發(fā)布時間：2018-05-04 16:55

  本文選題：土壤含水量 + 降水量�。� 參考：《生態(tài)學雜志》2017年12期

【摘要】：迄今為止,墑情診斷與預測模型由于缺乏通用性難以應用。本文介紹專欄6個獨立模型中的差減統(tǒng)計法模型。差減統(tǒng)計法模型中2次監(jiān)測的土壤含水量變化量為因變量,土壤初始含水量和時段降水量(含灌溉量)為自變量。應用7個省23個縣87個監(jiān)測點2012—2014年的數(shù)據(jù)建模,應用2015年的數(shù)據(jù)進行驗證。結(jié)果表明:差減統(tǒng)計法模型診斷和預測合格率達90%左右,表明該模型適用性好;合格率高的主要原因是該模型遵循質(zhì)量守恒定律和統(tǒng)計學規(guī)律;差減統(tǒng)計法預測誤差主要來源于異地降水量數(shù)據(jù)和缺少灌溉記錄數(shù)據(jù)。與傳統(tǒng)模型相比,差減統(tǒng)計法具有以下特點:參數(shù)少、參數(shù)容易獲得,參數(shù)具有統(tǒng)計意義、模型覆蓋全部降水量范圍、模型按點建模不受下墊面因素影響等。因此,差減統(tǒng)計法模型作為墑情診斷和預報模型是科學和實用的,可以單獨使用。
[Abstract]:So far, it is difficult to apply soil moisture diagnosis and prediction model due to lack of generality. This paper introduces the statistical model of difference subtraction in six independent models. The variation of soil water content twice monitored in the model was dependent, and the initial soil water content and precipitation (including irrigation amount) were independent variables. The data from 87 monitoring points in 23 counties in 7 provinces were used to model the data from 2012 to 2014, and the data from 2015 were used to verify the model. The results show that the qualified rate of diagnosis and prediction of the model is about 90%, which indicates that the model has good applicability, and the main reason for the high qualified rate is that the model follows the law of conservation of quality and the law of statistics. The prediction error of subtractive statistical method is mainly derived from precipitation data and lack of irrigation record data. Compared with the traditional model, the difference subtraction statistical method has the following characteristics: few parameters, easy to obtain, the parameters have statistical significance, the model covers the whole range of precipitation, the model is not affected by the underlying surface factors, and so on. Therefore, the statistical model of difference subtraction is scientific and practical as the model of moisture diagnosis and forecast, and can be used separately.
【作者單位】： 農(nóng)業(yè)部環(huán)境保護科研監(jiān)測所;北部灣環(huán)境演變與資源利用教育部重點實驗室(廣西師范學院)廣西地表過程與智能模擬重點實驗室(廣西師范學院);
【基金】：天津市科技支撐計劃項目(15ZCZDNC00700) “中國農(nóng)業(yè)科學院科技創(chuàng)新工程”項目(2016-cxgc-hyl) 廣西科技開發(fā)項目(14125008-2-24) 全國農(nóng)業(yè)技術推廣中心節(jié)水處項目(2016-hx-hyl-5)資助
【分類號】：S152.7
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本文編號：1843835