Applicability of Different Assimilation Algorithms in Crop Growth Model Simulation of Evapotranspiration DOI Creative Commons
Jingshu Wang, Ping Li, Rutian Bi

et al.

Agronomy, Journal Year: 2024, Volume and Issue: 14(11), P. 2674 - 2674

Published: Nov. 14, 2024

Remote sensing spatiotemporal fusion technology can provide abundant data source information for assimilating crop growth model data, enhancing monitoring, and providing theoretical support irrigation management. This study focused on the winter wheat planting area in southeastern part of Loess Plateau, a typical semi-arid region, specifically Linfen Basin. The SEBAL ESTARFM were used to obtain 8 d, 30 m evapotranspiration (ET) period wheat. Then, based ‘localization’ CERES-Wheat model, fused results incorporated into assimilation process further determine optimal method. indicate that (1) ET accurately capture spatial details (R > 0.9, p < 0.01). (2) calibrated characteristic curve effectively reflects variation throughout while being consistent with trend magnitude variation. (3) correlation between Ensemble Kalman filter (EnKF) (R2 = 0.7119, 0.01) was significantly higher than Four-Dimensional Variational (4DVar) 0.5142, particle (PF) 0.5596, guidance improve yield water use efficiency which will help promote sustainable agricultural development.

Language: Английский

Climate Change-Driven Hydrological Shifts in the Kon-Ha Thanh River Basin DOI Open Access
Cuong Manh Vu, Binh Quang Nguyen, Thanh‐Nhan‐Duc Tran

et al.

Water, Journal Year: 2024, Volume and Issue: 16(23), P. 3389 - 3389

Published: Nov. 25, 2024

Climate change is projected to bring substantial changes hydroclimatic extremes, which will affect natural river regimes and have wide-ranging impacts on human health ecosystems, particularly in Central Highland Vietnam. This study focuses understanding quantifying the of climate streamflow Kon-Ha Thanh River basin, using Soil Water Assessment Tool (SWAT) between 2016 2099. The examined across three time periods (2016–2035, 2046–2065, 2080–2029) under two scenarios, Representative Conversion Pathways (RCPs) 4.5 8.5. model was developed validated a daily scale with performance, yielding good performance scores, including Coefficient Determination (R2), Nash-Sutcliffe Efficiency (NSE), Root Mean Squared Error (RMSE) values 0.79, 0.77, 50.96 m3/s, respectively. Our findings are (1) during wet season increase by up 150%, December, RCP 8.5; (2) dry flows expected decrease over 10%, beginning May, heightening risk water shortages critical agricultural periods; (3) shifts timing flood seasons found toward 2099 that require adaptive measures for resource management. These provide scientific foundation incorporating into regional management strategies enhancing resilience local communities future challenges.

Language: Английский

Citations

11

Prediction of drought-flood prone zones in inland mountainous regions under climate change with assessment and enhancement strategies for disaster resilience in high-standard farmland DOI Creative Commons
Yongheng Shen,

Qingxia Guo,

Zhenghao Liu

et al.

Agricultural Water Management, Journal Year: 2025, Volume and Issue: 309, P. 109349 - 109349

Published: Feb. 5, 2025

Language: Английский

Citations

2

Integrating artificial intelligence and machine learning in hydrological modeling for sustainable resource management DOI

Stephanie Marshall,

Thanh‐Nhan‐Duc Tran, Mahesh R. Tapas

et al.

International Journal of River Basin Management, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 17

Published: March 27, 2025

Language: Английский

Citations

2

Climate Smart Land Management Practices for Livelihood Resilience in Ethiopia: A systematic Review DOI Creative Commons
Abrha Asefa, Mitiku Haile,

Melaku Berhe

et al.

Heliyon, Journal Year: 2025, Volume and Issue: unknown, P. e42950 - e42950

Published: Feb. 1, 2025

Language: Английский

Citations

1

Seasonal dynamics of water quality in response to land use changes in the Chi and Mun River Basins Thailand DOI Creative Commons
Kwanchai Pakoksung, Nantawoot Inseeyong,

Nattawin Chawaloesphonsiya

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 27, 2025

The Chi and Mun River Basins, the primary tributary of Mekong Basin in Thailand, is undergoing significant land use changes that impact water quality. Understanding relationship between quality crucial for effective river basin management, providing insights applicable to global systems. While past studies have examined Basin, research specifically focusing on Chi-Mun remains limited. This study analyzes spatial temporal effects from 2007 2021 using change estimation, 11 parameters, redundancy analysis (RDA). Water samples were collected January, March, May, August across multiple years. Seasonal variations assessed, with dry season January March wet May August. Key findings include: (1) pH, Biochemical Oxygen Demand, Total Coliform Bacteria, Fecal Phosphorus, Nitrate Nitrogen, Ammonia-Nitrogen, Suspended Solids increased during season, while (2) Dissolved Oxygen, Electrical Conductivity, Quality Index higher season. (3) Land had a greater driven by runoff expanding urban agricultural areas declining paddy forest cover. (4) Forests aquatic improved quality, expansion contributed its deterioration. These underscore need sustainable management strategies balance regional development ecological conservation Basin.

Language: Английский

Citations

1

Prediction of Pan Evaporation in diverse climates and scenarios using Temporal Attention Clockwork Recurrent Neural Networks coupled with Long-Short Term Memory DOI Creative Commons
Azadeh Goodarzi,

Mahdi Mohammadi Sergini,

Ali Saber

et al.

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

Published: March 1, 2025

Language: Английский

Citations

1

Long-term assessment of hydropeaking and cumulative impacts on sediment transport, grain size dynamics, channel stability and water resource management DOI
Binh Quang Nguyen, Sameh A. Kantoush, Thanh‐Nhan‐Duc Tran

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 380, P. 124983 - 124983

Published: March 16, 2025

Language: Английский

Citations

1

Evaluating combinations of rainfall datasets and optimization techniques for improved hydrological predictions using the SWAT+ model DOI
Mahesh R. Tapas, Randall Etheridge, Thanh‐Nhan‐Duc Tran

et al.

Journal of Hydrology Regional Studies, Journal Year: 2024, Volume and Issue: 57, P. 102134 - 102134

Published: Dec. 17, 2024

Language: Английский

Citations

6

Assessing long-term water storage dynamics in Afghanistan: An integrated approach using machine learning, hydrological models, and remote sensing DOI Creative Commons
Abdul Haseeb Azizi, Fazlullah Akhtar, Bernhard Tischbein

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 370, P. 122901 - 122901

Published: Oct. 21, 2024

Language: Английский

Citations

4

Soil moisture and its applications in the Mekong River Basin DOI
Son K., Thanh‐Nhan‐Duc Tran, Kyung Y. Kim

et al.

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 195 - 227

Published: Nov. 15, 2024

Language: Английский

Citations

3