bluuebunny/crossref_metadata_2025_split huggingface dataset:
InSAR Measurements and Viscoelastic Modeling of Sinkhole Precursory Subsidence: Implications for Sinkhole Formation, Early Warning, and Sediment Properties
Authors: Baer G. , Magen Y. , Nof R. N. , Raz E. , Lyakhovsky V. , Shalev E. 
Published: March 2018

AbstractDuring the past three decades, thousands of sinkholes were formed along the Dead Sea (DS) shorelines in Israel and Jordan, due to dissolution of subsurface salt by undersaturated groundwater. The sinkholes are associated with gradual subsidence preceding their collapse by periods ranging from a few days to almost 5 years. To determine the factors controlling this precursory subsidence, we examine tens of subsidence‐sinkhole sequences along the DS shorelines in Israel. The duration and magnitude of the precursory subsidence are determined by Interferometric Synthetic Aperture Radar (InSAR) measurements and simulated by viscoelastic damage rheology models. Longer periods of precursory subsidence are found in the cemented alluvial fans and in simulations of higher‐viscosity sediments. While surface subsidence accelerates during the precursory period, the widths of the subsiding areas remain uniform, suggesting that during this period upward propagation of damage from the subsurface cavity is not accompanied by upward migration of the actual cavity. Our observations and simulations are used to constrain the viscosity of the sediments along the DS and to reduce sinkhole hazards by assessing the precursory times of future sinkholes in the different sedimentary environments.
A New Scheme for Considering Soil Water‐Heat Transport Coupling Based on Community Land Model: Model Description and Preliminary Validation
Authors: Wang Chenghai , Yang Kai 
Published: March 2018

AbstractLand surface models (LSMs) have developed significantly over the past few decades, with the result that most LSMs can generally reproduce the characteristics of the land surface. However, LSMs fail to reproduce some details of soil water and heat transport during seasonal transition periods because they neglect the effects of interactions between water movement and heat transfer in the soil. Such effects are critical for a complete understanding of water‐heat transport within a soil thermohydraulic regime. In this study, a fully coupled water‐heat transport scheme (FCS) is incorporated into the Community Land Model (version 4.5) to replaces its original isothermal scheme, which is more complete in theory. Observational data from five sites are used to validate the performance of the FCS. The simulation results at both single‐point and global scale show that the FCS improved the simulation of soil moisture and temperature. FCS better reproduced the characteristics of drier and colder surface layers in arid regions by considering the diffusion of soil water vapor, which is a nonnegligible process in soil, especially for soil surface layers, while its effects in cold regions are generally inverse. It also accounted for the sensible heat fluxes caused by liquid water flow, which can contribute to heat transfer in both surface and deep layers. The FCS affects the estimation of surface sensible heat (SH) and latent heat (LH) and provides the details of soil heat and water transportation, which benefits to understand the inner physical process of soil water‐heat migration.
The Madden‐Julian Oscillation and the Indo‐Pacific Warm Pool
Authors: Raymond David J. , Fuchs Željka 
Published: March 2018

AbstractA minimal model of the interaction of the Madden‐Julian oscillation (MJO) with the Indo‐Pacific warm pool is presented. This model is based on the linear superposition of the flow associated with a highly simplified treatment of the MJO plus the flow induced by the warm pool itself. Both of these components parameterize rainfall as proportional to the column water vapor, which in turn is governed by a linearized moisture equation in which WISHE (wind induced surface heat exchange) plays a governing role. The MJO component has maximum growth rate for planetary wavenumber 1 and is equatorially trapped with purely zonal winds. The warm pool component exhibits a complex flow pattern, differing significantly from the classical Gill model as a result of the mean easterly flow. The combination of the two produce a flow that reproduces many aspects of the observed global flow associated with the MJO.
Characterization of Short‐Wave Fadeout Seen in Daytime SuperDARN Ground Scatter Observations
Authors: Chakraborty S. , Ruohoniemi J. M. , Baker J. B. H. , Nishitani N. 
Published: March 2018

AbstractShort‐wave fadeout (SWF) is a well‐known radio wave anomaly which follows Earth‐directed solar flares and leads to severe disruption of transionospheric high‐frequency systems. The disruption is produced by flare‐enhanced soft and hard X‐rays that penetrate to the D layer where they dramatically enhance ionization leading to heavy high‐frequency absorption over much of the dayside for an hour or more. In this paper, we describe how Super Dual Auroral Radar Network (SuperDARN) observations can be exploited to analyze SWF events. Superposed epoch analysis of multiple signatures reveals the typical characteristics of SWF. The number of SuperDARN ground scatter echoes drops suddenly (≈100 s) and sharply after a solar flare, reaching a maximum depth of suppression within a few tens of minutes, and then recovering to pre‐SWF conditions over half an hour or so. The depth of echo suppression depends on the solar zenith angle, radio wave frequency, and intensity of the flare. Furthermore, ground scatter echoes typically exhibit a sudden phase change leading to a dramatic increase in apparent Doppler velocity (the so‐called “Doppler flash”), which statistically precedes the dropout in ground scatter echoes. We report here on the characterization of SWF effects in SuperDARN ground scatter observations produced by several X class solar flares. We also describe the functional dependence of peak Doppler flash on solar zenith angle, frequency, and peak intensity of solar flux.
Solar Influences on the Return Direction of High‐Frequency Radar Backscatter
Authors: Burrell Angeline G. , Perry Gareth W. , Yeoman Timothy K. , Milan Stephen E. , Stoneback Russell 
Published: March 2018

AbstractCoherent‐scatter, high‐frequency, phased‐array radars create narrow beams through the use of constructive and destructive interference patterns. This formation method leads to the creation of a secondary beam, or lobe, that is sent out behind the radar. This study investigates the relative importance of the beams in front of and behind the high‐frequency radar located in Hankasalmi, Finland, using observations taken over a solar cycle, as well as coincident observations from Hankasalmi and the Enhanced Polar Outflow Probe Radio Receiver Instrument. These observations show that the relative strength of the front and rear beams is frequency dependent, with the relative amount of power sent to the front lobe increasing with increasing frequency. At the range of frequencies used by Hankasalmi, both front and rear beams are always present, though the main beam is always stronger than the rear lobe. Because signals are always transmitted to the front and rear of the radar, it is always possible to receive backscatter from both return directions. Examining the return direction as a function of local time, season, and solar cycle shows that the dominant return direction depends primarily on the local ionospheric structure. Diurnal changes in plasma density typically cause an increase in the amount of groundscatter returning from the rear lobe at night, though the strength of this variation has a seasonal dependence. Solar cycle variations are also seen in the groundscatter return direction, modifying the existing local time and seasonal variations.
Conditioning a Hydrologic Model Using Patterns of Remotely Sensed Land Surface Temperature
Authors: Zink Matthias , Mai Juliane , Cuntz Matthias , Samaniego Luis 
Published: March 2018

AbstractHydrologic models are usually calibrated using observed river runoff at catchment outlets. Streamflow, however, represents an integral response of the entire catchment and is observed at a few locations worldwide. Parameter estimation based on streamflow has the disadvantage that it does not consider the spatiotemporal variability of hydrologic states and fluxes such as evapotranspiration. Remotely sensed data, in contrast, include these variabilities and are broadly available. In this study, we assess the predictive skill of satellite‐derived land surface temperature (Ts) with respect to river runoff (Q). We developed a bias‐insensitive pattern‐matching criterion to focus the parameter optimization on spatial patterns of Ts. The proposed method is extensively tested in six distinct large German river basins and cross validated in 222 additional basins in Germany. We conclude that land surface temperature calibration outperforms random drawn parameter sets, which could be meaningful for calibrating hydrologic models in ungauged locations. A combined calibration with Q and Ts reduces the root mean squared error in the predicted evapotranspiration by 8% compared to flux tower observations but reduces the NSEs of the streamflow predictions by 6% on average for the six large basins. Our results show that patterns of Ts better constrain model parameters when considered in a calibration next to Q, which finally reduces parametric uncertainty.
Identifying and Modeling Dynamic Preference Evolution in Multipurpose Water Resources Systems
Authors: Mason E. , Giuliani M. , Castelletti A. , Amigoni F. 
Published: March 2018

AbstractMultipurpose water systems are usually operated on a tradeoff of conflicting operating objectives. Under steady state climatic and socioeconomic conditions, such tradeoff is supposed to represent a fair and/or efficient preference. Extreme variability in external forcing might affect water operators' risk aversion and force a change in her/his preference. Properly accounting for these shifts is key to any rigorous retrospective assessment of the operator's behaviors, and to build descriptive models for projecting the future system evolution. In this study, we explore how the selection of different preferences is linked to variations in the external forcing. We argue that preference selection evolves according to recent, extreme variations in system performance: underperforming in one of the objectives pushes the preference toward the harmed objective. To test this assumption, we developed a rational procedure to simulate the operator's preference selection. We map this selection onto a multilateral negotiation, where multiple virtual agents independently optimize different objectives. The agents periodically negotiate a compromise policy for the operation of the system. Agents' attitudes in each negotiation step are determined by the recent system performance measured by the specific objective they maximize. We then propose a numerical model of preference dynamics that implements a concept from cognitive psychology, the availability bias. We test our modeling framework on a synthetic lake operated for flood control and water supply. Results show that our model successfully captures the operator's preference selection and dynamic evolution driven by extreme wet and dry situations.
Effects of Flood Control Strategies on Flood Resilience Under Sociohydrological Disturbances
Authors: Sung Kyungmin , Jeong Hanseok , Sangwan Nikhil , Yu David J. 
Published: March 2018

AbstractA community capacity to cope with flood hazards, or community flood resilience, emerges from the interplay of hydrological and social processes. This interplay can be significantly influenced by the flood control strategy adopted by a society, i.e., how a society sets its desired flood protection level and strives to achieve this goal. And this interplay can be further complicated by rising land‐sea level differences, seasonal water level fluctuations, and economic change. But not much research has been done on how various forms of flood control strategies affect human‐flood interactions under these disturbances and therefore flood resilience in the long run. The current study is an effort to address these issues by developing a conceptual model of human‐flood interaction mediated by flood control strategies. Our model extends the existing model of Yu et al. (2017), who investigated the flood resilience of a community‐based flood protection system in coastal Bangladesh. The major extensions made in this study are inclusions of various forms of flood control strategies (both adaptive and nonadaptive ones), the challenge of rising land‐sea level differences, and various high tide level scenarios generated from modifying the statistical variances and averages. Our results show that adaptive forms of flood control strategies tend to outperform nonadaptive ones for maintaining the model community's flood protection system. Adaptive strategies that dynamically adjust target flood protection levels through close monitoring of flood damages and social memories of flood risk can help the model community deal with various disturbances.
Inspiring a Broader Socio‐Hydrological Negotiation Approach With Interdisciplinary Field‐Based Experience
Authors: Massuel S. , Riaux J. , Molle F. , Kuper M. , Ogilvie A. , Collard A‐L. , Leduc C. , Barreteau O. 
Published: March 2018

AbstractSocio‐hydrology advanced the field of hydrology by considering humans and their activities as part of the water cycle, rather than as external drivers. Models are used to infer reproducible trends in human interactions with water resources. However, defining and handling water problems in this way may restrict the scope of such modeling approaches. We propose an interdisciplinary socio‐hydrological approach to overcome this limit and complement modeling approaches. It starts from concrete field‐based situations, combines disciplinary as well as local knowledge on water‐society relationships, with the aim of broadening the hydrocentric analysis and modeling of water systems. The paper argues that an analysis of social dynamics linked to water is highly complementary to traditional hydrological tools but requires a negotiated and contextualized interdisciplinary approach to the representation and analysis of socio‐hydro systems. This reflection emerged from experience gained in the field where a water‐budget modeling framework failed to adequately incorporate the multiplicity of (nonhydrological) factors that determine the volumes of withdrawals for irrigation. The pathway subsequently explored was to move away from the hydrologic view of the phenomena and, in collaboration with social scientists, to produce a shared conceptualization of a coupled human‐water system through a negotiated approach. This approach changed the way hydrological research issues were addressed and limited the number of strong assumptions needed for simplification in modeling. The proposed socio‐hydrological approach led to a deeper understanding of the mechanisms behind local water‐related problems and to debates on the interactions between social and political decisions and the dynamics of these problems.
How Does Snow Persistence Relate to Annual Streamflow in Mountain Watersheds of the Western U.S. With Wet Maritime and Dry Continental Climates?
Authors: Hammond John C. , Saavedra Freddy A. , Kampf Stephanie K. 
Published: March 2018

AbstractWith climate warming, many regions are experiencing changes in snow accumulation and persistence. These changes are known to affect streamflow volume, but the magnitude of the effect varies between regions. This research evaluates whether variables derived from remotely sensed snow cover can be used to estimate annual streamflow at the small watershed scale across the western U.S., a region with a wide range of climate types. We compared snow cover variables derived from MODIS, snow persistence (SP), and snow season (SS), to more commonly utilized metrics, snow fraction (fraction of precipitation falling as snow, SF), and peak snow water equivalent (SWE). Each variable represents different information about snow, and this comparison assesses similarities and differences between the snow metrics. Next, we evaluated how two snow variables, SP and SWE, related to annual streamflow (Q) for 119 USGS reference watersheds and examined whether these relationships varied for wet/warm (precipitation surplus) and dry/cold (precipitation deficit) watersheds. Results showed high correlations between all snow variables, but the slopes of these relationships differed between climates, with wet/warm watersheds displaying lower SF and higher SWE for the same SP. In dry/cold watersheds, both SP and SNODAS SWE correlated with Q spatially across all watersheds and over time within individual watersheds. We conclude that SP can be used to map spatial patterns of annual streamflow generation in dry/cold parts of the region. Applying this approach to the Upper Colorado River Basin demonstrates that 50% of streamflow comes from areas >3,000 masl. If the relationship between SP and Q is similar in other dry/cold regions, this approach could be used to estimate annual streamflow in ungauged basins.
On the Sensitivity of Annual Streamflow to Air Temperature
Authors: Milly P. C. D. , Kam J. , Dunne Krista A. 
Published: March 2018

AbstractAlthough interannual streamflow variability is primarily a result of precipitation variability, temperature also plays a role. The relative weakness of the temperature effect at the annual time scale hinders understanding, but may belie substantial importance on climatic time scales. Here we develop and evaluate a simple theory relating variations of streamflow and evapotranspiration (E) to those of precipitation (P) and temperature. The theory is based on extensions of the Budyko water‐balance hypothesis, the Priestley‐Taylor theory for potential evapotranspiration (
), and a linear model of interannual basin storage. The theory implies that the temperature affects streamflow by modifying evapotranspiration through a Clausius‐Clapeyron‐like relation and through the sensitivity of net radiation to temperature. We apply and test (1) a previously introduced “strong” extension of the Budyko hypothesis, which requires that the function linking temporal variations of the evapotranspiration ratio (E/P) and the index of dryness (
/P) at an annual time scale is identical to that linking interbasin variations of the corresponding long‐term means, and (2) a “weak” extension, which requires only that the annual evapotranspiration ratio depends uniquely on the annual index of dryness, and that the form of that dependence need not be known a priori nor be identical across basins. In application of the weak extension, the readily observed sensitivity of streamflow to precipitation contains crucial information about the sensitivity to potential evapotranspiration and, thence, to temperature. Implementation of the strong extension is problematic, whereas the weak extension appears to capture essential controls of the temperature effect efficiently.
Predicting Hydrologic Function With Aquatic Gene Fragments
Authors: Good S. P. , URycki D. R. , Crump B. C. 
Published: March 2018

AbstractRecent advances in microbiology techniques, such as genetic sequencing, allow for rapid and cost‐effective collection of large quantities of genetic information carried within water samples. Here we posit that the unique composition of aquatic DNA material within a water sample contains relevant information about hydrologic function at multiple temporal scales. In this study, machine learning was used to develop discharge prediction models trained on the relative abundance of bacterial taxa classified into operational taxonomic units (OTUs) based on 16S rRNA gene sequences from six large arctic rivers. We term this approach “genohydrology,” and show that OTU relative abundances can be used to predict river discharge at monthly and longer timescales. Based on a single DNA sample from each river, the average Nash‐Sutcliffe efficiency (NSE) for predicted mean monthly discharge values throughout the year was 0.84, while the NSE for predicted discharge values across different return intervals was 0.67. These are considerable improvements over predictions based only on the area‐scaled mean specific discharge of five similar rivers, which had average NSE values of 0.64 and −0.32 for seasonal and recurrence interval discharge values, respectively. The genohydrology approach demonstrates that genetic diversity within the aquatic microbiome is a large and underutilized data resource with benefits for prediction of hydrologic function.
On Permeability Prediction From Complex Conductivity Measurements Using Polarization Magnitude and Relaxation Time
Authors: Robinson Judith , Slater Lee , Weller Andreas , Keating Kristina , Robinson Tonian , Rose Carla , Parker Beth 
Published: March 2018

AbstractGeophysical length scales determined from complex conductivity (CC) measurements can be used to estimate permeability
when the electrical formation factor F is known. Two geophysical length scales have been proposed: (1) the specific polarizability
normalized by the imaginary conductivity
and (2) the time constant
multiplied by a diffusion coefficient
. The parameters
and
account for the control of fluid chemistry and/or varying minerology on the geophysical length scale. We evaluated the predictive capability of two CC permeability models: (1) an empirical formulation based on
or normalized chargeability
and (2) a mechanistic formulation based on
. The performance of the CC models was evaluated against measured
; and further compared against that of well‐established
estimation equations that use geometric length scales. Both CC models predict permeability within one order of magnitude for a database of 58 sandstone samples, with the exception of samples characterized by high pore volume normalized surface area
. Variations in
and
likely contribute to the poor model performance for the high
samples, which contain significant dolomite. Two observations favor the implementation of the
‐based model over the
‐based model for field‐scale
estimation: (1) a limited range of variation in
relative to
and (2)
field measurements are less time consuming to acquire relative to
. The need for a reliable field‐estimate of
limits application of either model, in particular the
model due to a high power law exponent associated with
.
Stochastic Scenario Evaluation in Evolutionary Algorithms Used for Robust Scenario‐Based Optimization
Authors: Sankary Nathan , Ostfeld Avi 
Published: March 2018

AbstractThis paper focuses on evaluating a scenario‐based multiobjective evolutionary algorithm for real‐world design problems in which the environment where a system will operate is dynamic, and uncertain. Subsequently, the performance of a stochastic scenario selection scheme, inspired by methods to reduce overfitting in genetic programming, is investigated for scenario‐based optimization. Using a scenario‐based scheme to address uncertainty in a real‐world system's operational environment, system designs are developed via aggregating the performance of a solution evaluated across many scenarios. Within each generation of the evolutionary algorithm the evaluation suite is resampled and evaluated by the current generation's solutions. This scheme is evaluated on two historical noisy test problems and two real‐world water resources design problem instances. For each case, the stochastic scenario selection scheme is compared to a static selection scheme at various evaluation suite sizes. Results show the proposed scenario selection scheme to outperform static sampling schemes and increase efficiency of a multiobjective evolutionary algorithm for robust optimization objectives.