Investigação dos processos hidrossedimentológicos em parcela experimental no semi-árido potiguar

In northeastern semiarid, seasonality on precipitation temporal distribution, high intensity storm events and inadequate management of native vegetation can promote soil erosion. Vegetation removal causes soil surface exposure, reduces soil water storage capacity and can be the source degradation processes. In this context, this approach aims to analyze water and soil erosion processes on a 250 m2 undisturbed experimental plot with native vegetation, slope 2.5% by using 2006 and 2007 monitoring data. The site was instrumented to monitor rainfall, overland flow runoff and erosion by using a 5 m³ tank downstream the plot. Soil erosion monitoring was made by transported sediment and organic matter collection after each event. Field infiltration experiments were made at 16 points randomly distributed within the plot area by using a constant head infiltrometer during drought and rainy seasons, respectively. Infiltration data revealed high spatial and temporal variability. It was observed that during the beginning of the rainy period, 77% of the events showed runoff coefficient less than 0.05. As the rainy season began, soil water increase produced annual species germination. High intensity storms resulted in runoff coefficients varying between 0.33 and 0.42. Once the annual species was established, it was observed that approximately 39% of the events produced no runoff, which reflects an increase on soil water retention capacity caused by the vegetation. A gradual runoff reduction during the rainy season emphasizes the effect of vegetative density increase. Soil erosion observed data allowed to fit an empirical relationship involving soil loss and precipitation height, which was used to analyze the plot installation impact on soil erosion. Observed soil loss in 2006 and 2007 was 230 Kg/ha and 54 Kg/ha, respectively

Análise da precipitação no semi-árido potiguar

The semiarid rainfall regime is northeastern Brazil is highly variable. Climate processes associated with rainfall are complex and their effects may represent extreme situations of drought or floods, which can have adverse effects on society and the environment. The regional economy has a significant agricultural component, which is strongly influenced by weather conditions. Maximum precipitation analysis is traditionally performed using the intensity-duration-frequency (IDF) probabilistic approach. Results from such analysis are typically used in engineering projects involving hydraulic structures such as drainage network systems and road structures. On the other hand, precipitation data analysis may require the adoption of some kind of event identification criteria. The minimum inter-event duration (IMEE) is one of the most used criteria. This study aims to analyze the effect of the IMEE on the obtained rain event properties. For this purpose, a nine-year precipitation time series (2002- 2011) was used. This data was obtained from an automatic raingauge station, installed in an environmentally protected area, Ecological Seridó Station. The results showed that adopted IMEE values has an important effect on the number of events, duration, event height, mean rainfall rate and mean inter-event duration. Furthermore, a higher occurrence of extreme events was observed for small IMEE values. Most events showed average rainfall intensity higher than 2 mm.h-1 regardless of IMEE. The storm coefficient of advance was, in most cases, within the first quartile of the event, regardless of the IMEE value. Time series analysis using partial time series made it possible to adjust the IDF equations to local characteristics

Estudo do balanço de umidade por meio de modelos regionais para o clima do passado e do futuro sobre a América do Sul

In the context of climate change over South America (SA) has been observed that the combination of high temperatures and rain more temperatures less rainfall, cause different impacts such as extreme precipitation events, favorable conditions for fires and droughts. As a result, these regions face growing threat of water shortage, local or generalized. Thus, the water availability in Brazil depends largely on the weather and its variations in different time scales. In this sense, the main objective of this research is to study the moisture budget through regional climate models (RCM) from Project Regional Climate Change Assessments for La Plata Basin (CLARIS-LPB) and combine these RCM through two statistical techniques in an attempt to improve prediction on three areas of AS: Amazon (AMZ), Northeast Brazil (NEB) and the Plata Basin (LPB) in past climates (1961-1990) and future (2071-2100). The moisture transport on AS was investigated through the moisture fluxes vertically integrated. The main results showed that the average fluxes of water vapor in the tropics (AMZ and NEB) are higher across the eastern and northern edges, thus indicating that the contributions of the trade winds of the North Atlantic and South are equally important for the entry moisture during the months of JJA and DJF. This configuration was observed in all the models and climates. In comparison climates, it was found that the convergence of the flow of moisture in the past weather was smaller in the future in various regions and seasons. Similarly, the majority of the SPC simulates the future climate, reduced precipitation in tropical regions (AMZ and NEB), and an increase in the LPB region. The second phase of this research was to carry out combination of RCM in more accurately predict precipitation, through the multiple regression techniques for components Main (C.RPC) and convex combination (C.EQM), and then analyze and compare combinations of RCM (ensemble). The results indicated that the combination was better in RPC represent precipitation observed in both climates. Since, in addition to showing values be close to those observed, the technique obtained coefficient of correlation of moderate to strong magnitude in almost every month in different climates and regions, also lower dispersion of data (RMSE). A significant advantage of the combination of methods was the ability to capture extreme events (outliers) for the study regions. In general, it was observed that the wet C.EQM captures more extreme, while C.RPC can capture more extreme dry climates and in the three regions studied.