Department Systems Analysis, Integrated Assessment and Modelling

This paper presents some of the reasons for studying the history of hydrology and for the formation of the International Association of Hydrological Sciences (IAHS) History of Hydrology Working Group. In particular, we consider the importance of recording the histories of hydrological data, catchments, diversity in hydrology (of both people and topics), and what can be gained from the historical literature in hydrology. We also consider why the classical concepts of catchment response to rainfall have evolved slowly in hydrology, despite identified limitations, and how the major impetus for change in the 1970s, in the form of techniques for measuring environmental tracers, effectively came from developments outside the discipline. We conclude by speculating whether the questions posed by recent machine learning studies might lead to further change and understanding.

The Indian Ocean plays a crucial role in water cycle dynamics around the Indian Ocean Basin, yet the relationships between the Indian Walker Circulation (IWC) and hydroclimate variability remain poorly understood. We examine the IWC-hydroclimate linkages throughout the Indian Ocean Basin during two study periods (instrumental era and the last millennium), using the ECHAM5-wiso, iCESM-iLME, and ERA5 global data products. We leverage the stable isotopic composition of precipitation ((Formula presented.) ¹⁸O_P) as an integrative water cycle tracer to elucidate the link between large-scale atmospheric processes and regional hydroclimate characteristics. We find a strong statistical relationship between the East African short rain (Formula presented.) ¹⁸O_P and IWC in Eastern Africa and Horn of Africa. In Indonesia, the relationship is weaker due to the strong influence of the Pacific Walker Circulation (PWC). These patterns arise over multiple time scales and are consistent with the strong tie between the IWC and precipitation variability during the short rain season in Eastern Africa and Horn of Africa that had previously been reported in the instrumental era but not yet for the last millennium. We document strong fluctuations in the strength of the IWC during the last millennium, with periods of stronger or weaker interactions with the PWC that influenced (Formula presented.) ¹⁸O_P variability. Finally, our study underscores the ability of (Formula presented.) ¹⁸O_P to capture major atmospheric circulation signals, demonstrating its potential to examine the impact of interacting Walker Circulations on regional hydroclimate even during periods of low precipitation.

The interplay between abiotic (resource supply, temperature) and biotic (grazing) factors determines growth and loss processes in phytoplankton through resource competition and trophic interactions, which are mediated by morphological traits like size. Here, we study the relative importance of grazers, water physics, and chemistry on the daily net accumulation rates (ARs) of individual phytoplankton from natural communities, grouped into six size classes from circa 10 to 500 μm. Using a Random Forest modelling approach and 4 years of daily data from a lake, we find that water temperature is generally a pivotal control of all phytoplankton ARs. At the same time, nutrients and light are important for the smallest and the largest classes. Mesozooplankton abundance is a key predictor of the AR for small phytoplankton, with microzooplankton being important for the middle-size range. In our data, large and small phytoplankton have different (seasonal) blooming patterns: small forms are favoured by low temperature and grazing, and high phosphorus levels. Larger forms show positive ARs at high temperatures and low phosphorus (being relatively insensitive to zooplankton grazing). These results help us understand the opportunities and limitations of using size to explain and model phytoplankton responses to biotic and abiotic environmental change.

This study presents a comprehensive dataset from Lake Greifen, Switzerland, collected between April 2018 and June 2023, using high-frequency automated monitoring systems. The dataset integrates meteorological data, nutrient chemistry, water column profiles for water physics, and plankton underwater imaging, offering insights into the lake's physical and biological processes. A dual-magnification dark field underwater microscope captured hourly plankton dynamics at 3 m depth, providing size, shape, and taxonomic information. A profiler with a multiparametric probe monitored water temperature, oxygen, and other key parameters from 1 to 17 m depth, while weekly nutrient sampling complemented the measurements. Data processing involved rigorous cleaning protocols to remove technical artefacts, ensuring data quality. Our dataset showcases the utility of integrating different approaches for high-frequency monitoring to detect lake temporal processes, from phytoplankton blooms to zooplankton vertical migration and seasonal shifts in water column stability. This dataset provides a unique resource for studying limnology and plankton community ecology. All data and related processing codes are publicly available for further research, supporting interdisciplinary studies.

This study proposes a novel deep learning (DL)-based surrogate model that incorporates the calculation of net rainfall using the SCS-CN method, providing a flexible framework for evaluating the influence of rainfall events under different antecedent moisture conditions (AMC). The proposed framework involves establishing a ground truth model (Iber-SWMM) and defining the necessary terrain features and rainfall patterns for training the surrogate. A benchmark surrogate model using only gross rainfall, replicating methodologies from previous studies, is also developed for comparison. The trained models are then applied to predict water depth maps using test rainfall patterns under different scenarios, both with and without net rainfall. The results demonstrate that the proposed surrogate model reduces the computational times of Iber-SWMM by 2 to 4 orders of magnitude while outperforming the benchmark surrogate in all the measures. It presents satisfactory accuracy in water depth prediction, with 80% to 95% of predictions within a -0.2 to 0.2 m error range and hit ratios between 0.87 to 0.91 in terms of flooded pixels in the more extreme events. These outcomes are comparable to those achieved by a physics-based model on one of the test events. The study also suggests future lines for refinement.

Background: Understanding the temporal development of community assembly processes is essential for assessing the recovery of degraded ecosystems after restoration. Community development in restored streams is often slow or absent, due to inadequate restoration, catchment-scale pressures, and/or colonisation barriers. Recovery processes involve three key filters: dispersal, environmental conditions and biotic interactions. Dispersal is critical for initial colonisation, while environmental conditions influence successful population establishment. Lastly, as available niches fill, biotic interactions, such as competition, gain importance. Despite the presence of many theories on how these three filters interact during community assembly, they have rarely been investigated simultaneously. Our detailed species- and site-specific approach allowed us to analyse the three filters in a hierarchical analysis. We assessed the effect of the three filters, by examining benthic invertebrate communities at 20 sites in the Boye catchment (Western Germany). The Boye and most of its tributaries were used as open sewers for a century, i.e. they were concrete channels transporting untreated sewage before gradual restoration was started in the 1990s. The bank reinforcements and concrete beds were removed, while riparian vegetation was left to natural succession. Accordingly, the sites were grouped as 'unimpacted', 'recently restored' (< 4 years), and 'mature restored' (> 10 years). An additional 28 sites provided information on distances to source populations, while the species’ habitat suitability assessed environmental filtering. Biotic (interaction) filtering was evaluated through trait overlap analysis. Results: Communities at recently restored sites differed from mature and unimpacted sites, while mature sites resembled unimpacted ones. Taxa at recently restored sites had nearer source populations, while those at mature and unimpacted sites better matched present habitats. Trait overlap did not differ between present and absent taxa. Conclusions: Our results indicate that dispersal was essential in early recovery stages, with mass effects from upstream sources supporting taxa found at recently restored sites despite low habitat suitability. Over time, habitat suitability became more influential, shaping mature communities. Competition appeared relatively unimportant, yet competitive exclusion may explain small proportions of absent taxa at mature and recently restored sites. Hence, to effectively support stream recovery, it is essential to consider how different filtering processes operate at various stages of the recovery process. For example, mature communities could further develop if habitat availability increases, while the connectivity to source populations would only play a minor role.