Models & Datasets
ET & Irrigation Decision Support
PT-SS coefficients: A global dataset of PT coefficients to improve reference evapotranspiration estimation in hydrologic and crop models: Su, Q. (2023), “Global-scale monthly Priestley-Taylor (PT) coefficients for reference evapotranspiration (ETo) estimation”, Mendeley Data, V1. ➡️[Download]
Seasonal weather forecast tool: An algorithm to improve the seasonal weather forecasts for regional crop modeling and irrigation management using the North American Multi-Model Ensemble (NMME).
Illustration of global scale monthly Priestley-Taylor coefficients for ETo estimation
Crop Responses to climate stressors
Rice heat stress dataset: A dataset of difference rice varieties in responses to daytime and nighttime temperature increase. ➡️[Download]
WEEF Nexus Models
SyDWEM-Texas model: A GIS-based Decision Support System for decision makers and stakeholders in Texas to evaluate the impacts of climate change, socioeconomic development, and irrigation management on water resources at local scales. ➡️[ref.]
CGE-SyDWEM model: An integrated economic-hydrologic-water quality model to support water and energy planners to evaluate the carbon mitigation strategies on macroeconomic, welfare, and water use and water-related pollutant discharges at watershed scales. ➡️[ref.]
Few tools exist to aid decision-making regarding the management of water, food, and energy resources at the watershed level. CGE-SyDWEM is developed to capture the cross-sector interactions and feedback among economic, energy, and water systems, which can help policymakers identify the possible co-benefits or trade-offs across different systems and design effective policies and measures.
Figure below illustrates the conceptual integration of the CGE and SyDWEM models. The IMED|CGE (Integrated Model of Energy, Environment and Economy for Sustainable Development | Computable General Equilibrium) model includes a production block; a market block with domestic, government, and household income and expenditure blocks; and international transactions. The CGE model can simulate GHG emissions from energy use, macroeconomic impacts (e.g., GDP, government expenditure, welfare, import, and export), detailed industrial outputs, and carbon intensity for each sector under carbon mitigation strategies.The System Dynamics and Water Environmental Model (SyDWEM) is used to simulate socio-economic subsystems, water infrastructures, and receiving water systems at the sub-watershed level. It includes five modules: (1) Population/GRP (Gross Regional Product, i.e., GDP for regional analysis) module; (2) Water demand/pollutant generation module; (3) Water supply module; (4) Sewer and WWTPs module; and (5) Receiving water module. More details of each module can be found in Su et al. (2018), Su et al. (2019) and Su et al. (2023).
Conceptual integration of the CGE and SyDWEM models (Su et al., 2023)
Machine Learning in Precision Agriculture
GBiDC-PEST: a mobile app that incorporates an improved, lightweight detection algorithm based on the you only look once (YOLO) series single-stage architecture, for real-time detection of four tiny pests (wheat mites, sugarcane aphids, wheat aphids, and rice planthoppers). ➡️[Download]
YOLO-Tpest app: a mobile application for real-time multiclass pest detection. ➡️[Download]
SCAs-SSV2-YOLO algorithm: a lightweight deep learning model for detection of sugarcane aphids in unstructured natural environments. ➡️[Download]