Showing papers in "Water Resources Research in 2011"

Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water

Abstract: Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (∼10–100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface-subsurface interactions due to fine-scale topography and vegetation; improved representation of land-atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a “grand challenge” to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

A physically based description of floodplain inundation dynamics in a global river routing model

Abstract: [1] Current global river routing models do not represent floodplain inundation dynamics realistically because the storage and movement of surface waters are regulated by small-scale topography rather than the commonly used spatial resolution of global models. In this study, we propose a new global river routing model, CaMa-Flood, which explicitly parameterizes the subgrid-scale topography of a floodplain, thus describing floodplain inundation dynamics. The relationship between water storage, water level, and flooded area in the model is decided on the basis of the subgrid-scale topographic parameters based on 1 km resolution digital elevation model. Horizontal water transport is calculated with a diffusive wave equation, which realizes the backwater effect in flat river basins. A set of global-scale river flow simulations demonstrated an improved predictability of daily-scale river discharge in many major world rivers by incorporating the floodplain inundation dynamics. Detailed analysis of the simulated results for the Amazon River suggested that introduction of the diffusive wave equation is essential for simulating water surface elevation realistically. The simulated spatiotemporal variation of the flooded area in the Amazon basin showed a good correlation with satellite observations, especially when the backwater effect was considered. The improved predictability for daily river discharge, water surface elevation, and inundated areas by the proposed model will promote climate system studies and water resource assessments.

Pursuing the method of multiple working hypotheses for hydrological modeling

Abstract: Ambiguities in the representation of environmental processes have manifested themselves in a plethora of hydrological models, differing in almost every aspect of their conceptualization and implementation. The current overabundance of models is symptomatic of an insufficient scientific understanding of environmental dynamics at the catchment scale, which can be attributed to difficulties in measuring and representing the heterogeneity encountered in natural systems. This commentary advocates using the method of multiple working hypotheses for systematic and stringent testing of model alternatives in hydrology. We discuss how the multiple-hypothesis approach provides the flexibility to formulate alternative representations (hypotheses) describing both individual processes and the overall system. When combined with incisive diagnostics to scrutinize multiple model representations against observed data, this provides hydrologists with a powerful and systematic approach for model development and improvement. Multiple-hypothesis frameworks also support a broader coverage of the model hypothesis space and hence improve the quantification of predictive uncertainty arising from system and component nonidentifiabilities. As part of discussing the advantages and limitations of multiple-hypothesis frameworks, we critically review major contemporary challenges in hydrological hypothesis-testing, including exploiting different types of data to investigate the fidelity of alternative process representations, accounting for model structure ambiguities arising from major uncertainties in environmental data, quantifying regional differences in dominant hydrological processes, and the grander challenge of understanding the self-organization and optimality principles that may functionally explain and describe the heterogeneities evident in most environmental systems. We assess recent progress in these research directions, and how new advances are possible using multiple-hypothesis methodologies.

Quantifying the relative contribution of the climate and direct human impacts on mean annual streamflow in the contiguous United States

Abstract: [1] Both climate change and human activities are known to have induced changes to hydrology. Consequently, quantifying the net impact of human contribution to the streamflow change is a challenge. In this paper, a decomposition method based on the Budyko hypothesis is used to quantify the climate (i.e., precipitation and potential evaporation change) and direct human impact on mean annual streamflow (MAS) for 413 watersheds in the contiguous United States. The data for annual precipitation, runoff, and potential evaporation are obtained from the international Model Parameter Estimation Experiment (MOPEX), which is often assumed to only include gauges unaffected by human interferences. The data are split into two periods (1948–1970 and 1971–2003) to quantify the change over time. Although climate is found to affect MAS more than direct human impact, the results show that assuming the MOPEX data set to be unaffected by human activities is far from realistic. Climate change causes increasing MAS in most watersheds, while the direct human-induced change is spatially heterogeneous in the contiguous United States, with strong regional patterns, e.g., human activities causing increased MAS in the Midwest and significantly decreased MAS in the High Plains. The climate- and human-induced changes are found to be more severe in arid regions, where water is limited. Comparing the results to a collection of independent data sets indicates that the estimated direct human impacts on MAS in this largely nonurban set of watersheds might be attributed to several human activities, such as cropland expansion, irrigation, and the construction of reservoirs.

A simple framework for relating variations in runoff to variations in climatic conditions and catchment properties

Abstract: [1] We use the Budyko framework to calculate catchment-scale evapotranspiration (E) and runoff (Q) as a function of two climatic factors, precipitation (P) and evaporative demand (Eo = 0.75 times the pan evaporation rate), and a third parameter that encodes the catchment properties (n) and modifies how P is partitioned between E and Q. This simple theory accurately predicted the long-term evapotranspiration (E) and runoff (Q) for the Murray-Darling Basin (MDB) in southeast Australia. We extend the theory by developing a simple and novel analytical expression for the effects on E and Q of small perturbations in P, Eo, and n. The theory predicts that a 10% change in P, with all else constant, would result in a 26% change in Q in the MDB. Future climate scenarios (2070–2099) derived using Intergovernmental Panel on Climate Change AR4 climate model output highlight the diversity of projections for P (±30%) with a correspondingly large range in projections for Q (±80%) in the MDB. We conclude with a qualitative description about the impact of changes in catchment properties on water availability and focus on the interaction between vegetation change, increasing atmospheric [CO2], and fire frequency. We conclude that the modern version of the Budyko framework is a useful tool for making simple and transparent estimates of changes in water availability.

Time stability of catchment model parameters: Implications for climate impact analyses

Abstract: [1] Climate impact analyses are usually based on driving hydrological models by future climate scenarios, assuming that the model parameters calibrated to past runoff are representative of the future In this paper we calibrate the parameters of a conceptual rainfall-runoff model to six consecutive 5 year periods between 1976 and 2006 for 273 catchments in Austria and analyze the temporal change of the calibrated parameters The calibrated parameters representing snow and soil moisture processes show significant trends For example, the parameter controlling runoff generation doubled, on average, in the 3 decades Comparisons of different subregions, comparisons with independent data sets, and analyses of the spatial variability of the model parameters indicate that these trends represent hydrological changes rather than calibration artifacts The trends can be related to changes in the climatic conditions of the catchments such as higher evapotranspiration and drier catchment conditions in the more recent years The simulations suggest that the impact on simulated runoff of assuming time invariant parameters can be very significant For example, if using the parameters calibrated to 1976 – 1981 for simulating runoff for the period 2001 – 2006, the biases of median flows are, on average, 15% and the biases of high flows are about 35% The errors increase as the time lag between the simulation and calibration periods increases The implications for hydrologic prediction in general and climate impact analyses in particular are discussed

Urban Water Demand Modeling: Review of Concepts, Methods, and Organizing Principles

Abstract: [1] In this paper, we use a theoretical framework of coupled human and natural systems to review the methodological advances in urban water demand modeling over the past 3 decades. The goal of this review is to quantify the capacity of increasingly complex modeling techniques to account for complex human and natural processes, uncertainty, and resilience across spatial and temporal scales. This review begins with coupled human and natural systems theory and situates urban water demand within this framework. The second section reviews urban water demand literature and summarizes methodological advances in relation to four central themes: (1) interactions within and across multiple spatial and temporal scales, (2) acknowledgment and quantification of uncertainty, (3) identification of thresholds, nonlinear system response, and the consequences for resilience, and (4) the transition from simple statistical modeling to fully integrated dynamic modeling. This review will show that increasingly effective models have resulted from technological advances in spatial science and innovations in statistical methods. These models provide unbiased, accurate estimates of the determinants of urban water demand at increasingly fine spatial and temporal resolution. Dynamic models capable of incorporating alternative future scenarios and local stochastic analysis are leading a trend away from deterministic prediction.

Global monthly water stress: 2. Water demand and severity of water stress

Abstract: [1] This paper assesses global water stress at a finer temporal scale compared to conventional assessments. To calculate time series of global water stress at a monthly time scale, global water availability, as obtained from simulations of monthly river discharge from the companion paper, is confronted with global monthly water demand. Water demand is defined here as the volume of water required by users to satisfy their needs. Water demand is calculated for the benchmark year of 2000 and contrasted against blue water availability, reflecting climatic variability over the period 1958–2001. Despite the use of the single benchmark year with monthly variations in water demand, simulated water stress agrees well with long‐term records of observed water shortage in temperate, (sub)tropical, and (semi)arid countries, indicating that on shorter (i.e., decadal) time scales, climatic variability is often the main determinant of water stress. With the monthly resolution the number of people experiencing water scarcity increases by more than 40% compared to conventional annual assessments that do not account for seasonality and interannual variability. The results show that blue water stress is often intense and frequent in densely populated regions (e.g., India, United States, Spain, and northeastern China). By this method, regions vulnerable to infrequent but detrimental water stress could be equally identified (e.g., southeastern United Kingdom and northwestern Russia). Citation: Wada, Y., L. P. H. van Beek, D. Viviroli, H. H. Durr, R. Weingartner, and M. F. P. Bierkens (2011), Global monthly water stress: 2. Water demand and severity of water stress, Water Resour. Res., 47, W07518, doi:10.1029/2010WR009792.

Global monthly water stress: 1. Water balance and water availability

Abstract: [1] Surface fresh water (i.e., blue water) is a vital and indispensable resource for human water use in the agricultural, industrial, and domestic sectors. In this paper, global water availability is calculated by forcing the global hydrological model PCR-GLOBWB with daily global meteorological fields for the period 1958–2001. To represent blue water availability, a prognostic reservoir operation scheme was included in order to produce monthly time series of global river discharge modulated by reservoir operations. To specify green water availability for irrigated areas, actual transpiration from the model was used. Thus, the computed water availability reflects the climatic variability over 1958–2001 and is contrasted against the monthly water demand using the year 2000 as a benchmark in the companion paper. As the water that is withdrawn to meet demand directly interferes with blue water availability along the drainage network, this paper evaluates model performance for three regimes reflecting different degrees of human interference: natural discharge, discharge regulated by reservoirs, and modified discharge. In the case of modified discharge, the net blue water demand for the year 2000 is subtracted directly from the regulated discharge, taking water demand equal to consumptive water use. Results show that model simulations of monthly river discharge compare well with observations from most of the large rivers. Exceptions are basins subject to large extractions for irrigation purposes, where simulated discharge exceeds the observations even when water demand is taken into account. Including the prognostic reservoir operation scheme results in mixed performance, with a poorer approximation of peak flows but with a marginally better simulation of low flows and persistence. A comparison of simulated actual evapotranspiration with that from the ERA-40 reanalysis as a proxy for observed rates shows similar patterns over nonirrigated areas but substantial deviations over major irrigated areas. As expected, assimilated actual evapotranspiration over these areas includes water from alternative sources, whereas the simulations with PCR-GLOBWB are limited by soil moisture, i.e., green water availability. On the basis of this evidence we conclude that the simulation provides adequate fields of water availability to assess water stress at the monthly scale, for which a separate validation is provided in the companion paper.

Impact of reservoirs on river discharge and irrigation water supply during the 20th century

Abstract: This paper presents a quantitative estimation of the impact of reservoirs on discharge and irrigation water supply during the 20th century at global, continental, and river basin scale. Compared to a natural situation the combined effect of reservoir operation and irrigation extractions decreased mean annual discharge to oceans and significantly changed the timing of this discharge. For example, in Europe, May discharge decreased by 10%, while in February it increased by 8%. At the end of the 20th century, reservoir operations and irrigation extractions decreased annual global discharge by about 2.1% (930 km3 yr-1). Simulation results show that reservoirs contribute significantly to irrigation water supply in many regions. Basins that rely heavily on reservoir water are the Colorado and Columbia River basins in the United States and several large basins in India, China, and central Asia (e.g., in the Krishna and Huang He basins, reservoirs more than doubled surface water supply). Continents gaining the most are North America, Africa, and Asia, where reservoirs supplied 57, 22, and 360 km3 yr-1 respectively between 1981–2000, which is in all cases 40% more than the availability in the situation without reservoirs. Globally, the irrigation water supply from reservoirs increased from around 18 km3 yr-1 (adding 5% to surface water supply) at the beginning of the 20th century to 460 km3 yr-1 (adding almost 40% to surface water supply) at the end of the 20th century. The analysis is performed using a newly developed and validated reservoir operation scheme within a global-scale hydrology and vegetation model (LPJmL)

Overall uncertainty study of the hydrological impacts of climate change for a Canadian watershed

Abstract: [1] General circulation models (GCMs) and greenhouse gas emissions scenarios (GGES) are generally considered to be the two major sources of uncertainty in quantifying the climate change impacts on hydrology. Other sources of uncertainty have been given less attention. This study considers overall uncertainty by combining results from an ensemble of two GGES, six GCMs, five GCM initial conditions, four downscaling techniques, three hydrological model structures, and 10 sets of hydrological model parameters. Each climate projection is equally weighted to predict the hydrology on a Canadian watershed for the 2081–2100 horizon. The results show that the choice of GCM is consistently a major contributor to uncertainty. However, other sources of uncertainty, such as the choice of a downscaling method and the GCM initial conditions, also have a comparable or even larger uncertainty for some hydrological variables. Uncertainties linked to GGES and the hydrological model structure are somewhat less than those related to GCMs and downscaling techniques. Uncertainty due to the hydrological model parameter selection has the least important contribution among all the variables considered. Overall, this research underlines the importance of adequately covering all sources of uncertainty. A failure to do so may result in moderately to severely biased climate change impact studies. Results further indicate that the major contributors to uncertainty vary depending on the hydrological variables selected, and that the methodology presented in this paper is successful at identifying the key sources of uncertainty to consider for a climate change impact study.

Global river temperatures and sensitivity to atmospheric warming and changes in river flow

Abstract: [1] This study investigates the impact of both air temperature and river discharge changes on daily water temperatures for river stations globally. A nonlinear water temperature regression model was adapted to include discharge as a variable in addition to air temperature, and a time lag was incorporated to apply the model on a daily basis. The performance of the model was tested for a selection of study basin stations and 157 river temperature stations globally using historical series of daily river temperature, air temperature, and river discharge for the 1980–1999 period. For the study basin stations and for 87% of the global river stations, the performance of the model improved by including discharge as an input variable. Greatest improvements were found during heat wave and drought (low flow) conditions, when water temperatures are most sensitive to atmospheric influences and can reach critically high values. A sensitivity analysis showed increases in annual mean river temperatures of +1.3 °C, +2.6 °C, and +3.8 °C under air temperature increases of +2 °C, +4 °C, and +6 °C, respectively. Discharge decreases of 20% and 40% exacerbated water temperature increases by +0.3 °C and +0.8 °C on average. For several stations, maximum water temperatures on a daily basis were higher under an air temperature increase of +4 °C combined with a 40% discharge decrease compared to an air temperature increase of +6 °C (without discharge changes). Impacts of river discharge on water temperatures should therefore be incorporated to provide more accurate estimations of river temperatures during historical and future projected dry and warm periods.

Representing spatial variability of snow water equivalent in hydrologic and land-surface models: A review

Abstract: [1] This paper evaluates the use of field data on the spatial variability of snow water equivalent (SWE) to guide the design of distributed snow models. An extensive reanalysis of results from previous field studies in different snow environments around the world is presented, followed by an analysis of field data on spatial variability of snow collected in the headwaters of the Jollie River basin, a rugged mountain catchment in the Southern Alps of New Zealand. In addition, area-averaged simulations of SWE based on different types of spatial discretization are evaluated. Spatial variability of SWE is shaped by a range of different processes that occur across a hierarchy of spatial scales. Spatial variability at the watershed-scale is shaped by variability in near-surface meteorological fields (e.g., elevation gradients in temperature) and, provided suitable meteorological data is available, can be explicitly resolved by spatial interpolation/extrapolation. On the other hand, spatial variability of SWE at the hillslope-scale is governed by processes such as drifting, sloughing of snow off steep slopes, trapping of snow by shrubs, and the nonuniform unloading of snow by the forest canopy, which are more difficult to resolve explicitly. Subgrid probability distributions are often capable of representing the aggregate-impact of unresolved processes at the hillslope-scale, though they may not adequately capture the effects of elevation gradients. While the best modeling strategy is case-specific, the analysis in this paper provides guidance on both the suitability of several common snow modeling approaches and on the choice of parameter values in subgrid probability distributions.

Elements of a flexible approach for conceptual hydrological modeling : 1. Motivation and theoretical development

Abstract: This paper introduces a flexible framework for conceptual hydrological modeling, with two related objectives: (1) generalize and systematize the currently fragmented field of conceptual models and (2) provide a robust platform for understanding and modeling hydrological systems. In contrast to currently dominant “fixed” model applications, the flexible framework proposed here allows the hydrologist to hypothesize, build, and test different model structures using combinations of generic components. This is particularly useful for conceptual modeling at the catchment scale, where limitations in process understanding and data availability remain major research and operational challenges. The formulation of the model architecture and individual components to represent distinct aspects of catchment-scale function, such as storage, release, and transmission of water, is discussed. Several numerical strategies for implementing the model equations within a computationally robust framework are also presented. In the companion paper, the potential of the flexible framework is examined with respect to supporting more systematic and stringent hypothesis testing, for characterizing catchment diversity, and, more generally, for aiding progress toward more unified hydrological theory at the catchment scale.

National microalgae biofuel production potential and resource demand

Abstract: [1] Microalgae are receiving increased global attention as a potential sustainable “energy crop” for biofuel production. An important step to realizing the potential of algae is quantifying the demands commercial-scale algal biofuel production will place on water and land resources. We present a high-resolution spatiotemporal assessment that brings to bear fundamental questions of where production can occur, how many land and water resources are required, and how much energy is produced. Our study suggests that under current technology, microalgae have the potential to generate 220 × 109 L yr−1 of oil, equivalent to 48% of current U.S. petroleum imports for transportation. However, this level of production requires 5.5% of the land area in the conterminous United States and nearly three times the water currently used for irrigated agriculture, averaging 1421 L water per liter of oil. Optimizing the locations for microalgae production on the basis of water use efficiency can greatly reduce total water demand. For example, focusing on locations along the Gulf Coast, southeastern seaboard, and Great Lakes shows a 75% reduction in consumptive freshwater use to 350 L per liter of oil produced with a 67% reduction in land use. These optimized locations have the potential to generate an oil volume equivalent to 17% of imports for transportation fuels, equal to the Energy Independence and Security Act year 2022 “advanced biofuels” production target and utilizing some 25% of the current irrigation demand. With proper planning, adequate land and water are available to meet a significant portion of the U.S. renewable fuel goals.

Evaluation of flow resistance in gravel‐bed rivers through a large field data set

Abstract: [1] A data set of 2890 field measurements was used to test the ability of several conventional flow resistance equations to predict mean flow velocity in gravel bed rivers when used with no calibration. The tests were performed using both flow depth and discharge as input since discharge may be a more reliable measure of flow conditions in shallow flows. Generally better predictions are obtained when using flow discharge as input. The results indicate that the Manning-Strickler and the Keulegan equations show considerable disagreement with observed flow velocities for flow depths smaller than 10 times the characteristic grain diameter. Most equations show some systematic deviation for small relative flow depth. The use of new definitions for dimensionless variables in terms of nondimensional hydraulic geometry equations allows the development of a new flow resistance equation. The best overall performance is obtained by the Ferguson approach, which combines two power law flow resistance equations that are different for deep and shallow flows. To use this approach with flow discharge as input, a logarithmic matching equation in terms of the new dimensionless variables is proposed. For the domains of intermediate and large-scale roughness, the field data indicate a considerable increase in flow resistance as compared with the domain of small-scale roughness. The Ferguson approach is used to discuss the importance of flow resistance partitioning for bed load transport calculations at flow conditions with intermediate- and large-scale roughness in natural gravel, cobble, and boulder bed streams.

Hierarchical controls on runoff generation: Topographically driven hydrologic connectivity, geology, and vegetation

Abstract: [1] Understanding the relative influence of catchment structure (topography and topology), underlying geology, and vegetation on runoff response is key to interpreting catchment hydrology. Hillslope-riparian-stream (HRS) water table connectivity serves as the hydrologic linkage between a catchment's uplands and the channel network and facilitates the transmission of water and solutes to streams. While there has been tremendous interest in the concept of hydrological connectivity to characterize catchments, few studies have quantified hydrologic connectivity at the stream network and catchment scales with observational data. Here we examine how catchment topography, vegetation, and geology influenced patterns of stream network HRS connectivity and runoff dynamics across 11 nested headwater catchments in the Tenderfoot Creek Experimental Forest (TCEF), MT. This study builds on the empirical findings of Jencso et al. (2009) who found a strong linear relationship (r2 = 0.91) between the upslope accumulated area (UAA) and the annual duration of shallow groundwater table connectivity observed across 24 HRS transects (146 groundwater recording wells). We applied this relationship to the entire stream network across 11 nested catchments to quantify the frequency distribution of stream network connectivity through time, and quantify its relationship to catchment-scale runoff dynamics. Each catchment's hydrologic connectivity duration curve (CDC) was highly related to its flow duration curve (FDC) and the slope of the relationship varied across catchments. The slope represents the streamflow yield per unit connectivity (Conyield). We analyzed the slope of each catchment's CDC-FDC relationship or Conyield (annual, peak, transition, and base flow periods) in multiple linear regression models with common terrain, land cover vegetation, and geology explanatory variables. Significant predictors (p < 0.05) across 11 catchments included the ratio of flow path distances and gradients to the creek (DFC/GTC), geology, and a vegetation index. The order and strength of these predictors changed seasonally and highlight the hierarchical controls on headwater catchment runoff generation. Our results highlight direct and quantifiable linkages between catchment topography, vegetation, geology, their topology, and hydrologic dynamics.

Water for food: The global virtual water trade network

Abstract: We present a novel conceptual framework and methodology for studying virtual water trade We utilize complex network theory to analyze the structure of the global virtual water trade associated with the international food trade In the global virtual water trade network, the nations that participate in the international food trade correspond to the nodes, and the links represent the flows of virtual water associated with the trade of food from the country of export to the country of import We find that the number of trade connections follows an exponential distribution, except for the case of import trade relationships, while the volume of water that each nation trades compares well with a stretched exponential distribution, indicating high heterogeneity of flows between nations There is a power law relationship between the volume of virtual water traded and the number of trade connections of each nation Highly connected nations are preferentially linked to poorly connected nations and exhibit low levels of clustering However, when the volume of virtual water traded is taken into account, this structure breaks down This indicates a global hierarchy, in which nations that trade large volumes of water are more likely to link to and cluster with other nations that trade large volumes of water, particularly when the direction of trade is considered Nations that play a critical role in maintaining the global network architecture are highlighted Our analysis provides the necessary framework for the development of a model of global virtual water trade aimed at applications ranging from network optimization to climate change impact evaluations

Relative dominance of hydrologic versus biogeochemical factors on solute export across impact gradients

Abstract: [1] Many processes lead to variability of catchment concentration-discharge relationships, but exports of geogenic (weathering derived) solutes and nutrients (nitrogen and phosphorus species) from agricultural basins display relatively constant concentrations despite large variations in streamflow. These “chemostatic” responses are hypothesized to arise when a large mass store, the parent material for geogenics or chemically recalcitrant legacies of fertilization in agricultural catchments, buffers concentration variability. This hypothesis implies that (1) chemostatic behavior should be a general response to elevated external inputs to a catchment and (2) chemostatic behavior should be predictable from theory. Data- and model-based analyses were used to explore these hypotheses. We evaluated concentration variability relative to discharge (expressed as the ratio of the coefficients of variation of concentration and flow, or CVC/CVQ) across a gradient of increasing exported load, as a proxy for an external impact gradient. The CVC/CVQ of multiple solutes declined with increasing exported load. Exceptions included the geogenic solutes, which showed chemostatic responses for all sites, phosphorus, and some nitrogen species. Nitrate showed a suggestive pattern in CVC/CVQ with export, but further data are needed to confirm its generality. A simple model of runoff generation and solute export suggested that the decline in CVC/CVQ arises if the internal mass store is distributed homogeneously in space and there is sufficient time for mass transfer to reach steady state between runoff events. Export from catchments may become more predictable in impacted watersheds, simplifying water quality prediction but inducing strong hysteresis in recovery and making restoration efforts challenging.

Examination of change factor methodologies for climate change impact assessment

Abstract: [1] A variety of methods are available to estimate values of meteorological variables at future times and at spatial scales that are appropriate for local climate change impact assessment. One commonly used method is Change Factor Methodology (CFM), sometimes referred to as delta change factor methodology. Although more sophisticated methods exist, CFM is still widely applicable and used in impact analysis studies. While there are a number of different ways by which change factors (CFs) can be calculated and used to estimate future climate scenarios, there are no clear guidelines available in the literature to decide which methodologies are most suitable for different applications. In this study several categories of CFM (additive versus multiplicative and single versus multiple) for a number of climate variables are compared and contrasted. The study employs several theoretical case studies, as well as a real example from Cannonsville watershed, which supplies water to New York City, USA. Results show that in cases when the frequency distribution of Global Climate Model (GCM) baseline climate is close to the frequency distribution of observed climate, or when the frequency distribution of GCM future climate is close to the frequency distribution of GCM baseline climate, additive and multiplicative single CFMs provide comparable results. Two options to guide the choice of CFM are

Impact of climate change on the water resources of the eastern Mediterranean and Middle East region: Modeled 21st century changes and implications

Abstract: [1] The likely effects of climate change on the water resources of the eastern Mediterranean and Middle East region are investigated using a high-resolution regional climate model (PRECIS) by comparing precipitation simulations of 2040–2069 and 2070–2099 with 1961–1990. The simulations show about a 10% decline in precipitation across the region by both the middle and the end of the century, with considerable variation between countries and international river basins. Results suggest that per capita water resources will not change particularly significantly in southeastern Europe, where they are relatively plentiful and population growth is minimal. However, in much of the Middle East, climate change coupled with population growth is likely to reduce per capita water resources considerably. This will inevitably result in major social, economic, and environmental change in the region. Countries where the required adaptation is likely to be particularly challenging include Turkey and Syria because of the large agricultural workforces, Iraq because of the magnitude of the change and its downstream location, and Jordan because of its meager per capita water resources coupled with limited options for desalination. If the internal water footprint of the region declines in line with precipitation but the total water footprint of the region increases in line with population, then by midcentury, as much as half the total water needs of the region may need to be provided through desalination and imported in the form of virtual water.

Impact of climate change on the hydroclimatology of Lake Tana Basin, Ethiopia

Abstract: [1] Climate change has the potential to reduce water resource availability in the Nile Basin countries in the forthcoming decades. We investigated the sensitivity of water resources to climate change in the Lake Tana Basin, Ethiopia, using outputs from global climate models (GCMs). First, we compiled projected changes in monthly precipitation and temperature in the basin from 15 GCMs. Although the GCMs uniformly suggest increases in temperature, the rainfall projections are not consistent. Second, we investigated how changes in daily temperature and precipitation might translate into changes in streamflow and other hydrological components. For this, we generated daily climate projections by modifying the historical data sets to represent the changes in the GCM climatologies and calculated hydrological changes using the Soil and Water Assessment Tool (SWAT). The SWAT model itself was calibrated and validated using the flows from four tributaries of Lake Tana. For the Special Report on Emissions Scenarios A2 scenario, four of the nine GCMs investigated showed statistically significant declines in annual streamflow for the 2080–2100 period. We interpret our results to mean that anthropogenic climate changes may indeed alter the water balance in the Lake Tana Basin during the next century but that the direction of change cannot be determined with confidence using the current generation of GCMs.

Present and future contribution of glacier storage change to runoff from macroscale drainage basins in Europe

Abstract: [1] The contribution of glaciers to runoff from large-scale drainage basins in Europe is analyzed for the major streams originating in the Alps: Rhine, Rhone, Po, and Danube. Detailed information on glacier storage change is available from monthly mass balance data of 50 Swiss glaciers for the period 1908–2008. Storage changes are extrapolated to all glaciers in the European Alps. By comparing monthly runoff yields from glacierized surfaces in the summer months with measured runoff at gauges along the entire length of the streams, the relative portion of water from glacier storage change for each month is calculated. Macroscale drainage basins with a size of 100,000 km2 (1% ice-covered) can show a 25% contribution of glaciers to August runoff over the last century. In the lower Danube (0.06% glacierization) glacier meltwater accounts for 9% of observed runoff in September of the extreme year 2003. The relative importance of glacier contribution to runoff does not scale linearly with the percentage of glacierization, as high glacier runoff in summer dominates lowland areas with little precipitation and high evapotranspiration. Thus, glacial meltwaters are relevant to the hydrological regime of macroscale watersheds and do not only have a regional impact. By transiently modeling future glacier retreat until 2100 using climate scenarios, a reduction of glacierized areas in the Alps to 12% of the current value is found. In consequence, summer runoff contribution from currently glacierized basins will be strongly reduced, intensifying issues with water shortage in summer also in poorly glacierized catchments.

Relative importance of impervious area, drainage density, width function, and subsurface storm drainage on flood runoff from an urbanized catchment

Abstract: urbanized catchment, the 14.3 km 2 Dead Run watershed near Baltimore, Maryland, USA, and the physics-based gridded surface/subsurface hydrologic analysis (GSSHA) model to examine the relative effect of each of these factors on ood peaks, runoff volumes, and runoff production efciencies. GSSHA was used because the model explicitly includes the spatial variability of land-surface and hydrodynamic parameters, including subsurface storm drains. Results indicate that increases in drainage density, particularly increases in density from low values, produce signicant increases in the ood peaks. For axed land-use and rainfall input, the ood magnitude approaches an upper limit regardless of the increase in the channel drainage density. Changes in imperviousness can have a signicant effect on ood peaks for both moderately extreme and extreme storms. For an extreme rainfall event with a recurrence interval in excess of 100 years, imperviousness is relatively unimportant in terms of runoff efciency and volume, but can affect the peak ow depending on rainfall rate. Changes to the width function affect ood peaks much more than runoff efciency, primarily in the case of lower density drainage networks with less impermeable area. Storm drains increase ood peaks, but are overwhelmed during extreme rainfall events when they have a negligible effect. Runoff in urbanized watersheds with considerable impervious area shows a marked sensitivity to rainfall rate. This sensitivity explains some of the contradictoryndings in the literature.

Toward a reliable decomposition of predictive uncertainty in hydrological modeling: Characterizing rainfall errors using conditional simulation

Abstract: [1] This study explores the decomposition of predictive uncertainty in hydrological modeling into its contributing sources. This is pursued by developing data-based probability models describing uncertainties in rainfall and runoff data and incorporating them into the Bayesian total error analysis methodology (BATEA). A case study based on the Yzeron catchment (France) and the conceptual rainfall-runoff model GR4J is presented. It exploits a calibration period where dense rain gauge data are available to characterize the uncertainty in the catchment average rainfall using geostatistical conditional simulation. The inclusion of information about rainfall and runoff data uncertainties overcomes ill-posedness problems and enables simultaneous estimation of forcing and structural errors as part of the Bayesian inference. This yields more reliable predictions than approaches that ignore or lump different sources of uncertainty in a simplistic way (e.g., standard least squares). It is shown that independently derived data quality estimates are needed to decompose the total uncertainty in the runoff predictions into the individual contributions of rainfall, runoff, and structural errors. In this case study, the total predictive uncertainty appears dominated by structural errors. Although further research is needed to interpret and verify this decomposition, it can provide strategic guidance for investments in environmental data collection and/or modeling improvement. More generally, this study demonstrates the power of the Bayesian paradigm to improve the reliability of environmental modeling using independent estimates of sampling and instrumental data uncertainties.

Determinants of residential water consumption: Evidence and analysis from a 10-country household survey

Abstract: [1] Household survey data for 10 countries are used to quantify and test the importance of price and nonprice factors on residential water demand and investigate complementarities between household water-saving behaviors and the average volumetric price of water. Results show (1) the average volumetric price of water is an important predictor of differences in residential consumption in models that include household characteristics, water-saving devices, attitudinal characteristics and environmental concerns as explanatory variables; (2) of all water-saving devices, only a low volume/dual-flush toilet has a statistically significant and negative effect on water consumption; and (3) environmental concerns have a statistically significant effect on some self-reported water-saving behaviors. While price-based approaches are espoused to promote economic efficiency, our findings stress that volumetric water pricing is also one of the most effective policy levers available to regulate household water consumption.

Evaluation of satellite rainfall products through hydrologic simulation in a fully distributed hydrologic model

Abstract: [1] The goal of this study is to evaluate the accuracy of four global high-resolution satellite rainfall products (CMORPH, TMPA 3B42RT, TMPA 3B42, and PERSIANN) through the hydrologic simulation of a 1656 km2 mountainous watershed in the fully distributed MIKE SHE hydrologic model. This study shows that there are significant biases in the satellite rainfall estimates and large variations in rainfall amounts, leading to large variations in hydrologic simulations. The rainfall algorithms that use primarily microwave data (CMORPH and TMPA 3B42RT) show consistent and better performance in streamflow simulation (bias in the order of −53% to −3%, Nash-Sutcliffe efficiency (NSE) from 0.34 to 0.65); the rainfall algorithm that uses primarily infrared data (PERSIANN) shows lower performance (bias from −82% to −3%, Nash-Sutcliffe efficiency from −0.39 to 0.43); and the rainfall algorithm that merges the satellite data with rain gage data (TMPA 3B42) shows inconsistencies and the lowest performance (bias from −86% to 0.43%, Nash-Sutcliffe efficiency from −0.50 to 0.27). A dilemma between calibrating the hydrologic model with rain gage data and calibrating it with the corresponding satellite rainfall data is presented. Calibrating the model with corresponding satellite rainfall data increases the performance of satellite streamflow simulation compared to the model calibrated with rain gage data, but decreases the performance of satellite evapotranspiration simulation.

Derivation of climate elasticity of runoff to assess the effects of climate change on annual runoff

Abstract: [1] Climate elasticity of runoff is an important indicator for evaluating the effects of climate change on runoff. Consequently, this paper proposes an analytical derivation of climate elasticity. Based on the mean annual water-energy balance equation, two dimensionless numbers (the elasticities of runoff to precipitation and potential evaporation) were derived. Combining the first-order differential of the Penman equation, the elasticities of runoff to precipitation, net radiation, air temperature, wind speed, and relative humidity were derived to separate the contributions of different climatic variables. The case study was carried out in the Futuo River catchment in the Hai River basin, as well as in 89 catchments of the Hai River and the Yellow River basins of China. Based on the mean annual of climatic variables, the climate elasticity in the Futuo River basin was estimated as follows: precipitation elasticity , net radiation elasticity , air temperature elasticity , wind speed elasticity , and relative humidity elasticity . In this catchment, precipitation decrease was mainly responsible for runoff decline, and wind speed decline had the second greatest effect on runoff. In the 89 catchments of the Hai River and the Yellow River basins of China, climate elasticity was estimated as follows: ranging from 1.6 to 3.9, ranging from −1.9 to −0.3, ranging from −0.11 to −0.02°C−1, ranging from −0.8 to −0.1, and ranging from 0.2 to 1.9. Additional analysis shows that climate elasticity was sensitive to catchment characteristics.

Comparative hydrology across AmeriFlux sites: The variable roles of climate, vegetation, and groundwater

Abstract: Watersheds can be characterized as complex space?time filters that transform incoming fluxes of energy, water, and nutrients into variable output signals. The behavior of these filters is driven by climate, geomorphology, and ecology and, accordingly, varies from site to site. We investigated this variation by exploring the behavior of evapotranspiration signals from 14 different AmeriFlux sites. Evapotranspiration is driven by water and energetic forcing and is mediated by ecology and internal redistribution of water and energy. As such, it integrates biological and physical controls, making it an ideal signature to target when investigating watershed filtering. We adopted a paradigmatic approach (referred to as the null model) that couples the Penman?Monteith equation to a soil moisture model and explored the deviations between the predictions of the null model and the observed AmeriFlux data across the sites in order to identify the controls on these deviations and their commonalities and differences across the sites. The null model reproduced evapotranspiration fluxes reasonably well for arid, shallow?rooted systems but overestimated the effects of water limitation and could not reproduce seasonal variation in evapotranspiration at other sites. Accounting for plant access to groundwater (or deep soil moisture) reserves and for the effects of soil temperature on limiting evapotranspiration resolved these discrepancies and greatly improved prediction of evapotranspiration at multiple time scales. The results indicate that site?specific hydrology and climatic factors pose important controls on biosphere?hydrosphere interactions and suggest that plant–water table interactions and early season phenological controls need to be incorporated into even simple models to reproduce the seasonality in evapotranspiration.

Catchment travel time distributions and water flow in soils

Abstract: Many details about the flow of water in soils in a hillslope are unknowable given current technologies. One way of learning about the bulk effects of water velocity distributions on hillslopes is through the use of tracers. However, this paper will demonstrate that the interpretation of tracer information needs to become more sophisticated. The paper reviews, and complements with mathematical arguments and specific examples, theory and practice of the distribution(s) of the times water particles injected through rainfall spend traveling through a catchment up to a control section (i.e., "catchment" travel times). The relevance of the work is perceived to lie in the importance of the characterization of travel time distributions as fundamental descriptors of catchment water storage, flow pathway heterogeneity, sources of water in a catchment, and the chemistry of water flows through the control section. The paper aims to correct some common misconceptions used in analyses of travel time distributions. In particular, it stresses the conceptual and practical differences between the travel time distribution conditional on a given injection time (needed for rainfall-runoff transformations) and that conditional on a given sampling time at the outlet (as provided by isotopic dating techniques or tracer measurements), jointly with the differences of both with the residence time distributions of water particles in storage within the catchment at any time. These differences are defined precisely here, either through the results of different models or theoretically by using an extension of a classic theorem of dynamic controls. Specifically, we address different model results to highlight the features of travel times seen from different assumptions, in this case, exact solutions to a lumped model and numerical solutions of the 3-D flow and transport equations in variably saturated, physically heterogeneous catchment domains. Our results stress the individual characters of the relevant distributions and their general nonstationarity yielding their legitimate interchange only in very particular conditions rarely achieved in the field. We also briefly discuss the impact of oversimple assumptions commonly used in analyses of tracer data.