ALBERT

Description: This paper aims to evaluate the characteristics of rainfall events of three experimental basins located in northeast Brazil. The study areas are located, one in Ceará State and two in Paraíba State. Thus, the definition of rainfall events was based on two characteristics: minimum inter-event time and minimum event depth. Then, they were classified according to the shape of the hyetograph: to the left rectangular, triangular, and triangular with peak, and to the right, bimodal and unshaped. Evaluation of the percentages of each type of hyetograph and the main characteristics of rainfall events (peak, duration and intensity) was carried out. The results shows that the two experimental basins located in the semi-arid region have similar characteristics, and shapeless events have significant accumulated rainfall.

Description: Approximately 57% of the Brazilian Northeast region is recognized as semiarid land and has been undergoing intense land use processes in the last decades, which have resulted in severe degradation of its natural assets. Therefore, the objective of this study is to identify the areas that are susceptible to desertification in this region based on the eleven driving factors of desertification (pedology, geology, geomorphology, topography data, land use and land cover change, aridity index, livestock density, rural population density, fire hot spot density, human development index (HDI), conservation units) which were model-simulated for two different periods: 2000 and 2010. Each indicator were assigned weights ranging from 1 to 2 (representing the best and the worst conditions), representing classes indicating low, moderate and high susceptibility to desertification. The result indicates that 94% of the Brazilian Northeast region is under moderate to high susceptibility to desertification. The areas that were susceptible to soil desertification increased by approximately 4.6% (83.35 km2) from 2000 to 2010. The implementation of the methodology provide the technical basis for decision making that involves mitigating actions, as well as the first comprehensive national assessment within the United Nations Convention to Combat Desertification framework.

Description: We have developed a fast total-field anomaly inversion to estimate the magnetization direction of multiple sources with approximately spherical shape and known centres. Our method can be applied to interpret multiple sources with different magnetization directions. It neither requires the prior computation of any transformation like reduction to the pole nor the use of regularly spaced data on a horizontal grid. The method contains flexibility to be implemented as a linear or non-linear inverse problem, which results, respectively, in a least-squares or robust estimate of the components of the magnetization vector of the sources. Applications to synthetic data show the robustness of our method against interfering anomalies and errors in the location of the sources' centre. Besides, we show the feasibility of applying the upward continuation to interpret non-spherical sources. Applications to field data over the Goiás Alkaline Province (GAP), Brazil, show the good performance of our method in estimating geological meaningful magnetization directions. The results obtained for a region of the GAP, near from the alkaline complex of Diorama, suggest the presence of non-outcropping sources marked by strong remanent magnetization with inclination and declination close to -70.35° and -19.81°, respectively. This estimated magnetization direction leads to predominantly positive reduced-to-the-pole anomalies, even for other region of the GAP, in the alkaline complex of Montes Claros de Goiás. These results show that the non-outcropping sources near from the alkaline complex of Diorama have almost the same magnetization direction of that ones in the alkaline complex of Montes Claros de Goiás, strongly suggesting that these sources have emplaced the crust almost within the same geological time interval.

Description: Monitoring of volcanic activity is important for learning about the properties of each volcano and for providing early warning systems to the population. Monitoring equipment can be expensive, and thus the degree of monitoring varies from volcano to volcano and from country to country, with many volcanoes not being monitored at all. This paper describes the development of a wireless sensor network (WSN) capable of collecting geophysical measurements on remote active volcanoes. Our main goals were to create a flexible, easy-to-deploy and easy-to-maintain, adaptable, low-cost WSN for temporary or permanent monitoring of seismic tremor. The WSN enables the easy installation of a sensor array in an area of tens of thousands of m2, allowing the location of the magma movements causing the seismic tremor to be calculated. This WSN can be used by recording data locally for later analysis or by continuously transmitting it in real time to a remote laboratory for real-time analyses. We present a set of tests that validate different aspects of our WSN, including a deployment on a suspended bridge for measuring its vibration.

Description: Seven soil-gas radon monitoring stations were placed along the active front of a granite quarry in Canas de senhorim, Central Portugal, recording continuously for 81 days. Important differences in the radon concentration were found between stations, with average values comprised between 102 and 2982 Bq m−3, which can be explained by the local presence of uranium anomalies in the regional late-orogenic Hercynian granite, usually associated with faults. One of the boreholes exhibits large radon anomalies lasting for several days, and two, contrary to the others, show a clear daily periodic behaviour, with minima around 19:00 LT and maxima around 07:00 LT. The different patterns observed in stations placed at such a short distance (

Description: The study of long-term trends in tide gauge data is important for understanding the present and future risk of changes in sea-level variability for coastal zones, particularly with respect to the ongoing debate on climate change impacts. Traditionally, most corresponding analyses have exclusively focused on trends in mean sea-level. However, such studies are not able to provide sufficient information about changes in the full probability distribution (especially in the more extreme quantiles). As an alternative, in this paper we apply quantile regression (QR) for studying changes in arbitrary quantiles of sea-level variability. For this purpose, we chose two different QR approaches and discuss the advantages and disadvantages of different settings. In particular, traditional linear QR poses very restrictive assumptions that are often not met in reality. For monthly data from 47 tide gauges from along the Baltic Sea coast, the spatial patterns of quantile trends obtained in linear and nonparametric (spline-based) frameworks display marked differences, which need to be understood in order to fully assess the impact of future changes in sea-level variability on coastal areas. In general, QR demonstrates that the general variability of Baltic sea-level has increased over the last decades. Linear quantile trends estimated for sliding windows in time reveal a wide-spread acceleration of trends in the median, but only localised changes in the rates of changes in the lower and upper quantiles.

Description: The analysis of trends in air temperature observations is one of the most common activities in climate change studies. This work examines the changes in daily mean air temperature over Central Europe using quantile regression, which allows the estimation of trends, not only in the mean but in all parts of the data distribution. A bootstrap procedure is applied for assessing uncertainty on the derived slopes and the resulting distributions are summarised via clustering. The results show considerable spatial diversity over the central European region. A distinct behaviour is found for lower (5%) and upper (95%) quantiles, with higher trends around 0.15 °C decade−1 at the 5% quantile and around 0.20 °C decade−1 at the 95% quantile, the largest trends (〉0.2 °C decade−1) occurring in the Alps.

Description: Monitoring of volcanic activity is important to learn about the properties of each volcano and provide early warning systems to the population. Monitoring equipment can be expensive and thus, the degree of monitoring varies from volcano to volcano and from country to country, with many volcanoes not being monitored at all. This paper describes the development of a Wireless Sensor Network (WSN) capable of collecting geophysical measurements on remote active volcanoes. Our main goals were to create a flexible, easy to deploy and maintain, adaptable, low-cost WSN for temporary or permanent monitoring of seismic tremor. The WSN enables the easy installation of a sensor array on an area of tens of thousand of m2, allowing the location of the magma movements causing the seismic tremor to be calculated. This WSN can be used by recording data locally for latter analysis or by continuously transmitting it in real time to a remote laboratory for real-time analyses.

Description: We propose a composite drought vulnerability indicator (DVI) that reflects different aspects of drought vulnerability evaluated at Pan-African level for four components: the renewable natural capital, the economic capacity, the human and civic resources, and the infrastructure and technology. The selection of variables and weights reflects the assumption that a society with institutional capacity and coordination, as well as with mechanisms for public participation, is less vulnerable to drought; furthermore, we consider that agriculture is only one of the many sectors affected by drought. The quality and accuracy of a composite indicator depends on the theoretical framework, on the data collection and quality, and on how the different components are aggregated. This kind of approach can lead to some degree of scepticism; to overcome this problem a sensitivity analysis was done in order to measure the degree of uncertainty associated with the construction of the composite indicator. Although the proposed drought vulnerability indicator relies on a number of theoretical assumptions and some degree of subjectivity, the sensitivity analysis showed that it is a robust indicator and hence able of representing the complex processes that lead to drought vulnerability. According to the DVI computed at country level, the African countries classified with higher relative vulnerability are Somalia, Burundi, Niger, Ethiopia, Mali and Chad. The analysis of the renewable natural capital component at sub-basin level shows that the basins with high to moderate drought vulnerability can be subdivided into the following geographical regions: the Mediterranean coast of Africa; the Sahel region and the Horn of Africa; the Serengeti and the Eastern Miombo woodlands in eastern Africa; the western part of the Zambezi Basin, the southeastern border of the Congo Basin, and the belt of Fynbos in the Western Cape province of South Africa. The results of the DVI at the country level were compared with drought disaster information from the EM-DAT disaster database. Even if a cause–effect relationship cannot be established between the DVI and the drought disaster database, a good agreement is observed between the drought vulnerability maps and the number of persons affected by droughts. These results are expected to contribute to the discussion on how to assess drought vulnerability and hopefully contribute to the development of drought early warning systems in Africa.

Description: Drought monitoring is a key component to mitigate impacts of droughts. Lack of reliable and up-to-date precipitation data sets is a common challenge across the globe. This study investigates different data sets and drought indicators on their capability to improve drought monitoring in Africa. The study was performed for four river basins located in different climatic regions (the Oum er-Rbia in Morocco, the Blue Nile in eastern Africa, the Upper Niger in western Africa, and the Limpopo in southeastern Africa) as well as the Greater Horn of Africa. The five precipitation data sets compared are the ECMWF ERA-Interim reanalysis, the Tropical Rainfall Measuring Mission satellite monthly rainfall product 3B-43, the Global Precipitation Climatology Centre gridded precipitation data set, the Global Precipitation Climatology Project Global Monthly Merged Precipitation Analyses, and the Climate Prediction Center Merged Analysis of Precipitation. The set of drought indicators used includes the Standardized Precipitation Index, the Standardized Precipitation-Evaporation Index, and Soil Moisture Anomalies. A comparison of the annual cycle and monthly precipitation time series shows a good agreement in the timing of the rainy seasons. The main differences between the data sets are in the ability to represent the magnitude of the wet seasons and extremes. Moreover, for the areas affected by drought, all the drought indicators agree on the time of drought onset and recovery although there is disagreement on the extent of the affected area. In regions with limited rain gauge data the estimation of the different drought indicators is characterized by a higher uncertainty. Further comparison suggests that the main source of differences in the computation of the drought indicators is the uncertainty in the precipitation data sets rather than the estimation of the distribution parameters of the drought indicators.