How do large wildfires impact sediment redistribution over multiple decades?

Wildfires have become an increasing threat for Mediterranean ecosystems, due to increasing climate change-induced wildfire activity and changing land management practices. In addition to the initial risk, wildfires can alter the soil in various ways—depending on fire severity—and cause enhanced post-fire erosion. Usually, post-fire erosion studies focus on a short time window and lack the attention for sediment dynamics at larger spatial scales. Yet, these large spatial and temporal scales are fundamental for a better understanding of long-term destructive effects of multiple recurring wildfires on post-fire erosion processes and catchment sediment dynamics. In this study the landscape evolution model LAPSUS was used to simulate erosion and deposition in the 404 km2 Águeda catchment in north-central Portugal over a 41-year (1979–2020) timespan, including eight wildfires each burning >1000 ha. To include variation in fire severity and its impact on the soil, four burn severity classes, represented by the difference normalized burn ratio (dNBR), were parameterized. Although model calibration was difficult due to lack of spatial and temporal measured data, the results show that long-term post-fire net erosion rates were significantly higher in the wildfire scenarios (5.95 ton ha−1 yr−1) compared to those of a non-wildfire scenario (0.58 ton ha−1 yr−1). Furthermore, erosion values increased with burn severity and multiple wildfires increased the overall catchment sediment build-up. Simulated erosion patterns showed great spatial variability, with large deposition and erosion rates inside streams. This variability made it difficult to identify land uses that were most sensitive for post-fire erosion, because some land uses were located in more erosion-sensitive areas (e.g. streams, gullies) or were more affected by high burn severity levels than others. Despite these limitations, LAPSUS performed well on addressing spatial sediment processes and can contribute to pre-fire management strategies, by identifying locations at risk of post-fire erosion.info:eu-repo/semantics/publishedVersio

Intra-annual sediment dynamic assessment in the Wei River Basin, China, using the AIC functional-structural connectivity index

Hydrological and sediment dynamics have changed considerably on the Chinese Loess Plateau during the last six decades due to large scale land use changes and numerous water regulation actions. Understanding the mechanism of sediment transport change and its effects is of great importance to food and environmental security. Numerical approaches are useful to map and assess spatio-temporal patterns in sediment dynamics. This study evaluates monthly and annual sediment connectivity in the Wei River Basin (134,800 km2) at the basin and sub-basin scales using the aggregated index of sediment connectivity (AIC). For the first time, this index is applied on this relatively large regional scale. The two objectives were to (1) evaluate the performance of the AIC at the regional scale, addressing substantial differences among areas, and (2) analyze how each AIC sub-factor co-determines the monthly sediment and connectivity patterns. Results show that AIC has strong or moderate positive correlation with sediment yield from 15 out of 23 stations in the Wei and Jing sub-basin. The Jing sub-basin has the highest sediment connectivity due to degraded vegetation, while the Beiluo sub-basin has the lowest sediment connectivity on average due to better ecological restoration. Within the year, sediment connectivity is highest in April and lowest in January, due to the rainfall regime and intra-annual land cover variations. Among the AIC factors, the rainfall factor has the highest effect on sediment connectivity, implying that functional connectivity (graded by rainfall and soil cover) determines sediment dynamics more than structural connectivity (mainly determined by topography and soil permeability). This study provides one of the first large-scale estimates of spatial and temporal sediment connectivity from hillslopes to river stream and including large reservoirs, which can be further employed to implement regional ecological construction works and environmental catchment management.info:eu-repo/semantics/publishedVersio

Епідигматичний модус англійських числівників

У статті розглядаються англійські числівники, денумеративи та їх епідигматичний модус. Семантична структура порівнюваних груп розглядаються на векторах їх походження та модифікації. Частиномовна представленість досліджується на просторах їх граматичного, семантичного і словотворчого буття. Визначаються перспективи подальшого дослідження. При цитуванні документа, використовуйте посилання http://essuir.sumdu.edu.ua/handle/123456789/30551В статье исследуются английские числительные, денумеративы, а также их эпидигматичекие аспекты. Семантическая структура сравниваемых единиц изучается на векторах семантики, грамматики и словотворчества. Намечаются перспективы дальнейшего исследования. При цитировании документа, используйте ссылку http://essuir.sumdu.edu.ua/handle/123456789/30551The article in question deals with the English numerals, denumerals and their epidigmatic tendencies. The semantic structures of both groups are being focused upon. The words under analysis are viewed in terms of their initial and secondary grounds. The item of part of speech charge is being considered in terms of grammatical, semantic and epidigmatic aspects. Thus, the modus of the paradigmatic groups have been considered wide perspectives for further investigation. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3055

An improved method for calculating slope length (λ) and the LS parameters of the Revised Universal Soil Loss Equation for large watersheds

The Universal Soil Loss Equation (USLE) and its revised version (RUSLE) are often used to estimate soil erosion at regional landscape scales. USLE/RUSLE contain parameters for slope length factor (L) and slope steepness factor (S), usually combined as LS. However a major limitation is the difficulty in extracting the LS factor. Methods to estimate LS based on geographic information systems have been developed in the last two decades. L can be calculated for large watersheds using the unit contributing area (UCA) or the slope length (λ) as input parameters. Due to the absence of an estimation of slope length, the UCA method is insufficiently accurate. Improvement of the spatial accuracy of slope length and LS factor is still necessary for estimating soil erosion. The purpose of this study was to develop an improved method to estimate the slope length and LS factor. We combined the algorithm for multiple-flow direction (MFD) used in the UCA method with the LS-TOOL (LS-TOOLSFD) algorithms, taking into account the calculation errors and cutoff conditions for distance, to obtain slope length (λ) and the LS factor. The new method, LS-TOOLMFD, was applied and validated in a catchment with complexly variable slopes. The slope length and LS calculated by LS-TOOLMFD both agreed better with field data than with the calculations using the LS-TOOLSFD and UCA methods, respectively. We then integrated the LS-TOOLMFD algorithm into LS-TOOL developed in Microsoft's.NET environment using C# with a user-friendly interface. The method can automatically calculate slope length, slope steepness, L, S, and LS factor, providing the results as ASCII files that can be easily used in GIS software and erosion models. This study is an important step forward in conducting accurate large-scale erosion evaluation

Quality of terrestrial data derived from UAV photogrammetry : A case study of Hetao irrigation district in northern China

Most crops in northern China are irrigated, but the topography affects the water use, soil erosion, runoff and yields. Technologies for collecting high-resolution topographic data are essential for adequately assessing these effects. Ground surveys and techniques of light detection and ranging have good accuracy, but data acquisition can be time-consuming and expensive for large catchments. Recent rapid technological development has provided new, flexible, high-resolution methods for collecting topographic data, such as photogrammetry using unmanned aerial vehicles (UAVs). The accuracy of UAV photogrammetry for generating high-resolution Digital Elevation Model (DEM) and for determining the width of irrigation channels, however, has not been assessed. A fixed-wing UAV was used for collecting high-resolution (0.15 m) topographic data for the Hetao irrigation district, the third largest irrigation district in China. 112 ground checkpoints (GCPs) were surveyed by using a real-time kinematic global positioning system to evaluate the accuracy of the DEMs and channel widths. A comparison of manually measured channel widths with the widths derived from the DEMs indicated that the DEM-derived widths had vertical and horizontal root mean square errors of 13.0 and 7.9 cm, respectively. UAV photogrammetric data can thus be used for land surveying, digital mapping, calculating channel capacity, monitoring crops, and predicting yields, with the advantages of economy, speed and ease.</p

How to quantify the impacts of diversification on sustainability? A review of indicators in coffee systems

Despite the potential of diversification strategies to achieve sustainability, diversified systems such as agroforestry are still not widely implemented by farmers, which indicates the need to further understand and adequately assess the impacts of diversification to inform the design of complex systems. In this paper, we conduct a systematic literature review focused on agroforestry coffee systems, to assess (i) how current methods and indicators are used to quantify the impact of diversification on multiple dimensions of system sustainability, and (ii) to assess the impact of diversification through coffee agroforestry on multiple dimensions of sustainability. Our analysis was based on 215 selected papers and all the indicators identified could be classified in one of the sustainability dimensions proposed in our framework: ecosystem services (57.2%), biodiversity (35.6%), input use (4%), socio-economic sustainability (2.7%) and resilience capacity (0.5%). Despite the broad scope of the indicators, individual studies were found to often lack interdisciplinarity and a systemic view on agroecosystems. Besides, not only were there few studies that included the impacts of diversification on input use, socio-economic sustainability and resilience capacity, but specific biodiversity attributes (e.g. functional diversity, landscape diversity) and ecosystem services (e.g. soil biological quality, water regulation, pollination) were generally underreported. The impact of diversification was more positive than negative in all dimensions of sustainability, with the exception of crop productivity. Yet, diversified systems are associated with reduced costs and high yields can still be achieved in diversified systems with appropriate agricultural management (e.g. adequate number and type of shade trees). Key to reaping the benefits of diversified systems is that the diversity of elements is carefully integrated considering the impact on multiple dimensions of system sustainability. A better understanding of synergies and trade-offs remains crucial for the customized design of diverse and sustainable systems for a variety of geo-climatic conditions

Soil-Improving Cropping Systems for Sustainable and Profitable Farming in Europe

Soils form the basis for agricultural production and other ecosystem services, and soil management should aim at improving their quality and resilience. Within the SoilCare project, the concept of soil-improving cropping systems (SICS) was developed as a holistic approach to facilitate the adoption of soil management that is sustainable and profitable. SICS selected with stakeholders were monitored and evaluated for environmental, sociocultural, and economic effects to determine profitability and sustainability. Monitoring results were upscaled to European level using modelling and Europe-wide data, and a mapping tool was developed to assist in selection of appropriate SICS across Europe. Furthermore, biophysical, sociocultural, economic, and policy reasons for (non)adoption were studied. Results at the plot/farm scale showed a small positive impact of SICS on environment and soil, no effect on sustainability, and small negative impacts on economic and sociocultural dimensions. Modelling showed that different SICS had different impacts across Europe-indicating the importance of understanding local dynamics in Europe-wide assessments. Work on adoption of SICS confirmed the role economic considerations play in the uptake of SICS, but also highlighted social factors such as trust. The project's results underlined the need for policies that support and enable a transition to more sustainable agricultural practices in a coherent way

Soil-Improving Cropping Systems for Sustainable and Profitable Farming in Europe

Soils form the basis for agricultural production and other ecosystem services, and soil management should aim at improving their quality and resilience. Within the SoilCare project, the concept of soil-improving cropping systems (SICS) was developed as a holistic approach to facilitate the adoption of soil management that is sustainable and profitable. SICS selected with stakeholders were monitored and evaluated for environmental, sociocultural, and economic effects to determine profitability and sustainability. Monitoring results were upscaled to European level using modelling and Europe-wide data, and a mapping tool was developed to assist in selection of appropriate SICS across Europe. Furthermore, biophysical, sociocultural, economic, and policy reasons for (non)adoption were studied. Results at the plot/farm scale showed a small positive impact of SICS on environment and soil, no effect on sustainability, and small negative impacts on economic and sociocultural dimensions. Modelling showed that different SICS had different impacts across Europe—indicating the importance of understanding local dynamics in Europe-wide assessments. Work on adoption of SICS confirmed the role economic considerations play in the uptake of SICS, but also highlighted social factors such as trust. The project’s results underlined the need for policies that support and enable a transition to more sustainable agricultural practices in a coherent way

A wrapper feature selection approach for efficient modelling of gully erosion susceptibility mapping

Identifying the vulnerability level of an area to soil erosion, particularly gully erosion, is key to the development of an efficient management strategy for policymakers. While efforts into susceptibility mapping of natural disasters have grown in recent years, understanding the most relevant predictive causal factors is still a challenge. As the selection of these factors, among many potentially relevant factors, is an important part of the model selection process, we propose a hybrid intelligent approach for the optimal selection of a set of relevant factors based on logistic regression (LR) and genetic algorithms. In order to verify the effectiveness of the proposed approach, this study also identified areas that were highly susceptible to gully erosion using three different classifiers – namely, the LR, support vector machine (SVM) and k-nearest neighbours (k-NN) techniques. We tested the approach in the Yeli Bedrag watershed in north-eastern Golestan province, Iran. The results showed that the elevation, distance to fault, slope and the index of connectivity were the most important causal factors affecting the successful prediction of gully occurrence. Comparison of maximum True Skill Statistic values showed that increased model sophistication did not necessarily result in a higher level of model performance. In terms of performance, k-NN was superior to the SVM and LR methods. This method can be effectively used for gully erosion susceptibility (GES) zonation in the study area, which is very important to support spatial planning to initiate designing mitigation strategies and conservation needs over a large area, or to plan additional conservation efforts and relocate soil conservation plans. In conclusion, our findings indicate that by incorporating the proposed hybrid intelligent approach, the number of relevant factors for GES mapping was reduced, while classification accuracy was increased.</p

Field Guide to the Guadalentín (Spain)

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