王 艷,焦 燕,楊文柱,閆穎超,鄔 宏,靈 靈,史月超

內(nèi)蒙古河套灌區(qū)農(nóng)田非點(diǎn)源氮磷污染負(fù)荷估算

王 艷,焦 燕*,楊文柱,閆穎超,鄔 宏,靈 靈,史月超

(內(nèi)蒙古師范大學(xué)化學(xué)與環(huán)境科學(xué)學(xué)院,內(nèi)蒙古自治區(qū)環(huán)境化學(xué)重點(diǎn)實(shí)驗(yàn)室,內(nèi)蒙古 呼和浩特 010022)

為了解內(nèi)蒙古河套灌區(qū)農(nóng)田非點(diǎn)源污染現(xiàn)狀,引入降雨影響因子()和地形影響因子()對(duì)傳統(tǒng)的輸出系數(shù)模型(ECM)進(jìn)行改進(jìn),量化該地區(qū)的農(nóng)田非點(diǎn)源氮、磷污染負(fù)荷,結(jié)合污染物入河系數(shù)(),對(duì)農(nóng)田非點(diǎn)源氮磷入河(烏梁素海)量進(jìn)行估算,并識(shí)別污染物關(guān)鍵源區(qū).結(jié)果表明,河套灌區(qū)2021年農(nóng)田非點(diǎn)源總氮(TN)、總磷(TP)污染負(fù)荷為3520.998和407.125t,分別占不同土地利用類型污染負(fù)荷總量的79.674%和89.201%;農(nóng)田非點(diǎn)源TN、TP污染負(fù)荷空間分布一致,表現(xiàn)為靠近水體、排干的鄉(xiāng)鎮(zhèn)貢獻(xiàn)量最高,依次為新華鎮(zhèn)、新安鎮(zhèn)和塔爾湖鎮(zhèn),TN、TP污染負(fù)荷分別為316.658, 236.725, 199.344t/a和36.615, 27.371, 23.050t/a;農(nóng)田非點(diǎn)源TN、TP入河量為387.310t/a和16.285t/a,其中新華鎮(zhèn)、新安鎮(zhèn)、塔爾湖鎮(zhèn)、隆興昌鎮(zhèn)、團(tuán)結(jié)鎮(zhèn)和蠻會(huì)鎮(zhèn)是河套灌區(qū)的農(nóng)田非點(diǎn)源污染重點(diǎn)防治鄉(xiāng)鎮(zhèn);與實(shí)測(cè)值進(jìn)行比較,驗(yàn)證了改進(jìn)的輸出系數(shù)模型的合理性,相對(duì)誤差分別為-4.743%和19.037%.

河套灌區(qū)；農(nóng)田非點(diǎn)源污染；改進(jìn)的輸出系數(shù)模型；TN；TP

在過去的幾十年里,我國(guó)氮肥和磷肥的施用在提高作物產(chǎn)量的同時(shí),一系列農(nóng)業(yè)環(huán)境污染問題也逐漸顯現(xiàn),其中水環(huán)境污染問題尤其嚴(yán)重,水環(huán)境污染主要由點(diǎn)源污染和非點(diǎn)源污染兩部分構(gòu)成[1].隨著點(diǎn)源污染得到有效治理后,非點(diǎn)源污染對(duì)水環(huán)境的影響逐漸突出,其中,農(nóng)業(yè)非點(diǎn)源污染已成為水體富營(yíng)養(yǎng)化的主要污染源[2].《第二次全國(guó)污染源普查公報(bào)》[3]結(jié)果顯示,2017年農(nóng)業(yè)源水污染物中的化學(xué)需氧量、氨氮、總氮(TN)以及總磷(TP)排放量分別為1067.13,21.62,141.49和21.20萬t.

然而,農(nóng)業(yè)非點(diǎn)源污染的廣泛性、隨機(jī)性、潛伏性[4]等特點(diǎn),增加了研究和控制農(nóng)業(yè)非點(diǎn)源污染的難度,利用模型對(duì)農(nóng)業(yè)非點(diǎn)源污染負(fù)荷進(jìn)行定量估算是主要的研究方法之一.輸出系數(shù)模型[5](ECM)由于不考慮污染物運(yùn)移的復(fù)雜過程,具有參數(shù)少、建模成本低等特點(diǎn)而得到廣泛應(yīng)用,特別是對(duì)觀測(cè)數(shù)據(jù)和以往研究不足地區(qū)優(yōu)勢(shì)愈加明顯[6-7].一些學(xué)者通過對(duì)輸出系數(shù)模型進(jìn)行不同方面的改進(jìn)[8-10],探究更適合本流域的輸出系數(shù)模型,使模型模擬值與實(shí)測(cè)值更加吻合,并結(jié)合GIS等技術(shù)對(duì)污染物的空間分布特征進(jìn)行探究.由于污染物被農(nóng)作物、河道的截留等作用而產(chǎn)生滯留[11],并不會(huì)完全進(jìn)入水體.王萌等[12]在分析流域農(nóng)業(yè)非點(diǎn)源污染負(fù)荷時(shí),又考慮了污染物的入河系數(shù),減少了非點(diǎn)源污染估算過程中的不確定性.盡管眾多學(xué)者對(duì)模型的改進(jìn)提高了模型估算精度,但針對(duì)南方區(qū)域研究較多,對(duì)于北方區(qū)域研究較少.另外,將輸出系數(shù)模型應(yīng)用于農(nóng)業(yè)非點(diǎn)源污染負(fù)荷估算的研究多集中于污染物輸出或者單一階段的污染物入河估算[13].由于農(nóng)業(yè)非點(diǎn)源對(duì)水環(huán)境的污染要經(jīng)歷一定階段[14],故本研究結(jié)合污染物入河系數(shù),綜合污染物輸出量與污染物入河量估算農(nóng)業(yè)非點(diǎn)源污染負(fù)荷.

內(nèi)蒙古河套灌區(qū)是中國(guó)三大灌區(qū)之一,也是國(guó)家和自治區(qū)重要的商品糧油生產(chǎn)基地[15],該地區(qū)農(nóng)業(yè)活動(dòng)顯著,化肥施用量大,但利用率低[16],其余部分則是隨著農(nóng)田退水和地表徑流等匯入烏梁素海湖泊,容易造成烏梁素海水環(huán)境的惡化.因此,本研究以內(nèi)蒙古河套灌區(qū)為對(duì)象,采用考慮降雨和地形影響因子的輸出系數(shù)模型,量化河套灌區(qū)農(nóng)田非點(diǎn)源TN、TP污染負(fù)荷,結(jié)合污染物入河系數(shù),進(jìn)行農(nóng)田氮、磷污染入河量的估算,并識(shí)別污染關(guān)鍵源區(qū),為烏梁素海富營(yíng)養(yǎng)化的防治以及區(qū)域水環(huán)境的保護(hù)提供參考.

1 材料與方法

1.1 研究區(qū)概況

河套灌區(qū)位于黃河內(nèi)蒙古段北岸的“幾”字彎上(40°19′～41°18′N,106°20′～109°19′E),南北跨度約50km,東西跨度約250km[17].該區(qū)域?qū)儆诘湫偷拇箨懶詺夂?降雨少、蒸發(fā)強(qiáng),多年平均氣溫8.6～12℃,多年平均蒸發(fā)量2000～2400mm,多年平均降雨量111～236mm,且降水量分布極不均勻,夏季降水量(6～8月)占全年降水量的63%～70%,僅靠降雨不能滿足河套灌區(qū)農(nóng)作物的用水需求,春季播種(春灌)與夏季生長(zhǎng)期(夏灌)都需要依靠灌溉來保證農(nóng)業(yè)生產(chǎn)[18].河套灌區(qū)年均引黃水量約48億m3[19],90%以上的農(nóng)田退水會(huì)通過排干匯入烏梁素海,從而引起烏梁素海水體的污染.研究區(qū)具體位置以及農(nóng)田退水排干分布情況見圖1.

圖1 研究區(qū)概況和土地利用類型

1.2 數(shù)據(jù)來源及處理

本研究以2021年為基準(zhǔn)年,所涉及的數(shù)據(jù)包括數(shù)字高程圖(DEM)、土地利用數(shù)據(jù)、氣象數(shù)據(jù)、水文水質(zhì)數(shù)據(jù)等,各類型空間數(shù)據(jù)的地理坐標(biāo)和投影統(tǒng)一,所有的空間操作基于ArcGIS10.7軟件進(jìn)行,詳細(xì)數(shù)據(jù)來源見表1.其中,土地利用數(shù)據(jù)利用ArcGIS進(jìn)行重分類,分為耕地、林地、草地、水域、建設(shè)用地和未利用地6類.

表1 數(shù)據(jù)來源

1.3 改進(jìn)的輸出系數(shù)模型

輸出系數(shù)模型是一種基于統(tǒng)計(jì)學(xué)的線性數(shù)學(xué)模型,由Johnes和O’Sulivan于1989年正式提出, 隨后Johnes又對(duì)其進(jìn)行了修正,一般表達(dá)式為:

式中:為土地利用類型;為污染物類型;為土地利用類型的種類;L為污染物的輸出量,t/a;E為類土地利用類型中污染物的輸出系數(shù),t/(km2·a);A為類土地利用類型的面積,km2;為降雨直接帶來的污染物負(fù)荷,t/a.

傳統(tǒng)的輸出系數(shù)模型忽略了降雨、地形等條件對(duì)模擬結(jié)果的影響,而降雨、地形和土地利用方式在非點(diǎn)源污染物的輸移過程中起著重要作用[20],陳學(xué)凱等[21]在輸出系數(shù)模型的基礎(chǔ)上,加入降雨、坡度影響因子對(duì)模型進(jìn)行優(yōu)化,并驗(yàn)證了改進(jìn)輸出系數(shù)模型的合理性,李華林等[22]通過模擬分析,確定改進(jìn)的輸出系數(shù)模型模擬結(jié)果更符合流域非點(diǎn)源污染特征.由于河套灌區(qū)干旱少雨,直接由降雨帶來的污染較小,故而在模擬中忽略不計(jì).因此本文構(gòu)建改進(jìn)的輸出系數(shù)模型,計(jì)算公式為:

式中:為降水影響因子;為地形影響因子.

輸出系數(shù)模型模擬出來的結(jié)果是污染物的輸出量,在降水沖刷和坡度作用下向河道輸移的過程中,會(huì)受到植被攔截、自然沉降以及各種生化作用的影響,導(dǎo)致產(chǎn)生的污染物不可能全部到達(dá)附近排水溝以及烏梁素海,因此需要引入污染物入河系數(shù)來表征污染物遷移過程中的衰減影響[23-24].公式如下:

L

=

ljLj

(3)

式中:L為污染物輸出量,t/a;為污染物入河量,t/a;λ為污染物的入河系數(shù).

圖2 河套灌區(qū)2021年降雨量和降雨影響因子空間分布

1.3.1 降雨影響因子的確定 降雨量對(duì)氮、磷流失量具有較為顯著的影響,降雨影響因子主要受時(shí)間不均勻性影響因子t和空間不均勻性因子s的影響[25-26],計(jì)算公式為:

式中:為研究區(qū)給定年年降雨總量,mm;R為研究區(qū)多年平均年降雨量,mm;r為子流域給定年年降雨總量,mm;r為子流域多年平均年降雨量,mm.

圖3 河套灌區(qū)地形影響因子

利用河套灌區(qū)2021年7個(gè)氣象站點(diǎn)的降雨量數(shù)據(jù),經(jīng)過插值得到研究區(qū)年降雨量的空間分布圖(圖2),研究區(qū)2021年降雨量為57.219～192.798mm,整體呈現(xiàn)由東至西逐漸降低的空間分布特征.

根據(jù)巴彥淖爾市統(tǒng)計(jì)年鑒獲得研究區(qū)多年平均降雨量159.5mm,以研究區(qū)鄉(xiāng)鎮(zhèn)為輸出單元進(jìn)行劃分,帶入公式(4)進(jìn)行計(jì)算,插值得到各個(gè)鄉(xiāng)鎮(zhèn)的降雨影響因子,研究區(qū)降雨影響因子為0.420～0.694.根據(jù)有關(guān)研究成果,為0.6104[28],對(duì)河套灌區(qū)的DEM數(shù)據(jù)進(jìn)行提取計(jì)算,獲得研究區(qū)坡度為1.801°～8.217°,平均坡度為3.693°,帶入公式(6),借助ArcGIS10.7獲得研究區(qū)地形影響因子的空間分布圖(圖3).研究區(qū)地形影響因子為0.649～1.618,空間分布上與坡度分布一致,研究區(qū)西北部的坡度影響因子較大.

1.3.2 地形影響因子的確定 在匯流過程中,坡度主要通過影響徑流量來影響其攜帶的污染物的流失量,且坡度與地面徑流量呈正相關(guān)關(guān)系,坡度越大地表水流速度越大,地表徑流越大.相關(guān)研究表明,徑流量可以表示為坡度的冪函數(shù)與常量的乘積[27],表達(dá)式為:

通過徑流量與地形的關(guān)系,則地形影響因子可以表示為:

式中:為徑流量,m3/s;為坡度,°;,為常量;S為各鄉(xiāng)鎮(zhèn)坡度;為研究區(qū)平均坡度.

1.3.3 輸出系數(shù)的確定 確定合理的污染物輸出系數(shù)是輸出系數(shù)模型的關(guān)鍵,輸出系數(shù)的確定有3種常用方法,即文獻(xiàn)分析法、試驗(yàn)?zāi)M法和水文統(tǒng)計(jì)法[29].鑒于河套灌區(qū)無土地利用輸出系數(shù)實(shí)驗(yàn)數(shù)據(jù),本研究采用文獻(xiàn)分析法[30-31], 盡可能選擇與河套灌區(qū)相符或相近研究區(qū)域的輸出系數(shù),計(jì)算其平均值,最終得到本研究的不同土地利用類型的輸出系數(shù),見表2.

表2 河套灌區(qū)不同土地利用類型TN、TP輸出系數(shù)

1.4 模型的驗(yàn)證

將模型模擬值與實(shí)測(cè)值進(jìn)行對(duì)比分析,通過相對(duì)誤差(e)這一指標(biāo)來驗(yàn)證改進(jìn)的輸出系數(shù)模型的適用性.計(jì)算方法如下:

式中:e為相對(duì)誤差;為模擬值;0為監(jiān)測(cè)值.若e為正則說明模擬值偏大,若e為負(fù)則說明模擬值偏小,e的絕對(duì)值越小,則模型模擬效果較好,反之則模型模擬效果較差.

2 結(jié)果與分析

2.1 河套灌區(qū)不同土地利用類型非點(diǎn)源TN、TP污染負(fù)荷分析

在選定的TN、TP輸出系數(shù)以及不考慮流域損失的情況下,根據(jù)模型模擬得到河套灌區(qū)不同土地利用類型所產(chǎn)生的非點(diǎn)源污染負(fù)荷(圖4).2021年河套灌區(qū)不同土地利用類型下所產(chǎn)生的非點(diǎn)源TN、TP污染負(fù)荷分別為4419.251t和456.414t,其中污染物輸出負(fù)荷量最高的土地利用類型為耕地,TN、TP污染負(fù)荷分別為3520.998t、407.125t,占河套灌區(qū)不同土地利用類型下非點(diǎn)源TN、TP污染負(fù)荷的79.674%和89.201%.河套灌區(qū)其他土地利用類型TN污染負(fù)荷的貢獻(xiàn)率大小依次為草地>未利用地>水域>建設(shè)用地>林地,TP污染負(fù)荷的貢獻(xiàn)率大小依次為草地>建設(shè)用地>未利用地>水域>林地.

圖4 不同土地利用類型下TN、TP污染負(fù)荷占比

2.2 河套灌區(qū)農(nóng)田非點(diǎn)源TN、TP污染負(fù)荷分析

由圖5可知,河套灌區(qū)農(nóng)田非點(diǎn)源TN、TP污染負(fù)荷空間分布規(guī)律基本一致,但整體上分布不均,呈現(xiàn)出污染負(fù)荷局部集中、靠近水體、排干的鄉(xiāng)鎮(zhèn)污染負(fù)荷高.很可能是由于該區(qū)域的土地利用方式以耕地為主,從事較多的農(nóng)事活動(dòng),且農(nóng)田排水溝是農(nóng)業(yè)非點(diǎn)源氮磷等污染物運(yùn)輸和遷移至水體的主要途徑[44],因此污染負(fù)荷高,而灌區(qū)西部污染負(fù)荷比較低的區(qū)域則以草地和未利用地居多,農(nóng)用地少,氮磷等營(yíng)養(yǎng)物質(zhì)的輸入量也相對(duì)較低.其中農(nóng)田非點(diǎn)源TN、TP污染負(fù)荷最高的幾個(gè)鄉(xiāng)鎮(zhèn)依次為新華鎮(zhèn)、新安鎮(zhèn)和塔爾湖鎮(zhèn),TN、TP輸出量分別為316.658, 236.725, 199.344t/a和36.615, 27.371, 23.050t/a,占農(nóng)田非點(diǎn)源TN、TP輸出總量的21.378%.

圖5 農(nóng)田非點(diǎn)源TN、TP污染負(fù)荷空間分布

2.3 河套灌區(qū)農(nóng)田非點(diǎn)源TN、TP污染負(fù)荷強(qiáng)度分析

為避免流域面積對(duì)污染負(fù)荷的影響,本文采用污染負(fù)荷強(qiáng)度法分析不同鄉(xiāng)鎮(zhèn)的TN、TP污染負(fù)荷強(qiáng)度(圖6).TN污染負(fù)荷強(qiáng)度在0.020～5.826kg/hm2之間,平均值為3.042kg/hm2,TP污染負(fù)荷強(qiáng)度在0.002～0.674kg/hm2之間,平均值為0.352kg/hm2,且TN、TP污染負(fù)荷強(qiáng)度空間分布一致.污染負(fù)荷強(qiáng)度較高的地區(qū)依次為團(tuán)結(jié)鎮(zhèn)、新華鎮(zhèn)和蠻會(huì)鎮(zhèn),表明這幾個(gè)鄉(xiāng)鎮(zhèn)對(duì)整個(gè)研究區(qū)來說,更易產(chǎn)生氮、磷污染.最高污染負(fù)荷強(qiáng)度與最高污染負(fù)荷區(qū)域不一致,污染負(fù)荷強(qiáng)度最高的區(qū)域?yàn)閳F(tuán)結(jié)鎮(zhèn),TN、TP污染負(fù)荷強(qiáng)度分別為5.826和0.674kg/hm2.最低污染負(fù)荷強(qiáng)度地區(qū)為臨河區(qū)各辦事處.分析其原因,團(tuán)結(jié)鎮(zhèn)和蠻會(huì)鎮(zhèn)土地利用以耕地為主,耕地面積分別占鄉(xiāng)鎮(zhèn)總面積的87.726%和82.936%,且總排干流經(jīng)該鄉(xiāng)鎮(zhèn)導(dǎo)致TN、TP污染強(qiáng)度較高,而各辦事處土地利用類型以居民建設(shè)用地為主,幾乎不存在農(nóng)田非點(diǎn)源輸出.

圖6 農(nóng)田非點(diǎn)源TN、TP污染負(fù)荷強(qiáng)度空間分布

2.4 河套灌區(qū)農(nóng)田非點(diǎn)源TN、TP入河量分析

圖7 農(nóng)田非點(diǎn)源TN、TP入河量空間分布

各地農(nóng)田非點(diǎn)源TN、TP的入河系數(shù)各有差異,一般南方地區(qū)為0.1～0.3,而北方地區(qū)由于氣候干旱,降雨量低于南方地區(qū),一般取值0.03～0.1.考慮到河套灌區(qū)農(nóng)田的傳統(tǒng)灌溉方式等措施,結(jié)合文獻(xiàn)資料[23-24,45],選取河套灌區(qū)農(nóng)田非點(diǎn)源TN入河系數(shù)為0.11,TP入河系數(shù)為0.04.

圖7為河套灌區(qū)農(nóng)田非點(diǎn)源TN、TP入河量的空間分布圖,河套灌區(qū)農(nóng)田非點(diǎn)源TN、TP的入河量空間分布特征一致,整體上與污染物輸出負(fù)荷具有相似的空間分布,均為靠近水體、排干的鄉(xiāng)鎮(zhèn)污染貢獻(xiàn)量大,農(nóng)田非點(diǎn)源TN、TP入河總量分別為387.310和16.285t/a,其中新華鎮(zhèn)、新安鎮(zhèn)、塔爾湖、西小召鎮(zhèn)和隆興昌鎮(zhèn)對(duì)TN、TP入湖量的貢獻(xiàn)較大,占污染物入河總量的30.852%,是今后農(nóng)田非點(diǎn)源污染防治的關(guān)鍵區(qū)域.

2.5 模型驗(yàn)證分析

為了驗(yàn)證改進(jìn)輸出系數(shù)模型的合理性,本研究選取六、七排干及皂沙排干匯水區(qū)所在鄉(xiāng)鎮(zhèn)作為模型的驗(yàn)證區(qū),根據(jù)《五原縣水體達(dá)標(biāo)方案》獲取六、七排干、皂沙排干溝的排水量分別為1065.33萬m3、1354.69萬m3和381.3萬m3,將污染物濃度與排水量進(jìn)行乘積后得到驗(yàn)證區(qū)TN、TP實(shí)測(cè)值.

表3 改進(jìn)的輸出系數(shù)模型模擬精度

結(jié)合公式(7),結(jié)果如表3所示,驗(yàn)證區(qū)農(nóng)田非點(diǎn)源TN、TP入河量實(shí)測(cè)值為73.023t/a和2.457t/a,改進(jìn)輸出系數(shù)模型模擬值為69.559t/a和2.925t/a.模型模擬結(jié)果與實(shí)測(cè)值較為相近,相對(duì)誤差分別為-4.743%和19.037%,且由降雨影響因子和地形影響因子同時(shí)改進(jìn)的輸出系數(shù)模型提高了模型模擬精度,表明所選用的系數(shù)合理可靠,模型具有較好的模擬能力.

3 討論

氮磷流失的數(shù)據(jù)源是基于種植面積的估算,計(jì)算子流域的負(fù)荷可以有效降低估算帶來的誤差[46],所以本研究以鄉(xiāng)鎮(zhèn)為輸出單元,基于改進(jìn)的輸出系數(shù)模型并借助GIS技術(shù),進(jìn)行河套灌區(qū)2021年農(nóng)田非點(diǎn)源TN、TP污染負(fù)荷估算.結(jié)果表明,耕地是不同土地利用類型中非點(diǎn)源污染貢獻(xiàn)量最大的土地利用類型,孫海軍等[47]研究了太湖流域北部山區(qū)小流域非點(diǎn)源污染,說明了種植業(yè)是該流域的主要污染源.河套灌區(qū)農(nóng)田非點(diǎn)源TN、TP污染負(fù)荷空間分布一致,靠近水體、排干的鄉(xiāng)鎮(zhèn)農(nóng)田非點(diǎn)源TN、TP貢獻(xiàn)量最高,這與王文章等[48]對(duì)射洪縣非點(diǎn)源評(píng)估的結(jié)果相符.TN、TP污染負(fù)荷最高的幾個(gè)鄉(xiāng)鎮(zhèn)依次為新華鎮(zhèn)、新安鎮(zhèn)和塔爾湖鎮(zhèn),這是由于該區(qū)域的土地利用方式以耕地為主,耕地面積較大,從事較多的農(nóng)事活動(dòng),這與石慶玲等[49]通過探究農(nóng)業(yè)非點(diǎn)源污染負(fù)荷對(duì)土地利用的響應(yīng)關(guān)系,證明污染負(fù)荷與耕地面積所占比重有很大關(guān)系結(jié)論一致.

目前,將輸出系數(shù)模型應(yīng)用于農(nóng)業(yè)非點(diǎn)源污染負(fù)荷估算的研究多集中于污染物輸出或者單一階段的污染物入河估算[50],但農(nóng)業(yè)非點(diǎn)源對(duì)水環(huán)境的污染要經(jīng)歷一定階段[51],故本文結(jié)合污染物入河系數(shù),將污染物輸出與污染物入河聯(lián)系起來,結(jié)果表明,2021年河套灌區(qū)農(nóng)田非點(diǎn)源TN、TP污染負(fù)荷為3520.998t,407.125t,TN貢獻(xiàn)量約為TP的8.65倍,李娜等[52]在長(zhǎng)春市新立城水庫(kù)的研究中,若不考慮牛的養(yǎng)殖,TN與TP的排放比達(dá)到8.32,本結(jié)果與其研究結(jié)果相似.TN、TP污染負(fù)荷強(qiáng)度平均值分別為3.042和0.352kg/hm2,吳用[53]利用SWAT模型對(duì)烏梁素海流域的非點(diǎn)源污染進(jìn)行模擬,結(jié)果表明,平原區(qū)流域中、東部氮和磷元素的輸出平均值分別為5.6,2.3kg/hm2和0.25,0.86kg/hm2,本研究與其研究結(jié)果相符.農(nóng)田非點(diǎn)源TN、TP入河量分別為387.310 和16.285t,管玉玲[54]利用排污系數(shù)法估算烏梁素海流域2001～2014年農(nóng)田非點(diǎn)源污染物入河量,其中TN、TP入河量分別為673.18～918.90t和28.27～ 38.59t.總氮總磷入河量比本研究偏高,可能是因?yàn)榻陙頌趿核睾８黜?xiàng)水質(zhì)指標(biāo)入河污染負(fù)荷均呈現(xiàn)出不同程度的下降趨勢(shì)[55],且其研究區(qū)域?yàn)檎麄€(gè)烏梁素海流域,范圍較大.考慮到研究區(qū)缺乏TN、TP輸出系數(shù)的監(jiān)測(cè)數(shù)據(jù),模型所使用的輸出系數(shù)參考其他地理環(huán)境相似流域的平均值,模擬結(jié)果會(huì)具有一定的誤差,以上分析表明本研究結(jié)果具有一定的可信度,今后,在相關(guān)數(shù)據(jù)的支撐下,基于本研究方法所得出的結(jié)果將會(huì)更加準(zhǔn)確.

4 結(jié)論

4.1 耕地是河套灌區(qū)不同土地利用類型中非點(diǎn)源TN、TP污染負(fù)荷量最大的土地利用類型,其他土地利用類型對(duì)TN污染負(fù)荷的貢獻(xiàn)率大小依次為草地>未利用地>水域>建設(shè)用地>林地,TP污染負(fù)荷的貢獻(xiàn)率大小依次為草地>建設(shè)用地>未利用地>水域>林地.

4.2 河套灌區(qū)2021年農(nóng)田非點(diǎn)源TN、TP污染負(fù)荷分別為3520.998和407.125t,污染負(fù)荷強(qiáng)度平均值分別為3.042 和0.352kg/hm2,污染貢獻(xiàn)量最高的幾個(gè)鄉(xiāng)鎮(zhèn)依次為新華鎮(zhèn)、新安鎮(zhèn)和塔爾湖鎮(zhèn),占農(nóng)田非點(diǎn)源TN、TP輸出總量的21.378%.

4.3 結(jié)合污染物入河系數(shù),估算農(nóng)田非點(diǎn)源TN、TP進(jìn)入烏梁素海的負(fù)荷量,河套灌區(qū)農(nóng)田非點(diǎn)源TN、TP的入河量空間分布特征一致,整體上與污染物輸出負(fù)荷具有相似的空間分布,均為靠近水體、排干的鄉(xiāng)鎮(zhèn)污染貢獻(xiàn)量大,農(nóng)田非點(diǎn)源TN、TP入河總量分別為387.310和16.285t/a,其中新華鎮(zhèn)、新安鎮(zhèn)、塔爾湖鎮(zhèn)、西小召鎮(zhèn)、隆興昌鎮(zhèn)、團(tuán)結(jié)鎮(zhèn)和蠻會(huì)鎮(zhèn)是河套灌區(qū)農(nóng)田非點(diǎn)源污染的重點(diǎn)污染防治鄉(xiāng)鎮(zhèn).

4.4 基于降雨和地形影響因子修正改進(jìn)的輸出系數(shù)模型,對(duì)農(nóng)田非點(diǎn)源TN、TP污染負(fù)荷模擬的相對(duì)誤差分別為-4.743%和19.037%,模型模擬能力比較好.

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Estimation of nitrogen and phosphorus pollution loads from non-point sources in farmland of Hetao Irrigation District, Inner Mongolia.

WANG Yan, JIAO Yan*, YANG Wen-zhu, YAN Ying-chao, WU Hong, LING Ling, SHI Yue-chao

(Inner Mongolia Key Laboratory of Environmental Chemistry, College of Chemistry and Environmental Science, Inner Mongolia Normal University, Hohhot 010022, China)., 2023,43(12)：6551～6560

To understand the current situation of farmland non-point source pollution in the Hetao irrigation district of Inner Mongolia, the traditional export coefficient model (ECM) was improved, and the farmland non-point source nitrogen and phosphorus pollution load was quantified by precipitation impact factor () and terrain impact factor () in the area. The farmland non-point source nitrogen and phosphorus discharged into the river (Wuliangsuhai) was estimated, and the critical source areas of pollution was identified by the pollution river influx coefficient (). The total export load of non-point source total nitrogen (TN) and total phosphorus (TP) from farmland were 3520.998 and 407.125t in the Hetao irrigation district in 2021, accounting for 79.674% and 89.201% of the total pollution load from different land use types, respectively. The spatial distribution of the export loads for TN and TP of farmland non-point sources was consistent, and the contribution in towns near drainage was the highest. The export loads of TN and TP pollution were 316.658, 236.725, 199.344t/a and 36.615, 27.371, 23.050t/a in Xinhua, Xin'an and Talhu township, respectively. The amount of TN and TP discharged into the river were 387.310 and 16.285t/a from non-point sources of farmland. The towns of Xinhua, Xin'an, Talhu, Longxingchang, Tuanjie and Manhui were key areas for pollution prevention and control in the Hetao irrigation district. The rationality of the improved export coefficient model with relative errors of -4.743% and 19.037% had been verified by comparing with measured values.

Hetao irrigation district；farmland non-point source pollution；improved export coefficient model；TN；TP

X502

A

1000-6923(2023)12-6551-10

王 艷,焦 燕,楊文柱,等.內(nèi)蒙古河套灌區(qū)農(nóng)田非點(diǎn)源氮磷污染負(fù)荷估算 [J]. 中國(guó)環(huán)境科學(xué), 2023,43(12):6551-6560.

Wang Y, Jiao Y, Yang W Z, et al. Estimation of nitrogen and phosphorus pollution loads from non-point sources in farmland of Hetao Irrigation District, Inner Mongolia [J]. China Environmental Science, 2023,43(12):6551-6560.

2023-04-24

國(guó)家自然科學(xué)基金資助項(xiàng)目(42175038);內(nèi)蒙古自治區(qū)杰出青年基金資助項(xiàng)目(2022JQ02);內(nèi)蒙古自治區(qū)高等學(xué)校青年科技英才支持計(jì)劃項(xiàng)目(NJYT23041);2022年蒙古自治區(qū)重點(diǎn)研發(fā)和成果轉(zhuǎn)化計(jì)劃項(xiàng)目(2022YFHH0035);內(nèi)蒙古師范大學(xué)基本科研業(yè)務(wù)費(fèi)專項(xiàng)資金資助項(xiàng)目(2022JBTD009);內(nèi)蒙古師范大學(xué)高層次人才科研啟動(dòng)項(xiàng)目(2020YJRC056)

* 責(zé)任作者, 教授, jiaoyan@imnu.edu

王 艷(1996-),女,河南周口人,內(nèi)蒙古師范大學(xué)碩士研究生,主要從事農(nóng)業(yè)非點(diǎn)源污染研究.發(fā)表文章1篇.2469736853@qq.com.