Drought is closely related to the early stages of the water cycle. Due to the influence of snow cover and soil freezethaw processes, the water cycle process in cold regions presents specific and complex characteristics in the early spring. Therefore, the driving factors of spring drought in cold regions are different from those in warmer regions. This work takes the cold region of Northeast China as the study area. The early spring period was divided into four periods: the prefreezing period, rapid freezing period, stable freezing period, and melting period. Precipitation, evapotranspiration, and snow depth were selected as candidate driving factors in each period. The rough set conditional information entropy method was used to calculate the weights of the driving factors, and the main driving factors were preferably selected. The results indicated that as soil depth increased, the range of drought expanded. Spring drought was mainly concentrated in the western, central, and central western regions of the study area, whereas the northern, eastern, and southeastern regions were relatively humid. The precipitation and evapotranspiration during the prefreezing and melting periods had a considerable impact on spring drought, and for shallow spring drought, the impact of precipitation was greater, whereas the impact of evapotranspiration during deep drought was greater. The impermeability and evaporation suppression function of frozen soil resulted in early water retention in the soil, which in turn affected the soil moisture of the following year. During the rapid freezing period, snow depth was the main factor driving spring drought. The snow during the freezing period helped to suppress soil moisture evaporation, and the infiltration of snowmelt effectively increased the soil moisture content. Studying the driving factors of spring drought can help identify the formation mechanism of agricultural drought in cold regions and provide a reference for disaster prevention.

Due to the influence of snow cover and soil freeze–thaw processes in the early spring, the characteristics of spring drought in cold regions are different from those in other regions. This paper takes Qiqihar, a cold and semiarid grain production area in Northeast China, as the study area. Based on factors such as snow cover in the early spring period and precipitation, temperature, evapotranspiration, and soil moisture during the spring sowing period, a projection pursuit model with analysis of variance (ANOVA PPM) was used to analyze the spatiotemporal variation characteristics of regional spring drought. For the ANOVA PPM, based on the grouping of the projection points, local aggregation is measured by the mean square within groups, and overall dispersion is measured by the mean square between groups, thus achieving comparability and balance between overall dispersion and local aggregation. The spatial analysis of spring drought showed that, from a spatial perspective, there were significant spatial differences in spring drought in different subregions, and spring drought was closely related to latitude, with significant differences occurring at different latitudes. The northern region is relatively light, while the central and southern regions are more severe. From a temporal perspective, there are significant differences in spring droughts between different decades (1980 s, 1990 s, 2000 s and 2010 s). Overall, spring drought first intensifies and then decreases.

Northeast China is an important grain-producing area, and spring is the sowing time for crops. Drought hinders crop germination and leads to crop failure. Spring drought analysis helps to understand the characteristics of regional spring drought and provides a reference for formulating disaster prevention and reduction measures. Considering the characteristics of seasonally frozen soil regions in northeastern China, sampling at a resolution of 0.5 degrees, accounting for the snow cover factors in the early spring, as well as precipitation, temperature, evapotranspiration, and soil moisture during the spring planting period, and uses the projection pursuit information entropy model to analyze the spatial and temporal variability of spring drought in Northeast China. In the model, a new method was proposed to calculate the cutoff radius by adjusting the radius size with the parameter. The optimal parameters were ultimately determined using the Shapiro-Wilk test, Kolmogorov-Smirnov test, and Epps-Pulley test. The results are as follows: drought is relatively severe in the eastern parts of Inner Mongolia, as well as in the northwest of Liaoning. The central and northern parts of Inner Mongolia, the northern and northeastern parts of Heilongjiang, the southeastern parts of Jilin, and the eastern parts of Liaoning are relatively humid, while the drought situation in other regions is relatively moderate. Regional spring drought shows an increasing trend, and most regions show statistical significance. Areas with high temperatures and low precipitation, as well as low snow cover in the early spring, are prone to spring drought. Moist regions are characterized by high precipitation, low evapotranspiration, and abundant snow resources.

The drought index is an important indicator that reflects the degree of regional drought and plays an important role in drought disaster monitoring, prediction and evaluation. According to the process definition of the standard precipitation evapotranspiration index (SPEI), the influence of cumulative effect attenuation was considered and aggregated at different time scales k, the linear attenuation coefficient was defined, and attenuation parameters were used to adjust the degree of attenuation. A value closer to the current month was assigned a larger weight, and a value closer to the current month was assigned a smaller weight. Thus, the cumulative water surplus or deficit was recalculated, and the standard precipitation evapotranspiration index based on the cumulative effect attenuation (CASPEI) was defined and applied to the drought analysis of Heilongjiang Province, which has the highest grain output in China. The comparative analysis showed that the CASPEI dataset was more consistent with the log-logistic distribution, and its sensitivity in identifying regional drought events was greater than that of the SPEI, which effectively corrected the original index's errors in identifying the drought levels of some stations and was more consistent with regional historical drought events. The temporal and spatial variation analysis revealed that drought occurrence is seasonal: summer is the season with the highest frequency of severe drought and extreme drought, and the area experiencing extreme drought is greater than that during other seasons. The areas with moderate drought in spring and autumn were relatively large. With the increase in time scale, the area of extreme drought decreased, and the area of severe drought increased. The area of moderate drought increased, while the area of light drought decreased. The CASPEI can accurately judge the extent to which drought occurs to respond to drought and effectively reduce or prevent large losses in people and the economy caused by drought.

由于对机械加工零件表面进行磨损图像检测的过程中存在噪声,影响了检测精度,为此以模糊神经网络为技术支持,结合人工智能技术,设计一种机械加工零件表面磨损图像检测方法.选取某锻造加工厂一台金属切削机械车床,就其加工零件表面展开检测分析.将模糊化概念与模糊推理融入神经元,构建五层结构的模糊神经网络,通过数控车床控制系统运行与训练,明确各网络层相关参数.利用灰度增强、中值滤波、阈值分割等预处理手段,对车床加工零件表面图像进行预处理.基于模糊神经网络结构,将预处理后零件表面图像输入网络输入层,经模糊化层、规则层、求和层的处理,由反模糊化层输出最终的磨损图像检测结果.实验结果表明,所提方法的车床加工零件表面磨损图像检测精度较高,对加工现场复杂的光照环境,具备较强的抗干扰能力,可行性与可靠性优势显著.

As the conflict between the supply and demand of resources intensifies, it is critical to deeply study the important relationships and symbiotic evolution mechanisms among water resource development and utilization, energy production, agriculture, and the socioeconomic system to promote multiresource synergy management. This study introduced symbiosis theory to build a regional water-energy-food complex system in which the water-energy-food nexus was the main body and the social-economic-natural system was the external environment. Then, a symbiosis evaluation index system was established from three dimensions, including the symbiotic unit, symbiotic relationship, and symbiotic environment. Using the improved cloud model, we judged the symbiosis level of the water-energy-food complex system in Heilongjiang Province from 2010 to 2019. The results indicated that (1) the symbiosis level of the provincial water-energy-food complex system, symbiotic unit, and symbiotic environment was on the rise from level II in 2010 to level IV in 2019, and the symbiosis level of the symbiotic unit fluctuated between level III and level IV. The system exhibited an overall strong symbiosis state. (2) The weights of the three criteria were ranked as symbiotic environment > symbiotic unit > symbiotic relationship. The state of the social-economic-natural system could be considered a “monitor” of the symbiosis level, the symbiotic unit was an important basis for the evolution of the complex system, and the symbiotic relationship was the shortcoming of the system symbiosis enhancement. (3) The trade-offs between food production and water savings constrained socioeconomic development in the province. The resource demands of the economic and social systems and the emissions to the natural system that occurred during the resource exploitation and utilization processes were important factors affecting the coordinated development of the studied system. Overall, the experimental results were consistent with the research subjects’ actual situations, and the government should promote the regional three-way flow of social, natural, and economic resources to allow the targeted management of multiresource security.

马铃薯晚疫病是由马铃薯晚疫病菌引起的一种严重影响马铃薯产量和质量的病害.农业生产者需在早期发现病害,以便采取必要措施防止病害传播到田间其他地方.在农业生产活动中,病害严重程度是一个重要参数,可用于预测产量、推荐防治措施、减少生产损失并控制成本.研究提出一种基于Mask R-CNN的马铃薯晚疫病量化评价方法,该方法包括数据集创建、图像分割、统计计算和表格查询操作等步骤.具体地,通过Mask R-CNN分割算法检测单个马铃薯叶片中的晚疫病斑,同时在正常和受病害感染区域生成高质量的分割掩膜,并计算病斑面积与叶片总面积之比K,根据K的取值确定病害的严重程度级别从而对病害进行量化评价.结果表明,研究提出的马铃薯晚疫病量化评价方法在保留测试集上总体精度可达到87.50％.

传统农业用水量预测算法忽略了对较小流量数据的处理与预测,导致预测结果与实际情况的拟合度不高,且传统方法应用过程复杂,应用难度较高.为此提出农业种植区域用水量数据化预测算法.填补用水量缺失数据,同时运用归一化方法将用水量数据归一化处理,并将其简单化处理,完成数据预处理.构建灰色预测模型预测流量较大的用水量,且针对流量较小的用水量数据构建三次指数平滑预测模型,将两种模型组合,求出预测值并进行反归一化处理,实现农业种植区域用水量数据化预测.实验结果表明,所提方法的预测拟合度高、复杂度低和可靠度高.

In order to solve the problem that water resources in a certain province are relatively scarce and the spatial matching effect of resources is poor, which causes the w-e-f system to face the problem of trade-off, the water-energy-food coupling coordination and collaborative optimization system is proposed. By constructing the w-e-f multi-objective collaborative optimization model, the multi-objective optimization schemes under different weight scenarios are compared, and scenario 2 with better effect is selected as the best scheme for collaborative optimization. The results show that, on the basis of meeting the constraint conditions, by adjusting the crop planting structure and making efficient use of resource elements, the water resource consumption of major grain crops can be reduced by 7.3% and the total energy consumption can be reduced by 2.5% by 2030 compared with 2019.ConclusionThe system provides solutions to alleviate the pressure on water resources and ecological environment to a certain extent. Compared with the single objective optimization scheme, multi-objective optimization can effectively alleviate the trade-off conflict between w-e-f.

The projection pursuit model is an important tool for processing high-dimensional nonnormal and nonlinear data, and it has a wide range of applications. In this paper, clustering analysis and information entropy theory are simultaneously introduced into the projection pursuit model. The K-means clustering method is used to cluster high-dimensional data, and information entropy is used to measure the overall dispersion and local aggregation of projection data. A projection pursuit model based on clustering and information entropy is proposed. The new model has both the classification advantages of clustering analysis and the evaluation advantages of the projection pursuit model. In the case test, different cases are tested by using the Shapiro-Wilk test, Kolmogorov-Smirnov test, Epps-Pulley test, etc. The results show that in most cases, the new model is better than the original model, and the advantage is clearer when the data dimension is higher. Finally, the new model is applied to the agricultural drought risk assessment of Qiqihar, a major grain-producing area in China that is prone to drought. The regional agricultural drought risk shows a downward trend over time. Spatially, the risk of the central and southern regions is low, while the risk of the northern and western regions is high. Regional ability to resist disasters is the main reason for the spatial and temporal differences. This paper extends projection pursuit model theory, analyzes the characteristics of the spatiotemporal variation in regional agricultural drought risk, and provides a reference for identifying the hidden dangers of drought disasters and disaster reduction.

Drought is one of the main natural disasters affecting economic development and food security. Drought monitoring and identification are the premise of disaster risk management, and the drought index is the main means of monitoring and identifying drought. The paper proposes a new drought index, the agricultural crop drought index (ACDI), which is suitable for rainfed agriculture in arid areas. ACDI calculates water deficit from precipitation and evapotranspiration and considers the weight of crop growth stage. The weight of growth stage and water deficit constitute the weighted data series. The fitting distribution is optimized by Kolmogorov–Smirnov test, and the data are standardized to obtain ACDI. The weight of growth stage is determined by the multiple correlation coefficient between meteorological factors and grain yield. A large weight is equivalent to a large coefficient, large coefficient means that meteorological factors in this growth stage will have a greater impact on grain yield, so the water deficit in this growth stage should play a more important role in defining drought index to better identify agricultural drought from the perspective of crops. Finally, Qiqihar, a semiarid area in Northeast China, is selected as the research area for the case study. Comparing ACDI with standard precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI) and crop water deficit index (CWDI), the standard deviation of ACDI is larger, which indicates that the difference between index values is larger and it is relatively good in distinguishing the degree of drought. In addition, the correlation coefficient between ACDI and climate grain yield passed the test with a significance level of 0.05, while the other three indexes did not pass the test, which shows that the relationship between ACDI and grain yield is higher than the other three drought indexes. For arid areas, grain yield can reflect the impact of drought. Therefore, ACDI looks more promising to identify agricultural drought from the perspective of crops. ACDI provides a reference for monitoring agricultural drought from the perspective of crop growth stage, and enriches the drought index theory.

农业科技水平是区域农业综合生产能力的表现.为探寻黑龙江省未来农业科技发展趋势,结合黑龙江省农业发展状况,从投入与产出两方面构建黑龙江省农业科技水平预测指标体系.基于2003-2017年数据,采用ARIMA-Holt组合预测模型预测未来5年黑龙江省农业科技水平.结果表明:黑龙江省不仅应从农业科研经费与农业技术人才培养两方面继续加大投入力度,更要注重农业科研成果的推广和资源的高效整合.基于预测结果,给出提升黑龙江省农业科技水平的对策建议.

[目的]研究区域水—能源—粮食关联系统(WEFN)的协同发展状况,促进区域水、能源、粮食的可持续利用.[方法]基于复杂适应系统理论,从水、能源、粮食3方面构建区域WEFN协同发展评价指标体系,以协同进化算法、灰色关联等为基础提出一种基于各要素条件和相互作用机理的综合协同发展模型,并以黑龙江省为例测算2009-2018年WEFN的协同发展度及子系统的发展度、协同度,评价其协同发展状况.[结果]①各子系统发展程度中等,差距较小,协同度差距较大但均呈波动上升趋势,其中水资源对能源和粮食、能源对粮食的协同作用明显.②WEFN协调发展状况中等,与各子系统协同发展趋势一致,波动上升后保持稳定,粮食子系统协同发展程度最高.③子系统间协同作用差是造成WEFN协同发展状况不高的原因,应以水、能源在农业生产中的高效应用为突破口,促进子系统间的协同发展.[结论]综合协同发展模型能够有效评价区域WEFN的协同发展状况,有助于区域可持续发展决策.

The risk analysis of flood and drought disasters and the study of their influencing factors enhance our understanding of the temporal and spatial variation law of disasters and help identify the main factors affecting disasters. This paper uses the provincial administrative region of China as the research area. The proportion of the disaster area represents the degree of the disaster. The statistical distribution of the proportions was optimized from 10 alternative distributions based on a KS test, and the disaster risk was analyzed. Thirty-five indicators were selected from nature, agriculture and the social economy as alternative factors. The main factors affecting flood and drought disasters were selected by Pearson, Spearman and Kendall correlation coefficient test. The results demonstrated that the distribution of floods and drought is right-skewed, and the gamma distribution is the best statistical distribution for fitting disasters. In terms of time, the risk of flood and drought disasters in all regions showed a downward trend. Economic development and the enhancement of the ability to resist disasters were the main reasons for the change in disasters. Spatially, the areas with high drought risk were mainly distributed in Northeast and North China, and the areas with high flood risk were mainly distributed in the south, especially in Hubei, Hunan, Jiangxi and Anhui. The distribution of floods and drought disasters was consistent with the distribution characteristics of precipitation and water resources in China. Among the natural factors, precipitation was the main factor causing changes in floods and drought disasters. Among the agricultural and socioeconomic factors, the indicators reflecting the disaster resistance ability and regional economic development level were closely related to flood and drought disasters. The research results have reference significance for disaster classification, disaster formation mechanisms and flood and drought resistance.

To improve the performance of agricultural water resources and food production against a background of China's agricultural water price reform, an interval two-stage stochastic programming model is established and applied to account for impacts of agricultural water price reform and a water-saving technology subsidy in Heilongjiang Province, China. A water price affordability constraint and a water-saving technology subsidy to support uptake of water-saving irrigation technology are both introduced. Results of model runs show that when the current agricultural water price is increased to reflect national water price reform without a technology subsidy, the total income of irrigation farming is reduced by 2%-8%, with potential negative impacts on food production. However when an irrigation water-saving technology subsidy is introduced to accompany the increased water price, farm income can be protected and overall food production can be maintained. The two part mechanism of increased water price and water-saving technology subsidy can be used to encourage farmer to reduce water application rates as well as reduce land in production of high-water-consuming crops. Such a two part program offers considerable hope for protecting unsustainable use of water in water scarce regions while protecting farm income and food security in the face of unknown future water supply fluctuations. (c) 2021 Elsevier Inc. All rights reserved.

The spatial distribution of staple crops is related to the distribution of the agricultural industrial structure and national food security. Based on the interval-parameter stochastic programming method, the randomness and uncertainty of parameters are represented by intervals and the initial optimization model is established. In addition to conventional factors, such as land resources and food demand, the initial model also takes national and local agricultural supply policies as constraints. Furthermore, based on the two-stage interval-parameter stochastic programming method, natural disasters are regarded as a penalty in the second stage, and a two-stage model is established. The initial decision is modified so that the two-stage model can find a compromise optimization result under the constraints of feasibility and disaster impact. The initial model and the two-stage model are applied to optimize the staple crop spatial distribution in China’s provincial administrative districts. The initial optimization results show that rice is mainly planted in the southern region of China; wheat is planted in the central and eastern regions; maize is planted in the north-central and northeastern regions; and soybean is planted in the northeastern, middle-eastern and southwestern regions. Compared with the initial optimization results, the two-stage model optimization results showed that the area of wheat, rice and maize decreased while the area of soybean increased. Natural disasters led to crop yield reductions. In the initial model, the final yield of soybean could not meet the constraints. Therefore, the distribution area of soybean should be increased so that the soybean yield can still meet the constraints and ensure food security when the yield is reduced. The results of this study can provide a reference for adjusting the spatial distribution of staple crops at the provincial level in China from the perspective of food self-sufficiency.

农业是国民经济的支柱产业.农业经济竞争力是农业经济发展表现出的综合能力.该研究根据2017年数据,构建黑龙江省农业经济竞争力评价指标体系,采用3种客观赋权方法改进级差最大化组合赋权模型,综合评价黑龙江省13个地市的农业经济竞争力强弱程度并进行排序,最大可能的拉开被评价对象的差异,并通过组合权重保证了多种评价结果排序的合理性.基于综合评价结果给出提升黑龙江省农业经济竞争力的对策及建议.

生态农业经济竞争力是农业经济发展的综合能力.基于2017年的数据,建立由8个子系统支撑的黑龙江省生态农业经济竞争力系统,构建相应的评价指标体系,采用基于因子分析的系统聚类模型测算黑龙江省13个地市的生态农业经济竞争力强弱程度并进行排序聚类,绘制竞争力分布图.将熵权法与灰色关联度分析结合,计算出各影响因素及子系统核心度.结果 表明,农业科研人员全时当量为核心因素,农业科教支持竞争力为核心竞争力,因此提升农业科技水平是提升黑龙江省生态农业经济竞争力的核心途径.

文章针对日益突出的水土资源生态安全问题,构建DPSIR水土资源生态安全指标体系.在此基础上提出了兼顾指标主客观、相关性与区分度的概念模型,运用层次分析法、熵权法、person相关系数与指标信息贡献率等方法对原始指标体系进行筛选与度量.通过灰色熵权法与综合评价法对2003-2015年黑龙江水土资源生态安全现状进行实例验证.结果显示:原始指标评价结果与核心指标评价结果误差绝对值＜10％、隶属安全等级一致,2003-2011年生态安全等级为Ⅲ级、2012-2015年生态安全等级为Ⅳ级.表明该方法针对多因素指标筛选合理有效,对评价过程中指标冗余问题具有较好的精简能力.

通过对现有文献给出的农村剩余劳动力估算方法中的基准年法、生产函数法、边际收益法、产值比例法、劳均耕地法和生产资源优化配置模型法进行了分析与研究,给出了这些方法的文字描述和数学模型.在此基础上,分析指出了这些方法存在的不足,为进一步深入研究农村剩余劳动力估算方法奠定了理论基础,同时也可为选择农村剩余劳动力估算方法提供理论参考.