王秋霞,張勇,丁樹文,3?,葉馨陽,劉丹露,徐加盼,朱慧鑫

(1.華中農(nóng)業(yè)大學(xué)資源與環(huán)境學(xué)院，430070，武漢；2.長江水利委員會(huì)長江流域水土保持監(jiān)測(cè)中心站，430070，武漢；3.農(nóng)業(yè)部長江中下游耕地保育重點(diǎn)實(shí)驗(yàn)室，430070,武漢)

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花崗巖崩崗區(qū)土壤可蝕性因子估算及其空間變化特征

王秋霞1,張勇2,丁樹文1,3?,葉馨陽1,劉丹露1,徐加盼1,朱慧鑫1

(1.華中農(nóng)業(yè)大學(xué)資源與環(huán)境學(xué)院，430070，武漢；2.長江水利委員會(huì)長江流域水土保持監(jiān)測(cè)中心站，430070，武漢；3.農(nóng)業(yè)部長江中下游耕地保育重點(diǎn)實(shí)驗(yàn)室，430070,武漢)

土壤可蝕性K值是土壤侵蝕模型的必要參數(shù)，研究花崗巖崩崗區(qū)土壤可蝕性K值有助于宏觀判斷和定量分析崩崗區(qū)土壤侵蝕的空間變化特征。采集湖北通城花崗巖典型崩崗淋溶層、淀積層、母質(zhì)層土壤，運(yùn)用5種土壤可蝕性K值估算方法分析各層土壤可蝕性差異，通過室內(nèi)人工模擬降雨實(shí)驗(yàn)驗(yàn)證花崗巖風(fēng)化土可蝕性K值的有效性及5種估算方法的靈敏度。結(jié)果表明：花崗巖風(fēng)化土的各層土壤可蝕性差異顯著，母質(zhì)層平均K值最大，是淋溶層的1.20倍，淀積層的1.03倍，且各層土壤的穩(wěn)定含沙率和各粒徑流失量差異顯著；諾莫法估算的各層土壤的可蝕性K值與40 min每層土的穩(wěn)定含沙率之比最接近，諾莫法估算各層土壤可蝕性K值的靈敏度最高，為修正諾莫的1.5倍，EPIC模型法的6倍。因此，針對(duì)南方花崗巖風(fēng)化土可采用諾莫法準(zhǔn)確評(píng)價(jià)土壤可蝕性K值。通過估算崩崗不同層次土壤的可蝕性K值及其空間變化特征，對(duì)針對(duì)性地研究崩崗形成機(jī)制及其治理具有一定指導(dǎo)意義。

可蝕性因子; 估算; 諾謨方程; 修正諾謨方程; EPIC模型; Shirazi公式法; Torri模型法

淋溶層(eluvial horizon，EH)、淀積層(illuvial horizon，IH)和母質(zhì)層(parent material horizon)崩崗是在水力和重力綜合作用下山坡土體受破壞而崩塌和沖刷的侵蝕現(xiàn)象，屬于復(fù)合侵蝕類型[1-2]。對(duì)于南方花崗巖地區(qū)崩崗而言，崩崗各土層(淋溶層、淀積層和母質(zhì)層)的物質(zhì)組成，理化性質(zhì)，物質(zhì)遷移等都有較大差異[3-4]。崩崗的發(fā)生破壞了原有地形地貌和植被，導(dǎo)致大量的泥沙堆積，河道淤塞、農(nóng)田沖毀等，其危害僅次于滑坡、泥石流[5-6]。由于不同類型崩崗的侵蝕特征不同，須有針對(duì)性地采取有效措施進(jìn)行治理。

土壤可蝕性是定量計(jì)算土壤流失的重要指標(biāo)，是土壤侵蝕預(yù)報(bào)模型的必要參數(shù)[7]。土壤可蝕性反映土壤在雨滴打擊、徑流沖刷等外營力作用下被分散、搬運(yùn)的難易程度[8-9]。1963年，W.H.Wischmeier等[10]首先提出土壤可蝕性因子，并用K值來衡量土壤可蝕性大小。D.D.Christianson等[11]利用人工模擬降雨實(shí)驗(yàn)研究發(fā)現(xiàn)5種土壤的理化性質(zhì)與可蝕性因子K的關(guān)系，從而得出包含24個(gè)變量的土壤K值估算方法。K.Auerswald等[12]基于EPIC模型，建立由土壤有機(jī)碳質(zhì)量分?jǐn)?shù)和粒徑組成估算土壤可蝕性K值的方法。R.M.Bajracharya等[13]建立基于土壤理化性質(zhì)非線性最佳擬合計(jì)算公式。基于各個(gè)理化性質(zhì)指標(biāo)的土壤可蝕性估算方法的建立，在土壤侵蝕敏感性評(píng)價(jià)分析、土壤流失量預(yù)測(cè)及水土資源利用等方面得到廣泛應(yīng)用[14-15]。根據(jù)研究地點(diǎn)的土壤結(jié)構(gòu)組成、土壤理化性質(zhì)及土壤侵蝕特征，可采用不同的估算方法系統(tǒng)分析土壤的可蝕性隨時(shí)間、空間的變化特征。

我國楊萍等[16]和朱冰冰等[17]在小流域尺度下通過數(shù)學(xué)統(tǒng)計(jì)方法闡明土壤可蝕性K值存在很強(qiáng)的空間變異性。卜兆宏等[18]針對(duì)我國亞熱帶7種代表性土壤，采用人工模擬降雨和田間實(shí)測(cè)法對(duì)比研究，發(fā)現(xiàn)紫色土的土壤可蝕性K值最高。姜小蘭等[19]、張科利等[20]和趙輝等[21]針對(duì)我國南方主要易蝕土壤，采用土壤可蝕性K值經(jīng)驗(yàn)計(jì)算模型并結(jié)合二次樣條函數(shù)插值法，研究發(fā)現(xiàn)第四紀(jì)紅黏土發(fā)育的紅壤K值最大，紫色土次之，花崗巖發(fā)育的紅壤最小[19-21]。史學(xué)正等[22]針對(duì)江西紅壤區(qū)，采用小區(qū)試驗(yàn)資料，實(shí)測(cè)不同土壤類型的可蝕性因子K值，并比較了小區(qū)實(shí)測(cè)值與諾謨圖計(jì)算值的差異[23]。目前，關(guān)于紫色土的土壤可蝕性K值的研究較多，其估算方法較完善，而南方紅壤區(qū)花崗巖風(fēng)化土的可蝕性K值的估算方法及空間變化特征尚不明確；因此，本文擬應(yīng)用空間對(duì)比法對(duì)花崗巖風(fēng)化土進(jìn)行垂直向?qū)哟伍g的分析，通過人工模擬降雨實(shí)驗(yàn)檢驗(yàn)5種估算方法求得的花崗巖風(fēng)化土不同土層的可蝕性K值的有效性。

1　材料和方法

1.1實(shí)驗(yàn)設(shè)備和材料

實(shí)驗(yàn)裝置：長2 m×寬0.6 m×深0.2 m單土槽車，降雨器，雨量筒×4，1 L徑流瓶時(shí)域反射儀(TDR)。

實(shí)驗(yàn)材料：該試驗(yàn)研究樣品根據(jù)崩崗發(fā)生剖面的土壤層次，采取湖北通城花崗巖風(fēng)化土發(fā)育較典型的淋溶層、淀積層、母質(zhì)層土樣，采樣后用鋁盒和環(huán)刀測(cè)定土壤含水量及土壤密度大小，用環(huán)刀法測(cè)定各土層土壤的入滲過程。土樣經(jīng)風(fēng)干、過篩后采用吸管法測(cè)定土壤質(zhì)地，采用重鉻酸鉀法測(cè)定土壤有機(jī)質(zhì)質(zhì)量分?jǐn)?shù)。

1.2研究方法

實(shí)驗(yàn)在華中農(nóng)業(yè)大學(xué)水土保持研究中心降雨大廳內(nèi)進(jìn)行。分別對(duì)3土層進(jìn)行人工模擬降雨實(shí)驗(yàn)，根據(jù)南方年降雨情況及地形地貌狀況，本實(shí)驗(yàn)設(shè)計(jì)降雨強(qiáng)度為(70±4)mm/h，降雨時(shí)長40 min，設(shè)計(jì)坡度20°，收集徑流和泥沙，每土層做5個(gè)平行實(shí)驗(yàn)。

試驗(yàn)所采用的土槽為自行設(shè)計(jì)的鋼槽。規(guī)格為長2 m，寬0.6 m，深0.2 m。土槽徑流出口處安裝V形鋼槽用以收集徑流泥沙，將土樣按照室外實(shí)測(cè)密度裝在土槽車內(nèi)用以模擬自然條件下的坡面，每層土填車時(shí)以5 cm壓實(shí)1次，填裝3層，每層均勻壓實(shí)到固定密度1.37 g/cm3。

降雨過程中將4個(gè)雨量筒均勻擺放在土槽車兩側(cè)進(jìn)行降雨強(qiáng)度數(shù)據(jù)的收集，用徑流瓶收集每2 min土槽產(chǎn)生的徑流及泥沙，收集階段記錄細(xì)溝產(chǎn)生的時(shí)間并觀察細(xì)溝產(chǎn)生狀況。測(cè)量并記錄各土層每2 min收集的徑流量，并將收集的泥沙進(jìn)行烘干稱量。

運(yùn)用5種可蝕性K值估算方法，通過進(jìn)行降雨實(shí)驗(yàn)來驗(yàn)證花崗巖風(fēng)化土可蝕性K值的有效性。所得數(shù)據(jù)使用SPSS 18.0軟件進(jìn)行處理分析。

1.2.1諾謨方程

KNomo=[2.1(N1N2)1.14(12-O)×10-4+3.25(S-2)+2.5(F-3)]/100。

(1)

式中：N1=粉砂(0.002～0.05 mm)質(zhì)量分?jǐn)?shù)+極細(xì)砂(0.05～0.1 mm)質(zhì)量分?jǐn)?shù)，%；N2=100-黏粒(<0.002 mm)質(zhì)量分?jǐn)?shù)，% ；O為有機(jī)質(zhì)質(zhì)量分?jǐn)?shù)，%；S為土壤結(jié)構(gòu)參數(shù)；F為土壤滲透級(jí)別。

根據(jù)花崗巖崩崗區(qū)各土層的有機(jī)質(zhì)質(zhì)量分?jǐn)?shù)確定土壤結(jié)構(gòu)體大小，得出淋溶層、淀積層、母質(zhì)層的土壤結(jié)構(gòu)參數(shù)S均為1。根據(jù)每土層的飽和水力傳導(dǎo)率確定土壤滲透率，確定淋溶層、淀積層、母質(zhì)層的土壤滲透級(jí)別F分別為3、3、4。

1.2.2修正諾謨方程

KModified-nomo=[2.1(N1N2)1.14(12-O)×10-4+3.25(2-S)+2.5(F-3)]/100。

(2)

式中各參數(shù)意義及取值同式(1)。

1.2.3EPIC模型

KEPIC={0.2+0.3exp[-0.025 6YSAN(1.0-

YSIL/100)]}×[YSIL/(YCLA+YSIL)]0.3×

{1.0-0.25C/[C+exp(3.72-2.95C)]}×

{1.0-0.7YSN1/[YSN1+exp(-5.51+22.9YSN1)]}。

(3)

式中：YSAN為砂粒(0.05～2.0 mm)質(zhì)量分?jǐn)?shù)，%；YSIL為粉砂(0.002～0.05 mm)質(zhì)量分?jǐn)?shù)，%；YCLA為黏粒(<0.002 mm)質(zhì)量分?jǐn)?shù)，%；C為有機(jī)碳質(zhì)量分?jǐn)?shù)，%；YSN1=1-YSAN/100，可根據(jù)土壤有機(jī)質(zhì)質(zhì)量分?jǐn)?shù)得出。

1.2.4Shirazi公式法

(4)

Dg=exp[0.01∑fiInmi]。

式中:fi為原土壤中第i個(gè)粒徑級(jí)組成比例，%；mi為小于第i個(gè)粒徑級(jí)的算術(shù)平均值，mm。

1.2.5Torri模型法

(5)

式中:O為土壤有機(jī)質(zhì)質(zhì)量分?jǐn)?shù)，%；C為黏粒(<0.002 mm)的質(zhì)量分?jǐn)?shù)；di為土壤機(jī)械組成中第i級(jí)土壤顆粒的最大值，mm；di-1為第i等級(jí)土壤顆粒的最小值，mm；當(dāng)i=1時(shí),d0=0.000 05 mm。fi為相應(yīng)粒徑等級(jí)土壤顆粒質(zhì)量分?jǐn)?shù)。基于砂粒(0.05～2 mm)、粉粒 (0.002～0.05 mm) 和黏粒 (<0.002 mm)3個(gè)粒徑計(jì)算Dg。

2　分析與討論

2.1花崗巖風(fēng)化土不同土層質(zhì)地分析

采取花崗巖崩崗區(qū)各層土壤進(jìn)行室內(nèi)理化性質(zhì)分析(表1)。

土壤質(zhì)地是影響土壤可蝕性K值的直接原因，因此不同土層的土壤粒徑是評(píng)價(jià)K值的前提和基礎(chǔ)。由表1可得：母質(zhì)層顆粒組成主要為砂粒，且質(zhì)量分?jǐn)?shù)最高，平均可達(dá)到72.79%，黏粒質(zhì)量分?jǐn)?shù)最低，平均僅有8.61%，淋溶層顆粒較細(xì)，淀積層顆粒主要為粉粒和砂粒；崩崗區(qū)3層土的砂粒和黏粒質(zhì)量分?jǐn)?shù)差異顯著，母質(zhì)層的粉粒質(zhì)量分?jǐn)?shù)與淋溶層、淀積層差異顯著。由表1可知，在花崗巖風(fēng)化土不同土層中，淋溶層的有機(jī)質(zhì)質(zhì)量分?jǐn)?shù)為1.24%，遠(yuǎn)高于淀積層和母質(zhì)層。這可能因?yàn)榱苋軐颖砻嬗袡C(jī)物質(zhì)較多，經(jīng)過微生物分解轉(zhuǎn)化成有機(jī)質(zhì)，增強(qiáng)了土壤結(jié)構(gòu)穩(wěn)定性；母質(zhì)層是缺少有機(jī)質(zhì)的砂質(zhì)土，砂粒單個(gè)存在，并不粘結(jié)成結(jié)構(gòu)體，顆粒較易分散和搬運(yùn)：因此，淋溶層具有較強(qiáng)的抗蝕能力，淀積層次之，母質(zhì)層最弱。

2.2采用5種估算方法比較土壤可蝕性K值

在表1的基礎(chǔ)上，采用式(1)～(5)估算各土層的可蝕性K值，見表2。

表1　通城花崗巖風(fēng)化土基本性質(zhì)

注：淋溶層：eluvial horizon，在下文簡稱EH；淀積層：illuvial horizon，在下文簡稱IH；母質(zhì)層：parent material horizon，在下文簡稱PMH。相同粒級(jí)數(shù)據(jù)采用Duncan檢驗(yàn)，不同字母代表差異性顯著(P<0.05)。下同。 Note:Eluvial horizon hereafter abbreviated as EH; illuvial horizon hereafter abbreviated as IH; and parent material horizon hereafter abbreviated as PMH.The data in the same grade of particle size were verified by Duncan,and the different letter indicates the difference significant (P<0.05).The same below.

表2　花崗巖崗區(qū)不同層次土壤可蝕性K值比較

土壤可蝕性K由土壤內(nèi)在性質(zhì)決定，具有一定的穩(wěn)定性，采用均方差評(píng)價(jià)可蝕性K值的靈敏程度，均方差越大，靈敏度越高。采用平均值表征每層土的抗侵蝕能力，平均值越大，土壤抗侵蝕能力越弱，土壤越易受侵蝕。由表2可得：花崗巖風(fēng)化土的母質(zhì)層平均K值最大，為淋溶層的1.20倍，淀積層的1.03倍，母質(zhì)層抵抗侵蝕的能力最弱，泥沙較易被分離、搬運(yùn)；對(duì)于同一土層，修正諾謨法測(cè)得K值最大，Kshirazi測(cè)得K值最??；諾莫法測(cè)得的K值均方差最高，為修正諾莫法的1.5倍，EPIC模型法的6倍，該方法較其余4種可蝕性K值估算方法靈敏度高，較易反映可蝕性K的空間變化特征；由諾莫方程、修正諾莫方程、花崗巖風(fēng)化土3層土的土壤結(jié)構(gòu)參數(shù)S及土壤滲透級(jí)別參數(shù)F可知，KModified-nomo>KNomo

恒成立。由5種方法估算的各層次土壤的K值差異顯著，其原因可能是選擇的土壤理化性質(zhì)指標(biāo)不同。諾莫法和修正諾莫法選用的是砂粒、粉粒、黏粒、極細(xì)砂的質(zhì)量分?jǐn)?shù)、土壤入滲特性及有機(jī)質(zhì)質(zhì)量分?jǐn)?shù)6個(gè)指標(biāo)，限制性較高，且每層土的指標(biāo)差異顯著，能綜合性的表征可蝕性K的空間變化特征；EPIC模型法選用的砂粒、粉粒、黏粒的質(zhì)量分?jǐn)?shù)和有機(jī)碳質(zhì)量分?jǐn)?shù)4個(gè)指標(biāo)；Shirazi公式法選用土壤幾何平均粒徑1個(gè)指標(biāo)，限制性低，且該方法是在不考慮有機(jī)質(zhì)質(zhì)量分?jǐn)?shù)或分級(jí)不標(biāo)準(zhǔn)條件下使用，局限性較大。

2.3基于降雨條件的土壤可蝕性K值比較

通過模型簡單估算花崗巖風(fēng)化土的可蝕性K值并不能有效評(píng)價(jià)這種土壤的抗侵蝕的能力大小，土壤被分離搬運(yùn)的能力大小反映土壤流失的強(qiáng)弱，通過進(jìn)行降雨實(shí)驗(yàn)來驗(yàn)證花崗巖風(fēng)化土可蝕性K值的有效性更為直接。各層土的可蝕性K值分別為KEH、KIH、KPMH，坡度、坡長、管理水平均一致，控制降雨強(qiáng)度在(70±4)mm/h，每次降雨無顯著差異(P<0.05)，由通用水土流失方程

A=R·K·L·S·C·P，

(6)

式中：A為單位面積坡地的土壤流失量，t/(hm2·a)；R為降雨和徑流侵蝕因子；K為土壤可蝕性因子；L·S為地形因子；C為作物管理因子；P為治理措施因子，可知各層土可蝕性K值與土壤的流失量A成正相關(guān)。

含沙率由徑流量及含沙量計(jì)算得出，其變化過程綜合反映徑流量和含沙量的動(dòng)態(tài)變化過程。采用含沙率、流失量和徑流流速對(duì)模擬降雨條件下土壤可蝕性進(jìn)行定量描述。通過分析3層土15次降雨的產(chǎn)沙數(shù)據(jù)，在各層土初期含水量達(dá)(20±2)%的情況下，3層土在降雨時(shí)間段內(nèi)的含沙率如圖1。

圖1　3層土體的含沙率Fig.1　Sediment concentration of three soil layers

由圖1可知：母質(zhì)層的含沙率隨時(shí)間波動(dòng)較大，但整體呈下降趨勢(shì)；淀積層的含沙率呈緩慢上升趨勢(shì)；淋溶層含沙率整體呈緩慢下降趨勢(shì)。母質(zhì)層的含沙率明顯高于淀積層和淋溶層，淀積層平均含沙率高于淋溶層。

徑流流速指單位時(shí)間內(nèi)的徑流量，即是徑流對(duì)坡面土壤產(chǎn)生侵蝕的直接動(dòng)力。通過分析3層土15次降雨的徑流數(shù)據(jù)，在各層土初期含水量達(dá)(20±2)%、降雨雨強(qiáng)為70 mm/h和坡度20°的情況下，3層土在降雨時(shí)間段內(nèi)的徑流流速如圖2。

圖2　3層土體的徑流流速Fig.2　Runoff velocity of three soil layers

分析15次降雨徑流數(shù)據(jù)得出3層土體的徑流流速在整個(gè)降雨時(shí)間段內(nèi)表現(xiàn)出均勻差異，且在10 min后都趨于平穩(wěn)。母質(zhì)層的穩(wěn)定徑流流速最大，淋溶層次之，淀積層的穩(wěn)定徑流流速最小。這可能由于淋溶層顆粒較細(xì)，顆粒組成為黏粒，0.2～2 mm的土壤粒徑最多，土壤有機(jī)質(zhì)質(zhì)量分?jǐn)?shù)較高且結(jié)合緊密，密度小，小孔隙發(fā)育較完全。

40 min后各層土的含沙率和徑流流速逐漸穩(wěn)定。由3層土的穩(wěn)定含沙率、徑流流速和流失量(表3)可知：母質(zhì)層的穩(wěn)定含沙率與淋溶層、淀積層差異顯著；3層土的流失量差異顯著，母質(zhì)層的流失量最大；淋溶層、淀積層和母質(zhì)層的穩(wěn)定徑流流速無顯著差異。

假定淀積層可蝕性K值、穩(wěn)定含沙率、流失量為1，將5種可蝕性K值的相對(duì)大小與降雨產(chǎn)沙情況進(jìn)行對(duì)比，見表4。

由表4可知，母質(zhì)層的相對(duì)流失量為1.977 9，該值遠(yuǎn)大于其余4種方法估算的母質(zhì)層K值，這可能由于母質(zhì)層的砂粒質(zhì)量分?jǐn)?shù)較高，在降雨徑流沖刷過程中較易形成溝蝕，加劇母質(zhì)層的土壤侵蝕過程，使流失量急劇增加，而且受裝土條件的影響不能穩(wěn)定的檢驗(yàn)可蝕性；母質(zhì)層的相對(duì)穩(wěn)定含沙率為1.080 2，該值較接近其余4種方法估算的母質(zhì)層K值。這可能由于淋溶層黏粒及有機(jī)質(zhì)質(zhì)量分?jǐn)?shù)較高，增加了土壤結(jié)構(gòu)的穩(wěn)定性，在降雨徑流沖刷過程中顆粒不易被分離、搬運(yùn)；因而在非長期觀測(cè)條件下，選用3層土的穩(wěn)定含沙率來檢驗(yàn)可蝕性K值更有效。淋溶層的穩(wěn)定含沙率為0.271 8，該值小于對(duì)應(yīng)的K值，這可能由于淋溶層不易形成溝蝕，達(dá)到穩(wěn)定含沙率后的侵蝕過程比較穩(wěn)定。通過比較淋溶層的可蝕性K值大小確定最適合花崗巖風(fēng)化土的可蝕性K值估算諾謨法，修正諾莫法次之。

表3　不同土層的降雨指標(biāo)

注：相同粒級(jí)數(shù)據(jù)采用Duncan檢驗(yàn)，不同字幕代表差異性顯著(P<0.05)。Note:The data in the same grade of particle size were verified by Duncan,and the different letter indicates the difference significant (P<0.05)

表4　綜合比較各土層可蝕性K值及降雨指標(biāo)

3　結(jié)論

1)花崗巖崩崗區(qū)不同土層理化性質(zhì)差異顯著。母質(zhì)層顆粒組成主要為砂粒，黏粒質(zhì)量分?jǐn)?shù)最低，平均僅有8.61%，淋溶層顆粒較細(xì)，淀積層顆粒主要為粉粒和砂粒；各土層的有機(jī)質(zhì)質(zhì)量分?jǐn)?shù)差異明顯。淋溶層的有機(jī)質(zhì)質(zhì)量分?jǐn)?shù)為1.24%，遠(yuǎn)高于淀積層和母質(zhì)層；因而，淋溶層具有較強(qiáng)的抗蝕能力，淀積層次之，母質(zhì)層最弱。在崩崗治理中應(yīng)加強(qiáng)對(duì)母質(zhì)層和淀積層的保護(hù)。鄧良基等[24]對(duì)四川自然土壤和旱地土壤可蝕性進(jìn)行研究，發(fā)現(xiàn)土壤理化性質(zhì)是影響K值大小的內(nèi)在原因，且土壤侵蝕進(jìn)程直接影響K值大??；因此，在崩崗不斷發(fā)育過程中，各層土土壤可蝕性K值將會(huì)發(fā)生變化。

2)花崗巖風(fēng)化土的母質(zhì)層平均K值為淋溶層的1.20倍，淀積層的1.03倍，土壤抗侵蝕能力越弱，泥沙較易被分離、搬運(yùn)；諾莫法估算K值的均方差最高，為修正諾莫法的1.50倍，EPIC模型法的6.00倍，諾莫法靈敏度高較易反映可蝕性K的空間變化特征；通過進(jìn)行降雨實(shí)驗(yàn)來驗(yàn)證花崗巖風(fēng)化土可蝕性K值的有效性更為直接。在未長期觀測(cè)條件下，用40 min穩(wěn)定含沙率檢驗(yàn)不同土層可蝕性的敏感程度，各土層的穩(wěn)定含沙率之比為0.271 8∶1∶1.080 2，諾莫法測(cè)得的各土層可蝕性K值之比為0.673 6∶1∶1.025 4，該比值最接近于各土層穩(wěn)定含沙率之比，且諾莫法估算的土壤可蝕性的靈敏度高，因而選用諾莫法估算花崗巖風(fēng)化土崩崗區(qū)可蝕性K值及研究其空間變化特征。

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Estimation and spatial variation characteristics of soil erosion factors of granite collapse region

Wang Qiuxia1,Zhang Yong2,Ding Shuwen1,3,Ye Xinyang1,Liu Danlu1,Xu Jiapan1,Zhu Huixin1

(1.College of resources and environment,Huazhong Agricultural University,430070,Wuhan,China; 2.Yangtze River Basin Monitoring Center Station for Soil and Water Conservation,Changjiang Water Resource Commission of the Ministry of Water Resources, 430070,Wuhan,China; 3.Key Laboratory of Arable Land Conservation (Middle and Lower Reaches of Yangtze River), Ministry of Agriculture,430070,Wuhan,China)

[Background] Soil erodibility K value is a required parameter of soil erosion models,it is an index to indicate the sensitivity degree of soil erosion,and an accurate K is the prerequisite for constructing soil erosion model.Studying soil erodibility K-factor of granite collapse region contributes to macro-scope estimation and quantitative analysis on spatial variation characteristics of different soil layers.[Methods] Collecting eluvial horizon,illuvial horizon and parent material horizon of different soil layers in granite collapse region developing in Tongcheng,Hubei Province,then estimating by using five estimation methods of soil erodibility K value (nomo equation,modified-nomo equation,EPIC model,Shirazi model,Torri model),artificial simulated rainfall experiments were conducted to verify the effectiveness of the Soil erodibility K values of different soil layers in granite collapse region and the sensitivity of five estimation methods.According to the situation of the annual rainfall,topography and geomorphology,the rainfall intensity was designed (70±4) mm/h,rainfall duration was 40 min,the slope was 20°.[Results] 1) Parent material horizon (PMH) was mainly composed of sand particles; clay content was the lowest with the average of 8.61%.The particles in illuvial horizon (IH) were mainly silt and sand,and the soil organic matter content difference was significant.The mass fraction of organic matter in eluvial horizon (EH) was 1.24%,far higher than that in IH and PMH,therefore,EH possessed the strongest anti-erosion ability,the second for IH,and the worst for PMH.Thus,in the governance of collapse mound,the PMH and IH should be protected.Deng Liangji,et al [24] has revealed that in development process of collage mound,each layer of soil erodibility K value will change,therefore the change of K value was investigated as below.2) The soil erodibility of different soil layers in granite collapse region were significantly different,the average K value of the parent material layer was the highest,it was 1.20 times of the eluvial horizon and 1.03 times of the illuvial horizon; the stable sediment rate and the loss of particle sizes of different soil layers in granite collapse region were also significantly different.Erodibility K value of different soil layers by nomo equation was the closest to the stable sediment rate of different soil layers at 40 min precipitation.The sensitivity in estimating the soil erodibility K value of different layers by nomo equation was the highest,it was 1.5 times of modified-nomo equation and 6 times of EPIC model.[Conculsions] Therefore,nomo equation can accurately evaluate soil erodibility value of different soil layers in the granite collapse region.By estimating soil erodibility K value and the spatial variation characteristics of different soil layers in granite collapse region,this work is of certain guiding significance for the particular study of the formation mechanism and its governance of granite gully.

soil erodibility K value; estimation; nomo equation; modified-nomo equation; EPIC model; Shirazi model; Torri model

2016-01-08

2016-06-18

項(xiàng)目名稱：國家科技支撐計(jì)劃子課題“紅壤崩崗侵蝕區(qū)農(nóng)田質(zhì)量保護(hù)與崩崗治理技術(shù)與示范”(2011BAD31BO4)；國家自然科學(xué)基金“花崗巖紅壤優(yōu)先流及其與崩崗侵蝕發(fā)育的關(guān)系”(41571258)

王秋霞 (1991—),女，碩士研究生。主要研究方向：花崗巖風(fēng)化土可蝕性及崩崗穩(wěn)定性。E-mail:qxwangchn@163.com

簡介：丁樹文 (1964—),男，本科，副教授。主要研究方向：水土保持和農(nóng)業(yè)生態(tài)環(huán)境保護(hù)。E-mail:dingshuwen@mail.hzau.edu.cn

S157.1

A

1672-3007(2016)04-0001-08

10.16843/j.sswc.2016.04.001