Creation of an Exceptional Natural Phenomenon of Chains of Dunes and Lagoons through a Rare Balance of Five Key Elements in the National Park Lençóis Maranhenses in the Northeast of Brazil: Sand, Rain, Wind, River and Vegetation – An Artistic Approach (Published)
During our travels in the State of Maranhão in the northeast of Brazil, we explored the region of the National Park Lençóis Maranhenses in 2012 and 2013 before crossing the park during 5 days in September 2013 with the aim to produce nature art photography and organize subsequent itinerant exhibition throughout the country and abroad. We could confirm in loco the creation and constant modification of an exceptional natural phenomenon of chains of dunes and lagoons through a rare balance of five key elements in the park: sand, rain, wind, river and vegetation. Questions were raised and answers need to be found. Where is the sand coming from? What are the roles of the tides? How is the wind transforming the dunes? What are the natural lagoons or water ponds that exist in the middle of the dunes? What is the role of the vegetation? The dunes are in constant movement, what is their annual rate of dislocation? Is the balance of the five key elements to recreate the phenomenon threatened at present time or in the future, for instant due to ongoing, negative climate changes? A special approach was taken, as the production of nature photography of the dunes and lagoons in the park allowed us to know and observe the vast park area very closely. For the consecution of the aim of the research, we collected data based on bibliographic research, extents field studies in the area of the Lençóis Maranhenses National Park in 2012 and 2013, while conducting interviews with the habitants of the three communities living in the middle of the park and realizing artistic productions of nature photography and itinerant exhibitions to accompany the process of creation of dunes and lagoons in the park. We concluded that the balance of the five key elements to recreate the phenomenon depends on some fundamental factors such as, for instant, the same direction of the steady winds throughout the year, the elevation of the groundwater level due to rainfall during the month of January until July and the drying out of the water ponds during the month of July to December. We could distinguish the existence of free dunes inside the park and the fixed dunes on the Southern borders of the park and near to the village Atins. An important role plays the vegetation, that are fixing the dunes and delimitating the area of the park as further crowing of dunes is inhibited beyond theses areas due to the fixation of the dunes by vegetation. Furthermore, vegetation can deviate the direction of the winds, which might result in some cases in accumulation of a great amount of sand where vegetation was able to fix itself on the surface of a dune (the so called shadow dunes). In the first six months, due to rainfall, elevated groundwater level causing the creation of lagoons or water ponds, the free dunes in the park are almost not migrating, whereas during the months between July and December, with the drying out of the lagoons, sinking of the groundwater level and the continuing steady winds, the free dunes are migrating and moving in average 20m per year. The change of the landscape is confirmed by members of the three families living in the middle of the park, the Paulos, the Britos and the habitants of Baixa Grande during interviews. In the dry period of the year without rainfall, algae and vegetation can be found on the bottom of the lagoons and serve as food for domestic animals as pigs, horses and sheeps that are walking free inside the park. One scenario in the future is that the crossing of the park might be prohibit by the park administration alleging environmental prejudice to the balance of the park, as well as dust left behind while camping inside the park. Based on our experience, this kind of alternative tourism is not threatening the environment, as, for instant, we did not see any remains, and nothing was left behind by ourselves during the crossing and due to the fact that only few people are entering the park by food. As the results of our research show, the exceptional natural phenomenon of chains of dunes and lagoons through a rare balance of five key elements in the park: sand, rain, wind, river and vegetation continuous to be intact and is not threatened, even not due to climate changes that occurred in this area. In recent years, it could be observed that, due to a dryer year with less rain occurrence during the month of January to July, the lagoons dried out in the subsequence months very quickly. Some lagoons contain fish. Even drying out (in the case of the not perennial water ponds) in the second half of the year and located in the middle of the park with no other water source visible next to it, the fish reappears in the following rainy season at the beginning of the year. One explanation is the possible ability of the fish to adapt to the situation by digging themselves into the sand into ground water layers where they are able to survive. Future research needs to be carried out to accompany closely the recreation and constant modification of an exceptional natural phenomenon of chains of dunes and lagoons through a rare balance of the five key elements needed.
Design of a Renewable Energy Output Prediction System for 1000mw Solar-Wind Hybrid Power Plant (Published)
Problems associated with non-renewable energy sources such as fossil fuels make it necessary to move to cleaner renewable energy sources such as wind and solar. But the wind and sun are both intermittent sources of energy therefore accurate forecasts of wind and solar power are necessary to ensure the safety, stability and economy of utilizing these resources in large scale power generation. In this study, five meteorological parameters namely Temperature, Rainfall, Dew Point, Relative Humidity and Cloud Cover were collected for the year 2012 and used to predict wind and solar power output in Jos, Nigeria. The study used prediction algorithms such as Regression techniques and Artificial Neural Networks to predict the output of a 1000mW Solar-Wind Hybrid Power Plant over a period of one year. Individual prediction techniques were compared and Isotonic Regression was found to have the highest accuracy with errors of 40.5% in predicting solar power generation and 35.4% in predicting wind power generation. The relatively high levels of error are attributed to several limitations of the research work.