Ecological footprint and carrying capacity of agricultural water-land-energy nexus in China DOI Creative Commons
Xiaolei Ma,

Hong-Kai Yuan

Ecological Indicators, Journal Year: 2024, Volume and Issue: 168, P. 112786 - 112786

Published: Nov. 1, 2024

Language: Английский

Impact of Climate Change on Regional Water Availability and Demand for Agricultural Production: Application of Water Footprint Concept DOI

T. R. Sreeshna,

P. Athira,

B. Soundharajan

et al.

Water Resources Management, Journal Year: 2024, Volume and Issue: 38(10), P. 3785 - 3817

Published: April 17, 2024

Language: Английский

Citations

5
Patterns of blue and green water in the Yellow River Basin from 1998 to 2020: Influence of climate change and human activity DOI

Dongxue Yu,

Qiuan Zhu,

Jiang Zhang

et al.

Journal of Hydrology Regional Studies, Journal Year: 2025, Volume and Issue: 59, P. 102367 - 102367

Published: April 11, 2025

Language: Английский

Citations

0
Comparison and Prediction of the Ecological Footprint of Water Resources—Taking Guizhou Province as an Example DOI Creative Commons
Yongtao Wang,

Wenfeng Yang,

Jian Liu

et al.

Hydrology, Journal Year: 2025, Volume and Issue: 12(5), P. 99 - 99

Published: April 22, 2025

Water resources are considered to be of paramount importance the natural world on a global scale, being critical for sustenance ecosystems, support life, and achievement sustainable development. However, these under threat from climate change, population growth, urbanization pollution. This necessitates development robust effective assessment methods ensure their use. Although assessing ecological footprint (EF) urban water systems plays role in advancing cities managing assets, existing research has largely overlooked application geospatial visualization techniques evaluating resource allocation strategies within karst mountain watersheds, an oversight this study aims correct through innovative methodological integration. establishes evaluation framework predicting availability Guizhou synergistic three methodologies: (1) water-based accounting (WEF), (2) ecosystem service thresholds defined by carrying capacity (WECC) thresholds, (3) composite sustainability metrics, all correlated with contemporary hydrological utilization profiles. Spatiotemporal patterns were quantified across province’s nine administrative divisions during 2013–2022 period time-series analysis, subsequent WEF projections 2023–2027 generated via Long Short-Term Memory (LSTM) temporal forecasting techniques.

Language: Английский

Citations

0
Analysis of coupling coordination structural characteristics of water-energy-food-ecosystems based on SNA model: A case study in the nine provinces along the Yellow River, China DOI
Zhang Lin,

Xiaohui Jiang,

Yuehong Li

et al.

Physics and Chemistry of the Earth Parts A/B/C, Journal Year: 2024, Volume and Issue: 135, P. 103654 - 103654

Published: June 5, 2024

Language: Английский

Citations

3
Modeling and Evaluating the Socio-Economic–Flood Safety–Ecological System of Landong Floodplain Using System Dynamics and the Weighted Coupling Coordination Degree Model DOI Open Access
Ming Li, Chaojie Niu, Xiang Li

et al.

Water, Journal Year: 2024, Volume and Issue: 16(17), P. 2366 - 2366

Published: Aug. 23, 2024

The lower course of the Yellow River is a “hanging river” across hinterland China, and safety its flood control measures/systems closely tied to stability nation. Ensuring high-quality, sustainable development floodplain while maintaining crucial for entire Basin. Previous studies have primarily focused on overall Basin or economic–ecological coupling cities along river, often neglecting floodplain. This study optimizes socio-economic–flood-safety–ecological (SFE) system typical downstream Landong within dynamics model (SDM) can simulate dynamic behavior SFE systems by constructing mathematical models that incorporate feedback loops time delays. primary components include causal loop modules stock-flow modules. Then, coordination degree established using comprehensive subjective objective weighting method, assessing system’s under five scenarios: inertial development, economic environmental protection, safety, development. results historical validity tests indicate SDM effectively system. suggest increases most scenario, indicating should not only focus socio-economic growth, but also consider ecological concerns. In addition, regulation from socio-economic, environment indicators are necessary achieve coordinated has significant implications policy formulation management high-quality in River.

Language: Английский

Citations

3
The Measure of Scarcity of Blue and Green Water and Its Driving Factors via the SWAT Model: An Application to the Upper Qingjiang River, China DOI
Min An, Xu Wei, Xue Fang

et al.

Irrigation and Drainage, Journal Year: 2025, Volume and Issue: unknown

Published: April 4, 2025

ABSTRACT Blue and green water is vital for the economy life. Water scarcity occurs when resource supply insufficient to support human, ecological economic activities within a certain time space. The index quantifies regional blue–green shortages providing new perspective evaluating usage. Moreover, analysing driving factors of changes can offer reliable reference exploring their causes. Taking Qingjiang River as an example, this study first used SWAT model simulate upper River's monthly streamflow. Then, management levels were mapped township scale via GIS calculate scarcities. Finally, geo‐detector detected impacts natural socio‐economic on water. results show that (1) has good simulation accurately describes cycle process in River. (2) From 2010 2022, blue indices stable, whereas increased but then decreased. (3) force interaction stronger than single‐factor effect This examines conditions basin, offering insights township‐scale management.

Language: Английский

Citations

0
Modelling water scarcity and water footprint of agricultural crops: A case from a semi-arid region in Morocco DOI
Oumaima Attar, Marianna Leone, Anna Maria De Girolamo

et al.

Journal of Hydrology Regional Studies, Journal Year: 2025, Volume and Issue: 59, P. 102455 - 102455

Published: May 10, 2025

Language: Английский

Citations

0
Forecasting Blue and Green Water Footprint of Wheat Based on Single, Hybrid, and Stacking Ensemble Machine Learning Algorithms Under Diverse Agro-Climatic Conditions in Nile Delta, Egypt DOI Creative Commons

A Lotfy,

Mohamed E. Abuarab, Eslam Farg

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(22), P. 4224 - 4224

Published: Nov. 13, 2024

The aim of this research is to develop and compare single, hybrid, stacking ensemble machine learning models under spatial temporal climate variations in the Nile Delta regarding estimation blue green water footprint (BWFP GWFP) for wheat. Thus, four single (XGB, RF, LASSO, CatBoost) eight hybrid (XGB-RF, XGB-LASSO, XGB-CatBoost, RF-LASSO, CatBoost-LASSO, CatBoost-RF, XGB-RF-LASSO, XGB-CatBoost-LASSO) were used, along with ensembles, five scenarios including crop parameters remote sensing-based indices. highest R2 value predicting wheat BWFP was achieved XGB-LASSO scenario 4 at 100%, while minimum 0.16 LASSO 3 (remote sensing indices). To predict GWFP, 100% RF-LASSO across 1 (all parameters), 2 (climate (Peeff, Tmax, Tmin, SA), 5 (Peeff Tmax). lowest recorded 3. use individual showed high efficiency wheat, ratings according statistical performance standards. However, programs, whether binary or triple, outperformed both ensemble.

Language: Английский

Citations

0
Ecological footprint and carrying capacity of agricultural water-land-energy nexus in China DOI Creative Commons
Xiaolei Ma,

Hong-Kai Yuan

Ecological Indicators, Journal Year: 2024, Volume and Issue: 168, P. 112786 - 112786

Published: Nov. 1, 2024

Language: Английский

Citations

0