|
|
Holmes, M., Campbell, E. E., Wit, M. de, & Taylor, J. C. (2023). Can diatoms be used as a biomonitoring tool for surface and groundwater?: Towards a baseline for Karoo water. South African Journal of Botany, 161, 211–221.
Abstract: The environmental risks from shale gas extraction through the unconventional method of ‘fracking’ are considerable and impact on water supplies below and above ground. Since 2010 the recovery of natural shale gas through fracking has been proposed in parts of the fragile semi-arid ecosystems that make up the Karoo biome in South Africa. These unique ecosystems are heavily reliant on underground water, intermittent and ephemeral springs, which are at great risk of contamination by fracking processes. Diatoms are present in all water bodies and reflect aspects of the environment in which they are located. As the possibility of fracking has not been removed, the aim of the project was to determine if diatoms could be used for rapid biomonitoring of underground and surface waters in the Karoo. Over a period of 24 months, water samples and diatom species were collected simultaneously from 65 sites. A total of 388 diatom taxa were identified from 290 samples with seasonal and substrate variation affecting species composition but not the environmental information. Species diversity information, on the other hand, often varied significantly between substrates within a single sample. Analysis using CCA established that the diatom composition was affected by lithium, oxidized nitrogen, electrical conductivity, and sulphate levels in the sampled water. We conclude that changes in diatom community composition in the Karoo do reflect the water chemistry and could be useful as bioindicators.
|
|
|
|
Aderemi, B. A., Olwal, T. O., Ndambuki, J. M., & Rwanga, S. S. (2023). Groundwater levels forecasting using machine learning models: A case study of the groundwater region 10 at Karst Belt, South Africa. Systems and Soft Computing, 5, 200049.
Abstract: The crucial role which groundwater resource plays in our environment and the overall well-being of all living things can not be underestimated. Nonetheless, mismanagement of resources, over-exploitation, inadequate supply of surface water and pollution have led to severe drought and an overall drop in groundwater resources’ levels over the past decades. To address this, a groundwater flow model and several mathematical data-driven models have been developed for forecasting groundwater levels. However, there is a problem of unavailability and scarcity of the on-site input data needed by the data-driven models to forecast the groundwater level. Furthermore, as a result of the dynamics and stochastic characteristics of groundwater, there is a need for an appropriate, accurate and reliable forecasting model to solve these challenges. Over the years, the broad application of Machine Learning (ML) and Artificial Intelligence (AI) models are gaining attraction as an alternative solution for forecasting groundwater levels. Against this background, this article provides an overview of forecasting methods for predicting groundwater levels. Also, this article uses ML models such as Regressions Models, Deep Auto-Regressive models, and Nonlinear Autoregressive Neural Networks with External Input (NARX) to forecast groundwater levels using the groundwater region 10 at Karst belt in South Africa as a case study. This was done using Python Mx. Version 1.9.1., and MATLAB R2022a machine learning toolboxes. Moreover, the Coefficient of Determination (R2);, Root Mean Square Error (RMSE), Mutual Information gain, Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), Mean Absolute Error (MAE), and the Mean Absolute Scaled Error (MASE)) models were the forecasting statistical performance metrics used to assess the predictive performance of these models. The results obtained showed that NARX and Support Vector Machine (SVM) have higher performance metrics and accuracy compared to other models used in this study.
|
|
|
|
YI, Z. -ji, LIAN, B., YANG, Y. -qun, & ZOU, J. -ling. (2009). Treatment of simulated wastewater from in situ leaching uranium mining by zerovalent iron and sulfate reducing bacteria. Transactions of Nonferrous Metals Society of China, 19, 840.
Abstract: Batch and column experiments were conducted to determine whether zerovalent iron (ZVI) and sulfate reducing bacteria (SRB) can function synergistically and accelerate pollutant removal. Batch experiments suggest that combining ZVI with SRB can enhance the removal of U(?) synergistically. The removal rate of U(?) in the ZVI+SRB combining system is obviously higher than the total rate of ZVI system and SRB system with a difference of 13.4% at t=2 h and 29.9% at t=4 h. Column experiments indicate that the reactor filled with both ZVI and SRB biofilms is of better performance than the SRB bioreactor in wastewater basification, desulfurization and U(?) fixation. The results imply that the ZVI+SRB permeable reactive barrier may be a promising method for treating subsurface uranium contamination.
|
|
|
|
Ubierna, J. A. J. (1998). Tunnel heritage in Spain: Roots of the underground. Tunnelling and Underground Space Technology, 13(2), 131–141.
Abstract: Spain has deep roots in the underground. The territory of myth and legend, of cave and tunnel, has existed in Spain since that ancient time overwhelmed with shreds of fog, where all was myth around heros like Túbal Hércules, Gárgoris and Abidis. The underground evokes strong links with life and death, light and darkness, and has served as a source of inspiration for art through the centuries. The history of tunnels in Spain reflects the mosaic of cultures that have inhabited Iberia from prehistoric times till today. This contribution on the subterranean History of Spain traces the country’s heritage in the form of natural caves, troglodyte dwellings, mining, crypts, galleries in fortresses and castles, aqueducts, qanats, cellars, and other landmarks.
|
|
|
|
Carrión, A., & Fornes, A. (2016). Underground medieval water distribution network in a Spanish town. Tunnelling and Underground Space Technology, 51, 90–97.
Abstract: The city of Alcudia de Crespins, in the centre of the Valencia province (east of Spain), has an exceptional water distribution system that in the past served fresh water to many houses in the town. This system is formed by more than one km of tunnels and underground cisterns, and dates probably in the late medieval times, while it has been in use and suffering modifications until 1955. This paper presents the structure and characteristics of such exceptional system, and explains the functioning parameters of the infrastructure.
|
|
|
|
Arya, S., & Kumar, A. (2023). Evaluation of stormwater management approaches and challenges in urban flood control. Urban Climate, 51, 101643.
Abstract: Across the globe, the damage caused by urban floods has increased manifold. The unchecked development has encroached the natural drainage, and the conventional drainage systems are inadequate in handling the augmented hydrological response. To counter this, a variety of approaches with the ability to adjust within the constraints of complex environments by managing surface runoff are being widely investigated and applied worldwide. These can put the flood water to better use, and the ecological balance may get restored. This review discusses recent progress made in the area of Green Infrastructure (GI), modelling tools that help in stormwater management, vulnerability analysis and flood risk assessment. Different ways of handling the problem are summarized through an extensive literature survey. The gaps and barriers that impede the implementation of stormwater management solutions and strategies for further improvement have also been presented. A case study of Gurugram city, India depicting the challenges being faced by urban flooding and the possible solutions through an expert survey is also presented.
|
|
|
|
Illgen, M., & Ackermann, H. (2019). In S. Köster, M. Reese, & J. ’e Zuo (Eds.), Urban Flood Prevention: Technical and Institutional Aspects from Chinese and German Perspective (pp. 173–193). Cham: Springer International Publishing.
Abstract: Today’s cities face the challenge of climate change adaptation worldwide. In this context, prevention of damage caused by flash floods plays an important role. This requires a cooperative pluvial flood risk management approach, which includes planning, technical, and administrative measures and involves preliminary flood risk analyses. This article outlines the main components of this risk management approach, which has proven its effectiveness in Europe. The recommendations formulated for this purpose are applicable or adaptable to regions with other constraints, such as China, for example.
|
|
|
|
Eliades, M., Bruggeman, A., Djuma, H., Christofi, C., & Kuells, C. (2022). Quantifying Evapotranspiration and Drainage Losses in a Semi-Arid Nectarine (Prunus persica var. nucipersica) Field with a Dynamic Crop Coefficient (Kc) Derived from Leaf Area Index Measurements. Water, 14(5).
Abstract: Quantifying evapotranspiration and drainage losses is essential for improving irrigation efficiency. The FAO-56 is the most popular method for computing crop evapotranspiration. There is, however, a need for locally derived crop coefficients (Kc) with a high temporal resolution to reduce errors in the water balance. The aim of this paper is to introduce a dynamic Kc approach, based on Leaf Area Index (LAI) observations, for improving water balance computations. Soil moisture and meteorological data were collected in a terraced nectarine (Prunus persica var. nucipersica) orchard in Cyprus, from 22 March 2019 to 18 November 2021. The Kc was derived as a function of the canopy cover fraction (c), from biweekly in situ LAI measurements. The use of a dynamic Kc resulted in Kc estimates with a bias of 17 mm and a mean absolute error of 0.8 mm. Evapotranspiration (ET) ranged from 41% of the rainfall (P) and irrigation (I) in the wet year (2019) to 57% of P + I in the dry year (2021). Drainage losses from irrigation (DR_I) were 44% of the total irrigation. The irrigation efficiency in the nectarine field could be improved by reducing irrigation amounts and increasing the irrigation frequency. Future studies should focus on improving the dynamic Kc approach by linking LAI field observations with remote sensing observations and by adding ground cover observations.
|
|
|
|
Eliades, M., Bruggeman, A., Djuma, H., Christofi, C., & Kuells, C. (2022). Quantifying Evapotranspiration and Drainage Losses in a Semi-Arid Nectarine (Prunus persica var. nucipersica) Field with a Dynamic Crop Coefficient (Kc) Derived from Leaf Area Index Measurements. Water, 14(5).
Abstract: Quantifying evapotranspiration and drainage losses is essential for improving irrigation efficiency. The FAO-56 is the most popular method for computing crop evapotranspiration. There is, however, a need for locally derived crop coefficients (Kc) with a high temporal resolution to reduce errors in the water balance. The aim of this paper is to introduce a dynamic Kc approach, based on Leaf Area Index (LAI) observations, for improving water balance computations. Soil moisture and meteorological data were collected in a terraced nectarine (Prunus persica var. nucipersica) orchard in Cyprus, from 22 March 2019 to 18 November 2021. The Kc was derived as a function of the canopy cover fraction (c), from biweekly in situ LAI measurements. The use of a dynamic Kc resulted in Kc estimates with a bias of 17 mm and a mean absolute error of 0.8 mm. Evapotranspiration (ET) ranged from 41% of the rainfall (P) and irrigation (I) in the wet year (2019) to 57% of P + I in the dry year (2021). Drainage losses from irrigation (DR_I) were 44% of the total irrigation. The irrigation efficiency in the nectarine field could be improved by reducing irrigation amounts and increasing the irrigation frequency. Future studies should focus on improving the dynamic Kc approach by linking LAI field observations with remote sensing observations and by adding ground cover observations.
|
|
|
|
Eliades, M., Bruggeman, A., Djuma, H., Christofi, C., & Kuells, C. (2022). Quantifying Evapotranspiration and Drainage Losses in a Semi-Arid Nectarine (Prunus persica var. nucipersica) Field with a Dynamic Crop Coefficient (Kc) Derived from Leaf Area Index Measurements. Water, 14(5).
Abstract: Quantifying evapotranspiration and drainage losses is essential for improving irrigation efficiency. The FAO-56 is the most popular method for computing crop evapotranspiration. There is, however, a need for locally derived crop coefficients (Kc) with a high temporal resolution to reduce errors in the water balance. The aim of this paper is to introduce a dynamic Kc approach, based on Leaf Area Index (LAI) observations, for improving water balance computations. Soil moisture and meteorological data were collected in a terraced nectarine (Prunus persica var. nucipersica) orchard in Cyprus, from 22 March 2019 to 18 November 2021. The Kc was derived as a function of the canopy cover fraction (c), from biweekly in situ LAI measurements. The use of a dynamic Kc resulted in Kc estimates with a bias of 17 mm and a mean absolute error of 0.8 mm. Evapotranspiration (ET) ranged from 41% of the rainfall (P) and irrigation (I) in the wet year (2019) to 57% of P + I in the dry year (2021). Drainage losses from irrigation (DR_I) were 44% of the total irrigation. The irrigation efficiency in the nectarine field could be improved by reducing irrigation amounts and increasing the irrigation frequency. Future studies should focus on improving the dynamic Kc approach by linking LAI field observations with remote sensing observations and by adding ground cover observations.
|
|
