Soil moisture profile estimation under bare and vegetated soils using combined L-band and P-band radiometer observations: An incoherent modeling approach DOI Creative Commons
Foad Brakhasi, Jeffrey P. Walker, Jasmeet Judge

и другие.

Remote Sensing of Environment, Год журнала: 2024, Номер 307, С. 114148 - 114148

Опубликована: Апрель 11, 2024

Effective water management in agriculture requires a comprehensive understanding of the distribution content throughout soil profile to root zone. This knowledge empowers farmers and managers make informed decisions regarding irrigation timing quantity for optimizing crop growth. To estimate moisture profile, this study utilized combined L- P-band radiometry with four incoherent radiative transfer models, including three multi-layer models based on zero-order (IZ), first order (IF) solution (IS) approximation, uniform model (UM) model, as well stratified coherent Njoku (NM). The impact vegetation was considered through conventional tau-omega model. Linear (Li) second-order polynomial (Pn2) functions were used represent shape profile. Observations from tower-based experiment under various land cover conditions, bare, bare-weed, grass, wheat corn, used. mean square error (RMSE) calculated between observed estimated profiles. results revealed comparable RMSE values all five Pn2 function outperforming Li estimating deeper layers. Regardless employed utilizing employing yielded RMSEs 0.03 m3/m3, 0.08 0.1 m3/m3 over depths 0–5 cm, 0–30 0–60 respectively. A comparison indicated that latter slightly outperformed former dry bare exhibiting 0.003 lower at surface while nearly equal performance bottom Furthermore, provided only better than UM especially shallow layers, average entire being 0.002 lower. Consequently, complexity is not justified small gain performance. depth which reasonable ranged 1 cm (under wet corn) 39 bare), depended gradient These important findings pave way global scale using future satellite missions.

Язык: Английский

Evaluating Wheat Pre‐Harvest Sprouting Risk Using Indicator Based on Meteorological Data From 1981 to 2020 in China DOI Open Access

Yu Hu,

Y. F. Sang, Meiling Li

и другие.

Journal of Agronomy and Crop Science, Год журнала: 2025, Номер 211(2)

Опубликована: Март 1, 2025

ABSTRACT The occurrence of wheat pre‐harvest sprouting (PHS) has been intensified with global climatic change and increasing rainfall from 1981 to 2020, which led a drastic reduction in quality yield. Therefore, scientific assessments the potential risk PHS different areas based on historical meteorological data help identify high‐risk areas, select suitable cultivars optimise cultivation measures for production. However, date, assessment criteria have not established evaluating risks associated areas. This study analysed temperature relative humidity trends identified boundary line between Yellow Huai River Valley Facultative Wheat Zone Middle Lower Yangtze Winter using climatically similar points. experimental material comprised PHS‐sensitive variety Xiaoyan 22. were proposed whole ear germination test daily collected during harvest period 2020 two regions. was graded these Our results showed that increased by 0.38°C/10 years 0.26°C/10 years, while decreased 1.8%/10 0.39%/10 Further analysis factors influencing climate revealed that, 1986 eastern section exhibited significant southward or northward migration Anhui Jiangsu Provinces. central Henan Hubei Provinces also trend but relatively small range, whereas western fluctuated up down original dividing line, Gansu Province. A new indicator, P, this China. During period, north south west east Zone. Furthermore, overall lower than Risk distribution damage will provide basis accurate sprouting‐resistant varieties improve resistance natural disasters safety

Язык: Английский

Процитировано

0
Interannual and seasonal relationships between photosynthesis and summer soil moisture in the Ili River basin, Xinjiang, 2000–2018 DOI
Yu Tao,

Guli Jiapaer,

Gang Long

и другие.

The Science of The Total Environment, Год журнала: 2022, Номер 856, С. 159191 - 159191

Опубликована: Окт. 1, 2022

Язык: Английский

Процитировано

16
Climate overtakes vegetation greening in regulating spatiotemporal patterns of soil moisture in arid Central Asia in recent 35 years DOI Creative Commons
Nigenare Amantai, Yuanyuan Meng, Jingzhe Wang

и другие.

GIScience & Remote Sensing, Год журнала: 2023, Номер 61(1)

Опубликована: Дек. 6, 2023

Satellite datasets have revealed significant greening and soil drying in arid Central Asia. However, the influence mechanism of vegetation climate on moisture dynamics is still unclear. In this study, we investigated spatiotemporal consistency changes, examined controlling factors under different indices (normalized differential index, NDVI; leaf area LAI), explored time lag accumulation effects Asia period 1985 to 2020. The results showed that co-occurrence 30.4% (NDVI) 19.4% (LAI) study spatially. Temporally, increased from 1989, but decreased 1989 or 1990 contrast, activity continuously during 1985–2020. Precipitation accounted for most variance moisture. greenness demonstrated positive correlations with moisture, representing 20.7% (for NDVI) 39.3% LAI) vegetated areas (areas long-term mean NDVI ≥ 0.1 LAI > 0), while negative were observed only 5.4% 3.3% areas, respectively. Soil exhibited varying response indices, precipitation, temperature. main temporal temperature simultaneous changes no precipitation included 1-month their Considering inconsistencies patterns between as well dominance variations, concluded climate, especially rather than greening, regulates These findings provide a scientific basis restoration regional water resource management drylands.

Язык: Английский

Процитировано

9
Spatial patterns of toxic elements in stream sediment transportation at a hilly mine area DOI
Jie Cao, Zhaohui Guo

The Science of The Total Environment, Год журнала: 2024, Номер 948, С. 174597 - 174597

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

3
Soil moisture profile estimation under bare and vegetated soils using combined L-band and P-band radiometer observations: An incoherent modeling approach DOI Creative Commons
Foad Brakhasi, Jeffrey P. Walker, Jasmeet Judge

и другие.

Remote Sensing of Environment, Год журнала: 2024, Номер 307, С. 114148 - 114148

Опубликована: Апрель 11, 2024

Effective water management in agriculture requires a comprehensive understanding of the distribution content throughout soil profile to root zone. This knowledge empowers farmers and managers make informed decisions regarding irrigation timing quantity for optimizing crop growth. To estimate moisture profile, this study utilized combined L- P-band radiometry with four incoherent radiative transfer models, including three multi-layer models based on zero-order (IZ), first order (IF) solution (IS) approximation, uniform model (UM) model, as well stratified coherent Njoku (NM). The impact vegetation was considered through conventional tau-omega model. Linear (Li) second-order polynomial (Pn2) functions were used represent shape profile. Observations from tower-based experiment under various land cover conditions, bare, bare-weed, grass, wheat corn, used. mean square error (RMSE) calculated between observed estimated profiles. results revealed comparable RMSE values all five Pn2 function outperforming Li estimating deeper layers. Regardless employed utilizing employing yielded RMSEs 0.03 m3/m3, 0.08 0.1 m3/m3 over depths 0–5 cm, 0–30 0–60 respectively. A comparison indicated that latter slightly outperformed former dry bare exhibiting 0.003 lower at surface while nearly equal performance bottom Furthermore, provided only better than UM especially shallow layers, average entire being 0.002 lower. Consequently, complexity is not justified small gain performance. depth which reasonable ranged 1 cm (under wet corn) 39 bare), depended gradient These important findings pave way global scale using future satellite missions.

Язык: Английский

Процитировано

2