Environmental flow assessment
Flow records and hydraulic models are linked to the habitat needs of fish, vegetation and wetlands to define the flow regime that sustains them.
GCRI · Biodiversity Nexus
Hydrology connects biodiversity to water: flow regimes shape freshwater habitats, wetlands store and release water, and catchment condition affects the quantity and quality of water reaching people. It quantifies the water services ecosystems provide and the flows ecosystems themselves need.
Hydrology studies the movement, distribution and quality of water across the land surface, subsurface and atmosphere. It underpins the assessment of floods, droughts and water supply, which affect food, energy, health and infrastructure together. In biodiversity and nature, climate and hazards and oceans and coasts, hydrological estimates set design standards for dams, levees and drainage and inform water allocation between competing users. They link climate hazards to downstream effects on power generation, crops and public health. The canonical description is on STEM Commons.
Flow records and hydraulic models are linked to the habitat needs of fish, vegetation and wetlands to define the flow regime that sustains them.
Rainfall-runoff and routing models are run with and without floodplain storage or forest cover to estimate how ecosystems change flood peaks downstream.
Sediment and nutrient models trace how land cover and erosion upstream affect water quality at intakes, reservoirs and coastal habitats.
Flood water, rain and root-zone soil moisture over the Amazon Basin, from NASA GIBS. Each layer carries its own date.
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最新の利用可能データ
NASA GIBS / EOSDIS · ASTER GDEM(METI、NASA)· Blue Marble(NASA)· © OpenStreetMap 貢献者(ODbL)· Natural Earth
最新のNASA画像を読み込んでいます。
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Water now, framed on the Amazon Basin.NASA が公開するままの衛星およびモデルのプロダクトで、それぞれに固有の日付があります。指標であり、特定の場所の評価ではありません。
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Datasets and records used by hydrology and water science on this platform, with the role each plays and the label its values carry. Sources are listed in 出典の登録簿.
| データ | 役割 | ラベル |
|---|---|---|
| Stream gauge records | Flow regime and calibration | 観測 |
| JRC Global Surface Water | Wetland and floodplain inundation | 観測 |
| HydroSHEDS river networks | Catchment delineation and connectivity | モデル化 |
| Water quality monitoring | Nutrient and sediment loads | 観測 |
この手法を追跡するためにチームが使う画面:その指標、状態、決定。名前は例であり、値はイメージです。
Biodiversity · Hydrology for ecosystems · Run R-6654
held-out period
| T+2 | 0.21 | 0.14 | 0.22 | Skilful |
| T+4 | 0.21 | 0.19 | 0.38 | Skilful |
| T+6 | 0.36 | 0.25 | 0.19 | Skilful |
| T+8 | 0.20 | 0.20 | 0.18 | Skilful |
Models are calibrated on one period of observed flows and tested on an independent period or neighbouring catchment. Skill scores and comparison with surveyed flood extents are used to judge performance.
| 確認 | 実施方法 |
|---|---|
| Split-sample calibration | Models are fitted on one period and tested on another, with test-period skill reported |
| Ecological response validation | Flow-ecology relationships are checked against field surveys of the species or habitats they claim to support |
| Paired scenario runs | With-and-without ecosystem runs use the same forcing so that differences can be attributed |
Assumptions of stationarity weaken as climate and land use change. Ungauged basins, karst aquifers and rapid urbanisation are poorly represented by parameters fitted elsewhere.
Rain becomes runoff by the curve number method, drains each sub-catchment through a linear reservoir and travels down the main stem by Muskingum routing; play it to watch the flood wave move and flatten. Teaching model with stated illustrative values, not a prediction. The map on this page shows The Amazon Basin; the model itself is not tied to a place.
管理策
読み取り値
| Hour | Outlet (m³/s) | Unrouted (m³/s) | Upper reach (m³/s) |
|---|---|---|---|
| 2.4 | 0.0 | 678.9 | 0.0 |
| 12.0 | 308.3 | 1,151.4 | 181.8 |
| 21.6 | 452.4 | 35.1 | 73.7 |
| 31.2 | 363.3 | 1.1 | 11.1 |
| 40.8 | 198.8 | 0.0 | 1.5 |
| 50.4 | 79.3 | 0.0 | 0.2 |
| 60.0 | 25.4 | 0.0 | 0.0 |
| 69.6 | 6.9 | 0.0 | 0.0 |
| 79.2 | 1.7 | 0.0 | 0.0 |
| 88.8 | 0.4 | 0.0 | 0.0 |
| 98.4 | 0.1 | 0.0 | 0.0 |
| 108.0 | 0.0 | 0.0 | 0.0 |
| 117.6 | 0.0 | 0.0 | 0.0 |
| 127.2 | 0.0 | 0.0 | 0.0 |
| 136.8 | 0.0 | 0.0 | 0.0 |
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
6 本の柱を通じて、Nexus Consortium が主導
Assembled from the Nexus Standards area profile 生物多様性・自然リスクの標準: the hazards it names, the システム and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
ハザード
システムと連成
管理策
NS-0 憲章と原則NS-1 社会を動かし続ける UNI と成果物カタログ(文法 v0.2:分野、部門、地域、環境の区分)NS-3 リスク記録の UNI(文法、旧体系との対照、割当権限)NS-3b データセットとプロダクトのメタデータ・プロファイル(STAC、DCAT、PROV-O)NS-5 図表・地図・可視化の標準(UI/UX キットと併用)NS-9 文脈 UNI(展開、インスタンス、プログラム・インスタンス)NS-11 検証とモニタリング(エビデンス、証明、ゼロトラストの適合性観測)NRS-N5 生物多様性と自然のリスクとレジリエンスNRS-H65 ハザード・ファミリー:プラネタリー・バウンダリーの逸脱(NHS-1 planet.boundary)NRS-H27 ハザードファミリー:生物多様性と種へのストレス(NHS-1 eco.species)NRS-H26 ハザード・ファミリー:土地と湿地の劣化(NHS-1 eco.land)NRS-H28 ハザード分類:気候状態の移行(NHS-1 eco.climate-state)NRS-H64 ハザード・ファミリー:生態系のレジーム・シフト(NHS-1 eco.regime-shift)観測
例示の地理
Water Nexus stewards hydrology and water science for the Consortium and reviews how it is applied across platforms.
The sectors hydrology for ecosystems touches and how strongly they depend on each other: what a study has to observe and model together.
署名
Water and Biodiversity
Water gives biodiversity environmental flows (0.6): the strongest relations between the sectors this subject joins.
W · E · I · F · H · B
モデル、その仮定、データ、不確実性を、科学者やエンジニアが確認する形で示します。構造は公表された手法に従っています。描かれた値は例示であり、知見ではありません。
How a satellite or sensor record becomes evidence on hydrology for ecosystems, and where each step adds uncertainty.
報告書 is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
個人データ、重要インフラの機微な詳細、共有する権利のないものは決して送らないでください。寄稿は利用前にレビューされます。送付によって著作者としての権利や編集上の権利が生じることはなく、スポンサーシップで調査結果を買うことは決してできません。
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