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There is an immediate need to develop accurate and reliable global hydrological forecasts in light of the future vulnerability to hydrological hazards and water scarcity under a changing climate. As a part of the World Meteorological Organization’s (WMO) Global Hydrological Status and Outlook System (HydroSOS) initiative, we investigated different approaches to blending multi-model simulations for developing holistic operational global forecasts. The ULYSSES (mULti-model hYdrological SeaSonal prEdictionS system) dataset, to be published as ‘‘Global seasonal forecasts and reforecasts of river discharge and related hydrological variables ensemble from four state-of-the-art land surface and hydrological models’’ is used in this study. The first step for improving these forecasts is to investigate ways to improve the model simulations, as global models are not calibrated for local conditions. The analysis was performed over 119 different catchments worldwide for the baseline period of 1981–2019 for three variables: evapotranspiration, surface soil moisture and streamflow. This study evaluated blending approaches with a performance metric based (weighted) averaging of the multi-model simulations, using the catchment’s Kling-Gupta Efficiency (KGE) for the variable to define the weight. Hydrological model simulations were also bias-corrected to improve the multi-model blending output. Weighted blending in conjunction with bias-correction provided the best improvement in performance for the catchments investigated. Applying modelled weights during blending original simulations improved performance over ungauged catchments. The results indicate that there is potential to successfully and easily implement the bias-corrected weighted blending approach to improve operational forecasts globally. This work can be used to improve water resources management and hydrological hazard mitigation, especially in data-sparse regions. This research was funded by the Natural Environment Research Council, UK through UKCEH’s SUNRISE (award number NE/R000131/1) and NC-International (award number NE/X006247/1) programmes delivering National Capability, as well as the Net Zero Capacity Building Project and UKRI-NERC STF Global Water Tools Project.

The newly developed WRF-Hydro model is a fully coupled atmospheric and hydrological processes model suitable for studying the intertwined atmospheric hydrological processes. This study utilizes the WRF-Hydro system on the Three-River source region. The Nash-Sutcliffe efficiency for the runoff simulation is 0.55 compared against the observed daily discharge amount of three stations. The coupled WRF-Hydro simulations are better than WRF in terms of six ground meteorological elements and turbulent heat flux, compared to the data from 14 meteorological stations located in the plateau residential area and two flux stations located around the lake. Although WRF-Hydro overestimates soil moisture, higher anomaly correlation coefficient scores (0.955 versus 0.941) were achieved. The time series of the basin average demonstrates that the hydrological module of WRF-hydro functions during the unfrozen period. The rainfall intensity and frequency simulated by WRF-Hydro are closer to global precipitation mission (GPM) data, attributed to higher convective available potential energy (CAPE) simulated by WRF-Hydro. The results emphasized the necessity of a fully coupled atmospheric-hydrological model when investigating land-atmosphere interactions on a complex topography and hydrology region.

Hydrology is still, and for good reasons, an inexact science, even if evolving hydrological understanding has provided a basis for improved water management for at least the last three millennia. The limitations of that understanding have, however, become much more apparent and important in the last century as the pressures of increasing populations, and the anthropogenic impacts on catchment forcing and responses, have intensified. At the same time, the sophistication of hydrological analyses and models has been developing rapidly, often driven more by the availability of computational power and geographical data sets than any real increases in understanding of hydrological processes. This sophistication has created an illusion of real progress but a case can be made that we are still rather muddling along, limited by the significant uncertainties in hydrological observations, knowledge of catchment characteristics and related gaps in conceptual understanding, particularly of the sub-surface. These knowledge gaps are illustrated by the fact that for many catchments we cannot close the water balance without significant uncertainty, uncertainty that is often neglected in evaluating models for practical applications.

A key aspect of the land surface response to the atmosphere is how quickly it dries after a rainfall event. It is key because it will determine the intensity and speed of the propagation of drought and also affects the atmospheric state through changes in the surface heat exchanges. Here, we test the theory that this response can be studied as an inherent property of the land surface that is unchanging over time unless the above- and below-ground structures change. This is important as a drydown metric can be used to evaluate a landscape and its response to atmospheric drivers in models used in coupled land&ndash, atmosphere mode when the forcing is often not commensurate with the actual atmosphere. We explore whether the speed of drying of a land unit can be quantified and how this can be used to evaluate models. We use the most direct observation of drying: the rate of change of evapotranspiration after a rainfall event using eddy-covariance observations, or commonly referred to as flux tower data. We analyse the data and find that the drydown timescale is characteristic of different land cover types, then we use that to evaluate a suite of global hydrological and land surface models. We show that, at the site level, the data suggest that evapotranspiration decay timescales are longer for trees than for grasslands. The studied model&rsquo, s accuracy to capture the site drydown timescales depends on the specific model, the site, and the vegetation cover representation. A more robust metric is obtained by grouping the modeled data by vegetation type and, using this, we find that land surface models capture the characteristic timescale difference between trees and grasslands, found using flux data, better than large-scale hydrological models. We thus conclude that the drydown metric has value in understanding land&ndash, atmosphere interactions and model evaluation.

A parameterisation to incorporate the effects of frozen soil on modelled hydrology is described and implemented within a land surface model, the Joint UK Land Surface Environment Simulator. It is shown to generally improve the modelled flow of Siberian rivers compared to observations, specifically in seasons of freezing or thawing soil. Most noticeably, the revised model increases the snowmelt flow peak by 26–100% compared to the control model thereby better matching observed flows. The model physics resulting in the changes to river flow are discussed and attention is given to the effect of inaccuracies in snowfall driving data which can hinder the comparison of new model processes.

Evaporation is made up of three components: interception, soil surface evaporation and transpiration. They each have different stores of water and different characteristic timescales. It would be useful to be able to identify the relative proportions of these components at large, even global, scales for land surface model validation. The possibility of separating out the components of observed evaporation at large scales is reviewed with reference to methods used at local scales, landscape scales and scales used in remote sensing. Many of the traditional methods used require intensive measurement programmes and are unlikely to be practical at large scales. New techniques using time-series analysis may be used to deliver a global three-component evaporation product.

Siberian rivers are of global importance as they impact on the freshwater budget of the Arctic Ocean, which affects the Thermo-Haline circulation in the North Atlantic Ocean. Siberian rivers, in particular the tributaries to the larger rivers, are under-represented in the international river-regime databases. The runoff of three Russian rivers in the Central Siberian taiga (Kureyka, Karabula and Erba) is modelled to analyse the relative influence of climate. In addition three rivers (Rhine, Maas and Odra) in Western Europe are similarly assessed as a control. The results show that the role of precipitation and autocorrelation as factors in the formation of river runoff is stronger under oceanic climate conditions, increasing from the central regions of Northern Eurasia towards the Arctic Ocean in the North and the Atlantic in the West. At the same time the influence of summer temperatures is weakened. The formation of Northern Eurasian river runoff appears to be influenced by periodically thawing top horizons of permafrost soil. Time served as an indicator for land use change after inclusion of meteorological data in the models. Maas and Erba showed a significant influence of the time factor. For the Erba the onset of agricultural land use in the catchment coincides with a drop in runoff. A similar causal relationship is suggested for the Maas. Land use can change the formation of runoff, which in turn can be used as an environmental indicator for sustainable land use.

A land-surface model is used to simulate the albedo and mass of patchy snowcovers during radiation-driven melt for three years at a site in Svalbard. Performing single energy and mass balance calculations for the combined snow-covered and snow-free parts of the surface gives a faster decrease in albedo than observed because too much of the solar radiation absorbed by the composite surface is used to melt snow. Representing the snowcover separately allows the model to be calibrated to give a good match to the observed albedo for each of the years studied. A single set of model parameters cannot, however, give a good simulation for all of the years. The average snow mass and snowcover fraction measured on a grid of points can be simulated using either a distributed version of the model or a more efficient tiled version supplied with the observed relationship between snow mass and fractional coverage. Parameters obtained by optimising the snow mass simulations are more consistent from year to year than from the albedo simulations.

Current techniques to disentangle the evaporative fluxes from the continental surface into a contribution evaporated from soils and canopy, or transpired by plants, are under debate. Many isotope-based studies show that transpiration contributes generally more than 70% to the total evaporation, while other isotope-independent techniques lead to considerably smaller transpiration fractions. This paper provides a perspective on isotope-based versus non-isotope-based partitioning studies. Some partitioning results from isotope-based methods, hydrometric measurements, and modeling are presented for comparison. Moreover, the methodological aspects of the partitioning analysis are considered, including their limitations, and explanations of possible discrepancies between the methods are discussed. We suggest sources of systematic error that may lead to biases in the results, e.g., instruments inaccuracy, assumptions used in analyses, and calibration parameters. A number of comparison studies using isotope-based methods and hydrometric measurements in the same plants and climatic conditions are consistent within the errors; however, models tend to produce lower transpiration fractions. The relatively low transpiration fraction in current state-of-the-art land-surface models calls for a reassessment of the skill of the underlying model parameterizations. The scarcity of global evaporation data makes calibration and validation of global isotope-independent and isotope-based results difficult. However, isotope-enabled land-surface and global climate modeling studies allow for the evaluation of the parameterization of land-surface models by comparing the computed water isotopologue signals in the atmosphere with the available remote sensing and flux-based data sets. Future studies that allow for this evaluation could provide a better understanding of the hydrological cycle in vegetated regions.

Evaporation is an important component of the hydrological cycle. Potential evaporation (PE) from a vegetated surface is the amount of water that would be lost to the atmosphere were the supply unlimited; actual evaporation (AE) is a fraction of PE dependent on soil wetness. Many formulae exist for estimating PE from meteorological data. PE is usually a required input, with rainfall, for hydrological modelling, but PE accuracy is generally considered less important than rainfall accuracy for model performance. Few studies investigate historical evaporation trends in Britain, but generally indicate increases. Most studies presenting future PE projections for Britain indicate increased annual PE, but some suggest small decreases in some months. Limited consensus on the best formulae to derive PE projections from climate model data is further complicated by possible changes in plant behaviour (transpiration and growth) under higher carbon dioxide concentrations. Appropriate PE estimation could be particularly important in regions where precipitation and PE are in close balance, but PE uncertainty could be less important than climate model uncertainty for hydrological impacts. Further research is needed into which PE formulae are likely to be most reliable when applied with climate model data, and into climate change and plant feedbacks.

The validation of general circulation model (GCM) land surface schemes requires observations of energy and water fluxes averaged over an area of a typical GCM grid cell (100 km x 100 km) for a time period long enough to include the typical climatic conditions in that area. To create such a consolidated data set, soil moisture and surface evaporation are estimated with a detailed model of the surface energy and water balance. Observations from the Hydrological Atmospheric Pilot Experiment in the Sahel (HAPEX-Sahel) in Niger, West Africa, have shown that rainfall is a key source of spatial variability in the water and energy balance in semi arid regions. The model is therefore run for two wet seasons, forced by observations from a dense rain gauge network over an area of 10,000 km 2 . Analysis of the estimated surface fluxes indicates that bare soil evaporation has a strong influence on the spatial variability of evaporation during the wet season. On the other hand, leaf-level transpiration is relatively uniform and unstressed by soil moisture for most of the period. Modest spatial variability in transpiration develops through rainfall-induced contrasts in growth rates. The representation in GCMs of these moisture controls on evaporation can be problematic. In this case, where leaf area index is < 1, transpiration is well-represented by areal mean surface properties. However, an interactive growth model may be a useful component of the surface scheme when considering the large interannual rainfall variability typical of the Sahel. It is also found that the effect of spatial variability due to subgrid rainfall can not be ignored when modeling interception and bare soil evaporation. Methods of calculating mean fluxes based on mean moisture variables are therefore proposed. Using such a subgrid scheme, total evaporation errors are reduced by 50%.

WATER RESOURCES RESEARCH, VOL. 48, W01802, doi:10.1029/2011WR011202, 2012 Reply to comment by Keith J. Beven and Hannah L. Cloke on ‘‘Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth’s terrestrial water’’ Eric F. Wood, 1 Joshua K. Roundy, 1 Tara J. Troy, 1 Rens van Beek, 2 Marc Bierkens, 2 Eleanor Blyth, 3 Ad de Roo, 4 Petra Doll, 5 Mike Ek, 6 James Famiglietti, 7 David Gochis, 8 Nick van de Giesen, 9 Paul Houser, 10 Peter Jaffe, 1 Stefan Kollet, 11 Bernhard Lehner, 12 Dennis P. Lettenmaier, 13 Christa D. Peters-Lidard, 14 Murugesu Sivapalan, 15 Justin Sheffield, 1 Andrew J. Wade, 16 and Paul Whitehead 17 Received 25 July 2011; revised 9 November 2011; accepted 3 December 2011; published 21 January 2012. Citation: Wood, E. F., et al. (2012), Reply to comment by Keith J. Beven and Hannah L. Cloke on ‘‘Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth’s terrestrial water’’ Water Resour. Res., 48, W01802, doi:10.1029/ 2011WR011202. Introduction [ 1 ] The authors of Wood et al. [2011, hereafter W2011] would like to thank Beven and Cloke [2012, hereafter BC2012] for furthering the discussion about the pathway to- ward a global-scale hyper-resolution water-energy-biogeo- chemistry land surface modeling capability: its need, feasibility and development. Their comment brings focus to the discussion and shows that the proposed challenge to our community is one element in a long history of hydrology Department of Civil and Environmental Engineering, Princeton Uni- versity, Princeton, New Jersey, USA. Department of Physical Geography, University of Utrecht, Utrecht, Netherlands. Centre for Ecology and Hydrology, Wallingford, UK. Institute for Environment and Sustainability, European Commission Joint Research Center, Ispra, Italy. Institute of Physical Geography, J. W. Goethe University, Frankfurt am Main, Germany. Environmental Modeling Center, National Centers for Environmental Protection, Suitland, Maryland, USA. UC Center for Hydrologic Modeling, University of California-Irvine, Irvine, California, USA. Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA. Department of Water Management, Delft University of Technology, Delft, Netherlands. Department of Geography and GeoInformation Science, George Mason University, Fairfax, Virginia, USA. Meteorological Institute, University of Bonn, Bonn, Germany. Department of Geography, McGill University, Montreal, Quebec, Canada. Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, USA. Hydrological Sciences Laboratory, NASA Goddard Space Flight Cen- ter, Greenbelt, Maryland, USA. Department of Civil and Environmental Engineering and Department of Geography, University of Illinois Urbana-Champaign, Urbana, Illinois, USA. School of Human and Environmental Science, University of Reading, Reading, UK. School of Geography and the Environment, Oxford University, Oxford, UK. Copyright 2012 by the American Geophysical Union 0043-1397/12/2011WR011202 model developments with the goal to improving hydrologic predictions and understanding. [ 2 ] What is laid out in W2011 is, first and foremost, a grand challenge because (1) there is a grand need, (2) there are great new opportunities, and (3) if the hydrologic com- munity does not do it someone else will do it, albeit poorly. The reader is directed to W2011 for a discussion of the growing need for continental-scale land surface models that consider improved, scale-appropriate parameteriza- tions of the water, energy and biogeochemical cycles at resolutions on the order of 10 2 to 10 3 m grid resolutions. Some examples are presented, which were not meant be to comprehensive in their scope of detail, that include surface-subsurface interactions, land-atmospheric interac- tions and coupling, water quality that includes nonpoint pollution, and human impacts that include water manage- ment, land cover change and the effects of climate change. [ 3 ] The commentary by BC2012 focuses on just one chal- lenge or building block described in W2011: the issue of parameterization of subgrid heterogeneity and the resulting uncertainty—what they refer to as ‘‘epistemic uncertainty.’’ BC2012 interprets the Grand Challenge in W2011 as ‘‘simply moving to finer resolutions.’’ This is not what W2011 says or proposes. There are many new building blocks available for the research into hyper-resolution modeling: (1) new data sources and measurement techniques for precipitation, topog- raphy, vegetation cover, soils, but also soil moisture, evapo- transpiration, water storages (rivers, lakes, groundwater storages, soil moisture); (2) new physics—new sets of gov- erning equations, including new approaches to developing closure relations; (3) new approaches to handling known and unknown uncertainties in model structure, variables and numerics, including characterizing subgrid heterogeneity (including new ways to capture their effects) based on new insights into ecohydrology and hydropedology and approaches that utilize the coevolution of climate, soils, vege- tation and topography; (4) new approaches that can better include nonlinear feedbacks between various subsystems, and local, regional and global cycles and teleconnections; (5) new regionalization efforts aimed at learning from compara- tive analysis across climatic, geologic and human-impact W01802 1 of 3

We’ve argued in this opinion paper that the hydrology community needs a hyper-resolution land surface modeling (HyRLSM) to address the water problems facing society. We strongly believe that addressing this need, as described above, will ultimately lead to a more informed and aware society that can sustain the water needs of the future., JRC.H.7-Land management and natural hazards

[1] Observed river gauging data show significant evaporative losses from the land and water surface in the Niger inland delta. These losses indicate an important potential feedback between the land surface and atmosphere. Moreover, the reduction in river flow downstream of the wetland has clear implications for water management in the region and beyond. Here we have modeled the evaporative losses that occur over the Niger inland delta by adding an overbank flow parameterization to the Joint UK Land-Environment Simulator (JULES) land surface model. The hydrological component of this model comprises a probability-distributed model of soil moisture and runoff production coupled with a discrete approximation to the one-dimensional kinematic wave equation to route river water downslope. We use subgrid-resolution topographic data to derive a two-parameter frequency distribution of inundated areas for each grid box which we then employ to represent overbank inundation in the model. The model was driven using data from the ALMIP experiment (ALMIP stands for AMMA Land surface Model Intercomparison Project, wherein AMMA stands for African Monsoon Multidisciplinary Analyses). The model reproduces the salient features of the observed river flow and inundation patterns; these include significant evaporative losses from the inundated region accounting for doubling of the total land-atmosphere water flux during periods of greatest flooding. Our predictions of inundated area are in good agreement with observed estimates of the extent of inundation obtained using satellite infrared and microwave remote sensing.

Evaporation provides a significant energy input from land surfaces to the atmosphere and is also a primary factor in the way that incoming precipitation is lost from hydrological catchments worldwide. Therefore correctly modelling the global land–surface evaporation is critically important both for providing improved climate and weather predictions and for interpreting the potential impact of global climate change on water resources systems. Scientists worldwide are working to improve the documentation of land surface evaporation using understanding of the evaporation process in combination with data from in situ measurements, earth satellite systems, and model reanalyses. Consequently, there is an emerging ensemble of estimates of global land surface evaporation. If these are to be of value to benchmark Global Climate Model performance, then there is a need to define the nature and extent of this ensemble. It was therefore decided to bring together international scientists working in this subject area to define the current status and guide the future development of worldwide research into global evaporation measurement and modelling.

Theoretical studies dealing with aggregation of surface parameters at small scale are reviewed. Finding effective parameters for surface resistance is possible for most cases by taking simple geometric or arithmetic averages of the component resistances. The use of more sophisticated techniques such as the blending height improves the calculations. Resistances for heat and water vapour behave differently in heterogeneous terrain. A simple surface energy balance model is adapted to show the behaviour of the roughness length of heat and water vapour in heterogeneous terrain. It is suggested that this simple parameterization can adequately take into account the effect of variation in surface cover on the fluxes of heat and water vapour.

The variation in evaporative fraction and actual evaporation is examined for three sample days in the HAPEX-Sahel Intensive Observation Period (IOP), including data from all the vegetation types and sites. The trends in evaporative fraction over the IOP are also presented for eight sites. The high rate of evaporation from bare soil in the days following rainfall produces a variability in evaporation which makes differences between sites difficult to interpret on a day-to-day basis, but over the whole IOP it is shown that the millet uses a smaller proportion of the available energy for evaporation than the tiger bush or fallow savannah. The combined effect of differences in the total energy used and its partitioning into evaporation and sensible heat flux is demonstrated from the trends in cumulative total energy use and evaporation at the three southern sites, where it is shown that there is systematically less evaporation from the millet than from the savannah or tiger bush sites. (Résumé d'auteur)