崔 凡,陳柏平,吳志遠(yuǎn),聶俊麗,李思遠(yuǎn),耿曉航,李 帥
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基于探地雷達(dá)功率譜和雷達(dá)波振幅包絡(luò)估算砂壤含水率
崔 凡1,陳柏平2,吳志遠(yuǎn)3,聶俊麗4※,李思遠(yuǎn)2,耿曉航2,李 帥2
(1. 中國礦業(yè)大學(xué)(北京)煤炭資源與安全開采國家重點(diǎn)實(shí)驗(yàn)室,北京 100083; 2. 中國礦業(yè)大學(xué)(北京)地球科學(xué)與測繪工程學(xué)院,北京 100083; 3. 華北科技學(xué)院安全工程學(xué)院(中心),廊坊 065201; 4. 貴州大學(xué)國土資源部喀斯特環(huán)境與地質(zhì)災(zāi)害重點(diǎn)實(shí)驗(yàn)室,貴陽 550025)
為實(shí)現(xiàn)探地雷達(dá)(ground penetrating radar,GPR)技術(shù)對中國西部干旱地區(qū)淺部砂壤介質(zhì)含水率分布精確、快速、連續(xù)的探測,該文研究了耦合自回歸滑動(dòng)平均功率譜估計(jì)方法(auto regressive and moving average,ARMA)和雷達(dá)波振幅包絡(luò)平均值方法(average envelope amplitude,AEA)反演含水率提高反演精度的可行性。首先,使用自回歸滑動(dòng)平均功率譜估計(jì)方法(auto regressive and moving average,ARMA)和雷達(dá)波振幅包絡(luò)平均值方法(average envelope amplitude,AEA)分別反演雷達(dá)有效探深范圍內(nèi)的砂壤介質(zhì)體積含水率值。將雷達(dá)探測結(jié)果分別與取樣烘干法在各深度的測試結(jié)果進(jìn)行對比分析,發(fā)現(xiàn)針對研究區(qū)內(nèi)的干燥砂壤介質(zhì),使用ARMA方法能夠有效地反演出地表10 m深度內(nèi)砂壤介質(zhì)的體積含水率值,但0~0.5 m范圍內(nèi)含水率值反演結(jié)果不準(zhǔn)確;而AEA方法可準(zhǔn)確反演出該地區(qū)0~0.5 m范圍內(nèi)的體積含水率值。根據(jù)2種方法的適用性,構(gòu)建典型干旱地區(qū)淺部砂壤介質(zhì)(0~10 m)含水率的反演模型。實(shí)際探測顯示,聯(lián)合模型平均相對誤差為5.57%~16.71%、均方根誤差為0.62%~2.08%,在0~0.5 m范圍內(nèi)反演的含水率平均相對誤差比ARMA方法減少16.81%~41.80%,與AEA方法相比,聯(lián)合模型能夠反演更深地表的含水率。綜合表明聯(lián)合模型能夠快速、準(zhǔn)確、連續(xù)地獲得西部干旱區(qū)0~10 m范圍內(nèi)淺部砂壤介質(zhì)的體積含水率值。
土壤;含水率;探地雷達(dá);ARMA;振幅包絡(luò)平均值法
中國西部地區(qū)大多干旱且環(huán)境脆弱,地表主要介質(zhì)為砂壤,其含水率的分布是影響該地區(qū)植被生長及生態(tài)環(huán)境的關(guān)鍵因素??焖?、準(zhǔn)確地測定砂壤含水率,對環(huán)境治理和生態(tài)恢復(fù)有著重要意義[1-2]。目前,常見的土壤含水率測定方法中,烘干法的測定最為準(zhǔn)確[2],通常作為其他方法的標(biāo)定值,但其因費(fèi)時(shí)費(fèi)力并破壞土體本身,不適宜大面積實(shí)施。時(shí)域反射法(time domain reflectometry,TDR)、中子儀法等能夠較精確地探測出土壤的含水 率[3-4],但因其都以單點(diǎn)探測方式開展,同樣不能實(shí)現(xiàn)大面積的測量。以整體區(qū)域?yàn)槟繕?biāo)的遙感探測,雖然探測面積大,但因其為大尺度分析,探測精度無法滿足指導(dǎo)生態(tài)恢復(fù)的目的[5-8]。
探地雷達(dá)具有探測連續(xù)性強(qiáng)、速度快、精度高的特點(diǎn),是一種向地下介質(zhì)發(fā)射頻率為10~103MHz的電磁脈沖,對接收到的回波信號進(jìn)行處理分析,根據(jù)波形、強(qiáng)度、雙程走時(shí)等參數(shù)來推斷地下目標(biāo)體的空間位置、結(jié)構(gòu)及幾何形態(tài)等的方法[9]。近年來,探地雷達(dá)已被應(yīng)用于介質(zhì)含水率等物性的探測研究中,其中雷達(dá)反射波法、地面波法、鉆孔雷達(dá)法等,均屬于“波速-介電常數(shù)”法。這些方法都是通過雷達(dá)反射波、直達(dá)波計(jì)算波速,進(jìn)而獲取介質(zhì)的介電常數(shù),再由Topp等經(jīng)驗(yàn)公式計(jì)算含水率值[10]。這類方法由于地下介質(zhì)條件復(fù)雜,周圍干擾大,較難獲得精確的波速,從而影響含水率測量的精度。
相比于在時(shí)間域計(jì)算雷達(dá)信號的“波速-介電常數(shù)”方法,自回歸滑動(dòng)平均功率譜估計(jì)方法(auto regressive and moving average,ARMA)是一種頻率域譜分析方法,根據(jù)介質(zhì)及其物性的不同可引起頻域信號在能量、幅值、振幅包絡(luò)等信息的分布不同,達(dá)到反演介質(zhì)含水率的目的。崔凡等通過構(gòu)建“功率譜-含水率”模型有效反演出中國西部典型干旱地區(qū)10 m深度范圍內(nèi)的砂壤介質(zhì)含水率值[11-12]。但受算法原理所限,會導(dǎo)致第1個(gè)滾動(dòng)半時(shí)窗長度對應(yīng)的地表深度范圍內(nèi)(一般<1 m)含水率值計(jì)算不夠精確[13-14]。雷達(dá)波振幅包絡(luò)平均值法(average envelope amplitude,AEA)是在頻率域上通過分析、計(jì)算雷達(dá)早期信號的平均振幅包絡(luò)建立其與地層淺部介質(zhì)介電常數(shù)的關(guān)系,從而計(jì)算出介質(zhì)的介電常數(shù),再由Topp經(jīng)驗(yàn)公式計(jì)算含水率值[14-15]。Elena等驗(yàn)證雷達(dá)波早期振幅包絡(luò)與地層的介電常數(shù)存在很高的相關(guān)性[16]。Matteo等從理論上驗(yàn)證探地雷達(dá)信號第1半周期的振幅包絡(luò)與介電常數(shù)的相關(guān)性最好[17]。吳志遠(yuǎn)等通過對AEA、TDR、鉆孔取樣烘干3種方法進(jìn)行對比,表明AEA方法能夠快速、精確地反演早期信號對應(yīng)的淺部地層體積含水率[18]。
ARMA與AEA方法都可以有效避免“波速-介電常數(shù)”雷達(dá)含水率探測方法中難以獲取準(zhǔn)確波速的問題。但2種方法雖受各自原理所限,只能分別在一定深度范圍內(nèi)準(zhǔn)確反演含水率。本研究根據(jù)其各自特點(diǎn),從理論上構(gòu)建綜合反演地表砂壤介質(zhì)(0~10 m)含水率的關(guān)系模型,以期達(dá)到精確、快速、連續(xù)反演砂壤體積含水率的目標(biāo),為西部地區(qū)提供一種精確的砂壤含水率測量方法。
ARMA譜分析基于平穩(wěn)線性信號過程建立模型來估計(jì)功率譜的密度[19-21]。通過將平穩(wěn)的數(shù)字雷達(dá)信號進(jìn)行ARMA譜分析,可以得到譜密度[13,22],再使用Cadzow譜分析方法進(jìn)行計(jì)算[23-24],以減少對密度譜參數(shù)計(jì)算,并采用對數(shù)表示譜密度[9]。為獲得不同深度位置的含水率,對雷達(dá)信號加高斯時(shí)間窗口函數(shù)[9,25],選取長度為?(ns)的滾動(dòng)時(shí)間窗,從信號起點(diǎn)開始向下滾動(dòng),將整個(gè)雷達(dá)時(shí)間信號分成若干個(gè)時(shí)間窗,每個(gè)時(shí)間窗口對應(yīng)相應(yīng)的探測深度,則該深度的雷達(dá)反射能量可轉(zhuǎn)換為對應(yīng)窗口內(nèi)譜密度能量的均值[26],其形成的滾動(dòng)剖面如下[9,26]:
式中()為時(shí)間窗內(nèi)的譜均值;T為選取的滾動(dòng)時(shí)間窗,ns;為時(shí)間窗個(gè)數(shù)。
由于各頻率信號對應(yīng)的功率譜能量值是以各頻率為中心,以能量包絡(luò)的形式分布的,而介質(zhì)體積含水率值的不同會影響接收到雷達(dá)回波信號在不同頻率范圍內(nèi)的能量分布,通過計(jì)算各時(shí)間窗范圍內(nèi)包絡(luò)的功率譜能量值和高、低頻率范圍所占整個(gè)頻譜能量的百分比,由公式(2)獲得對應(yīng)深度的體積含水率[27]:
式中θ為砂壤介質(zhì)的體積含水率,%;0為低、高頻率包絡(luò)在頻率域上的分割點(diǎn);為連續(xù)分布的頻率值;為功率譜值;為全部頻率的功率譜能量總和,k為含水率模型的修正參數(shù),由于實(shí)際采集過程中,使用的天線不同,需要在實(shí)際探測前通過選定幾個(gè)試驗(yàn)樣點(diǎn)進(jìn)行標(biāo)定以確定k值。
但是,ARMA方法在第1個(gè)半滾動(dòng)時(shí)窗范圍內(nèi)不具有重疊性,無法獲得被測介質(zhì)表層極淺范圍內(nèi)精確的體積含水率值。
電磁波在地下介質(zhì)傳播時(shí),受介質(zhì)的電導(dǎo)率、介電常數(shù)等參數(shù)的影響,振幅會呈指數(shù)衰減。試驗(yàn)?zāi)M發(fā)現(xiàn)介質(zhì)的介電常數(shù)越小,雷達(dá)單道信號的波動(dòng)會較早起跳且振幅較大[18],根據(jù)此關(guān)系建立高擬合度的振幅倒數(shù)與介電常數(shù)關(guān)系模型。
AEA方法基于該關(guān)系模型對雷達(dá)早期信號振幅包絡(luò)平均值與淺部介質(zhì)的相對介電常數(shù)進(jìn)行分析。通過淺地表相對介電常數(shù)與雷達(dá)信號的振幅包絡(luò)之間的關(guān)系,計(jì)算出介質(zhì)的相對介電常數(shù)ε,再利用Topp公式計(jì)算含水率[18,28-29]:
該方法能夠很好地測量出介質(zhì)表層的體積含水率,但由于雷達(dá)信號在傳播過程中的能量衰減,不能準(zhǔn)確地建立介電常數(shù)與信號振幅包絡(luò)值倒數(shù)的關(guān)系,對地表中深部含水率測量效果較差。
基于ARMA方法可以探測到砂壤地表中深部的體積含水率[11],但由于ARMA方法選取的時(shí)間窗較大,同時(shí)受算法本身所限,在第1個(gè)半滾動(dòng)時(shí)窗范圍內(nèi)無法獲得精確結(jié)果,即第1個(gè)半滾動(dòng)時(shí)窗范圍內(nèi)的含水率計(jì)算不精確。滾動(dòng)時(shí)窗大小的選取以滾動(dòng)譜對象不發(fā)生奇變?yōu)樵瓌t,一般選取采樣時(shí)窗大小的1/10,采樣時(shí)窗大小可通過式(4)得到:
式中max為探測的最大深度,m;為電磁波在真空中傳播的速度,取0.3 m/ns。
在本研究實(shí)際探測中,采樣時(shí)窗設(shè)置為200 ns,選取的時(shí)間窗為20 ns,再根據(jù)被測砂壤的平均介電常數(shù)值約為8.5,則第1個(gè)半滾動(dòng)時(shí)窗范圍對應(yīng)深度約為0~0.5 m。
而AEA方法雖然因雷達(dá)信號能量的衰減,很難達(dá)到對一定深度的探測,但對地表極淺層的體積含水率值具有較高的測量準(zhǔn)確率[18]。
因此,綜合2種方法在含水率值反演上的適用性,本研究提出結(jié)合2種方法進(jìn)行聯(lián)合含水率反演的構(gòu)想,并基于雷達(dá)信號在時(shí)間與深度上的相關(guān)性,構(gòu)建了一個(gè)利用探地雷達(dá)數(shù)據(jù)反演砂壤地表體積含水率值θ的聯(lián)合關(guān)系模型,如式(5)所示:
研究區(qū)(圖1)選擇在陜西省與內(nèi)蒙古自治區(qū)交界處伊金霍洛旗烏蘭木倫鎮(zhèn)大柳塔礦區(qū),該研究區(qū)地表主要為砂壤地層,粒徑0.3~3.0 mm,有機(jī)質(zhì)質(zhì)量分?jǐn)?shù)為1.1~7.8 g/kg,厚度為3~13 m,平均為10 m。該地區(qū)平均每年的蒸發(fā)量是2 000~2 800 mm,而平均年降水量僅131~571 mm,具有典型的西部干旱地區(qū)特征。
圖1 研究區(qū)測線布置示意圖
如圖1所示,在研究區(qū)內(nèi)布設(shè)1條長900 m的測線,并在測線上以25 m為間隔布置采樣點(diǎn)共37個(gè)。使用中國礦業(yè)大學(xué)(北京)自主研發(fā)的GR型探地雷達(dá)系統(tǒng)對測線進(jìn)行探測。由于研究區(qū)地表介質(zhì)為干燥砂壤,電導(dǎo)率低不易造成雷達(dá)信號衰減,利于雷達(dá)波能量的傳播,故選用中心頻率為200 MHz的天線,即可滿足10 m的探測深度。對該區(qū)域的介質(zhì)進(jìn)行電性調(diào)查后,取平均相對介電常數(shù)為8.7,根據(jù)雷達(dá)電磁波在地下的傳播規(guī)律和探測深度要求,將采樣時(shí)窗設(shè)置為200 ns,采樣點(diǎn)數(shù)為1 024,使用時(shí)間觸發(fā)進(jìn)行連續(xù)探測,系統(tǒng)A/D轉(zhuǎn)換頻率為 200 kHz,天線平均移動(dòng)速度約1 m/s。在天線移動(dòng)到采樣點(diǎn)時(shí),通過儀器標(biāo)定位置,為后續(xù)數(shù)據(jù)處理分析作備用。
實(shí)際探測中,在探地雷達(dá)探測后,立即對測線上的每個(gè)采樣點(diǎn)處使用洛陽鏟進(jìn)行鉆孔取樣,每個(gè)鉆孔深度在10 m左右,每隔0.5 m深提鉆,用環(huán)刀在鏟頭內(nèi)取樣并密封保存,并在當(dāng)天采用實(shí)驗(yàn)室烘干法(110 ℃、5~24 h)測出樣本的質(zhì)量含水率,并轉(zhuǎn)換為體積含水率值[30]。
為驗(yàn)證聯(lián)合模型測量砂壤介質(zhì)體積含水率的準(zhǔn)確性,對測線上37個(gè)采樣點(diǎn)以0.5 m為間隔采用取樣烘干法測量的含水率作為標(biāo)定值,和ARMA、AEA方法、聯(lián)合模型的含水率值測量結(jié)果進(jìn)行對比分析。
將取樣烘干法和ARMA方法所測量的含水率值進(jìn)行比較,如圖2所示,結(jié)果顯示ARMA對地層0~0.5 m內(nèi)深度的含水率反演結(jié)果不理想,相對誤差范圍分別為19.13%~79.10%、9.11%~64.76%,平均相對誤差(mean relative error,MRE)分別為47.37%、30.32%,但在1.0、5.0、10.0 m處的地表含水率反演良好,相對誤差范圍分別為2.67%~19.46%、4.82%~25.96%、5.25%~30.60%,平均相對誤差分別為11.2%、14.22%、16.71%。結(jié)果表明ARMA方法能夠很好地反演出0.5~10 m深度內(nèi)地表的含水率,但對0~0.5 m內(nèi),即第1個(gè)半滾動(dòng)時(shí)窗(10 ns)對應(yīng)的深度范圍的含水率值反演不準(zhǔn)確。
注(Note):*,P<0.05
將取樣烘干法和AEA方法獲得地表深度在0、0.5、1 m的含水率值進(jìn)行對比分析,如圖3所示,可以看出AEA在0~0.5 m范圍內(nèi)的反演效果較好,與取樣烘干法測量的含水率值的相對誤差范圍分別為2.50%~10.22%、10.00%~17.17%,MRE為5.57%、13.51%,兩者間的相關(guān)系數(shù)分別為0.98、0.99。但隨著測量深度的增加,AEA方法反演的含水率值準(zhǔn)確程度不斷下降,在1 m處AEA反演的含水率與烘干法存在較大差異,相對誤差為20.69%~96.60%,MRE為54.15%,相關(guān)系數(shù)僅為0.07。分析結(jié)果表明AEA方法可適用于該研究區(qū)的0~0.5 m地表深度的含水率計(jì)算,但隨著深度加深,雷達(dá)信號的振幅衰減嚴(yán)重,已不能建立起振幅包絡(luò)平均值與介質(zhì)的介電常數(shù)的關(guān)系,反演結(jié)果準(zhǔn)確性低、不可用。
根據(jù)構(gòu)建的聯(lián)合模型,且由于式(5)中的ARMA選取的滾動(dòng)時(shí)間窗大小為采樣時(shí)窗的1/10(20 ns),故選擇賦值為10 ns。則聯(lián)合模型成為對0~10 ns對應(yīng)的地表深度(0~0.5 m)的含水率值,采用AEA方法反演的數(shù)值,對10~200 ns對應(yīng)的地表深度(0.5~10 m)采用ARMA方法反演的數(shù)值,從而獲得精確、完整的0~10 m深度范圍的砂壤介質(zhì)體積含水率分布值。圖4描述的是聯(lián)合模型方法和取樣烘干法在地表0、0.5、1.0、5.0、 10.0 m上體積含水率值的對比情況,結(jié)果顯示:使用聯(lián)合模型可以準(zhǔn)確地反演出研究區(qū)0~10 m的地表含水率值,MRE為5.57%~16.71%、RMSE為0.62%~2.08%,與AEA方法相比,提高了反演的深度,與ARMA方法相比,在0~0.5 m范圍內(nèi)MRE比ARMA方法減少16.81%~41.80%,提高了在地表淺部的反演精度。試驗(yàn)結(jié)果綜合表明聯(lián)合模型可以精確反演由淺到深的砂壤體積含水率值。
圖3 不同深度上烘干法與AEA體積含水率對比
圖4 不同深度上烘干法與聯(lián)合模型體積含水率對比圖
1)在典型砂壤地層中,利用AEA方法能夠測量研究區(qū)地表淺部(0~0.5 m)砂壤介質(zhì)的體積含水率,并與烘干法實(shí)測數(shù)值接近,MRE為5.57%~13.51%,但對更深的地表含水率反演效果不理想。
2)利用ARMA方法能夠測量地表中深部(0.5~10 m)的體積含水率,與實(shí)測含水率的MRE最大為16.71%,但淺部的地表含水率反演結(jié)果與實(shí)測數(shù)據(jù)相差較大,MRE為30.32%~47.37%,其與理論結(jié)果相符,表明使用ARMA方法適合反演研究區(qū)地表中深部的含水率。
3)利用AEA和ARMA聯(lián)合反演的模型方法能夠彌補(bǔ)ARMA與AEA各自的缺點(diǎn)。聯(lián)合模型反演方法MRE為5.57%~16.71%、RMSE為0.62%~2.08%,在0~0.5 m范圍內(nèi)反演的含水率MRE比ARMA方法減少16.81%~41.80%,與AEA方法相比,聯(lián)合模型提高了地表含水率的反演深度。綜合表明聯(lián)合模型能精確、快速、連續(xù)地測量出地表深度0~10 m內(nèi)的含水率,提高ARMA和AEA的適用性。
由于本研究針對的是砂壤介質(zhì),該方法對其他介質(zhì)的含水率測量的適用性以及更深深度的探測還有待進(jìn)一步研究。
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Soil moisture estimation based on GPR power spectrum and envelope amplitude in sand loam
Cui Fan1, Chen Baiping2, Wu Zhiyuan3, Nie Junli4※, Li Siyuan2, Geng Xiaohang2, Li Shuai2
(1.100083,;2.100083,;3.065201,;4.550025,)
The soil water is of great significance to the management and restoration of the ecological environment in western China. In order to realize an accurate, rapid and continuous detection of the distribution of water content in the shallow sandy loam by virtue of the ground penetrating radar (GPR) technology, 2 means were thus used including radar wave average envelope amplitude (AEA) and auto-regressive and moving average (ARMA) power spectrum recognition, which were also utilized to invert the water contents of the shallow sandy loam soils. AEA was used to analyze and establish the relationship between the radar early-time average amplitude envelope signal value and the dielectric constants of surface strata with depth less than 1 m. ARMA power spectrum recognition was used to build the relation between power spectrum and water contents of the sandy loam soils with depth range within radar’s maximum detection depth. The sandy loam soils with different water contents could differentiate the distribution of the envelopes of power spectrum. The variation of different frequency spectrum energy was related to the water contents in soil samples, which could be shown by the distribution of the high and low frequency envelopes. After the comparison of the water contents inverted by AEA, ARMA and drilling sampling, it was found that the water contents of the shallow sandy loam soils inverted by ARMA was effectively in the depth of 0-10 m. But the results were inaccurate in the depth of 0-0.5 m. However, the AEA provided accurate water contents of the shallow sandy loam soils in the depth of 0-0.5 m. The correlation coefficients of volumetric water contents derived by drilling sampling and inverted by ARMA were 0.57, 0.62, 0.96 and 0.99 respectively in the depth of 0, 0.5, 1.0 and 10.0 m, with the corresponding mean relative errors of 47.37%, 30.32%, 11.20%, and 16.71%. The volumetric water contents derived by AEA almost equaled the values derived by drilling sampling in the depth of 0-0.5 m. The correlation coefficient of volumetric water contents derived by drilling sampling and AEA were 0.98, 0.99 in the depth of 0-0.5 m respectively, but the correlation coefficient was only 0.07 when the depth was 1.0 m. Based on the applicability of the 2 methods, a joint model was established to invert the water contents of the shallow sandy loam soils in the depth of 0-10 m in the typical arid area of western China. The actual detection showed that the average relative error between the water contents and the drying method of the joint model in the range of 0-0.5 m decreased by 16.81%-41.80% compared to that of ARMA. Compared with AEA, the joint model could invert the water contents of deeper strata. The joint method had the average relative error and root mean square error was 5.57%-16.71% and 0.62%-2.08%, respectively. It indicates that the joint model can quickly, accurately and continuously obtain the volumetric water contents of the shallow sandy soils in the depth range varying from 0-10 m in the arid area of western China.
soils; water content; GPR; auto regressive and moving average; average envelope amplitude
崔 凡,陳柏平,吳志遠(yuǎn),聶俊麗,李思遠(yuǎn),耿曉航,李 帥. 基于探地雷達(dá)功率譜和雷達(dá)波振幅包絡(luò)估算砂壤含水率[J]. 農(nóng)業(yè)工程學(xué)報(bào),2018,34(7):121-127. doi:10.11975/j.issn.1002-6819.2018.07.016 http://www.tcsae.org
Cui Fan, Chen Baiping, Wu Zhiyuan, Nie Junli, Li Siyuan, Geng Xiaohang, Li Shuai. Soil moisture estimation based on GPR power spectrum and envelope amplitude in sand loam[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2018, 34(7): 121-127. (in Chinese with English abstract) doi:10.11975/j.issn.1002-6819.2018.07.016 http://www.tcsae.org
2017-10-10
2018-01-10
共伴生能源精準(zhǔn)開采北京市重點(diǎn)實(shí)驗(yàn)室;國家自然科學(xué)基金(41602364);國家重點(diǎn)研發(fā)計(jì)劃(2016YFC0801404);煤炭資源與安全開采國家重點(diǎn)實(shí)驗(yàn)室(中國礦業(yè)大學(xué))(SKLCRSM16KFA06,SKLCRSM16DCB14);山東省沉積成礦作用與沉積礦產(chǎn)重點(diǎn)實(shí)驗(yàn)室(DMSM2017051);青年人才拖舉工程(YESS20150139);貴州省工業(yè)攻關(guān)項(xiàng)目:黔科合GZ字[2015]3020;教育部人文社會科學(xué)研究青年基金(17YJCZH192)
崔 凡,安徽淮南人,博士,主要從事地球物理探測理論與方法的研究。Email:cuifan@cumtb.edu.cn
聶俊麗,博士,主要從事地球物理探測技術(shù)和環(huán)境問題的研究。Email:38240493@qq.com
10.11975/j.issn.1002-6819.2018.07.016
S152.7
A
1002-6819(2018)-07-0121-07