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Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

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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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Precipitation Gravimetry01:03

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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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Climate refers to the prevailing weather conditions in a specific area over an extended period. As the saying goes, “Climate is what you expect. Weather is what you get.” Climate is influenced by geographic factors, such as latitude, terrain, and proximity to bodies of water.
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Types of Coprecipitation01:10

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Coprecipitation is the contamination of a precipitate by otherwise soluble species and occurs via different processes. In colloidal precipitates, coprecipitation occurs via surface adsorption. For instance, barium sulfate has a primary layer of adsorbed barium ions and a secondary layer of nitrate counterions. This results in contamination of the precipitate by barium nitrate.
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Precipitation of Ions03:11

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Predicting Precipitation
The equation that describes the equilibrium between solid calcium carbonate and its solvated ions is:
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Watershed Planning within a Quantitative Scenario Analysis Framework
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Rainfall prediction using multiple inclusive models and large climate indices.

Sedigheh Mohamadi1, Zohreh Sheikh Khozani2, Mohammad Ehteram3

  • 1Department of Ecology, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran.

Environmental Science and Pollution Research International
|July 5, 2022
PubMed
Summary

This study improved rainfall prediction in Iran using optimized neural networks and ensemble models. Hybrid models significantly reduced errors, enhancing water resource management and meteorological forecasting.

Keywords:
Large climate indicesRainfall predictionSoft computing modelsUncertainty analysis

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Area of Science:

  • Hydrology and Water Resources
  • Artificial Intelligence in Environmental Science
  • Climate Science

Background:

  • Accurate rainfall prediction is crucial for effective water resource management.
  • Traditional prediction models often struggle with complex climate dynamics and uncertainty.
  • Optimizing artificial intelligence models and employing ensemble techniques can improve prediction accuracy.

Purpose of the Study:

  • To predict monthly rainfall in Iran's Sefidrood basin using advanced computational models.
  • To evaluate the performance of optimized artificial neural networks (ANNs) and ensemble methods.
  • To introduce novel hybrid models and input selection techniques for enhanced rainfall forecasting.

Main Methods:

  • Utilized radial basis function neural networks (RBFNN) and multilayer perceptron (MLP) networks.
  • Trained models using optimization algorithms: naked mole rat (NMR), firefly algorithm (FFA), genetic algorithm (GA), and particle swarm optimization (PSO).
  • Developed inclusive multiple models (IMM) and a hybrid gamma test (GT) for input selection and model enhancement.

Main Results:

  • Inclusive multiple models (IMM-MLP, IMM-RBFNN, SAM) outperformed standalone ANNs and their optimized versions.
  • The IMM-MLP model demonstrated significant reductions in root mean square error (RMSE) compared to other models.
  • Ensemble models provided narrower uncertainty bounds than standalone models, indicating increased robustness.

Conclusions:

  • The proposed ensemble models are robust and effective tools for predicting hydrological variables like rainfall.
  • Hybrid and ensemble approaches significantly improve rainfall prediction accuracy over standalone models.
  • These methods offer potential for forecasting other meteorological parameters and improving water resource management.