Institute of Water Problems

The Prediction in Ungauged Basins (PUB) initiative of the International Association of Hydrological Sciences (IAHS), launched in 2003 and concluded by the PUB Symposium 2012 held in Delft (23-25 October 2012), set out to shift the scientific culture of hydrology towards improved scientific understanding of hydrological processes, as well as associated uncertainties and the development of models with increasing realism and predictive power. This paper reviews the work that has been done under the six science themes of the PUB Decade and outlines the challenges ahead for the hydrological sciences community.

This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through online media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focused on the process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come.

Abstract Risk management has reduced vulnerability to floods and droughts globally 1,2 , yet their impacts are still increasing 3 . An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data 4,5 . On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change 3 .

Thirty‐three snowpack models of varying complexity and purpose were evaluated across a wide range of hydrometeorological and forest canopy conditions at five Northern Hemisphere locations, for up to two winter snow seasons. Modeled estimates of snow water equivalent (SWE) or depth were compared to observations at forest and open sites at each location. Precipitation phase and duration of above‐freezing air temperatures are shown to be major influences on divergence and convergence of modeled estimates of the subcanopy snowpack. When models are considered collectively at all locations, comparisons with observations show that it is harder to model SWE at forested sites than open sites. There is no universal “best” model for all sites or locations, but comparison of the consistency of individual model performances relative to one another at different sites shows that there is less consistency at forest sites than open sites, and even less consistency between forest and open sites in the same year. A good performance by a model at a forest site is therefore unlikely to mean a good model performance by the same model at an open site (and vice versa). Calibration of models at forest sites provides lower errors than uncalibrated models at three out of four locations. However, benefits of calibration do not translate to subsequent years, and benefits gained by models calibrated for forest snow processes are not translated to open conditions.

Abstract Modeling dynamic geophysical phenomena is at the core of Earth and environmental studies. The geoscientific community relying mainly on physical representations may want to consider much deeper adoption of artificial intelligence (AI) instruments in the context of AI's global success and emergence of big Earth data. A new perspective of using hybrid physics‐AI approaches is a grand vision, but actualizing such approaches remains an open question in geoscience. This study develops a general approach to improving AI geoscientific awareness, wherein physical approaches such as temporal dynamic geoscientific models are included as special recurrent neural layers in a deep learning architecture. The illustrative case of runoff modeling across the conterminous United States demonstrates that the physics‐aware DL model has enhanced prediction accuracy, robust transferability, and good intelligence for inferring unobserved processes. This study represents a firm step toward realizing the vision of tackling Earth system challenges by physics‐AI integration.

Twenty-one land surface schemes (LSSs) performed simulations forced by 18 yr of observed meteorological data from a grassland catchment at Valdai, Russia, as part of the Project for the Intercomparison of Land-Surface Parameterization Schemes (PILPS) Phase 2(d). In this paper the authors examine the simulation of snow. In comparison with observations, the models are able to capture the broad features of the snow regime on both an intra-and interannual basis. However, weaknesses in the simulations exist, and early season ablation events are a significant source of model scatter. Over the 18-yr simulation, systematic differences between the models' snow simulations are evident and reveal specific aspects of snow model parameterization and design as being responsible. Vapor exchange at the snow surface varies widely among the models, ranging from a large net loss to a small net source for the snow season. Snow albedo, fractional snow cover, and their interplay have a large effect on energy available for ablation, with differences among models most evident at low snow depths. The incorporation of the snowpack within an LSS structure affects the method by which snow accesses, as well as utilizes, available energy for ablation. The sensitivity of some models to longwave radiation, the dominant winter radiative flux, is partly due to a stability-induced feedback and the differing abilities of models to exchange turbulent energy with the atmosphere. Results presented in this paper suggest where weaknesses in macroscale snow modeling lie and where both theoretical and observational work should be focused to address these weaknesses.

In the Project for Intercomparison of Land-Surface Parameterization Schemes phase 2a experiment, meteorological data for the year 1987 from Cabauw, the Netherlands, were used as inputs to 23 land-surface flux schemes designed for use in climate and weather models. Schemes were evaluated by comparing their outputs with long-term measurements of surface sensible heat fluxes into the atmosphere and the ground, and of upward longwave radiation and total net radiative fluxes, and also comparing them with latent heat fluxes derived from a surface energy balance. Tuning of schemes by use of the observed flux data was not permitted. On an annual basis, the predicted surface radiative temperature exhibits a range of 2 K across schemes, consistent with the range of about 10 W m 2 in predicted surface net radiation. Most modeled values of monthly net radiation differ from the observations by less than the estimated maximum monthly observational error (10 W m 2 ). However, modeled radiative surface temperature appears to have a systematic positive bias in most schemes; this might be explained by an error in assumed emissivity and by models' neglect of canopy thermal heterogeneity. Annual means of sensible and latent heat fluxes, into which net radiation is partitioned, have ranges across schemes of

Abstract Many snow models have been developed for various applications such as hydrology, global atmospheric circulation models and avalanche forecasting. The degree of complexity of these models is highly variable, ranging from simple index methods to multi-layer models that simulate snow-cover stratigraphy and texture. In the framework of the Snow Model Intercomparison Project (SnowMIP), 23 models were compared using observed meteorological parameters from two mountainous alpine sites. The analysis here focuses on validation of snow energy-budget simulations. Albedo and snow surface temperature observations allow identification of the more realistic simulations and quantification of errors for two components of the energy budget: the net short- and longwave radiation. In particular, the different albedo parameterizations are evaluated for different snowpack states (in winter and spring). Analysis of results during the melting period allows an investigation of the different ways of partitioning the energy fluxes and reveals the complex feedbacks which occur when simulating the snow energy budget. Particular attention is paid to the impact of model complexity on the energy-budget components. The model complexity has a major role for the net longwave radiation calculation, whereas the albedo parameterization is the most significant factor explaining the accuracy of the net shortwave radiation simulation.

Abstract. This paper describes ESM-SnowMIP, an international coordinated modelling effort to evaluate current snow schemes, including snow schemes that are included in Earth system models, in a wide variety of settings against local and global observations. The project aims to identify crucial processes and characteristics that need to be improved in snow models in the context of local- and global-scale modelling. A further objective of ESM-SnowMIP is to better quantify snow-related feedbacks in the Earth system. Although it is not part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), ESM-SnowMIP is tightly linked to the CMIP6-endorsed Land Surface, Snow and Soil Moisture Model Intercomparison (LS3MIP).

It is generally accepted that drought is one of the most costly weather-related natural hazards. In 2015, a long-lasting drought hit Europe, particularly affecting central and eastern Europe. In some regions it was the driest (North Slovakia) and in others (Czech Republic and Poland) it was the second driest summer of the last 50 years (following 2003). Key questions are: (i) how extreme are these events, not only in terms of hydro-meteorological characteristics but also impacts? and (ii) how are these impacts managed? Droughts often are viewed from a climatic perspective (e.g. Herring et al., 2015; Heim, 2015), with their severity defined by the strength of the anomaly in meteorological conditions (e.g. sea surface temperature, geopotential height, precipitation or temperature). Normalized anomalies in climatic variables, such as the Standardized Precipitation Index (SPI, McKee et al., 1993; WMO, 2006) and the more recently developed Standardized Precipitation–Evapotranspiration Index (SPEI, Vicente-Serrano et al., 2010), have become standard tools to characterize drought. Although the SPI and SPEI have proved their applicability across a wide range of hydro-climatological regimes, there is a pressing need to monitor the impacts of climate and weather events in a more systematic way (Stahl et al., 2016). Many drought-related impacts (e.g. crop yields, water-borne transport, aquatic ecosystems, water supply, energy production) are associated with hydrology rather than solely with weather. Hydrologically oriented drought studies have shown that drought in groundwater or streamflow (hydrological drought) deviates from meteorological drought (precipitation anomalies) (Changnon, 1987; Peters et al., 2003; Vidal et al., 2010; Hannaford et al., 2011; Van Loon and Van Lanen, 2012; Van Dijk et al., 2013). Hydrological drought is a complex phenomenon that integrates many river basin characteristics, such as (but not limited to) land cover, topography, geology and river network structure (Van Lanen et al., 2013; Stoelzle et al., 2014). Minor meteorological droughts may not show up as a hydrological drought, whereas a series of meteorological droughts can merge to form a long-lasting hydrological drought, which usually has a later onset and recovery. Hydrological drought has in most cases a smaller intensity than meteorological drought. The areas that are covered by the different drought types are also varying (Peters et al., 2006; Tallaksen et al., 2009). Additionally, water managers take actions in response to the (forecasted) impacts (e.g. water storage, abstractions, water transfers) in which hydrology plays a key role. This commentary discusses how drought, from its origin as a meteorological anomaly, manifests itself as a deficiency in soil moisture and subsequently as a hydrological drought. Furthermore, the commentary emphasizes that better understanding and management of drought requires understanding this propagation of water deficits through the hydrological cycle, with consideration of the nature of the resultant impacts on socioeconomic and natural systems also of critical importance. Drought characterization from such a perspective requires concerted multi-disciplinary action from both the climatic and hydrological communities. Although some initiatives (Harding et al., 2011; Schellnhuber et al., 2013) are promising, more widespread and comprehensive action is necessary. We use the 2015 European drought as an example. The summer (June – August) of 2015 was characterized by daily maximum temperatures 2 °C higher than the seasonal mean over most of western Europe, and more than 3 °C higher in central Europe (Figure 1a). Large parts of Europe also experienced a severe lack of rainfall and higher evapotranspiration than normal, with negative values of the three-month standardized precipitation–evaporation anomaly (SPEI3) from June onwards across a widespread area. Summer SPEI3 values dropped to as low as −4 in central and eastern Europe (Figure 1b). Similar to the extreme 2003 summer drought, upper level atmospheric circulation over continental Europe was characterized by a large, positive 500-hPa geopotential height anomaly (Z500; Figure 1c). Positive anomalies first occurred in March, and persisted throughout the summer. This high pressure blocking pattern over Europe prevented the flow of moisture and precipitation across much of Europe. During summer, the positive European anomaly was bordered by a large negative Z500 over the central North Atlantic Ocean, extending to northern Scandinavia. Summer sea surface temperature (SST) was characterized by large negative anomalies in the central North Atlantic Ocean (with the peak difference approximately co-located with the peak Z500 difference), and large positive anomalies in the Mediterranean basin (Figure 1d). The 2015 negative Atlantic SST (JJA) anomaly was within the top 10 coldest summers in this region in the ERSST v4 record extending back to 1854. Vegetation stress in summer 2015 (anomaly of absorbed photosynthetically active radiation; Figure 2) displayed similarities to the SPEI pattern (Figure 1b), but also with obvious differences. At the end of June, only some scattered areas with vegetation stress occurred, mainly in eastern Europe (Ukraine, Romania, Balkan Adriatic coast). In August, these areas combined into a west-east zone stretching from central France into Ukraine and Belarus. In October, the west-east zone divided into three core regions: southern Germany, Poland and Ukraine, and some new areas (Latvia, northern Europe) in response to a precipitation deficit that developed in early autumn (not shown). In all cases, the area affected by vegetation stress was substantially smaller than the area experiencing moderate meteorological drought (SPEI < −1, Figure 1b), although they occupied similar regions. Low flow and drought characteristics were computed from about 800 daily streamflow time series across Europe (Laaha et al., 2016). The return period of the 7-day minimum flow in 2015 was determined for each month (Figure 3). In June, most gauging stations showed streamflow with return periods <2 years (Figure 3a), with a few exceptions (mostly <5 years). Although SPEI3 ≤ −1 in June occurred in a wide west-east band from the Benelux into Belarus and Ukraine (not shown), low flows remained in the normal range. In August, low flows became more extreme (Figure 3b) in a southwest-northeast zone north of the Alps. Particularly in central Europe (Czech Republic, Poland, southern Germany, northern Austria) and also France, the return period of the 7-day minimum flow increased to more than 50 years. In the Czech Republic and Poland (e.g. Vistula) many rivers recorded the lowest flow on record. Some recovery was seen in the autumn, but low flows were still extreme (return period >20 years) in southern Germany, southwestern Poland and the Czech Republic (Figure 3c). Return periods for drought duration (the period that streamflow is below flow equaled or exceeded 80% of the time over the period 1976–2010) are presented in Figure 3d. Drought characteristics could not be fully established for 2015, because for many gauging stations flow by the end of the autumn was still below the drought threshold. A typical feature of the 2015 drought was its long duration. For instance, one of the major rivers in Europe, the Rhine at the Dutch–German boundary, faced the longest running low flow period since the 1976 benchmark drought. Return periods in drought duration of more than 20 years were mainly seen in central Europe. The flow analysis showed that the drought followed the SPEI3 JJA pattern, but that the hydrological response was delayed through drought propagation and that local differences occurred because of catchment storage processes and antecedent conditions. The impacts of the 2015 drought were manifold across Europe, as derived from various text sources (e.g. reports, websites). The wide range of impacts is not uncommon as illustrated for previous events by the European Drought Impact Inventory, EDII (Stahl et al., 2016). In some central and eastern European regions the impacts continued even into 2016. No drought impacts were reported in Scandinavia and the UK, which matches the drought pattern in Figures 1–3. The vegetation stress (Figure 2) induced by excessive heat and soil water drought led to lower crop yields. For example, crop losses of up to 50% were reported in the Czech Republic, Germany, Poland and Slovakia for sugar beet and potatoes, while maize was unable to build cobs in some regions. The drought also had a significant impact on livestock farming, with a 50% lower hay harvest (Czech Republic), failing grass cuts (Germany, Slovakia) and substantially lower milk production (Slovakia and Romania). Czech authorities have estimated that the impact of the 2015 drought on agriculture amounts to € 50–100 million. The drought also led to worst summer for Czech firefighters in at least the last ten years, with almost twice as many fires as in 2014. In Austria the drought caused an exceptionally long wildfire season, lasting until the end of 2015. The hydrological component of the 2015 drought (Figure 3) had an impact on a wide range of sectors, including water supply, energy production, waterborne transportation, freshwater aquaculture and fisheries, water quality, fresh water ecology, tourism and recreation. A summary of these impacts follows. Across central Europe and parts of eastern Europe (e.g. Romania) hundreds of towns and villages faced drinking water supply deficiencies. In southern Germany, boreholes dried up in crystalline rocks leading to water supply shortages for cattle. In eastern Romania record-low groundwater levels were registered and because of groundwater overexploitation water quality deteriorated. Low flows and associated high water temperatures caused reduced energy production along rivers in southern Germany, Czech Republic, Poland and European Russia. Some hydropower stations had to be shut down: in the northeast Czech Republic the majority of small hydropower plants were out of service for four months. In August, 1600 of the biggest companies in Poland suffered from power restrictions. French and Czech hydropower production was 30–50% lower than normal in some summer and autumn months. Similar reductions were reported for one of the main hydropower stations in the downstream part of the Don River (Russia). The 2015 drought significantly impacted water-borne transportation, notably in France, Germany and European Russia. In Germany, load losses on the Rhine, Danube, Elbe, Oder and Weser Rivers and in Russia on the Don River were up to 50%. The drought and associated heat triggered oxygen deficits and high temperatures in surface water bodies in Germany, Slovakia and European Russia, which influenced freshwater aquaculture and fisheries (lower fish yields), while causing other water quality issues (blue–green algae blooms and botulism). Dried-up fish breeding grounds and dying fish were reported in several central and eastern European countries. Fresh water ecosystems in the Czech Republic were also impacted by hydropower plants; 25% of the small plants could not comply with the ecological minimum flow standard. Violation of environmental flow requirements in upstream headwaters also happened in Germany. Tourism and recreation were impacted in several countries because low reservoir and river levels restricted leisure activities in these water bodies. Access to forests was also restricted because of the high fire risk. The impacts of the 2015 drought were also felt beyond the core region in central and eastern Europe. For example, in Belgium and the Netherlands a 1-in-20 year meteorological drought occurred from April to August. Some early crops (such as potatoes) had yield losses of up to 30%. Low flow in the major Dutch rivers caused salt water intrusion in the river mouths over tens of kilometres, affecting fresh and brackish water ecosystems. Water-borne transport in the Netherlands was strongly impacted. The shallow water depth affected transport until late November (with up to 50% cargo losses in the autumn), mainly because of little river inflow from upstream (Switzerland and southern Germany). Shrinkage of old peat dikes caused cracks leading to increased flood risk in the Netherlands. In the autumn many houseboats were sitting askew on dry stream bottoms because of the unprecedented low water levels. Surface water and reservoirs are particularly important means to manage a drought. For instance, in the Czech Republic, reservoirs were 90% full at the start of the 2015 summer. During the drought event, reservoirs were emptied to provide direct water and to increase low flows downstream. Reservoir storage remained above 30% with a few exceptions, but most reservoirs were still in decline at the end of October 2015, which had not happened since 2003. In the eastern part of Romania, the volume of some large inter-annual regulation reservoirs was also very low (remaining storage: about 30%) at the end of 2015. In northeastern France, reservoirs used for sustaining low flows had their available volume below the 1-in-10 year level in early September. In Germany, record water transfers from the Danube to Main basins were implemented for low flow augmentation. In the Dutch lowlands, surface water levels were raised to conserve water. Some canals or sections in northeastern France were closed to water-borne transportation for several months, not re-opening until the end of 2015. Transport in Romania also faced restrictions. In the Netherlands, boats had to cope with more costly lock operations. Special measures were implemented in the main river network until the end of the autumn as a response to the low inflow from upstream. In many European regions crops were irrigated when possible. Record irrigation of corn and tobacco was reported in the Upper Rhine Valley in Germany. In contrast, water abstraction restrictions were in place in 70 French departments in early August, which enforced a complete water abstraction ban for all non-priority uses, including irrigation. In early November some crisis orders were still active in Burgundy. In the Netherlands there were bans on abstraction of surface water for irrigation to avoid deterioration of water quality until mid-August when rain caused relief. Locally, in the Czech Republic, Poland, Slovakia and southern Germany tank trucks were ordered to fill reservoirs in municipalities with water supply deficiencies because of low inflow from local springs. Many municipal councils banned water use for watering gardens, swimming pools or washing cars. Additional flushing of the regional surface water system in the Netherlands using water from the main rivers occurred to avoid further salinization. Emergency pumps were installed to reroute surface water and in other places surface water was blocked from flowing into certain streams to avoid further deterioration of water quality. Various water inlets were closed to avoid spreading of blue–green algae. Natural swimming baths were closed (Germany, the Netherlands) due to the deteriorated water quality (blue–green algae bloom and botulism). Resettlement of fish was reported in Germany, Czech Republic and Slovakia. Aquaculture had increased costs for extra oxygenation. Various measures were also taken for human health and public safety reasons. In German, Dutch Slovak and Romanian cities, additional water was required for watering parks to avoid further development of the urban heat island and to maintain aesthetic value. In Bratislava and Bucharest, water tanks were used to supply tourists and city inhabitants at selected points. The Dutch Water Boards had to frequently inspect 3500 km of drought sensitive peat dikes and to irrigate in case of drought cracks. As shown for the 2015 European event, drought impacts are largely connected to soil water drought (crop yield, wildfires) or to hydrological drought (water supply, energy, transportation, recreation, water quality) rather than directly to the meteorological drought. This implies that knowledge of hydrology, i.e. the propagation of meteorological drought into a hydrological drought, including the role of antecedent water storage, is needed to understand drought impacts. It is also illustrated that stakeholders and water managers respond to impacts by taking measures (e.g. irrigation, water abstractions, use of reservoir storage, rerouting, transfers, conservation) to mitigate impacts, but which can also enhance impacts elsewhere (Van Dijk et al., 2013; Van Loon et al., 2016). Enhancement of impacts typically involves ecological minimum flows that cannot be sustained because of upstream water use. During droughts there is a high pressure on groundwater resources and in several regions more groundwater is abstracted than recharged (e.g. Castle et al., 2014; Panda and Wahr, 2015), leading to undesirable impacts (e.g. reduced groundwater flow to riparian areas and rivers). However, reports on declining groundwater tables are not everywhere available, or no separation is made between impacts due to the drought itself as compared to abstractions due to increased groundwater exploitation, as advised by Van Loon and Van Lanen (2013). The need for an enhanced hydrological perspective in terms of understanding and managing drought impacts requires urgent action. First, the European water sector should make near-real time hydrological data as readily available as meteorological data (Haylock et al., 2008; Hannah et al., 2011). Currently, large-scale observed flow data become available not earlier than a year after measurement (Global Runoff Data Centre, www.bafg.de/GRDC/EN), which forces experts to resort to simulated flow for pan-European studies (e.g. Gudmundsson and Seneviratne, 2015). Furthermore, drought impacts and response measures (including their success rate) should be archived, for example using the European Drought Impact Inventory (Stahl et al., 2016). Second, multi-monthly and seasonal drought forecasting should be improved beyond the currently available 10 or 14-day forecasted atmospheric indices and soil water anomalies. Some encouraging initiatives at the national scale are ongoing, as reported by the Hydrological Ensemble Prediction Experiment (HEPEX) community. For example, Prudhomme (2015) presented the first operational forecast system for Great Britain that delivers an outlook of 1 to 3 months for river flow and groundwater levels. Promising results on the forecasted 7-day minimum flow for major German waterways were also shown by Meißner et al. (2015), which are based upon the seasonal correlation between global oceanic and climatic data, soil moisture and low river flow (Ionita et al., 2008; 2015). Third, drought monitoring and forecasting should be embedded in drought policy. Wilhite (2014) provides a template for action, which in Europe could improve the drought chapter in the River Basin Management Plans. Managing drought in a pro-active way requires a concerted action of the hydrological and climatic communities. Such action should include pan-European monitoring of hydro-meteorological variables and multi-monthly and seasonal forecasting of both climatic and hydrological variables. Furthermore, impact assessments and exploration of potential promising measures to reduce impacts (considering context specific conditions at the river basin scale) represent a critical research direction for drought impact mitigation. This commentary is by a of European drought experts from the Low and Drought which to near-real time hydrological data and impact reports across Europe, which have Data by national hydro-meteorological the European Drought and and from the Access for most of the Access and was

Two approaches can be distinguished in studies of climate change impacts on water resources when accounting for issues related to impact model performance: (1) using a multi-model ensemble disregarding model performance, and (2) using models after their evaluation and considering model performance. We discuss the implications of both approaches in terms of credibility of simulated hydrological indicators for climate change adaptation. For that, we discuss and confirm the hypothesis that a good performance of hydrological models in the historical period increases confidence in projected impacts under climate change, and decreases uncertainty of projections related to hydrological models. Based on this, we find the second approach more trustworthy and recommend using it for impact assessment, especially if results are intended to support adaptation strategies. Guidelines for evaluation of global- and basin-scale models in the historical period, as well as criteria for model rejection from an ensemble as an outlier, are also suggested.

Activated sludge (AS) plays a crucial role in the treatment of domestic and industrial wastewater. AS is a biocenosis of microorganisms capable of degrading various pollutants, including organic compounds, toxicants, and xenobiotics. We performed 16S rRNA gene sequencing of AS and incoming sewage in three wastewater treatment plants (WWTPs) responsible for processing sewage with different origins: municipal wastewater, slaughterhouse wastewater, and refinery sewage. In contrast to incoming wastewater, the taxonomic structure of AS biocenosis was found to become stable in time, and each WWTP demonstrated a unique taxonomic pattern. Most pathogenic microorganisms (Streptococcus, Trichococcus, etc.), which are abundantly represented in incoming sewage, were significantly decreased in AS of all WWTPs, except for the slaughterhouse wastewater. Additional load of bioreactors with influent rich in petroleum products and organic matter was associated with the increase of bacteria responsible for AS bulking and foaming. Here, we present a novel approach enabling the prediction of the metabolic potential of bacterial communities based on their taxonomic structures and MetaCyc database data. We developed a software application, XeDetect, to implement this approach. Using XeDetect, we found that the metabolic potential of the three bacterial communities clearly reflected the substrate composition. We revealed that the microorganisms responsible for AS bulking and foaming (most abundant in AS of slaughterhouse wastewater) played a leading role in the degradation of substrates such as fatty acids, amino acids, and other bioorganic compounds. Moreover, we discovered that the chemical, rather than the bacterial composition of the incoming wastewater was the main factor in AS structure formation. XeDetect (freely available: https://sourceforge.net/projects/xedetect) represents a novel powerful tool for the analysis of the metabolic capacity of bacterial communities. The tool will help to optimize bioreactor performance and avoid some most common technical problems.

The Rho ne-Aggregation (Rho ne-AGG) Land Surface Scheme (LSS) intercomparison project is an initiative within the Global Energy and Water Cycle Experiment (GEWEX)/Global Land-Atmosphere System Study (GLASS) panel of the World Climate Research Programme (WCRP). It is a intermediate step leading up to the next phase of the Global Soil Wetness Project (GSWP) (Phase 2), for which there will be a broader investigation of the aggregation between global scales (GSWP-1) and the river scale. This project makes use of the Rho ne modeling system, which was developed in recent years by the French research community in order to study the continental water cycle on a regional scale.

A comprehensive, physically based model of snow accumulation, redistribution, sublimation, and melt for open and forested catchments was assembled, based on algorithms derived from hydrological process research in Russia and Canada. The model was used to evaluate the long-term snow dynamics of a forested and an agricultural catchment in northwestern Russia without calibration from snow observations. The model was run with standard meteorological variables for the two catchments, and its results were tested against regular surface observations of snow accumulation throughout the winter and spring period for 17 seasons. The results showed mean errors in comparison to observations of less than 3% in estimating snow water equivalent during the winter and melt seasons. Snow surface evaporation and blowing snow were found to be small components of the mass balance, but intercepted snow sublimation removed notable amounts of snow over the winter from the forested catchment. Average snow accumulation was 15% higher in the open catchment, largely due to a lack of intercepted snow sublimation. Melt rates were 23% higher in the open than in the forest, but the effect on melt duration was suppressed by the smaller premelt accumulation in the forest. Only a moderate sensitivity of snow accumulation to forest leaf area was found, while a substantial variation was observed from season to season with changing weather patterns. This suggests that the ensemble of snow processes is more sensitive to variations in atmospheric processes than in vegetation cover. The success in using algorithms from both Canada and Russia in modeling snow dynamics suggests that there may be a potential for large-scale transferability of the modeling techniques.

The Project for Intercomparison of Land-Surface Parameterization Schemes phase 2(d) experiment at Valdai, Russia, offers a unique opportunity to evaluate land surface schemes, especially snow and frozen soil parameterizations. Here, the ability of the 21 schemes that participated in the experiment to correctly simulate the thermal and hydrological properties of the soil on several different timescales was examined. Using observed vertical profiles of soil temperature and soil moisture, the impact of frozen soil schemes in the land surface models on the soil temperature and soil moisture simulations was evaluated.

Climate change impacts on water availability and hydrological extremes are major concerns as regards the Sustainable Development Goals. Impacts on hydrology are normally investigated as part of a modelling chain, in which climate projections from multiple climate models are used as inputs to multiple impact models, under different greenhouse gas emissions scenarios, which are resulting in different amounts of global temperature rise. While the goal is generally to investigate the relevance of changes in climate for the water cycle, water resources or hydrological extremes, it is often the case that variations in other components of the model chain obscure the effect of climate scenario variation. This is particularly important when assessing the impacts of relatively lower magnitudes of global warming, such as those associated with the aspirational goals of the Paris Agreement.

Abstract Twenty-seven models participated in the Earth System Model–Snow Model Intercomparison Project (ESM-SnowMIP), the most data-rich MIP dedicated to snow modeling. Our findings do not support the hypothesis advanced by previous snow MIPs: evaluating models against more variables and providing evaluation datasets extended temporally and spatially does not facilitate identification of key new processes requiring improvement to model snow mass and energy budgets, even at point scales. In fact, the same modeling issues identified by previous snow MIPs arose: albedo is a major source of uncertainty, surface exchange parameterizations are problematic, and individual model performance is inconsistent. This lack of progress is attributed partly to the large number of human errors that led to anomalous model behavior and to numerous resubmissions. It is unclear how widespread such errors are in our field and others; dedicated time and resources will be needed to tackle this issue to prevent highly sophisticated models and their research outputs from being vulnerable because of avoidable human mistakes. The design of and the data available to successive snow MIPs were also questioned. Evaluation of models against bulk snow properties was found to be sufficient for some but inappropriate for more complex snow models whose skills at simulating internal snow properties remained untested. Discussions between the authors of this paper on the purpose of MIPs revealed varied, and sometimes contradictory, motivations behind their participation. These findings started a collaborative effort to adapt future snow MIPs to respond to the diverse needs of the community.

The Project for the Intercomparison of Land-Surface Parameterization Schemes (PILPS) aims to improve understanding and modeling of land surface processes. PILPS phase 2(d) uses a set of meteorological and hydrological data spanning 18 yr (1966-83) from a grassland catchment at the Valdai water-balance research site in Russia. A suite of stand-alone simulations is performed by 21 land surface schemes (LSSs) to explore the LSSs' sensitivity to downward longwave radiative forcing, timescales of simulated hydrologic variability, and biases resulting from single-year simulations that use recursive spinup. These simulations are the first in PILPS to investigate the performance of LSSs at a site with a well-defined seasonal snow cover and frozen soil. Considerable model scatter for the control simulations exists. However, nearly all the LSS scatter in simulated root-zone soil moisture is contained within the spatial variability observed inside the catchment. In addition, all models show a considerable sensitivity to longwave forcing for the simulation of the snowpack, which during the spring melt affects runoff, meltwater infiltration, and subsequent evapotranspiration. A greater sensitivity of the ablation, compared to the accumulation, of the winter snowpack to the choice of snow parameterization is found. Sensitivity simulations starting at prescribed conditions with no spinup demonstrate that the treatment of frozen soil (moisture) processes can affect the long-term variability of the models. The single-year recursive runs show large biases, compared to the corresponding year of the control run, that can persist through the entire year and underscore the importance of performing multiyear simulations.

The Upper Blue Nile (UBN) basin is less-explored in terms of drought studies as compared to other parts of Ethiopia and lacks a basin-specific drought monitoring system. This study compares six drought indices: Standardized Precipitation Index (SPI), Standardized Precipitation Evaporation Index (SPEI), Evapotranspiration Deficit Index (ETDI), Soil Moisture Deficit Index (SMDI), Aggregate Drought Index (ADI), and Standardized Runoff-discharge Index (SRI), and evaluates their performance with respect to identifying historic drought events in the UBN basin. The indices were calculated using monthly time series of observed precipitation, average temperature, river discharge, and modeled evapotranspiration and soil moisture from 1970 to 2010. The Pearson’s correlation coefficients between the six drought indices were analyzed. SPI and SPEI at 3-month aggregate period showed high correlation with ETDI and SMDI (r &gt; 0.62), while SPI and SPEI at 12-month aggregate period correlate better with SRI. The performance of the six drought indices in identifying historic droughts: 1973–1974, 1983–1984, 1994–1995, and 2003–2004 was analyzed using data obtained from Emergency Events Database (EM-DAT) and previous studies. When drought onset dates indicated by the six drought indices are compared with that in the EM-DAT. SPI, and SPEI showed early onsets of drought events, except 2003–2004 drought for which the onset date was unavailable in EM-DAT. Similarly, ETDI, SMDI and SRI-3 showed early onset for two drought events and late onsets in one-drought event. In contrast, ADI showed late onsets for two drought events and early onset for one drought event. None of the six drought indices could individually identify the onsets of all the selected historic drought events; however, they may identify the onsets when combined by considering several input variables at different aggregate periods.

Batch anaerobic codigestion of municipal household solid waste (MHSW) and digested manure in mesophilic conditions was carried out. The different waste-to-biomass ratios and intensity of mixing were studied theoretically and experimentally. The experiments showed that when organic loading was high, intensive mixing resulted in acidification and failure of the process, while low mixing intensity was crucial for successful digestion. However, when loading was low, mixing intensity had no significant effect on the process. We hypothesized that mixing was preventing establishment of methanogenic zones in the reactor space. The methanogenic zones are important to withstand inhibition due to development of acids formed during acidogenesis. The 2D distributed models of symmetrical cylinder reactor are presented based on the hypothesis of the necessity of a minimum size of methanogenic zones that can propagate and establish a good methanogenic environment. The model showed that at high organic loading rate spatial separation of the initial methanogenic centers from active acidogenic areas is the key factor for efficient conversion of solids to methane. The initial level of methanogenic biomass in the initiation centers is a critical factor for the survival of these centers. At low mixing, most of the initiation methanogenic centers survive and expand over the reactor volume. However, at vigorous mixing the initial methanogenic centers are reduced in size, averaged over the reactor volume, and finally dissipate. Using fluorescence in situ hybridization, large irregular cocci of microorganisms were observed in the case with minimal mixing, while in the case with high stirring mainly dead cells were found.