Quantifying the changes in solute transport caused by human influence on river connectivity in inland river basins

CATENA, Journal Year: 2024, Volume and Issue: 246, P. 108360 - 108360

Published: Sept. 9, 2024

Language: Английский

---

Convolutional Neural Networks Facilitate River Barrier Detection and Evidence Severe Habitat Fragmentation in the Mekong River Biodiversity Hotspot

Water Resources Research, Journal Year: 2024, Volume and Issue: 60(1)

Published: Jan. 1, 2024

Abstract Construction of river infrastructure, such as dams and weirs, is a global issue for ecosystem protection due to the fragmentation habitat hydrological alteration it causes. Accurate barrier databases, increasingly used determine ecologically sensitive management, are challenging generate. This especially so in large, poorly mapped basins where only large tend be recorded. The Mekong one world's most biodiverse but, like many rivers, impacts on from infrastructure documented. To demonstrate solution this, enable more basin we generated whole‐basin database Mekong, by training Convolutional Neural Network (CNN)–based object detection models, best which was identify 10,561 previously unrecorded barriers. Combining manual revision merged with existing database, our new Basin contains 13,054 Existing databases Lower documented under ∼3% barriers recorded CNN combined checking. Nam Chi/Nam Mun region, eastern Thailand, fragmented area within basin, median [95% CI] density 15.53 [0.00–49.30] per 100 km, Catchment Area‐based Fragmentation Index value, calculated an upstream direction, 1,178.67 [0.00–6,418.46], construction sluice gates. CNN‐based framework effective potentially can transform ability across facilitate ecologically‐sensitive management.

Language: Английский

---

Bending the curve of global freshwater biodiversity loss: what are the prospects?

Biological reviews/Biological reviews of the Cambridge Philosophical Society, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 2, 2024

ABSTRACT Freshwater biodiversity conservation has received substantial attention in the scientific literature and is finally being recognized policy frameworks such as Global Biodiversity Framework its associated targets for 2030. This important progress. Nonetheless, freshwater species continue to be confronted with high levels of imperilment widespread ecosystem degradation. An Emergency Recovery Plan (ERP) proposed 2020 comprises six measures intended “bend curve” loss, if they are widely adopted adequately supported. We review evidence suggesting that combined intensity persistent emerging threats become so serious current projected efforts preserve, protect restore inland‐water ecosystems may insufficient avert losses coming decades. In particular, climate change, complex harmful impacts, will frustrate attempts prevent from already affected by multiple threats. Interactions among these limit recovery populations exacerbate declines resulting local or even global extinctions, especially low‐viability degraded fragmented ecosystems. addition impediments represented we identify several other areas where absolute scarcity fresh water, inadequate information predictive capacity, a failure mitigate anthropogenic stressors, liable set limits on biodiversity. Implementation ERP rapidly at scale through many dispersed actions focused regions intense threat, together an intensification ex‐situ efforts, necessary preserve native during increasingly uncertain climatic future which poorly understood, emergent interacting have more influential. But implementation must accompanied improve energy food security humans – without further compromising condition Unfortunately, political policies arrest environmental challenges change do not inspire confidence about possible success ERP. parts world, Anthropocene seems certain include extended periods uncontaminated surface runoff inevitably appropriated humans. Unless there step‐change societal awareness commitment biodiversity, established methods protecting bend curve enough continued degradation loss.

Language: Английский

---

Towards a comprehensive river barrier mapping solution to support environmental management

Nature Water, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 13, 2025

Language: Английский

---

Strategic restoration-development mitigates tradeoffs between hydropower and fish habitat fragmentation in the Mekong

One Earth, Journal Year: 2024, Volume and Issue: 7(6), P. 1096 - 1107

Published: June 1, 2024

Hydropower can play an important role in decarbonizing energy systems, but opportunities for future low-impact hydropower are limited by existing dams, which driving declines freshwater fish worldwide. How to mitigate past development impacts while enabling expansion remains unclear. Here, we propose a strategic restoration-development paradigm break unfavorable lock-ins from development. For the Lower Mekong River, demonstrate how multi-objective optimization and habitat fragmentation modeling 710 species be used design policies. Our results show that combination of removing high-impact fishways retrofitting, planning locked-in environmental restore connectivity level achievable had been adopted before onset deployment. This highlights essential restoration with sustainable

Language: Английский

---

Enhanced River Connectivity Assessment Across Larger Areas Through Deep Learning With Dam Detection

Hydrological Processes, Journal Year: 2025, Volume and Issue: 39(1)

Published: Jan. 1, 2025

ABSTRACT Monitoring river connectivity across large regions is essential for understanding hydrological processes and environmental management. However, comprehensive assessments of are often hindered by inaccurate dam databases, which biased towards larger dams while overlooking smaller or low‐head dams. To enhance the accuracy assessments, we developed three advanced convolutional neural networks (CNNs; YOLOv5, Advance‐You Only Look Once [YOLO], Faster R‐CNN) to accurately classify evaluate using high‐resolution (1 m) remote sensing imagery. The evaluation results showed that Advance‐YOLO performs best with an average mean precision (mAP) 86.6%, R‐CNN mediocrely mAP 77.9%. Applying well‐trained model in Tarim River Basin (China), one largest inland basins around globe, found there currently 135 total on its sources. Conversely, existing public database underestimates 85.9% Notably, a 14.3% decline over past decade, current density four source rivers 1.12 per 10 000 km 2 . overestimated 83.9%. here enhances assessment areas long period, thereby fostering more research effective water resource

Language: Английский

---

An annotated satellite imagery dataset for automated river barrier object detection

Scientific Data, Journal Year: 2025, Volume and Issue: 12(1)

Published: Feb. 10, 2025

Language: Английский

---

Widespread and strong impacts of river fragmentation by human barriers on fishes in the Mekong River Basin

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: March 5, 2025

The Mekong River, a global freshwater biodiversity hotspot, has suffered from intensive barrier construction, resulting in major challenges safeguarding its fauna. Here, we provide comprehensive evaluation of the impacts river barriers on distribution 1,032 fish species Basin. Our analysis revealed that 93% suffer habitat fragmentation, and with larger range requirements experienced higher fragmentation impacts. Sub-basins along main channel Lower had high values richness but relatively Across all migration types, potamodromous worst status (Fragmentation Index, 42.56 [95% CI, 36.95–46.05]), followed by catadromous fish. Among IUCN conservation categories, Critically Endangered highest index (33.34 [12.53–46.40]). small dams sluice gates contribute more to than large dams.

Language: Английский

---

Intelligent remote sensing canal system detection and irrigation water use estimation: A case study in the transboundary Mekong River Basin

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 133110 - 133110

Published: March 1, 2025

Language: Английский

---

Revealing distribution patterns of river obstructions in China via deep-learning and satellite imagery

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 133299 - 133299

Published: April 1, 2025

Language: Английский

---