Reference evapotranspiration (ET₀) is an important factor for agricultural activity and water management. Its estimation methods have significant regional differences. The Penman–Monteith (P‐M) method, which is recommended by the Food and Agriculture Organization (FAO), has been widely accepted, but it requires a large amount of data. This study analysed the performance of 12 ET₀ estimation methods in different sub‐regions and periods by comparing them with the FAO P‐M method. Northeastern China was divided into eight sub‐regions according to their terrains and climates. Meteorological data obtained from 126 stations in these sub‐regions between the 1950s and 2014 were used to calculate the ET₀ values. The performances were identified via four indices: root mean squared error, mean absolute error, average ratio and Spearman's correlation co‐efficient. The optimal method for agricultural areas was then modified by using linear regression analysis. The results are as follows: the Valiantzas2, Romanenko2 and H‐Makkink methods are recommended as alternative methods during the crop‐growing period, whereas the Turc and Hargreaves–Samani methods can generate significant biases. The Valiantzas2 and H‐Makkink methods are the optimal ones for estimating ET₀ values in agricultural areas. Based on the outputs from the FAO P‐M method, ET₀ values are most sensitive to temperature, accounting for 59.5%. Other methods that provide similar results can be considered as alternatives. Finally, the modified equation can provide the most accurate results, but drought events also affect the accuracy of the modified method.

The Nanliujiang catchment is one of major rice production bases of South China. Irrigation districts play an important role in rice production which requires a large quantity of water. There are potential risks on future climate change in response to rice production, agricultural irrigation water use and pollution control locally. The SWAT model was used to quantify the yield and water footprint (WF) of rice in this catchment. A combined method of automatic and manual sub-basin delineation was used for the model setup in this work to reflect the differences between irrigation districts in yield and water use of rice. We validated our simulations against observed leaf area index, biomass and yield of rice, evapotranspiration and runoff. The outputs of three GCMs (GFDL-ESM2M, IPSL-CM5A-LR and HadGEM2-ES) under three RCPs (RCP2.6, 4.5, 8.5) were fed to the SWAT model. The results showed that: (a) the SWAT model is an ideal tool to simulate rice development as well as hydrology; (b) there would be increases in rice yield ranged from +1.4 to +10.6% under climate projections of GFDL-ESM2M and IPSL-CM5A-LR but slight decreases ranged from −3.5 to −0.8% under that of HadGEM2-ES; (c) the yield and WFs of rice displayed clear differences in the catchment, with a characteristic that high in the south and low in the north, mainly due to the differences in climatic conditions, soil quality and fertilization amount; (d) there would be a decrease by 45.5% in blue WF with an increase by 88.1% in green WF, which could provide favorable conditions to enlarge irrigated areas and take technical measures for improving green water use efficiency of irrigation districts; (e) a clear rise in future grey WF would present enormous challenges for the protection of water resources and environmental pollution control in this catchment. So it should be to improved nutrient management strategies for the agricultural non-point source pollution control in irrigation districts, especially for the Hongchaojiang and Hepu irrigation districts.

Green water accounts for two-thirds of precipitation, and the proportion could be even higher in dry years. Conflicts between water supply and demand have gradually become severe in the Hai River Basin (HRB) due to the socio-economic development. Thus, the exploitation and the utilization of green water have attracted increasing attention. By gathering the related hydrological, meteorological, and geographic data, the spatiotemporal distribution of green water in HRB and the impacts of land use types on green water are analyzed based on the SWAT (Soil and Water Assessment Tool) model in this study. Furthermore, three new indices are proposed for evaluation, including the maximum possible storage of green water (MSGW), the consumed green water (CGW), and the utilizable green water (UGW). The results show that (1) the MSGW is relatively low in plain areas and its spatial distribution is significantly associated with the soil type; (2) according to the evaluation results of CGW and UGW in HRB, a further improvement of utilization efficiency of green water could be achieved; (3) in general, the utilization efficiency of precipitation in farmlands is higher than other land use types, which means that the planting of appropriate plants could be helpful to enhance the utilization efficiency of green water. Our results summarize the spatiotemporal distribution of green water resource and provide a reference for water resources management in other water-short agricultural areas.

HIGHLIGHTS. Spatial differences in the causes of runoff variation in nine small watersheds in the middle reaches of the Yellow River were analyzed.The influence

Variations of precipitation type can exert substantial impacts on hydrological processes, yet few studies have quantified the impacts of precipitation type variations on runoff changes in high−altitude regions. In this study, we attempted to examine the potential impacts of precipitation type variations induced by the warming climate on the runoff changes of the source regions of the Yangtze River and Yellow River basins from 1979 to 2018, where the mean elevation is over 4000 m. A modified precipitation type identification method using the wet-bulb temperature, and a runoff change attribution method based on a modified Budyko framework has been applied. Results showed that fluctuations of precipitation contributed to the majority of the runoff variations in the source regions of the Yangtze River basin, which accounted for 51.64%. However, the changes of characteristic parameter n, which indicates the impacts of the underlying surface, explained 56.22% of the runoff changes in the source regions of the Yellow River. It was shown that the trend of shifting from snowfall to rainfall due to a warming climate could result in runoff decreasing, which contributed to 24.06% and 11.29% of the runoff changes in the two source regions, comparatively.

In the current human-influenced era, drought is initiated by natural and human drivers, and human activities are as integral to drought as meteorological factors. In large irrigated agricultural regions with high levels of human intervention, where the natural farmland soil moisture has usually been changed significantly by high-frequency irrigation, the actual severity of agricultural drought is distorted in traditional drought indices. In this work, an agricultural drought index that considering irrigation processes based on the Palmer drought severity index (IrrPDSI) was developed to interpret the real agricultural drought conditions in irrigated regions, with a case study in the Haihe River Basin in northeast China. The water balance model in the original PDSI was revised by an auto-irrigation threshold method combined with a local irrigation schedule. The auto-irrigation setting of the index was used by taking irrigation quotas during specific growth stages of specific crops (wheat–corn) into consideration. A series of weekly comparative analyses are as follows: (1) The soil moisture analyses showed that soil moisture values calculated by the modified water balance model were close to the real values; (2) The statistical analyses indicated that most of the stations in the study area based on IrrPDSI had nearly normal distributed values; (3) The time series and spatial analyses showed that the results of the IrrPDSI-reported dry-wet evaluation were more consistent with documented real conditions. All the results revealed that IrrPDSI performed well when used to assess agricultural drought. This work has direct significance for agricultural drought management in large irrigated areas heavily disturbed by human activity.