Search results for " PREDICTION"
showing 10 items of 366 documents
Measuring, modelling and managing gully erosion at large scales: A state of the art
2018
Soil erosion is generally recognized as the dominant process of land degradation. The formation and expansion of gullies is often a highly significant process of soil erosion. However, our ability to assess and simulate gully erosion and its impacts remains very limited. This is especially so at regional to continental scales. As a result, gullying is often overlooked in policies and land and catchment management strategies. Nevertheless, significant progress has been made over the past decades. Based on a review of >590 scientific articles and policy documents, we provide a state-of-the-art on our ability to monitor, model and manage gully erosion at regional to continental scales. In this…
ERA5-Land: A state-of-the-art global reanalysis dataset for land applications
2021
Framed within the Copernicus Climate Change Service (C3S) of the European Commission, the European Centre for Medium-Range Weather Forecasts (ECMWF) is producing an enhanced global dataset for the land component of the fifth generation of European ReAnalysis (ERA5), hereafter referred to as ERA5-Land. Once completed, the period covered will span from 1950 to the present, with continuous updates to support land monitoring applications. ERA5-Land describes the evolution of the water and energy cycles over land in a consistent manner over the production period, which, among others, could be used to analyse trends and anomalies. This is achieved through global high-resolution numerical integrat…
Predicting plot soil loss by empirical and process-oriented approaches. A review
2018
Soil erosion directly affects the quality of the soil, its agricultural productivity and its biological diversity. Many mathematical models have been developed to estimate plot soil erosion at different temporal scales. At present, empirical soil loss equations and process-oriented models are considered as constituting a complementary suite of models to be chosen to meet the specific user need. In this paper, the Universal Soil Loss Equation and its revised versions are first reviewed. Selected methodologies developed to estimate the factors of the model with the aim to improve the soil loss estimate are described. Then the Water Erosion Prediction Project which represents a process-oriente…
Genomic transformation and social organization during the Copper Age–Bronze Age transition in southern Iberia
2021
Description
High-Quality Genome Assembly and Annotation of the Big-Eye Mandarin Fish (Siniperca knerii)
2020
Abstract The big-eye mandarin fish (Siniperca knerii) is an endemic species of southern China. It belongs to the family Sinipercidae, which is closely related to the well-known North American sunfish family Centrarchidae. Determining the genome sequence of S. knerii would provide a foundation for better examining its genetic diversity and population history. A novel sequenced genome of the Sinipercidae also would help in comparative study of the Centrarchidae using Siniperca as a reference. Here, we determined the genome sequence of S. knerii using 10x Genomics technology and next-generation sequencing. Paired-end sequencing on a half lane of HiSeq X platform generated 56 Gbp of raw data. R…
Suppressiveness of 18 composts against 7 pathosystems : variability in pathogen response
2006
International audience; Compost is often reported as a substrate that is able to suppress soilborne plant pathogens, but suppression varies according to the type of compost and pathosystem. Reports often deal with a single pathogen while in reality crops are attacked by multiple plant pathogens. The goal of the present study was to evaluate the disease suppression ability of a wide range of composts for a range of plant pathogens. This study was conducted by a consortium of researchers from several European countries. Composts originated from different countries and source materials including green and yard waste, straw, bark, biowaste and municipal sewage. Suppressiveness of compost-amende…
Downscaling rice yield simulation at sub-field scale using remotely sensed LAI data
2019
Abstract Crop modeling and remote sensing are key tools to gain deeper understanding on cropping system dynamics and, ultimately, to increase the sustainability of agricultural productions. This study presents a system to estimate rice yields at sub-field scale based on the integration of a biophysical model and remotely sensed products. Leaf area index (LAI) data derived from decametric optical imageries (i.e., Landsat-8, Landsat-7 and Sentinel–2A) were assimilated into the WARM rice model via automatic recalibration of crop parameters at a fine spatial resolution (30 m × 30 m), targeting the lowest error between simulated and remotely sensed LAI. The performance of the system was evaluate…
Robust link prediction in criminal networks: A case study of the Sicilian Mafia
2020
Abstract Link prediction exercises may prove particularly challenging with noisy and incomplete networks, such as criminal networks. Also, the link prediction effectiveness may vary across different relations within a social group. We address these issues by assessing the performance of different link prediction algorithms on a mafia organization. The analysis relies on an original dataset manually extracted from the judicial documents of operation “Montagna”, conducted by the Italian law enforcement agencies against individuals affiliated with the Sicilian Mafia. To run our analysis, we extracted two networks: one including meetings and one recording telephone calls among suspects, respect…
Predictive pumping based on sensor data and weather forecast
2019
In energy production, peat extraction has a significant role in Finland. However, protection of nature has become more and more important globally. How do we solve this conflict of interests respecting both views? In peat production, one important phase is to drain peat bog so that peat production becomes available. This means that we have control over how we can lead water away from peat bog to nature without water contamination with solid and other harmful substances. In this paper we describe a novel method how fouling of water bodies from peat bog can be controlled more efficiently by using weather forecast to predict rainfall and thus, minimize the effluents to nature. peerReviewed
Input Selection Methods for Soft Sensor Design: A Survey
2020
Soft Sensors (SSs) are inferential models used in many industrial fields. They allow for real-time estimation of hard-to-measure variables as a function of available data obtained from online sensors. SSs are generally built using industries historical databases through data-driven approaches. A critical issue in SS design concerns the selection of input variables, among those available in a candidate dataset. In the case of industrial processes, candidate inputs can reach great numbers, making the design computationally demanding and leading to poorly performing models. An input selection procedure is then necessary. Most used input selection approaches for SS design are addressed in this …