农业工程学报
農業工程學報
농업공정학보
2014年
24期
124-132
,共9页
农作物%干旱%模式识别%农业干旱%降水量%平均温度%产量
農作物%榦旱%模式識彆%農業榦旱%降水量%平均溫度%產量
농작물%간한%모식식별%농업간한%강수량%평균온도%산량
crops%drought%pattern recognition%agricultural drought%precipitation%average temperature%yield
为准确判断作物生长发育过程中农业干旱的发生状况,并预估作物产量,该研究以半干旱区1986-2011年生育期气象和产量资料为基础,分析雨养春小麦产量形成所受因素,以产量变动状况作为春小麦干旱和正常年景的判断标准。采用模式识别法,迭代求解建立可预测春小麦年景的线性分类方程,对半干旱雨养区农业干旱的发生状况进行判定。研究结果表明:半干旱雨养区春小麦产量形成受诸多因素影响。若不剔除其他因素的影响,仅以气象要素为基础无法建立判别方程,从而难以定量判断春小麦生育期农业干旱的发生状况。但在剔除播前50 cm层次土壤相对含水率大于55%的年份后,以主要生育期平均温度和降水量能够建立判别方程预测春小麦年景,从而可以对春小麦生长发育过程中的农业干旱发生状况进行定量分析。同时,5月份降水量对春小麦生长发育具有非常重要的作用,在播前50 cm层次土壤相对含水率小于55%时,只用5月份降水量一个气象要素即可较为准确地模拟估测春小麦产出。该研究可为干旱致害机理的进一步深入探讨提供参考依据。
為準確判斷作物生長髮育過程中農業榦旱的髮生狀況,併預估作物產量,該研究以半榦旱區1986-2011年生育期氣象和產量資料為基礎,分析雨養春小麥產量形成所受因素,以產量變動狀況作為春小麥榦旱和正常年景的判斷標準。採用模式識彆法,迭代求解建立可預測春小麥年景的線性分類方程,對半榦旱雨養區農業榦旱的髮生狀況進行判定。研究結果錶明:半榦旱雨養區春小麥產量形成受諸多因素影響。若不剔除其他因素的影響,僅以氣象要素為基礎無法建立判彆方程,從而難以定量判斷春小麥生育期農業榦旱的髮生狀況。但在剔除播前50 cm層次土壤相對含水率大于55%的年份後,以主要生育期平均溫度和降水量能夠建立判彆方程預測春小麥年景,從而可以對春小麥生長髮育過程中的農業榦旱髮生狀況進行定量分析。同時,5月份降水量對春小麥生長髮育具有非常重要的作用,在播前50 cm層次土壤相對含水率小于55%時,隻用5月份降水量一箇氣象要素即可較為準確地模擬估測春小麥產齣。該研究可為榦旱緻害機理的進一步深入探討提供參攷依據。
위준학판단작물생장발육과정중농업간한적발생상황,병예고작물산량,해연구이반간한구1986-2011년생육기기상화산량자료위기출,분석우양춘소맥산량형성소수인소,이산량변동상황작위춘소맥간한화정상년경적판단표준。채용모식식별법,질대구해건립가예측춘소맥년경적선성분류방정,대반간한우양구농업간한적발생상황진행판정。연구결과표명:반간한우양구춘소맥산량형성수제다인소영향。약불척제기타인소적영향,부이기상요소위기출무법건립판별방정,종이난이정량판단춘소맥생육기농업간한적발생상황。단재척제파전50 cm층차토양상대함수솔대우55%적년빈후,이주요생육기평균온도화강수량능구건립판별방정예측춘소맥년경,종이가이대춘소맥생장발육과정중적농업간한발생상황진행정량분석。동시,5월빈강수량대춘소맥생장발육구유비상중요적작용,재파전50 cm층차토양상대함수솔소우55%시,지용5월빈강수량일개기상요소즉가교위준학지모의고측춘소맥산출。해연구가위간한치해궤리적진일보심입탐토제공삼고의거。
The mechanism of the damage process for agricultural drought is very complex, and many factors can affect it. Agricultural drought is the main limiting factor for crop yield in rainfed area. For defining drought occurrence during the crop growth, and predicting crop yield, we used pattern recognition based on meteorological data during growing season and yield data of spring wheat in semi-arid rainfed area in Dingxi, China from 1986 to 2011. Owing to the application of deviation for crop yield from its long-term mean to define agricultural drought, we divided the year pattern into two categories: drought series, and normal series on the basis of 30 percent deviation from the mean wheat yield. The iteration method was then applied in order to find a case wherein the drought could be linearly discriminated from normal category. According to our research, we find the spring wheat yield was affected by various factors. They can be categorized as 1) weather conditions, such as temperature, precipitation;2) farm management factors and crop variety, such as soil tillage, soil depth, planting density, sowing date, crop protection against pests and diseases, and soil fertility level;3) soil conditions, such as soil physical properties and soil water content. Measuring or estimating some of these factors was often not feasible, and the influence of some other factors may be considered insignificant or constant in an agrometeorological experimental station. It was therefore weather condition alone that can affect crop yield most significantly. However, it was found that no linear relation existed in any cases based on average temperature and precipitation during the main growing period without taking other factors into a consideration. After rejecting years in which the soil relative water content was more than 55%, we can predict if agricultural drought through establishing a linear equation with two parameters, the average temperature and precipitation during the main growth period for spring wheat. From the research, we also found the best parameter to predict the agricultural drought occurrence and factor that determined spring wheat yield was the precipitation in May. A Predictive Equation for spring wheat yield was also established by the least square method based on the precipitation in May. The predictive equation was simple but useful, and it can forecast spring wheat yield one and half month earlier before wheat harvest. Meanwhile, it should be noted that the predictive equation was established after rejecting the years in which the soil relative water content was more than 55%. We suggested that the agricultural drought differ from meteorological drought. As such, we should use the method much more carefully for quantitative prediction of agricultural drought occurrence and crop yield in future research.