AbstractSurface runoff and drainage were evaluated for southern Brazilian soils subjected to different rainfall intensities and management practices. Soils received up to four applications of simulated rainfall in sequences with one application per day. Seven lysimeters, each of 1 m3 volume, were used to measure drainage volume, with measurement of initial and final water content, times at which surface runoff and lysimeter drainage began, and the volume rates of flow. At the end of the second test, soils were subjected to two levels of disturbance (denoted by low and high soil movement) by opening furrows. These cultivation treatments altered the times at which lysimeter surface runoff and drainage were initiated, the rates of surface runoff, the final infiltration and internal drainage, and the components of the water balance throughout the series of trials. Mean times at which surface runoff was initiated in lysimeters subjected to greater soil disturbance were longer than those with little soil disturbance. Final infiltration rates were greater in lysimeters with little soil disturbance. It was also found that lysimeter surface runoff generation was influenced by the state of development of maize grown in the lysimeter.
Editor D. Koutsoyiannis; Associate editor G. Mahé 相似文献
Forest disturbances such as harvesting, wildfire and insect infestation are critical ecosystem processes affecting the carbon cycle. Because carbon dynamics are related to time since disturbance, forest stand age that can be used as a surrogate for major clear-cut/fire disturbance information has recently been recognized as an important input to forest carbon cycle models for improving prediction accuracy. In this study, forest disturbances in the USA for the period of ∼1990–2000 were mapped using 400+ pairs of re-sampled Landsat TM/ETM scenes in 500m resolution, which were provided by the Landsat Ecosystem Disturbance Adaptive Processing System project. The detected disturbances were then separated into two five-year age groups, facilitated by Forest Inventory and Analysis (FIA) data, which was used to calculate the area of forest regeneration for each county in the USA. 相似文献
The persistence and long-term memories in daily maximum and minimum temperature series during the instrumental period in southern South America were analysed. Here, we found a markedly seasonal pattern both for short- and long-term memories that can lead to enhanced predictability on intraseasonal timescales. In addition, well-defined spatial patterns of these properties were found in the region. Throughout the entire region, the strongest dependence was observed in autumn and early winter. In the Patagonia region only, the temperatures exhibited more memory during the spring. In general, these elements indicate that nonlinear interactions exist between the annual cycles of temperature and its anomalies. Knowledge of the spatiotemporal behaviour of these long-term memories can be used in the building of stochastic models that only use persistence. It is possible to propose two objective forecast models based on linear interactions associated with persistence and one that allows for the use of information from nonlinear interactions that are manifested in the form of forerunners. 相似文献
An indigenous bacterial strain of Delftia sp. capable of degrading 2,4‐dicholorophenol and an indigenous bacterial community that degrades 2,4,6‐trichlorophenol (TCP) were employed to inoculate continuous down‐flow fixed‐bed reactors. Continuous‐reactors were constructed from PVC employing hollow PVC cylinders as support material. Synthetic wastewater was prepared by dissolving the corresponding chlorophenol in non‐sterile groundwater. Biodegradation was evaluated by spectrophotometry, chloride release, GC, and microbial growth. Detoxification was evaluated by using Daphnia magna as test organism. Delftia sp. was able to remove an average of 95.6% of DCP. Efficiency in terms of chemical oxygen demand (COD) was of 88.9%. The indigenous bacterial community that degrades TCP reached an average efficiency of 96.5 and 91.6% in terms of compound and COD removal, respectively. In both cases stoichiometric removal of chloride and detoxification was achieved. When synthetic wastewater feed was cut off for 7 days, both reactors showed a fast recovery after inflow restarting, reaching average outlet concentration values within 36 h. The promising behavior of the microorganisms and the low cost of the reactors tested allow us to suggest their possible application to remediation processes. 相似文献
This paper analyses the responses related to land use of coffee growers in Chiapas, Mexico to the impact of Hurricane Stan
(October 2005). A multi-temporal analysis of the effect on land cover was performed through the combination of unsupervised
classification of SPOT multispectral images and visual interpretation of panchromatic images (8 months previous to the hurricane,
and 2, 14, and 40 months after the hurricane). The information provided by this geographic analysis was interpreted in light
of information gathered though household surveys. Although the hurricane wrecked havoc across the region, the main impact
in the study area was in the riparian zones where the extent of the loss experienced in terms of coffee harvest and soil was
such that, even 14 months after the event, households with land in those areas were struggling to recover. Nevertheless, after
40 months, the zones that had suffered total soil loss began to support soil and vegetation, indicating the possibility of
replanting coffee in those areas. Although the hurricane occurred when the coffee sector was particularly fragile as a result
of the preceding several years of poor prices, the impact did not trigger extensive land use change. The surveys showed, however,
that people are now more informed of the risk of living and farming on the river margins and are now performing soil conservation
practices and planting trees to reduce risk. 相似文献
We modelled the transport and deposition of ash from the June 2011 eruption from Cordón Caulle volcanic complex, Chile. The modelling strategy, currently under development at the Argentinean Naval Hydrographic Service and National Meteorological Service, couples the weather research and forecasting (WRF/ARW) meteorological model with the FALL3D ash dispersal model. The strategy uses volcanological inputs inferred from satellite imagery, eruption reports and preliminary grain-size data obtained during the first days of the eruption from an Argentinean ash sample collection network. In this sense, the results shown here can be regarded as a quasi-syn-eruptive forecast for the first 16 days of the eruption. Although this article describes the modelling process in the aftermath of the crisis, the strategy was implemented from the beginning of the eruption, and results were made available to the Buenos Aires Volcanic Ash Advisory Centers and other end users. The model predicts ash cloud trajectories, concentration of ash at relevant flight levels, expected deposit thickness and ash accumulation rates at relevant localities. Here, we validate the modelling strategy by comparing results with satellite retrievals and syn-eruptive ground deposit measurements. Results highlight the goodness of the combined WRF/ARW-FALL3D forecasting system and point out the usefulness of coupling both models for short-term forecast of volcanic ash clouds. 相似文献
Each volcano has its own unique seismic activity. The aim of this work is to construct a system able to classify seismic signals for the Villarrica volcano, one of the most active volcanoes in South America. Since seismic signals are the result of particular processes inside the volcano's structure, they can be used to forecast volcanic activity. This paper describes the different kinds of seismic signals recorded at the Villarrica volcano and their significance. Three kind of signals were considered as most representative of this volcano's activity: the long-period, the tremor, and the energetic tremor signals. A classifier is implemented to read the seismic registers at 30-second intervals, extract the most relevant features of each interval, and classify them into one of the three kinds of signals considered as most representative of this particular volcano. To do so, 1033 different kinds of 30-s signals were extracted and classified by a human expert. A feature extraction process was applied to obtain the main characteristics of each of them. This process was developed using criteria which have been shown by others to effectively classify seismic signals, based on the experience of a human expert. The classifier was implemented with a Multi-Layer Perceptron (MLP) artificial neural network whose architecture and training process were optimized by means of a genetic algorithm. This technique searched for the most adequate MLP configuration to improve the classification performance, optimizing the number of hidden neurons, the transfer functions of the neurons, and the training algorithm. The optimization process also performed a feature selection to reduce the number of signal features, optimizing the number of network inputs. The results show that the optimized classifier reaches more than 93% exactitude. identifying the signals of each kind. The amplitude of the signals is the most important feature for its classification, followed by its frequency content. The described methodology can be used to classify more seismic signals to improve the study of the activity of this volcano or to extend the study to other active volcanoes of the region. 相似文献
Chile has a rich, but poorly known history of placer gold mining. At present, this sector is almost nonexistent and there are some restrictions for its revival: disperse and partial information on existing resources and limited technical expertise to assess the potential of placer gold mine sites. This paper presents the background, methodology and results of the prioritization process of known prospects of this kind in Chile. This research was part of a publicly funded project aimed to incentivize the development of this industry. The ranking was carried out using the analytic hierarchy process, which allowed to include different quantitative and qualitative variables related to the economic potential, technical aspects, contextual viability and socioeconomic factors in the analysis. The results show that, despite the increasing relevance of environmental and community issues in mining development, the business potential and the economic/technical aspects are the main factors in the early selection of a site to advance in exploration and development activities. Both variables represented around 40% and 37% of weights in the final selection, respectively. In contrast, contextual viability and local socioeconomic impacts only accounted for the remaining 23%. This study also shows that the inclusion of experts with different backgrounds in the process enriches the analysis and does not significantly distort the final outcome of the prioritization. Finally, the relevance of using MCDM tools when assessing the attractiveness of mine sites for their development is highlighted, particularly when public funds for subsequent exploration activities are committed.