楊 廣,李萬精,任富天,何新林,王春霞,喬長錄,李小龍,雷 杰,李發(fā)東
·農(nóng)業(yè)水土工程·
不同礦化度咸水膜下滴灌棉花土壤鹽分累積規(guī)律及其數(shù)值模擬
楊 廣1,李萬精1,任富天1,何新林1※,王春霞1,喬長錄1,李小龍1,雷 杰1,李發(fā)東2,3
(1. 石河子大學(xué)水利建筑工程學(xué)院,寒旱區(qū)生態(tài)水利工程兵團重點實驗室,石河子 832003;2. 中國科學(xué)院大學(xué),北京 100049; 3.中國科學(xué)院地理科學(xué)與資源研究所,北京 100101)
咸水膜下滴灌技術(shù)是緩解干旱區(qū)灌溉水資源短缺的有效途徑之一。該研究基于3 a不同梯度礦化度(2、3、4、5、6 g/L)水源膜下滴灌棉花測坑試驗,分析棉花全生育期時段內(nèi)不同土層鹽分累積規(guī)律,并基于土壤水分及溶質(zhì)運動理論構(gòu)建了咸水滴灌棉田土壤鹽分HYDRUS-2D數(shù)值模擬模型,分析數(shù)值模擬不同咸水礦化度下土壤鹽分分布與運移累積特征的可行性。結(jié)果表明:1)3、4 g/L礦化度處理下鹽分在時間水平上積累量少,且棉花株高、葉綠素、籽棉產(chǎn)量高于5、6 g/L礦化度處理,4 g/L為灌溉水源鹽分閾值。2)土壤電導(dǎo)率隨灌溉生育期整體呈現(xiàn)出逐漸累加的趨勢,至吐絮期達到峰值;滴頭位置處電導(dǎo)率隨土層深度的增加均呈先增后減趨勢,在60~70 cm土層達到峰值,該土層各不同礦化度處理土壤電導(dǎo)率分別為3.04、3.18、3.15、3.00、3.12 dS/m;3)鹽分累積過程中呈鋸齒型波動,灌溉水源礦化度越高累積趨勢越顯著;各土層鹽分累積模擬精度以30 cm土層最高、10 cm土層最低,50 cm土層居中,不同土層實測值與模擬值的平均絕對誤差小于等于0.168、平均相對誤差小于等于15.321、均方根誤差小于0.2、決定系數(shù)大于 0.79,土壤鹽分實測值與模擬值具有很好的一致性,說明數(shù)值模擬的可行性。研究結(jié)果可為干旱區(qū)不同礦化度水源膜下滴灌棉花土壤鹽分運移機理研究提供依據(jù)。
土壤;鹽分;棉花;膜下滴灌;數(shù)值模擬
水資源是干旱區(qū)農(nóng)業(yè)生產(chǎn)和生態(tài)維系的關(guān)鍵要素[1]。由于氣候及地形條件原因,干旱內(nèi)陸區(qū)通常淡水資源短缺,但賦存有大量微咸水及咸水等非常規(guī)水資源,已逐步在農(nóng)業(yè)灌溉中大量使用,有效緩解了干旱區(qū)水資源農(nóng)業(yè)用水緊缺問題[2-3]。為明確合理的農(nóng)業(yè)灌溉水源礦化度閾值,國內(nèi)外相關(guān)專家學(xué)者針對全球不同地區(qū)和作物開展了研究工作。Daliakopoulos等[4]在地中海沿岸發(fā)現(xiàn)在3.5 dS/m的微咸水灌溉閾值下番茄早收對產(chǎn)量沒有顯著影響;Acosta-Motos等[5]在西班牙發(fā)現(xiàn)灌溉水礦化度在2.97 dS/m下,桃金娘植株存活率并未明顯降低;Arslan等[6]在敘利亞確定了鷹嘴豆、扁豆和蠶豆的耐鹽閾值分別為4.2、4.4和5.2 dS/m;Ghrab等[7]在北非突尼斯發(fā)現(xiàn)長期使用6.7 dS/m咸水灌溉橄欖樹可顯著提高產(chǎn)量,但橄欖油含量略有降低。以上研究為微咸水及咸水資源在干旱半干旱地區(qū)農(nóng)業(yè)灌溉利用提供了可靠依據(jù),由于各干旱半干旱地區(qū)不同的氣候和土壤條件,灌溉水源的礦化度閾值研究結(jié)果也不盡相同。
新疆位于中國西北內(nèi)陸干旱區(qū),棉花種植面積占中國的74.3%,是中國最大的優(yōu)質(zhì)棉生產(chǎn)基地[8]。膜下滴灌能淡化作物主根系周圍鹽分濃度,同時覆膜抑制了膜下土壤水分蒸發(fā),節(jié)水增產(chǎn)效果顯著[9]。針對西北干旱區(qū)棉花特殊種植環(huán)境,國內(nèi)學(xué)者對膜下滴灌棉花土壤鹽分分布與運移做了大量研究。王全九等[10]研究了滴灌過程中滴頭流量、灌水時間和土壤含鹽量對水鹽分布的影響;李明思等[11]研究了多年膜下滴灌下土壤鹽分變化與分布特征;同時,部分學(xué)者結(jié)合田間作物、土壤和氣象條件構(gòu)建數(shù)值模型模擬了微咸水和咸水膜下滴灌土壤水鹽運移特征[12]。王在敏等[13]在新疆利用HYDRUS模型建立含根系吸水項的土壤水鹽運移數(shù)值模型;黃金甌等[14]在南疆建立了棉花常規(guī)種植模式下的非飽和帶二維土壤水流運移模型;李仙岳等[15]在內(nèi)蒙古河套灌區(qū)對間作滴灌作物土壤水分的分布特征進行了HYDRUS模型模擬。以上研究定量分析了膜下滴灌棉花土壤鹽分運移基本規(guī)律,為咸水膜下滴灌棉花技術(shù)的推廣提供了可靠依據(jù)。
較少研究關(guān)注咸水及微咸水資源膜下滴灌棉花灌溉水源礦化度閾值,以及長期灌溉條件下棉田土壤鹽分運移與累積過程模擬。鑒此,本文采用測坑試驗和數(shù)值模擬相結(jié)合,分析連續(xù)3 a不同礦化度水源膜下滴灌棉花土壤鹽分分布及運移規(guī)律,并應(yīng)用HYDRUS模型對土壤水鹽動態(tài)進行數(shù)值模擬,以確定咸水水資源利用的礦化度閾值,為中國干旱區(qū)咸水及微咸水膜下滴灌技術(shù)進一步應(yīng)用提供依據(jù)。
試驗基地地理位置圖見圖1,基地平均海拔高度450.8 m,地理位置為85°59′47″E,44°19′26″N,2018-2020年3 a平均氣溫為7.9~8.7 ℃,最高氣溫約為43.8 ℃,最低氣溫約為?39.2 ℃。年降水量在125.0~207.7 mm之間,多年平均降雨量為207 mm、蒸發(fā)量為1 660 mm,6-9月份降水量占全年的55%~70%。地下水潛水埋深7~9 m。研究區(qū)位置示意圖見圖1。供試土壤為砂壤土,土壤平均容重為1.49 g/cm3,田間持水量為19.13%。氣象數(shù)據(jù)來自小型自動氣象站(Spectrum Watchdog 2 700,美國),觀測時間段為2018—2020年。試驗期間氣溫和降雨情況如圖2所示。
試驗利用測坑進行,測坑規(guī)格及試驗布置見圖3。滴灌帶直徑為16 mm,滴頭間距和流量分別為30 cm和2 L/h,為單翼迷宮式滴灌帶。灌溉水設(shè)2、3、4、5、6 g/L礦化度處理,根據(jù)研究區(qū)地下水組成人工配置而成,化學(xué)藥品NaHCO3、Na2SO4、NaCl、CaCl2、MgCl2的質(zhì)量比為1∶7∶8∶1∶1。每個處理設(shè)3個重復(fù)。不同礦化度灌溉水源電導(dǎo)率由電導(dǎo)率儀測定。肥料隨灌溉水滴施(N:300 kg/hm2;P:120 kg/hm2;K:60 kg/hm2)。棉花品種為農(nóng)豐NO.133,棉花灌溉定額為4 800 m3/hm2,出苗水為淡水,其余灌水日期均按照各處理對應(yīng)的礦化度水源灌溉,灌水上限控制在田間持水量的90%,灌溉制度見表1。
表1 不同礦化度咸水膜下滴灌棉花灌溉制度
咸水灌溉棉花的種植模式示意圖見圖3。利用便攜式土壤水分測定儀(Trime-Pico IPH2,德國)測量各不同礦化度處理0~100 cm土層電導(dǎo)率,播種前及試驗結(jié)束時測1次,每次灌水前及灌水后12 h測量,每個測點測量3次求取平均值[16];各不同礦化度處理隨機選擇3株棉花用卷尺測量棉花株高,取測量平均值進行分析;各不同礦化度處理連續(xù)隨機選擇3株棉花由葉綠素測定儀測定(TYS-4N,中國)葉綠素含量,在測定過程中,將每株棉花冠層分為上、中、下三個葉層,每一葉層選擇2片陽葉測量,每片陽葉測量5次,取測量平均值進行分析;棉花采摘后稱質(zhì)量得到每個小區(qū)產(chǎn)量,求取平均值得到不同礦化度處理下籽棉產(chǎn)量(kg/m2),進而計算得到單位面積籽棉產(chǎn)量(kg/hm2)[17]。
1.3.1 模擬單元設(shè)置與模型基本方程
本研究利用HYDRUS-2D軟件模擬不同礦化度水源膜下滴灌棉花條件下0~100 cm土層鹽分運移情況,以垂直棉花種植方向構(gòu)建2 m×2 m的二維剖面三角網(wǎng)幾何體(圖4)。灌溉水鹽分輸入按照不同鹽分濃度處理[18]。土壤水分運動、溶質(zhì)運移及根系吸水分別采用修正過的Richards方程、對流-彌散方程及修正的Feddes模型來描述[19-20]。邊界條件如圖4所示。模型基本方程如下所示:
1)土壤水分運移方程[21]如下:
式中()為土壤體積含水率,cm3/cm3;為壓力水頭cm;()為非飽和土壤導(dǎo)水率,cm/d;為時間,d;為橫向坐標(biāo);為垂向坐標(biāo);規(guī)定向上為正;為源匯項,此處表示根系吸水率,cm3/d。
2)土壤水力函數(shù)van Genuchten公式[22]
式中K為土壤飽和導(dǎo)水率,cm/d;θ為土壤相對飽和度;θ為土壤殘余體積含水率;θ為土壤飽和體積含水率;均為經(jīng)驗參數(shù);為孔隙關(guān)聯(lián)度參數(shù)。
3)鹽分運移基本方程[23]
式中θ為土壤中鹽分濃度為時的體積含水率,cm3/cm3;為溶質(zhì)質(zhì)量濃度,g/cm3;q為入滲率,cm/d;D為彌散系數(shù),cm2/d;x為空間坐標(biāo)(=1, 2),1=,2=,11=D,12=D;C為匯項鹽質(zhì)量濃度,g/L。
4)根系吸水模型[24]
式中為根系吸水項;(,h,,)為土壤水鹽脅迫函數(shù);h為滲透壓力,cm;(,)為根系分布函數(shù),cm-2;S為與蒸騰關(guān)聯(lián)的地表長度,cm;為根系吸水計算區(qū)域半徑,cm;T為潛在蒸發(fā)速率,cm/d;Ω為根系分布區(qū)域,cm2。
5)蒸發(fā)蒸騰量計算
根據(jù)研究區(qū)實測氣象資料,利用Penman-Monteith公式計算棉花蒸散量[25],計算公式為
式中ETP是潛在蒸散量,cm/d;K是作物系數(shù);ET0是參考作物蒸散量,cm/d;E是潛在蒸騰速率,cm/d;是飽和蒸汽壓曲線的斜率,kPa/℃;R是凈太陽輻射,MJ/(m2·d);是水蒸發(fā)潛熱,MJ/kg;是濕度計常數(shù),kPa/℃;LAI是葉面積指數(shù)。
1.3.2 參數(shù)擬定
依據(jù)試驗前求取的供試土壤飽和含水率、容重、土壤質(zhì)地等參數(shù),利用模型中Rosseta模塊初步擬定土壤水分特征參數(shù)。模型選用的土壤水分特征函數(shù)是van Genuchten-Mualem公式[22],通過觀測棉花生育期內(nèi)土壤水鹽數(shù)據(jù)擬定最終參數(shù)。本研究擬定了測坑0~30、>30~60、>60~100、>100~200 cm土層的參數(shù)值,結(jié)果見表2。
表2 土壤水分特征參數(shù)
根據(jù)前人的研究成果,水動力學(xué)彌散系數(shù)由穿透曲線(Breakthrough Curve,BTC)推導(dǎo)求取[26]??v向彌散系數(shù)為15 cm2/d,橫向彌散系數(shù)為4 cm2/d。根系吸水參數(shù)參照王在敏等[13]的調(diào)參結(jié)果。鹽分脅迫參數(shù)采用HYDRUS自帶數(shù)據(jù)庫中的作物參數(shù),棉花的閾值為15.4 cm,斜率值為2.6。
1.3.3 模型檢驗與評估
采用平均絕對誤差(Mean Absolute Error, MAE)、平均相對誤差(Mean Relative Error, MRE)、均方根誤差(Root Mean Square Error, RMSE)和決定系數(shù)(2)評價模擬值和實測值的吻合程度。其計算公式見文獻[27]。
2.1.1 年際尺度土壤鹽分累積動態(tài)
2018—2020年各處理土壤平均鹽分的累積情況,實測值如圖5所示。2018年試驗初始各測坑土壤平均鹽分差異不大,電導(dǎo)率在0.29~0.48 dS/m范圍內(nèi);灌溉后土壤平均鹽分隨灌溉水礦化度的升高呈現(xiàn)積累趨勢,其中5、6 g/L處理下鹽分積累最為明顯,試驗結(jié)束時電導(dǎo)率高達3.12、3.22 dS/m,分別是試驗初始時的10.4和9.76倍;各處理土壤鹽分在吐絮期內(nèi)(120~153 d)達到峰值。當(dāng)灌溉水礦化度小于4 g/L時,土壤鹽分累積量相對少,3 a咸水灌溉條件下未引起土壤鹽分累積。
2.1.2 空間尺度土壤鹽分的空間尺度變化
選取試驗第3年(2020年)棉花生育中期(蕾期末)第90天分析不同礦化度水源處理下0~100 cm土層鹽分的積累情況,實測值如圖6所示。在垂直方向上,各處理在窄行處電導(dǎo)率隨土層深度的增加呈現(xiàn)先增加后減小的趨勢,鹽分在40~70 cm土層出現(xiàn)明顯聚積,并在60~70 cm達到峰值;在寬行處,各處理電導(dǎo)率隨土層深度的增加,變化幅度較大,除2 g/L處理外在0~60和60~100 cm土層范圍內(nèi)出現(xiàn)2次先增加后減少的趨勢。灌水后窄行10 cm處電導(dǎo)率相對較低,2、3、4 g/L處理分別為0.43、1.72、1.38 dS/m,峰值出現(xiàn)在40~70 cm土層,分別為3.04、3.18、3.15 dS/m;5 和6 g/L處理下,灌水后窄行10 cm處電導(dǎo)率值較高,分別為1.56、2.64 dS/m,在60 cm處達到峰值,分別為3.00、3.12 dS/m。值得注意的是,當(dāng)灌溉水礦化度大于等于5 g/L時,灌水后土壤電導(dǎo)率大于灌水前土壤電導(dǎo)率,與2~4 g/L條件下土壤電導(dǎo)率在灌水后小于灌水前存在明顯的相反結(jié)果。
2.1.3不同生育期土層鹽分累積特征
實測結(jié)果表明,各處理下不同生育期土壤電導(dǎo)率呈現(xiàn)逐漸累加的趨勢,到吐絮期時各土層電導(dǎo)率達到峰值(圖7),微咸水礦化度為2、3、4、5、6 g/L時土壤電導(dǎo)率最高值分別達到2.59、2.83、3.02、3.45、3.57 dS/m,其中5、6 g/L處理下各灌溉生育期電導(dǎo)率高于其他處理,鹽分累積趨勢更為明顯。土壤鹽分在滴灌作用下難以運移到土壤深層,在吐絮期40~70 cm土層出現(xiàn)明顯的累積。
棉花株高、葉綠素含量、籽棉產(chǎn)量實測值如表3所示。隨著灌溉水礦化度逐漸增加,株高呈現(xiàn)減小趨勢,葉綠素含量、籽棉產(chǎn)量呈現(xiàn)先增加再緩慢減小的趨勢,4 g/L為葉綠素含量轉(zhuǎn)折點,3 g/L為籽棉產(chǎn)量轉(zhuǎn)折點。2、3 g/L處理下的棉花株高為84.7和83.3 cm,明顯高于5、6 g/L處理的67.3、59.7 cm;3、4 g/L處理下葉綠素含量相比5、6 g/L處理較高;各處理籽棉產(chǎn)量呈顯著差異,其中3、4 g/L處理下籽棉產(chǎn)量相對較高,分別為5 355.62、5 229.45 kg/hm2。當(dāng)灌溉水礦化度小于4 g/L時,不會因影響植株高度和葉綠素含量而抑制棉花的生長發(fā)育進而導(dǎo)致棉花產(chǎn)量降低。因此可認為小于4 g/L的咸水灌溉不會顯著影響籽棉產(chǎn)量,可以作為棉花灌溉水來源。
表3 2018-2020年不同礦化度水源處理下棉花株高、葉綠素、籽棉產(chǎn)量
注:同列不同字母表示在5%水平下差異顯著。
Note: Different letters in the same column indicate significant differences at the 5% level.
2.3.1不同礦化度水源處理下窄行(滴頭處)土壤鹽分模擬
整個試驗期內(nèi)各鹽分處理下土壤鹽分模擬呈現(xiàn)不同程度累積趨勢,這與實測值變化趨勢基本一致(圖8)。棉花根系主要分布在0~50 cm范圍,重點對比分析10、30、50 cm土層鹽分的運移情況。在整個生育期內(nèi),鹽分在累積過程中出現(xiàn)鋸齒型波動,其中10 cm土層鹽分波動范圍最大,其次是30 cm和50 cm。各處理的鹽分含量在10 cm土層最低,50 cm土層土壤鹽分較高,整體來看,隨灌溉水鹽分濃度的增大,土壤鹽分累積量逐漸增大。
2.3.2 不同礦化度水源灌溉下不同土層鹽分數(shù)值模擬評價
各鹽分處理下不同土層鹽分實測值與模擬值的MAE小于等于0.168、MRE小于等于15.321、RMSE小于0.2、2均大于0.79,模擬結(jié)果與實測值吻合程度良好,模擬結(jié)果能較好反映土層鹽分運移情況(表4)。同時,不同土層鹽分模擬效果不盡相同,30 cm土層實測值與模擬值吻合程度表現(xiàn)最好,其次是50 cm土層,表現(xiàn)最差的是10 cm土層。均方根誤差與相關(guān)系數(shù)顯示,3 g/L處理下各土層實測值與模擬值的整體擬合程度最好,10、30、50 cm土層實測值與模擬值的RMSE分別為0.078、0.121、0.114,2分別為0.924、0.952、0.934;而2 g/L處理下各土層實測值與模擬值的整體擬合程度最差,10、30、50 cm土層實測值與模擬值的RMSE分別為0.198、0.097、0.153,2分別為0.816、0.945、0.794。
表4 各鹽分處理不同土層鹽分模擬效果評價
咸水灌溉條件下,土壤鹽分淋洗的同時也會使得鹽分累積,這導(dǎo)致土壤鹽分難以保持在穩(wěn)定的靜態(tài)平衡狀態(tài)。當(dāng)灌溉水礦化度小于等于4 g/L時,可能由于水分入滲過程中帶入土壤的鹽分淋洗速率大于累積速率,造成灌溉后土壤電導(dǎo)率小于灌溉前土壤電導(dǎo)率,此時鹽分淋洗占主導(dǎo)地位;當(dāng)灌溉水礦化度大于4 g/L時,不同于淡水灌溉,可能由于咸水入滲帶入土壤的鹽分累積速率大于淋洗速率,造成灌溉后土壤電導(dǎo)率大于灌溉前土壤電導(dǎo)率,此時鹽分累積占主導(dǎo)地位。
咸水膜下滴灌帶入土壤的鹽分累積過高會導(dǎo)致棉花根系鹽脅迫,抑制其對水分的利用[28]。李明思等[11]研究發(fā)現(xiàn),地下水的上下波動、降雨和蒸發(fā)等共同作用決定了鹽荒地的鹽分分布狀況,處于自然平衡狀態(tài)。由于農(nóng)業(yè)生產(chǎn)需求,人為農(nóng)藝措施(覆膜、灌溉等)打破了鹽分平衡,導(dǎo)致土壤鹽分趨向一種新的平衡狀態(tài),并最終保持在一個較低的水平范圍且小幅波動[29]。本研究中,灌溉水礦化度水平對土壤含鹽量有很大的影響。由于灌溉輸入到土壤中的鹽分與水分深層淋洗作用對棉花根區(qū)鹽分影響顯著,隨著種植年限增加,鹽分隨灌溉水持續(xù)滲入土壤,導(dǎo)致根區(qū)鹽分逐步增加。與此同時,作物蒸騰受限與下滲淋洗量加大,當(dāng)根區(qū)土壤的輸入鹽量與淋洗鹽量相當(dāng),根區(qū)鹽分處于相對平衡狀態(tài)。表層土壤(0~20 cm)含鹽量直接受灌溉水礦化度和蒸發(fā)量的影響,該區(qū)域鹽分淋洗和累積都占主導(dǎo)地位。比較不同深度土壤含鹽量,發(fā)現(xiàn)各處理中土壤表層含鹽量都比較高。鹽分在土壤表層累積,以應(yīng)對高表面溫度、低植被覆蓋率和高蒸發(fā)率。此外,由于棉花根系吸水和毛管力的共同作用,咸水可以從深層土壤輸送到表層土壤,也會導(dǎo)致表層土壤含鹽量增大。20~60 cm土層是棉花根系和滴灌濕潤區(qū)關(guān)鍵位置,濕潤帶使鹽分從作物根區(qū)附近帶出(圖9),以上因素對微咸水膜下滴灌條件下土壤鹽分分布有顯著影響。在微咸水膜下滴灌條件下,濕潤帶周圍(60 cm以下)土壤鹽分水平最高。從長遠來看,需要清除在濕潤鋒“前沿”累積的鹽分,以保持土壤生產(chǎn)力。這也印證了宗含等[30]的研究結(jié)果,其研究認為在石河子墾區(qū)的鹽荒地塊實施膜下滴灌6~8 a,60、100 cm土層形成穩(wěn)定積鹽層,在60 cm以上土壤鹽分基本處于動態(tài)平衡。
不同礦化度水源膜下滴灌棉花會將鹽分帶入土壤中,長期灌溉下各土層鹽分會逐漸累積,若不采取合理的農(nóng)藝措施,將加重土壤鹽漬化[31-32]。本研究通過3a不同礦化度水源膜下滴灌棉花試驗,結(jié)果表明3、4 g/L處理下積鹽作用不明顯,但5、6 g/L處理下鹽分積累趨勢快且積鹽效果明顯。3、4 g/L處理下由于鹽分含量未達到抑制棉花生長發(fā)育閾值,2020年棉花產(chǎn)量分別為4 984.38、5 355.42、5 229.45 kg/hm2,相對于5、6 g/L處理籽棉產(chǎn)量較高,并未出現(xiàn)大幅降低的趨勢。鹽分的累積造成的鹽分脅迫已明顯抑制棉花的株高與葉綠素含量,這是造成籽棉產(chǎn)量降低的原因。總體來說,土壤鹽分水平在咸水灌溉試驗的第1年顯著增加,但在第2年和第3年試驗結(jié)束時保持穩(wěn)定。Li等[33-34]在另一種類型的鹽漬土中獲得了類似的結(jié)果。宋有璽等[35]研究發(fā)現(xiàn)在民勤綠洲區(qū)種植棉花的灌溉水礦化度閾值為3.51 g/L;劉雪艷等[36]在南疆發(fā)現(xiàn)當(dāng)灌溉水的礦化度為2.36~3.39 g/L時對棉花生長的抑制作用較?。欢狙芯堪l(fā)現(xiàn)灌溉水礦化度小于4 g/L時,未抑制棉花生長發(fā)育,這與前人研究結(jié)果無顯著差異。王久生等[37]認為灌水后土壤含鹽量總體是隨灌溉水礦化度的增大而增大,但未對不同鹽分處理下的土層鹽分積累程度作分析。眾多學(xué)者研究中雖然設(shè)置的灌溉水礦化度梯度不同,但總體結(jié)果是隨著灌溉水礦化度的增加,土壤鹽分累積趨勢越大[32,36],這與本研究結(jié)果一致。由于北疆冬季積雪化水和春季降雨對土層鹽分產(chǎn)生淋洗以及來年試驗開始時第1次灌溉淡水洗鹽[28](例如2018年測坑平均融雪水為0.26 m3,春季累計降雨量為22.30 mm,第1次灌溉淡水量為0.13 m3),生育期初期土壤鹽分較上年灌溉結(jié)束時會出現(xiàn)明顯降低。胡宏昌等[38]也認為春灌的鹽分淋洗作用明顯,在多年尺度上根區(qū)土壤鹽分未出現(xiàn)明顯累積。
對于不同礦化度水源膜下滴灌棉花0~100 cm土層鹽分的空間與時間尺度變化情況,膜間處垂直方向上0~20 cm土層鹽分較少,60~100 cm土層鹽分累積程度較大。滴灌水將鹽分向四周淋洗,在垂直方向上,隨著土層加深,淋洗效果逐漸減弱,鹽分最終累積在深層土壤中;水平方向上,膜間由于強烈的蒸發(fā)作用,擴散到該處的水分蒸發(fā)散失,最終導(dǎo)致鹽分在膜間處累積??拷喂鄮У闹鞲鶇^(qū)土壤處于脫鹽狀態(tài),遠離滴灌帶的土壤處于積鹽狀態(tài)。滴灌水對鹽分雖然有明顯的淋洗作用,但這是有一定次數(shù)且短暫的[35],而棉花強烈的蒸騰作用與根系吸水卻是持續(xù)不斷,根系吸水使得鹽分向根系處運移,土層中的鹽分沿棉花毛管上升,雖然棉花能吸收利用部分咸水中的微量元素(Zn、B等),但大部分鹽分(K+、Ca2+、Na+、Mg2+等)仍會滯留在根系層。因此,從土壤水鹽運移規(guī)律角度看,利用含鹽量為4 g/L咸水用于干旱和半干旱地區(qū)棉花灌溉是可行的,因為它不太可能導(dǎo)致土壤二次鹽漬化。
田間試驗可以獲得準(zhǔn)確的土壤鹽分含量,但限制條件多、工作量大,而建立土壤水鹽運移數(shù)值模型,可預(yù)測棉花各個生育期內(nèi)任何時刻和任何土壤深度處土壤水鹽動態(tài)變化和長期效應(yīng),明確棉花生長過程中土壤鹽分脅迫環(huán)境,進而獲得咸水灌溉滴灌方案。本研究數(shù)值模擬結(jié)果表明,50 cm土層由于水分滲入較少,鹽分動態(tài)變化范圍較小,相對穩(wěn)定。在土壤垂直深度層面上,40~60 cm土層鹽分明顯多于0~20 cm土層,由于蒸發(fā)、根系吸水等原因深層土壤水鹽具有向膜邊裸露地表提升遷移趨勢[39-40]。本研究發(fā)現(xiàn)棉花生育期內(nèi)土壤鹽分累積呈鋸齒型波動,且呈現(xiàn)出逐漸累積的趨勢。這是由于灌水后土壤含水率增高導(dǎo)致各土層鹽分出現(xiàn)短暫降低,而后土壤水分逐漸蒸發(fā)散失以及被棉花吸收利用,導(dǎo)致土層鹽分逐漸回升[41];同時由于模型邊界條件比試驗測坑實際環(huán)境更加理想,符合理論狀態(tài)下均質(zhì)連續(xù)假設(shè),這都是導(dǎo)致鹽分在累積過程中出現(xiàn)類似鋸齒形的規(guī)律性上下波動的原因[21]?;⒛憽ね埋R爾白等[42]通過研究發(fā)現(xiàn),30 cm深度土壤含鹽量實測值與計算值吻合最好,但10 cm與50 cm深度土壤含鹽量實測值與計算值存在不同程度差別,這與本文研究結(jié)果相一致。其原因可能是由于模型構(gòu)建時設(shè)置的上邊界條件與實際測坑土壤表層存在差別,難以達到理想條件,導(dǎo)致10 cm土層實測值與模擬值吻合程度表現(xiàn)最差;而30 cm土層受外界因素較少,相比50 cm土層水分能均勻滲透。Hydrus-2D模型可以較好模擬滴灌棉田土壤鹽分時空分布,但在模擬過程中邊界條件設(shè)定、土壤水鹽運移參數(shù)、土壤蒸發(fā)與植物蒸騰參數(shù)和根系吸水參數(shù)的選取非常重要,模型參數(shù)優(yōu)化設(shè)定越合理,模擬結(jié)果將會越接近實測值[43]。
1)在不同礦化度水源膜下滴灌條件下,在棉花生育期內(nèi)各處理土壤鹽分隨時間的增長均有不同程度累積,3、4 g/L處理下鹽分積累較為平緩且積鹽效果不明顯,5、6 g/L處理下鹽分積累趨勢快且積鹽明顯;隨著灌溉水礦化度逐漸增加,株高呈現(xiàn)減小趨勢,葉綠素含量、籽棉產(chǎn)量呈現(xiàn)先增加再緩慢減小的趨勢,棉花膜下滴灌水源礦化度閾值為4 g/L。
2)各礦化水源灌溉處理下電導(dǎo)率整體呈現(xiàn)逐漸累加的趨勢,到吐絮期時各土層電導(dǎo)率達到峰值;窄行處各鹽分處理下電導(dǎo)率隨土層深度的增加呈現(xiàn)先增加后減少的趨勢,在60~70 cm深處達到峰值;寬行處各處理的電導(dǎo)率隨土層深度的增加波動較大,出現(xiàn)兩次先增加后減少的趨勢。
3)整個生育期內(nèi)鹽分累積出現(xiàn)鋸齒型波動,且呈現(xiàn)出逐漸累積的趨勢。各鹽分處理不同土層實測值與模擬值的吻合程度整體表現(xiàn)由高到低為30、50、10 cm。各鹽分處理的不同土層實測值與模擬值的平均絕對誤差等于小于0.168、平均相對誤差等于小于15.321、均方根誤差(RMSE)小于0.2、決定系數(shù)(2)均大于0.79,土壤鹽分含量的實測值與模擬值具有很好的一致性,模擬結(jié)果能較好地反映不同土層鹽分運移累積情況。
[1] Songrui N, Beibei Z, Jianchu S, et al. Soil water/salt balance and water productivity of typical irrigation schedules for cotton under film mulched drip irrigation in northern Xinjiang [J]. Agricultural Water Management, 2021, 245: 106651.
[2] 蔡達偉,孔淑瓊,劉瑞琪. 微咸水農(nóng)田安全灌溉研究進展[J]. 節(jié)水灌溉,2020,10:91-95,100.
Cai Dawei, Kong Shuqiong, Liu Ruiqi. Advances in research on safe irrigation of brackish water farmland[J]. Water Saving Irrigation, 2020, 10: 91-95, 100. (in Chinese with English abstract)
[3] 馬東豪,王全九,來劍斌. 膜下滴灌條件下灌水水質(zhì)和流量對土壤鹽分分布影響的田間試驗研究 [J]. 農(nóng)業(yè)工程學(xué)報,2005,21(3):42-46.
Ma Donghao, Wang Quanjiu, Lai Jianbin. Field experiment study on the influence of irrigation water quality and flow on soil salt distribution under drip irrigation under mulch [J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2005, 21(3): 42-46. (in Chinese with English abstract)
[4] Daliakopoulos I N, Apostolakis A, Wagner K, et al. Effectiveness of Trichoderma harzianum in soil and yield conservation of tomato crops under saline irrigation [J]. Catena, 2019, 175: 144-153.
[5] Acosta-Motos J R, Hernández J A, Lvarez S, et al. The long-term resistance mechanisms, critical irrigation threshold and relief capacity shown by Eugenia myrtifolia plants in response to saline reclaimed water [J]. Plant Physiology and Biochemistry, 2017, 111: 244-256.
[6] Arslan A, Majid G A, Abdallah K, et al. Evaluating the productivity potential of chickpea, lentil and faba bean under saline water irrigation systems[J]. Irrigation and Drainage, 2016, 65(1): 19-28.
[7] Ghrab M, Ayadi M, Gargouri K, et al. Long-term effects of partial root-zone drying (PRD) on yield, oil composition and quality of olive tree (cv. Chemlali) irrigated with saline water in arid land[J]. Journal of Food Composition and Analysis, 2014, 36(1): 90-97.
[8] 潘偉,楊德剛,楊莉,等. 新疆棉花種植面積的時空變化及適度規(guī)模研究[J]. 中國生態(tài)農(nóng)業(yè)學(xué)報,2011,19(2):415-420.
Pan Wei, Yang Degang, Yang Li, et al. Study on the temporal and spatial changes and appropriate scale of cotton planting area in Xinjiang[J]. Chinese Journal of Eco-Agriculture, 2011, 19(2): 415-420. (in Chinese with English abstract)
[9] Wang X P, Wang H B, Si Z Y, et al. Modelling responses of cotton growth and yield to pre-planting soil moisture with the CROPGRO-Cotton model for a mulched drip irrigation system in the Tarim Basin[J]. Agricultural Water Management, 2020, 241: 106378.
[10] 王全九,王文焰,呂殿青,等. 膜下滴灌鹽堿地水鹽運移特征研究 [J]. 農(nóng)業(yè)工程學(xué)報,2000,16(4):54-57.
Wang Quanjiu, Wang Wenyan, Lü Dianqing, et al. Study on water and salt transport characteristics of saline-alkali land under drip irrigation under mulch[J]. Transactions of The Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2000, 16(4): 54-57. (in Chinese with English abstract)
[11] 李明思,劉洪光,鄭旭榮. 長期膜下滴灌農(nóng)田土壤鹽分時空變化[J]. 農(nóng)業(yè)工程學(xué)報,2012,28(22):82-87.
Li Mingsi, Liu Hongguang, Zheng Xurong. Spatiotemporal changes of soil salinity in farmland under long-term drip irrigation under mulch[J]. Transactions of The Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2012, 28(22): 82-87. (in Chinese with English abstract)
[12] Karandish F, Im-Nek J. A comparison of the HYDRUS (2D/3D) and SALTMED models to investigate the influence of various water-saving irrigation strategies on the maize water footprint[J]. Agricultural Water Management, 2019, 213: 809-820.
[13] 王在敏,何雨江,靳孟貴,等. 運用土壤水鹽運移模型優(yōu)化棉花微咸水膜下滴灌制度[J]. 農(nóng)業(yè)工程學(xué)報,2012,28(17):63-70.
Wang Zaimin, He Yujiang, Jin Menggui, et al. Optimization of mulched drip-irrigation with brackish water for cotton using soil-water-salt numerical simulation[J]. Transactions of The Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2012, 28(17): 63-70. (in Chinese with English abstract)
[14] 黃金甌,靳孟貴,周麗玲,等. 基于HYDRUS-2D微咸水膜下滴灌棉田水流運移模擬[C]//防治地災(zāi)除險安居. 杭州:浙江省地質(zhì)學(xué)會2017年學(xué)術(shù)年會,2017.
[15] 李仙岳,陳寧,史海濱,等. 膜下滴灌玉米番茄間作農(nóng)田土壤水分分布特征模擬[J]. 農(nóng)業(yè)工程學(xué)報,2019,35(10):50-59.
Li Xianyue, Chen Ning, Shi Haibin, et al. Simulation of soil moisture distribution characteristics in farmland of corn-tomato intercropping with drip irrigation under mulch[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(10): 50-59. (in Chinese with English abstract)
[16] 楊衛(wèi)中,王一鳴,李保國,等. 基于相位檢測原理的TDR土壤電導(dǎo)率測量研究[J]. 農(nóng)業(yè)機械學(xué)報,2010,41(11):183-187.
Yang Weizhong, Wang Yiming, Li Baoguo, et al. TDR soil conductivity measurement based on phase detection principle[J]. Transactions of the Chinese Society for Agricultural Machinery, 2010, 41(11): 183-187. (in Chinese with English abstract)
[17] Ren F T, Yang G, Li W J, et al. Yield-compatible salinity level for growing cotton () under mulched drip irrigation using saline water[J]. Agricultural Water Management, 2021, 250: 106859.
[18] 馬海燕,王昕,張展羽,等. 基于HYDRUS-3D的微咸水膜孔溝灌水鹽分布數(shù)值模擬[J]. 農(nóng)業(yè)機械學(xué)報,2015,46(2):137-145.
Ma Haiyan, Wang Xin, Zhang Zhanyu, et al. Numerical simulation of salt distribution in brackish water film hole and furrow irrigation based on HYDRUS-3D[J]. Transactions of the Chinese Society for Agricultural Machinery, 2015, 46(2): 137-145. (in Chinese with English abstract)
[19] 胡鉅鑫,虎膽·吐馬爾白,李卓然,等. 基于HYDRUS-2D模型膜下滴灌棉田不同上口寬排鹽淺溝下土壤水鹽運移模擬[J]. 水利科學(xué)與寒區(qū)工程,2019,2(5):1-9.
Hu Juxin, Hudan·Tumarbai, Li Zhuoran, et al. Based on HYDRUS-2D model drip irrigation under mulch in cotton fields, soil water and salt transport simulation under different upper mouth wide salt drainage shallow gully[J]. Water Conservancy Science and Cold Region Engineering, 2019, 2(5): 1-9. (in Chinese with English abstract)
[20] 莫彥,李光永,蔡明坤,等. 基于HYDRUS-2D模型的玉米高出苗率地下滴灌開溝播種參數(shù)優(yōu)選[J]. 農(nóng)業(yè)工程學(xué)報,2017,33(17):105-112.
Mo Yan, Li Guangyong, Cai Mingkun, et al. Optimum seeding parameters of corn high emergence rate subsurface drip irrigation based on HYDRUS-2D model [J]. Transactions of The Chinese Society of Agricultural Engineering (Transactions of the CSAE, 2017, 33(17): 105-112. (in Chinese with English abstract)
[21] Richards L A. Capillary conduction of liquids through porous mediums[J]. Physics, 1931, 1(5): 318-333.
[22] van Genuchten M T. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils[J]. Soil Science Society of America Journal, 1980, 44(5): 892-898.
[23] 馬波,周青云,張寶忠,等. 基于HYDRUS-2D的濱海地區(qū)膜下滴灌土壤水鹽運移模擬研究[J]. 干旱地區(qū)農(nóng)業(yè)研究,2020,38(5):182-191.
Ma Bo, Zhou Qingyun, Zhang Baozhong, et al. Simulation of soil water and salt transport under mulch drip irrigation based on HYDRUS-2D in coastal areas[J]. Agricultural Research in the Arid Areas, 2020, 38(5): 182-191. (in Chinese with English abstract)
[24] Feddes R A, Kowalik P J, Zaradny H. Simulation of field water use and crop yield.[J]. Soil Science, 1982, 129(3):193.
[25] Katerji N, Rana G. Crop reference evapotranspiration: A Discussion of the concept, analysis of the process and validation[J]. Water Resources Management, 2011, 25(6): 1581-1600.
[26] 李開明,劉洪光,石培君,等. 明溝排水條件下的土壤水鹽運移模擬[J]. 干旱區(qū)研究,2018,35(6):1299-1307.
Li Kaiming, Liu Hongguang, Shi Peijun, et al. Simulation of soil water and salt transport under open ditch drainage conditions[J]. Arid Zone Research, 2018, 35(6): 1299-1307. (in Chinese with English abstract)
[27] 丁奠元,趙英,孫本華,等. 根區(qū)水質(zhì)模型在黃土高原旱區(qū)冬小麥氮肥管理中的適用性分析[J]. 農(nóng)業(yè)工程學(xué)報,2015,31(23):111-121.
Ding Dianyuan, Zhao Ying, Sun Benhua, et al. Suitability analysis of nitrogen fertilizer management on dryland of Loess Plateau based on root zone water quality model[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015, 31(23): 111-121. (in Chinese with English abstract)
[28] Chen W P, Hou Z N, Wu L S, et al. Evaluating salinity distribution in soil irrigated with saline water in arid regions of northwest China[J]. Agricultural Water Management, 2010, 97(12): 2001-2008.
[29] 劉新永,田長彥. 棉花膜下滴灌鹽分動態(tài)及平衡研究[J]. 水土保持學(xué)報,2005,6(21):84-87.
Liu Xinyong, Tian Changyan. Research on salt dynamics and balance of drip irrigation under mulch on cotton[J]. Journal of Soil and Water Conservation, 2005, 6(21): 84-87. (in Chinese with English abstract)
[30] 宗含,高龍,王雅琴,等. 膜下滴灌條件下鹽荒地土壤鹽分變化規(guī)律研究[J]. 干旱地區(qū)農(nóng)業(yè)研究,2018,36(6):7-12.
Zong Han, Gao Long, Wang Yaqin, et al. Study on the change law of soil salinity in saline wasteland under drip irrigation under mulch[J]. Agricultural Research in the Arid Areas, 2018, 36(6): 7-12. (in Chinese with English abstract)
[31] 栗現(xiàn)文,靳孟貴,袁晶晶,等. 微咸水膜下滴灌棉田漫灌洗鹽評價[J]. 水利學(xué)報,2014,45(9):1091-1098,1105.
Li Xianwen, Jin Menggui, Yuan Jingjing, et al. Salt evaluation of drip irrigation in cotton field under film of brackish water[J]. Journal of Hydraulic Engineering, 2014, 45(9): 1091-1098, 1105. (in Chinese with English abstract)
[32] 彭遙,周蓓蓓,張繼紅,等. 磁化水膜下滴灌對棉田水鹽分布特征及棉花生長特性的影響[J]. 水土保持學(xué)報,2019,33(5):334-342,357.
Peng Yao, Zhou Beibei, Zhang Jihong, et al. Effects of drip irrigation under magnetized water film on the distribution characteristics of water and salt in cotton fields and cotton growth characteristics[J]. Journal of Soil and Water Conservation, 2019, 33(5): 334-342, 357. (in Chinese with English abstract)
[33] Li X, Kang Y, Wan S, et al. Response of a salt-sensitive plant to processes of soil reclamation in two saline-sodic, coastal soils using drip irrigation with saline water[J]. Agricultural Water Management, 2016, 164: 223-234.
[34] Li X, Kang Y, Wan S, et al. Effect of ridge planting on reclamation of coastal saline soil using drip-irrigation with saline water [J]. Catena, 2017, 150: 24-31.
[35] 宋有璽,安進強,何岸镕,等. 微咸水膜下滴灌對棉花生長發(fā)育及其產(chǎn)量的影響研究[J]. 水土保持研究,2016,23(1):128-132.
Song Youxi, An Jinqiang, He Anrong, et al. Effects of drip irrigation under mulch with brackish water on cotton growth and yield[J]. Research of Soil and Water Conservation, 2016, 23(1): 128-132. (in Chinese with English abstract)
[36] 劉雪艷,丁邦新,白云崗,等. 微咸水膜下滴灌對棉花生長及產(chǎn)量的影響[J]. 干旱區(qū)研究,2020,37(6):1627-1634.
Liu Xueyan, Ding Bangxin, Bai Yungang, et al. Effects of drip irrigation under mulch with brackish water on cotton growth and yield[J]. Arid Zone Research, 2020, 37(6): 1627-1634. (in Chinese with English abstract)
[37] 王久生,王龍,姚寶林,等. 微咸水膜下滴灌條件下水鹽對棉花生長的影響研究[J]. 節(jié)水灌溉,2012(12):9-15.
Wang Jiusheng, Wang Long, Yao Baolin, et al. The effect of water and salt on cotton growth under drip irrigation under mulch with brackish water[J]. Water Saving Irrigation, 2012 (12): 9-15. (in Chinese with English abstract)
[38] 胡宏昌,田富強,張治,等. 干旱區(qū)膜下滴灌農(nóng)田土壤鹽分非生育期淋洗和多年動態(tài)[J]. 水利學(xué)報,2015,46(9):1037-1046.
Hu Hongchang, Tian Fuqiang, Zhang Zhi, et al. Leaching and multi-year dynamics of soil salinity in non-growth period of farmland soil salinity under film drip irrigation in arid area[J]. Journal of Hydraulic Engineering, 2015, 46(9): 1037-1046. (in Chinese with English abstract)
[39] 李文昊,王振華,鄭旭榮,等. 滴灌年限對棉田苗期水鹽分布及棉花生長的影響[J]. 中國農(nóng)學(xué)通報,2014,30(2):169-175.
Li Wenhao, Wang Zhenhua, Zheng Xurong, et al. Effects of drip irrigation years on the distribution of water and salt in cotton field at seedling stage and cotton growth[J]. Chinese Agricultural Science Bulletin, 2014, 30(2): 169-175. (in Chinese with English abstract)
[40] 周和平,王少麗,姚新華,等. 膜下滴灌土壤水鹽定向遷移分布特征及排鹽效應(yīng)研究[J]. 水利學(xué)報,2013,44(11):1380-1388.
Zhou Heping, Wang Shaoli, Yao Xinhua, et al. Study on directional migration and distribution characteristics of soil water and salt and salt discharge effect of drip irrigation under mulch[J]. Journal of Hydraulic Engineering, 2013, 44(11): 1380-1388. (in Chinese with English abstract)
[41] 張安琪,鄭春蓮,李宗毅,等. 棉花成苗和幼苗生長對咸水滴灌的響應(yīng)特征[J]. 灌溉排水學(xué)報,2018,37(10):16-22.
Zhang Anqi, Zheng Chunlian, Li Zongyi, et al. Response characteristics of cotton seedling formation and seedling growth to salt water drip irrigation[J]. Journal of Irrigation and Drainage, 2018, 37(10): 16-22. (in Chinese with English abstract)
[42] 虎膽·吐馬爾白,吳爭光,蘇里坦,等. 棉花膜下滴灌土壤水鹽運移規(guī)律數(shù)值模擬[J]. 土壤,2012,44(4):665-670.
Hudan·Tumarbai, Wu Zhengguang, Suritan, et al. Numerical simulation of soil water and salt transport law of drip irrigation under cotton film[J]. Soil, 2012, 44(4): 665-670. (in Chinese with English abstract)
[43] 潘延鑫,羅紈,賈忠華,等. 基于HYDRUS模型的鹽堿地土壤水鹽運移模擬[J]. 干旱地區(qū)農(nóng)業(yè)研究,2017,35(1):135-142.
Pan Yanxin, Luo Wan, Jia Zhonghua, et al. Simulation of water and salt transport in saline-alkali soil based on HYDRUS model[J]. Agricultural Research in the Arid Areas, 2017, 35(1): 135-142. (in Chinese with English abstract)
Soil salinity accumulation and model simulation of cotton under mulch drip irrigation with different salinity level water
Yang Guang1, Li Wanjing1, Ren Futian1, He Xinlin1※, Wang Chunxia1, Qiao Changlu1, Li Xiaolong1, Lei Jie1, Li Fadong2,3
(1.,,,832000,; 2.,100049,;3.,,100101,)
Mulch drip irrigation has great benefits to save water for high cotton production in Xinjiang, China. Among them, freshwater has widely been used in agricultural irrigation. Highly efficient exploitation and utilization of saltwater resources have been the potential urgent to alleviate the ongoing freshwater shortages. In this study, a three-year growing season field experiment was conducted with different salinity level water irrigation, thereby analyzing the soil salt content within the different soil layers during the whole growth period of cotton. A salinity threshold of cotton was determined under saltwater mulch drip irrigation. An HYDRUS-2D model of soil salt was also built in cotton field under saltwater drip irrigation using the theory of soil water and solute movement. A numerical simulation was conducted for the distribution and accumulation characteristics of soil salt. The experiment was carried out in Shihezi University, China. The base presented an average altitude of 450.8 m and a geographical location of 85°59′47″ E, 44°19′26″ N. Cotton was planted in each plot with the size of 2 m×2 m×2 m. The irrigation water was treated with five salinity levels: 2, 3, 4, 5, and 6 g/L. The ratio of chemicals NaHCO3, Na2SO4, NaCl, CaCl2, and MgCl2were 1:7:8:1:1, according to the composition of local groundwater. The results showed that: 1) The salt accumulated less under 2, 3, and 4 g/L salinity treatments, where the plant height, chlorophyll, and yield of cotton were higher than those under 5 and 6 g/L salinity treatments. Therefore, 4 g/L salinity level was the threshold of irrigation water. 2) The soil salt gradually accumulated with the growth period of irrigationand reached the peak at the opening period. The soil electrical conductivity at the emitter increased at first and then decreased with the peak value in 60-70 cm soil layer, as the soil depth increased. The soil electrical conductivity of different salinity treatments were 3.04, 3.18, 3.15, 3.00, and 3.12 dS/m, respectively. 3) There was a more obvious accumulation trend with the increase in the salinity of irrigation water sources. The simulated salt accumulation was ranked in the order of 30 cm > 50 cm > 10 cm soil layers. There was in good agreement, where the Mean Absolute Error (MAE)<0.168, Mean Relative Error (MRE)< 15.321, Root Mean Square Error (RMSE)<0.2, Coefficient of determination2>0.79 between the measured and simulated values of different soil layers. Therefore, the 4 g/L salinity level was suitable for the mulch drip irrigation of cotton using saline water. The finding can provide promising guidance for further exploitation and utilization of saltwater resources, particularly for the sustainable development of irrigated agriculture in semi-arid and arid areas.
soils; salinity; cotton; mulch drip irrigation; numerical simulation
楊廣,李萬精,任富天,等. 不同礦化度咸水膜下滴灌棉花土壤鹽分累積規(guī)律及其數(shù)值模擬[J]. 農(nóng)業(yè)工程學(xué)報,2021,37(19):73-83.doi:10.11975/j.issn.1002-6819.2021.19.009 http://www.tcsae.org
Yang Guang, Li Wanjing, Ren Futian, et al. Soil salinity accumulation and model simulation of cotton under mulch drip irrigation with different salinity level water[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(19): 73-83. (in Chinese with English abstract) doi:10.11975/j.issn.1002-6819.2021.19.009 http://www.tcsae.org
2021-03-30
2021-09-13
國家自然科學(xué)基金-新疆聯(lián)合基金重點項目(U1803244);兵團科技攻關(guān)計劃項目(2021AB021);石河子大學(xué)科學(xué)技術(shù)研究項目(CXRC201801,RCZK2018C22,RCZK202026)
楊廣,博士,教授,博士生導(dǎo)師,研究方向為干旱區(qū)水資源高效利用技術(shù)。Email:mikeyork@163.com
何新林,博士,教授,博士生導(dǎo)師,研究方向為干旱區(qū)水資源高效利用技術(shù)。Email:hexinlin2002@163.com
10.11975/j.issn.1002-6819.2021.19.009
S275.6
A
1002-6819(2021)-19-0073-11