During this monitoring period, only winter crops like wheat and rapeseed were in the field, mostly in the north of the region, including parts of Hubei, Henan, Anhui and Jiangsu provinces. Limited winter crops were planted in Fujian, the southern Jiangxi and Hunan provinces.

According to the CropWatch agro-climatic indicators, the accumulated precipitation and temperature were 30% and 0.9℃ higher than the 15-year averages, respectively. The photosynthetically active radiation was below average (RADPAR -6%) because of increased number of rainy days. The above-average precipitation and temperature resulted in an increase of biomass potential production by 10%, as compared to the 15YA.

As shown in the NDVI development graph, crop conditions were slightly below the 5-year average. However, due to the abundant rainfall in April, the crop growth rate accelerated, and by the end of April and the beginning of May, the crop growth exceeded the best conditions of the past 5 years. The northern part of this region, including Jiangsu, Anhui, Henan, Hubei, and northern Zhejiang, accounts for approximately 50.2% of the total cultivated land in the region, the crop condition was close to the average level from January to February, and the low temperature from February to March led to a slowdown in crop growth, and subsequent improvements in agro-climatic conditions had restored the crop growth to above the average level. The potential biomass departure indicates that the agro-climatic conditions were generally above average. The potential biomass in the northern part of this region was higher than 10%. The average VCIx of this region was 0.90, and most of the area had VCIx values ranging from 0.8 to 1. The current value of the crop production index(CPI) is 1.04, which is higher than the same period last year and the 5-year average.

In general, the crop conditions in the Lower Yangtze region were slightly above average.

Figure 4.8 Crop condition China Lower Yangtze region, January 2024 – April 2024

(a) Crop condition development graph based on NDVI                                (b) Spatial NDVI patterns compared to 5YA                  (c) NDVI profiles

(d)Time series rainfall profile                                                                                                    (e)Time series temperature profile

(f) Maximum VCI                                                                        (g) Biomass departure                                                                            (h) CPI time series chart