Publications

@article{KRUGER2026134638,

title = {Reservoir-controlled stable isotope exchange fractionation at pore-scale in the unsaturated zone},

author = {Nina Kr\"{u}ger and Christoph K\"{u}lls},

url = {https://www.sciencedirect.com/science/article/pii/S002216942501978X},

doi = {https://doi.org/10.1016/j.jhydrol.2025.134638},

issn = {0022-1694},

year  = {2026},

date = {2026-01-01},

journal = {Journal of Hydrology},

volume = {665},

pages = {134638},

abstract = {Reservoir-controlled stable isotope exchange fractionation forces isotopic signatures of different waters to converge over time and has been incorporated into a one-dimensional numerical pore-space-differentiated isotope transport model. Over two years, the water stable isotope values of δ18O and δ2H were modeled within a soil profile of 1.80 m depth, with the pore continuum being discretized into fine, medium, and macropores. Equilibrium and kinetic isotope fractionation processes were described using the Craig-Gordon model. Results reveal that accounting for reservoir-controlled stable isotope exchange fractionation significantly affects model outcomes. Above the critical zone, reservoir-specific signature shifts of up to ±5.0 ‰ δ18O were observed, while below the critical zone, changes still reached up to ±3.0 ‰ δ18O. Interactions among fine, medium, and macropores drive reservoir-controlled isotope exchange, with the medium pores dominating the fractionation process, while temporarily activated macropores strongly influence isotopic signatures of percolating water. Reservoir-controlled exchange fractionation attenuates the variability of isotopic signatures in the unsaturated zone. This study highlights that accounting for reservoir-controlled exchange fractionation can significantly enhance the interpretation of soil water isotope data.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{LWEENDO2026104335,

title = {Land use/Land cover control on groundwater recharge: A multi-method assessment using remote sensing-based Water Balance in the Lusaka Aquifer, Zambia},

author = {Muumbe K. Lweendo and Benjamin Mapani and Kawawa Banda and Samuel Adelabu and Dimitrios Bassukas and Christoph K\"{u}lls},

url = {https://www.sciencedirect.com/science/article/pii/S1474706526000689},

doi = {https://doi.org/10.1016/j.pce.2026.104335},

issn = {1474-7065},

year  = {2026},

date = {2026-01-01},

journal = {Physics and Chemistry of the Earth, Parts A/B/C},

volume = {143},

pages = {104335},

abstract = {Land use and land cover (LULC) change serve as a major control on groundwater recharge, especially in urbanizing regions. This study assessed the impacts of LULC change on recharge to the Lusaka Aquifer, Zambia, between 1990 and 2022 using an Earth Observation (EO) based Water Balance Method (WBM). Recharge estimates were evaluated using the Water Table Fluctuation (WTF) and empirical methods for consistency and plausibility assessment. Results indicated a substantial decline in seasonal recharge from 212.7 mm in 1990 to 147.7 mm in 2022 driven by expansion of built-up areas (830.49%) and loss of forest cover (67.10%). Pronounced reductions in recharge occurred in 2004/05 (61.61 mm) and 2018/19 (55.14 mm), while the largest deviations between the simulations occurred in 2007/08 (108.12 mm) and 2016/17 (110.50 mm). Spatial patterns of recharge were strongly controlled by LULC and lithology. Carbonate formations exhibited the highest recharge (\>350 mm) under forest and vegetated cover, in contrast, granitic terrains consistently showed low recharge (\<10 mm) regardless of land cover and Schist formation showed moderate recharge, with values exceeding 150 mm under vegetation but experienced marked decline in built-up areas (\<50 mm). Comparison of WBM and WTF recharge estimates revealed consistent spatial patterns, though magnitudes differed by lithology: in dolomite, WBM estimated 227.95 mm compared to 291.67 mm from WTF; in limestone, 122.14 mm versus 123.45 mm; and in schists, 158.34 mm versus 82.00 mm. This corresponded to relative differences of −21.85%, −1.06%, and 93.09%, respectively. Recharge from empirical methods further corroborated the declining trends captured by WBM and reflected temporal variability linked to precipitation. Overall, the findings demonstrate the robustness of EO based water balance approach for quantifying recharge variability in data-scarce aquifers and highlight the critical role of LULC management in sustaining groundwater recharge under ongoing urban expansion. It also showed the importance of using multiple, conceptually distinct methods to reduce structural uncertainty in recharge estimation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{KISI2026103160,

title = {Cluster-based XGBoost framework for short-term rainfall\textendashrunoff prediction under uncertainty in the Sieber watershed, Germany},

author = {Ozgur Kisi and Salim Heddam and Sovan Sankalp and Andrea Petroselli and Christoph K\"{u}lls and Mohammad Zounemat-Kermani},

url = {https://www.sciencedirect.com/science/article/pii/S2214581826000583},

doi = {https://doi.org/10.1016/j.ejrh.2026.103160},

issn = {2214-5818},

year  = {2026},

date = {2026-01-01},

journal = {Journal of Hydrology: Regional Studies},

volume = {64},

pages = {103160},

abstract = {Study region 

The study focuses on the Sieber River watershed in northern Germany, a small mountainous catchment characterized by rapid rainfall\textendashrunoff response, limited hydrological data availability, and substantial short-term flow variability. These characteristics make the region an ideal testbed for developing robust, data-efficient short-term runoff prediction models. 

Study focus 

This research proposes a novel hybrid modeling framework combining eXtreme Gradient Boosting (XGBoost) with clustering algorithms (K-means and X-means) to improve multi-step-ahead rainfall\textendashrunoff forecasting under uncertainty. Hourly precipitation\textendashrunoff data and lagged precipitation inputs (Pt to Pt\textendash36) are used to generate predictions at 1-, 2-, 3-, and 6-hour horizons. The hybrid models are benchmarked against standalone XGBoost, Principal Component Regression (PCR), and the conceptual Event-Based Approach for Small and Ungauged Basins (EBA4SUB). Model performance is evaluated using RMSE, MAE, NSE, R², and uncertainty bounds. 

New hydrological insights for the region Clustering rainfall\textendashrunoff conditions into homogeneous hydrometeorological regimes considerably enhances prediction accuracy. The XGBoost\textendashK-means model provides the best performance, achieving low predictive error (6-hour ahead: RMSE = 0.580 m³/s},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kruger2025partitioning,

title = {Partitioning of flows in the unsaturated zone},

author = {Nina Kr\"{u}ger and Christoph K\"{u}lls},

year  = {2025},

date = {2025-01-01},

journal = {Journal of Hydrology},

pages = {132643},

publisher = {Elsevier},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{FIDELIBUS2025132775,

title = {A chloride threshold to identify the onset of seawater/saltwater intrusion and a novel categorization of groundwater in coastal aquifers},

author = {M. D. Fidelibus and G. Balacco and M. R. Alfio and M. Arfaoui and D. Bassukas and C. G\"{u}ler and F. Hamzaoui-Azaza and C. K\"{u}lls and A. Panagopoulos and A. Parisi and E. Sachsamanoglou and E. Tziritis},

url = {https://www.sciencedirect.com/science/article/pii/S0022169425001131},

doi = {https://doi.org/10.1016/j.jhydrol.2025.132775},

issn = {0022-1694},

year  = {2025},

date = {2025-01-01},

journal = {Journal of Hydrology},

volume = {653},

pages = {132775},

abstract = {Seawater intrusion is the primary cause of groundwater salinisation in coastal aquifers. However, attributing salinisation solely to seawater intrusion may not always be accurate, given the likely presence of other sources. To understand if salinisation comes from seawater intrusion and its onset is crucial for groundwater management, but there are no definite threshold values for common indicators such as chlorides. Based on 1662 groundwater analyses from five Mediterranean coastal aquifers, the study aimed to distinguish the effects of mixing with present-day seawater from those caused by other sources. The trend analysis of cumulative probability plots of chloride (and total dissolved solids) is a key method for discriminating different groundwater salinisation sources and processes. Results establish that chloride, as a non-reactive tracer, is a more reliable indicator of seawater intrusion than total dissolved solids, a reactive indicator. A chloride concentration threshold of 200 mg/L identifies the seawater intrusion onset. The threshold validation comes from groundwater salinisation facies, as provided by groundwater-type codification. Fresh groundwater (Cl \< 200 mg/L) anomalous total dissolved solids highlight the input of non-chloride salts and pollutants, providing caution regarding using total dissolved solids to recognise seawater intrusion. Beyond the threshold (Cl \> 200 mg/L), data disclose emergent signals of salinisation sources and water\textendashrock interaction processes overlapping seawater intrusion or the involvement of saline fluids different from present-day seawater. The threshold and a new categorisation of groundwater in coastal aquifers according to salinisation processes provide a benchmark for identifying and managing seawater intrusion in the Mediterranean area.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kisi_etal2025,

title = {Integration of Gaussian process regression and K means clustering for enhanced short term rainfall runoff modeling},

author = {O. Kisi and S. Heddam and K. S. Parmar and A. Petroselli and C. K\"{u}lls and M. Zounemat-Kermani},

doi = {10.1038/s41598-025-91339-8},

issn = {2045-2322},

year  = {2025},

date = {2025-01-01},

journal = {Scientific Reports},

volume = {15},

number = {1},

pages = {7444},

abstract = {Accurate rainfall-runoff modeling is crucial for effective watershed management, hydraulic infrastructure safety, and flood mitigation. However, predicting rainfall-runoff remains challenging due to the nonlinear interplay between hydro-meteorological and topographical variables. This study introduces a hybrid Gaussian process regression (GPR) model integrated with K-means clustering (GPR-K-means) for short-term rainfall-runoff forecasting. The Orgeval watershed in France serves as the study area, providing hourly precipitation and streamflow data spanning 1970\textendash2012. The performance of the GPR-K-means model is compared with standalone GPR and principal component regression (PCR) models across four forecasting horizons: 1-hour, 6-hour, 12-hour, and 24-hour ahead. The results reveal that the GPR-K-means model significantly improves forecasting accuracy across all lead times, with a Nash-Sutcliffe Efficiency (NSE) of approximately 0.999, 0.942, 0.891, and 0.859 for 1-hour, 6-hour, 12-hour, and 24-hour forecasts, respectively. These results outperform other ML models, such as Long Short-Term Memory, Support Vector Machines, and Random Forest, reported in the literature. The GPR-K-means model demonstrates enhanced reliability and robustness in hourly streamflow forecasting, emphasizing its potential for broader application in hydrological modeling. Furthermore, this study provides a novel methodology for combining clustering and Bayesian regression techniques in surface hydrology, contributing to more accurate and timely flood prediction.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{LANGE2025180175,

title = {Trifluoroacetate (TFA) \textendash Potentials and limits of a new hydrological pollution tracer},

author = {Jens Lange and Larissa Bulka and Dario N\"{o}ltge and Finnian Freeling and Konstantin Ilgen and Christoph K\"{u}lls and Michael M\"{u}ller},

url = {https://www.sciencedirect.com/science/article/pii/S0048969725018157},

doi = {https://doi.org/10.1016/j.scitotenv.2025.180175},

issn = {0048-9697},

year  = {2025},

date = {2025-01-01},

journal = {Science of The Total Environment},

volume = {997},

pages = {180175},

abstract = {Trifluoroacetate (TFA), the perfluorinated analogue of the acetate ion, is an emerging pollutant that is highly water-soluble, mobile and persistent in the environment. TFA has many precursors and a variety of atmospheric and terrestrial sources. This study investigates the suitability of this molecule to act as a hydrological pollution tracer to characterize water types and to identify young recharge components and river water infiltration. For this purpose, TFA was compared with classical environmental tracers (stable water isotopes and major ions) in depth-profiles of three groundwater wells and in surrounding rivers. The tapped porous aquifer supplies drinking water for the city of Freiburg, Germany, and is located in an area used by intense agriculture. Rising atmospheric inputs and, probably, the increased use of fluorinated pesticides led to a strong signal of TFA in recent soil water. This signal enabled efficient differentiation between different surface water types and groundwater of different ages. Dual−anion plots (TFA-Cl− and TFA-NO₃−) were more efficient than the traditional dual−isotope plot with 18O and deuterium. These plots allowed estimates about the approximate contribution of TFA from agricultural soil. Moreover, TFA traced the infiltration of river water into groundwater and contributions of relatively young soil water components down to deep groundwater. We see promising applications of TFA as a tracer in the future, provided that TFA input functions are well-defined, the major TFA sources are known, and other tracers are used in parallel to back up TFA-derived results.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{LWEENDO2025104073,

title = {Impacts of Landuse/Landcover change on groundwater recharge potential of the Lusaka Aquifer system using Fuzzy-AHP},

author = {Muumbe K. Lweendo and Benjamin Mapani and Kawawa Banda and Samuel Adelabu and Christoph K\"{u}lls},

url = {https://www.sciencedirect.com/science/article/pii/S1474706525002232},

doi = {https://doi.org/10.1016/j.pce.2025.104073},

issn = {1474-7065},

year  = {2025},

date = {2025-01-01},

journal = {Physics and Chemistry of the Earth, Parts A/B/C},

volume = {141},

pages = {104073},

abstract = {Landcover transformations exert pressure on aquifer systems by disrupting natural recharge, yet the extent of these impacts remain poorly understood. This study investigated impacts of land use and land cover (LULC) change on groundwater recharge potential zones (GRPZ) on the Lusaka Aquifer System. Geospatial techniques were combined with multi-criteria decision analysis to delineate GRPZs for the years 1990\textendash2022 with seven thematic layers. Results indicated that built-up areas expanded significantly from 70.13 km2 to 652.60 km2 (830.49 %) while forest and cropland declined by 593.81 km2 (67.10 %) and 258.65 km2 (33.54 %) respectively. The transition matrix showed that built-up areas had a gain of 25.26 % of the total study area, largely sourced from cropland (10.37 %), forest (8.13 %), and vegetation (5.55 %). Forest cover underwent notable transformations with a loss of 25.75 %. Cropland exhibited the highest degree of persistence, with 11.19 % remaining unchanged. The areal coverage of GRPZ showed that low and moderate recharge zones increased by 134.21 km2 (27.17 %) and 39.14 km2 (3.13 %) respectively. In contrast, high and very high zones declined by 164.90 km2 (33.33 %) and 8.47 km2 (74.48 %). Analysis of built-up area expansion on GRPZs revealed notable encroachments on low, moderate and high recharge zones by 127.28 km2, 332.02 km2 and 106.65 km2 respectively. This study highlights the ongoing shifts in recharge potential areas driven by urbanization, indicating a continued trend that increases the risk of reduced aquifer recharge and long-term groundwater depletion. The spatial overlap between built-up expansion and recharge potential zones indicates a disconnect between LULC change and groundwater management.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{KISI2024102017,

title = {Enhancing river flow predictions: Comparative analysis of machine learning approaches in modeling stage-discharge relationship},

author = {Ozgur Kisi and Hazi Mohammad Azamathulla and Fatih Cevat and Christoph Kulls and Mehdi Kuhdaragh and Mehdi Fuladipanah},

url = {https://www.sciencedirect.com/science/article/pii/S2590123024002706},

doi = {https://doi.org/10.1016/j.rineng.2024.102017},

issn = {2590-1230},

year  = {2024},

date = {2024-01-01},

journal = {Results in Engineering},

volume = {22},

pages = {102017},

abstract = {Streamflow, a pivotal variable in water resources management, holds profound significance in shaping the decision-making processes of hydrologic projects. This paper tries to delve into the exploration of the stage-discharge relationship using three machine learning methods (MLMs) namely multi-layer neural networks (MLNN), radial basis neural networks (RBNN), and neuro-fuzzy systems (ANFIS) to predict and simulate mean daily stage-discharge data derived from two monitoring stations, Bulakbasi and Karaoz\"{u}, Kizilirmak River, Turkey. Root mean square error (RMSE), Mean absolute percentage error (MAPE), coefficient of determination (R2), and the Developed Discrepancy Ratio (DDR) metrics were utilized to MLMs' performance assessment. The performance evaluation indices (RMSE, MAEP, R2, DDR) for the preeminent MLNN model applied to Bulakhbashi and Karasu stations were determined as (0.29, 1.57, 0.9998, 17.62) and (1.71, 6.56, 0.9980, 6.65), respectively. The MLNN model contributed to a notable enhancement in the RMSE performance index for the aforementioned stations, exhibiting improvements of 87% and 56%, respectively. These results affirm the MLNN's proficiency in accurately capturing the stage-discharge at both monitoring stations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{KRUGER2024131352,

title = {Groundwater recharge estimation in Mediterranean mountain environments by isotope profiles \textendash Partitioning of macropore and matrix flow},

author = {Nina Kr\"{u}ger and Christoph K\"{u}lls and Adriana Bruggeman and Christos Christofi},

url = {https://www.sciencedirect.com/science/article/pii/S0022169424007479},

doi = {https://doi.org/10.1016/j.jhydrol.2024.131352},

issn = {0022-1694},

year  = {2024},

date = {2024-01-01},

journal = {Journal of Hydrology},

pages = {131352},

abstract = {Developing and continuously improving effective and feasible methods to estimate groundwater recharge is essential to ensure sustainable resource assessment. Mountain environments represent key areas for the regional water balance. In this study, the isotope profile method was used to investigate water fluxes through the vadose zone and subsequent groundwater recharge in a Mediterranean mountain environment. Six high-resolution soil water isotope profiles were taken at two different locations in the Troodos Massif (Cyprus) in the eastern Mediterranean, focusing on estimating recharge in the soil of hillslopes. Analysis of the isotope profiles yielded recharge rates ranging from 30\textendash70 mm/year, leading to a re-evaluation of previous studies on groundwater recharge. The comparison of results obtained by the peak-shift method and mathematical modeling was used to partition matrix and macropore flow, reaching up to 39 %. Potential methodological limits of the environmental isotope profile method in skeleton-rich soils were found.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kisi2024improved,

title = {Improved monthly streamflow prediction using integrated multivariate adaptive regression spline with K-means clustering: implementation of reanalyzed remote sensing data},

author = {Ozgur Kisi and Salim Heddam and Kulwinder Singh Parmar and Zaheer Mundher Yaseen and Christoph Kulls},

year  = {2024},

date = {2024-01-01},

journal = {Stochastic Environmental Research and Risk Assessment},

volume = {38},

number = {6},

pages = {2489\textendash2519},

publisher = {Springer Berlin Heidelberg Berlin/Heidelberg},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ola2024remediating,

title = {Remediating Oil Contamination in the Niger Delta Region of Nigeria: Technical Options and Monitoring Strategies},

author = {Ibukun Ola and Carsten Drebenstedt and Robert M Burgess and Martin Mensah and Nils Hoth and Christoph K\"{u}lls},

year  = {2024},

date = {2024-01-01},

journal = {The Extractive Industries and Society},

volume = {17},

pages = {101405},

publisher = {Elsevier},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ola2024assessing,

title = {Assessing petroleum contamination in parts of the Niger Delta based on a sub-catchment delineated field assessment},

author = {Ibukun Ola and Carsten Drebenstedt and Robert M Burgess and Martin Mensah and Nils Hoth and Precious Okoroafor and Christoph K\"{u}lls},

year  = {2024},

date = {2024-01-01},

journal = {Environmental Monitoring and Assessment},

volume = {196},

number = {6},

pages = {585},

publisher = {Springer International Publishing Cham},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kulls2024grundwasserqualitat,

title = {Grundwasserqualit\"{a}t im Abstrom der Deponie Ihlenberg},

author = {Christoph K\"{u}lls},

year  = {2024},

date = {2024-01-01},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kisi2024comments,

title = {Comments on “Machine learning-based time series models for effective CO2 emission prediction in India” by Kumari and Singh, https://doi. org/10.1007/s11356-022\textendash21723-8},

author = {Ozgur Kisi and Cesar Gabriel Leite e Melo and Lars Fischer and Hanna Brandt and Lennart Heims and Alexandre Loaec and Wais Masomy and Mohammed Parvez and Jan Roehl and Christoph K\"{u}lls},

year  = {2024},

date = {2024-01-01},

journal = {Environmental Science and Pollution Research},

pages = {1\textendash4},

publisher = {Springer Berlin Heidelberg Berlin/Heidelberg},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ola2024application,

title = {Application of low-density polyethylene (LDPE) passive samplers for monitoring PAHs in groundwater},

author = {Ibukun Ola and Carsten Drebenstedt and Robert M Burgess and Ian J Allan and Nils Hoth and Christoph K\"{u}lls},

year  = {2024},

date = {2024-01-01},

journal = {Environmental Science and Pollution Research},

volume = {31},

number = {42},

pages = {54546\textendash54558},

publisher = {Springer Berlin Heidelberg Berlin/Heidelberg},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{idowu2024new,

title = {A new method for monthly streamflow prediction using multi-source data: range-dependent multivariate adaptive regression splines\textendashgenetic algorithm},

author = {Mariam Idowu and Christoph Kulls and Ozgur Kisi},

year  = {2024},

date = {2024-01-01},

journal = {Hydrological Sciences Journal},

volume = {69},

number = {13},

pages = {1860\textendash1880},

publisher = {Taylor \& Francis},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ola2024combined,

title = {Combined temperature and salinity effects on the passive sampling of PAHs with an assessment of impacts to petroleum toxicity},

author = {Ibukun Ola and Carsten Drebenstedt and Robert M Burgess and Lane Tidwell and Kim Anderson and Nils Hoth and Christoph K\"{u}lls},

year  = {2024},

date = {2024-01-01},

journal = {Environmental Science: Processes \& Impacts},

volume = {26},

number = {11},

pages = {2076\textendash2089},

publisher = {Royal Society of Chemistry},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{adnan2023modelling,

title = {Modelling biochemical oxygen demand using improved neuro-fuzzy approach by marine predators algorithm},

author = {Rana Muhammad Adnan and Hong-Liang Dai and Ozgur Kisi and Salim Heddam and Sungwon Kim and Christoph Kulls and Mohammad Zounemat-Kermani},

year  = {2023},

date = {2023-01-01},

journal = {Environmental Science and Pollution Research},

volume = {30},

number = {41},

pages = {94312\textendash94333},

publisher = {Springer Berlin Heidelberg Berlin/Heidelberg},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kisi2023discussion,

title = {Discussion of “Improving Prediction Accuracy of Hydrologic Time Series by Least-Squares Support Vector Machine Using Decomposition Reconstruction and Swarm Intelligence”},

author = {Ozgur Kisi and Kai Liepelt and Christoph Kulls},

year  = {2023},

date = {2023-01-01},

journal = {Journal of Hydrologic Engineering},

volume = {28},

number = {4},

pages = {07023001},

publisher = {American Society of Civil Engineers},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kisi2023comments,

title = {Comments on “Splitting tensile strength prediction of sustainable high-performance concrete using machine learning techniques” by Wu, Yangi et al., https://doi. org/10.1007/s11356-022-22048-2},

author = {Ozgur Kisi and Sara Ajri and Kim Cedric J\"{o}rgens and Arti Karande and Sabine Kraus and Benita Naumann and Kim Nierman and Wiebke Seel and Christoph Kulls},

year  = {2023},

date = {2023-01-01},

journal = {Environmental Science and Pollution Research},

volume = {30},

number = {50},

pages = {109854\textendash109855},

publisher = {Springer Berlin Heidelberg Berlin/Heidelberg},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kisi2023estimation,

title = {Estimation of mean velocity upstream and downstream of a bridge model using metaheuristic regression methods},

author = {Ozgur Kisi and Mehmet Ardi\c{c}lio\u{g}lu and Arzu MW Hadi and Alban Kuriqi and Christoph Kulls},

year  = {2023},

date = {2023-01-01},

journal = {Water Resources Management},

volume = {37},

number = {14},

pages = {5559\textendash5580},

publisher = {Springer Netherlands Dordrecht},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{eliades2022quantifying,

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},

author = {Marinos Eliades and Adriana Bruggeman and Hakan Djuma and Christos Christofi and Christoph Kuells},

year  = {2022},

date = {2022-01-01},

journal = {Water},

volume = {14},

number = {5},

pages = {734},

publisher = {MDPI},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{mehraein2022monthly,

title = {Monthly streamflow prediction by metaheuristic regression approaches considering satellite precipitation data},

author = {Mojtaba Mehraein and Aadhityaa Mohanavelu and Sujay Raghavendra Naganna and Christoph Kulls and Ozgur Kisi},

year  = {2022},

date = {2022-01-01},

journal = {Water},

volume = {14},

number = {22},

pages = {3636},

publisher = {MDPI},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{christofi2020hydrochemicalb,

title = {Hydrochemical evolution of groundwater in gabbro of the Troodos Fractured Aquifer. A comprehensive approach},

author = {Christos Christofi and Adriana Bruggeman and Christoph Kuells and Costas Constantinou},

year  = {2020},

date = {2020-01-01},

journal = {Applied Geochemistry},

volume = {114},

pages = {104524},

publisher = {Pergamon},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{mahindawansha2020investigatingb,

title = {Investigating unproductive water losses from irrigated agricultural crops in the humid tropics through analyses of stable isotopes of water},

author = {Amani Mahindawansha and Christoph K\"{u}lls and Philipp Kraft and Lutz Breuer},

year  = {2020},

date = {2020-01-01},

journal = {Hydrology and Earth System Sciences},

volume = {24},

number = {7},

pages = {3627\textendash3642},

publisher = {Copernicus Publications G\"{o}ttingen, Germany},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{christofi2020isotope,

title = {Isotope hydrology and hydrogeochemical modeling of Troodos Fractured Aquifer, Cyprus: The development of hydrogeological descriptions of observed water types},

author = {Christos Christofi and Adriana Bruggeman and Christoph Kuells and Costas Constantinou},

year  = {2020},

date = {2020-01-01},

journal = {Applied Geochemistry},

volume = {123},

pages = {104780},

publisher = {Pergamon},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{joseph2019applicationb,

title = {Application of a laser-based spectrometer for continuous in situ measurements of stable isotopes of soil CO 2 in calcareous and acidic soils},

author = {Jobin Joseph and Christoph K\"{u}lls and Matthias Arend and Marcus Schaub and Frank Hagedorn and Arthur Gessler and Markus Weiler},

year  = {2019},

date = {2019-01-01},

journal = {Soil},

volume = {5},

number = {1},

pages = {49\textendash62},

publisher = {Copernicus Publications G\"{o}ttingen, Germany},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{mahindawansha2019estimating,

title = {Estimating water flux and evaporation losses using stable isotopes of soil water from irrigated agricultural crops in tropical humid regions},

author = {Amani Mahindawansha},

year  = {2019},

date = {2019-01-01},

publisher = {Deutsche Nationalbibliothek},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ardelt2018towards,

title = {Towards intrinsic molecular communication using isotopic isomerism},

author = {Gunther Ardelt and Christoph K\"{u}lls and Horst Hellbr\"{u}ck},

year  = {2018},

date = {2018-01-01},

journal = {Open Journal of Internet Of Things (OJIOT)},

volume = {4},

number = {1},

pages = {135\textendash143},

publisher = {RonPub},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{androvitsanea2018hydrologische,

title = {Hydrologische Bedingungen im Heraion von Samos vom 12. bis 8. Jh. v. Chr. und ihre Bedeutung f\"{u}r die wasserbauliche Infrastruktur},

author = {Anna Androvitsanea and Mohammad Fawzy and Johanna Fuchs and Christoph Jan Kuells and Henning Fahlbusch and Joachim Heiden},

year  = {2018},

date = {2018-01-01},

journal = {Environmental Water Engineering},

volume = {1},

number = {1},

pages = {1\textendash21},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{mueller2014trackingb,

title = {Tracking water pathways in steep hillslopes by δ18O depth profiles of soil water},

author = {Matthias H Mueller and Abdallah Alaoui and Christoph Kuells and Hannes Leistert and Katrin Meusburger and Christine Stumpp and Markus Weiler and Christine Alewell},

year  = {2014},

date = {2014-01-01},

journal = {Journal of hydrology},

volume = {519},

pages = {340\textendash352},

publisher = {Elsevier},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{hamutoko2014fingerprintingb,

title = {A fingerprinting method for the identification of uranium sources in alluvial aquifers: An example from the Khan and Swakop Rivers, Namibia},

author = {JT Hamutoko and BS Mapani and R Ellmies and A Bittner and C Kuells},

year  = {2014},

date = {2014-01-01},

journal = {Physics and Chemistry of the Earth, Parts A/B/C},

volume = {72},

pages = {34\textendash42},

publisher = {Pergamon},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Klaus2013macropore,

title = {Macropore flow of old water revisited: experimental insights from a tile-drained hillslope},

author = {J. Klaus and E. Zehe and M. Elsner and C. K\"{u}lls and J. J. McDonnell},

doi = {https://doi.org/10.5194/hess-17-103-2013},

year  = {2013},

date = {2013-01-01},

journal = {Hydrology and Earth System Sciences},

volume = {17},

number = {1},

pages = {103},

publisher = {Copernicus GmbH},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{baram2013desiccationb,

title = {Desiccation-crack-induced salinization in deep clay sediment},

author = {S Baram and Z Ronen and D Kurtzman and C K\"{u}lls and O Dahan},

year  = {2013},

date = {2013-01-01},

journal = {Hydrology and Earth System Sciences},

volume = {17},

number = {4},

pages = {1533\textendash1545},

publisher = {Copernicus GmbH},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kulls12013passive,

title = {Passive barriers for long-term containment of Uranium and Vanadium},

author = {Christoph K\"{u}lls and Arnold Bittner},

year  = {2013},

date = {2013-01-01},

urldate = {2013-01-01},

keywords = {},

pubstate = {published},

tppubtype = {article}

}