication. Hence, knowledge of P sources is important for good environmental management. However, data on P, and related Fe, losses from various structures of a post-mining landscape are lacking. A year-long monitoring, and ten short rainfall simulations on plot scale, at ridges and rills and a combination of them, revealed high erosion from bare lignite mining dumps at Schlabendorf-North, Lusatia, Germany. The mean annual soil erosion rate from the year-long monitoring site was 18 × 10⁶ kg km^− 2 yr^− 1, corresponding to 0.034 g m^− 2 min^− 1. The erosion rates were lowest at rill plots (1.9–4.4 g m^− 2 min^− 1), intermediate at ridge plots (14.3–37.1 g m^− 2 min^− 1), and highest at a combined rill and ridge plot (48.7–63.4 g m^− 2 min^− 1). These differences in extent were due to small scale differences in morphology and extreme water repellency. The hydrophobicity leads to very low infiltration, thus generating surface runoff even at low rainfall intensities. Loss rates of P and Fe, as deduced from the year-long erosion rate, were 470–650 kg km^− 2 yr^− 1, and 37.9 × 10³–71 × 10³ kg km^− 2 yr^− 1 respectively. However, these P inputs from lignite mining dump erosion, consisting of P-poor (17–90 μg g^− 1) tertiary spoil materials, into aborning mining lakes, are negligible since they are accompanied by high Fe inputs, which favour an efficient P co-precipitation in the water column.     

Field characterization of olive (Olea europaea L.) tree crown architecture using terrestrial laser scanning data

Since the introduction of Terrestrial Laser Scanning (TLS) instruments, there now exists a means of rapidly digitizing intricate structural details of vegetation canopies using Light Detection and Ranging (LiDAR) technology. In this investigation, Intelligent Laser Ranging and Imaging System (ILRIS-3D) data was acquired of individual tree crowns at olive (Olea europaea L.) plantations in Córdoba, Spain. In addition to conventional tripod-mounted ILRIS-3D scans, the unit was mounted on a platform (12 m above ground) to provide nadir (top-down) observations of the olive crowns. 24 structurally variable olive trees were selected for in-depth analysis. From the observed 3D laser pulse returns, quantitative retrievals of tree crown structure and foliage assemblage were obtained. Robust methodologies were developed to characterize diagnostic architectural parameters, such as tree height (r² = 0.97, rmse = 0.21 m), crown width (r² = 0.97, rmse = 0.13 m), crown height (r² = 0.86, rmse = 0.14 m), crown volume (r² = 0.99, rmse = 2.6 m³), and Plant Area Index (PAI) (r² = 0.76, rmse = 0.26 m²/m²). With the development of such LiDAR-based methodologies to describe vegetation architecture, the forestry, agriculture, and remote sensing communities are now faced with the possibility of replacing current labour-intensive inventory practices with, modern TLS systems. This research demonstrates that TLS systems can potentially be the new observational tool and benchmark for precise characterization of vegetation architecture for improved agricultural monitoring and management.     

Field-scale spatial variability of saturated hydraulic conductivity on a recently constructed artificial ecosystem

Saturated hydraulic conductivity (K_s) influences water storage and movement, and is a key parameter of water and solute transport models. Systematic field evaluation of K_s and its spatial variability for recently constructed artificial ecosystems is still lacking. The objectives of the present study were; (1) to determine saturated hydraulic conductivity of an artificial ecosystem using field methods (Philip-Dunne, and Guelph permeameters), and compare their results to the constant-head laboratory method; (2) to evaluate the spatial variability of K_s using univariate and geostatistical analyses, and (3) to evaluate the ability of five pedotransfer functions to predict K_s. The results showed that K_s varied significantly (p < 0.05) among methods, probably reflecting differences in scales of measurement, flow geometry, assumptions in computation routines and inherent disturbances during sampling. Mean K_s values were very high for all methods (38.6-77.9 m day^− 1), exceeding values for natural sandy soils by several orders of magnitude. The high K_s values and low coefficients of variation (26-44%) were comparable to that of well-sorted unconsolidated marine sands. Geostatistical analysis revealed a spatial structure in surface K_s data described by a spherical model with a correlation range of 8 m. The resulting kriged map of surface K_s showed alternating bands of high and low values, consistent with surface structures created by wheel tracks of construction equipment. Vertical K_s was also spatially structured, with a short correlation range of 40 cm, presumably indicative of layering caused by post-construction mobilization and deposition of fine particles. K_s was linearly and negatively correlated with dry soil bulk density (ρ_b) (r² = 0.73), and to a lesser extent silt plus clay percentage (Si + C) (r² = 0.21). Combining both ρ_b and Si + C significantly (p < 0.05) improved the relationship and gave the best predictor of K_s (r² = 0.76). However, evaluation of five PTFs developed for natural soils showed that they all underestimated K_s by an order of magnitude, suggesting that application of water balance simulation models based on such PTFs to the present study site may constitute a bias in model outputs. Overall, the study demonstrated the influence of material handling, construction procedures and post-construction processes on the magnitude and spatial variability of K_s on a recently constructed artificial ecosystem. These unique hydraulic properties may have profound impacts on soil moisture storage, plant water relations and water balance fluxes on artificial ecosystems, particularly where such landforms are intended to restore pre-disturbance ecological and hydrological functions.     

Bioturbation on wildfire-affected southeast Australian hillslopes: Spatial and temporal variation

The importance of bioturbation as an agent of soil and geomorphological change is well known but few observations have been made of spatial and temporal variations in bioturbation rates. We quantified variations in surface bioturbation by ants (particularly Aphaenogaster longiceps) and vertebrates in the sandstone terrain of the Blue Mountains, southeast Australia. Following wildfire during the period late 2001–early 2002, we monitored thirty-three 5 m² plots positioned in six different slope units and in two catchments affected by different wildfire severities. Measurements were made seasonally for six years. Overall, mean rates of ant mounding and surface scraping by vertebrates were similar (246 ± 339 g m^− 2 yr^− 1 and 274 ± 179 g m^− 2 yr^− 1, respectively). However, rates varied substantially according to slope unit, showing a marked maximum for both ant mounding and total bioturbation on footslopes. Possible reasons for this spatial variation are discussed. A complex response to various soil and ecological factors such as soil texture, soil moisture and vegetation patterns is the most likely explanation. Associated estimates of topsoil (0–30 cm depth) turnover times, based on ant mounding rates alone, ranged from 300 to 100,000 years for different slope units. In contrast to previous findings, wildfire severity did not seem to affect bioturbation, possibly because of ant survival in deep nests and spatial patchiness of fire severity. There was likewise no clear link between temporal changes in bioturbation and fire severity; high rates in the first two years after wildfire were followed by lower rates for all burn severity types. There was also seasonal variability that was not directly related to rainfall. The results substantiate the importance of bioturbation in modifying soil characteristics and influencing soil erosion, especially following a major disturbance event like wildfire.     

Effect of snow amount on runoff,soil loss and suspended sediment during periods of snowmelt in southern West Siberia

Surface runoff, soil loss, suspended sediment concentration (SSC), texture of eroded soils and suspended sediment were determined on slightly eroded chernozems (mouldboard fall-ploughed) during years with different amounts of snow in three areas of southern West Siberia (Predsalairye, Priobye and Kuznetsk hollow). These areas have different geomorphological and climatic characteristics and soils. Observations were made from 1969 to 2007. The soil loss during very low-snow and low-snow years did not exceed 2 t ha^− 1. After winters with normal amounts of snow, the runoff led to slight soil loss (2–5 t ha^− 1). Soil losses in high-snow and very high-snow years varied from slight to severe (4.8–15.8 t ha^− 1) depending on studied area. The main sediment exported during intensive snowmelt and the 1 mm of runoff transported from 35 to 150 kg ha^− 1 of soil material. The removal of soil particles < 0.01 mm (especially clay) prevailed during the initial and final stages of snowmelt. Clay removal by meltwater from the ploughed layer in high-snow and very high-snow years varied from 3300 to 4200 kg ha^− 1 and, in the initial and final stages of snowmelt clay removal, accounted for 1260–1,500 kg ha^− 1. Among the three studied regions, Predsalairye had decreased soil erosion resistance and was the area with the greatest danger of erosion.     

Multiscaling analysis of soil roughness variability

Soil surface roughness (SSR) is a parameter highly suited for the study of soil susceptibility to wind and water erosion. The development of a methodology for quantifying SSR has typically been based on field techniques to obtain data, rather than on the indexes used for interpreting soil roughness variability. One of the most used indexes to evaluate SSR is the random roughness (RR), easily calculated from the heights obtained with a pin meter. The RR index was obtained from soil elevation measurements collected at the intersections of a 2 × 2-cm² grid in a 100 × 400-cm² plot from three different types of soil. SSR values for all soil types were obtained after passing three different tillage tools (chisel, tiller, and roller) through three types of soils at field conditions. The RR index was calculated using the standard deviation (SD) of the lines parallel to the direction of tillage. Lines were 20 mm apart.Since RR assumes vertical random roughness without correlation, the variability of SSR was assessed using structure function (SF) to complement the study. Therefore, the main objective of this analysis was to better illustrate the variability of SSR in relation to spatial distribution. The SF was highly sensitive to soil roughness variability and depended on the tillage tool treatments and soil types, thereby illustrating the origin of the soil roughness variability, either from the soil itself or from the tillage tool used. We also demonstrate that the concept of a generalised Hurst exponent derived from the SF improves our ability to differentiate among the cases.     

Effects of vegetation restoration on soil organic carbon sequestration at multiple scales in semi-arid Loess Plateau,China

Soil organic carbon (SOC) sequestration by vegetation restoration is the theme of much current research. Since 1999, the program of “Grain for Green”has been implemented in the semi-arid Loess Plateau, China. Its scope represents the largest vegetation restoration activity in China. However, it is still unclear for the SOC sequestration effects of vegetation cover change or natural succession promoted by the revegetation efforts at different scales under the semi-arid conditions. In this study, the changes in SOC stocks due to the vegetation restoration in the middle of Loess Plateau were estimated at patch, hill slope transect and small watershed scale from 1998 to 2006. Soil samples were taken from field for the determination of cesium-137 (¹³⁷Cs) and SOC contents. Vegetation cover change from 1998 to 2006 at the small watershed scale was assessed using Geographic Information System. The results showed that cropland transforming to grassland or shrubland significantly increased SOC at patch scale. Immature woodland, however, has no significant effect. When vegetation cover has no transformation for mature woodland (25 years old), SOC has no significant increase implying that SOC has come to a stable level. At hill slope scale, three typical vegetation cover patterns showed different SOC sequestration effects of 8.6%, 24.6%, and 21.4% from 1998 to 2006, and these SOC increases mainly resulted from revegetation. At the small watershed scale, SOC stocks increased by 19% in the surface soil layer at 0–20 cm soil depth from 1998 to 2006, which was equivalent to an average SOC sequestration rate of 19.92 t C y^− 1 km^− 2. Meanwhile, SOC contents showed a significant positive correlation (P < 0.001) with the ¹³⁷Cs inventory at every soil depth interval. This implied significant negative impacts of soil erosion on SOC sequestration. The results have demonstrated general positive effects of vegetation restoration on SOC sequestration at multiple scales. However, soil erosion under rugged topography modified the spatial distribution of the SOC sequestration effects. Therefore, vegetation restoration was proved to be a significant carbon sink, whereas, erosion could be a carbon source in high erosion sensitive regions. This research can contribute to the performance assessment of ecological rehabilitation projects such as “Grain to Green” and the scientific understanding of the impacts of vegetation restoration and soil erosion on soil carbon dynamics in semi-arid environments.     

裸露砒砂岩区坡面侵蚀过程中地表粗糙度与水力侵蚀特征参数的关系

坡面地形起伏状况是影响土壤侵蚀状况的重要因素,深入了解地表粗糙度和产流产沙以及水动力参数之间的关系是研究坡面土壤侵蚀过程的基础.采用野外原位模拟冲刷试验,使用三维激光扫描仪结合ArcGIS提取地形因子参数,研究了裸露砒砂岩区坡面侵蚀过程中地表粗糙度与侵蚀特征参数的关系.结果表明:(1)冲刷强度的增大使得阻力特征参数逐渐...     

Reliability of an expert-based runoff and erosion model: Application of STREAM to different environments

During the last decades, the European loess belt has been confronted with a significant increase in environmental problems due to erosion on agricultural land. Spatially distributed runoff and erosion models operating at the catchment scale are therefore needed to evaluate the impact of potential mitigation measures. Expert-based models offer an alternative solution to process-based and empirical models, but their decision rules are only valid for the local conditions for which they have been derived. The STREAM model, which was developed in Normandy (France), has been applied in two Belgian catchments having a similar soil texture, as well as in a catchment of southern France differing by soil, land use and climate characteristics. The performance of hydrological models can be assessed for instance by calculating the Nash–Sutcliffe efficiency criterion (E_NS). When applied to Belgium, the model results are satisfactory to good after an adaptation of the decision rules (0.90 < E_NS < 0.93 for runoff predictions and 0.85 < E_NS < 0.89 for erosion predictions). Given the important environmental differences between Normandy and southern France, the model rules were also adapted for application in the latter environment. Unfortunately, the quality of runoff predictions was insufficient to simulate erosion in southern France. In conclusion, STREAM is a reliable model providing satisfactory runoff and erosion predictions in the regions where hortonian overland flow dominates. Nevertheless, an adaptation of decision rules based on local multi-scale (plot, field, catchment) data is needed, before running the model. STREAM can then serve as a decision support tool to design for instance flood control measures.