On the public citation graph
Analysis of parameter uncertainty in model simulations of irrigated and rainfed agroecosystems
0 signed · 113 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/2014ms000311openalex-snapshot
Dependency of parameter values of a crop model on the spatial scale of simulation
inferredcites →https://doi.org/10.1002/9781118033197openalex-snapshot
Bayesian Inference in Statistical Analysis
inferredcites →https://doi.org/10.1002/9781119054450.ch37openalex-snapshot
Plant growth under drought stress
inferredcites →https://doi.org/10.1002/hyp.3360060305openalex-snapshot
The future of distributed models: Model calibration and uncertainty prediction
inferredcites →https://doi.org/10.1002/hyp.6294openalex-snapshot
Towards dynamic catchment modelling: a Bayesian hierarchical mixtures of experts framework
inferredcites →https://doi.org/10.1007/978-94-010-0987-4openalex-snapshot
Assessment and Management of Environmental Risks
inferredcites →https://doi.org/10.1007/s00477-008-0274-yopenalex-snapshot
Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in hydrologic modeling?
inferredcites →https://doi.org/10.1007/s10584-011-0305-4openalex-snapshot
Effect of climate change on field crop production in California’s Central Valley
inferredcites →https://doi.org/10.1007/s10705-014-9622-0openalex-snapshot
Assessing the sensitivity of modelled estimates of N2O emissions and yield to input uncertainty at a UK cropland experimental site using the DailyDayCent model
inferredcites →https://doi.org/10.1016/j.agrformet.2005.05.003openalex-snapshot
Annual carbon dioxide exchange in irrigated and rainfed maize-based agroecosystems
inferredcites →https://doi.org/10.1016/j.agrformet.2008.04.002openalex-snapshot
Potential predictability of crop yield using an ensemble climate forecast by a regional circulation model
inferredcites →https://doi.org/10.1016/j.agrformet.2008.09.010openalex-snapshot
Evapotranspiration of irrigated and rainfed maize–soybean cropping systems
inferredcites →https://doi.org/10.1016/j.agrformet.2010.09.007openalex-snapshot
The simulation of phenological development in dynamic crop model: The Bayesian comparison of different methods
inferredcites →https://doi.org/10.1016/j.agrformet.2011.06.017openalex-snapshot
A Bayesian framework for model calibration, comparison and analysis: Application to four models for the biogeochemistry of a Norway spruce forest
inferredcites →https://doi.org/10.1016/j.agsy.2014.12.003openalex-snapshot
Parameter and uncertainty estimation for maize, peanut and cotton using the SALUS crop model
inferredcites →https://doi.org/10.1016/j.agwat.2006.06.016openalex-snapshot
Determining crop-water production functions using yield–irrigation gradient algorithms
inferredcites →https://doi.org/10.1016/j.agwat.2014.09.002openalex-snapshot
Developing and normalizing average corn crop water production functions across years and locations using a system model
inferredcites →https://doi.org/10.1016/j.ecolmodel.2007.06.028openalex-snapshot
Simulation of global crop production with the ecosystem model DayCent
inferredcites →https://doi.org/10.1016/j.ecolmodel.2012.01.024openalex-snapshot
Global sensitivity and uncertainty analysis of a dynamic agroecosystem model under different irrigation treatments
inferredcites →https://doi.org/10.1016/j.ecolmodel.2014.02.013openalex-snapshot
Multisite-multivariable sensitivity analysis of distributed watershed models: Enhancing the perceptions from computationally frugal methods
inferredcites →https://doi.org/10.1016/j.eja.2011.08.003openalex-snapshot
Combining the simulation crop model AquaCrop with an economic model for the optimization of irrigation management at farm level
inferredcites →https://doi.org/10.1016/j.eja.2016.02.001openalex-snapshot
Performance and sensitivity of the DSSAT crop growth model in simulating maize yield under conservation agriculture
inferredcites →https://doi.org/10.1016/j.envsoft.2009.09.012openalex-snapshot
Global sensitivity analysis measures the quality of parameter estimation: The case of soil parameters and a crop model
inferredcites →https://doi.org/10.1016/j.envsoft.2013.10.022openalex-snapshot
Parameter identification of the STICS crop model, using an accelerated formal MCMC approach
inferredcites →https://doi.org/10.1016/j.envsoft.2014.12.011openalex-snapshot
Understanding the DayCent model: Calibration, sensitivity, and identifiability through inverse modeling
inferredcites →https://doi.org/10.1016/j.envsoft.2015.08.013openalex-snapshot
Markov chain Monte Carlo simulation using the DREAM software package: Theory, concepts, and MATLAB implementation
inferredcites →https://doi.org/10.1016/j.envsoft.2016.04.009openalex-snapshot
Uncertainty in crop model predictions: What is the role of users?
inferredcites →https://doi.org/10.1016/j.fcr.2018.01.029openalex-snapshot
Responses of soybean to water stress and supplemental irrigation in upper Indo-Gangetic plain: Field experiment and modeling approach
inferredcites →https://doi.org/10.1016/j.geoderma.2011.11.009openalex-snapshot
A review on parameterization and uncertainty in modeling greenhouse gas emissions from soil
inferredcites →https://doi.org/10.1016/j.jhydrol.2009.10.025openalex-snapshot
Parameter optimization and uncertainty analysis for plot-scale continuous modeling of runoff using a formal Bayesian approach
inferredcites →https://doi.org/10.1016/j.jhydrol.2015.12.045openalex-snapshot
Uncertainty and sensitivity assessments of an agricultural–hydrological model (RZWQM2) using the GLUE method
inferredcites →https://doi.org/10.1016/s0921-8181(98)00040-xopenalex-snapshot
DAYCENT and its land surface submodel: description and testing
inferredcites →https://doi.org/10.1021/cr040659dopenalex-snapshot
Sensitivity Analysis for Chemical Models
inferredcites →https://doi.org/10.1029/2005wr004745openalex-snapshot
An integrated hydrologic Bayesian multimodel combination framework: Confronting input, parameter, and model structural uncertainty in hydrologic prediction
inferredcites →https://doi.org/10.1029/2007wr006720openalex-snapshot
Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation
inferredcites →https://doi.org/10.1029/2008wr006822openalex-snapshot
Appraisal of the generalized likelihood uncertainty estimation (GLUE) method
inferredcites →https://doi.org/10.1029/2009gb003544openalex-snapshot
Estimating uncertainty in N2O emissions from U.S. cropland soils
inferredcites →https://doi.org/10.1061/(asce)0733-9437(1990)116:3(399)openalex-snapshot
Deficit Irrigation. I: Analytical Framework
inferredcites →https://doi.org/10.1079/9781845939700.0000openalex-snapshot
Modeling physiology of crop development, growth and yield
inferredcites →https://doi.org/10.1080/00401706.1999.10485594openalex-snapshot
A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output
inferredcites →https://doi.org/10.1080/01431168508948283openalex-snapshot
Canopy reflectance, photosynthesis and transpiration
inferredcites →https://doi.org/10.1080/01904167.2013.868480openalex-snapshot
DOES NITROGEN FERTILIZATION ENHANCE DROUGHT TOLERANCE IN SUNFLOWER? A REVIEW
inferredcites →https://doi.org/10.1080/01904167.2018.1549676openalex-snapshot
Effect of nitrogen rates on drip irrigated maize grown under deficit irrigation
inferredcites →https://doi.org/10.1088/1748-9326/aa7287openalex-snapshot
Declining agricultural production in rapidly urbanizing semi-arid regions: policy tradeoffs and sustainability indicators
inferredcites →https://doi.org/10.1093/jxb/erl165openalex-snapshot
Deficit irrigation for reducing agricultural water use
inferredcites →https://doi.org/10.1111/insr.12243openalex-snapshot
Bayesian Model Averaging: A Systematic Review and Conceptual Classification
inferredcites →https://doi.org/10.1111/j.2517-6161.1964.tb00553.xopenalex-snapshot
An Analysis of Transformations
inferredcites →https://doi.org/10.1126/science.289.5477.284openalex-snapshot
Global Water Resources: Vulnerability from Climate Change and Population Growth
inferredcites →https://doi.org/10.1214/ss/1177011136openalex-snapshot
Inference from Iterative Simulation Using Multiple Sequences
inferredcites →https://doi.org/10.13031/2013.18515openalex-snapshot
SENSITIVITY AND UNCERTAINTY ANALYSES OF CROP YIELDS AND SOIL ORGANIC CARBON SIMULATED WITH EPIC
inferredcites →https://doi.org/10.13031/2013.24082openalex-snapshot
Use of Global Sensitivity Analysis for CROPGRO Cotton Model Development
inferredcites →https://doi.org/10.13031/2013.29218openalex-snapshot
Applying GLUE for Estimating CERES-Maize Genetic and Soil Parameters for Sweet Corn Production
inferredcites →https://doi.org/10.13031/2013.35820openalex-snapshot
Water Production Functions for Central Plains Crops
inferredcites →https://doi.org/10.13031/trans.13044openalex-snapshot
Sensitivity of Predicted Agro-Ecosystem Variables to Errors in Weather Input Data
inferredcites →https://doi.org/10.1515/ijnsns.2009.10.3.273openalex-snapshot
Accelerating Markov Chain Monte Carlo Simulation by Differential Evolution with Self-Adaptive Randomized Subspace Sampling
inferredcites →https://doi.org/10.1623/hysj.50.1.45.56334openalex-snapshot
Assessing uncertainties in a conceptual water balance model using Bayesian methodology / Estimation bayésienne des incertitudes au sein d’une modélisation conceptuelle de bilan hydrologique
inferredcites →https://doi.org/10.1890/09-0772.1openalex-snapshot
Simulating greenhouse gas budgets of four California cropping systems under conventional and alternative management
inferredcites →https://doi.org/10.2134/agronj2008.0206xopenalex-snapshot
Effects of Estimating Soil Hydraulic Properties and Root Growth Factor on Soil Water Balance and Crop Production
inferredcites →https://doi.org/10.2134/agronj2011.0349openalex-snapshot
Uncertainty Analysis and Parameter Estimation for the CSM‐CROPGRO‐Cotton Model
inferredcites →https://doi.org/10.2134/agronj2017.06.0328openalex-snapshot
Improved Crop Canopy and Water Balance Dynamics for Agroecosystem Modeling Using DayCent
inferredcites →https://doi.org/10.2134/agronj2017.10.0585openalex-snapshot
Modeling Deficit Irrigation of Maize with the DayCent Model
inferredcites →https://doi.org/10.2134/agronmonogr59openalex-snapshot
Precision Conservation: Geospatial Techniques for Agricultural and Natural Resources Conservation
inferredcites →https://doi.org/10.2134/agronmonogr59.c16openalex-snapshot
Field‐ and farm‐scale assessment of soil greenhouse gas mitigation using COMET‐Farm
inferredcites →https://doi.org/10.2134/jeq2005.0160openalex-snapshot
DAYCENT National‐Scale Simulations of Nitrous Oxide Emissions from Cropped Soils in the United States
inferredcites →https://doi.org/10.2134/jeq2007.0292openalex-snapshot
Testing DAYCENT Model Simulations of Corn Yields and Nitrous Oxide Emissions in Irrigated Tillage Systems in Colorado
inferredcites →https://doi.org/10.2134/jeq2007.0614openalex-snapshot
Comparison of DAYCENT‐Simulated and Measured Nitrous Oxide Emissions from a Corn Field
inferredcites →https://doi.org/10.2134/jeq2012.0486openalex-snapshot
Simulation of Nitrous Oxide Emissions and Estimation of Global Warming Potential in Turfgrass Systems Using the DAYCENT Model
inferredcites →https://doi.org/10.2136/sssaj1986.03615995005000040039xopenalex-snapshot
Estimating Generalized Soil‐water Characteristics from Texture
inferredcites →https://doi.org/10.2136/sssaj1987.03615995005100050015xopenalex-snapshot
Analysis of Factors Controlling Soil Organic Matter Levels in Great Plains Grasslands
inferredcites →https://doi.org/10.2136/sssaj2012.0354openalex-snapshot
Using DayCENT to Simulate Carbon Dynamics in Conventional and No‐Till Agriculture
inferredcites →https://doi.org/10.2307/2266156openalex-snapshot
Modeling Biological Systems: Principles and Applications.
inferredcites →https://doi.org/10.2307/2285412openalex-snapshot
Bayesian Inference in Statistical Analysis.
inferredcites →https://doi.org/10.25675/3.019818openalex-snapshot
Simulating canopy dynamics, productivity and water balance of annual crops from field to regional scales
inferredcites →https://doi.org/10.3133/cir1344openalex-snapshot
Estimated use of water in the United States in 2005
inferredcites →https://doi.org/10.3133/sir20145218openalex-snapshot
Water-level changes and change in water in storage in the High Plains aquifer, predevelopment to 2013 and 2011-13
inferredcites →https://doi.org/10.3390/agronomy9020109openalex-snapshot
Optimizing the Sowing Date and Irrigation Strategy to Improve Maize Yield by Using CERES (Crop Estimation through Resource and Environment Synthesis)-Maize Model
inferredcites →https://doi.org/10.5194/hess-15-3701-2011openalex-snapshot
DREAM (D) : an adaptive Markov Chain Monte Carlo simulation algorithm to solve discrete, noncontinuous, and combinatorial posterior parameter estimation problems
inferredcites →https://doi.org/10.5860/choice.34-2738openalex-snapshot
Modeling biological systems: principles and applications
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4649855openalex-extracted
A Dream-Based Inverse Model for Continuous Release Source Identification in River Pollution Incidents: Quantitative Evaluation and Sensitivity Analysis
inferred← citeshttps://doi.org/10.1007/978-3-030-50436-6_54openalex-snapshot
Sensitivity Analysis of Soil Parameters in Crop Model Supported with High-Throughput Computing
inferred← citeshttps://doi.org/10.1016/j.agsy.2024.104243openalex-snapshot
Enhancing simulations of biomass and nitrous oxide emissions in vineyard, orchard, and vegetable cropping systems
inferred← citeshttps://doi.org/10.1016/j.agwat.2023.108225openalex-snapshot
Generalized water production relations through process-based modeling: A viticulture example
inferred← citeshttps://doi.org/10.1016/j.agwat.2023.108653openalex-snapshot
Dynamics of soil water and nitrate within the vadose zone simulated by the WHCNS model calibrated based on deep learning
inferred← citeshttps://doi.org/10.1016/j.agwat.2025.109462openalex-snapshot
Evaluation of best management practices for controlling water pollution in an arid irrigation district
inferred← citeshttps://doi.org/10.1016/j.ecolmodel.2025.111116openalex-snapshot
Improving process-based modeling of crop production in the DayCent ecosystem model with solar-induced chlorophyll fluorescence
inferred← citeshttps://doi.org/10.1016/j.eja.2021.126371openalex-snapshot
Global sensitivity and uncertainty analysis of a sugarcane model considering the trash blanket effect
inferred← citeshttps://doi.org/10.1016/j.eja.2021.126429openalex-snapshot
Bayesian calibration and uncertainty analysis of an agroecosystem model under different N management practices
inferred← citeshttps://doi.org/10.1016/j.eja.2022.126668openalex-snapshot
Simulations of nitrous oxide emissions and global warming potential in a C4 turfgrass system using process-based models
inferred← citeshttps://doi.org/10.1016/j.envpol.2024.123448openalex-snapshot
A DiffeRential Evolution Adaptive Metropolis (DREAM)-based inverse model for continuous release source identification in river pollution incidents: Quantitative evaluation and sensitivity analysis
inferred← citeshttps://doi.org/10.1016/j.envsoft.2021.105130openalex-snapshot
Evaluating crop-soil-water dynamics in waterlogged areas using a coupled groundwater-agronomic model
inferred← citeshttps://doi.org/10.1016/j.fcr.2025.109754openalex-snapshot
Key genotype and soil parameters for sugarcane growth: A sensitivity analysis of the SAMUCA model in Brazilian agroecosystems
inferred← citeshttps://doi.org/10.1016/j.fcr.2025.110197openalex-snapshot
Controlled-release nitrogen in paddies: Bridging food security and carbon neutrality through carbon-nitrogen coupling
inferred← citeshttps://doi.org/10.1016/j.geoderma.2023.116647openalex-snapshot
Validating DayCent-CR for cropland soil carbon offset reporting at a national scale
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2020.125336openalex-snapshot
Agricultural water optimization coupling with a distributed ecohydrological model in a mountain-plain basin
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2021.126304openalex-snapshot
Evaluating nitrate and phosphorus remediation in intensively irrigated stream-aquifer systems using a coupled flow and reactive transport model
inferred← citeshttps://doi.org/10.1017/s0021859624000030openalex-snapshot
Sample size, range of parameters and time-dependent effects on global sensitivity analysis in sugarcane modelling
inferred← citeshttps://doi.org/10.1029/2020jg005750openalex-snapshot
DayCent Model Predictions of NPP and Grain Yields for Agricultural Lands in the Contiguous U.S.
inferred← citeshttps://doi.org/10.1038/s41598-021-99371-0openalex-snapshot
Uncertainty analysis of model inputs in riverine water temperature simulations
inferred← citeshttps://doi.org/10.1080/01904167.2023.2280142openalex-snapshot
Variance-based global sensitivity analysis and uncertainty quantification of the AquaCrop model parameters for basil ( Ocimum basilicum L.) under different nitrogen fertilizer rates
inferred← citeshttps://doi.org/10.11606/t.11.2023.tde-13042023-082447openalex-snapshot
Sensitivity and uncertainty analysis of SAMUCA crop model across contrasting environments in Brazil
inferred← citeshttps://doi.org/10.3390/agronomy12112793openalex-snapshot
Uncertainty Analysis of HYDRUS-1D Model to Simulate Soil Salinity Dynamics under Saline Irrigation Water Conditions Using Markov Chain Monte Carlo Algorithm
inferred← citeshttps://doi.org/10.3390/hydrology9050091openalex-snapshot
Assessing the Impact of Artificial Recharge Ponds on Hydrological Fluxes in an Irrigated Stream–Aquifer System
inferred← citeshttps://doi.org/10.3390/ijerph20054567openalex-snapshot
Application of Parameter Optimization Methods Based on Kalman Formula to the Soil—Crop System Model
inferred← citeshttps://doi.org/10.3390/w13030318openalex-snapshot
Hydrologic Analysis of an Intensively Irrigated Area in Southern Peru Using a Crop-Field Scale Framework
inferred← citeshttps://doi.org/10.3390/w15061250openalex-snapshot
Uncertainty Assessment of WinSRFR Furrow Irrigation Simulation Model Using the GLUE Framework under Variability in Geometry Cross Section, Infiltration, and Roughness Parameters
inferred← citeshttps://doi.org/10.4148/2378-5977.8321openalex-snapshot
Simulation of Nitrous Oxide Emissions in Zoysia Turfgrass Using DAYCENT and DNDC Ecosystem Models
inferred← citeshttps://doi.org/10.5194/bg-18-3147-2021openalex-snapshot
Simulating measurable ecosystem carbon and nitrogen dynamics with the mechanistically defined MEMS 2.0 model
inferred← citeshttps://doi.org/10.5194/bg-23-2079-2026openalex-snapshot
Interpreting carbon-water trade-offs in Daisy crop model using Pareto-based calibration
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.