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Drought stress is a major environmental limiting factor for grape growth in the Bohai Rim Region (BRR) in China. The investigation of process-based meteorological evaluation indicators is of particular interest to precisely understand the spatiotemporal characteristics of grape drought processes, providing substantial support for grape drought monitoring, prevention, and mitigation. In this study, a daily grape drought index (GDI) was constructed based on a rolling calculation of water profit and deficit. The characteristics of the GDI in historical drought disaster samples were analyzed and drought evaluation level indicators were constructed, facilitating the assessment of process-based grape drought risk. The results showed that duration days with GDI < − 0.4 could be used as drought level indicators, and the thresholds of grape drought in germination to new shoot (P1), flowering to fruit setting (P2), fruit expansion (P3), and coloring to maturity (P4) were 14, 13, 12, and 13 days with GDI < − 0.4, respectively. The identification results calculated by grape drought indicators were basically consistent with historic occurrence levels of grape drought, with 76.9% of the calculated grape level being completely consistent with the historical records and 15.4% being within one level. The process-based grape drought risk gradually decreased with the advancement of grape process, with grape drought risk in the order of P1 > P2 > P3 > P4. Beijing, Tianjin, Hebei, and western Liaoning exhibited the highest grape drought risk. [ABSTRACT FROM AUTHOR]

Frequent occurrences of late spring frost disaster create severe agricultural/forest damage, even given the background of global warming. In the warm temperate zone of China, which is the largest planting area for fresh apricot, late spring frost disaster has become one of the major meteorological hazards during flowering. To prevent cold weather–induced apricot frost disaster and reduce potential losses in related fruit economic value, it is vital to establish a meteorological indicator for timely and accurate identification of cold weather process–based apricot frost disaster, to provide support for timely apricot frost monitoring and warning in late spring. In this study, daily minimax temperature ( T min ) and apricot frost disaster data during flowering were combined to establish meteorological identification indicators of apricot frost based on cold weather processes. A process-based apricot frost model f (D , T cum) was firstly constructed, and characteristics of T cum (accumulated harmful temperature) were explored under different D (duration days) based on the representation of historical apricot frost processes. Thresholds for the T cum for apricot frost in 1, 2, 3, 4, and more than 5 days of apricot frost process were determined as − 1.5, − 2.9, − 4.4, − 5.8, and − 7.3 °C, respectively. Validation results by reserved independent disaster samples were generally consistent with the historical records of apricot frost disasters, with 89.00% accuracy for indicator-based identification results. Typical process tracking of the proposed identification indicator to an apricot frost event that occurred in North Hebei during April 3–9, 2018, revealed that the indicator-based identification result basically coincides with the historical disaster record and can reflect more detailed information about the apricot frost process. [ABSTRACT FROM AUTHOR]

We investigated potential factors influencing variations in isotopic composition of external precipitation and internal drip water at Zhenzhu Cave, Hebei Province, north China. Two meteoric precipitation sites and three cave drip sites were monitored monthly during April 2012-April 2014. The results of meteoric precipitation present: on monthly timescale, δ18Op and δDp showed a significant seasonal double peak characterized by depleted isotopic values in both dry and wet seasons (but a significant seasonal variation in d-excess). There is a weakly negative correlation with monthly mean precipitation amount but no significant correlation with surface air temperature. Based on GNIP data, there are no significant correlations on an interannual scale between annual weighted mean δ18Op (and δDp) and annual precipitation or annual mean temperature. This implies the variation of δ18Op (and δDp) in the area cannot be interpreted solely as reflecting an "amount effect" or "temperature effect" on either seasonal or interannual scale, and may be affected by moisture sources. There isn't any significant change in δ18Od and δDd values of cave drip water during monitoring period, demonstrating that cave drip water comprise a mixture of precipitation integrated over a long period rather than seasonal timescale. There were significant seasonal changes in cave air CO2 concentration, with higher concentrations in summer and lower concentrations in winter that is well correlated with environmental variables such as surface temperature and precipitation, which may help improve the interpretation of stable carbon isotope records from speleothems (δ13Cs) in relation to cave air CO2. [ABSTRACT FROM AUTHOR]

Abstract: Hebei Plain is located in the north of Huabei Plain and it is one of the regions where the demand of water resource exceeds the supply of that greatly in current China. Because the region is short of surface water, the groundwater becomes the main supply resources. With the developing of social economy and the increasing of the population, the demand of water resource is increasing continuously. The exploitation of the groundwater exceeds the limitation of that. This paper studies the sustainable utilization of the groundwater resources in Hebei Plain by the methods such as Grey System, time series and NN. The results showed that the groundwater resources would decrease in future, and the depth of the groundwater would deepen more. The groundwater table in Shijiazhuang and Cangzhou city would decrease below sea level 30 meters by 2020. [Copyright &y& Elsevier]

Remote sensing technologies are frequently employed in monitoring and evaluating agricultural meteorological disasters because they can provide high throughput and cost-effective accesses to obtain a variety of real-time spatial data related to crop growth information. Accurately and timely estimating the drought dynamics using remote sensing is valuable for improving crop management level and promoting agricultural sustainable development. In this study, the responses of winter wheat during the critical growth stages to different drought levels from 2010 to 2020 in the Huang-Huai-Hai (HHH) region of China were evaluated based on Google Earth Engine. Four critical developmental stages of winter wheat were highlighted: greening－jointing, jointing－heading, heading－milking maturity, and milking maturity－maturity stages. The temperature vegetation dryness index (TVDI) was constructed for evaluating the drought of winter wheat. Our results indicated that the winter wheat in the HHH region during 2010－2020 was clearly impacted by drought disasters, mainly mild to moderate droughts. In particular, the TVDI index during the critical development stages of winter wheat from 2010 to 2020 wavered in the scope of 0.48 and 0.61, and the soil moisture content at a depth of 10 cm tended to obviously reducing with a rate of − 0.1615/a. For critical growth stages, the winter wheat in the HHH Region was the most prone to threatened by drought during the stage of jointing－heading, following the stage of milking maturity－maturity. The high probability incidence of drought in winter wheat gradually shifted from the nutritional growth to the reproductive growth stages, which increased the risk of drought affecting yield. Furthermore, the notable spatial variations of drought in winter wheat in the HHH region were found. The winter wheat was evidently threatened by moderate and severe droughts in certain areas such as southern Hebei province, northern Jiangsu province, Anhui province, etc. Our results provide new insights into the studies on monitoring and evaluating agricultural meteorological disasters based on remote sensing technology. [Display omitted] • We established temperature vegetation dryness index (TVDI) for winter wheat. • We explored the spatiotemporal dynamics in drought of winter wheat based on TVDI. • We revealed the responses of winter wheat during the critical stages to droughts. • Google Earth Engine technology and long-term field observations were used. [ABSTRACT FROM AUTHOR]