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【Objective】 Drought is a significant abiotic stress affecting agricultural production in many regions of China. This study investigates the spatiotemporal variations in drought during the growing seasons of summer maize in the Huaibei Plain. 【Method】 The analysis was based on the drought severity index (DSI) from 2010 to 2019 calculated using metrological data measured from weather stations across the region. We focused on the top 0-10 cm soil layer and the root zone from the soil surface to the depth of 50 cm. The M-K test and the Kriging spatial interpolation were used to analyze the spatiotemporal variation in droughts over the region at different time scales. 【Result】 ① Since 2016, the severity and frequency of droughts have both significantly increased in the areas of Dangshan, Mengcheng, and Qiaocheng, while decreased in the area of Fuyang. In Suzhou, droughts mainly occurred in 2010—2012 and 2019. Compared to seasonal scale, some drought events exhibited greater severity and higher frequency at the ten-day scale with unpredictable onset. ②The highest average annual drought index and frequency both occurred during the sowing-emergence stage, reaching moderate level or above, with the frequencies exceeding 40%. Severe droughts or worse at both timescales occurred in northern Dangshan and central Mengcheng and Suzhou. The frequency of the 0-10 cm soil-layer droughts was higher in the southwest, while the frequency of 0-50 cm soil-layer droughts was higher in the east and north than in other areas. ③ At the ten-day scale, the periods with the highest drought severity in each growing season mostly started in the early stage of sowing - emergence, emergence - jointing, and the mid-stage of jointing - tasseling. Severe droughts occurred primarily in August and September. 【Conclusion】 Since 2016, there has been a significant increase in drought severity and frequency for summer maize in the Huaibei Plain, particularly during the sowing seedling stage. Severe droughts were observed at uncertain ten-day scales, with increased drought frequency.

【Objective】 Winter wheat in Huaibei plain experiences temporal water stress during its growing season. This paper investigates the characteristics and trends of the droughts in attempts to help improve agricultural management in this region. 【Method】 Soil in the studied region is Shajiang black soil. Soil moisture measured from 1986 to 2018 was used to analyze the key soil layers that influence wheat yield and to calculate the drought severity index (DSI). The Mann Kendall test and sliding T-test were used to analyze the drought trends and compare the characteristics of drought before and after sudden temperature changes. 【Result】 From 1986 to 2018, the wheat experienced mild and moderate droughts during the sowing-emergence stage, and it only encountered one severe drought. From the dormancy stage to heading stage, only mild and moderate droughts were identified. During the maturity stage, three droughts and five extreme droughts were recorded. From 2007 to 2012, the frequency of drought was declining in the sowing-emergence stage and dormancy stage. There were no significant changes in drought in other growth stages. Following sudden temperature changes, the frequency and degree of droughts at different growth stages both increased. 【Conclusion】 A sudden temperature change resulted in an increase in drought frequency and intensification of extreme drought. Future work should focus on improving irrigation during the maturity stage and timely replenishing soil moisture to mitigate the impact of extreme droughts.

【Background and objective】 The average global temperature has risen by 0.74 ℃ over the last century, which has alerted the global hydrological cycle with extreme weather events occurring more frequently. This, together with anthropogenic activities, has affected the runoffs of most catchments and led to soil degradation and deterioration. Understanding the change in runoff of a river in response to climate change and anthropogenic activity is hence critical to mitigating their detrimental impacts. Taking Xilamulun River basin as an example, this paper is to identify the environmental factors underlying its runoff change. 【Method】 The analysis was based on meteorological and hydrological data measured from 1958 to 2015 across the basin. The factors that affected the runoff changes in the basin were calculated using Pearson correlation analysis, stepwise multiple regression, double cumulative curve, cumulative anomaly and SCRCQ method. 【Result】 Both runoff and precipitation in the basin had been in decline at decadal rates of 4 mm/10 a and 8.24 mm/10 a respectively, while the annual average temperature has been rising at an average decadal rate of 0.32 ℃/10 a. Annual average temperature, average summer temperature, average autumn temperature and annual runoff were all closely correlated. The annual runoff was affected by rainfall in summer the most, followed by the average temperature in summer. There was a correlation between precipitation and runoff after 1971, and the significance of the correlation endured reflection changes in 1972, 1982, and 1998, respectively. The contribution of the precipitation to runoff has been in decline and was 0.26%, 17.51% and 26.13%, respectively, in 1972—1981, 1982—1997, and 1998—2015, while during the same periods the associated contribution of human activities to the runoff changes was 99.74%, 82.49% and 73.88% respectively. 【Conclusion】 Anthropogenic activities affected the runoff change in Xilamulun river the most from 1985 to 2015, but its influence has been waning compared to that of climate change.

【Objective】 Soil water controls all physical and biological processes in soil and understanding its dynamics is central to improving agronomic and irrigation management. The objective of this paper is to analyze soil water variation in winter wheat fields across Huaibei plain in attempts to provide baseline data to help improve agricultural water management in this region. 【Methods】 Soils in the studied areas are predominantly luvisol soil and the analysis was based on soil water content measured from 1992 to 2018 over the wheat fields in Huaibei plain. For each growth stage of the wheat, we set a threshold soil moisture below which the wheat was deemed to suffer water stress. Spatiotemporal change in soil water content was analyzed using the Mann-Kendall test, the sliding T-test, and the Kriging interpolation. 【Result】 ①Soil water content in the top 0~20 cm soil has been in decline while the water content at the depth of 50 cm has been in increase over the past few decades. Across the plain, soil water content at the depths of 10 cm, 20 cm and 50 cm did not show massive upheaval. ②The probability of soil water content dropping below the thresholds at jointing - heading stage, heading - milk ripe stage and milk ripe -ripping stage was 38.5%, 46.2% and 46.2% respectively. In contrast, the probability of soil water content exceeding the threshold at reviving - jointing stage was high, indicating that water stress is unlikely to occur during this stage. ③Spatially, water content in the surface soil was the highest in the southwest and the least in the middle, while soil water content at the depth of 50 cm decreases from the south to the north. ④The probability that soil water content at Bengbu and Mengcheng dropped below the threshold at the jointing - heading stage was 45.5% and 50.0% respectively, and increased to 62.0% and 38.1% respectively at the heading - milk ripe stage. 【Conclusion】 Soil water content measured from the past 30 years indicated that the surface soil moisture in the winter wheat field is likely to continue to decrease, making the winter wheat, especially at seedling stage, prone to water stress. Improving irrigation is hence required in the areas proximal to Bengbu and Mengcheng to safeguard their wheat production.

【Background】 Water uptake by plants and its subsequent transpiration is an important process in the hydrological cycle but difficult to measure and calculate. In irrigation management, the evapotranspiration is often calculated from the reference evapotranspiration multiplied by a crop coefficient. 【Objective】 The purpose of this paper is to study the spatiotemporal variation of the crop coefficient of winter wheat in Huaibei plain of China. 【Method】 Using data measured from 1991 to 2018, we calculated the crop coefficient of the winter wheat based on water balance method, eddy covariance measurements and the Bouchet complementary relationship theory. The reference evapotranspiration was calculated from the Penman-Montieth formula. The spatiotemporal variation of the crop coefficient and its determinants were calculated using linear fitting method, Mann-Kendall trend test, Mann-Kendall jump test and moving t-test, and the ArcGIS. 【Result】 The annual mean evapotranspiration during the growth season of the winter wheat in Huaibei plain is 429.3 mm, and the reference crop evapotranspiration and the crop coefficient were 541.3 mm and 0.79 respectively. As the wheat grew, its crop coefficient decreased first and then increased, followed by a decline. Spatially, the crop coefficient was lowest at the northwest corner, and it was higher in the north than in the south. Temperature affected the crop coefficient most, followed by relative humidity and precipitation; it was least affected by wind speed. 【Conclusion】 The spatiotemporal variation of crop coefficient of winter wheat calculated for Huaibei plain provided guidance for calculating water requirement by irrigation. In particular, we found that the crop coefficient had been in increase from 1991 to 2018 possibly due to the climate change, which needs to be considered in evaluating water requirements in agricultural structure design for this region.

Root zone soil moisture (RZSM) is critical for water resource management, drought monitoring and sub-seasonal flood climate prediction. While RZSM is not directly observable from space, several RZSM products are available and widely used at global and continental scales. This study conducts a comprehensive and quantitative evaluation of eight RZSM products using observations from 58 in situ soil moisture stations over the Huai River basin (HRB) in China. Attention is drawn to the potential factors that contribute to the uncertainties of model-based RZSM, including the errors in atmospheric forcing, vegetation parameterizations, soil properties and spatial scale mismatch. The results show that the Global Land Data Assimilation System Catchment Land Surface Model (GLDAS_CLSM) outperforms the other RZSM products with the highest correlation coefficient (R= 0.69) and the lowest unbiased root mean square error (ubRMSE = 0.018 m 3 m -3), while SMOS Level 4 (L4) RZSM shows the worst performance among eight RZSM products. The RZSM products based on land surface models generally perform better in the wet season than in the dry season due to the enhanced ability to capture of the temporal dynamics of in situ observations in the wet season and the inertia of remaining high soil moisture values even in the dry season, while the SMOS L4 RZSM product, derived from SMOS L3 surface moisture (SSM) combined with an exponential filter method, performs better in the dry season due to the attenuated ground microwave radiation signal caused by the increased water vapour absorption and scattering in the wet season. The underestimated SMOS L3 SSM triggers the underestimation of RZSM in SMOS L4. The overestimated RZSM products based on land surface models could be associated with the overestimated precipitation amounts and frequency, the underestimated air temperature, and the underestimated ratio of transpiration to the total terrestrial evapotranspiration. In addition, the biased soil properties and flawed vegetation parameterizations affect the hydrothermal transport processes represented in different land surface models (LSMs) and lead to inaccurate soil moisture simulation. The scale mismatch between point and footprint also introduces representative errors. The comparison of frequency of normalized soil moisture between RZSM products and in situ observations indicates that the LSMs should focus on reducing the frequency of wet soil moisture, increasing the frequency of dry soil moisture and the ability to capture the frequency peak of soil moisture. The study provides some insights into how to improve the ability of land surface models to simulate the land surface states and fluxes by taking into account the issues mentioned above. Finally, these results can be extrapolated to other regions located in similar climate zones, as they share similar precipitation patterns that dominate the terrestrial water cycle. [ABSTRACT FROM AUTHOR]