TRMM在海河流域南系的降水估算精度评价及其对SWAT模型的适用性

准确估算区域降水对水文过程评价和水资源管理意义重大。为评估TRMM 3B42V7降水产品在海河流域南系的估算精度及其在土壤和水评估模型(Soil and Water Assessment Tool,SWAT)中的适用性,利用28个气象站降水观测数据(2007-2016年)和101个雨量站观测数据(2010-2016年)开展研究。研究表明:站点尺度上,3B42V7降水产品对月降水估算的均方根误差小于15 mm,平均误差小于8.5 mm;在湿润季节的估算精度更好。流域尺度上,日降水估算精度较差,相关系数小于0.6。分区尺度上,3B42V7能够很好地捕捉到不同等级降水强度,但对微量降雨有所低估;山区和平原的年降水量均出现高估现象,平原区较为突出;此外,3B42V7能够较好地捕捉到研究区内极端降水的时间和空间分布。分2种情景进行水文模拟,利用月平均流量对模型进行校准和验证,在情景Ⅰ中,验证期模拟结果较好,决定系数在0.56~0.96之间,纳什效率系数在-11.09~0.94之间。TRMM 3B42V7可为海河流域及其类似区域的水资源管理提供参考。

Evaluation of TRMM satellite-based rainfall data in southern Haihe River Basin and suitability for SWAT model

Accurate estimation of regional precipitation plays an important role in hydrologic process evaluation and water resources management. Southern Haihe River Basin is the region with the highest degree of water resources exploitation and utilization, however, excessive exploitation of surface water and groundwater causes a series of ecological and environmental problems, which leads to a serious threat to water security. In this study, the accuracy of 3 B42 V7 estimation of precipitation in Southern Haihe River Basin was evaluated on different spatial and temporal scales, and its applicability to hydrological model SWAT was verified. The daily rainfall data from 28 meteorological stations(2007-2016) and 101 rain gauges(2010-2016)were used to evaluate the accuracy on TRMM 3 B42 V7. Correlation coefficient, relative bias ratio, mean error and root mean square error were used to quantitatively evaluate the rainfall accuracy of 3 B42 V7. Moreover, determinate coefficient and Nash-Sutcliffe coefficient of efficiency were used to quantitatively evaluate SWAT simulation results. Two scenarios were set up to drive the SWAT model. In scenario I, the daily rainfall data(2010-2014) from rain gauges and 3 B42 V7 grid rainfall(2015-2016) were utilized to drive the model. In scenario II, the daily rainfall data(2010-2016) from meteorological stations were used to drive the model. The results showed 3 B42 V7 had strong estimation ability in monthly estimation of precipitation with the root mean square error less than 15 mm and average monthly precipitation error less than 8.5 mm. However, it was poor in daily precipitation estimation with the correlation coefficient less than 0.6. The number of rainfall stations with the relative bias ratio between-20% and 20% accounted for 81% and 79% during the summer season and growing period of maize, which indicated that 3 B42 V7 performed better during the wet seasons. In addition, 3 B42 V7 could well capture the rainfall intensity at all levels, however, zero/light rain were underestimated in four zones. In the yearly estimation, the relative bias ratio values in mountainous area of the Daqinghe watershed, plain of the Daqinghe watershed, mountainous area of the Ziyahe watershed and plain of the Ziyahe watershed were 2.64%, 9.59%, 7.72%, 20.32%, respectively. It means the overestimation in plain and mountainous areas, especially in plain areas. Moreover, 3 B42 V7 well captured the temporal and spatial distribution of extreme precipitation in this study area. The simulated discharges of SWAT driven by data from rain gauge and TRMM 3 B42 V7 were in good agreement with the observed ones. During the validation period, the determinate coefficient was between 0.56 and 0.96 and the Nash-Sutcliffe coefficient of efficiency was between-11.09 and 0.94. The TRMM 3 B42 V7 provides the possibility to expand the time and space scale of hydrological simulation and can provide data support for water resource management and ecological security research.