Christoph Külls

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Technical University of Applied Sciences Lübeck

Germany

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Professor Christoph Külls is a faculty member at Technische Hochschule Lübeck in Germany. His research interests encompass hydrology, groundwater contamination, and climate impact analysis, as reflected in his recent publications on precipitation variation, seawater intrusion, and rainfall runoff modeling. He employs innovative statistical methods and machine learning techniques to enhance environmental monitoring and prediction models.

Recent Grants

Grant: Close

MEDSAL - Groundwater Salinization in the Mediterranean

Open Date: 2018-10-01

Close Date: 2023-02-01

Grant: Close

Isotope Technologies for Water Management in Mediterranean Countries

Open Date: 2018-08-01

Close Date: 2021-07-01

Grant: Close

Water and cult in the Heraion of Samos

Open Date: 2016-01-01

Close Date: 2021-12-31

Grant: Close

enable Water-Carbon-Management

Open Date: 2011-04-01

Close Date: 2014-03-01

Grant: Close

WADE

Open Date: 2004-10-01

Close Date: 2006-09-01

Articles (12)

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2025

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2025

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2025

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2025

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2024

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2024

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2024

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2024

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2024

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2024

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2020

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2020

Collaborators (1)

Ozgur Kisi

Guest Professor

University of Applied Sciences

GERMANY

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Christoph Külls

Research Interests

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About

Recent Grants

Articles (12)

Spatial-temporal variation of precipitation in Niedersachsen, Germany, using statistical and graphical trend methods considering climatic drivers

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

Integration of Gaussian process regression and K means clustering for enhanced short term rainfall runoff modeling

Partitioning of flows in the unsaturated zone

A new method for monthly streamflow prediction using multi-source data: range-dependent multivariate adaptive regression splines–genetic algorithm

Application of low-density polyethylene (LDPE) passive samplers for monitoring PAHs in groundwater

Assessing petroleum contamination in parts of the Niger Delta based on a sub-catchment delineated field assessment

Combined temperature and salinity effects on the passive sampling of PAHs with an assessment of impacts to petroleum toxicity

Comments on “Machine learning‑based time series models for effective CO2 emission prediction in India” by Kumari and Singh, https://doi.org/10.1007/s11356-022–21723-8

Enhancing river flow predictions: Comparative analysis of machine learning approaches in modeling stage-discharge relationship

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

Hydrochemical evolution of groundwater in gabbro of the Troodos Fractured Aquifer. A comprehensive approach

Collaborators (1)

Ozgur Kisi

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