A5061220632- Soil and Unsaturated Flow
- Soil Moisture and Remote Sensing
- Irrigation Practices and Water Management
- Plant Water Relations and Carbon Dynamics
- Hydrology and Watershed Management Studies
- Remote Sensing in Agriculture
- Soil Carbon and Nitrogen Dynamics
- Hydrological Forecasting Using AI
- Plant nutrient uptake and metabolism
- Crop Yield and Soil Fertility
- Plant responses to water stress
- Soil Geostatistics and Mapping
- Rice Cultivation and Yield Improvement
- Sunflower and Safflower Cultivation
- Groundwater flow and contamination studies
- Solar Radiation and Photovoltaics
- Climate change impacts on agriculture
- Flood Risk Assessment and Management
- Greenhouse Technology and Climate Control
- Plant Micronutrient Interactions and Effects
- Smart Agriculture and AI
- Water resources management and optimization
- Essential Oils and Antimicrobial Activity
- Spectroscopy and Chemometric Analyses
- Agronomic Practices and Intercropping Systems
Hohai University
2016-2025
Guangzhou University of Chinese Medicine
2025
Chengdu University of Traditional Chinese Medicine
1992-2025
Wuhan University
2015-2024
State Key Laboratory of Water Resources and Hydropower Engineering Science
2016-2022
Fujian Agriculture and Forestry University
2020-2022
China Institute of Water Resources and Hydropower Research
2019-2021
University of Bonn
2016-2018
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering
2016-2017
University of Arizona
2016
Crop yield forecasting depends on many interactive factors, including crop genotype, weather, soil, and management practices. This study analyzes the performance of machine learning deep methods for winter wheat prediction using an extensive dataset phenology variables in 271 counties across Germany from 1999 to 2019. We proposed a Convolutional Neural Network (CNN) model, which uses 1-dimensional convolution operation capture time dependencies environmental variables. used eight supervised...
Accurate estimation of pan evaporation (Ep) is great significance to the development agricultural irrigation systems and water resources management. The purpose this study was explore applicability coupling extreme learning machine (ELM) model with two new meta-heuristic algorithms, i.e. whale optimization algorithm (WOA) flower pollination (FPA) for monthly Ep prediction. To achieve goal, hybrid models WOAELM FPAELM were developed predicting in Poyang Lake Basin Southern China as a case...
Abstract Modeling variably saturated flow in the vadose zone is of vital importance to many scientific fields and engineering applications. Richardson–Richards equation (RRE, which conventionally known as Richards' equation) often chosen physically represent fluxes when accurate characterization soil water dynamics required. Being a highly nonlinear partial differential equation, RRE solved numerically. Although there are mature software codes available for simulating by solving RRE,...
Accurate estimation of pan evaporation (Ep) is vital for the development water resources and agricultural management, especially in arid semi-arid regions where it restricted to set up facilities measure accurately consistently. Besides, using estimating models coefficient (kp) a classic method assess reference evapotranspiration (ET0) which indispensable crop growth, irrigation scheduling, economic assessment. This study estimated potential novel hybrid machine learning model Coupling Bat...
Accurate estimation of reference evapotranspiration (ETo) is key to agricultural irrigation scheduling and water resources management in arid semiarid areas. This study evaluates the capability coupling a Bat algorithm with XGBoost method (i.e., BAXGB model) for estimating monthly ETo regions China. Meteorological data from three stations (Datong, Yinchuan, Taiyuan) during 1991–2015 were used build model, multivariate adaptive regression splines (MARS), gaussian process (GPR) model. Six...
To investigate the diversity and structure of soil bacterial fungal communities in saline soils, samples with three increasing salinity levels (S1, S2 S3) were collected from a maize field Yanqi, Xinjiang Province, China. The results showed that K+, Na+, Ca2+ Mg2+ values bulk higher than those rhizosphere soil, significant differences S3 (p < 0.05). enzyme activities alkaline phosphatase (ALP), invertase, urease catalase (CAT) lower rhizosphere. Principal coordinate analysis (PCoA)...
Heavy metals in farmlands represent a severe concern for food security. Particularly with the ongoing increase its release to environment. In this regard, intercropping is natural way remediate polluted soil via enhancing phytoremediation efficacy of heavy metals. Besides, biochar amendments were also found be an effective strategy removal from soils. Thus, present study aimed compare and reducing potential risk Cd both Corchorus olitorius Zea mays alkaline The results showed that amendment...
The implementation of current drip irrigation scheduling, which only considers crop water demands (referred to as empirical irrigation) during the growth period and uncontrolled leaching fallow periods, exacerbates issues soil salinization scarcity in Xinjiang region. In pursuit more scientifically effective methods, this study employed H2DSWAP model coupled by HYDRUS-2D a Soil–Water–Atmosphere–Plant (SWAP) for scenario experiments. Results showed that prolonged without drainage (winter-free...
Groundwater is a primary source of drinking water for billions worldwide. It plays crucial role in irrigation, domestic, and industrial uses, significantly contributes to drought resilience various regions. However, excessive groundwater discharge has left many areas vulnerable potable shortages. Therefore, assessing potential zones (GWPZ) essential implementing sustainable management practices ensure the availability present future generations. This study aims delineate with high Bankura...
This research examines the simultaneous retrieval of surface soil moisture and salt concentrations using hyperspectral reflectance data in an arid environment. We conducted laboratory outdoor field experiments which we examined three key variables: moisture, texture (silty loam, clay silty clay). The content models for multiple textures (M_SMC models) were based on selected located around 1460, 1900 2010 nm resulted R2 values higher than 0.933. Meanwhile, also accurately (R2 > 0.748)...
Abstract Hydraulic tomography (HT) is a recently developed technology for characterizing high‐resolution, site‐specific heterogeneity using hydraulic data ( n d ) from series of cross‐hole pumping tests. To properly account the subsurface and to flexibly incorporate additional information, geostatistical inverse models, which permit large number spatially correlated unknowns y ), are frequently used interpret collected data. However, memory storage requirements covariance × in these models...