APEX模型在淮河流域中上游的适宜性研究

探讨了APEX(Agricultural Policy/Environmental eXtender)模型在淮河流域中上游的适宜性。将APEX模型用于淮河流域中上游监测资料较匮乏的3个径流小区,用日径流/产沙的实测值和模拟值校正和验证模型,用校正过的模型评价不同土地管理措施的长期水土保持效益(1981~2005)。在模型校正阶段,3个小区日径流量和产沙量的平均百分误差绝对值(APE)小于20%,平均纳希-苏特克利夫有效系数(EF)大于0.6,平均R2大于0.7;在模型验证阶段,3个小区日径流量和产沙量的平均APE小于12%,平均EF大于0.5,平均R2大于0.7,APEX模型可模拟出径流、产沙的日变异。在水土保持效益评价结果中,与对照(休闲地)相比,管理措施2(林地-水平沟)的径流量平均减少37%,产沙量平均减少89%,管理措施1(林草混交-水平梯田)的水土保持效益要略低于管理措施2,构建水平沟、水平梯田以及增加地表植被是控制该地区水土流失的有效措施。研究结果表明:APEX模型适应性强,可用于预测和评价淮河流域中上游不同土地管理措施下的水土流失,这为资料匮乏地区研究土壤侵蚀提供了一种新的思路和工具。

Applicability of APEX in the Middle and Upland Huaihe River Watershed

This study was conducted to evaluate the applicability of Agricultural Policy/Environmental eXtender(APEX).APEX model was tested and used to compare benefits of different land management measures in three experimental plots in the middle and upland Huaihe river watershed.Simulated average daily runoff and sediment yield were within 20% of observed values,the average Nash-Sutcliffe efficiency coefficient(EF) above 0.6 and average R2 above 0.7 during the calibration period.For the validation period,simulated average daily runoff and sediment yield were within 12% of observed values,APEX model tracked the variability of daily runoff and sediment yield with the average EF above 0.5 and average R2 above 0.7.The long-term benefits of management practice 2(woodland with horizontal-ditch) over the baseline(fallow) were quantified as a 37% surface runoff reduction and 89% sediment yield reduction.Benefits of management practice 1(mixed wood-grass with horizontal-terrace) were slightly less than these of management practice 2.Constructions of horizontal ditch,horizontal terrace and enhancing vegetation are efficient strategies for controlling runoff and sediment in the research area.The results suggested that APEX is a useful tool for evaluating soil and water loss under different management practices in the middle and upland Huaihe river watershed.A new approach was proposed for soil erosion study in the area lacking detailed information.