灌区干旱风险评估模型研究

根据风险理论,建立了包括农业干旱发生概率、抗旱能力、受灾体种植面积比等多因子的灌区农业干旱风险评估模型。并将相对产量作为灌区农业干旱评估指标,能够反映土壤 作物 大气系统中水分运动对农业生产的影响,利用该指标结合干旱风险评估模型对灌区农业干旱进行风险评估,分析出灌区各种作物对干旱风险度影响最大的生育阶段和风险度最高的农作物,以便灌区制定合理的抗旱方案以减小灌区干旱损失。     

The impact of irrigation water supply rate on agricultural drought disaster risk: a case about maize based on EPIC in Baicheng City,China

This study presents a methodology for risk analysis, assessment, and combination of drought disasters under the different irrigational levels in Baicheng City, which is supported by run theory, copula functions, crop growth model, and technique of natural disaster risk assessment from the viewpoints of climatology, geography, hydrology, agricultural science, disaster science, environmental science, and so on. Along with the global warming, the occurrences of water-related disasters become more frequent and more serious. It is necessary to determine the laws of the relationship between irrigational ability and the loss caused by drought. Drought events were identified by using run theory; the drought frequency was calculated by using copula function; the loss of every drought event was simulated by using EPIC model; and the relationship curves under the different irrigational supply conditions between the drought frequency and the yield reduction rate of the drought event were fitted to assess the impact of irrigational supply rate on the loss caused by drought. The results show that in the range of crop water demand, the loss caused by drought decreases as the result of the increase in irrigational supply rate; however, their variations are not proportional. The loss caused by the certain frequency drought event under the certain irrigational supply condition could be calculated by the curve of drought disaster risk assessment constructed by this study. The results obtained from this study are specifically intended to support local and national governmental agencies on agricultural disaster management.     

Dynamic risk assessment of drought disaster for maize based on integrating multi-sources data in the region of the northwest of Liaoning Province, China

The traditional studies on drought disaster risk were based on the ground point data, which were unable to realize the continuity of space and the timeliness. It is shown that the monitoring and evaluation precision on drought were reduced significantly. However, remote sensing data in adequate spatial and temporal resolution can overcome these limitations. It can better monitor the crop in large area dynamically. This study presents a methodology for dynamic risk analysis and assessment of drought disaster to maize production in the northwest of Liaoning Province based on remote sensing data and GIS from the viewpoints of climatology, geography and disaster science. The model of dynamic risk assessment of drought disaster was established based on risk formation theory of natural disaster, and the expression of risk by integrating data came from sky, ground and space. The risk indexes were divided into four classes by data mining method, and the grade maps of drought disaster risk were drawn by GIS. It is shown that the spatial and temporal risk distributions of maize at each growth stage changed over time. The model has been verified against reduction in maize yield caused by drought. It demonstrated the reasonability, feasibility and reliability of the model and the methodology. The dynamic risk assessment of regional drought disaster for maize can be used as a tool, which can timely monitor the status (the possibility and extent of drought) and trends of regional drought disaster. The results obtained in this study can provide the latest information of regional drought disaster and the decision-making basis of disaster prevention and mitigation for government management and farmers.     

Agricultural drought risk analysis based on three main crops in prefecture-level cities in the monsoon region of east China

Drought, a frequent environmental disaster in the monsoon region of east China, significantly affects the agricultural economy. In recent years, researchers have emphasised drought risk management. This paper presents a preliminary method to analyse the risk of agricultural drought with regard to the loss of three main crops in individual prefecture-level cities in the monsoon region of east China. In this study, the agricultural drought risk is assessed by developing the index of consecutive rainless days and establishing loss rate curves based on the historical drought data from 1995 to 2008. The results show that the North China is seriously affected by drought hazard. Northeast China is the most sensitive to drought due to its large sown crop areas and weak irrigation. Approximately 11 % of the cities are in the extreme risk category; this category includes 26 % of the cultivated land area and 11 % of the total crop yields in the region. Twenty-three per cent of the cities, accounting for 28.5 % of the total cultivated land area and 26.4 % of the crop yields of the study area, are in high-risk areas, and 77 % of the cities with high and extreme risk levels are distributed in North and Northeast China. Moreover, 64 % of the cities in the monsoon region of East China are in moderate- and low-risk levels. These cities are primarily located south of the Yangtze River. In conclusion, minimising the risk of agricultural drought must be emphasised in northern China because of the high level of risk.     

农业干旱灾害风险模糊集对评价法及其应用

开展农业干旱灾害风险评估,有利于定量认识农业旱灾和科学指导防旱抗旱工作。基于集对分析原理和模糊理论建立的模糊集对评价法,兼顾了信息的多尺度特征和评价等级的模糊性,概念清晰,计算简洁。构建了由旱灾危险性子系统、旱灾暴露性子系统、灾损敏感性子系统和抗旱能力子系统组成的干旱灾害风险评估体系和评价指标。将模糊集对评价法应用于2012年安徽省亳州市农业干旱灾害风险评估,研究结果表明,建议方法是可靠的,为农业干旱灾害风险评估提供了一种新途径。     

Assessing Vulnerability to Agricultural Drought: A Nebraska Case Study

Recent drought events in the United States and the magnitude of drought losses indicate the continuing vulnerability of the country to drought. Until recently, drought management in many states, including Nebraska, has been largely response oriented with little or no attention to mitigation and preparedness. In 1998, Nebraska began to revise its drought plan in order to place more emphasis on mitigation. One of the main aspects of drought mitigation and planning is the assessment of who and what is vulnerable and why. This paper presents a method for spatial, Geographic Information Systems-based assessment of agricultural drought vulnerability in Nebraska. It was hypothesized that the key biophysical and social factors that define agricultural drought vulnerability were climate, soils, land use, and access to irrigation. The framework for derivation of an agricultural drought vulnerability map was created through development of a numerical weighting scheme to evaluate the drought potential of the classes within each factor. The results indicate that the most vulnerable areas to agricultural drought were non-irrigatedcropland and rangeland on sandy soils, located in areas with a very high probability of seasonal crop moisture deficiency. The identification of drought vulnerability is an essential step in addressing the issue of drought vulnerability in the state and can lead to mitigation-oriented drought management.     

Dynamic risk prediction based on discriminant analysis for maize drought disaster

This study presents a discriminant analysis-based method for prediction of agriculture drought disaster risk. We selected the Chaoyang city in the Northeast China as the study area. We employed multi-scale standard precipitation index (SPI) to reflect drought hazard. We used the yield losses to indicate the drought disaster risk, which was divided into no, low, or high drought risk. We used the multi-scale SPI and drought disaster risk as the input factors for the discriminant analysis-based risk prediction model. The results showed that the model’s prediction accuracy varied between 40 and 82.4 %. The accuracy of high drought disaster risk category was higher than low and no drought disaster risk category. The prediction accuracy of the milky maturity stage was highest. We use leave-one-out cross-validation method to validate the model’s accuracy. And the results showed that the model validation accuracy of high drought group could reach 70.6 % in milky maturity stage. This study showed discriminant analysis is an effective and operable method for disaster risk prediction. This model can provide timely information for decision makers to make effective measures for drought disaster management and to reduce the drought effects to yields at the minimum level.     

中国北方地区几种农业气象灾害指标研究综述

针对我国北方地区常见的几种农业气象灾害:干旱、低温冷害、霜冻和干热风,对其各类指标进行了归纳和描述。干旱指标是从监测、防御、经济损失评估、社会经济发展水平和科技进步5个方面来分别描述;冷害指标就目前常见的几类进行了简要介绍;霜冻指标多针对不同作物给出具体判别标准;干热风指标从气象、判别、危害和防御4个方面进行了描述。总结了不同指标的优缺点,同时也对这些灾害指标目前存在的问题和今后改进的方向提出了看法,为形成北方地区农业气象灾害指标体系奠定基础,同时为今后该地区各类农业气象灾害的监测、评估及防灾减灾工作提供参考与支撑。     

青海省气象干旱对粮食产量的影响及其评估方法研究

气象干旱是青海省发生最为频繁的气象灾害之一, 具有出现频率高、 持续时间长、 影响范围广等特点, 对农业生产造成极大的影响, 严重的干旱少雨之年常使农业大幅度减产, 甚至绝收. 为了研究气象干旱对青海省粮食产量产生的影响, 根据拉格朗日插值方法给出了青海省无干旱时"期望产量"的确定方法, 并据此求算出历年干旱对青海省粮食产量的损失量值, 然后依据农作物不同生育期所发生的干旱的强度、 范围以及作物对干旱的敏感度等关系, 建立了干旱损失量的统计和评估模式. 在2006-2010年青海省粮食产量评估中进行应用, 5 a中有4 a误差小于5%, 仅2006年误差百分率达到-9.38%; 由此, 证明了运用干旱损失评估方法, 可以评估出干旱对粮食产量的损失量, 从而评估出青海省的实际粮食产量, 效果较好, 可以在青海省今后的粮食产量预报和评估中推广应用.     

Severity–duration–frequency curves in the mitigation of drought impact: an agricultural case study

Severity–duration–frequency (SDF) curves are very useful in the analysis of drought phenomena. Station-level information obtained from SDF curves can be interpolated to obtain severity maps for fixed return period, in order to jointly analyse the spatial variability of drought characteristics (e.g. severity, duration and frequency). This approach is limited because the severity is usually quantified through indices that use hydrological and meteorological data, depending on the type of requirements. Therefore, drought indices can only reflect hydrological conditions, but are unable to quantify economic losses associated with droughts. In other words, SDF curves do not allow effective quantification of the impact expected with a certain return period. This paper proposes the methodology drought economic risk assessment (DERA) as an approach that emphasizes the importance of the relationship between a generic drought index (which quantifies water deficit) and the economic impact of the failure to meet water demand. Using integrated SDF curves, this relationship enables drought severity and corresponding impacts to be mapped. This procedure was applied to agricultural droughts (sunflower crop) in Umbria Region (central Italy). The agricultural drought impact variable was identified by sunflower yield (Y); the economic impact variable by net benefit depletion (EL); and the drought index by Relative Severity Index (RSI), which is quantifiable by a soil–water balance model. The relationships Y = g(RSI) and EL = f(Y) were specifically determined. Using DERA, it was possible to derive curves for SDF, impact–duration–frequency, and economic losses–duration–frequency (ELDF), which were then used to map severity, impact and economic losses for the assigned return period and duration. From the ELDF curves, further information was obtained by mapping critical drought durations for the assigned return period and economic loss threshold. The case study supports the potential of the proposed approach, both in the planning and real-time management of drought effects.     

判别分析法在农业旱情识别中的应用

在本文中,作者提出了利用数理统计学中的判别分析法,来进行农业旱情识别的方法,该方法从水文和气象对水量进行识别,以水文、气象和作物受旱三个方面综合起来对农业旱情进行识别。在邵阳市农业干旱研究中应用了判别分析法对当地的农业旱情进行了识别,识别结果与实际情况较为符合。该方法为农业旱情识别提供了一种新的途径。     

Assessment on agricultural drought vulnerability in the Yellow River basin based on a fuzzy clustering iterative model

Drought is one of the major natural disasters occurring in China and causes severe impacts on agricultural production and food security. Therefore, agricultural drought vulnerability assessment has an important significance for reducing regional agricultural drought losses and drought disaster risks. In view of agricultural drought vulnerability assessment with the characteristics of multiple factors and uncertainty, we applied the fuzzy comprehensive evaluation framework to agricultural drought vulnerability model. The agricultural drought vulnerability assessment model was constructed based on the multi-layer and multi-index fuzzy clustering iterative method, which can better reveal the drought vulnerability (including sensitivity and adaptation capacity). Furthermore, the cycle iterative algorithm was used to obtain the optimal index weight vector of a given accuracy by setting the objective function. It provides a new approach to weight determination of agricultural drought vulnerability assessment. In this study, agricultural drought vulnerability of 65 cities (as well as leagues and states) in the Yellow River basin was investigated using a fuzzy clustering iterative model and visualized by using GIS technique. The results showed clear differences and regularities among the spatial distribution of agricultural drought vulnerability of different regions. A large number of the regions in the basin consisted of those exhibiting high to very high vulnerability and were mainly distributed throughout Qinghai, Gansu, northern Shaanxi, and southern Shanxi, accounting for 46 % of the total assessment units. However, the regions exhibiting very high vulnerability were not significantly affected by droughts. Most of the regions exhibiting moderate vulnerability (21.5 % of the assessment units) were mainly concentrated among agricultural irrigation areas, where agriculture is highly sensitive to droughts, and drought occurrence in these regions will likely cause heavy losses in the future. The regions exhibiting slight to low vulnerability were relatively concentrated, accounting for 32.3 % of the assessment units, and were mainly distributed in the plains of the lower reaches of the Yellow River, where the economy was rather well developed and the agricultural production conditions were relatively stronger.     

The agricultural utility of lithic-mulch gardens: Past and present

The mulching of agricultural fields and gardens with stones, pebbles, volcanic ash and similar lithic materials is a variant agricultural strategy uniquely suited to the constraints of a dryland environment. While the agricultural literature contains reports on limited experiments with stone or gravel mulch, data regarding the employment of lithic mulch are lacking. This paper works to bridge this gap by comparing empirical data collected from prehistoric pebble-mulch gardens in the Galisteo Basin (New Mexico) to contemporary agricultural experiments with lithic mulch. Such past-present and experimental-real world comparisons allow us to more fully address the effectiveness of lithic mulching as an agricultural strategy. It is affirmed that lithic mulch is applied to garden plots, especially during periods of drought, in order to reduce soil erosion from wind and water, increase soil temperature to extend the growing season, increase water infiltration, and reduce the evaporative loss of water from wind and sun. The cumulative effect of this soil and water conserving technique is an increase in crop biomass and crop yield.     

"全球农情遥感速报系统(CropWatch)"新进展

目前由中国科学院遥感应用研究所建设和运行的"全球农情遥感速报系统",是世界上开展全球尺度农情遥感业务监测的主要运行系统之一,可以在中国和全球尺度提供作物长势、单产、种植面积、产量和旱情等农情信息.自1998年建设至今,已经发展成为一个独立运行、监测内容全面、技术先进、监测结果可靠,并具有快速响应能力的系统.2004年,<遥感学报>(第8卷第6期)对该系统的主要技术方法进行了系统介绍.2005-2009年,通过对CropWatch的不断完善,提高了系统的独立性和运行效率,并在2008年春季雪灾、汶川地震、2009年冬小麦种植区春季干旱、2010年西南大旱等关键时期发挥了重要作用.详细介绍了2005-2009年间在系统化建设、监测的独立性和系统的应用推广等方面的进展,并对系统在"十二五"期间的发展重点进行了展望.     

国外农情遥感监测系统现状与启示

大范围的可靠农情信息对粮食市场及相关政策的制定至关重要,是保障区域及全球粮食安全的重要依据,在全球气候变化、人口增长、土地利用/覆盖变化剧烈的背景下,对这一信息的需求也更加迫切.传统农情信息的获取依赖于庞大的调查队伍和大量的调查工作,信息的获取存在成本高、时效性差和结果受主观影响大的缺点.伴随着近30年遥感技术本身及其在农情信息获取领域能力的提升,一些国家与国际组织建设了各自的农情遥感监测系统,并开展了运行化的监测.对美国、欧盟、FAO、加拿大、巴西、阿根廷、俄罗斯、印度等主要的农情遥感监测系统进展进行了详细的介绍,并通过对这些系统的分析得到一些农情监测系统建设的启示.指出作物种植面积估算、单产预测、长势监测、旱情监测是农情遥感监测中最主要的4个主题.在面积估算方面,各个系统在遥感技术不断发展的同时对地面调查的依赖并没有减少,甚至得到了强化,这与遥感降低地面调查的初衷相违背,导致遥感技术在大范围农情监测中的潜力没有得到充分发挥,在单产预测方面,需要发展独立的遥感预测方法.提升遥感的作用是未来一段时间内农情遥感监测系统建设的主要方向.     

Risk assessment to China’s agricultural drought disaster in county unit

China faces drought disaster risk under the changing climate. Risk analysis is a suitable approach in order to design ex-ante measure able to anticipate effects of drought on agricultural production. In this article, with the support of historic drought disaster data from 583 agro-meteorological observations (1991–2009), a risk analysis method based on information diffusion theory was applied to create a new drought risk analysis model, and the risk of China’s agriculture drought disaster was evaluated on higher spatial resolution of county unit. The results show that in more than three hundred counties of China, risk probability was biyearly or annually when Drought Affected Index (DAI) was over 5%. When DAI was up to 40%, more than one hundred counties were prone to drought disaster annually or once every 5 years. This showed that the impact of drought disaster on China’s agriculture, whether in frequency or intensity, was large. With the different level of DAI, China’s agricultural drought risk pattern showed variable pattern characteristics. When DAI was low, the distribution of county agricultural drought risk in China presented the East–West pattern of differentiation, and high risk mainly lied in the eastern, low risk mainly in the western. On the other hand, when DAI was high, the distribution of county risk appeared a pattern of high in center, and the north areas higher than the south, increased gradually from southwest to northeast. Drought risk presents a clear zonal differentiation that may be result from stepped topography, different precipitation and hazard-affected bodies. Spread of high value area of drought risk in northern may be related to the southeast monsoon and ecological degradation in northern Ecotone.     

Assessment of regional drought vulnerability and risk using principal component analysis and a Gaussian mixture model

Due to the complex characteristics of drought, drought risk needs to be quantified by combining drought vulnerability and drought hazard. Recently, the major focus in drought vulnerability has been on how to calculate the weights of indicators to comprehensively quantify drought risk. In this study, principal component analysis (PCA), a Gaussian mixture model (GMM), and the equal-weighting method (EWM) were applied to objectively determine the weights for drought vulnerability assessment in Chungcheong Province, located in the west-central part of South Korea. The PCA provided larger weights for agricultural and industrial factors, whereas the GMM computed larger weights for agricultural factors than did the EWM. The drought risk was assessed by combining the drought vulnerability index (DVI) and the drought hazard index (DHI). Based on the DVI, the most vulnerable region was CCN9 in the northwestern part of the province, whereas the most drought-prone region based on the DHI was CCN12 in the southwest. Considering both DVI and DHI, the regions with the highest risk were CCN12 and CCN10 in the southern part of the province. Using the proposed PCA and GMM, we validated drought vulnerability using objective weighting methods and assessed comprehensive drought risk considering both meteorological hazard and socioeconomic vulnerability.

     

气象干旱对青海牧草产量的影响及其在产量预报中的应用

研究了降水偏少造成的气象干旱对青海省牧草产量的影响,得出牧草生长季降水与产量的关系模式,计算出气象干旱造成的牧草产量损失量。但该方法模拟误差较大,且不能满足牧草产量预报、草场载畜量确定和牲畜出栏率确定等牧业生产服务需求。因此,根据拉格朗日插值方法给出了青海省无干旱时“未受旱产量”的确定方法,并据此求算出历年干旱对青海省牧草产量的损失量值,然后依据天然牧草不同生育期发生干旱的强度、范围以及牧草对干旱的敏感度等关系,建立了干旱损失量的统计和评估模式。在2013-2015年青海省曲麻莱县牧草产量评估中进行了应用,3年的误差在3.59%～6.02％之间,证明了该方法可以评估出研究区干旱对牧草产量的损失量,从而评估出实际牧草产量。拉格朗日插值方法效果较好,可以在青海省今后的牧草产量预报、草场载畜量预报、牲畜出栏率确定等畜牧业生产评估中推广应用。     

Drought hazard assessment using geoinformatics over parts of Chotanagpur plateau region, Jharkhand, India

Recurrent drought events in the Palamu district of Jharkhand state and the magnitude of drought losses primarily toward agricultural production in this dominantly monocropped region indicate the continuing susceptibility of the society to drought. This paper presents a method for spatial, geoinformatics-based assessment of agricultural, meteorological, and hydrological drought hazard in Palamu district. It was hypothesized that the key climatic, biophysical and social factors that define agricultural drought hazard were soils, geomorphology, drainage density, land use, and relief, whereas for meteorological drought hazard, it is rainfall, coefficient of variation of rainfall and for hydrological drought hazard, it is lithology, depth to water table, aquifer yield, and surface water bodies. The framework for the derivation of an agricultural, meteorological, and hydrological drought hazard map was created through the development of a numerical weighting scheme to evaluate the drought potential of the classes within each factor. A cumulative map created through spatial join of all the three types of drought provided a drought hazard scenario in totality. The area with different severity of drought hazards under cumulative drought hazards scenario (viz. very low (8.9?%), low (24.2?%), moderate (29.2?%), high (20.13), and very high (17.3?%)) revealed high drought proneness of the area and the usefulness of geoinformatics in better spatial prognosis of drought hazards.