•We modeled hydrology of the entire European continent with SWAT.•We included river discharge and nitrate loads as well as crop yield in the model.•We provide a protocol for calibration of ...large-scale models with uncertainty analysis.•We modeled blue and green water resources of Europe at subbasin level.•We improved SWAT-CUP to include parallel processing and visualization.
A combination of driving forces are increasing pressure on local, national, and regional water supplies needed for irrigation, energy production, industrial uses, domestic purposes, and the environment. In many parts of Europe groundwater quantity, and in particular quality, have come under sever degradation and water levels have decreased resulting in negative environmental impacts. Rapid improvements in the economy of the eastern European block of countries and uncertainties with regard to freshwater availability create challenges for water managers. At the same time, climate change adds a new level of uncertainty with regard to freshwater supplies. In this research we build and calibrate an integrated hydrological model of Europe using the Soil and Water Assessment Tool (SWAT) program. Different components of water resources are simulated and crop yield and water quality are considered at the Hydrological Response Unit (HRU) level. The water resources are quantified at subbasin level with monthly time intervals. Leaching of nitrate into groundwater is also simulated at a finer spatial level (HRU). The use of large-scale, high-resolution water resources models enables consistent and comprehensive examination of integrated system behavior through physically-based, data-driven simulation. In this article we discuss issues with data availability, calibration of large-scale distributed models, and outline procedures for model calibration and uncertainty analysis. The calibrated model and results provide information support to the European Water Framework Directive and lay the basis for further assessment of the impact of climate change on water availability and quality. The approach and methods developed are general and can be applied to any large region around the world.
Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope‐scale terrain structures that fundamentally organize water, ...energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid‐level water, energy, and biogeochemical fluxes. In contrast to the one‐dimensional (1‐D), 2‐ to 3‐m deep, and free‐draining soil hydrology in most ESM land models, we hypothesize that 3‐D, lateral ridge‐to‐valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing hypotheses and a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions.
Plain Language Summary
Hillslopes are key landscape features that organize water availability on land. Valley bottoms are wetter than hilltops, and sun‐facing slopes are warmer and drier than shaded ones. This hydrologic organization leads to systematic differences in soil and vegetation between valleys and hilltops, and between sunny and shady slopes. Although these patterns are fundamental to understanding the structures and functions of water and terrestrial ecosystems, they are too fine grained to be represented in global‐scale Earth System Models. Here we bring together Critical Zone scientists who study the interplay of vegetation, the porous upper layer of the continental crust from vegetation to bedrock, and moisture dynamics deep into the weathered bedrock underlying hillslopes and Earth System Model scientists who develop global models, to ask: Do hillslope‐scale processes matter to predicting global change? The answers will help scientists understand where and why hillslopes matter, and to better predict how terrestrial ecosystems, including societies, may affect and be affected by our rapidly changing planet.
Key Points
Lateral flow from ridges to valleys, and contrasts between sunny and shady slopes organize water, energy and vegetation across landscapes
These processes may affect Earth System Model predictions of terrestrial water storage and fluxes, as well as ecosystem resilience to stress
The greatest knowledge gap is the subsurface structure; Critical Zone science can offer new insights into terrestrial water storage/fluxes
Large-scale hydrologic models are being used more and more in watershed management and decision making. Sometimes rapid modeling and analysis is needed to deal with emergency environmental disasters. ...However, time is often a major impediment in the calibration and application of these models. To overcome this, most projects are run with fewer simulations, resulting in less-than-optimum solutions. In recent years, running time-consuming projects on gridded networks or clouds in Linux systems has become more and more prevalent. But this technology, aside from being tedious to use, has not yet become fully available for common usage in research, teaching, and small to medium-size applications. In this paper we explain a methodology where a parallel processing scheme is constructed to work in the Windows platform. We have parallelized the calibration of the SWAT (Soil and Water Assessment Tool) hydrological model, where one could submit many simultaneous jobs taking advantage of the capabilities of modern PC and laptops. This offers a powerful alternative to the use of grid or cloud computing. Parallel processing is implemented in SWAT-CUP (SWAT Calibration and Uncertainty Procedures) using the optimization program SUFI2 (Sequential Uncertainty FItting ver. 2). We tested the program with large, medium, and small-size hydrologic models on several computer systems, including PCs, laptops, and servers with up to 24 CPUs. The performance was judged by calculating speedup, efficiency, and CPU usage. In each case, the parallelized version performed much faster than the non-parallelized version, resulting in substantial time saving in model calibration.
•Interrelations among users and countries in water scarce areas are geo-temporally identified.•Water scarcity occurs mainly in isolated locations in the winter.•Water scarcity occurs on vastest areas ...in the summer due to irrigation.•Water scarcity should primarily be mitigated at national level.•International cooperation is key to mitigate water scarcity in certain countries.
Large-scale water scarcity indicators have been widely used to map and inform decision makers and the public about the use of river flows, a vital and limited renewable resource. However, spatiotemporal interrelations among users and administrative entities are still lacking in most large-scale studies. Water scarcity and interrelations are at the core of the water-ecosystem-energy-food nexus. In this paper, we balance water availability in the Black Sea catchment with requirements and consumptive use of key water users, i.e., municipalities, power plants, manufacturing, irrigation and livestock breeding, accounting for evaporation from major reservoirs as well as environmental flow requirements. We use graph theory to highlight interrelations between users and countries along the hydrological network. The results show that water scarcity occurs mainly in the summer due to higher demand for irrigation and reservoir evaporation in conjunction with relatively lower water resources, and in the fall-winter period due to lower water resources and the relatively high demand for preserving ecosystems and from sectors other than irrigation. Cooling power plants and the demands of urban areas cause scarcity in many isolated locations in the winter and, to a far greater spatial extent, in the summer with the demands for irrigation. Interrelations in water scarcity-prone areas are mainly between relatively small, intra-national rivers, for which the underlying national and regional governments act as key players in mitigating water scarcity within the catchment. However, many interrelations exist for larger rivers, highlighting the need for international cooperation that could be achieved through a water-ecosystem-energy-food nexus.
The calibration and execution of large hydrological models, such as SWAT (soil and water assessment tool), developed for large areas, high resolution, and huge input data, need not only quite a long ...execution time but also high computation resources. SWAT hydrological model supports studies and predictions of the impact of land management practices on water, sediment, and agricultural chemical yields in complex watersheds. The paper presents the gSWAT application as a web practical solution for environmental specialists to calibrate extensive hydrological models and to run scenarios, by hiding the complex control of processes and heterogeneous resources across the grid based high computation infrastructure. The paper highlights the basic functionalities of the gSWAT platform, and the features of the graphical user interface. The presentation is concerned with the development of working sessions, interactive control of calibration, direct and basic editing of parameters, process monitoring, and graphical and interactive visualization of the results. The experiments performed on different SWAT models and the obtained results argue the benefits brought by the grid parallel and distributed environment as a solution for the processing platform. All the instances of SWAT models used in the reported experiments have been developed through the enviroGRIDS project, targeting the Black Sea catchment area.
Most Earth system models are based on grid-averaged soil columns that do not communicate with one another, and that average over considerable sub-grid heterogeneity in land surface properties, ...precipitation (P), and potential evapotranspiration (PET). These models also typically ignore topographically driven lateral redistribution of water (either as groundwater or surface flows), both within and between model grid cells. Here, we present a first attempt to quantify the effects of spatial heterogeneity and lateral redistribution on grid-cell-averaged evapotranspiration (ET) as seen from the atmosphere over heterogeneous landscapes. Our approach uses Budyko curves, as a simple model of ET as a function of atmospheric forcing by P and PET. From these Budyko curves, we derive a simple sub-grid closure relation that quantifies how spatial heterogeneity affects average ET as seen from the atmosphere. We show that averaging over sub-grid heterogeneity in P and PET, as typical Earth system models do, leads to overestimations of average ET. For a sample high-relief grid cell in the Himalayas, this overestimation bias is shown to be roughly 12 %; for adjacent lower-relief grid cells, it is substantially smaller. We use a similar approach to derive sub-grid closure relations that quantify how lateral redistribution of water could alter average ET as seen from the atmosphere. We derive expressions for the maximum possible effect of lateral redistribution on average ET, and the amount of lateral redistribution required to achieve this effect, using only estimates of P and PET in possible source and recipient locations as inputs. We show that where the aridity index P/PET increases with altitude, gravitationally driven lateral redistribution will increase average ET (and models that overlook lateral redistribution will underestimate average ET). Conversely, where the aridity index P/PET decreases with altitude, gravitationally driven lateral redistribution will decrease average ET. The effects of both sub-grid heterogeneity and lateral redistribution will be most pronounced where P is inversely correlated with PET across the landscape. Our analysis provides first-order estimates of the magnitudes of these sub-grid effects, as a guide for more detailed modeling and analysis.
Accurately estimating large-scale evapotranspiration (ET) rates is essential to understanding and predicting global change. Evapotranspiration models
that are applied at a continental scale typically ...operate on relatively large spatial grids, with the result that the heterogeneity in land surface
properties and processes at smaller spatial scales cannot be explicitly represented. Averaging over this spatial heterogeneity may lead to biased
estimates of energy and water fluxes. Here we estimate how averaging over spatial heterogeneity in precipitation (P) and potential
evapotranspiration (PET) may affect grid-cell-averaged evapotranspiration rates, as seen from the atmosphere over heterogeneous landscapes
across the globe. Our goal is to identify where, under what conditions, and at what scales this “heterogeneity bias” could be most important but
not to quantify its absolute magnitude. We use Budyko curves as simple functions that relate ET to precipitation and potential
evapotranspiration. Because the relationships driving ET are nonlinear, averaging over subgrid heterogeneity in P and PET will lead to biased
estimates of average ET. We examine the global distribution of this bias, its scale dependence, and its sensitivity to variations in P vs.
PET. Our analysis shows that this heterogeneity bias is more pronounced in mountainous terrain, in landscapes where spatial variations in P and PET
are inversely correlated, and in regions with temperate climates and dry summers. We also show that this heterogeneity bias increases on average,
and expands over larger areas, as the grid cell size increases.
Evapotranspiration (ET) influences land–climate interactions, regulates the
hydrological cycle, and contributes to the Earth's energy balance. Due to
its feedback to large-scale hydrological ...processes and its impact on
atmospheric dynamics, ET is one of the drivers of droughts and heatwaves.
Existing land surface models differ substantially, both in their estimates
of current ET fluxes and in their projections of how ET will evolve in the
future. Any bias in estimated ET fluxes will affect the partitioning between sensible and latent heat and thus alter model predictions of temperature and precipitation. One potential source of bias is the so-called “aggregation bias” that arises whenever nonlinear processes, such as those that regulate ET fluxes, are modeled using averages of heterogeneous inputs. Here we demonstrate a general mathematical approach to quantifying and correcting for this aggregation bias, using the GLEAM land evaporation model as a relatively simple example. We demonstrate that this aggregation bias can lead to substantial overestimates in ET fluxes in a typical large-scale land surface model when sub-grid heterogeneities in land surface properties are averaged out. Using Switzerland as a test case, we examine the scale dependence of this aggregation bias and show that it can lead to an average overestimation of daily ET fluxes by as much as 10 % across the whole country (calculated as the median of the daily bias over the growing season). We show how our approach can be used to identify the dominant drivers of aggregation bias and to estimate sub-grid closure relationships that can correct for aggregation biases in ET estimates, without explicitly representing sub-grid heterogeneities in large-scale land surface models.
•Reconciling the DPSIR and vulnerability frameworks was achieved by linking the terms and concepts.•Vulnerability assessments should orient themselves towards more dynamic models.•Vulnerability ...resulted from lower river discharge conflicting between irrigation and environmental water demands.•Some countries might benefit from climate change, while others might encounter worse agro-climatic conditions in future.•Many policies based on DPSIR indicators (e.g. WFD) could benefit from integrating the vulnerability framework.
Agriculture in the Black Sea catchment is responsible for a considerable share of the area's total water withdrawal and the majority of its total water consumption. It therefore plays a key role in sustainable water resources management. However, in the future water resources will be exposed to climate change.
This assessment aims at identifying the most vulnerable regions and to explain the reasons of this vulnerability. It is based on a combination of the well-known Driver–Pressure–State–Impact–Response framework (DPSIR) and the vulnerability concept as defined by the Intergovernmental Panel on Climate Change (IPCC). Three distinctive climate change scenarios are used to assess their impacts on water resources for agriculture: (1) an increase in temperature; (2) a decrease in precipitation; and (3) a combination of the first and second scenarios. The data for this assessment is derived from a SWAT model (Soil and Water Assessment Tool).
The results show that the regions of the Black Sea catchment are impacted by climate change differently. Some countries benefit from climate change (e.g., Turkey, Ukraine, Romania, Moldova, Hungary, Bulgaria) while others will encounter considerably worse agro-climatic conditions in the future (e.g., Montenegro, Austria, Bosnia–Herzegovina). Additionally, natural plant growth conditions mostly improve due to more suitable temperature conditions. In contrast, the deteriorating agricultural conditions mainly result from a diminishing irrigation potential that is caused by reduced precipitation.
The conclusion emphasises the important role of the legal framework as well as more sustainable agronomic practices and proposes improvements for future assessment methods in this research field.
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