A5103170646- Climate change impacts on agriculture
- Soil Carbon and Nitrogen Dynamics
- Agricultural Economics and Policy
- Crop Yield and Soil Fertility
- Plant Water Relations and Carbon Dynamics
- Hydrology and Watershed Management Studies
- Soil and Water Nutrient Dynamics
- Rice Cultivation and Yield Improvement
- Irrigation Practices and Water Management
- Soil erosion and sediment transport
- Greenhouse Technology and Climate Control
- Plant responses to elevated CO2
- Water resources management and optimization
- Sustainable Agricultural Systems Analysis
- Climate variability and models
- Peatlands and Wetlands Ecology
- Soil and Unsaturated Flow
- Bioenergy crop production and management
- Agriculture Sustainability and Environmental Impact
- Horticultural and Viticultural Research
- Soil Geostatistics and Mapping
- Forest Management and Policy
- Urban Planning and Valuation
- Land Use and Ecosystem Services
- Agronomic Practices and Intercropping Systems
Grassland, Soil and Water Research Laboratory
2017-2024
University of Sassari
2013-2023
Texas A&M University
2018-2022
Mitchell Institute
2022
Texas A&M University System
2016-2020
Northern Prairie Wildlife Research Center
2020
Agricultural Research Service
2020
United States Geological Survey
2020
Southeast Watershed Research Laboratory
2020
Forestry Research Centre
2017
We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use data of low resolution. Therefore, are often generated via averaging sampling area majority. This may bias scales, varying largely across models. Thus, we evaluated for 14 Yields winter wheat silage maize were under production conditions. calculated this from spatial...
Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security climate change mitigation, within multi-species contexts. We report an international comparison benchmarking exercise, showing potential multi-model ensembles nitrous oxide (N2 O) emissions wheat, maize, rice temperate grasslands. Using a...
CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout JournalEditorsSpecials 65:53-69 (2015) - DOI: https://doi.org/10.3354/cr01326 Contribution Special: 'Modelling climate change impacts for food security' Variability of effects spatial data aggregation on regional yield simulation by crop models H. Hoffmann1,*, G. Zhao1; L. J. van Bussel1,2, A. Enders1, X. Specka3, C. Sosa4, Yeluripati5, 16, F. Tao6,...
CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout JournalEditorsSpecials 65:141-157 (2015) - DOI: https://doi.org/10.3354/cr01301 Contribution Special: 'Modelling climate change impacts for food security' Effect of weather data aggregation on regional crop simulation different crops, production conditions, and response variables Gang Zhao1,*, Holger Hoffmann1, Lenny G. J. van Bussel1,2, Andreas...
Process-based cropping systems models (CSMs) are key components of measurement, monitoring, reporting, and verification (MMRV) frameworks carbon markets, but their application suffers from model-specific differences that keep any one model working well across all combinations soils, climates, crops, agronomic practices at varying scales. Multi-model ensemble (MME), successfully used to quantify soil, management climate impact on crop productivity, provide an opportunity better estimate...
The traditional agriculture production system in sub-Saharan Africa (SSA) caused significant soil erosion and degradation of quality. In addition, dependability rainfall for irrigation needs limits the crop production. Advanced agricultural practices are thus needed at local level to sustain livelihood smallholder farmers region. this study, conservation (CA) practice with drip technology was compared (using field experiments watershed modeling) conventional tillage (CT) its potential...