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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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In argentometric precipitation titrations, endpoints can be detected visually by the Mohr, Volhard, and Fajans methods. In the Mohr method, adding a soluble chromate indicator gives an initial yellow color to the analyte solution. As the titrant is added, the first excess of silver ions forms a red silver chromate precipitate, marking the endpoint. The solution pH should be maintained at about 8 by adding solid CaCO3.
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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.
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A Place-Based Approach to Drought Forecasting in South-Central Oklahoma.

Renee A McPherson1,2, Irenea L Corporal-Lodangco1, Michael B Richman3

  • 1South Central Climate Adaptation Science Center University of Oklahoma Norman OK USA.

Earth and Space Science (Hoboken, N.J.)
|January 2, 2023
PubMed
Summary

This study develops a drought forecasting model for Oklahoma using climate indices and historical data. The model provides 18-month drought predictions, aiding water managers in drought preparedness.

Keywords:
Palmer Drought Severity Index (PDSI)drought forecastingmultivariate regression modelsouth‐central Oklahoma drought

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Area of Science:

  • Environmental Science
  • Climate Science
  • Hydrology

Background:

  • Water managers in south-central Oklahoma require reliable drought forecasts for future planning.
  • Drought preparedness is crucial for regional water resource management.

Purpose of the Study:

  • To produce reliable, place-based drought forecasts for south-central Oklahoma.
  • To provide water managers with an early warning system for drought conditions.

Main Methods:

  • Utilized multivariate regression with climate indices (Multivariate ENSO Index, Pacific Decadal Oscillation, Atlantic Multidecadal Oscillation) and Palmer Drought Severity Index (PDSI) as predictors.
  • Developed a second-order model using a training dataset from 1901-2021, employing stepwise regression and cross-validation for predictor selection.
  • Generated 1000 bootstrapped restricted models, averaging monthly predictions to forecast PDSI 18 months in advance.

Main Results:

  • The developed model demonstrates sufficient skill for early drought warning.
  • The model captures the timing of severe to exceptional drought periods, despite slight overestimation of maxima and minima.
  • The adjusted R-squared value indicates an adequately accurate predictive model with good predictive ability.

Conclusions:

  • The forecasting technique provides a valuable tool for water managers in Oklahoma.
  • The model offers reliable, long-term drought intensity predictions, enhancing drought preparedness strategies.
  • Place-based drought forecasting is essential for effective water resource management in drought-prone regions.