Monthly streamflow forecasting using neuro-wavelet techniques and input analysis

ABSTRACT

Combinations of low-frequency components (also known as approximations) resulting from the wavelet decomposition are tested as inputs to an artificial neural network (ANN) in a hybrid approach, and compared to classical ANN models for flow forecasting for 1, 3, 6 and 12 months ahead. In addition, the inputs are rewritten in terms of the flow, revealing what type of information was being provided to the network, in order to understand the effect of the approximations on the forecasting performance. The results show that the hybrid approach improved the accuracy of all tested models, especially for 1, 3 and 6 months ahead. The input analyses show that high-frequency components are more important for shorter forecast horizons, while for longer horizons, they may worsen the model accuracy.     

Quantifying the impact of no-till on sediment yield in southern Brazil at the hillslope and catchment scales

No-till (NT) is a soil management system designed to protect soil resources from water erosion and provide numerous benefits compared to conventional tillage through the increase of organic matter inputs into the soil. However, NT in isolation is not sufficient to control erosion processes caused by an excessive production of surface runoff. This study evaluated soil losses on agricultural hillslopes under no-till characterized by contrasted water, soil, and crop management conditions. To this end, water and soil losses were monitored between 2014 and 2018 at two scales, including four macroplots (0.6 ha; 27 events) and two paired zero-order catchments (2.4 ha; 63 events). The resulting dataset covered a wide range of rainfall conditions that occurred in contrasted soil, crop, and runoff management conditions. Hyetographs, hydrographs, and sedigraphs were constructed, and these data were used to evaluate the impact of management on sediment yields, including that of terraces, scarification, and phytomass on sediment yield. The installation of terraces reduced sediment yield by 58.7%, mainly through surface runoff control. Crop management including an increased phytomass input efficiently controlled soil losses (63%), although it did not reduce runoff volume and peak flow. In contrast, scarification had no impact on runoff and soil losses. The current research demonstrated the need to combine the installation of terraces and leaving a high amount of phytomass on the soil to control surface runoff and erosion and reduce sediment yield. The current research therefore reinforces the relevance of the monitoring strategy conducted at the scale of macroplots and zero-order catchments to evaluate the impact of contrasted water, soil, and crop management methods and select the most effective conservation agriculture practices.     

Analysis of Wind Roses Using Hierarchical Cluster and Multidimensional Scaling Analysis at La Plata,Argentina

Knowledge of frequency wind patterns is very important for air pollution modelling, especially in a city like La Plata (approximately 850,000 inhabitants) with high vehicular and industrial activities and no air monitoring network. An hourly wind analysis was carried out on data from two local weather stations (points A and J). An initial result was that, in spite of differences in data quality, the local weather stations observations were consistent with local and regional National Meteorological Service (NMS) monthly based observations. Two non conventional multivariate statistical methods were employed to further analyse hourly data at points A and J. Hierarchical cluster resulted in a good summarising tool to visualise prevailing hourly winds. Resultant vectors emerging from the clustering process showed good similarity between sites and seasons; this allowed a further visualization of the average diurnal wind development. Multidimensional scaling (MDS) permitted a pairwise comparison of a large number of hourly wind roses. These wind roses were more similar to each other in colder seasons and at site A (the one that is closer to the river) than in warmer seasons and at site J. Most of the observed variations regarding seasons and sites revealed by cluster and MDS analysis are explained in terms of the sea-land breeze circulations. The methodology applied proved to be of utility for simplifying the analysis of high dimensional data with numerous observations.     

Charmed meson pair production in high-energy pp collisions within the QCD color dipole approach

A study of double-charmed meson production in high-energy proton–proton collisions at the Large Hadron Collider is presented. Considering the color dipole formalism developed in the transverse momentum representation along with the double parton scattering mechanism, predictions are made for the transverse momentum differential cross section for different pairs of -mesons. The theoretical results cover the center-of-mass energy and forward rapidities available by the LHCb experiment. The proton–proton results considering different unintegrated gluon distributions are compared to the respective data collected at the LHC.     

Development of regional future climate change scenarios in South America using the Eta CPTEC/HadCM3 climate change projections: climatology and regional analyses for the Amazon, S?o Francisco and the Paraná River basins

The objective of this study is to assess the climate projections over South America using the Eta-CPTEC regional model driven by four members of an ensemble of the Met Office Hadley Centre Global Coupled climate model HadCM3. The global model ensemble was run over the twenty-first century according to the SRES A1B emissions scenario, but with each member having a different climate sensitivity. The four members selected to drive the Eta-CPTEC model span the sensitivity range in the global model ensemble. The Eta-CPTEC model nested in these lateral boundary conditions was configured with a 40-km grid size and was run over 1961–1990 to represent baseline climate, and 2011–2100 to simulate possible future changes. Results presented here focus on austral summer and winter climate of 2011–2040, 2041–2070 and 2071–2100 periods, for South America and for three major river basins in Brazil. Projections of changes in upper and low-level circulation and the mean sea level pressure (SLP) fields simulate a pattern of weakening of the tropical circulation and strengthening of the subtropical circulation, marked by intensification at the surface of the Chaco Low and the subtropical highs. Strong warming (4–6°C) of continental South America increases the temperature gradient between continental South America and the South Atlantic. This leads to stronger SLP gradients between continent and oceans, and to changes in moisture transport and rainfall. Large rainfall reductions are simulated in Amazonia and Northeast Brazil (reaching up to 40%), and rainfall increases around the northern coast of Peru and Ecuador and in southeastern South America, reaching up to 30% in northern Argentina. All changes are more intense after 2040. The Precipitation–Evaporation (P–E) difference in the A1B downscaled scenario suggest water deficits and river runoff reductions in the eastern Amazon and S?o Francisco Basin, making these regions susceptible to drier conditions and droughts in the future.     

Co-seismic landslide detection after M 7.4 earthquake on June 23, 2020, in Oaxaca,Mexico, based on rapid mapping method using high and medium resolution synthetic aperture radar (SAR) images

Landslides are the fourth most common natural disasters in the world, with Costa Rica and southern Mexico being the most affected regions of Central America (Froude and Petley, 2018). In this work, we propose a semi-automated method to detect earthquake-triggered landslides for rapid mapping after a disaster event using open Sentinel-1 data. We used high-resolution TerraSAR-X data and very high-resolution Spot-7 images to compare and evaluate the accuracy of landslide distribution maps generated from the semi-automated method, applied to the M 7.1 earthquake on June 23, 2017, in Oaxaca, Mexico. The outcomes showed better accuracy in descending orbits due to ‘windward-leeward’ physiographic conditions, with a 50.56% quality percentage. This shows a reasonably good capacity to detect co-seismic landslides. However, the breaching factor was also high because several features, such as bare soils and agricultural areas, were incorrectly identified as co-seismic landslides. Finally, this semi-automated method establishes a basis for future improvements in methodologies applied to construct rapid mapping inventories using medium SAR scales.

     

The complementary use of H NMR, C NMR, FTIR and size exclusion chromatography to investigate the principal structural changes associated with composting of organic materials with diverse origin

The aim of this work is to study the structural changes involved in humification processes. Total humic extracts (THE) obtained from five composted materials of diverse origin (solid wastes of wineries, solid mill olive wastes, domestic wastes, ovine manures plus straw, and a mixture of animal manures), and their corresponding initial raw fresh organic mixtures were studied using ¹³C nuclear magnetic resonance (NMR) using the cross-polarization magic angle spinning technique (CPMAS), ¹H NMR, Fourier transform infrared spectroscopy (FTIR) and high pressure size exclusion chromatography (HPSEC). One group of three humic acids extracted from soils, and a second group consisting of two reference humic acids and two reference fulvic acids (1S104H, 1R103H, 1R101F and 1R107F) obtained from the International Humic Substances Society were also characterized using these techniques, in order to compare the features of reference humic and fulvic acids with those of composted materials. Likewise, the results were compared with those obtained in previous studies, in which UV–Visible and fluorescence spectroscopies were employed to characterize the humification degree of the molecular systems.The results obtained by ¹³C CPMAS NMR, ¹H NMR and FTIR indicate that, in general, humification seems to be associated with an increase in the aromatic character of the systems, with the presence of phenol groups as principal substituents and a reduction in oxygen containing functional groups, principally carboxylic or carbonylic groups, as well as the development of molecular fractions with larger size. These results also support the suitability of UV–Visible and fluorescence spectroscopies in the assessment of the humification course of humic extracts in composting processes.