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関連する概念動画

Adaptations that Reduce Water Loss01:57

Adaptations that Reduce Water Loss

26.6K
Though evaporation from plant leaves drives transpiration, it also results in loss of water. Because water is critical for photosynthetic reactions and other cellular processes, evolutionary pressures on plants in different environments have driven the acquisition of adaptations that reduce water loss.
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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...
131
Design Example: Creating a Hydraulic Model of a Dam Spillway01:21

Design Example: Creating a Hydraulic Model of a Dam Spillway

365
Scaled hydraulic models of dam spillways provide a practical way to replicate and study the intricate flow dynamics of these structures. Often built to a 1:15 ratio, these models allow for observing critical water behavior, such as velocity distribution, flow patterns, and energy dissipation.
365
Conservation of Declining Populations02:07

Conservation of Declining Populations

9.8K
Conservation of declining population focuses on ways of detecting, diagnosing, and halting a population decline. The approach uses methods to prevent populations from going extinct.
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Conservation of Small Populations02:04

Conservation of Small Populations

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Small population sizes put a species at extreme risk of extinction due to a lack of variation, and a consequent decrease in adaptability. This weakens the chances of survival under pressures such as climate change, competition from other species, or new diseases. Large populations are more likely to survive pressures such as these, as such populations are more likely to harbor individuals that have genetic variants that are adaptive under new stresses. Small populations are much less...
13.8K
Regulation of Water Output01:26

Regulation of Water Output

1.2K
The human body predominantly expels water through the urinary system. On average, an individual generates around 1.5 liters of urine each day. This amount can fluctuate based on how well a person is hydrated, but a critical minimum quantity of urine must be produced to ensure the body's proper functioning. Daily, the kidneys remove 600 to 1200 milliosmoles of dissolved substances, effectively excreting excess minerals and water-soluble toxins such as creatinine, urea, and uric acid from the...
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Updated: Oct 3, 2025

Author Spotlight: Developing Cost-Effective and Customizable Balloon Tags for Fish Passage Studies
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アマゾンのダムを自然に最適化

Gordon W Holtgrieve1, Mauricio E Arias2

  • 1School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA, USA.

Science (New York, N.Y.)
|February 17, 2022
PubMed
まとめ
この要約は機械生成です。

アルゴリズムは潜在的利益や 逃した利益や 環境への影響を評価します この研究は,複雑なシナリオにおける情報に基づいた意思決定のための枠組みを提供します.

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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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Watershed Planning within a Quantitative Scenario Analysis Framework
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関連する実験動画

Last Updated: Oct 3, 2025

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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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Watershed Planning within a Quantitative Scenario Analysis Framework
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科学分野:

  • 環境科学
  • コンピュータ科学
  • 意思決定科学

背景:

  • 複数の目標を持つ複雑な決定を 評価することは困難です
  • 環境のトレードオフを理解することは 持続可能な開発に不可欠です

研究 の 目的:

  • 機会,利益の喪失,環境のトレードオフの評価のためのアルゴリズムを開発し,適用する.
  • 競合する利益のシナリオにおける意思決定のための定量的な枠組みを提供すること.

主な方法:

  • 意思決定結果のアルゴリズムによる評価
  • 利益と環境への影響の定量化
  • 逃した機会の分析

主要な成果:

  • アルゴリズムによって 重要な機会を特定し 失われた利益を定量化することができました
  • 環境へのトレードオフは体系的に評価された.
  • このフレームワークは複雑な意思決定シナリオにおいて有用であることが示されました.

結論:

  • アルゴリズムのアプローチは 多面的な決定を評価するための 堅固な方法を提供します
  • この研究は,トレードオフを明確にすることで,より情報に基づいた持続可能な選択を容易にする.