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Related Concept Videos

Precipitation Gravimetry01:03

Precipitation Gravimetry

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Precipitation gravimetry is based on converting an analyte into a sparingly soluble precipitate, which is separated by filtration and weighed. An ideal precipitate should be pure, insoluble, of known composition, and easily filtered from the reaction mixture.
In determining nickel by gravimetric analysis, a precipitant of ethanolic dimethylglyoxime is added to a hot nickel salt solution. This is quickly followed by the dropwise addition of dilute ammonia solution until precipitation occurs. A...
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Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
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The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
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During leveling, the Earth's curvature and atmospheric refraction introduce deviations in the line of sight from a true horizontal reference. When the line of sight is leveled, it remains perpendicular to the plumb line only at a single point. Beyond this, it deviates due to the Earth’s curvature, represented by the correction C. For a sight distance D, the deviation can be derived using the relationship:This relationship shows that the deviation increases quadratically with distance. Over a...
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Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

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Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
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Precipitation Titration: Overview01:26

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Precipitation titration involves the reaction of a titrant and an analyte to generate an insoluble precipitate. While precipitation titration uses various precipitating agents, silver nitrate is the most common precipitating reagent; titrations involving Ag+ are called argentometric titrations. Usually, the endpoint in a precipitation titration can be detected by visual indicators.
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Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds
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GRACE improves seasonal groundwater forecast initialization over the U.S.

Augusto Getirana1,2, Matthew Rodell1, Sujay Kumar1

  • 1Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD.

Journal of Hydrometeorology
|September 9, 2020
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Summary
This summary is machine-generated.

Integrating Gravity Recovery and Climate Experiment (GRACE) data assimilation into hydrological models improves seasonal groundwater forecasts. This enhancement aids in developing a more accurate U.S. drought monitoring and forecasting system.

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Area of Science:

  • Hydrology
  • Climate Science
  • Geophysics

Background:

  • Accurate initialization of hydrological models is crucial for effective seasonal forecasting.
  • Terrestrial Water Storage (TWS) estimates from the GRACE mission offer valuable data for improving model states.
  • Groundwater storage is a key component of the hydrological cycle and drought prediction.

Purpose of the Study:

  • To evaluate the impact of GRACE data assimilation (GRACE-DA) on seasonal hydrological forecast initialization over the U.S.
  • To assess the influence of GRACE-DA on groundwater storage forecasts.
  • To determine the effectiveness of GRACE-DA for improving drought monitoring and forecasting systems.

Main Methods:

  • Assimilating GRACE-based TWS estimates into a land surface model for the period 2003-2016.
  • Performing three-month hindcast simulations initialized with and without GRACE-DA.
  • Comparing initial hydrological condition (IHC) sets using depth-to-water-table measurements at 305 wells.

Main Results:

  • GRACE-DA-based IHC significantly improves seasonal groundwater forecast performance (RMSE and correlation).
  • Forecast improvements were observed across most regions, with notable exceptions in the High Plains.
  • Degradation in the High Plains highlights the need to simulate irrigation practices for accurate groundwater variability modeling.

Conclusions:

  • GRACE data assimilation is a valuable tool for enhancing seasonal groundwater forecasts.
  • The study underscores the importance of incorporating anthropogenic factors like irrigation into hydrological models.
  • Findings support the development of improved U.S. drought monitoring and forecasting capabilities.