Floris van Ogtrop

Evaluation of an ensemble of regional hydrological models in 12 large-scale river basins worldwide

In regional climate impact studies, good performance of regional models under present/historical climate conditions is a prerequisite for reliable future projections. This study aims to investigate the overall performance of 9 hydrological models for 12 large-scale river basins worldwide driven by the reanalysis climate data from the Water and Global Change (WATCH) project. The results serve as the basis of the application of regional hydrological models for climate impact assessment within the second phase of the Inter-Sectoral Impact Model Intercomparison project (ISI-MIP2). The simulated discharges by each individual hydrological model, as well as the ensemble mean and median series were compared against the observed discharges for the period 1971–2001. In addition to a visual comparison, 12 statistical criteria were selected to assess the fidelity of model simulations for monthly hydrograph, seasonal dynamics, flow duration curves, extreme floods and low flows. The results show that most regional hydrological models reproduce monthly discharge and seasonal dynamics successfully in all basins except the Darling in Australia. The moderate flow and high flows (0.02–0.1 flow exceedance probabilities) are also captured satisfactory in many cases according to the performance ratings defined in this study. In contrast, the simulation of low flow is problematic for most basins. Overall, the ensemble discharge statistics exhibited good agreement with the observed ones except for extremes in particular basins that need further scrutiny to improve representation of hydrological processes. The performances of both the conceptual and process-based models are comparable in all basins.

Microbial players involved in the decline of filamentous and colonial cyanobacterial blooms with a focus on fungal parasitism

In the forthcoming decades, it is widely believed that the dominance of colonial and filamentous bloom-forming cyanobacteria (e.g. Microcystis, Planktothrix, Anabaena and Cylindrospermopsis) will increase in freshwater systems as a combined result of anthropogenic nutrient input into freshwater bodies and climate change. While the physicochemical parameters controlling bloom dynamics are well known, the role of biotic factors remains comparatively poorly studied. Morphology and toxicity often - but not always - limit the availability of cyanobacteria to filter feeding zooplankton (e.g. cladocerans). Filamentous and colonial cyanobacteria are widely regarded as trophic dead-ends mostly inedible for zooplankton, but substantial evidence shows that some grazers (e.g. copepods) can bypass this size constraint by breaking down filaments, making the bloom biomass available to other zooplankton species. A wide range of algicidal bacteria (mostly from the Alcaligenes, Flavobacterium/Cytophaga group and Pseudomonas) and viruses (Podoviridae, Siphoviridae and Myoviridae) may also contribute to bloom control, via their lytic activity underpinned by a diverse array of mechanisms. Fungal parasitism by the Chytridiomycota remains the least studied. While each of these biotic factors has traditionally been studied in isolation, emerging research consistently point to complex interwoven interactions between biotic and environmental factors.

Key Ecological Roles for Zoosporic True Fungi in Aquatic Habitats

The diversity and abundance of zoosporic true fungi have been analyzed recently using fungal sequence libraries and advances in molecular methods, such as high-throughput sequencing. This review focuses on four evolutionary primitive true fungal phyla: the Aphelidea, Chytridiomycota, Neocallimastigomycota, and Rosellida (Cryptomycota), most species of which are not polycentric or mycelial (filamentous), rather they tend to be primarily monocentric (unicellular). Zoosporic fungi appear to be both abundant and diverse in many aquatic habitats around the world, with abundance often exceeding other fungal phyla in these habitats, and numerous novel genetic sequences identified. Zoosporic fungi are able to survive extreme conditions, such as high and extremely low pH; however, more work remains to be done. They appear to have important ecological roles as saprobes in decomposition of particulate organic substrates, pollen, plant litter, and dead animals; as parasites of zooplankton and algae; as parasites of vertebrate animals (such as frogs); and as symbionts in the digestive tracts of mammals. Some chytrids cause economically important diseases of plants and animals. They regulate sizes of phytoplankton populations. Further metagenomics surveys of aquatic ecosystems are expected to enlarge our knowledge of the diversity of true zoosporic fungi. Coupled with studies on their functional ecology, we are moving closer to unraveling the role of zoosporic fungi in carbon cycling and the impact of climate change on zoosporic fungal populations.

Identifying model consistency through stepwise calibration to capture streamflow variability

The consistency of calibrated hydrological models (whether the model is internally consistent) is often ignored as model calibration generally only evaluates performance. A correlation matrix is developed in this paper to assess model consistency by comparing different flow dynamics combined with a stepwise calibration approach targeting different flow signals (low, medium and high). The Soil Water Assessment tool (SWAT) was used as an example model and simulations were conducted using Sequential Uncertainty Fitting-2 (SUFI-2) algorithm. Critical evaluation of the method demonstrates that satisfactory model performance does not necessarily lead to a consistent model and this yields poor performance in validation. However, results may vary depending on climatic conditions and temporal scales. By calibrating on disaggregated flow signals and evaluating based on consistency, the proposed method improves model realism which will improve understanding of catchment functioning. A correlation matrix was developed to identify model consistency.A stepwise calibration approach can improve model consistency.Calibration was based on different flow signals of the hydrograph.SWAT model (Arnold etźal., 1998) was used to demonstrate the methodology.

The value of remotely sensed surface soil moisture for model calibration using SWAT

Remotely sensed (RS) data can add value to a hydrological model calibration. Among this, RS soil moisture (SM) data have mostly been assimilated into conceptual hydrological models using various transformed variable or indices. In this study, raw RS surface SM is used as a calibration variable in the Soil and Water Assessment Tool (SWAT) model. This means the SM values were not transformed into another variable (e.g. soil water index, root zone soil moisture index). Using a nested catchment, calibration based only on RS SM, and optimizing model parameters sensitive to SM using Particle Swarm Optimization (PSO) improved variations in streamflow predictions at some of the gauging stations compared to the un-calibrated model. This highlighted part of the catchments where the SM signal directly influenced the flow distribution. Additionally, highlighted high and low flow signals were mostly influenced. The seasonal breakdown indicates that the SM signal is more useful for calibrating in wetter seasons and in areas with higher variations in elevation. The results identified that calibration only on RS SM improved the general rainfall-runoff response simulation by introducing delays, but cannot correct the overall routing effect. Furthermore, catchment characteristics (e.g. landuse, elevation, soil types, precipitation) regulating SM variation in different seasons highlighted by the model calibration are identified. This provides further opportunities to improve model parameterization.

Wildfire effects on soil carbon and water repellency under eucalyptus forest in Eastern Australia

Soil properties can be considerably modified as a result of wildfire. This study examined the impact of wildfire on total carbon and water repellency at two study sites, namely Cranebrook and Wentworth Falls, located 45 and 75 km west of Sydney, Australia, respectively. Within each study site, we measured soil properties at two depth intervals from five burn severity classes along 15 transects (10 sample points per transect). Samples were taken 6, 12 and 36 months after wildfire. Soil total carbon was measured using LECO combustion analysis and potential soil water repellency was determined using water drop penetration time. Two-way analysis of variance (ANOVA) was used to analyse the results, with burn severity and time as factors. Burn severity had a significant effect on both soil total carbon and water repellency at both study sites, whereas time was only significant for soil carbon at Wentworth Falls. Soil total carbon and water repellency were variable through time due to local environmental variables, such as rainfall and temperature. The relationship between soil total carbon and water repellency was strong for Cranebrook in the surface soil (r = 0.62) and lower in the subsurface soil (r = 0.41), but weaker at Wentworth Falls, with values of r = 0.22 and r = 0.15 in the surface and subsurface soils respectively.

Erratum to: Evaluation of an ensemble of regional hydrological models in 12 large-scale river basins worldwide

Evaluation of an ensemble of regional hydrological models in 12 large-scale river basins worldwide (vol 141, pg 381, 2017)

Using paired catchments to quantify the human influence on hydrological droughts

Quantifying the influence of human activities, such as reservoir building, water abstraction, and land use change, on hydrology is crucial for sustainable future water management, especially during drought. Model-based methods are very time-consuming to set up and require a good understanding of human processes and time series of water abstraction, land use change, and water infrastructure and management, which often are not available. Therefore, observation-based methods are being developed that give an indication of the direction and magnitude of the human influence on hydrological drought based on limited data. We suggest adding to those methods a “paired-catchment” approach, based on the classic hydrology approach that was developed in the 1920s for assessing the impact of land cover treatment on water quantity and quality. When applying the pairedcatchment approach to long-term pre-existing human influences trying to detect an influence on extreme events such as droughts, a good catchment selection is crucial. The disturbed catchment needs to be paired with a catchment that is similar in all aspects except for the human activity under study, in that way isolating the effect of that specific activity. In this paper, we present a framework for selecting suitable paired catchments for the study of the human influence on hydrological drought. Essential elements in this framework are the availability of qualitative information on the human activity under study (type, timing, and magnitude), and the similarity of climate, geology, and other human influences between the catchments. We show the application of the framework on two contrasting case studies, one impacted by groundwater abstraction and one with a water transfer from another region. Applying the paired-catchment approach showed how the groundwater abstraction aggravated streamflow drought by more than 200 % for some metrics (total drought duration and total drought deficit) and the water transfer alleviated droughts with 25 % to 80 %, dependent on the metric. Benefits of the paired-catchment approach are that climate variability between preand postdisturbance periods does not have to be considered as the same time periods are used for analysis, and that it avoids assumptions considered when partly or fully relying on simulation modelling. Limitations of the approach are that finding a suitable catchment pair can be very challenging, often no pre-disturbance records are available to establish the natural difference between the catchments, and long time series of hydrological data are needed to robustly detect the effect of the human activities on hydrological drought. We suggest that the approach can be used for a first estimate of the human influence on hydrological drought, to steer campaigns to collect more data, and to complement and improve other existing methods (e.g. model-based or large-sample approaches). Published by Copernicus Publications on behalf of the European Geosciences Union. 1726 A. F. Van Loon et al.: Using paired catchments to quantify the human influence on hydrological droughts

Inferring catchment flow path responses using a data-driven model: an exploratory study based on a generalized additive model

ABSTRACT Identifying physical catchment processes from streamflow data, such as quick- and slow-flow paths, remains challenging. This study is designed to explore whether a flexible nonparametric regression model (generalized additive model, GAM) can be used to infer different flow paths. This assumes that the data relationship in data-driven models is also a reflection of catchment physical processes. The GAM, using time-lagged flow covariates, was fitted to synthetic rainfall–runoff data simulated using simple linear reservoirs. Partial plots of the time-lagged covariates show that the model could differentiate simple and more complex flow paths in simulated synthetic data with short and long memory systems and varying between dry and wet climates. Further analysis of data from real catchments showed that the model could differentiate catchments dominated by slow flow and by quick flow. Therefore, this study indicates that GAM can be used to identify catchment storages and delay processes from streamflow data.