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GUNS N ROSES / AXL ROSE LIVE / MAGAZINE FULL PAGE PINUP POSTER C
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GUNS N ROSES / AXL ROSE LIVE / MAGAZINE FULL PAGE PINUP POSTER C
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“THIS IS A MAGAZINE ONE PAGE PAPER PICTURE / CLIPPING.”
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11 X 8
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United States
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Guns N' Roses
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GUNS N ROSES / AXL ROSE LIVE / MAGAZINE FULL PAGE PINUP POSTER C
This study aims at designing water supply strategies that are robust against climate, social, and land use changes in a sub-Saharan river basin. We found that robustness analysis supports the discovery of policies enhancing the resilience of water resources systems, benefiting the agricultural, energy, and urban sectors. We show how energy sustainability is affected by water availability, while urban and irrigation resilience also depends on infrastructural interventions and land use changes.
Many communities in the Sahel rely solely on groundwater. We develop a machine learning technique to map areas of groundwater potential. Algorithms are trained to detect areas where there is a confluence of factors that facilitate groundwater occurrence. Our contribution focuses on using variable scaling to minimize expert bias and on testing our results beyond standard metrics. This approach is illustrated through its application to two administrative regions of Mali.
Hourly streamflow ensemble forecasts with the CSSPv2 land surface model and ECMWF meteorological forecasts reduce both the probabilistic and deterministic forecast error compared with the ensemble streamflow prediction approach during the first week. The deterministic forecast error can be further reduced in the first 72 h when combined with the long short-term memory (LSTM) deep learning method. The forecast skill for LSTM using only historical observations drops sharply after the first 24 h.
Preprint under review for HESS(discussion: open, 0 comments)
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In this text, we show how the Eyes on Earth Study politicizing the Chinese mainstream reservoirs affected the transboundary water governance and how to ensure the accountable research dialogue in water science. Our data show that since the publication of the Eyes on Earth Study in April 2020, there are growing disputes which contribute to the political distrusts, degradation of the water science and the rise of anti-science movements undermining the accountable research dialogue.
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Watertable fluctuations and seawater intrusion are characteristic features of coastal unconfined aquifers. A modified expression is first proposed for the dynamic effective porosity due to watertable fluctuations. Then, the new expression is implemented in existing Boussinesq equations and a numerical model, allowing for examination of the effects of the dynamic effective porosity on watertable fluctuations and seawater intrusion in coastal unconfined aquifers, respectively.
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The Belgian city of Spa is known worldwide for its ferruginous and naturally sparkling groundwater springs that gave their name to the bathing tradition commonly called ‘spa’. However, the origin of the dissolved CO2 they contain was still a matter of debate. Thanks to new analysis on groundwater samples, particularly carbon and helium isotopes together with dissolved gases, this study has demonstrated the volcanic origin of the CO2, presumably from the Eifel Volcanic Fields degassing plume.
Preprint under review for HESS(discussion: open, 1 comment)
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This study proposes an approach for generating future multisite daily streamflow conditioned on a relationship between annual maximum temperature and annual streamflow. The approach can avoid uncertainties during realization for climate model-based rainfall information. Results show that the generated sequences preserve many of the historical characteristics. For future streamflow simulations, significant decreases are projected, likely giving nontrivial impacts on regional water security.
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How to combine multi-source precipitation data effectively is one of the hot topics in hydrometeorological research. This study presents a two-step merging strategy based on machine learning to merge multi-source precipitation over China. The results demonstrate that the proposed method effectively distinguishes the occurrence of precipitation events and reduces the error of precipitation amounts. XGBoost is more efficient and has referential significance for other areas with large data amounts.
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A WEAP based hydrological model study exploring the causes of a lake desiccation, was transformed into a multiple question driven process to help answer the diversity of questions instigating conflict in a parallel collaborative process. The identification and evaluation of strategies allowed to better adjust the model, address questions that were causing suspicions and conflicts, while identifying a combination of strategies that were of moderate impact, but of higher local acceptability.
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The Digital Earth (DE) metaphor is very useful for both end users and for hydrological modellers. We analyse different categories of models, with the view of making them part of a Digital eARth Twin Hydrology system (called DARTH). We also stress the idea that DARTHs are not models in and of themselves, rather they need to be built on an appropriate information technology infrastructure. The urgency for DARTHs to be in light of the Open Science movement and its ideas.
We investigated how a precipitation post-processor interacts with other tools for uncertainty quantification in a hydrometeorological forecasting chain. Four systems were implemented to generate 7 d ensemble streamflow forecasts, which vary from partial to total uncertainty estimation. Overall analysis showed that post-processing and initial condition estimation ensure the most skill improvements, in some cases even better than a system that considers all sources of uncertainty.
Using specific conductivity (SC) to estimate groundwater inflow to rivers is complicated by bank return waters, interflow, and flows off floodplains contributing to baseflow in all but the driest years. Using the maximum SC of the river in dry years to estimate the SC of groundwater produces the best baseflow vs. streamflow trends. The variable composition of baseflow hinders calibration of hydrograph-based techniques to estimate groundwater inflows.
Preprint under review for HESS(discussion: open, 0 comments)
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It is found that the precipitation variability dominantly controls global ET in the dry climates, the net radiation has substantial control over ET in the tropical regions, and VPD is impacting ET trends in boreal mid-latitude climate. The critical role of VPD in controlling ET trends is particularly emphasized due to its influence in controlling the land-atmosphere interactions.
The development of high-resolution global precipitation forecasts and the lack of reliable precipitation forecasts over Africa motivates this work to evaluate the precipitation forecasts from the Global Forecast System (GFS) over the Niger river basin in Africa. The GFS forecasts, at a 15 d accumulation timescale, have an acceptable performance; however, the forecasts are highly biased. It is recommended to apply bias correction to GFS forecasts before their application.
Preprint under review for HESS(discussion: open, 0 comments)
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Heat in the subsurface can be used to characterize aquifer flow behaviour. The temperature data obtained can be useful to understand the groundwater flow which is of particular importance in waste disposal studies. Satellite images of surface temperature and a temperature-time curve were used implemented in a heat-transport model. Results indicate conduction playing a major role in the aquifer, and support the usefulness of temperature measurements.
Preprint under review for HESS(discussion: open, 2 comments)
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A sound understanding of how floods come about allows the development of more reliable flood management tools that assist in mitigating their negative impacts. This article reviews river flood generation processes and flow paths across space scales, starting from water movement in the soil pores, and moving up to hillslopes, catchments, regions and entire continents. To assist model development, there is a need to learn from observed patterns of flood generation processes at all spatial scales.
Preprint under review for HESS(discussion: open, 0 comments)
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Although the “dry gets drier and wet gets wetter” (DDWW) paradigm is widely used to describe the trends in wetting and drying globally, we show that 27.1 % of global land agrees with the paradigm, while 22.4 % shows the opposite pattern during the period 1985–2014 from the perspective of terrestrial water storage change. Similar percentages are discovered under different scenarios during the future period. Our findings will benefit the understanding of hydrological responses under climate change.
Timely projections of seasonal streamflow extremes on a river network can be useful for flood risk mitigation, but this is challenging, particularly under space–time nonstationarity. We develop a space–time Bayesian hierarchical model (BHM) using temporal climate covariates and copulas to project seasonal streamflow extremes and the attendant uncertainties. We demonstrate this on the Upper Colorado River basin to project spring flow extremes using the preceding winter’s climate teleconnections.
This study aims to predict long-term averages of low flow on a hydrologically diverse dataset in Austria. We compared seven statistical learning methods and included a backward variable selection approach. We found that separating the low-flow processes into winter and summer low flows leads to good performance for all the models. Variable selection results in more parsimonious and more interpretable models. Linear approaches for prediction and variable selection are sufficient for our dataset.
Preprint under review for HESS(discussion: open, 0 comments)
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Increasing amounts of water are being used for agriculture. Therefore, we looked into how the irrigation requirement will evolve under a changing climate over Europe. Our results show that, for the end of the century and under high emissions, the irrigation water will increase by 30 % compared to the year 2000. Moreover, the irrigation requirement is likely to vary more from one year to another. However, if emissions are mitigated, these effects are reduced.
The aim of this study was to develop a high-accuracy micro-lysimeter system for the quantification of non-rainfall water inputs that overcomes existing drawbacks. The micro-lysimeter system had a high accuracy and allowed us to quantify and distinguish between different types of non-rainfall water inputs, like dew and fog. Non-rainfall water inputs occurred frequently in a Swiss Alpine grassland ecosystem. These water inputs can be an important water source for grasslands during dry periods.
In this study, we presented stable isotopes in atmospheric water vapor and precipitation for five extreme winter precipitation events in Nanjing, southeastern China, from December 2018 to February 2019. Our results imply that multiple moisture sources and the rapid shift among them are important conditions for sustaining extreme precipitation events, especially in the relatively cold and dry winter.
Preprint under review for HESS(discussion: open, 0 comments)
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Managing for environmental streamflows involve the practice of prioritizing healthy stream ecosystems while distributing water resources. Classifying similar streams is a useful step in developing environmental streamflows. Environmental streamflows are often needed on streams that must be modeled because they do not contain flow data. This paper has developed a new method of classification that prioritizes model accuracy. The new method advances environmental streamflow management.
Preprint under review for HESS(discussion: open, 0 comments)
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Patchy snow cover is a common phenomenon in mountain landscapes. It leads to a longer period of snowmelt contribution to streams. Our study shows that surface variability of snow cover leads to differences in streamflow, evapotranspiration and snowmelt responses. We have used up-to-date hydrological tools strongly constrained with data collected from field and satellite images. The study finding will be helpful for the mountain hydrology community in the proper estimation of water resources.
Preprint under review for HESS(discussion: open, 0 comments)
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Aquifers often act as low-pass filters, dampening high-frequency (infra-annual) and amplifying low-frequency (LFV, multi-annual to multidecadal) variabilities originating from climate variability. By processing groundwater level signals, we show the key role of LFV in the occurrence of extreme groundwater levels (GWE). Results highlight how changes in LFV may impact future GWE, as well as the importance of correct representation of LFV in General Circulation Model outputs for GWE projection.
Preprint under review for HESS(discussion: open, 3 comments)
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A concurrent in-depth investigation of rainfall partitioning at inter- and intra-event scales for two xerophytic shrubs was conducted. Inter-event rainfall partitioning amount and percentage depended more on rainfall amount, and rainfall intensity and duration controlled intra-event rainfall partitioning variables. Shrub has larger branch angle, more small branch and smaller canopy area to produce stemflow more efficiently, and the one has larger biomass to intercept more rainfall.
Preprint under review for HESS(discussion: open, 0 comments)
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We proposed a deep learning technique-based data-driven flood prediction approach, employing an integration of the LSTM technique and Bayesian optimization approach. Results showed that the proposed model can accurately produce flood maps for various hyetograph inputs, meanwhile with substantial improvements in computation time. The proposed model can potentially replace and/or complement the conventional hydrodynamic model for urban flood assessment and management.
Geophysical instruments are often used in hydrological surveys. A geophysical model that couples electrical conductivity in the subsurface layers with measurements from an electromagnetic induction instrument was combined with a machine learning algorithm. The study reveals that this combination can estimate the identifiability of electrical conductivity in a layered soil and provide insight into the best way to configure the instrument for a specific field site.
We present an approach on how to incorporate crop phenology in a regional hydrological model using decision tables and global datasets of rainfed and irrigated cropland with the associated cropping calendar and management practices. Results indicate improved temporal patterns of leaf area index (LAI) and evapotranspiration (ET) simulations in comparison with remote sensing data. In addition, the improvement of the cropping season also helps to improve soil erosion estimates in cultivated areas.
Preprint under review for HESS(discussion: open, 0 comments)
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The geologic structure of mountain watersheds is thought to control how groundwater and stream water exchange. We measured bedrock depth at 191 locations along eight headwater streams, and paired with stream temperature records and observations of channel dewatering. The data indicated a prevalence of shallow bedrock. We hypothesized that variation in bedrock depth might cause stream dewatering, which was found to be true for some streams but not others, based on local groundwater supply.
Preprint under review for HESS(discussion: open, 0 comments)
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Seasonal forecasts can help in safely and efficiently managing a fresh water reservoir in the Netherlands. We compare hydrological forecast systems of the river Rhine, the lakes most important source and analyze forecast skill for over 1993–2016 and for specific extreme years. On average, forecast skill is high in spring due to Alpine snow and smaller in summer. Dry summers appear to be more predictable, skill increases with event extremity. In those cases, seasonal forecasts are valuable tools.
Drying soil layers (DSLs) have been extensively reported in artificial forestland in the Loess Plateau, China, which has limited water resources and deep loess. To address this issue relating to plant root–soil water interactions, this study developed a root growth model that simulates both the dynamic rooting depth and fine-root distribution. Evaluation vs. field data proved a positive performance. Long-term simulation reproduced the evolution process of the DSLs and revealed their mechanisms.
Many data sources are available to evaluate components of the water cycle (precipitation, evapotranspiration, runoff, and terrestrial water storage). Despite this variety, it remains unclear how different combinations of datasets satisfy the conservation of mass. We conducted the most comprehensive analysis of water budget closure on a global scale to date. Our results can serve as a basis to select appropriate datasets for regional hydrological studies.
Preprint under review for HESS(discussion: open, 0 comments)
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We developed a Gaussian Bayesian Network (GBN) for seasonal forecasting of lake water quality, including algal bloom risk, in a shallow nutrient-impacted lake in southern Norway. Discrete Bayesian networks are commonly used in environmental modelling, but this is one of very few applications of a continuous BN. The GBN approach proved to be promising, particularly where training datasets are small.
We investigate the impact of baseflow contribution on concentration–flow (C–Q) relationships across the Australian continent. We developed a novel Bayesian hierarchical model for six water quality variables across 157 catchments that span five climate zones. For sediments and nutrients, the C–Q slope is generally steeper for catchments with a higher median and a greater variability of baseflow contribution, highlighting the key role of variable flow pathways in particulate and solute export.
Analytical solutions are derived for steady-state seawater intrusion in annulus segment aquifers. These analytical solutions are validated by comparing their predictions with experimental data. We find seawater intrusion is the most extensive in divergent aquifers, and the opposite is the case for convergent aquifers. The analytical solutions facilitate engineers and hydrologists in evaluating seawater intrusion more efficiently in annulus segment aquifers with a complex geometry.
Eva Sebok, Hans Jørgen Henriksen, Ernesto Pastén-Zapata, Peter Berg, Guillume Thirel, Anthony Lemoine, Andrea Lira-Loarca, Christiana Photiadou, Rafael Pimentel, Paul Royer-Gaspard, Erik Kjellström, Jens Hesselbjerg Christensen, Jean-Philippe Vidal, Philippe Lucas-Picher, Markus G. Donat, Giovanni Besio, María José Polo, Simon Stisen, Yvan Caballero, Ilias G. Pechlivanidis, Lars Troldborg, and Jens Christian Refsgaard
Preprint under review for HESS(discussion: open, 1 comment)
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Hydrological models projecting the impact of changing climate carry a lot of uncertainty. Thus, these models usually have a multitude of simulations using different future climate data. This study used the subjective opinion of experts to assess which climate and hydrological models are the most likely to correctly predict climate impacts, thereby easing the computational burden. The experts could select more likely hydrological models, while the climate models were deemed equally probable.
Preprint under review for HESS(discussion: open, 1 comment)
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Given the recent developments in socio-hydrology and its potential contributions to reduce disaster risk, we conducted research focused on evaluating the extent to which socio-hydrology studies in the areas of natural hazards and disaster are integrative. Based on the persisting gaps identified, we highlighted the specific research needs that will play an important role in ensuring socio-hydrology is capable of holistically addressing natural hazards and disasters.
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In this study, we proposed a new framework that considered the uncertainties of model simulations to quantify the contribution rate of climate change and human activities to streamflow changes. Then, the Lancang River Basin was selected for the case study. The results of quantitative analysis using the new framework showed that the reason for the decrease in the streamflow at Yunjinghong station was mainly due to human activities.
Lorenzo Alfieri, Francesco Avanzi, Fabio Delogu, Simone Gabellani, Giulia Bruno, Lorenzo Campo, Andrea Libertino, Christian Massari, Angelica Tarpanelli, Dominik Rains, Diego G. Miralles, Raphael Quast, Mariette Vreugdenhil, Huan Wu, and Luca Brocca
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This work shows advances in high resolution satellite data for hydrology. We performed hydrological simulations for the Po River Basin using various satellite products, including precipitation, evaporation, soil moisture and snow depth. Evaporation and snow depth improved a simulation based on high quality ground observations. Interestingly, a model calibration relying on satellite data skillfully reproduces observed discharges, paving the way to satellite-driven hydrological applications.
Laurent Lassabatere, Pierre-Emmanuel Peyneau, Deniz Yilmaz, Joseph Pollacco, Jesús Fernández-Gálvez, Borja Latorre, David Moret-Fernández, Simone Di Prima, Mehdi Rahmati, Ryan D. Stewart, Majdi Abou Najm, Claude Hammecker, and Rafael Angulo-Jaramillo
Preprint under review for HESS(discussion: open, 1 comment)
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Sorptivity is one of the most important parameters for the quantification of water infiltration into soils. A specific formulation is commonly used to derive sorptivity from the soil hydraulic diffusivity, initial and final conditions. In this study, we propose a mixed formulation that avoids numerical issues and allows for the computation of sorptivity for all types of models chosen for describing water retention and hydraulic conductivity functions, and all initial and final conditions.
Using a statistical model that can also take complex systems into account, the most important factors affecting wheat yield in Germany are determined. Different spatial damage potentials are taken into account. In many parts of Germany, yield losses are caused by too much soil water in spring. Negative heat effects as well as damaging soil drought are identified especially for north-eastern Germany. The model is able to explain years with exceptionally high yields (2014) and losses (2003, 2018).
This work demonstrates the relevance of using a water budget model to understand long-term transient and regional-scale groundwater recharge (GWR) in cold and humid climates where groundwater observations are scarce. Monthly GWR is simulated for 57 years on 500 m x 500 m cells in Canada (36 000 km2 area) with limited uncertainty due to a robust automatic calibration method. The increases in precipitation and temperature since the 1960s have not yet produced significant changes in annual GWR.
Cosmic-ray neutron sensing provides areal average soil moisture measurements. We investigated how distinct differences in spatial soil moisture patterns influence the soil moisture estimates and present two approaches to improve the estimate of soil moisture close to the instrument by reducing the influence of soil moisture further afield. Additionally, we show that the heterogeneity of soil moisture can be assessed based on the relationship of different neutron energies.
Preprint under review for HESS(discussion: open, 0 comments)
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Comparison of streamflow composition of two small experimental catchments simulated with three well-known rainfall-runoff (RR) models against the End-Member Mixing Analysis (EMMA) results. All used RR models and EMMA outcome demonstrate that two neighboring catchments significantly different in mutual dynamics of the runoff fractions. Three data aggregation intervals (season, month and pentad) were applied to assess proximity of the RR models and EMMA hydrograph decomposition outcome.
The rapid increase in economic development and urbanization is contributing to the imbalances and conflicts between water supply and demand and further deteriorates river ecological health, which intensifies their interactions and causes water unsustainability. This paper proposes a methodology for sustainable development of water resources, considering socioeconomic development, food safety, and ecological protection, and the dynamic interactions across those water users are further assessed.
Preprint under review for HESS(discussion: open, 2 comments)
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River discharge is strongly influenced by the temporal structure of precipitation. Here, we show how extreme precipitation events that occur a few days or weeks after a previous event have a larger effect on river discharge than events occurring in isolation. Windows of two weeks or less between events have the most impact. Similarly, periods of persistent high discharge tend to be associated with the occurrence of several extreme precipitation events in close succession.
Preprint under review for HESS(discussion: open, 3 comments)
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We showed that flash floods occurred more often in recent years in central western Europe. Therefore, we identified and analysed the major atmospheric ingredients for rain-intense thunderstorms: high atmospheric moisture, sufficient latent instability, and weak thunderstorm cell motion. Between 1981–2020, atmospheric conditions became likelier to support strong thunderstorms. The occurrence of extreme rainfall events, as well as their rainfall intensity, stayed, however, mostly unchanged.
Response surfaces are increasingly used to identify the hydroclimatic conditions leading to a water resources system's failure. Partitioning the surface usually requires performance thresholds that are not necessarily crisp. We propose a methodology that combines the inherent uncertainty of response surfaces with the ambiguity of performance thresholds. The proposed methodology is illustrated with a multireservoir system in Canada for which some performance thresholds are imprecise.
Increased nitrate concentrations in surface waters can compromise river ecosystem health. As riverine nitrate uptake is hard to measure, we explore how low-frequency nitrate concentration and discharge observations (that are widely available) can help to identify (in)efficient uptake in river networks. We find that channel geometry and water velocity rather than the biological uptake capacity dominate the nitrate-discharge pattern at the outlet. The former can be used to predict uptake.
We examine the performance of a widely used Lagrangian method for moisture tracking by comparing it with a highly accurate Eulerian tool, both operating on the same WRF atmospheric model fields. Although the Lagrangian approach is very useful for a qualitative analysis of moisture sources, it has important limitations in quantifying the contribution of individual sources to precipitation. These drawbacks should be considered by other authors in the future so as to not draw erroneous conclusions.
Extreme rainfall events are modeled in this study for different timescales. A new parameterization of the dependence between extreme values and their timescale enables our model to estimate extremes on very short (1 min) and long (5 d) timescales simultaneously. We compare different approaches of modeling this dependence and find that our new model improves performance for timescales between 2 h and 2 d without affecting model performance on other timescales.
Preprint under review for HESS(discussion: open, 0 comments)
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We applied the CoupModel to quantify the impacts of natural and human disturbances to adjacent water bodies in regulating net CO2 uptake of northern peatlands. We found 1 m drops of the water level at the beaver pond, lower the peatland water table depth, 250 m away by 0.15 m and reduce the peatland net CO2 uptake by 120 g C m−2 yr−1 therefore even though bogs are ombrotrophic rainfed systems, the boundary hydrological conditions play an important role in regulating water storage and CO2 uptake.
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Preprint under review for HESS(discussion: open, 0 comments)
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In this paper we developed semi-distributed rainfall-runoff models in predictive mode and provided better or similar performance compared to lumped models calibrated on internal stations. NDII proves to be effective to distribute root zone moisture capacity over sub-catchments and is well correlated with the percentage of evergreen forest. Soil moisture simulations are highly correlated with NDII in the dry season and water limited ecosystems, and agree with the SWI index in all seasons.
Preprint under review for HESS(discussion: open, 1 comment)
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The common practice of calibrating lake hydrodynamics models only to temperature data is shown to be unable to reproduce the flow dynamics well. We proposed a new dynamically normalized objective function (DyNO) for multi-variable calibration to be used with parallel or serial optimization methods. DyNO is successfully applied to simultaneously calibrate the temperature and velocity of a 3-dimensional tropical lake model.