Modeling of soil moisture movement and wetting behavior under point-source trickle irrigation

[1]  A. Naorem,et al.  Review of artificial intelligence and internet of things technologies in land and water management research during 1991-2021: A bibliometric analysis , 2023, Eng. Appl. Artif. Intell..

[2]  Arvind Singh Tomar,et al.  Eco-hydrological modeling of soil wetting pattern dimensions under drip irrigation systems , 2023, Heliyon.

[3]  R. Gondim,et al.  The use of numerical modelling to assess soil water dynamics in subsurface irrigation , 2023, REVISTA CIÊNCIA AGRONÔMICA.

[4]  Dinesh Kr. Vishwakarma,et al.  Forecasting of stage-discharge in a non-perennial river using machine learning with gamma test , 2023, Heliyon.

[5]  Shahab S. Band,et al.  A novel hybrid AIG-SVR model for estimating daily reference evapotranspiration , 2023, Arabian Journal of Geosciences.

[6]  Dinesh Kr. Vishwakarma,et al.  GLUE analysis of meteorological-based crop coefficient predictions to derive the explicit equation , 2023, Neural Computing and Applications.

[7]  Jingkuan Wang,et al.  Simulation of Soil Water Movement and Root Uptake under Mulched Drip Irrigation of Greenhouse Tomatoes , 2023, Water.

[8]  M. Jamei,et al.  A comprehensive investigation of wetting distribution pattern on sloping lands under drip irrigation: A new gradient boosting multi-filtering-based deep learning approach , 2023, Journal of Hydrology.

[9]  Duong Tran Anh,et al.  Performance of Machine Learning Techniques for Meteorological Drought Forecasting in the Wadi Mina Basin, Algeria , 2023, Water.

[10]  Yanwei Fan,et al.  Moisture content distribution model for the soil wetting body under moistube irrigation , 2023, Water SA.

[11]  Dinesh Kr. Vishwakarma,et al.  Prediction of meteorological drought and standardized precipitation index based on the random forest (RF), random tree (RT), and Gaussian process regression (GPR) models , 2023, Environmental Science and Pollution Research.

[12]  Rohitash Kumar,et al.  Application of Innovative Machine Learning Techniques for Long-Term Rainfall Prediction , 2023, Pure and Applied Geophysics.

[13]  Dinesh Kr. Vishwakarma,et al.  Deficit irrigation scheduling with mulching and yield prediction of guava (Psidium guajava L.) in a subtropical humid region , 2022, Frontiers in Environmental Science.

[14]  Pute Wu,et al.  Subsurface irrigation with ceramic emitters: Evaluating soil water effects under multiple precipitation scenarios , 2022, Agricultural Water Management.

[15]  Dinesh Kr. Vishwakarma,et al.  Evaluation and development of empirical models for wetted soil fronts under drip irrigation in high-density apple crop from a point source , 2022, Irrigation Science.

[16]  A. H. Elmetwalli,et al.  Effects of Irrigation Method and Water Flow Rate on Irrigation Performance, Soil Salinity, Yield, and Water Productivity of Cauliflower , 2022, Agriculture.

[17]  D. R. Sena,et al.  Evaluation of Data-driven Hybrid Machine Learning Algorithms for Modelling Daily Reference Evapotranspiration , 2022, Atmosphere-Ocean.

[18]  Dinesh Kr. Vishwakarma,et al.  Novel Genetic Algorithm (GA) based hybrid machine learning-pedotransfer Function (ML-PTF) for prediction of spatial pattern of saturated hydraulic conductivity , 2022, Engineering Applications of Computational Fluid Mechanics.

[19]  A. Sahoo,et al.  Prediction of groundwater-level using novel SVM-ALO, SVM-FOA, and SVM-FFA algorithms at Purba-Medinipur, India , 2022, Arabian Journal of Geosciences.

[20]  S. Mehan,et al.  Comparative study on morphometric analysis and RUSLE-based approaches for micro-watershed prioritization using remote sensing and GIS , 2022, Arabian Journal of Geosciences.

[21]  Dinesh Kr. Vishwakarma,et al.  Modelling daily reference evapotranspiration based on stacking hybridization of ANN with meta-heuristic algorithms under diverse agro-climatic conditions , 2022, Stochastic Environmental Research and Risk Assessment.

[22]  Dinesh Kr. Vishwakarma,et al.  Methods to estimate evapotranspiration in humid and subtropical climate conditions , 2022, Agricultural Water Management.

[23]  Xiaogang Liu,et al.  Optimizing irrigation and fertilization at various growth stages to improve mango yield, fruit quality and water-fertilizer use efficiency in xerothermic regions , 2022, Agricultural Water Management.

[24]  Zhen-wen Yu,et al.  Optimized split nitrogen fertilizer increase photosynthesis, grain yield, nitrogen use efficiency and water use efficiency under water-saving irrigation , 2020, Scientific Reports.

[25]  Sinan Q. Salih,et al.  Modeling wetted areas of moisture bulb for drip irrigation systems: An enhanced empirical model and artificial neural network , 2020, Comput. Electron. Agric..

[26]  Afaq Ahmad,et al.  Evaluating the Impacts of Pumping on Aquifer Depletion in Arid Regions Using MODFLOW, ANFIS and ANN , 2020, Water.

[27]  O. Kisi,et al.  Artificial intelligence models versus empirical equations for modeling monthly reference evapotranspiration , 2020, Environmental Science and Pollution Research.

[28]  Arpna Bajpai,et al.  Soil moisture distribution under trickle irrigation: a review , 2020 .

[29]  P. Jacoby,et al.  Direct root-zone irrigation outperforms surface drip irrigation for grape yield and crop water use efficiency while restricting root growth , 2020 .

[30]  Anurag Malik,et al.  Modeling monthly pan evaporation process over the Indian central Himalayas: application of multiple learning artificial intelligence model , 2020, Engineering Applications of Computational Fluid Mechanics.

[31]  Wei-Hong Liu,et al.  EFFECT OF A ROOT‐ZONE INJECTION IRRIGATION METHOD ON WATER PRODUCTIVITY AND APPLE PRODUCTION IN A SEMI‐ARID REGION IN NORTH‐WESTERN CHINA , 2019, Irrigation and Drainage.

[32]  Francisco Dirceu Duarte Arraes,et al.  MODELING SOIL WATER REDISTRIBUTION UNDER SURFACE DRIP IRRIGATION , 2019, Engenharia Agrícola.

[33]  Mukesh Kumar,et al.  Moisture dynamics and irrigation modelling in apple (Malus domestica) trees using CROPWAT model in temperate region of India , 2018, The Indian Journal of Agricultural Sciences.

[34]  C. Dirksen,et al.  Hydraulic Conductivity and Diffusivity: Laboratory Methods , 2018, SSSA Book Series.

[35]  A. Klute,et al.  Water Retention: Laboratory Methods , 2018, SSSA Book Series.

[36]  D. Vishwakarma,et al.  Modeling of Rainfall and Ground Water Fluctuation of Gonda District Uttar Pradesh, India , 2018 .

[37]  Mukesh Kumar,et al.  Efficient Design of Drip Irrigation System using Water and Fertilizer Application Uniformity at Different Operating Pressures in a Semi‐Arid Region of India , 2017 .

[38]  S. Jha,et al.  Root development and water uptake in winter wheat under different irrigation methods and scheduling for North China , 2017 .

[39]  M. K. Rowshon,et al.  Wetting patterns estimation under drip irrigation systems using an enhanced empirical model , 2016 .

[40]  Binyebebe Maurice,et al.  ASSESSMENT OF WETTING PATTERN AND MOISTURE DISTRIBUTION UNDER POINT SOURCE DRIP IRRIGATION IN NYAGATARE - RWANDA , 2016 .

[41]  Heeyoung Kim,et al.  A new metric of absolute percentage error for intermittent demand forecasts , 2016 .

[42]  Zayani Khemaies,et al.  An analytical approach to predict the moistened bulb volume beneath a surface point source , 2016 .

[43]  A. Wayayok,et al.  A MODIFIED EMPIRICAL MODEL FOR ESTIMATING THE WETTED ZONE DIMENSIONS UNDER DRIP IRRIGATION , 2015 .

[44]  M. K. Jat,et al.  Evaluation of root water uptake models – a review , 2015 .

[45]  Vishwamitra Oree,et al.  A hybrid method for forecasting the energy output of photovoltaic systems , 2015 .

[46]  S. H. Ahmadi,et al.  Effect of drip irrigation and fertilizer regimes on fruit yields and water productivity of a pomegranate (Punica granatum (L.) cv. Rabab) orchard , 2014 .

[47]  F. Coulon,et al.  Numerical investigation of the influence of texture, surface drip emitter discharge rate and initial soil moisture condition on wetting pattern size , 2014, Irrigation Science.

[48]  Gerard Arbat,et al.  Drip-Irriwater: Computer software to simulate soil wetting patterns under surface drip irrigation , 2013 .

[49]  Nicholas Dercas,et al.  Simulation of Soil Water Dynamics Under Surface Drip Irrigation from Equidistant Line Sources , 2013, Water Resources Management.

[50]  Rangavajhala Subbauah,et al.  Modeling for predicting soil wetting radius under point source surface trickle irrigation , 2013 .

[51]  R. Subbaiah A review of models for predicting soil water dynamics during trickle irrigation , 2013, Irrigation Science.

[52]  M. A. Skewes,et al.  Evaluation of soil plant system response to pulsed drip irrigation of an almond tree under sustained stress conditions , 2013 .

[53]  R. Troy Peters,et al.  Wetting Pattern Models for Drip Irrigation: New Empirical Model , 2011 .

[54]  Juan Li,et al.  Simulation of point source wetting pattern of subsurface drip irrigation , 2011, Irrigation Science.

[55]  M. Th. van Genuchten,et al.  Soil Water Content Distributions between Two Emitters of a Subsurface Drip Irrigation System , 2011 .

[56]  Indrajeet Chaubey,et al.  Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds , 2010 .

[57]  J. Šimůnek,et al.  Numerical simulations of water movement in a subsurface drip irrigation system under field and laboratory conditions using HYDRUS-2D , 2010 .

[58]  Maziar M. Kandelous,et al.  Comparison of numerical, analytical, and empirical models to estimate wetting patterns for surface and subsurface drip irrigation , 2010, Irrigation Science.

[59]  T. Rajput,et al.  Dynamics and modeling of soil water under subsurface drip irrigated onion , 2008 .

[60]  R. G. Evans,et al.  Methods and technologies to improve efficiency of water use , 2008 .

[61]  Giuseppe Provenzano,et al.  Using HYDRUS-2D Simulation Model to Evaluate Wetted Soil Volume in Subsurface Drip Irrigation Systems , 2007 .

[62]  N. Malamos,et al.  Estimation of Width and Depth of the Wetted Soil Volume Under a Surface Emitter, Considering Root Water-Uptake and Evaporation , 2007 .

[63]  Peter J. Thorburn,et al.  Modelling trickle irrigation: Comparison of analytical and numerical models for estimation of wetting front position with time , 2006, Environ. Model. Softw..

[64]  Gulshan Mahajan,et al.  Response of Greenhouse tomato to irrigation and fertigation , 2006 .

[65]  N. Leech,et al.  Understanding Correlation: Factors That Affect the Size of r , 2006 .

[66]  A. G. Asuero,et al.  The Correlation Coefficient: An Overview , 2006 .

[67]  M. Amin,et al.  Wetted surface radius under point-source trickle irrigation in sandy soil , 2005 .

[68]  S. Kaparthi,et al.  A Bibliometric Analysis , 2005, J. Decis. Syst..

[69]  P. H. Groenevelt,et al.  A new model for the soil‐water retention curve that solves the problem of residual water contents , 2004 .

[70]  J. Ben-Asher,et al.  Dripper Discharge Rates and the Hydraulic Properties of the Soil , 2003 .

[71]  P. Thorburn,et al.  Micro-Irrigation: Advances in system design and management - Introduction , 2003 .

[72]  Shaozhong Kang,et al.  The effects of partial rootzone drying on root, trunk sap flow and water balance in an irrigated pear (Pyrus communis L.) orchard , 2003 .

[73]  Peter J. Thorburn,et al.  WetUp: a software tool to display approximate wetting patterns from drippers , 2003, Irrigation Science.

[74]  Peter J. Thorburn,et al.  Soil-dependent wetting from trickle emitters: implications for system design and management , 2003, Irrigation Science.

[75]  D. L. Brakensiek,et al.  Estimating Soil Water Retention from Soil Properties , 1982 .

[76]  Van Genuchten,et al.  A closed-form equation for predicting the hydraulic conductivity of unsaturated soils , 1980 .

[77]  E. Bresler,et al.  Infiltration from a Trickle Source: I. Mathematical Models1 , 1971 .

[78]  LABORATORY METHODS , 1937 .

[79]  L. A. Richards Capillary conduction of liquids through porous mediums , 1931 .

[80]  Rohitash Kumar,et al.  Yield response and validation of CROPWAT for baby corn under drip irrigation , 2022, Journal of Soil and Water Conservation.

[81]  Yaohui Cai Subsurface Irrigation with Ceramic Emitters: Evaluating Soil Water Effects Under Multiple Precipitation Scenarios , 2022, SSRN Electronic Journal.

[82]  A. Elbeltagi,et al.  Artificial intelligent-based water and soil management , 2022, Deep Learning for Sustainable Agriculture.

[83]  Rohitash Kumar,et al.  Water requirement and fertigation in high density planting of apples , 2021, Indian Journal of Horticulture.

[84]  Zhenhua Wang,et al.  Adapting Root Distribution and Improving Water Use Efficiency via Drip Irrigation in a Jujube ( Zizyphus jujube Mill.) Orchard after Long-Term Flood Irrigation , 2021 .

[85]  Mukesh Kumar,et al.  Effect of drip irrigated mulch on soil properties and water use efficiency-A review , 2020 .

[86]  Mukesh Kumar,et al.  Water and nitrate dynamics in baby corn (Zea mays L.) under different fertigation frequencies and operating pressures in semi-arid region of India , 2016 .

[87]  Md Rowshon Kamal,et al.  WPEDIS – wetting pattern estimator under drip irrigation systems , 2016 .

[88]  Xin-ping Chen,et al.  Integrated Nutrient Management for Food Security and Environmental Quality in China , 2012 .

[89]  M. M. Kandolous,et al.  ESTIMATING SOIL MOISTURE PATTERN IN SUBSURFACE DRIP IRRIGATION USING DIMENSIONAL ANALYSIS METHOD , 2008 .

[90]  Yang Wei-we A Review on , 2008 .

[91]  K. Z. Ahmed,et al.  Artificial neural networks approach to estimate wetting pattern under point source trickle irrigation. , 2007 .

[92]  M. Amin,et al.  DIPAC-Drip Irrigation Water Distribution Pattern Calculator , 2005 .

[93]  M. Shukla,et al.  Principles of Soil Physics , 2004 .

[94]  Rajakrishnan Rajkumar,et al.  Grammar Engineering for CCG using Ant and XSLT ∗ , 2001 .

[95]  D. Or,et al.  Practical Applications of Drip Irrigation , 1999 .

[96]  Y. Cohen,et al.  IMPROVING AVOCADO TREE WATER STATUS UNDER SEVERE CLIMATIC CONDITIONS BY INCREASING WETTED SOIL VOLUME , 1995 .

[97]  Feike J. Leij,et al.  The RETC code for quantifying the hydraulic functions of unsaturated soils , 1992 .

[98]  A. M. Michael,et al.  Irrigation, Theory and Practice , 1978 .