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Döll, P.; Krol, M.; Fuhr, D.; Gaiser, T.; Herfort, J.; Höynck, S.; Jaeger, A.; Külls, C.; Mendiondo, E.M.; Printz, A.; others |
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Title |
Integrated scenarios of regional development in Ceará and Piauí |
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2003 |
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Global Change and Regional Impacts |
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19-41 |
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Springer, Berlin, Heidelberg |
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THL @ christoph.kuells @ Doll2003integrated |
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39 |
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Author |
Doulgeris, C.; Tziritis, E.; Pisinaras, V.; Panagopoulos, A.; Külls, C. |
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Title |
Prediction of seawater intrusion to coastal aquifers based on non-dimensional diagrams |
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Conference Article |
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Year |
2020 |
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EGU Geophysical Abstracts |
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4073 |
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THL @ christoph.kuells @ Doulgeris2020prediction |
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41 |
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Author |
Dutova, E.M.; Nikitenkov, A.N.; Pokrovskiy, V.D.; Banks, D.; Frengstad, B.S.; Parnachev, V.P. |
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Title |
Modelling of the dissolution and reprecipitation of uranium under oxidising conditions in the zone of shallow groundwater circulation |
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Journal Article |
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2017 |
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Journal of Environmental Radioactivity |
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178-179 |
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63-76 |
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Keywords |
Groundwater, Hydrochemical modelling, Mineralisation, Natural uranium, Ore, Solubility |
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Abstract |
Generic hydrochemical modelling of a grantoid-groundwater system, using the Russian software “HydroGeo”, has been carried out with an emphasis on simulating the accumulation of uranium in the aqueous phase. The baseline model run simulates shallow granitoid aquifers (U content 5 ppm) under conditions broadly representative of southern Norway and southwestern Siberia: i.e. temperature 10 °C, equilibrated with a soil gas partial CO2 pressure (PCO2, open system) of 10−2.5 atm. and a mildly oxidising redox environment (Eh = +50 mV). Modelling indicates that aqueous uranium accumulates in parallel with total dissolved solids (or groundwater mineralisation M – regarded as an indicator of degree of hydrochemical evolution), accumulating most rapidly when M = 550–1000 mg L−1. Accumulation slows at the onset of saturation and precipitation of secondary uranium minerals at M = c. 1000 mg L−1 (which, under baseline modelling conditions, also corresponds approximately to calcite saturation and transition to Na-HCO3 hydrofacies). The secondary minerals are typically “black” uranium oxides of mixed oxidation state (e.g. U3O7 and U4O9). For rock U content of 5–50 ppm, it is possible to generate a wide variety of aqueous uranium concentrations, up to a maximum of just over 1 mg L−1, but with typical concentrations of up to 10 μg L−1 for modest degrees of hydrochemical maturity (as indicated by M). These observations correspond extremely well with real groundwater analyses from the Altai-Sayan region of Russia and Norwegian crystalline bedrock aquifers. The timing (with respect to M) and degree of aqueous uranium accumulation are also sensitive to Eh (greater mobilisation at higher Eh), uranium content of rocks (aqueous concentration increases as rock content increases) and PCO2 (low PCO2 favours higher pH, rapid accumulation of aqueous U and earlier saturation with respect to uranium minerals). |
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0265-931x |
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THL @ christoph.kuells @ dutova_modelling_2017 |
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114 |
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Author |
Edmunds, W.M.; Shand, P.; Hart, P.; Ward, R.S. |
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Title |
The natural (baseline) quality of groundwater: a UK pilot study |
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Journal Article |
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Year |
2003 |
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Science of The Total Environment |
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310 |
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1 |
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25-35 |
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Baseline quality, Groundwater, Hydrogeochemistry, Monitoring, Water Policy |
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Knowledge of the natural baseline quality of groundwaters is an essential prerequisite for understanding pollution and for imposing regulatory limits. The natural baseline of groundwaters may show a range of concentrations depending on aquifer mineralogy, facies changes, flow paths and residence time. The geochemical controls on natural concentrations are discussed and an approach to defining baseline concentrations using geochemical and statistical tools is proposed. The approach is illustrated using a flowline from the Chalk aquifer in Berkshire, UK where aerobic and anaerobic sections of the aquifer are separately considered. The baseline concentrations for some elements are close to atmospheric values whereas others evolve through time-dependent water–rock interaction. Certain solutes (K, NH4+), often considered contaminants, reach naturally high concentrations due to geochemical controls; transition metal concentrations are generally low, although their concentrations may be modified by redox controls. It is recommended that the baseline approach be incorporated into future management strategies, notably monitoring. |
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0048-9697 |
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THL @ christoph.kuells @ edmunds_natural_2003 |
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166 |
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Author |
Eliades, M.; Bruggeman, A.; Djuma, H.; Christofi, C.; Kuells, C. |
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Title |
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 |
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2022 |
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Water |
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14 |
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5 |
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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. |
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2073-4441 |
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THL @ christoph.kuells @ Marinos2022 |
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82 |
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