陳世超,劉文豐,杜太生
基于水氮管理與種植結(jié)構(gòu)優(yōu)化的作物豐產(chǎn)高效管理策略
陳世超,劉文豐,杜太生※
(1. 中國(guó)農(nóng)業(yè)大學(xué)中國(guó)農(nóng)業(yè)水問(wèn)題研究中心,北京 100083;2. 甘肅武威綠洲農(nóng)業(yè)高效用水國(guó)家野外科學(xué)觀測(cè)研究站,武威 733000)
河西走廊農(nóng)業(yè)生產(chǎn)受到水資源短缺與農(nóng)業(yè)資源利用效率低的限制,制約著該地區(qū)的種子、糧食生產(chǎn)與農(nóng)業(yè)可持續(xù)發(fā)展戰(zhàn)略。該研究構(gòu)建了考慮作物水氮需求量、降雨量、土壤初始含氮量的水氮管理制度優(yōu)化方法,并結(jié)合所構(gòu)建的考慮空間尺度作物產(chǎn)量與水氮利用效率的多目標(biāo)種植結(jié)構(gòu)優(yōu)化方法,為河西走廊制種玉米、大田玉米和小麥制定豐產(chǎn)高效的水氮管理與種植結(jié)構(gòu)調(diào)整策略,從而實(shí)現(xiàn)作物產(chǎn)量和水氮利用效率的協(xié)同提升。結(jié)果顯示:優(yōu)化的水氮管理制度相比管理現(xiàn)狀可減少單位面積灌水量9.1%~27.3%、施氮量26.6%~50.0%;以作物產(chǎn)量和水氮利用效率最大為目標(biāo),以種植面積、產(chǎn)量需求和水氮投入量為約束,調(diào)整制種玉米、大田玉米和小麥的種植面積與空間分布,優(yōu)化后制種玉米和小麥種植面積減少、大田玉米種植面積增加,總種植面積減少4 874.8 hm2,且作物種植空間分布較優(yōu)化前差異明顯;水氮管理與種植結(jié)構(gòu)優(yōu)化協(xié)同作用可以在水氮用量分別減少0.29×109m3和3.36×107kg的情況下,作物總產(chǎn)量提升0.16×109kg,區(qū)域灌溉水生產(chǎn)力和氮肥利用效率分別提升0.62 kg/m3和18.97 kg/kg。該研究可以為產(chǎn)糧區(qū)和缺水區(qū)的作物豐產(chǎn)高效和農(nóng)業(yè)可持續(xù)發(fā)展提供科學(xué)指導(dǎo)與決策參考。
作物;灌溉;優(yōu)化;種植結(jié)構(gòu);水氮管理;灌溉水生產(chǎn)力;氮肥利用效率
河西走廊是中國(guó)重要的玉米制種基地,豐富的光熱資源是該地區(qū)成為制種和糧食基地的重要資源保障,年產(chǎn)玉米種子約63萬(wàn)t;同時(shí)該區(qū)域也是重要的商品糧基地,以甘肅省18%的耕地生產(chǎn)了全省約40%的大田玉米和小麥。然而水資源短缺、水肥利用效率低、農(nóng)業(yè)布局不合理與生態(tài)脆弱嚴(yán)重制約著農(nóng)業(yè)可持續(xù)發(fā)展[1]。面對(duì)日益增長(zhǎng)的糧食需求,如何優(yōu)化區(qū)域水氮管理制度和作物種植結(jié)構(gòu),是實(shí)現(xiàn)河西走廊制種玉米、大田玉米和小麥豐產(chǎn)高效的關(guān)鍵,也是河西走廊農(nóng)業(yè)可持續(xù)發(fā)展與生態(tài)環(huán)境良性循環(huán)的必然要求。
優(yōu)化灌溉施氮制度是提高水氮利用效率和生產(chǎn)率的重要措施[2],已有研究在田間尺度上基于試驗(yàn)與模型對(duì)河西走廊制種玉米、大田玉米和小麥豐產(chǎn)高效制定了水氮管理策略。如趙建華等[3-4]基于田間試驗(yàn)發(fā)現(xiàn)灌水量為330~450 mm、施氮量為150~225 kg/hm2可以使制種玉米產(chǎn)量、水分利用效率和氮利用效率分別提升13%、20%和32%;Xiao等[5]基于田間試驗(yàn)確定了410~450 mm灌水量和140~180 kg/hm2施氮量可以綜合提升大田玉米生產(chǎn)、經(jīng)濟(jì)和環(huán)境效益;Yang等[6]基于田間試驗(yàn)確定了小麥最優(yōu)灌水量為274 mm、施氮量為180 kg/hm2,與Li等[7]在河西走廊石羊河流域的優(yōu)化結(jié)果相似。作物對(duì)水分與氮素的實(shí)際需求量是水氮管理制度優(yōu)化的基礎(chǔ),并與氣候條件與土壤養(yǎng)分相關(guān),存在區(qū)域異質(zhì)性[8]。上述田間尺度的試驗(yàn)與模擬結(jié)果可以為區(qū)域尺度作物水氮管理提供參考,但如何考慮氣候、土壤的空間變異特征從而在區(qū)域尺度上為不同作物優(yōu)化水氮管理制度,還需要進(jìn)一步研究。
種植結(jié)構(gòu)優(yōu)化是實(shí)現(xiàn)區(qū)域水資源與土地資源優(yōu)化配置的基礎(chǔ),對(duì)于水資源短缺、種植結(jié)構(gòu)不合理的地區(qū)尤為重要[9]。通過(guò)優(yōu)化區(qū)域不同作物種植面積與空間分布,可對(duì)水資源、土地資源的合理配置,實(shí)現(xiàn)生產(chǎn)效益、環(huán)境效益和經(jīng)濟(jì)效益的最大化。隨著智能算法的發(fā)展,種植結(jié)構(gòu)優(yōu)化方法由灰色分析法、目標(biāo)權(quán)重法等發(fā)展到遺傳算法[10]、粒子群算法[11]等。Liu等[12]結(jié)合SWAT(Soil and Water Assessment Tool)模型和元胞自動(dòng)機(jī)模型優(yōu)化了黑河中上游地區(qū)小麥、玉米、棉花、大麥、油菜和苜蓿的種植結(jié)構(gòu),實(shí)現(xiàn)了作物水分生產(chǎn)力、經(jīng)濟(jì)水分生產(chǎn)力和養(yǎng)分水分生產(chǎn)力的協(xié)同提升。種植結(jié)構(gòu)優(yōu)化可以實(shí)現(xiàn)水資源的空間優(yōu)化配置,而與灌溉制度優(yōu)化相結(jié)合則可以進(jìn)一步提升作物產(chǎn)量和農(nóng)業(yè)資源利用效率[13]。但目前在區(qū)域尺度上不同作物水氮管理制度優(yōu)化與作物種植結(jié)構(gòu)優(yōu)化的研究仍較少。
因此,本研究以河西走廊制種玉米、大田玉米和小麥為研究對(duì)象,以作物產(chǎn)量、灌溉水生產(chǎn)力和氮素利用效率協(xié)同提升為目標(biāo),考慮土壤養(yǎng)分含量和作物生育期內(nèi)氣候條件,優(yōu)化不同作物水氮管理制度與種植結(jié)構(gòu),在確保作物產(chǎn)量的同時(shí)減少農(nóng)業(yè)水氮投入量,為河西走廊作物豐產(chǎn)高效與綠色發(fā)展提供科學(xué)指導(dǎo)與決策參考。
河西走廊位于甘肅省西北部(37°17′~42°48′ N,92°12′~104°20′ E),面積約27萬(wàn)km2,行政區(qū)劃主要包含武威、張掖、金昌、嘉峪關(guān)和酒泉5個(gè)地級(jí)市共20個(gè)縣(區(qū))(圖1)。河西走廊屬于溫帶大陸性氣候,年均氣溫7.6 ℃,年日照時(shí)數(shù)為3 000 h,年均降水量為130 mm,年均蒸發(fā)量為2 000 mm,且光熱資源豐富,有利于農(nóng)作物生長(zhǎng)發(fā)育;灌溉農(nóng)業(yè)發(fā)達(dá),年產(chǎn)玉米種子占全國(guó)大田玉米年用種量50%以上,同時(shí)是甘肅省重要的商品糧種植基地和經(jīng)濟(jì)作物生產(chǎn)基地。
圖1 河西走廊高程和氣象站點(diǎn)空間分布圖
本文以河西走廊為研究區(qū)域,以制種玉米(先玉335)、大田玉米(強(qiáng)盛51)和小麥(永良4)為研究對(duì)象。歷史氣象數(shù)據(jù)采用“中國(guó)區(qū)域地面氣象要素驅(qū)動(dòng)數(shù)據(jù)集1979—2018(China Meteorological Forcing Dataset,CMFD)”[14],空間分辨率為0.1°;土壤理化性質(zhì)采用“世界土壤數(shù)據(jù)庫(kù)(Harmonized World Soil Database,HWSD)”[15],空間分辨率為1 km;作物種植面積采用“作物空間分配模型數(shù)據(jù)集(Spatial Production Allocation Model,SPAM-2010)”[16],空間分辨率為5′,基于河西走廊5個(gè)地級(jí)市(武威、張掖、金昌、嘉峪關(guān)和酒泉)統(tǒng)計(jì)年鑒(1979—2018)中各縣(區(qū))制種玉米、大田玉米和小麥的種植面積進(jìn)行校驗(yàn);縣級(jí)尺度3種作物單位面積產(chǎn)量、灌水施氮量、種植面積數(shù)據(jù)取自《甘肅發(fā)展年鑒(1979—2018)》和河西走廊5個(gè)地級(jí)市的統(tǒng)計(jì)年鑒(1979—2018);制種玉米、大田玉米與小麥的實(shí)測(cè)產(chǎn)量數(shù)據(jù),來(lái)自于甘肅武威綠洲農(nóng)業(yè)高效用水國(guó)家野外科學(xué)觀測(cè)研究站和甘肅省農(nóng)科院張掖節(jié)水農(nóng)業(yè)試驗(yàn)站開展的多年不同水氮處理試驗(yàn)數(shù)據(jù)。鑒于土壤、氣候、作物分布數(shù)據(jù)的空間尺度與分辨率不一致,使用ArcGIS 10.6(ESRI,USA)基于河西走廊區(qū)域面數(shù)據(jù)按區(qū)域提取各數(shù)據(jù)集,使用氣候數(shù)據(jù)處理軟件CDO(Climate Data Operators:https://code.mpimet.mpg.de/projects/cdo)中的一階保守重映射[17]將各數(shù)據(jù)集重采樣至5′的空間分辨率。
1.3.1 APSIM-Maize和APSIM-Wheat模塊及其參數(shù)率定
APSIM(Agricultural Production Systems sIMulator)模型是由澳大利亞農(nóng)業(yè)生產(chǎn)系統(tǒng)研究組(APSRU)開發(fā)的可以模擬農(nóng)業(yè)系統(tǒng)生物物理和化學(xué)過(guò)程機(jī)理及其對(duì)氣候變化響應(yīng)規(guī)律的作物生長(zhǎng)模型。其中,土壤、作物與管理模塊決定作物可利用水分和養(yǎng)分,進(jìn)而影響作物的光合速率與生育進(jìn)程并最終影響產(chǎn)量,因此,APSIM模型可以精確模擬不同水氮管理情景下的作物產(chǎn)量。本文使用APSIM version7.10進(jìn)行模擬,通過(guò)R語(yǔ)言中的CroptimizR程序包[18]在APSIM中構(gòu)建制種玉米品種并校正關(guān)鍵參數(shù),同時(shí)校正大田玉米和小麥的關(guān)鍵參數(shù)。為實(shí)現(xiàn)區(qū)域尺度的模型模擬,使用Python語(yǔ)言編程批量調(diào)用APSIM模型,實(shí)現(xiàn)區(qū)域每個(gè)柵格批量輸入、模擬、輸出。
1.3.2 模型評(píng)價(jià)指標(biāo)
采用歸一化均方根誤差(nRMSE)和確定性系數(shù)(2)評(píng)價(jià)APSIM模型在河西走廊對(duì)制種玉米、大田玉米和小麥的適用性。
1.3.3 水氮管理制度優(yōu)化方法
河西走廊農(nóng)業(yè)生產(chǎn)中目前存在嚴(yán)重的水氮過(guò)量施入情況[19]。該區(qū)域?yàn)楣喔绒r(nóng)業(yè),作物生長(zhǎng)所需水量主要來(lái)源于灌溉水和作物生育期內(nèi)降水,而所需氮元素主要來(lái)自于追施氮肥和土壤初始含氮量。河西走廊地下水埋深平均值約11.7 m,部分地區(qū)地下水埋深超過(guò)20 m[20]。因此,本研究基于氣象與土壤養(yǎng)分?jǐn)?shù)據(jù)優(yōu)化區(qū)域尺度3種作物的水氮投入量,模擬中忽略地下水位動(dòng)態(tài)變化。
1)不同作物區(qū)域尺度灌水量
作物生育期內(nèi)灌水量根據(jù)作物耗水量和降水量確定。其中,作物耗水量由單作物系數(shù)法確定[21]。
式中ET為逐日標(biāo)準(zhǔn)條件(非脅迫)下的作物耗水量,mm;K為作物系數(shù),研究表明作物系數(shù)在時(shí)間和空間尺度上的變異程度較弱[22],因此在區(qū)域尺度上使用統(tǒng)一的K:大田玉米和小麥前期、中期、后期的K使用FAO-56提供的參考值[21],制種玉米前期、中期、后期的K參考Jiang等[23]研究結(jié)果。ET0為參考作物蒸發(fā)蒸騰量(mm),由于APSIM模型中使用Priestley-Taylor法[24]計(jì)算ET0,本研究中也將使用該方法,所涉及的變量均可根據(jù)“中國(guó)區(qū)域地面氣象要素驅(qū)動(dòng)數(shù)據(jù)集1979—2018(CMFD)”數(shù)據(jù)集獲得或計(jì)算得到,計(jì)算公式為
式中為Priestley-Taylor系數(shù),取值為1.26;為干濕度計(jì)常數(shù),kPa/℃;△為飽和水汽壓與溫度關(guān)系曲線上的斜率,kPa/℃;R為植被表面凈輻射量,W/m2;為土壤熱通量,W/m2。
河西走廊每個(gè)柵格內(nèi)灌水量為
式中Irr、ET和P分別為第個(gè)柵格內(nèi)第(=1,2,3)種作物的灌水量、耗水量和作物生育期內(nèi)降雨量,mm;為農(nóng)田灌溉水利用系數(shù),本文取0.53[25]。
2)不同作物區(qū)域尺度施氮量
作物生育期內(nèi)施氮量根據(jù)作物吸氮量和土壤含氮量確定。其中,作物吸氮量由作物氮濃度和生物量累積曲線確定。
式中NU為作物吸氮量,kg/hm2;Bio為作物生物量,kg/hm2;N為作物氮濃度,依據(jù)Liang等[26]的研究結(jié)果,確定制種玉米、大田玉米和小麥成熟期N分別為1.4%、1.1%和1.6%。作物生物量累計(jì)曲線基于Logistic曲線確定[27]。
式中GDD為有效積溫,℃;Biomax為作物最大生物量,kg/hm2,根據(jù)田間實(shí)測(cè)數(shù)據(jù),對(duì)制種玉米、大田玉米和小麥分別取值為29 800 kg/hm2[3]、44 532 kg/hm2[28]和26 379 kg/hm2[6]。因此,河西走廊每個(gè)柵格內(nèi)施氮量為
式中Nfer、NU和NS分別為在第個(gè)柵格內(nèi)第種作物的施氮量、吸氮量和土壤含氮量,單位均為kg/hm2;為氮肥利用效率,本文取0.75[29]。土壤含氮量數(shù)據(jù)來(lái)自世界土壤數(shù)據(jù)庫(kù)(Harmonized World Soil Database,HWSD)數(shù)據(jù)集。
1.4.1 種植結(jié)構(gòu)優(yōu)化模型構(gòu)建
1)目標(biāo)函數(shù)
①作物產(chǎn)量最大目標(biāo)函數(shù)為
式中=1,2,3分別對(duì)應(yīng)制種玉米、大田玉米和小麥;Y為在第個(gè)柵格內(nèi)第種作物的單位面積產(chǎn)量,kg/hm2;A為在第個(gè)柵格內(nèi)第種作物的種植面積,hm2;sum為研究區(qū)內(nèi)3種作物總產(chǎn)量,kg。
②灌溉水生產(chǎn)力、氮肥利用效率最大目標(biāo)函數(shù)
式中WPIaver和NUEaver分別為研究區(qū)域灌溉水生產(chǎn)力(kg/m3)和氮素利用效率(kg/kg)的平均值。
2)約束條件
①作物種植面積約束
式中CAsum為3種作物種植總面積現(xiàn)狀,hm2。參考Lalehzari等[30]的研究成果,設(shè)置優(yōu)化后每個(gè)柵格內(nèi)3種作物的種植面積的變化幅度均小于30%,即
當(dāng)CA=0時(shí),上述約束條件無(wú)效,因此設(shè)置以下約束
式中CA為在第個(gè)柵格內(nèi)第種作物的種植面積現(xiàn)狀,hm2;min和max分別為河西走廊柵格編號(hào)的最小值和最大值。
②農(nóng)業(yè)水氮用量約束
式中Irrsum和Nfersum分別為研究區(qū)域種植3種作物所需灌溉總水量m3和總施氮量kg。以《甘肅發(fā)展年鑒(1979 —2018)》3種作物總水氮用量最大值為約束上限,設(shè)置Irrsum=1.49×109m3,Nfersum=9.7×107kg。
③作物產(chǎn)量約束
式中1sum、2sum和3sum分別為研究區(qū)域內(nèi)制種玉米、大田玉米和小麥的生產(chǎn)下限,kg。基于《甘肅發(fā)展年鑒》中的糧食產(chǎn)量數(shù)據(jù)與《振興河西國(guó)家玉米繁育制種基地實(shí)施方案》所提出的玉米種子生產(chǎn)需求,設(shè)置1sum、2sum、3sum分別為0.61×109,0.81×109,0.82×109kg。
1.4.2 模型求解方法
模型利用遺傳算法求解,通過(guò)調(diào)用Python 3.9中的scikit-opt程序包實(shí)現(xiàn)遺傳算法的參數(shù)設(shè)置與使用?;谝延醒芯繉?duì)種植結(jié)構(gòu)優(yōu)化模型參數(shù)的設(shè)置[10],本研究中遺傳算法的主要參數(shù)設(shè)置為:種群中規(guī)模為為500,最大代數(shù)為為1 000,選擇方式為比例選擇,交叉方式為單點(diǎn)交叉,交叉概率P為0.75,變異概率P為0.01。
收集基于河西走廊區(qū)域制種玉米[3-4,31-32]、大田玉米[5,28,33-34]和小麥[6,34-36]田間試驗(yàn)發(fā)表的學(xué)術(shù)論文數(shù)據(jù)(表 1),將數(shù)據(jù)分為7∶3作為校正集與驗(yàn)證集,對(duì)APSIM模型中的作物參數(shù)進(jìn)行校正,參數(shù)校正結(jié)果與模型驗(yàn)證結(jié)果分別如表2和圖2所示。收集的數(shù)據(jù)來(lái)自于武威、張掖、玉門和瓜州開展的田間試驗(yàn),分別位于河西走廊東部、中西部和西部,具有一定的代表性。作物產(chǎn)量的模擬值和實(shí)測(cè)值2為0.80~0.85、nRMSE為11.0%~15.6%,說(shuō)明校正的APSIM適于模擬河西走廊區(qū)域不同水氮投入下制種玉米、大田玉米和小麥的產(chǎn)量。
表1 APSIM模型參數(shù)校正所用數(shù)據(jù)來(lái)源
表2 制種玉米、大田玉米和小麥的關(guān)鍵參數(shù)校正
圖2 校正后的APSIM模型對(duì)制種玉米、大田玉米和小麥產(chǎn)量的模擬效果
灌水施氮量現(xiàn)狀與優(yōu)化結(jié)果如表3所示。對(duì)比現(xiàn)狀情況,河西走廊制種玉米、大田玉米和小麥的優(yōu)化灌水量可分別節(jié)省22.1%~22.3%、9.1%~17.0%和22.9%~27.3%,施氮量可分別節(jié)省32.2%~50.0%、37.5%~44.0%和26.6%~33.6%。綜合考慮初始土壤養(yǎng)分和生育期內(nèi)降雨量?jī)?yōu)化的水氮管理制度可以明顯減少水氮投入量,而在此基礎(chǔ)上進(jìn)行空間尺度上作物種植結(jié)構(gòu)優(yōu)化,作物產(chǎn)量和水氮利用效率的提升潛力需要進(jìn)一步量化分析。
使用APSIM模型模擬傳統(tǒng)管理與水氮優(yōu)化管理2種情景下的作物產(chǎn)量、灌溉水生產(chǎn)力和氮肥利用效率,作為種植結(jié)構(gòu)優(yōu)化模型的輸入數(shù)據(jù),優(yōu)化后作物空間分布與各地區(qū)種植面積統(tǒng)計(jì)結(jié)果分別如圖3和表4所示。優(yōu)化前后3種作物的空間分布存在明顯差異(圖3):優(yōu)化后,制種玉米和大田玉米在西部的種植面積減少,在中部和東部的種植面積增加,并集中于酒泉、張掖和武威地區(qū);而小麥在西部區(qū)域種植較分散,在中部和東部的種植面積增加,并集中于山丹、永昌和武威地區(qū)。對(duì)比種植結(jié)構(gòu)優(yōu)化前后3種作物種植面積(表 4)可以發(fā)現(xiàn),優(yōu)化后制種玉米和小麥種植面積分別減少1 095.1 hm2(-1.26%)和4 472.1 hm2(-3.07%),而大田玉米種植面積增加692.4 hm2(+0.96%),種植總面積較現(xiàn)狀減少4 874.8 hm2。
表3 河西走廊制種玉米、大田玉米和小麥單位面積水氮投入量?jī)?yōu)化與現(xiàn)狀
水氮管理優(yōu)化、水氮管理與種植結(jié)構(gòu)優(yōu)化以及現(xiàn)狀3種情景下河西走廊制種玉米、大田玉米和小麥的產(chǎn)量、灌溉水生產(chǎn)力、氮肥利用效率和水氮用量計(jì)算結(jié)果如表 5所示。相比現(xiàn)狀,僅施行優(yōu)化水氮管理制度可使產(chǎn)量提升0.29×108~0.45×108kg(3.6%~6.7%)、灌溉水生產(chǎn)力提升0.44~0.59 kg/m3(22.6%~37.9%)、氮肥利用效率提升11.6~23.2 kg/kg(50.2%~89.0%),灌溉水量減少0.55×108~1.30×108m3(13.6%~24.8%)、施氮量減少1.00×107~1.13×107kg(31.1%~43.5%);而綜合水氮管理與種植結(jié)構(gòu)優(yōu)化可使產(chǎn)量提升0.50×108~0.55×108kg(6.7%~8.1%)、灌溉水生產(chǎn)力提升0.49~0.71 kg/m3(25.1%~46.4%)、水氮肥利用效率提升13.7~24.3 kg/kg(59.6%~93.6%),灌溉水量減少0.59×108~1.42×108m3(14.6%~27.0%)、施氮量減少1.06×107~1.16×107kg(33.1%~44.2%)。
圖3 種植結(jié)構(gòu)優(yōu)化前后廊制種玉米、大田玉米和小麥空間分布
表4 種植結(jié)構(gòu)優(yōu)化前后河西走廊各市制種玉米、大田玉米和小麥的種植面積
表5 不同管理情景下河西走廊制種玉米、大田玉米和小麥產(chǎn)量、灌溉水生產(chǎn)力、氮肥利用效率和水氮用量
注:INO,水氮管理優(yōu)化;PSO,種植結(jié)構(gòu)優(yōu)化。
Note: INO, Optimized irrigation and nitrogen fertilization management; PSO, Optimized planting structure.
河西走廊制種玉米、大田玉米和小麥總產(chǎn)量、水氮總投入量和區(qū)域平均水氮利用效率計(jì)算結(jié)果如表6所示。相比生產(chǎn)和管理現(xiàn)狀,實(shí)行優(yōu)化的水氮管理制度可以在產(chǎn)量浮動(dòng)較?。ㄔ霎a(chǎn)0.12×109kg,約5.4%)的情況下使灌溉水生產(chǎn)力提升0.54 kg/m3(32.1%)、氮肥利用效率提升17.35 kg/kg(68.3%),灌溉水量減少0.27×109m3(20.5%)、施氮量減少3.26×107kg(37.5%);水氮管理與種植結(jié)構(gòu)優(yōu)化可使產(chǎn)量提升0.16×109kg(7.2%)、灌溉水生產(chǎn)力提升0.62 kg/m3(36.9%)、氮肥利用效率提升18.97 kg/kg(74.7%),灌水量減少0.29×109m3(22.0%)、施氮量減少3.36×107kg(38.6%)。
表6 不同管理情景下河西走廊作物總產(chǎn)量、灌溉水生產(chǎn)力、氮肥利用效率和總水氮用量
提升作物產(chǎn)量與水氮利用效率是保障糧食安全與農(nóng)業(yè)可持續(xù)發(fā)展的重要方法,尤其是水資源短缺、農(nóng)業(yè)資源利用效率低、且肩負(fù)種子與糧食生產(chǎn)重任的河西走廊地區(qū)。針對(duì)河西走廊主要種植的作物:制種玉米、大田玉米和小麥,已有許多研究基于田間試驗(yàn)[2-6]與站點(diǎn)模型模擬[7,37]探討3種作物產(chǎn)量與水氮利用效率協(xié)同提升的管理模型。本文在收集的田間試驗(yàn)數(shù)據(jù)和模型模擬的基礎(chǔ)上,通過(guò)評(píng)估區(qū)域尺度不同作物的耗水量、吸氮量,考慮降雨和土壤含氮量的時(shí)空變異特征,為河西走廊制種玉米、大田玉米和小麥在區(qū)域上優(yōu)化了水氮管理制度,根據(jù)作物需求精準(zhǔn)控制水氮投入量,是保證作物產(chǎn)量、提升水氮利用效率的關(guān)鍵,降低水分滲漏與氮素淋失風(fēng)險(xiǎn)。
在區(qū)域尺度優(yōu)化種植結(jié)構(gòu)可以解決區(qū)域協(xié)調(diào)發(fā)展問(wèn)題,是減少農(nóng)業(yè)資源使用量、提升資源利用效率的重要途徑[38]。Tan等[39]基于多目標(biāo)魯棒模糊優(yōu)化法對(duì)河西走廊區(qū)域內(nèi)的民勤縣小麥、玉米、棉花、向日葵、瓜類和蔬菜進(jìn)行種植結(jié)構(gòu)優(yōu)化,實(shí)現(xiàn)了經(jīng)濟(jì)效益和生態(tài)效益的顯著提升。彭致功等[13]對(duì)北京市大興區(qū)多種作物進(jìn)行灌溉制度優(yōu)化與種植結(jié)構(gòu)優(yōu)化,在不同總灌溉水量控制情況下可以提升農(nóng)業(yè)發(fā)展閾值41%~61%,并確定了傳統(tǒng)農(nóng)業(yè)與設(shè)施農(nóng)業(yè)的合理發(fā)展閾值。本文將水氮管理與種植結(jié)構(gòu)優(yōu)化相結(jié)合,相比生產(chǎn)與管理現(xiàn)狀,優(yōu)化后的制種玉米、大田玉米和小麥的種植總面積減少,可供其他作物種植或用于生態(tài)修復(fù),并可以提升灌溉水生產(chǎn)力0.62 kg/m3、氮肥利用效率18.97 kg/kg,減少灌溉水量0.29×109m3、施氮量3.36×107kg,同時(shí)作物產(chǎn)量增加0.16×109kg。種植結(jié)構(gòu)調(diào)整將重分配作物的種植區(qū)域與面積,擴(kuò)大綜合效益高的區(qū)域、縮減效益低的區(qū)域,可以實(shí)現(xiàn)水氮管理優(yōu)化方案下的產(chǎn)量與水氮利用效率的進(jìn)一步提升。相比目前農(nóng)戶與農(nóng)場(chǎng)過(guò)量投入農(nóng)業(yè)資源以追求高產(chǎn)的低效管理模式,本研究提出的水分和氮素精準(zhǔn)管理、種植結(jié)構(gòu)因地制宜是保障作物高產(chǎn)并減少水氮投入的關(guān)鍵,從而實(shí)現(xiàn)種子、糧食產(chǎn)糧與農(nóng)業(yè)水氮利用效率的協(xié)同提升。
1)在維持河西走廊區(qū)域作物種植現(xiàn)狀情況下,綜合考慮土壤含氮量和作物生育期內(nèi)降雨量對(duì)水氮管理制度進(jìn)行優(yōu)化,相比水氮管理現(xiàn)狀,可使制種玉米、大田玉米和小麥的單位面積灌水量分別減少22.1%~22.3%、9.1%~17.0%和22.9%~27.3%,單位面積施氮量分別減少32.2%~50.0%、37.5%~44.0%和26.6%~33.6%。
2)種植結(jié)構(gòu)優(yōu)化改變了作物的空間分布與種植面積,優(yōu)化后河西走廊制種玉米和小麥的種植面積分別減少1 095.1 hm2和4 472.1 hm2,大田玉米種植面積增加692.4 hm2,總種植面積減少4 874.8 hm2。
3)僅實(shí)行優(yōu)化的水氮管理制度可以使灌溉水生產(chǎn)力提升0.54 kg/m3、氮肥利用效率提升17.35 kg/kg、產(chǎn)量提升0.12×109kg,灌溉水量減少0.27×109m3、施氮量減少3.26×107kg;水氮管理與種植結(jié)構(gòu)優(yōu)化協(xié)同作用相比生產(chǎn)與管理現(xiàn)狀,可以使灌溉水生產(chǎn)力提升0.62 kg/m3、氮肥利用效率提升18.97 kg/kg、產(chǎn)量提升0.16×109kg,灌水量減少0.29×109m3、施氮量減少3.36×107kg。水氮管理與種植結(jié)構(gòu)優(yōu)化協(xié)同作用可以協(xié)同保障河西走廊制種玉米、大田玉米和小麥的生產(chǎn),并為其他作物種植或生態(tài)修復(fù)提供可利用空間。
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Achieving high-yield and high-efficient management strategy based on optimized irrigation and nitrogen fertilization management and planting structure
Chen Shichao, Liu Wenfeng, Du Taisheng※
(1.,,100083,; 2.,733000,)
The Hexi Corridor is an important production base of maize seed and commodity grain in China. The ample sunshine and temperature greatly contribute to crop production in sustainable agriculture. However, the shortage of water resources has posed a serious threat to the efficiency of resource utilization. An adaption strategy can be expected to promote crop yield and resource use efficiency in changing environments, including the optimization of management measures and the adjustment of planting structure. Taking the seed maize, field maize, and wheat as the research objects, this study aimed to optimize the irrigation and nitrogen fertilization in the crop planting structure, in order to comprehensively improve the crop yield, irrigation Water Productivity (WPI), and Nitrogen Use Efficiency (NUE). An Agricultural Production Systems sIMulator (APSIM) model was also calibrated to evaluate the optimization using the simulations. The field experimental data was collected from the different stations over several years. The profile of seed maize was established for the crop type. The key parameters of field maize and wheat were calibrated in the APSIM. There was the high accuracy of calibrated APSIM model (0.80 <2< 0.85, 11.0% < normalized Root Mean Square Error (nRMSE) < 15.6%), indicating the better applicability of APSIM simulation for the seed maize, field maize, and wheat. The optimization module of irrigation was taken the single crop coefficient as the key component, considering the precipitation during the crop growth period. The optimization module of nitrogen fertilization selected the crop nitrogen concentration and biomass accumulation curve as the important components, in order to jointly constitute the irrigation nitrogen application for the optimization framework. The optimal inputs of irrigation water and nitrogen fertilization were reduced evidently. The irrigation water amount of seed maize, field maize, and wheat was saved by 22.1%-22.3%, 9.1%-17.0%, and 22.9%-27.3%, respectively, and the nitrogen application amount was saved by 32.2%-50.0%, 37.5%-44.0%, and 26.6%-33.6%, respectively, compared with the present. The objective functions included the maximum crop yield, WPI, and NUE in the optimization of crop planting structure. The boundary constraints included the total crop planting area, crop yield demand, as well as irrigation water and nitrogen fertilization input. The planting areas of seed maize and wheat after optimization were reduced by 1 095.1 and 4 472.1 hm2, respectively. By contrast, the planting area of field maize increased by 692.4 hm2. The total planting area was reduced by 4 874.8 hm2. There was a significant difference in the spatial distribution of crop planting after optimization. The total crop production, WPI, and NUE increased by 0.12×109kg, 0.54 kg/m3, and 17.35 kg/kg, respectively, whereas, the irrigation water and nitrogen fertilization inputs decreased by 0.27×109m3and 3.26×107kg, respectively, under the optimization of the irrigation and nitrogen fertilization. After the optimization of irrigation, nitrogen fertilization, and the crop planting structure, the total crop production, WPI, and NUE increased by 0.16×109kg, 0.62 kg/m3, and 18.97 kg/kg, respectively, whereas, the irrigation water and nitrogen fertilization inputs decreased by 0.29×109m3and 3.36×107kg, respectively. The finding can provide scientific guidance and reference for the high-efficient and high-yield crop production in sustainable agriculture in areas with the major grain-producing and water shortages.
crop; irrigation; optimization; planting structure; irrigation and nitrogen fertilization management; irrigation water productivity; nitrogen use efficiency
10.11975/j.issn.1002-6819.2022.16.016
S274
A
1002-6819(2022)-16-0144-09
陳世超,劉文豐,杜太生. 基于水氮管理與種植結(jié)構(gòu)優(yōu)化的作物豐產(chǎn)高效管理策略[J]. 農(nóng)業(yè)工程學(xué)報(bào),2022,38(16):144-152.doi:10.11975/j.issn.1002-6819.2022.16.016 http://www.tcsae.org
Chen Shichao, Liu Wenfeng, Du Taisheng. Achieving high-yield and high-efficient management strategy based on optimized irrigation and nitrogen fertilization management and planting structure[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(16): 144-152. (in Chinese with English abstract) doi:10.11975/j.issn.1002-6819.2022.16.016 http://www.tcsae.org
2022-07-04
2022-08-14
國(guó)家自然科學(xué)基金項(xiàng)目(51725904、51861125103、52109071)
陳世超,博士后,研究方向?yàn)楣?jié)水灌溉理論與新技術(shù)。Email:chenshichaocsc@cau.edu.cn
杜太生,博士,教授,研究方向?yàn)檗r(nóng)業(yè)節(jié)水與水資源高效利用。Email:dutaisheng@cau.edu.cn