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Hydrological droughts are closely related to the meteorological ones in the arid and semi-arid areas. It is of great significance to reveal the response relationship between the meteorological and hydrological droughts in drought warning and water resource management. In this study, the changing patterns of drought were determined in the Xiangjiang River Basin of western China using Copula functions. Daily precipitation data was collected from 40 meteorological stations, while the monthly runoff data was from three hydrological stations (Laobutou, Hengyang, and Xiangtan stations). The standardized precipitation index (SPI) and standardized runoff index (SRI) were adopted to describe meteorological and hydrological droughts. The Pearson correlation coefficient was used to determine the response time to drought. The run theory was used to identify, merge, and remove the drought events. The Mann-Kendall trend test and wavelet analysis were employed to reveal the trend and periodicity of drought in different seasons in the upper, middle, and lower reaches. Furthermore, seven widely used distribution functions were selected to fit the duration and severity sequences of meteorological and hydrological drought that were obtained from SPI and SRI. The optimal parameter estimation was obtained in each marginal distribution using the maximum likelihood. There were strong links between meteorological and hydrological droughts using three Archimedean Copula functions (Frank, Gumbel, and Clayton Copula) by coupling the response probability curve in a Bayesian network model. Finally, the model performance was evaluated using the Akaike information criterion (AIC) and ordinary least squares (OLS). The main results demonstrate: 1) The run theory [0.5, 0, −0.5] was achieved to better identify the drought events, with a matching rate of over 90% between meteorological and hydrological droughts. There was a two-month propagation time from the meteorological to hydrological drought in the whole watershed. The SPI and SRI effectively detected the drought events and better matched them with the historical drought statistics from the different periods (in 1963, 1986, and 2003). 2) The frequency of meteorological drought was higher than that of hydrological drought. The duration and severity of hydrological drought were greater than those of meteorological one, where the downstream area experienced the most severe hydrological drought, but the midstream is the most severely affected by meteorological drought. The difference was attributed to the higher evapotranspiration and high level of socio-economic development in the downstream. 3) There was a tendency toward wetness of the historical data in the basin, which was consistent with the remote sensing monitoring of terrestrial water storage anomaly. However, there was a distinct seasonal variation in the inter-annual wetness of the basin. The upper and middle reaches showed a drier trend in the autumn, while the middle reaches were in a trend toward dryness in the summer. Additionally, there were several outstanding oscillation periods of dry and wet, namely 3-5, 6-10, and 18-21 a. 4) The optimal joint distribution of meteorological-hydrological drought severity in the upstream and downstream area was the Gumbel Copula function, while the Frank Copula function was the optimal joint distribution for the rest. 5) The response probability of hydrological drought duration and severity increased with the increase of characteristic variables in the meteorological drought. There was a stable response probability of hydrological drought duration when the duration of meteorological drought exceeded a specific threshold. This study is of great significance in understanding the mechanism of drought in the Xiangjiang River Basin as well as guiding the drought prevention and fighting work in the region. [ABSTRACT FROM AUTHOR]

Late frost is one of the most destructive meteorological disasters in the Loess Plateau of China. A great threat can be posed to the sustainable production of apples, leading to great economic losses in the apple industry. Thus, it is a high demand to explore the occurrence of late frost events for the prevention of apple late frost disasters in the decision-making of the local apple industry. In this study, the late frost return periods were investigated on the duration and severity of late frost events using the Coupla functions. The reliability of the model was then verified to analyze the characteristics of apple late frost. The study area was taken as the apple-producing areas of Shaanxi Province in western China. The meteorological datasets were collected from the seven weather stations from 1971-2018. The daily minimum temperature (Tmin) of 0℃ was taken as the critical temperature for the occurrence of apple late frost events, in order to extract the two characteristic variables of duration and severity of late frost events. These characteristic variables of late frost events were first fitted by seven common distribution functions, respectively. Kolmogorov Smirnov (K-S) test was then carried out to verify the model. The joint distributions of late frost characteristic variables were constructed to evaluate the goodness-of-fit using six Copula functions. The occurrence probability and return period of late frost events were analyzed with the optimized Copula functions. The results showed that the severity of late frost risks generally increased from the southeast to northwest in the study area from 1971 to 2018. The optimal marginal distribution of late frost duration was in the log-normal distribution, while there was a great difference in the optimal marginal distributions of late frost severity. A significant positive correlation was found between the duration variables and the severity of late frost at each station. The goodness-of-fit test demonstrated that most of the stations presented the optimal distribution of Normal Copula function for late frost events. The joint cumulative probability increased significantly, as the severity and duration of late frost increased, but the increasing trend was much slower than before. A much more significant increase was observed in the co-occurrence return period under the same increase of univariate value, compared with the joint. The univariate return period was always between the joint and co-occurrence return period. Once the univariate return period was small enough, the optimal range of the actual univariate return period can be estimated, according to the joint and the co-occurrence return period. In general, a low probability was found in the late frost events with long duration and high severity at the weather stations in apple-producing areas in Shaanxi Province of China. However, the stations in the Yan’an area were more susceptible to the late frost events with high severity or long duration, as well as the late frost events with both high severity and long duration. Thus, more attention can be paid to late frost risks in the Yan’an area. This finding can provide a theoretical base to deal with the late frost disaster in apple production. [ABSTRACT FROM AUTHOR]

Human activity has been one of the most important factors inducing regional ecological risks in recent years. But, there are different visualization and response degree of ecological risks and human activities in different land scales. It is a high demand to scientifically analyze the correlation characteristics of regional Landscape Ecological Risk (LER) and Human Activity Intensity (HAI), in order to coordinate the territorial system of human-environment interaction for better regional high-quality development. The ever-increasing conflict can be found between ecological protection and economic and social development, due mainly to rapid urbanization. The Yangtze River Delta (YRD) is one of the typical regions with intensive human activities, remarkable economic development, and outstanding ecological status. Taking the YRD as the subject, a three-level scale of city, county, and grid was established to construct the LER and HAI assessment models, in order to characterize the spatial and temporal response at different scales. The data was also collected from the land use, nighttime lighting, and population spatial distribution in the four periods from 1990 to 2020. The Copula function, bivariate spatial autocorrelation, and coupled coordination degree models were used to reveal the spatial and temporal correlation between the LER and HAI. The results show that (1) the spatial distribution pattern of LER was high in the north of the study area, and low in the south under different scales. The high risk areas continued to decrease during 1990-2020, whereas, the low risk areas showed an increasing trend. There was the most outstanding reduction in the high risk areas at the city scale, with a decrease of 19.51 percentage points over 30 years. By contrast, there was the most significant increase in the low-medium risk and low risk areas at the county scale, indicating an increase of 16.29 percentage points over 30 years. (2) The spatial distribution pattern of HAI was high in the northeast of the study area during 1990-2020, while low in the southwest under different scales. All the regions with high HAI showed a significant increasing trend. There was a significant decreasing trend in the regions with low HAI. The high intensity region presented the largest increase at 13.42 percentage points on the grid scale, whereas, the low intensity region was the most significant decrease at 9.76 percentage points on the city scale. (3) The correlation between HAI and LER shared a positive correlation between 1990 and 2020, but the correlation between them was weakening, indicating the weak influence of regional HAI on LER. By contrast, the coupling and coordination between them showed an increasing trend from 0.3031 in 1990 to 0.3112 in 2020. It infers that the relationship between them was gradually shifting from conflict to coordination. Spatially, there was a continuous decreasing trend in the H-H clustering area. Furthermore, the L-L clustering area showed an increasing and then decreasing trend with an overall decrease. Both L-H and H-L increased significantly after 2010. The spatial correlation characteristics of regional LER and HAI were combined to manage and control the regional ecological environment. The finding can provide a theoretical basis for land management and landscape planning, together with the spatial guidelines for the regional ecological risk prevention and ecological restoration. [ABSTRACT FROM AUTHOR]

Both Reservoir Inflow (RI) and Irrigation Water Demand (IWD) depend mainly on the basin-wide climate. Hence, various unpredictable (stochastic) weather and climate have induced significant variation in the water supply and demand processes in recent years. Meanwhile, the spatial similarity of climate conditions was also required to consider the relevancy between water supply and demand. More importantly, the smaller the basin is, the more considerable the relevancy is. However, the traditional one-dimensional stochastic dynamic programming cannot concern the relevancy between the multiple variables of water resources. In this study, a novel multi-dimensional stochastic dynamic programming was developed to deal with the relevancy and stochasticity in the streamflow and demand for the reservoir operations. Firstly, the one-dimensional distribution was selected to characterize the stochasticity of individual RI and IWD processes. Secondly, a Copula function of several variables was constructed using the marginal distribution. Specifically, the relevancy involved two aspects, i.e., the RI or IWD between the adjacent time intervals, and between RI and IWD at the same time. The stochasticity was referred to the individual RI, IWD, as well as the two-dimensional RI and IWD processes. Finally, the Copula function was integrated into the stochastic dynamic programming for the optimal dispatching model of the reservoir. A case study was set as an annual regulating reservoir responsible for agricultural irrigation. The results indicate that: 1) The Generalized Extreme Value (GEV) distribution was performed better on the RI and IWD in months. 2) There was remarkable relevancy of RI or IWD between a few adjacent time intervals. Moreover, there was a strong significance in April, May, June, July, September, and October. 3) Various types of Copula function were selected to model the dependent structure of RI/IWD variables at the adjacent time intervals. A Frank Copula was also employed to describe the negative relationship of dependent structure between RI and IWD at the same time. 4) The reservoir operation model considering the relevancy between RI and IWD was performed better than not. Specifically, the case study showed that the total water shortage was 10.37 × 108 m³, when considering the relevancy and stochasticity of multiple variables, which was less than before (10.49×108 m³). Nevertheless, there was a little difference between the optimal total water shortages by the two multi-dimensional stochastic dynamic programmings. This trend was attributed to a little difference of state transition probability between with and without considering the relevancy of RI and IWD. Consequently, the newly-developed multi-dimensional stochastic dynamic programming can be widely expected to extend for the multi-dimensional stochastic optimal scheduling in fields, such as the multi-energy supplementary model considering the hydropower, wind, and light energy. Moreover, a better fitting can be suitable for the current relevancy and stochasticity in multi-dimensional processes, where the wind speed and solar radiation are stochastic variables in this case. [ABSTRACT FROM AUTHOR]

Drought is a complex and recurrent climate phenomenon, and understanding the development of the drought event is of great significance in preventing the damage. Current studies have analyzed the drought duration and severity based on run theory and Coupla function but few focuses on the drought recurrent interval and its relationship with agricultural drought disaster. In this study, the drought recurrence interval was investigated based on the drought duration and severity using run theory and Coupla function and the results were applied to agricultural drought disaster analysis in order to verify the reliability of the method for agricultural application. The study area was Northern Shannxi and the precipitation data from 1960 to 2015 were collected for drought grade classification based on standardized precipitation index (SPI). The drought duration and severity of drought event was calculated based on SPI values using run theory. Each drought characteristic index was evaluated for its distribution by comparing 7 different distributions. Then, the joint distribution of the 2 indices was established based on their correlation. Then the recurrence interval of each index was calculated for determination of their joint recurrence interval. The agricultural disaster area data were obtained from Statistic Yellow Book. The results showed that the drought occurred 94-103 times in 1960-2015 in the Northern Shannxi. The main drought area with high frequency was the area such as Yunlin, Yanan et al and that with low frequency was in the area such as Baoji, Xian, Xianyang et al. The distribution of drought duration and severity belonged to Weibull and Gamma distribution, respectively. The joint function of the 2 indices could be well fitted by the Frank-copula function with smaller squared euclidean distance and akaike information criterions. With the increase of drought duration and severity, the joint probability and recurrence interval gradually increased. The joint recurrence interval variation of different meteorological stations had different changing trend. The actual droughtaffected area of the crops in the Northen Shannxi was closely related to the drought duration and severity. The drought events joint recurrence interval was coincide with the actual drought disaster situation in the region. In the period of 1995-2005, the actual and theoretical drought duration was consistent mostly and the absolute errors between the actual and theoretical drought recurrence interval were only 0.1-0.3 a. The results indicated that the method proposed here was reliable in analyzing drought characteristics and could be used for agricultural drought disaster assessment. [ABSTRACT FROM AUTHOR]