龙笛

副教授 特别研究员 博士生导师

Email: dlong@tsinghua.edu.cn

通信地址:北京市海淀区清华大学新水利馆202

邮编:100084


个人主页
教育背景

2008/08-2011/08  美国德克萨斯农业和工程大学 遥感水文 博士
2005/09-2008/07  中国科学院 遥感水文 硕士
2001/09-2005/07  清华大学 水利水电工程系 学士

工作履历

2020/2-至今 清华大学水利水电工程系,长聘副教授,特别研究员

2017/7-2020/1 清华大学水利水电工程系,副教授,特别研究员

2014/12-2017/6 清华大学水利水电工程系,助理教授,特别研究员

2011/09-2014/11 美国德克萨斯大学奥斯汀分校地球科学学院,博士后


开设课程

(1)现代遥感水文(英文,研究生)

(2)遥感基本原理与方法(英文,本科生)


研究领域

区域地下水储量变化的重力卫星(GRACE)反演理论、方法和应用

地表水储量(湖、库、冰、雪等)的多源遥感反演理论、方法和应用

地表温度、蒸散发和土壤水分的热红外遥感反演理论、方法和应用

冰冻圈水文学及无资料流域径流预测和成分划分

社会水文学及强人类活动区水文过程模拟和预测


科研项目

(8)国家自然科学基金,面上项目,气候变化和南水北调影响下华北平原及主要城市地下水储量演变的评估和预测(52079065)(2021-2024),在研,主持

(7)内蒙古自治区科技厅,十三五重大科技专项课题,黄河流域内蒙古段嵌套式多尺度生态水文一体化综合观测试验及其时空格局和适宜性评估(2020SZD0031)(2020-2023),在研,主持

(6) 国家科技部,十三五重点研发计划子课题,气候变化下西北地区水储量演变规律与预测及对能源开发的影响(2018YFE0196000)(2019-2021),在研,主持

(5) 国家科技部,第二次青藏高原综合科学考察任务一专题五,青藏高原水储量变化分析及各组分水储量贡献解析(2019QZKK0100)(2019-2022),在研,主持

(4) 国家自然科学基金,优秀青年科学基金项目,遥感水文学(51722903)(2018-2020),在研,主持

(3)国家科技部,十三五重点研发计划课题,水资源立体监测协同机理与国家水资源立体监测体系研究(2017YFC0405801)(2017-2020),在研,主持

(2)国家自然科学基金,“西南河流源区径流变化和适应性利用”重大研究计划重点项目,西南河流源区关键水文气象变量的多源遥感观测与数据集成(91547210)(2016-2019),结题(12A2B),主持

(1)国家自然科学基金,面上项目,重力卫星总储水量变化信号校正与回推重建方法研究与应用(51579128)(2016-2019),结题,主持

学术兼职

Water Resources Research (IF = 4.31, 一区),Associate Editor

Journal of Hydrology (IF = 4.500, 一区),Associate Editor

Remote Sensing of Environment (IF = 9.085, 一区),Editorial Board Member

《中国科学:技术科学(英文版)》,青年编委

《南水北调与水利科技》,编委

《遥感技术与应用》,编委


奖励与荣誉

2020年 高等学校水利类专业教学成果一等奖(排名第1)

2020年 清华大学优秀博士学位论文指导教师(博士生黄琦获2020年清华大学优秀博士论文)

2019年 美国地球物理联合会水文青年科学奖(2009年该奖设立以来首位获奖华人)

2019年 李小文遥感科学奖(全国2名,每2年评选一次)

2019年 清华大学先进工作者

2018年 清华大学年度教学优秀奖

2014年 Geophysical Research Letters 优秀审稿人

2014年 美国德克萨斯大学奥斯汀分校Author Achievement Award

2013年 美国德克萨斯大学奥斯汀分校Author Achievement Award

2009-2011年 美国德克萨斯农业和工程大学Graduate Research Assistantship

2009-2010年 美国德克萨斯水资源研究所Mills Scholarship Award

2008-2009年 美国德克萨斯农业和工程大学Graduate Teaching Assistantship

2008-2009年 美国德克萨斯农业和工程大学Graduate Enhancement Funds

2008-2009年 美国德克萨斯农业和工程大学Incentive Scholarship


学术成果

[1] *Long, D., Yang W.T., Scanlon, B.R., Zhao, J.S., Liu, D.G., Burek, P., Pan, Y., You, L. Z., & Wada, Y (2020). South-to-North Water Diversion stabilizing Beijing’s groundwater levels. Nature Communications, 2020, 11(2020), 1863‒1880.

[2] *Long, D., Yan, L., Bai, L.L., Zhang, C.J., Li, X.Y., Lei, H.M., Yang, H.B., Tian, F.Q., Zeng, C., Meng, X.Y., & Shi, C.X(2020). Generation of MODIS-like land surface temperatures under all-weather conditions based on a data fusion approach. Remote Sensing of Environment, 246, 111863

[3] *Long, D., Bai, L., Yan, L., Zhang, C., Yang, W., Lei, H., *Quan, J., Meng, X., & Shi, C. (2019). Generation of spatially complete and daily continuous surface soil moisture of high spatial resolution. Remote Sensing of Environment, 233, 111364. 

[4] *Long, D., Pan, Y., Zhou, J., Chen, Y., Hou, X.Y., Hong, Y., Scanlon, B.R., & Longuevergne, L. (2017). Global analysis of spatiotemporal variability in merged total water storage changes using multiple GRACE products and global hydrological models. Remote Sensing of Environment, 192, 198-216. 

[5] *Long, D., Chen, X., Scanlon, B.R., Wada, Y., Hong, Y., Singh, V.P., Chen, Y., Wang, C., Han, Z., & Yang, W. (2016). Have GRACE satellites overestimated groundwater depletion in the Northwest India Aquifer? Scientific Reports, 6, 24398. 

[6] *Long, D., Longuevergne, L., & Scanlon, B.R. (2015a). Global analysis of approaches for deriving total water storage changes from GRACE satellites. Water Resources Research, 51, 2574-2594. 

[7] *Long, D., Yang, Y.T., Wada, Y., Hong, Y., Liang, W., Chen, Y.N., Yong, B., Hou, A.Z., Wei, J.F., & Chen, L. (2015b). Deriving scaling factors using a global hydrological model to restore GRACE total water storage changes for China's Yangtze River basin. Remote Sensing of Environment, 168, 177-193. 

[8] *Long, D., Longuevergne, L., & Scanlon, B.R. (2014a). Uncertainty in evapotranspiration from land surface modeling, remote sensing, and GRACE satellites. Water Resources Research, 50, 1131–1151. 

[9] *Long, D., Shen, Y.J., Sun, A.Y., Hong, Y., Longuevergne, L., Yang, Y.T., Li, B., & Chen, L. (2014b). Drought and flood monitoring for a large karst plateau in Southwest China using extended GRACE data. Remote Sensing of Environment, 145–160. 

[10] *Long, D., Scanlon, B.R., Longuevergne, L., Sun, A.-Y., Fernando, D.N., & Save, H. (2013). GRACE satellite monitoring of large depletion in water storage in response to the 2011 drought in Texas. Geophysical Research Letters, 40, 3395–3401. 

[11] *Long, D., & Singh, V.P. (2013a). Assessing the impact of end-member selection on the accuracy of satellite-based spatial variability models for actual evapotranspiration estimation. Water Resources Research, 49, 2601–2618. 

[12] *Long, D., & Singh, V.P. (2013b). An entropy-based multispectral image classification algorithm. IEEE Transactions on Geoscience and Remote Sensing, 51, 5225–5238. 

[13] *Long, D., Scanlon, B.R., Fernando, D.N., Meng, L., & Quiring, S.M. (2012a). Are Temperature and Precipitation Extremes Increasing over the U.S. High Plains? Earth Interactions, 16, 1–20. 

[14] *Long, D., Singh, V.P., & Scanlon, B.R. (2012b). Deriving theoretical boundaries to address scale dependencies of triangle models for evapotranspiration estimation. Journal of Geophysical Research-Atmospheres, 117. 

[15] *Long, D., & Singh, V.P. (2012a). A modified surface energy balance algorithm for land (M-SEBAL) based on a trapezoidal framework. Water Resources Research, 48. 

[16] *Long, D., & Singh, V.P. (2012b). A Two-source Trapezoid Model for Evapotranspiration (TTME) from satellite imagery. Remote Sensing of Environment, 121, 370–388. 

[17] *Long, D., Singh, V.P., & Li, Z.L. (2011). How sensitive is SEBAL to changes in input variables, domain size and satellite sensor? Journal of Geophysical Research-Atmospheres, 116. 

[18] *Long, D., Gao, Y.C., & Singh, V.P. (2010). Estimation of daily average net radiation from MODIS data and DEM over the Baiyangdian watershed in North China for clear sky days. Journal of Hydrology, 388, 217–233. 

[19] *Long, D., & Singh, V.P. (2010). Integration of the GG model with SEBAL to produce time series of evapotranspiration of high spatial resolution at watershed scales. Journal of Geophysical Research-Atmospheres, 115. 

[20] Li. X.Y., & *Long, D. (2020). An improvement in accuracy and spatiotemporal continuity of the MODIS precipitable water vapor product based on a data fusion approach. Remote Sensing of Environment, 248, 111966. 

[21] Sun, Z.L., *Long. D., Yang W.T., Li. X.Y., & Pan, Y. (2020). Reconstruction of GRACE data on changes in total water storage over the global land surface and 60 basins. Water Resources Research, 55, e2019WR026250. 

[22] Han, Z.Y., *Long. D., Huang, Q., Li, X.D., Zhao, F.Y., & Wang, J.H. (2020). Improving reservoir outflow estimation for ungauged basins using satellite observations and a hydrological model. Water Resources Research, 56, e2020WR027590. 

[23] Huang, Q., *Long. D., Du, M.D., Han, Z.Y., & Han, P.F. (2020). Daily continuous river discharge estimation for ungauged basins using a hydrologic model calibrated by satellite altimetry: Implications for the SWOT mission. Water Resources Research, 56, e2020WR027309.

[24] Bai, L., *Long, D., Yan, L., 2019. Estimation of surface soil moisture with downscaled land surface temperatures using a data fusion approach for heterogeneous agricultural land. Water Resources Research, 55, 1105‒1128. 

[25] Li, X., *Long, D., Huang, Q., Han, P., Zhao, F., & Wada, Y. (2019). High-temporal-resolution water level and storage change data sets for lakes on the Tibetan Plateau during 2000–2017 using multiple altimetric missions and Landsat-derived lake shoreline positions. Earth System Science Data, 11, 1603–1627. 

[26] Yang, W., *Long, D., & Bai, P. (2019). Impacts of future land cover and climate changes on runoff in the mostly afforested river basin in North China. Journal of Hydrology, 570, 201‒219. 

[27] Han, Z., *Long, D., Fang, Y., Hou, A., & Hong, Y. (2019). Impacts of climate change and human activities on the flow regime of the dammed Lancang River in Southwest China. Journal of Hydrology, 570, 96‒105. 

[28] Li, X.Y., *Long, D., Han, Z.Y., Scanlon, B.R., Sun, Z.L., Han, P.F., & Hou, A.Z. (2019). Evapotranspiration estimation for Tibetan Plateau headwaters using conjoint terrestrial and atmospheric water balances and multisource remote sensing. Water Resources Research, 55, 8608‒8630. 

[29] Han, P., *Long, D., Han, Z., Du, M., Dai, L., & Hao, X. (2019). Improved understanding of snowmelt runoff from the headwaters of China's Yangtze River using remotely sensed snow products and hydrological modeling. Remote Sensing of Environment, 224, 44‒59.

[30] Chen, X.N., *Long, D., Liang, S.L., He, L., Zeng, C., Hao, X.H., & Hong, Y. (2018). Developing a composite daily snow cover extent record over the Tibetan Plateau from 1981 to 2016 using multisource data. Remote Sensing of Environment, 215, 284‒299. 

[31] Huang, Q., *Long, D., Du, M.D., Zeng, C., Li, X.D., Hou, A.Z., & Hong, Y. (2018). An improved approach to monitoring Brahmaputra River water levels using retracked altimetry data. Remote Sensing of Environment, 211, 112‒128.

[32] Huang, Q., *Long, D., Du, M.D., Zeng, C., Qiao, G., Li, X.D., Hou, A.Z., & Hong, Y. (2018). Discharge estimation in high-mountain regions with improved methods using multisource remote sensing: A case study of the Upper Brahmaputra River. Remote Sensing of Environment, 219, 115‒134. 

[33] Tang, G.Q., *Long, D., *Hong, Y., Gao, J.Y., & Wan, W. (2018). Documentation of multifactorial relationships between precipitation and topography of the Tibetan Plateau using spaceborne precipitation radars. Remote Sensing of Environment, 208, 82‒96. 

[34] Zeng, C., *Long, D., Shen, H., Wu, P., Cui, Y., & *Hong, Y. (2018). A two-step framework for reconstructing remotely sensed land surface temperatures contaminated by cloud. ISPRS Journal of Photogrammetry and Remote Sensing, 141, 30‒45. 

[35] Tang, G., *Long, D., Behrangi, A., Wang, C., & *Hong, Y (2018). Exploring deep neural networks to retrieve rain and snow in high latitudes using multisensor and reanalysis data. Water Resources Research, 54 (10), 8253‒8278. 

[36] Chen, X.N., *Long, D., Hong, Y., Hao, X.H., & Hou, A.Z. (2018). Climatology of snow phenology over the Tibetan plateau for the period 2001-2014 using multisource data. International Journal of Climatology, 38, 2718‒2729. 

[37] Chen, X., *Long, D., Hong, Y., Zeng, C., & Yan, D.H. (2017a). Improved modeling of snow and glacier melting by a progressive two-stage calibration strategy with GRACE and multisource data: How snow and glacier meltwater contributes to the runoff of the Upper Brahmaputra River basin? Water Resources Research, 53, 2431‒2466. 

[38] Chen, X.N., *Long, D., Hong, Y., Liang, S.L., & Hou, A.Z. (2017b). Observed radiative cooling over the Tibetan Plateau for the past three decades driven by snow cover-induced surface albedo anomaly. Journal of Geophysical Research-Atmospheres, 122, 6170‒6185. 

[39] Gao, Z., *Long, D., Tang, G.Q., Zeng, C., Huang, J.S., & Hong, Y. (2017). Assessing the potential of satellite-based precipitation estimates for flood frequency analysis in ungauged or poorly gauged tributaries of China's Yangtze River basin. Journal of Hydrology, 550, 478‒496. 

[40] Li, D.N., Long, D., *Zhao, J.S., Lu, H., & Hong, Y. (2017). Observed changes in flow regimes in the Mekong River basin. Journal of Hydrology, 551, 217‒232. 

[41] Cui, Y.K., *Long, D., *Hong, Y., Zeng, C., Zhou, J., Han, Z.Y., Liu, R.H., & Wan, W. (2016). Validation and reconstruction of FY-3B/MWRI soil moisture using an artificial neural network based on reconstructed MODIS optical products over the Tibetan Plateau. Journal of Hydrology, 543, 242‒254. 

[42] Hou, X.Y., *Long, D., *Hong, Y., & Xie, H.J. (2016). Seasonal to interannual variability of satellite-based precipitation estimates in the Pacific Ocean associated with ENSO from 1998 to 2014. Remote Sensing, 8, 18. 

[43] Tang, G.Q., *Long, D., & *Hong, Y. (2016b). Systematic anomalies over inland water bodies of High Mountain Asia in TRMM precipitation estimates: No longer a problem for the GPM Era? IEEE Geoscience and Remote Sensing Letters, 13, 1762‒1766.

[44] Wan, W., Long, D., *Hong, Y., Ma, Y.Z., Yuan, Y., Xiao, P.F., Duan, H.T., Han, Z.Y., & *Gu, X.F. (2016). A lake data set for the Tibetan Plateau from the 1960s, 2005, and 2014. Scientific Data, 3, 13. 

[45] *Yang, Y.T., Long, D., Guan, H.D., Liang, W., Simmons, C.T., & Batelaan, O. (2015b). Comparison of three dual-source remote sensing evapotranspiration models during the MUSOEXE-12 campaign: Revisit of model physics. Water Resources Research, 51, 3145‒3165. 

[46] Meng, L., Long, D., Quiring, S.M., & *Shen, Y. (2014). Statistical analysis of the relationship between spring soil moisture and summer precipitation in East China. International Journal of Climatology, 34, 1511‒1523. 

[47] *Yang, Y., Long, D., Guan, H., Scanlon, B.R., Simmons, C.T., Jiang, L., & Xu, X. (2014a). GRACE satellite observed hydrological controls on interannual and seasonal variability in surface greenness over mainland Australia. Journal of Geophysical Research: Biogeosciences, 119, 2014JG002670. 

[48] *Yang, Y.T., Long, D., & Shang, S.H. (2013). Remote estimation of terrestrial evapotranspiration without using meteorological data. Geophysical Research Letters, 40, 3026‒3030. 

[49] *Gao, Y.C., & Long, D. (2008). Intercomparison of remote sensing-based models for estimation of evapotranspiration and accuracy assessment based on SWAT. Hydrological Processes, 22, 4850‒4869. 

[50] *Gao, Y.C., Long, D., & Li, Z.L. (2008). Estimation of daily actual evapotranspiration from remotely sensed data under complex terrain over the upper Chao river basin in North China. International Journal of Remote Sensing, 29, 3295‒3315. 

[51] Tang, G., Behrangi, A., Long, D.*, Li, C., and Hong, Y.*, 2018. Accounting for spatiotemporal errors of gauges: A critical step to evaluate gridded precipitation products. Journal of Hydrology, 294‒306.

[52] *Zheng, H., Hong, Y., Long, D., & Jing, H. (2017). Monitoring surface water quality using social media in the context of citizen science. Hydrology and Earth System Sciences, 21, 949‒961. 

[53] Tang, G., Ma, Y., *Long, D., Zhong, L., & *Hong, Y. (2016a). Evaluation of GPM Day-1 IMERG and TMPA Version-7 legacy products over Mainland China at multiple spatiotemporal scales. Journal of Hydrology, 533, 152‒167. 

[54] Ma, Y.Z., Tang, G.Q., *Long, D., Yong, B., Zhong, L.Z., Wan, W., & *Hong, Y. (2016). Similarity and error intercomparison of the GPM and its predecessor-TRMM multisatellite precipitation analysis using the best available hourly gauge network over the Tibetan Plateau. Remote Sensing, 8, 17. 

[55] Zeng, Z.Y., Tang, G.Q., *Long, D., Zeng, C., Ma, M.H., *Hong, Y., Xu, H., & Xu, J. (2016). A cascading flash flood guidance system: development and application in Yunnan Province, China. Natural Hazards, 84, 2071‒2093. 

[56] Tang, G.Q., Zeng, Z.Y., *Long, D., Guo, X.L., Yong, B., Zhang, W.H., & Hong, Y. (2015). Statistical and hydrological comparisons between TRMM and GPM Level-3 products over a mid-latitude basin: Is Day-1 IMERG a good successor for the TMPA 3B42 Version-7 legacy? Journal of Hydrometeorology, 17, 121‒137.

[57] *Yang, Y., Guan, H., Long, D., Liu, B., Qin, G., Qin, J., & Batelaan, O. (2015a). Estimation of surface soil moisture from thermal infrared remote sensing using an improved trapezoid method. Remote Sensing, 7, 8250. 

[58] Scanlon, B.R., Longuevergne, L., & Long, D. (2012). Ground referencing GRACE satellite estimates of groundwater storage changes in the California Central Valley, USA. Water Resources Research, 48. 

[59] Huang, Q., Li, X., Han, P., *Long, D., Zhao, F., & Hou, A. (2019). Validation and application of water levels derived from Sentinel-3A for the Brahmaputra River. Science China Technological Sciences, 62, 1760‒1772.

[60] Tang, G., *Behrangi, A., Ma, Z., Long, D., and *Hong, Y., 2018. Downscaling of ERA-Interim temperature in the contiguous United States and its implications for rain-snow partitioning. Journal of Hydrometeorology, 19: 1215‒1233.

[61] Tang, G.Q., Wen, Y.X., Gao, J.Y., *Long, D., Ma, Y.Z., Wan, W., & *Hong, Y. (2017a). Similarities and differences between three coexisting spaceborne radars in global rainfall and snowfall estimation. Water Resources Research, 53, 3835‒3853. 

[62] Wan, W., Bai, W.H., Zhao, L.M., Long, D., Sun, Y.Q., Meng, X.G., Chen, H., Cui, X.A., & Hong, Y. (2015). Initial results of China's GNSS-R airborne campaign: soil moisture retrievals. Science Bulletin, 60, 964‒971. 

[63] *Yang, Y.T., Guan, H.D., Shang, S.H., Long, D., & Simmons, C.T. (2014b). Toward the use of the MODIS ET product to estimate terrestrial GPP for nonforest ecosystems. IEEE Geoscience and Remote Sensing Letters, 11, 1624‒1628. 

[64] Yang, X.*, Yong B.*, Ren, L., Zhang, Y., and Long, D. (2017). Multi-scale validation of GLEAM evapotranspiration products over China via ChinaFLUX ET measurements. International Journal of Remote Sensing, 38 (20), 5688‒5709. 

[65] Wan, W., Li, H., *Xie, H.J., *Hong, Y., Long, D., Zhao, L.M., Han, Z.Y., Cui, Y.K., Liu, B.J., Wang, C.G., & Yang, W.T. (2017). A comprehensive data set of lake surface water temperature over the Tibetan Plateau derived from MODIS LST products 2001-2015. Scientific Data, 4, 10. 

[66] *Yang, Y.T., Guan, H., Batelaan, O., McVicar, T.R., Long, D., Piao, S.L., Liang, W., Liu, B., Jin, Z., & Simmons, C.T. (2016). Contrasting responses of water use efficiency to drought across global terrestrial ecosystems. Scientific Reports, 6, 8.

[67] Tong, X., *Liu, T.X., Singh, V.P., Duan, L.M., & Long, D. (2016). Development of in situ experiments for evaluation of anisotropic reflectance effect on spectral mixture analysis for vegetation cover. IEEE Geoscience and Remote Sensing Letters, 13, 636‒640. 

[68] Pei, H.W., Scanlon, B.R., *Shen, Y.J., Reedy, R.C., Long, D., & Liu, C.M. (2015). Impacts of varying agricultural intensification on crop yield and groundwater resources: comparison of the North China Plain and US High Plains. Environmental Research Letters, 10, 14. 

[69] Tang, Y., Hooshyar, M., Zhu, T.J., Ringler, C., Sun, A.Y., Long, D., & *Wang, D.B. (2017b). Reconstructing annual groundwater storage changes in a large-scale irrigation region using GRACE data and Budyko model. Journal of Hydrology, 551, 397‒406. 

[70] *Scanlon, B.R., Zhang, Z.Z., Save, H., Wiese, D.N., Landerer, F.W., Long, D., Longuevergne, L., & Chen, J. (2016). Global evaluation of new GRACE mascon products for hydrologic applications. Water Resources Research, 52, 9412‒9429. 

[71] *Scanlon, B.R., Zhang, Z.Z., Reedy, R.C., Pool, D.R., Save, H., Long, D., Chen, J., Wolock, D.M., Conway, B.D., & Winester, D. (2015). Hydrologic implications of GRACE satellite data in the Colorado River Basin. Water Resources Research, 51, 9891‒9903. 

[72] Liang, W., Yang, Y., Fan, D., Guan, H., Zhang, T., Long, D., Zhou, Y., & Bai, D. (2015b). Analysis of spatial and temporal patterns of net primary production and their climate controls in China from 1982 to 2010. Agricultural and Forest Meteorology, 204, 22‒36. 

[73] Yang, L., Song, X., Zhang, Y., Han, D., Zhang, B., & Long, D. (2012). Characterizing interactions between surface water and groundwater in the Jialu River basin using major ion chemistry and stable isotopes. Hydrology and Earth System Sciences, 16, 4265‒4277. 

[74] Ma, Y., *Hong, Y., Chen, Y., Yang, Y., Tang, G., Yao, Y., Long, D., Li, C., Han, Z., and *Liu, R. (2018). Performance of optimally merged multisatellite precipitation products using the dynamic Bayesian model averaging scheme over the Tibetan Plateau. Journal of Geophysical Research-Atmospheres, 123: 814‒834.

[75] Liu, X., *Song, X.F., Zhang, Y.H., Xia, J., Zhang, X.C., Yu, J.J., Long, D., Li, F.D., & Zhang, B. (2011). Spatio-temporal variations of delta H-2 and delta O-18 in precipitation and shallow groundwater in the Hilly Loess Region of the Loess Plateau, China. Environmental Earth Sciences, 63, 1105‒1118. 

[76] Liang, W., *Bai, D., Wang, F., Fu, B., Yan, J., Wang, S., Yang, Y., Long, D., & Feng, M. (2015a). Quantifying the impacts of climate change and ecological restoration on streamflow changes based on a Budyko hydrological model in China's Loess Plateau. Water Resources Research, 51, 6500‒6519. 

[77] Scanlon, B.R.*, Zhang, Z., Save, H., Sun, A.Y., Mueller Schmied, H., van Beek, L.P.H., Wiese, D.N., Wada, Y., Long D., Reedy, R. C., Longuevergne, L., Doll, P., and Bierkens, M.F.P. (2018). Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data. Proceedings of the National Academy of Sciences of the United States of America, 115 (6): E1080‒1089.

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(10)韩忠颖, 龙笛. 水库调节径流的计算方法、装置、计算机设备和存储介质 (已授权,专利号:201911071637.9)

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