| Records |
| Author |
Eliades, M.; Bruggeman, A.; Djuma, H.; Christofi, C.; Kuells, C. |
| 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 |
Type |
Journal Article |
| Year |
2022 |
Publication |
Water |
Abbreviated Journal |
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| Volume |
14 |
Issue |
5 |
Pages |
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| Keywords |
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| 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. |
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2073-4441 |
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| Call Number |
THL @ christoph.kuells @ w14050734 |
Serial |
81 |
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| Author |
Aldawsari, S.; Kampmann, R.; Harnisch, J.; Rohde, C. |
| Title |
Setting Time, Microstructure, and Durability Properties of Low Calcium Fly Ash/Slag Geopolymer: A Review |
Type |
Journal Article |
| Year |
2022 |
Publication |
Materials |
Abbreviated Journal |
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| Volume |
15 |
Issue |
3 |
Pages |
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| Abstract |
Ordinary Portland cement (OPC) is known for its significant contribution to carbon dioxide emissions. Geopolymer has a lower footprint in terms of CO2 emissions and has been considered as an alternative for OPC. A well-developed understanding of the use of fly-ash-based and slag-based geopolymers as separate systems has been reached in the literature, specifically regarding their mechanical properties. However, the microstructural and durability of the combined system after slag addition introduces more interactive gels and complex microstructural formations. The microstructural changes of complex blended systems contribute to significant advances in the durability of fly ash/slag geopolymers. In the present review, the setting time, microstructural properties (gel phase development, permeability properties, shrinkage behavior), and durability (chloride resistance, sulfate attack, and carbonatation), as discussed literature, are studied and summarized to simplify and draw conclusions. |
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1996-1944 |
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| Call Number |
THL @ christoph.kuells @ ma15030876 |
Serial |
84 |
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| Author |
Eliades, M.; Bruggeman, A.; Djuma, H.; Christofi, C.; Kuells, C. |
| 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 |
Type |
Journal Article |
| Year |
2022 |
Publication |
Water |
Abbreviated Journal |
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| Volume |
14 |
Issue |
5 |
Pages |
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| Keywords |
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| 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. |
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2073-4441 |
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no |
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THL @ christoph.kuells @ w14050734 |
Serial |
85 |
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| Author |
Benites Lazaro, L.L.; Bellezoni, R.; Puppim de Oliveira, J.; Jacobi, P.R.; Giatti, L. |
| Title |
Ten Years of Research on the Water-Energy-Food Nexus: An Analysis of Topics Evolution |
Type |
Journal Article |
| Year |
2022 |
Publication |
Frontiers in Water |
Abbreviated Journal |
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| Volume |
4 |
Issue |
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Pages |
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no |
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THL @ christoph.kuells @ article |
Serial |
86 |
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| Author |
de Jong, I.J.H.; Arif, S.S.; Gollapalli, P.K.R.; Neelam, P.; Nofal, E.R.; Reddy, K.Y.; Röttcher, K.; Zohrabi, N. |
| Title |
Improving agricultural water productivity with a focus on rural transformation* |
Type |
Journal Article |
| Year |
2021 |
Publication |
Irrigation and Drainage |
Abbreviated Journal |
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| Volume |
70 |
Issue |
3 |
Pages |
458-469 |
| Keywords |
irrigation efficiency, water productivity, rural transformation, efficacité de l’irrigation, productivité de l’eau, transformation rurale |
| Abstract |
ABSTRACT As a result of population growth, economic development and climate change, feeding the world and providing water security will require important changes in the technologies, institutions, policies and incentives that drive present-day water management, as captured in Goal 6.4 of the Millennium Development Goals. Irrigation is the largest and most inefficient water user, and there is an expectation that even small improvements in agricultural water productivity will improve water security. This paper argues that improvements in irrigation water productivity involves a complex and comprehensive rural transformation that goes beyond mere promotion of water saving technologies. Many of the measures to improve water productivity require significant changes in the production systems of farmers and in the support provided to them. Looking forward, water use and competition over water are expected to further increase. By 2025, about 1.8 billion people will be living in regions or countries with absolute water scarcity. Demand for water will rise exponentially, while supply becomes more erratic and uncertain, prompting the need for significant shifts of inter-sectoral water allocation to support continued economic growth. Advances in the use of remote sensing technologies will make it increasingly possible to cost-effectively and accurately estimate crop evapotranspiration from farmers’ fields. |
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THL @ christoph.kuells @ https://doi.org/10.1002/ird.2451 |
Serial |
89 |
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| Author |
Stone, A.E.C.; Edmunds, W.M. |
| Title |
Naturally-high nitrate in unsaturated zone sand dunes above the Stampriet Basin, Namibia |
Type |
Journal Article |
| Year |
2014 |
Publication |
Journal of Arid Environments |
Abbreviated Journal |
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| Volume |
105 |
Issue |
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Pages |
41-51 |
| Keywords |
Kalahari, Namibia, Nitrate in the unsaturated zone, Stampriet Basin, Transboundary basin, Unsaturated zone recharge |
| Abstract |
Elevated groundwater nitrate levels are common in drylands, often in excess of WHO guidelines, with concern for human and animal health. In light of recent attempts to identify nitrate sources in the Kalahari this paper presents the first unsaturated zone (USZ) nitrate profiles and recharge rate estimates for the important transboundary Stampriet Basin, alongside the first rainfall chemistry records. Elevated subsurface nitrate reaches 100–250 and 250–525 mg/L NO3–N, with NO3–N/Cl of 4–12, indicating input above evapotranspiration. Chloride mass balance recharge rates range from 4 to 27 mm/y, indicating a vertical movement of these nitrate pulses toward the water table over multi-decadal timescales. These profiles are sampled from dune crests, away from high concentrations of animals and without termite mounds. Given low-density animal grazing is unlikely to contribute consistent spot-scale nitrate over decades, these profiles give an initial estimate of naturally-produced concentrations. This insight is important for the management of the Stampriet Basin and wider Kalahari groundwater. This study expands our knowledge about elevated nitrate in dryland USZs, demonstrating that it can occur as pulses, probably in response to transient vegetation cover and that it is not limited to long-residence time USZs with very limited downward moisture flux (recharge). |
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0140-1963 |
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no |
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THL @ christoph.kuells @ Stone201441 |
Serial |
218 |
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| Author |
Aderemi, B.A.; Olwal, T.O.; Ndambuki, J.M.; Rwanga, S.S. |
| Title |
Groundwater levels forecasting using machine learning models: A case study of the groundwater region 10 at Karst Belt, South Africa |
Type |
Journal Article |
| Year |
2023 |
Publication |
Systems and Soft Computing |
Abbreviated Journal |
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5 |
Issue |
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Pages |
200049 |
| Keywords |
Artificial intelligence, Forecasting model, Groundwater levels, Machine learning, Neural networks, Rainfall, Regression, Temperature, Time series |
| 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. |
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Edition |
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| ISSN |
2772-9419 |
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no |
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THL @ christoph.kuells @ Aderemi2023200049 |
Serial |
219 |
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| Author |
Rajfur, M.; Kłos, A.; Wacławek, M. |
| Title |
Sorption properties of algae Spirogyra sp. and their use for determination of heavy metal ions concentrations in surface water |
Type |
Journal Article |
| Year |
2010 |
Publication |
Bioelectrochemistry |
Abbreviated Journal |
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| Volume |
80 |
Issue |
1 |
Pages |
81-86 |
| Keywords |
Biomonitoring, Heavy metal ions, Algae sp., Sorption kinetics, Langmuir isotherm |
| Abstract |
Kinetics of heavy-metal ions sorption by alga Spirogyra sp. was evaluated experimentally in the laboratory, using both the static and the dynamic approach. The metal ions – Mn2+, Cu2+, Zn2+ and Cd2+ – were sorbed from aqueous solutions of their salts. The static experiments showed that the sorption equilibria were attained in 30min, with 90-95% of metal ions sorbed in first 10min of each process. The sorption equilibria were approximated with the Langmuir isotherm model. The algae sorbed each heavy metal ions proportionally to the amount of this metal ions in solution. The experiments confirmed that after 30min of exposition to contaminated water, the concentration of heavy metal ions in the algae, which initially contained small amounts of these metal ions, increased proportionally to the concentration of metal ions in solution. The presented results can be used for elaboration of a method for classification of surface waters that complies with the legal regulations. |
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1567-5394 |
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| Notes |
A Selection of Papers presented at the 4th International Workshop on Surface Modification for Chemical and Biochemical Sensing (SMCBS 2009) |
Approved |
no |
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THL @ christoph.kuells @ Rajfur201081 |
Serial |
283 |
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Konapala, G.; Mishra, A.K.; Wada, Y.; Mann, M.E. |
| Title |
Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation |
Type |
Journal Article |
| Year |
2020 |
Publication |
Nature Communications |
Abbreviated Journal |
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| Volume |
11 |
Issue |
1 |
Pages |
3044 |
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| Abstract |
Both seasonal and annual mean precipitation and evaporation influence patterns of water availability impacting society and ecosystems. Existing global climate studies rarely consider such patterns from non-parametric statistical standpoint. Here, we employ a non-parametric analysis framework to analyze seasonal hydroclimatic regimes by classifying global land regions into nine regimes using late 20th century precipitation means and seasonality. These regimes are used to assess implications for water availability due to concomitant changes in mean and seasonal precipitation and evaporation changes using CMIP5 model future climate projections. Out of 9 regimes, 4 show increased precipitation variation, while 5 show decreased evaporation variation coupled with increasing mean precipitation and evaporation. Increases in projected seasonal precipitation variation in already highly variable precipitation regimes gives rise to a pattern of “seasonally variable regimes becoming more variable”. Regimes with low seasonality in precipitation, instead, experience increased wet season precipitation. |
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English |
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2041-1723 |
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THL @ christoph.kuells @ Konapala2020 |
Serial |
284 |
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| Author |
Wolfe, P. |
| Title |
The Simplex Method For Quadratic Programming |
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Journal Article |
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1959 |
Publication |
Econometrica |
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27 |
Issue |
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170 |
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THL @ christoph.kuells @ Wolfe1959 |
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285 |
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