供应中断下具有随机需求的闭环供应链最优差别定价模型

研究了在供应中断下具有随机需求的闭环供应链系统的最优差别定价模型.基于博弈论的理论和方法分别在集中式和分散式决策情形下,确定了最优批发价、最优销售价、最优订购量及系统利润. 最后通过数值例子对最优差别定价模型进行了实证分析.     

基于双区间两阶段随机规划的黑河中游主要农作物种植结构优化

为优化有限农业水资源量下的种植结构以实现最大经济效益,考虑种植结构优化过程中存在的水文要素与社会经济要素中存在的不确定性,构建以经济效益最大为目标的双区间两阶段随机规划模型。在农业水资源量测算时出现了双区间特点,故使用双区间理论对农业水资源量进行表征计算。将构建的模型用于黑河中游甘肃省张掖市甘州区、临泽县、高台县的5种水文年(枯水年、较枯水年、平水年、较丰水年以及丰水年)下的种植结构优化,比较了优化结果与现状水平年种植结构与经济收益。结果表明:通过双区间两阶段随机规划模型得到的3种种植结构优化方案即保守决策方案、趋于平均决策方案和乐观决策方案产生的经济效益比现状水平年种植结构下的经济效益分别提高[1.97,8.53]、[4.20,11.04]、[6.43,13.56]亿元。     

ICP-AES法测定水溶肥料中硼含量的不确定度分析

对ICP-AES测定水溶肥料中硼的分析方法的测量不确定度进行了分析;建立了测定过程中各分量的数学模型,并识别了测量过程中不确定度来源;估算了各不确定度分量对总不确定度的影响,确定了测量结果的置信区间;给出了水溶肥料中硼的含量及其不确定度:w (B)=（0.553±0.042）%（k=2）。     

基于改进的标准化降水指数的黄河中游干旱情势研究

提出了一种基于旬累积尺度的月标准化降水指数(SPI)计算方法,该方法不仅考虑了前期降雨量对区域当前旱情的影响,因而对旱情的评估更为客观,同时在实际应用中更具有时间上的灵活性,更能体现气象干旱的累积效应和预报的时效性。计算了黄河中游山西省境内近40a(1971-2009年)各旬干旱指数,分析结果表明改进的标准化降水指数能够很好地表征黄河中游山西省境内的历史旱情状况。引入国际上常用的多种未来气候情景,研究分析了未来气候变化下2021-2050年黄河中游山西省境内地区旱情发展的可能情势,结果表明其存在对农业不利影响加重的可能,需要引起水资源管理部门的重视。     

百草枯水剂中百草枯含量测量不确定度评估

测定农药百草枯水剂中百草枯的含量,分析评定测量过程的不确定度来源,计算合成不确定度,并给出百草枯测量不确定度表达式.     

Optimizing Phosphorus and Potassium Fertilizer Recommendations using Spatial Uncertainty Assessments

Abstract

Variable‐rate nutrient management relies on soil fertility maps, yet the associated uncertainty is typically ignored in developing recommendations. In this article, ordinary kriging (OK) and several alternatives that rely on local estimates of uncertainty derived via probability kriging (PK) are evaluated for developing phosphorus (P) and potassium (K) fertilizer recommendations, using soil data collected at two different intensities. A decision support framework that incorporates economic and agronomic criteria to derive block‐average optimal quantile estimates (Opt Q) maximized net return for an 8‐year fertilization program. The economic results show an increase of $7.31 ha^?1 and $1.04 ha^?1 for P and K fertilization, respectively, using Opt Q rather than OK with the 0.2‐ha sampling grid and $14.79 ha^?1 and $8.93 ha^?1 for P and K fertilization, respectively, using the 0.5‐ha sampling grid. These results illustrate the importance of accounting for estimation uncertainty in developing variable‐rate fertilizer recommendations.     

基于不确定性理论的区域土地利用结构优化

为了还原土地利用结构优化的不确定环境,提高土地利用结构优化水平,同时为了开拓土地利用结构优化的新视角,该文基于不确定性对土地利用结构进行优化。该文将基于不确定性的土地利用结构优化分为不确定因素最可能发生时的优化与不确定因素在一定发生可能范围时的优化,前者的优化结果是单一的土地利用结构,后者的优化结果是土地结构弹性区间。首先用期望值模型求取不确定因素最可能发生时的土地优化结构;其次以多目标遗传算法为基础,用随机模拟法求取不确定因素在一定发生可能范围时的优化结构弹性区间。结果表明:不确定因素最可能发生时,扬州2020年土地最优结构的经济利益、生态利益分别是10.0×1011和8.98×1011元,大于现状土地结构与扬州土地利用总体规划中土地结构的经济与生态利益;2020年扬州市土地利用优化结构弹性区间中,对不确定性承纳贡献最大的土地类型是耕地、城镇工矿用地、园地,对不确定因素敏感性最高的土地类型是林地、园地、交通水利用地。该研究为土地利用类型弹性区间大小划定及土地利用结构调整提供依据。     

基于证据理论和可变模糊集的成都市洪灾风险评估

洪灾系统的高维性和不确定性,给灾害风险评估带来较多困难,为了提高评估的准确性和合理性,实现科学灾害管理,该文将Dempster_Shafer证据理论应用到洪水灾害风险评估中,同时利用可变模糊集理论来构造证据理论基本信任分配,实现了客观合理的证据建模,最后利用经典组合原理进行证据组合。以成都市区2012年风险等级的计算为例,风险为高等级时的信任区间为[0,0.52],似然区间为[0,0.54],不确定大小为0.019,根据判断规则,确定市区2012年的洪灾风险等级为高。基于此方法采用相同处理,对研究区成都市风险等级的时空分布进行了计算分析。结果表明该方法能够较好地融合洪水灾害系统各方面信息以及处理风险评估中的不确定性,实现了洪灾风险的准确评估。     

Digital assessments of soil organic carbon storage using digital maps provided by static and dynamic environmental covariates

Understanding the vertical and lateral distribution of soil organic carbon (SOC) and soil organic carbon density (SOCD) is indispensable for soil use and environmental management because of their vital role in soil quality assessments. Primarily, they are needed in calculating soil organic carbon storage (SOCS). The objective of this research was to provide digital maps of SOC and SOCD variation as well as their uncertainties at multiple standardized depths (H1: 0–5, H2: 5–15, H3: 15–30, H4: 30–60 and H5: 60–100 cm) using a parsimonious model with optimized terrain-related attributes and satellite-derived data. SOCS were evaluated at soil subgroup levels. An area of about 808 km² with varying elevation, plant cover and lithology from the Miandoab region, West Azerbaijan Province, Iran was selected as a case study area. A total of 386 soil samples were collected from 104 profiles comprising various soil genetic horizons. A continuous spline function was then fitted to the target properties in advance of creating a dataset at five standard depth intervals (following the GlobalSoilMap project). These were then grouped into three classes including top (H1), middle (H2, H3 and H4) and bottom (H5) depths to ease interpretation. Static and dynamic covariates (30-m resolution) were derived from a digital elevation model (DEM) and a suite of Landsat-8 spectral imageries, respectively. Four candidate models including stepwise multiple linear regression (SMLR), random forest (RF), cubist (CU) and extreme gradient boosting (XGBoost) Tree were tested in this study. Finally, the digital maps at 30-m resolution of SOC and SOCD and their uncertainties were prepared using the best-fit model and the bootstrapping method, respectively. Four soil subgroups (Gypsic Haploxerepts, Typic Calcixerepts, Typic Haploxerepts and Xeric Haplocalcids) were identified across the study area. The covariates had variable contributions on the evaluated models. The XGBoost Tree model generally outperformed other models for prediction of SOC and SOCD (R² = 0.60, on average). Regardless of soil subgroups, the uncertainty analysis showed that the SOCD map had a low prediction interval range value indicating high accuracy. Additionally, the highest SOCS and SOCD was observed at the top followed by middle and bottom depths in the study area. All subgroups exhibited a decreasing trend of SOCD with increasing depth. A similar trend was also observed for SOCS. The highest SOCD (on average) was observed in Gypsic Haploxerepts (4.71 kg C/m²) followed by Typic Calcixerepts (4.46 kg C/m²), Typic Haploxerepts (4.45 kg C/m²) and Xeric Haplocalcids (4.40 kg C/m²). Overall, the SOCS normalized by area within soil order boundaries was greater in Inceptisols than Aridisols across the study area. The findings of this study provide critical information for sustainable management of soil resources in the area for agricultural production and environmental health in the Miandoab region of Iran.     

Agricultural zinc fluxes into soils and crops of central Iran at regional scale

Mass flux assessment can provide information that is essential for a sustainable management of elements in agricultural soils. In this article, we present an assessment of regional-scale averages of zinc (Zn) fluxes into agricultural soils and crops of central Iran for the period 1997–2011, using available databases such as regional agricultural statistics. The basic units of the balances were 15 townships of the provinces Qom, Isfahan and Fars. Averaged over the entire study region, the net Zn input into arable soil resulting from all fertilizer inputs – Zn removal with harvested crops was 1515 g ha^?1 yr^?1 across the entire region, with a range of 438–3009 g ha^?1 yr^?1 among townships. Estimated average Zn inputs with manure, mineral fertilizers, sewage sludge and compost were 1254, 531, 19 and 7 g ha^?1 yr^?1, respectively. The input-to-output ratio of these fluxes ranged from 1.8 to 12.9 among townships and averaged 6.1 for the entire study area. Considering that outputs other than with crop harvests are minor, Zn stocks are rapidly building up in the soils of the study region. Uncertainties in the manure and crop removal data were the main sources of estimation uncertainty in this study.