Wenzhi Zeng

ORCID: 0000-0003-0667-3604
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About
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Research Areas
  • 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
  • Rice Cultivation and Yield Improvement
  • Plant responses to water stress
  • Soil Geostatistics and Mapping
  • Crop Yield and Soil Fertility
  • Smart Agriculture and AI
  • Spectroscopy and Chemometric Analyses
  • Sunflower and Safflower Cultivation
  • Groundwater flow and contamination studies
  • Solar Radiation and Photovoltaics
  • Climate change impacts on agriculture
  • Greenhouse Technology and Climate Control
  • Plant Micronutrient Interactions and Effects
  • Water resources management and optimization
  • Environmental and Agricultural Sciences
  • Flood Risk Assessment and Management
  • Essential Oils and Antimicrobial Activity

Hohai University
2016-2025

Guangzhou University of Chinese Medicine
2025

Chengdu University of Traditional Chinese Medicine
1992-2025

Zhejiang Sci-Tech University
2025

China Medical University
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

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...

10.1038/s41598-022-06249-w article EN cc-by Scientific Reports 2022-02-25

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...

10.1016/j.compag.2019.105115 article EN cc-by Computers and Electronics in Agriculture 2019-11-28

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,...

10.1002/wat2.1364 article EN Wiley Interdisciplinary Reviews Water 2019-06-19

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...

10.3390/w13030256 article EN Water 2021-01-21

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...

10.1155/2019/9575782 article EN cc-by Advances in Meteorology 2019-10-17

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)...

10.3390/biology10111114 article EN cc-by Biology 2021-10-29

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...

10.1016/j.eti.2023.103033 article EN cc-by Environmental Technology & Innovation 2023-01-20

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...

10.1016/j.agwat.2024.108679 article EN cc-by Agricultural Water Management 2024-01-21

The application of plant growth-promoting rhizosphere (PGPR) and Gamma-polyglutamic acid (γ-PGA) has a potential role in improving tolerance under abiotic stress, while their combined effects remain largely unexplored. This study aimed to evaluate the joint PGPR γ-PGA on maize growth microbial communities salt stress. A pot experiment consisting two strain treatments (CK, M10), (γ0, γ1) (S1, S2) was performed for this purpose. results showed that S1 treatment, M10 could increase height, leaf...

10.1016/j.agwat.2024.108736 article EN cc-by Agricultural Water Management 2024-02-28

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...

10.1186/s12302-024-00981-y article EN cc-by-nc-nd Environmental Sciences Europe 2024-09-02

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...

10.1002/2017wr021884 article EN Water Resources Research 2018-02-16

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 &gt; 0.748)...

10.3390/rs8010042 article EN cc-by Remote Sensing 2016-01-07
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