Spatial-temporal evolution and driving factors analysis of oasis evapotranspiration in the middle reaches of the Keriya River basin

doi:10.13474/j.cnki.11-2246.2024.0306

Abstract

Abstract: Evapotranspiration is a key component in assessing the water-heat cycle of desert oasis areas, and monitoring its spatio-temporal variations and studying its driving forces can provide scientific basis for precise water resources management and ecological environment protection. Taking the middle reaches of the Keriya River basin as the study area, this paper analyzes the spatio-temporal variations of evapotranspiration from 2010 to 2022 based on Landsat remote sensing imagery and the SEBS model. The accuracy of the estimation results is verified using evaporation pan measurements and the Penman-Monteith model, and further investigation is conducted on the influencing factors of evapotranspiration. The results show that:①The correlation coefficient and R² between the SEBS simulated values of evapotranspiration and the evaporation pan observations are 0.93 and 0.87, respectively, with an RMSE of 0.96mm/d. The correlation coefficient and R² between the SEBS simulated values and the Penman formula observations are 0.90 and 0.81, respectively, with an RMSE of 0.64mm/d. ②The actual evapotranspiration from 2010 to 2022 shows a decreasing trend, with a change rate of 14.75mm/a. It decreases in spring, summer, and autumn, while increases in winter. ③The spatial heterogeneity of evapotranspiration is evident, with high values mainly concentrated near the Keriya River and low values distributed in the sandy areas at the edge of the oasis. In the past 13 years, about 70.2% of the study area's pixels show no significant decrease trend, while 10.4% of the pixels exhibite a significant decrease trend. ④Evapotranspiration is significantly correlated with temperature, air pressure, sunshine duration, land surface temperature, and NDVI. It has a weak correlation with wind speed and surface albedo. Overall, the research results can effectively simulate the spatio-temporal heterogeneity of evapotranspiration in the middle reaches of the Keriya River basin. This study contributes to the rational planning and management of water resources in the basin.

Key words: Keriya River basin, evapotranspiration, SEBS model, Landsat, Mann-Kendall trend analysis, impact factor

CLC Number:

P237

WANG Ranran, Lü Guanghui, HE Xuemin, LI Jinbao. Spatial-temporal evolution and driving factors analysis of oasis evapotranspiration in the middle reaches of the Keriya River basin[J]. Bulletin of Surveying and Mapping, 2024, 0(3): 31-36,139.

References

[1] 孟莹,姜鹏,董巍.基于遥感的地表蒸散发研究进展[J].遥感技术与应用,2022,37(4):839-853.
[2] 杨文静,赵建世,赵勇,等.基于结构方程模型的蒸散发归因分析[J].清华大学学报(自然科学版),2022,62(3):581-588.
[3] 张圆,贾贞贞,刘绍民,等.遥感估算地表蒸散发真实性检验研究进展[J].遥感学报,2020,24(8):975-999.
[4] 刘洋,于恩涛,杨建军,等.西北干旱区1960-2019年实际蒸散发时空变化特征[J].水土保持研究,2021,28(6):75-80.
[5] KHOSHNOOD S,LOTFATA A,MOMBENI M,et al.A spatial and temporal correlation between remotely sensing evapotranspiration with land use and land cover[J].Water,2023,15(6):1068.
[6] 宁锋伟,张兰慧,曾璇,等.CLM5.0对高寒山区蒸散发模拟的适用性评估[J].冰川冻土,2023,45(1):119-129.
[7] 张荣华,杜君平,孙睿.区域蒸散发遥感估算方法及验证综述[J].地球科学进展,2012,27(12):1295-1307.
[8] HU Xiaolong,SHI Liangsheng,LIN Guang,et al.Comparison of physical-based,data-driven and hybrid modeling approaches for evapotranspiration estimation[J].Journal of Hydrology,2021,601:126592.
[9] 刘萌,唐荣林,李召良,等.数据驱动的蒸散发遥感反演方法及产品研究进展[J].遥感学报,2021,25(8):1517-1537.
[10] 张娣,魏征,冯天权,等.灌区蒸散发遥感反演及其时空变化特征分析:以漳河灌区为例[J].测绘通报,2022(12):57-63.
[11] 温馨,周纪,刘绍民,等.基于多源产品的西南河流源区地表蒸散发时空特征[J].水资源保护,2021,37(3):32-42.
[12] 张永强,孔冬冬,张选泽,等.2003-2017年植被变化对全球陆面蒸散发的影响[J].地理学报,2021,76(3):584-594.
[13] 宫兆宁,陆丽,金点点,等.土地利用/覆被变化扎龙湿地蒸散发量及生态需水量的遥感估算[J].生态学报,2021,41(9):3572-3587.
[14] 鞠艳,张珂,李炳锋,等.金沙江流域实际蒸散发时空分布特征及其影响因子[J].水资源保护,2022,38(6):104-110.
[15] MUYIBUL Z,XIA Jianxin,MUHTAR P,et al.Spatiotemporal changes of land use/cover from 1995 to 2015 in an oasis in the middle reaches of the Keriya River,southern Tarim Basin,Northwest China[J].CATENA,2018,171:416-425.
[16] SU Z.The surface energy balance system (SEBS) for estimation of turbulent heat fluxes[J].Hydrology and Earth System Sciences,2002,6(1):85-100.
[17] PEREIRA L S,ALLEN R G,SMITH M,et al.Crop evapotranspiration estimation with FAO56:past and future[J].Agricultural Water Management,2015,147:4-20.
[18] LI Wanxin,BRUNNER P,HENDRICKS FRANSSEN H J,et al.Potential evaporation dynamics over saturated bare soil and an open water surface[J].Journal of Hydrology,2020,590:125140.
[19] 涂晨雨,贾绍凤,朱文彬,等.柴达木盆地蒸散发遥感估算与耗水有效性评价[J].生态学报,2022,42(13):5404-5415.
[20] 詹云军,章文,严岩,等.长江流域实际蒸散发演变趋势及影响因素[J].生态学报,2021,41(17):6924-6935.
[21] 马亚丽,许健,张芮,等.石羊河流域参考作物蒸散发时空变化及其对气候变化的响应[J].干旱地区农业研究,2022,40(1):95-103.