Project

Green development of vegetable production in Yangtze basin

This PhD project focuses on vegetable production in Yangtze basin, which contributes largely to the national economic development. A green developmental pathway of vegetable production is urgently needed for sustainable yield increase and clean water. This research aims to develop improved vegetable crop models that will be coupled to basin level water pollution models as a combined quantitative tool to better evaluate the present and future contribution to water pollution from the vegetable system in Yangtze River basin.

Introduction

Vegetable production (e.g., pepper, Chinese cabbage) in the Yangtze basin is one of the largest in China. However, the excessive use of synthetic fertilizer of vegetable production in Yangtze River basin (YRB) has caused serious environmental cost such as eutrophication and harmful algae blooms.

Objective

The aim of this project is to evaluate innovative fertilizer strategies to improve nutrient use efficiency in the vegetable system of Yangtze River basin now and under future climate change.

Method

  • Field trails implementation
  • Model parameterization, calibration, validation, and sensitivity analysis
  • Multi model coupling and upscaling
  • Scenario analysis with future climate change

(Expected) results

  • Develop two vegetable versions (chili pepper & Chinese cabbage) of WOFOST for the most popular grown vegetables in YRB to realistically estimate their potential yield and nutrient uptake status.
  • Use the coupled WOFOST and MARINA models to quantify the environmental cost of soil nutrient leaching and riverine nutrient export from vegetable production system in YRB.
  • Explore alternative fertilizer strategies under future climate change that can safeguard yield and reduce pollution in YRB.

Publications

Ruoling Tang, Iwan Supit, Ronald Hutjes, Fen Zhang, Xiaozhong Wang, Xuanjing Chen, Fusuo Zhang, Xinping Chen, 2023. Modelling growth of chili pepper (Capsicum annuum L.) with the WOFOST model. Agricultural Systems. https://doi.org/10.1016/j.agsy.2023.103688.