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Showing papers in "Water Resources Research in 2010"


Journal ArticleDOI
TL;DR: In this article, the authors focus on the total predictive uncertainty and its decomposition into input and structural components under different inference scenarios, and highlight the inherent limitations of inferring inaccurate hydrologic models using rainfall runoff data with large unknown errors.
Abstract: [1] Meaningful quantification of data and structural uncertainties in conceptual rainfall-runoff modeling is a major scientific and engineering challenge. This paper focuses on the total predictive uncertainty and its decomposition into input and structural components under different inference scenarios. Several Bayesian inference schemes are investigated, differing in the treatment of rainfall and structural uncertainties, and in the precision of the priors describing rainfall uncertainty. Compared with traditional lumped additive error approaches, the quantification of the total predictive uncertainty in the runoff is improved when rainfall and/or structural errors are characterized explicitly. However, the decomposition of the total uncertainty into individual sources is more challenging. In particular, poor identifiability may arise when the inference scheme represents rainfall and structural errors using separate probabilistic models. The inference becomes ill-posed unless sufficiently precise prior knowledge of data uncertainty is supplied; this ill-posedness can often be detected from the behavior of the Monte Carlo sampling algorithm. Moreover, the priors on the data quality must also be sufficiently accurate if the inference is to be reliable and support meaningful uncertainty decomposition. Our findings highlight the inherent limitations of inferring inaccurate hydrologic models using rainfall-runoff data with large unknown errors. Bayesian total error analysis can overcome these problems using independent prior information. The need for deriving independent descriptions of the uncertainties in the input and output data is clearly demonstrated.

622 citations


Journal ArticleDOI
TL;DR: In this article, the authors make use of new definitions of moisture recycling to study the complete process of continental moisture feedback and identify regions that rely heavily on recycled moisture as well as those that are supplying the moisture.
Abstract: There has been a long debate on the extent to which precipitation relies on terrestrial evaporation (moisture recycling). In the past, most research focused on moisture recycling within a certain region only. This study makes use of new definitions of moisture recycling to study the complete process of continental moisture feedback. Global maps are presented identifying regions that rely heavily on recycled moisture as well as those that are supplying the moisture. An accounting procedure based on ERA‐Interim reanalysis data is used to calculate moisture recycling ratios. It is computed that, on average, 40% of the terrestrial precipitation originates from land evaporation and that 57% of all terrestrial evaporation returns as precipitation over land. Moisture evaporating from the Eurasian continent is responsible for 80% of China’s water resources. In South America, the Rio de la Plata basin depends on evaporation from the Amazon forest for 70% of its water resources. The main source of rainfall in the Congo basin is moisture evaporated over East Africa, particularly the Great Lakes region. The Congo basin in its turn is a major source of moisture for rainfall in the Sahel. Furthermore, it is demonstrated that due to the local orography, local moisture recycling is a key process near the Andes and the Tibetan Plateau. Overall, this paper demonstrates the important role of global wind patterns, topography and land cover in continental moisture recycling patterns and the distribution of global water resources.

609 citations


Journal ArticleDOI
TL;DR: For a long-term initiative to address the regional implications of environmental change, hydrologists must become both synthesists and analysts, understanding the functioning of individual system components, while operating firmly within a well-designed hypothesis testing framework.
Abstract: Human activities exert global-scale impacts on our environment with significant implications for freshwater-driven services and hazards for humans and nature. Our approach to the science of hydrology needs to significantly change so that we can understand and predict these implications. Such an adjustment is a necessary prerequisite for the development of sustainable water resource management strategies and to achieve long-term water security for people and the environment. Hydrology requires a paradigm shift in which predictions of system behavior that are beyond the range of previously observed variability or that result from significant alterations of physical (structural) system characteristics become the new norm. To achieve this shift, hydrologists must become both synthesists, observing and analyzing the system as a holistic entity, and analysts, understanding the functioning of individual system components, while operating firmly within a well-designed hypothesis testing framework. Cross-disciplinary integration must become a primary characteristic of hydrologic research, catalyzing new research and nurturing new educational models. The test of our quantitative understanding across atmosphere, hydrosphere, lithosphere, biosphere, and anthroposphere will necessarily lie in new approaches to benchmark our ability to predict the regional hydrologic and connected implications of environmental change. To address these challenges and to serve as a catalyst to bring about the necessary changes to hydrologic science, we call for a long-term initiative to address the regional implications of environmental change.

575 citations


Journal ArticleDOI
TL;DR: In this article, the authors proposed a closed-form equation for effective stress in unsaturated soil, which is intrinsically related to the soil water characteristic curve by two pore parameters: the air entry pressure and pore size spectrum number.
Abstract: [1] We propose that the recently conceptualized suction stress characteristic curve represents the effective stress for the shear strength behavior of unsaturated soil. Mechanically, suction stress is the interparticle stress called tensile stress. The working hypothesis is that the change in the energy of soil water from its free water state is mostly consumed in suction stress. We demonstrate that the suction stress lies well within the framework of continuum mechanics where free energy is the basis for any thermodynamic formulation. Available experimental data on soil water characteristic curves and suction stress characteristic curves are used to test the hypothesis, thus validating a closed-form equation for effective stress in unsaturated soil. The proposed closed-form equation is intrinsically related to the soil water characteristic curve by two pore parameters: the air entry pressure and pore size spectrum number. Both semiquantitative and quantitative validations show that the proposed closed-form equation well represents effective stress for a variety of earth materials ranging from sands to clays. Of important practical implications are (1) the elimination of the need for any new shear strength criterion for unsaturated soil, (2) the elimination of the need for determining the Bishop's effective stress parameter χ because the new form of effective stress is solely a function of soil suction, and (3) the ready extension of all classical soil mechanics work on limit equilibrium analysis to unsaturated soil conditions.

542 citations


Journal ArticleDOI
TL;DR: In this paper, a generalized likelihood function is presented to estimate both the parameter and predictive uncertainty of hydrologic models, which can be used for handling complex residual errors in other models.
Abstract: Estimation of parameter and predictive uncertainty of hydrologic models has traditionally relied on several simplifying assumptions. Residual errors are often assumed to be independent and to be adequately described by a Gaussian probability distribution with a mean of zero and a constant variance. Here we investigate to what extent estimates of parameter and predictive uncertainty are affected when these assumptions are relaxed. A formal generalized likelihood function is presented, which extends the applicability of previously used likelihood functions to situations where residual errors are correlated, heteroscedastic, and non?Gaussian with varying degrees of kurtosis and skewness. The approach focuses on a correct statistical description of the data and the total model residuals, without separating out various error sources. Application to Bayesian uncertainty analysis of a conceptual rainfall?runoff model simultaneously identifies the hydrologic model parameters and the appropriate statistical distribution of the residual errors. When applied to daily rainfall?runoff data from a humid basin we find that (1) residual errors are much better described by a heteroscedastic, first?order, auto?correlated error model with a Laplacian distribution function characterized by heavier tails than a Gaussian distribution; and (2) compared to a standard least?squares approach, proper representation of the statistical distribution of residual errors yields tighter predictive uncertainty bands and different parameter uncertainty estimates that are less sensitive to the particular time period used for inference. Application to daily rainfall?runoff data from a semiarid basin with more significant residual errors and systematic underprediction of peak flows shows that (1) multiplicative bias factors can be used to compensate for some of the largest errors and (2) a skewed error distribution yields improved estimates of predictive uncertainty in this semiarid basin with near?zero flows. We conclude that the presented methodology provides improved estimates of parameter and total prediction uncertainty and should be useful for handling complex residual errors in other hydrologic regression models as well.

510 citations


Journal ArticleDOI
TL;DR: In this paper, a multiscale parameter regionalization (MPR) technique is proposed as a way to address the issues of overparameterization, the lack of an effective technique to integrate the spatial heterogeneity of physiographic characteristics, and the nontransferability of parameters across scales and locations.
Abstract: [1] The requirements for hydrological models have increased considerably during the previous decades to cope with the resolution of extensive remotely sensed data sets and a number of demanding applications. Existing models exhibit deficiencies such as overparameterization, the lack of an effective technique to integrate the spatial heterogeneity of physiographic characteristics, and the nontransferability of parameters across scales and locations. A multiscale parameter regionalization (MPR) technique is proposed as a way to address these issues simultaneously. Using this technique, parameters at a coarser scale, in which the dominant hydrological processes are represented, are linked with their corresponding ones at a finer resolution in which input data sets are available. The linkage is done with upscaling operators such as the harmonic mean, among others. Parameters at the finer scale are regionalized through nonlinear transfer functions which link basin predictors with global parameters to be determined through calibration. MPR was compared with a standard regionalization (SR) method in which basin predictors instead of model parameters are first aggregated. Both methods were tested in a basin located in Germany using a distributed hydrologic model. Results indicate that MPR is superior to SR in many respects, especially if global parameters are transferred from coarser to finer scales. Furthermore, MPR, as opposed to SR, preserves the spatial variability of state variables and conserves the mass balance with respect to a control scale. Cross-validation tests indicate that the transferability of the global parameters to ungauged locations is possible.

509 citations


Journal ArticleDOI
TL;DR: In this article, a satellite remote sensing-based evapotranspiration (ET) algorithm was applied to assess global terrestrial ET from 1983 to 2006 using a modified Penman-Monteith approach with biome-specific canopy conductance determined from the normalized difference vegetation index (NDVI) and quantifying open water evaporation using a Priestley-Taylor approach.
Abstract: [1] We applied a satellite remote sensing-based evapotranspiration (ET) algorithm to assess global terrestrial ET from 1983 to 2006. The algorithm quantifies canopy transpiration and soil evaporation using a modified Penman-Monteith approach with biome-specific canopy conductance determined from the normalized difference vegetation index (NDVI) and quantifies open water evaporation using a Priestley-Taylor approach. These algorithms were applied globally using advanced very high resolution radiometer (AVHRR) GIMMS NDVI, NCEP/NCAR Reanalysis (NNR) daily surface meteorology, and NASA/GEWEX Surface Radiation Budget Release-3.0 solar radiation inputs. We used observations from 34 FLUXNET tower sites to parameterize an NDVI-based canopy conductance model and then validated the global ET algorithm using measurements from 48 additional, independent flux towers. Two sets of monthly ET estimates at the tower level, driven by in situ meteorological measurements and meteorology interpolated from coarse resolution NNR meteorology reanalysis, agree favorably (root mean square error (RMSE) = 13.0-15.3 mm month -1 ; R 2 = 0.80-0.84) with observed tower fluxes from globally representative land cover types. The global ET results capture observed spatial and temporal variations at the global scale and also compare favorably (RMSE = 186.3 mm yr -1 ; R 2 = 0.80) with ET inferred from basin-scale water balance calculations for 261 basins covering 61 % of the global vegetated area. The results of this study provide a relatively long term global ET record with well-quantified accuracy for assessing ET climatologies, terrestrial water, and energy budgets and long-term water cycle changes.

509 citations


Journal ArticleDOI
TL;DR: This work proposes to sample directly the training image for a given data event, making the database unnecessary, and shows its applicability in the presence of complex features, nonlinear relationships between variables, and with various cases of nonstationarity.
Abstract: [1] Multiple-point geostatistics is a general statistical framework to model spatial fields displaying a wide range of complex structures. In particular, it allows controlling connectivity patterns that have a critical importance for groundwater flow and transport problems. This approach involves considering data events (spatial arrangements of values) derived from a training image (TI). All data events found in the TI are usually stored in a database, which is used to retrieve conditional probabilities for the simulation. Instead, we propose to sample directly the training image for a given data event, making the database unnecessary. Our method is statistically equivalent to previous implementations, but in addition it allows extending the application of multiple-point geostatistics to continuous variables and to multivariate problems. The method can be used for the simulation of geological heterogeneity, accounting or not for indirect observations such as geophysics. We show its applicability in the presence of complex features, nonlinear relationships between variables, and with various cases of nonstationarity. Computationally, it is fast, easy to parallelize, parsimonious in memory needs, and straightforward to implement.

457 citations


Journal ArticleDOI
TL;DR: In this paper, the interfacial interaction between mineral surfaces and immiscible fluids determines the efficiency of enhanced oil or gas recovery operations as well as our ability to inject and store CO2 in geological formations.
Abstract: [1] The interfacial interaction between mineral surfaces and immiscible fluids determines the efficiency of enhanced oil or gas recovery operations as well as our ability to inject and store CO2 in geological formations Previous studies have shown that the interfacial tension and contact angle in CO2-water-mineral systems change noticeably with fluid pressure We compile previous results and extend the scope of available data to include saline water, different substrates (quartz, calcite, oil-wet quartz, and polytetrafluoroethylene (PTFE)), and a wide pressure range (up to 20 MPa at 298K) Data analysis provides interfacial tension and contact angle as a function of fluid pressure; in addition, we recover the diffusion coefficient of water in liquid CO2 from long-term observations Results show that CO2-water interfacial tension decreases significantly as pressure increases in agreement with previous studies Contact angle varies with CO2 pressure in all experiments in response to changes in CO2-water interfacial tension: it increases on nonwetting surfaces such as PTFE and oil-wet quartz and slightly decreases in water-wet quartz and calcite surfaces Water solubility and its high diffusivity (D = 2 × 10−8 to 2 × 10−7 m2/s) in liquid CO2 govern the evolution of interparticle pendular water CO2-derived ionic species interaction with the substrate leads to surface modification if reactions are favorable, eg, calcite dissolution by carbonic acid and precipitation as water diffuses and migrates into the bulk CO2 Pressure-dependent interfacial tension and contact angle affect injection patterns and breakthrough mechanisms, in other words, the performance of geological formations that act as either reservoirs or seals

410 citations


Journal ArticleDOI
TL;DR: In this article, a distributed physically based model incorporating novel approaches for the representation of surface-subsurface processes and interactions is presented, with several options for identifying flow directions, for separating channel cells from hillslope cells, and for representing stream channel hydraulic geometry.
Abstract: Received 21 October 2008; revised 2 September 2009; accepted 16 September 2009; published 13 February 2010. [1] A distributed physically based model incorporating novel approaches for the representation of surface-subsurface processes and interactions is presented. A path-based description of surface flow across the drainage basin is used, with several options for identifying flow directions, for separating channel cells from hillslope cells, and for representing stream channel hydraulic geometry. Lakes and other topographic depressions are identified and specially treated as part of the preprocessing procedures applied to the digital elevation data for the catchment. Threshold-based boundary condition switching is used to partition potential (atmospheric) fluxes into actual fluxes across the land surface and changes in surface storage, thus resolving the exchange fluxes, or coupling, between the surface and subsurface modules. Nested time stepping allows smaller steps to be taken for typically faster and explicitly solved surface runoff routing, while a mesh coarsening option allows larger grid elements to be used for typically slower and more compute-intensive subsurface flow. Sequential data assimilation schemes allow the model predictions to be updated with spatiotemporal observation data of surface and subsurface variables. These approaches are discussed in detail, and the physical and numerical behavior of the model is illustrated over catchment scales ranging from 0.0027 to 356 km 2 , addressing different hydrological processes and highlighting the importance of describing coupled surfacesubsurface flow.

399 citations


Journal ArticleDOI
TL;DR: In this paper, the authors used a portable Time Domain Reflectometer (TDRS) to measure the soil moisture at the field and catchment scale. But the accuracy of the measured soil moisture was only 2.38%.
Abstract: [1] The soil moisture is a quantity of paramount importance in the study of hydrologic phenomena and soil-atmosphere interaction. Because of its high spatial and temporal variability, the soil moisture monitoring scheme was investigated here both for soil moisture retrieval by remote sensing and in view of the use of soil moisture data in rainfall-runoff modeling. To this end, by using a portable Time Domain Reflectometer, a sequence of 35 measurement days were carried out within a single year in seven fields located inside the Vallaccia catchment, central Italy, with area of 60 km2. Every sampling day, soil moisture measurements were collected at each field over a regular grid with an extension of 2000 m2. The optimization of the monitoring scheme, with the aim of an accurate mean soil moisture estimation at the field and catchment scale, was addressed by the statistical and the temporal stability. At the field scale, the number of required samples (NRS) to estimate the field-mean soil moisture within an accuracy of 2%, necessary for the validation of remotely sensed soil moisture, ranged between 4 and 15 for almost dry conditions (the worst case); at the catchment scale, this number increased to nearly 40 and it refers to almost wet conditions. On the other hand, to estimate the mean soil moisture temporal pattern, useful for rainfall-runoff modeling, the NRS was found to be lower. In fact, at the catchment scale only 10 measurements collected in the most “representative” field, previously determined through the temporal stability analysis, can reproduce the catchment-mean soil moisture with a determination coefficient, R2, higher than 0.96 and a root-mean-square error, RMSE, equal to 2.38%. For the “nonrepresentative” fields the accuracy in terms of RMSE decreased, but similar R2 coefficients were found. This insight can be exploited for the sampling in a generic field when it is sufficient to know an index of soil moisture temporal pattern to be incorporated in conceptual rainfall-runoff models. The obtained results can address the soil moisture monitoring network design from which a reliable soil moisture temporal pattern at the catchment scale can be derived.

Journal ArticleDOI
TL;DR: In this article, the authors focus on a coastal groundwater system that is already threatened by a relatively high seawater level: the low-lying Dutch Delta and calculate the possible impacts of future sea level rise, land subsidence, changes in recharge, autonomous salinization, and the effects of two mitigation countermeasures with a three-dimensional numerical model for variable density groundwater flow and coupled solute transport.
Abstract: [1] Climate change in combination with increased anthropogenic activities will affect coastal groundwater systems throughout the world. In this paper, we focus on a coastal groundwater system that is already threatened by a relatively high seawater level: the low-lying Dutch Delta. Nearly one third of the Netherlands lies below mean sea level, and the land surface is still subsiding up to 1 m per century. This densely populated delta region, where fresh groundwater resources are used intensively for domestic, agricultural, and industrial purposes, can serve as a laboratory case for other low-lying delta areas throughout the world. Our findings on hydrogeological effects can be scaled up since the problems the Dutch face now will very likely be the problems encountered in other delta areas in the future. We calculated the possible impacts of future sea level rise, land subsidence, changes in recharge, autonomous salinization, and the effects of two mitigation countermeasures with a three-dimensional numerical model for variable density groundwater flow and coupled solute transport. We considered the effects on hydraulic heads, seepage fluxes, salt loads to surface waters, and changes in fresh groundwater resources as a function of time and for seven scenarios. Our numerical modeling results show that the impact of sea level rise is limited to areas within 10 km of the coastline and main rivers because the increased head in the groundwater system at the coast can easily be produced though the highly permeable Holocene confining layer. Along the southwest coast of the Netherlands, salt loads will double in some parts of the deep and large polders by the year 2100 A.D. due to sea level rise. More inland, ongoing land subsidence will cause hydraulic heads and phreatic water levels to drop, which may result in damage to dikes, infrastructure, and urban areas. In the deep polders more inland, autonomous upconing of deeper and more saline groundwater will be responsible for increasing salt loads. The future increase of salt loads will cause salinization of surface waters and shallow groundwater and put the total volumes of fresh groundwater volumes for drinking water supply, agricultural purposes, industry, and ecosystems under pressure.

Journal ArticleDOI
TL;DR: In this paper, the authors investigated stream and hillslope runoff dynamics through a wet-up period in watershed 10 of the H. J. Andrews Experimental Forest in the western Cascades of Oregon where the riparian zone has been removed by debris flows.
Abstract: [1] Subsurface flow from hillslopes is widely recognized as an important contributor to streamflow generation; however, processes that control how and when hillslopes connect to streams remain unclear. We investigated stream and hillslope runoff dynamics through a wet-up period in watershed 10 of the H. J. Andrews Experimental Forest in the western Cascades of Oregon where the riparian zone has been removed by debris flows. We examined the controls on hillslope-stream connectivity on the basis of observations of hydrometric, stable isotope, and applied tracer responses and computed transit times for multiple runoff components for a series of storms during the wet-up phase of the 2002–2003 winter rainy season. Hillslope discharge was distinctly threshold-like with a near linear response and average quick flow ratio of 0.58 when antecedent rainfall was greater than 20 mm. Hillslope and stream stormflow varied temporally and showed strong hysteretic relationships. Event water mean transit times (8–34 h) and rapid breakthrough from applied hillslope tracer additions demonstrated that subsurface contributing areas extend far upslope during events. Despite rapid hillslope transport processes during events, soil water and runoff mean transit times during nonstorm conditions were greater than the time scale of storm events. Soil water mean transit times ranged between 10 and 25 days. Hillslope seepage and catchment base flow mean transit times were between 1 and 2 years. We describe a conceptual model that captures variable physical flow pathways, their synchronicity, threshold activation, hysteresis, and transit times through changing antecedent wetness conditions that illustrate the different stages of hillslope and stream connectivity.

Journal ArticleDOI
TL;DR: In this paper, the authors quantitatively investigate processing methods and their impacts on bias, leakage, GRACE noise reduction, and estimated total error, allowing solution of the trade-offs.
Abstract: The Gravity Recovery and Climate Experiment (GRACE) satellites provide observations of water storage variation at regional scales. However, when focusing on a region of interest, limited spatial resolution and noise contamination can cause estimation bias and spatial leakage, problems that are exacerbated as the region of interest approaches the GRACE resolution limit of a few hundred km. Reliable estimates of water storage variations in small basins require compromises between competing needs for noise suppression and spatial resolution. The objective of this study was to quantitatively investigate processing methods and their impacts on bias, leakage, GRACE noise reduction, and estimated total error, allowing solution of the trade-offs. Among the methods tested is a recently developed concentration algorithm called spatiospectral localization, which optimizes the basin shape description, taking into account limited spatial resolution. This method is particularly suited to retrieval of basin-scale water storage variations and is effective for small basins. To increase confidence in derived methods, water storage variations were calculated for both CSR (Center for Space Research) and GRGS (Groupe de Recherche de Geodesie Spatiale) GRACE products, which employ different processing strategies. The processing techniques were tested on the intensively monitored High Plains Aquifer (450,000 km2 area), where application of the appropriate optimal processing method allowed retrieval of water storage variations over a portion of the aquifer as small as ˜200,000 km2.

Journal ArticleDOI
TL;DR: A review of current psychological research that examines the five broad causes of residential water conservation behaviors: attitudes, beliefs, habits or routines, personal capabilities, and contextual factors is presented in this paper.
Abstract: [1] The availability of fresh water for human consumption is a critical global issue and one that will be exacerbated by the impacts of climate change. Water demand management has an important role to play in reducing the vulnerability of freshwater supplies to climate change impacts. In this paper, we argue that the field of psychology and environmental psychology in particular can make a vital contribution in understanding further the drivers of residential water demand. A growing body of literature in environmental psychology has examined the determinants of water conservation behavior, and this research has many potential applications for water demand policy. In this paper we offer a review of current psychological research that examines the five broad causes of residential water conservation behaviors: attitudes, beliefs, habits or routines, personal capabilities, and contextual factors. We assess how psychologists have studied water conservation behavior to date, identify shortcomings, and indicate how this research can be used to further promote residential water conservation and to inform evidence-based policy and practice.

Journal ArticleDOI
TL;DR: In this article, the authors compare two different visions of similarity: the apparent similarity defined on the basis of observable catchment properties, and behavioral similarity judged through the use of hydrological models.
Abstract: [1] This paper discusses the notion of similarity often used in the regionalization studies of hydrological models. We compare two different visions of similarity: the apparent similarity defined on the basis of observable catchment properties, and behavioral similarity judged through the use of hydrological models. These two visions are generally assumed to be merged in regionalization studies: Catchments having apparently similar physical characteristics are assumed to have a similar hydrological behavior. In this paper, we wished to test the validity of this assumption. To this aim, we defined behavioral (hydrological) similarity on the basis of model parameter transferability. Then pools of hydrologically similar catchments are compared with pools of apparently physically similar catchments, as identified on the basis of physiographic catchment descriptors. The overlap between the two pools of similar catchments is analyzed, making it possible to judge the efficiency of the physical similarity measure and to identify hydrologically similar catchments in an ungauged context. The results show that the overlap between the two pools is significant for only 60% of the catchments. For the other catchments, two major reasons were identified as contributing to the lack of overlap: (1) these catchments often have a quite specific hydrological behavior and (2) the role of the underground properties of the catchment on its hydrological behavior was not found to be accurately described by the available physical descriptors, meaning that more relevant catchment descriptors should be sought to better describe the geological and lithological context in hydrological terms.

Journal ArticleDOI
TL;DR: In this paper, a new multivariate extreme value distributions can be easily constructed by exploiting recent theoretical developments in the theory of copulas, in particular, a suitable number of parameters can be introduced, a feature not shared by traditional extreme value models.
Abstract: [1] Multivariate extreme value models are a fundamental tool in order to assess potentially dangerous events. The target of this paper is two-fold. On the one hand we outline how, exploiting recent theoretical developments in the theory of copulas, new multivariate extreme value distributions can be easily constructed; in particular, we show how a suitable number of parameters can be introduced, a feature not shared by traditional extreme value models. On the other hand, we introduce a proper new definition of multivariate return period and show the differences with (and the advantages over) the definition presently used in literature. An illustration involving flood data is presented and discussed, and a generalization of the well-known multivariate logistic Gumbel model is also given.

Journal ArticleDOI
TL;DR: In this paper, the authors examined the values of goods and services provided by wetland ecosystems through a meta-analysis of an expanded database of wetland value estimates and with a focus on human-made wetlands.
Abstract: [1] The values of goods and services provided by wetland ecosystems are examined through a meta-analysis of an expanded database of wetland value estimates and with a focus on human-made wetlands. This study extends and improves upon previous meta-analyses of the wetland valuation literature in terms of the number of observations, geographical coverage, wetland class and integrity, and the measurement of the effects of scarcity and anthropogenic pressure. We find that water quality improvement, nonconsumptive recreation, and provision of natural habitat and biodiversity are highly valued services. Substitution effects are observed through the negative correlation between values and abundance of other wetlands. Wetland values are found to increase with anthropogenic pressure. An extended metaregression model with cross effects shows that the valuation of specific services varies with the type of wetland producing them. Human-made wetlands are highly valued for biodiversity enhancement, water quality improvement, and flood control.

Journal ArticleDOI
TL;DR: The Gravity Recovery and Climate Experiment (GRACE) satellite gravity mission provides a new capability for measuring extreme climate events such as floods and droughts associated with large-scale terrestrial water storage (TWS) change as mentioned in this paper.
Abstract: [1] The Gravity Recovery and Climate Experiment (GRACE) satellite gravity mission provides a new capability for measuring extreme climate events, such as floods and droughts associated with large‐scale terrestrial water storage (TWS) change. GRACE gravity measurements show significant TWS increases in the lower Amazon basin in the first half of 2009, clearly associated with the exceptional flood season in that region. The extended record of GRACE monthly gravity solutions reveals the temporal and spatial evolution of both nonseasonal and interannual TWS change in the Amazon basin over the 7 year mission period from April 2002 to August 2009. GRACE observes a very dry season in 2002–2003 and an extremely wet season in 2009. In March 2009 (approximately the peak of the recent Amazon flood), total TWS surplus in the entire Amazon basin is ∼624 ± 32 Gt, roughly equal to U.S. water consumption for a year. GRACE measurements are consistent with precipitation data. Interannual TWS changes in the Amazon basin are closely connected to ENSO events in the tropical Pacific. The 2002–2003 dry season is clearly tied to the 2002–2003 El Nino and the 2009 flood to the recent La Nina event. The most significant contribution of this study in the area of water resources is to confront the hydrological community with the latest results of the GRACE satellite mission and further demonstrates the unique strength of GRACE and follow‐up satellite gravity observations for measuring large‐scale extreme climate events.

Journal ArticleDOI
TL;DR: In this article, the authors propose a mathematical framework for the general definition and computation of travel time distributions defined by the closure of a catchment control volume, where the input flux is an arbitrary rainfall pattern and the output fluxes are green and blue water flows (namely, evapotranspiration and hydrologic response embedding runoff production through soil water dynamics).
Abstract: We propose a mathematical framework for the general definition and computation of travel time distributions defined by the closure of a catchment control volume, where the input flux is an arbitrary rainfall pattern and the output fluxes are green and blue water flows (namely, evapotranspiration and the hydrologic response embedding runoff production through soil water dynamics). The relevance of the problem is both practical, owing to implications in hydrologic watershed modeling, and conceptual for the linkages and the explanations the theory provides, chiefly concerning the role of geomorphology, climate, soils, and vegetation through soil water dynamics and the treatment of the so called old water paradox. The work focuses in particular on the origins of the conditional and time-variant nature of travel time distributions and on the differences between unit hydrographs and travel time distributions. Both carrier flow and solute matter transport in the control volume are accounted for coherently. The key effect of mixing processes occurring within runoff production is also investigated, in particular by a model that assumes that mobilization of soil water involves randomly sampled particles from the available storage. Travel time distributions are analytically expressed in terms of the major water fluxes driving soil moisture dynamics, irrespectively of the specific model used to compute them. Relevant numerical examples and a set of generalized applications are provided and discussed.

Journal ArticleDOI
TL;DR: In this paper, two standard tropical rain measuring mission (TRMM) Multisatellite Precipitation Analysis (TMPA) products, 3B42RT and V6, were quantitatively evaluated in the Laohahe basin, China, located within the TMPA product latitude band (50°NS) but beyond the inclined TRMM satellite latitude band(36°NS).
Abstract: [1] Two standard Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) products, 3B42RT and 3B42V6, were quantitatively evaluated in the Laohahe basin, China, located within the TMPA product latitude band (50°NS) but beyond the inclined TRMM satellite latitude band (36°NS). In general, direct comparison of TMPA rainfall estimates to collocated rain gauges from 2000 to 2005 show that the spatial and temporal rainfall characteristics over the region are well captured by the 3B42V6 estimates. Except for a few months with underestimation, the 3B42RT estimates show unrealistic overestimation nearly year round, which needs to be resolved in future upgrades to the real-time estimation algorithm. Both model-parameter error analysis and hydrologic application suggest that the three-layer Variable Infiltration Capacity (VIC-3L) model cannot tolerate the nonphysical overestimation behavior of 3B42RT through the hydrologic integration processes, and as such the 3B42RT data have almost no hydrologic utility, even at the monthly scale. In contrast, the 3B42V6 data can produce much better hydrologic predictions with reduced error propagation from input to streamflow at both the daily and monthly scales. This study also found the error structures of both RT and V6 have a significant geo-topography-dependent distribution pattern, closely associated with latitude and elevation bands, suggesting current limitations with TRMM-era algorithms at high latitudes and high elevations in general. Looking into the future Global Precipitation Measurement (GPM) era, the Geostationary Infrared (GEO-IR) estimates still have a long-term role in filling the inevitable gaps in microwave coverage, as well as in enabling sub-hourly estimates at typical 4-km grid scales. Thus, this study affirms the call for a real-time systematic bias removal in future upgrades to the IR-based RT algorithm using a simple scaling factor. This correction is based on MW-based monthly rainfall climatologies applied to the combined monthly satellite-gauge research products.

Journal ArticleDOI
TL;DR: In this paper, the authors show that soil moisture, snow, and biomass each have a distinct influence on the spectrum, height profile, and directional intensity of neutrons above the ground, suggesting that different sources of water at the land surface can be distinguished with neutron data alone.
Abstract: [1] Fast neutrons are generated naturally at the land surface by energetic cosmic rays. These “background” neutrons respond strongly to the presence of water at or near the land surface and represent a hitherto elusive intermediate spatial scale of observation that is ideal for land surface studies and modeling. Soil moisture, snow, and biomass each have a distinct influence on the spectrum, height profile, and directional intensity of neutron fluxes above the ground, suggesting that different sources of water at the land surface can be distinguished with neutron data alone. Measurements can be taken at fixed sites for long-term monitoring or in a moving vehicle for mapping over large areas. We anticipate applications in many previously problematic contexts, including saline environments, wetlands and peat bogs, rocky soils, the active layer of permafrost, and water and snow intercepted by vegetation, as well as calibration and validation of data from spaceborne sensors.

Journal ArticleDOI
TL;DR: In this article, an analysis of droughts in mainland Portugal based on monthly precipitation data, from September 1910 to October 2004, in 144 rain gages distributed uniformly over the country is presented.
Abstract: [1] An analysis of droughts in mainland Portugal based on monthly precipitation data, from September 1910 to October 2004, in 144 rain gages distributed uniformly over the country is presented. The drought events were characterized by means of the Standardized Precipitation Index (SPI) applied to different time scales (1, 6, and 12 consecutive months and 6 months from April to September and 12 months from October to September). To assess spatial and temporal patterns of droughts, a principal component analysis (PCA) and K-means clustering (KMC) were applied to the SPI series. In this way, three different and spatially well-defined regions with different temporal evolution of droughts were identified (north, central, and south regions of Portugal). A spectral analysis of the SPI patterns obtained with principal component analysis and clusters analysis, using the fast Fourier transform algorithm (FFT), showed that there is a manifest 3.6-year cycle in the SPI pattern in the south of Portugal and evident 2.4-year and 13.4-year cycles in the north of Portugal. The observation of the drought periods supports the occurrence of more frequent cycles of dry events in the south (droughts from moderate to extreme approximately every 3.6 years) than in the north (droughts from severe to extreme approximately every 13.4 years). These results suggest a much stronger immediate influence of the NAO in the south than in the north of Portugal, although these relations remain a challenging task.

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TL;DR: In this paper, the authors examined abrupt changes in the mean and variance of flood peak distributions through change point analyses and temporal trends in the flood peak records through nonparametric tests.
Abstract: [1] Annual maximum peak discharge time series from 572 stations with a record of at least 75 years in the eastern United States are used to examine flood peak distributions from a regional perspective. The central issues of this study are (1) "mixtures" of flood peak distributions, (2) upper tail properties of flood peaks, (3) scaling properties of flood peaks, (4) spatial heterogeneities of flood peak distributions, and (5) temporal nonstationarities of annual flood peaks. Landfalling tropical cyclones are an important element of flood peak distributions throughout the eastern United States, but their relative importance in the "mixture" of annual flood peaks varies widely, and abruptly, in space over the region. Winter-spring extratropical systems and warm season thunderstorm systems also introduce distinct flood peak populations, with spatially varying control of flood frequency distributions over the eastern United States. We examine abrupt changes in the mean and variance of flood peak distributions through change point analyses and temporal trends in the flood peak records through nonparametric tests. Abrupt changes, rather than slowly varying trends, are typically responsible for nonstationarities in annual flood peak records in the eastern United States, and detected change points are often linked to regulation of river basins. Trend analyses for the 572 eastern United States gaging stations provide little evidence at this point (2009) for increasing flood peak distributions associated with human-induced climate change. Estimates of the location, scale, and shape parameters of the generalized extreme value (GEV) distribution provide a framework for examining scaling properties of flood peaks and upper tail properties of flood distributions. It is shown that anomalously large values of the GEV shape parameter estimates are linked to the role of tropical cyclones in controlling the upper tail of flood distributions. Scaling analyses of flood peaks highlight the heterogeneities in flood magnitudes over the region with maxima in scaled flood magnitudes in the high-elevation Appalachian Mountains and minima in the low-gradient Coastal Plain.

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TL;DR: The relationship between the duration of hillslope-riparian-stream hydrologic connectivity and the rate and degree of riparian shallow groundwater turnover along four HRS well transects within a set of nested mountain catchments (Tenderfoot Creek Experimental Forest, MT) was investigated in this paper.
Abstract: [1] Hydrologic connectivity between catchment upland and near stream areas is essential for the transmission of water, solutes, and nutrients to streams. However, our current understanding of the role of riparian zones in mediating landscape hydrologic connectivity and the catchment scale export of water and solutes is limited. We tested the relationship between the duration of hillslope-riparian-stream (HRS) hydrologic connectivity and the rate and degree of riparian shallow groundwater turnover along four HRS well transects within a set of nested mountain catchments (Tenderfoot Creek Experimental Forest, MT). Transect HRS water table connectivity ranged from 9 to 123 days during the annual snowmelt hydrograph. Hillslope water was always characterized by low specific conductance (∼27 μS cm−1). In transects with transient hillslope water tables, riparian groundwater specific conductance was elevated during base flow conditions (∼127 μS cm−1) but shifted toward hillslope signatures once a HRS groundwater connection was established. The degree of riparian groundwater turnover was proportional to the duration of HRS connectivity and inversely related to the riparian: hillslope area ratios (buffer ratio; r2 = 0.95). We applied this relationship to the stream network in seven subcatchments within the Tenderfoot Creek Experimental Forest and compared their turnover distributions to source water contributions measured at each catchment outlet. The amount of riparian groundwater exiting each of the seven catchments was linearly related (r2 = 0.92) to their median riparian turnover time. Our observations suggest that the size and spatial arrangement of hillslope and riparian zones along a stream network and the timing and duration of groundwater connectivity between them is a first-order control on the magnitude and timing of water and solutes observed at the catchment outlet.

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TL;DR: In this paper, a passive soil distributed temperature sensing (DTS) method is introduced as an experimental method of measuring soil moisture on the basis of DTS and several fiberoptic cables in a vertical profile are used as thermal sensors, measuring propagation of temperature changes due to the diurnal cycle.
Abstract: Through its role in the energy and water balances at the land surface, soil moisture is a key state variable in surface hydrology and land?atmosphere interactions. Point observations of soil moisture are easy to make using established methods such as time domain reflectometry and gravimetric sampling. However, monitoring large?scale variability with these techniques is logistically and economically infeasible. Here passive soil distributed temperature sensing (DTS) will be introduced as an experimental method of measuring soil moisture on the basis of DTS. Several fiber?optic cables in a vertical profile are used as thermal sensors, measuring propagation of temperature changes due to the diurnal cycle. Current technology allows these cables to be in excess of 10 km in length, and DTS equipment allows measurement of temperatures every 1 m. The passive soil DTS concept is based on the fact that soil moisture influences soil thermal properties. Therefore, observing temperature dynamics can yield information on changes in soil moisture content. Results from this preliminary study demonstrate that passive soil DTS can detect changes in thermal properties. Deriving soil moisture is complicated by the uncertainty and nonuniqueness in the relationship between thermal conductivity and soil moisture. A numerical simulation indicates that the accuracy could be improved if the depth of the cables was known with greater certainty.

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TL;DR: In this paper, the authors compare the abilities of coupled and uncoupled inversion using a synthetic example where surface-based electrical conductivity surveys are used to monitor one-dimensional infiltration and redistribution.
Abstract: [1] There is increasing interest in the use of multiple measurement types, including indirect (geophysical) methods, to constrain hydrologic interpretations. To date, most examples integrating geophysical measurements in hydrology have followed a three-step, uncoupled inverse approach. This approach begins with independent geophysical inversion to infer the spatial and/or temporal distribution of a geophysical property (e.g., electrical conductivity). The geophysical property is then converted to a hydrologic property (e.g., water content) through a petrophysical relation. The inferred hydrologic property is then used either independently or together with direct hydrologic observations to constrain a hydrologic inversion. We present an alternative approach, coupled inversion, which relies on direct coupling of hydrologic models and geophysical models during inversion. We compare the abilities of coupled and uncoupled inversion using a synthetic example where surface-based electrical conductivity surveys are used to monitor one-dimensional infiltration and redistribution. Through this illustrative example, we show that the coupled approach can provide significant reductions in uncertainty for hydrologic properties and associated predictions if the underlying model is a faithful representation of the hydrologic processes. However, if the hydrologic model exhibits structural errors, the coupled inversion may not improve the hydrologic interpretation. Despite this limitation, our results support the use of coupled hydrogeophysical inversion both for the direct benefits of reduced errors during inversion and because of the secondary benefits that accrue because of the extensive communication and sharing of data necessary to produce a coupled model, which will likely lead to more thoughtful use of geophysical data in hydrologic studies.

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TL;DR: This study demonstrates that regional scale hydrology simulations on the order of 103 km2 are feasible at hydrologic resolution with reasonable computation times, which has been previously assumed to be an intractable computational problem.
Abstract: [1] We present the results of a unique, parallel scaling study using a 3-D variably saturated flow problem including land surface processes that ranges from a single processor to a maximum number of 16,384 processors. In the applied finite difference framework and for a fixed problem size per processor, this results in a maximum number of approximately 8 × 109 grid cells (unknowns). Detailed timing information shows that the applied simulation platform ParFlow exhibits excellent parallel efficiency. This study demonstrates that regional scale hydrologic simulations on the order of 103 km2 are feasible at hydrologic resolution (∼100–101 m laterally, 10−2–10−1 m vertically) with reasonable computation times, which has been previously assumed to be an intractable computational problem.

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TL;DR: In this article, the authors examined the uptake of groundwater by deciduous blue oak trees (Quercus douglasii) in a California oak savanna and found that during the dry season, groundwater uptake rates ranged from 4 to 25 mm month−1 and approximately 80% of total ET during June, July, and August came from groundwater.
Abstract: [1] Groundwater can serve as an important resource for woody vegetation in semiarid landscapes, particularly when soil water is functionally depleted and unavailable to plants. This study examines the uptake of groundwater by deciduous blue oak trees (Quercus douglasii) in a California oak savanna. Here we present a suite of direct and indirect methods that demonstrate its occurrence and quantify its rates. The study site is underlain by a thin soil layer and fractured metavolcanic bedrock. Typical depth to groundwater is approximately 8 m. A variety of water storage and flux measurements were collected from 2005 to 2008, including groundwater levels, soil moisture contents, sap flows, and latent heat fluxes. During the dry season, groundwater uptake rates ranged from 4 to 25 mm month−1 and approximately 80% of total ET during June, July, and August came from groundwater. Leaf and soil water potentials supported these results, indicating that groundwater uptake was thermodynamically favorable over soil water uptake for key portions of the growing season. These findings strongly suggest that blue oaks should be considered obligate phreatophytes and that groundwater reserves provide a buffer to rapid changes in their hydroclimate, if these assets are not otherwise depleted by prolonged drought or human consumption. While groundwater uptake may provide for short-term protection, it should be viewed not as a mechanism for continued plant growth. It allows the woody vegetation to subsist during the summer but not to flourish.

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TL;DR: In this article, a fiber optic cable with an electrically conductive armoring was buried in variably saturated sand and heated via electrical resistance to create thermal pulses monitored by observing the distributed Raman backscatter.
Abstract: Accurate methods are needed to measure changing soil water content from meter to kilometer scales. Laboratory results demonstrate the feasibility of the heat pulse method implemented with fiber optic temperature sensing to obtain accurate distributed measurements of soil water content. A fiber optic cable with an electrically conductive armoring was buried in variably saturated sand and heated via electrical resistance to create thermal pulses monitored by observing the distributed Raman backscatter. A new and simple interpretation of heat data that takes advantage of the characteristics of fiber optic temperature measurements is presented. The accuracy of the soil water content measurements varied approximately linearly with water content. At volumetric moisture content of 0.05 m3/m3 the standard deviation of the readings was 0.001 m3/m3, and at 0.41 m3/m3 volumetric moisture content the standard deviation was 0.046 m3/m3. This uncertainty could be further reduced by averaging several heat pulse interrogations and through use of a higher?performance fiber optic sensing system.