| Author |
Title |
Year |
Publication |
Volume |
Pages |
| Eliades, M.; Bruggeman, A.; Djuma, H.; Christofi, C.; Kuells, C. |
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 |
2022 |
Water |
14 |
|
| Aldawsari, S.; Kampmann, R.; Harnisch, J.; Rohde, C. |
Setting Time, Microstructure, and Durability Properties of Low Calcium Fly Ash/Slag Geopolymer: A Review |
2022 |
Materials |
15 |
|
| Eliades, M.; Bruggeman, A.; Djuma, H.; Christofi, C.; Kuells, C. |
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 |
2022 |
Water |
14 |
|
| Benites Lazaro, L.L.; Bellezoni, R.; Puppim de Oliveira, J.; Jacobi, P.R.; Giatti, L. |
Ten Years of Research on the Water-Energy-Food Nexus: An Analysis of Topics Evolution |
2022 |
Frontiers in Water |
4 |
|
| Illgen, M.; Ackermann, H. |
|
2019 |
Urban Flood Prevention: Technical and Institutional Aspects from Chinese and German Perspective |
|
173-193 |
| Severi, A.; Masoudian, M.; Kordi, E.; Roettcher, K. |
Discharge coefficient of combined-free over-under flow on a cylindrical weir-gate |
2015 |
ISH Journal of Hydraulic Engineering |
21 |
42-52 |
| de Jong, I.J.H.; Arif, S.S.; Gollapalli, P.K.R.; Neelam, P.; Nofal, E.R.; Reddy, K.Y.; Röttcher, K.; Zohrabi, N. |
Improving agricultural water productivity with a focus on rural transformation* |
2021 |
Irrigation and Drainage |
70 |
458-469 |
| Röttcher, K. |
|
2018 |
Risikomanagement und Nachhaltigkeit in der Wasserwirtschaft: Erfolgreiche Navigation durch die Komplexität und Dynamik des Risikos |
|
165-174 |
| Stone, A.E.C.; Edmunds, W.M. |
Naturally-high nitrate in unsaturated zone sand dunes above the Stampriet Basin, Namibia |
2014 |
Journal of Arid Environments |
105 |
41-51 |
| Aderemi, B.A.; Olwal, T.O.; Ndambuki, J.M.; Rwanga, S.S. |
Groundwater levels forecasting using machine learning models: A case study of the groundwater region 10 at Karst Belt, South Africa |
2023 |
Systems and Soft Computing |
5 |
200049 |
