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Author |
Lim, S.; Chase, B.M.; Chevalier, M.; Reimer, P.J. |
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Title |
50,000years of vegetation and climate change in the southern Namib Desert, Pella, South Africa |
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Journal Article |
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Year |
2016 |
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Palaeogeography, Palaeoclimatology, Palaeoecology |
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451 |
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197-209 |
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Climate reconstruction, Late Quaternary, Namib Desert, Pollen, Rock hyrax middens, South Africa |
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This paper presents the first continuous pollen record from the southern Namib Desert spanning the last 50,000years. Obtained from rock hyrax middens found near the town of Pella, South Africa, these data are used to reconstruct vegetation change and quantitative estimates of temperature and aridity. Results indicate that the last glacial period was characterised by increased water availability at the site relative to the Holocene. Changes in temperature and potential evapotranspiration appear to have played a significant role in determining the hydrologic balance. The record can be considered in two sections: 1) the last glacial period, when low temperatures favoured the development of more mesic Nama-Karoo vegetation at the site, with periods of increased humidity concurrent with increased coastal upwelling, both responding to lower global/regional temperatures; and 2) the Holocene, during which time high temperatures and potential evapotranspiration resulted in increased aridity and an expansion of the Desert Biome. During this latter period, increases in upwelling intensity created drier conditions at the site. Considered in the context of discussions of forcing mechanisms of regional climate change and environmental dynamics, the results from Pella stand in clear contrast with many inferences of terrestrial environmental change derived from regional marine records. Observations of a strong precessional signal and interpretations of increased humidity during phases of high local summer insolation in the marine records are not consistent with the data from Pella. Similarly, while high percentages of Restionaceae pollen has been observed in marine sediments during the last glacial period, they do not exceed 1% of the assemblage from Pella, indicating that no significant expansion of the Fynbos Biome has occurred during the last 50,000years. These findings pose interesting questions regarding the nature of environmental change in southwestern Africa, and the significance of the diverse records that have been obtained from the region. |
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0031-0182 |
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THL @ christoph.kuells @ lim_50000years_2016 |
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107 |
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Pham, Q.-N.; Nguyen, T.-C.; Ta, T.-T.; Tran, T.-L. |
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Title |
Comprehensive approach to sustainable groundwater management in semi-arid Ninh Thuan plain, Vietnam |
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Journal Article |
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2023 |
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Groundwater for Sustainable Development |
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23 |
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101031 |
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Climate change, Groundwater, Managed aquifer recharge (MAR), Modeling, Sea level rise, Seawater intrusion, Sustainable groundwater management |
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Vietnam is a country with a long coastline and a high population density residing in the coastal plains. The largest dry area in Vietnam, the coastal plain of Ninh Thuan province, always lacks water in the first dry months of the year (Jan., Feb., Mar., and Apr.). Groundwater is an extremely valuable resource for supplies at this time. Therefore, the objective of this study is to establish a comprehensive approach to sustainable groundwater management in this semi-arid region. This approach is not only mitigating the negative impacts of factors such as climate change, sea level rise, and socio-economic development but also suggesting measures for management of aquifer recharge. A groundwater model for a 3-layer system with variable density flow SEAWAT is built to predict the impacts of climate change and sea level rise without a change in groundwater abstraction. This model helps to understand the trend of salt intrusion and lowering groundwater level in the study area. Afterwards, scenarios with different ground water abstraction and groundwater development such as ground dam, infiltration basin have been set up to meet the demands of socio-economic development in the future. Predicted results will show the impacts of the groundwater systems in the area such as groundwater level change, and saltwater intrusion. Controlled groundwater abstraction and some measures of groundwater development such as infiltration basin, underground dam would allow for an increase of up to 50000m3/day in the year 2050 without negative impacts on the aquifer system. |
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2352-801x |
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THL @ christoph.kuells @ pham_comprehensive_2023 |
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174 |
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Mekuria, W.; Tegegne, D. |
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Water harvesting |
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2023 |
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Encyclopedia of Soils in the Environment (Second Edition) |
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593-607 |
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Climate change, Ecosystem services, Environmental benefits, Population growth, Resilient community, Resilient environment, Socio-economic benefits, Urbanizations, Water harvesting, Water quality, Water security |
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Water harvesting is the intentional collection and concentration of rainwater and runoff to offset irrigation demands. Secondary benefits include decreased flood and erosion risk. Water harvesting techniques include micro- and macro-catchment systems, floodwater harvesting, and rooftop and groundwater harvesting. The techniques vary with catchment type and size, and the method of water storage. Micro-catchment water harvesting, for example, requires the development of small structures and targets increased water delivery and storage to the root zone whereas macro-catchment systems collect runoff water from large areas. The sustainability of water harvesting techniques at the local level are usually constrained by several factors such as labor, construction costs, loss of productive land, and maintenance, suggesting that multiple solutions are required to sustain the benefits of water harvesting techniques. |
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Academic Press |
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Oxford |
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Goss, M.J.; Oliver, M. |
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978-0-323-95133-3 |
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THL @ christoph.kuells @ Mekuria2023593 |
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225 |
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Author |
Mekuria, W.; Tegegne, D. |
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Title |
Water harvesting |
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2023 |
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Encyclopedia of Soils in the Environment (Second Edition) |
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593-607 |
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Climate change, Ecosystem services, Environmental benefits, Population growth, Resilient community, Resilient environment, Socio-economic benefits, Urbanizations, Water harvesting, Water quality, Water security |
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Abstract |
Water harvesting is the intentional collection and concentration of rainwater and runoff to offset irrigation demands. Secondary benefits include decreased flood and erosion risk. Water harvesting techniques include micro- and macro-catchment systems, floodwater harvesting, and rooftop and groundwater harvesting. The techniques vary with catchment type and size, and the method of water storage. Micro-catchment water harvesting, for example, requires the development of small structures and targets increased water delivery and storage to the root zone whereas macro-catchment systems collect runoff water from large areas. The sustainability of water harvesting techniques at the local level are usually constrained by several factors such as labor, construction costs, loss of productive land, and maintenance, suggesting that multiple solutions are required to sustain the benefits of water harvesting techniques. |
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Academic Press |
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Oxford |
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Goss, M.J.; Oliver, M. |
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978-0-323-95133-3 |
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THL @ christoph.kuells @ Mekuria2023593 |
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265 |
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Author |
Merembayev, T.; Yunussov, R.; Yedilkhan, A. |
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Title |
Machine Learning Algorithms for Stratigraphy Classification on Uranium Deposits |
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Journal Article |
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2019 |
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Procedia Computer Science |
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150 |
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46-52 |
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classification, geophysics logging data, machine learning, stratigraphy, uranium deposit |
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Machine learning today becomes more and more effective instrument to solve many particular problems, where there are difficulties to apply well known and described math model. In other words – it is a great tool to describe non-linear phenomena. We tried to use this technique to improve existing process of stratigraphy, and reduce costs on site by applying computer leaded predictions on the basis of existing on-field collected data. Article describes usage of machine learning algorithms for stratigraphy boundaries classification based on geophysics logging data for uranium deposit in Kazakhstan. Correct marking of stratigraphy from geophysics logging data is complex non-linear task. To solve this task we applied several algorithms of machine learning: random forest, logistic regression, gradient boosting, k nearest neighbour and XGBoost. |
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1877-0509 |
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THL @ christoph.kuells @ merembayev_machine_2019 |
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113 |
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