一、个人简介

张超，男，副教授，硕士生导师，陕西咸阳人，民盟盟员。2012年7月本科毕业于西北农林科技大学农业水利工程专业，获工学学士学位；2015年11月至2017年10月于加拿大农业部渥太华研究发展中心联合培养访学（CSC）；2018年12月毕业于西北农林科技大学农业水土工程专业，获工学博士学位；同年任扬州大学水利科学与工程学院讲师；2022年7月起任扬州大学水利科学与工程学院副教授。获扬州市“绿扬金凤计划” 优秀博士、“青蓝工程”中青年学术带头人和优秀青年骨干教师、校“技能先锋”等荣誉称号。

二、研究领域

1. 农业生态系统模拟

2.作物遥感定量监测

3. 农业水资源高效利用

三、科研、教学研究课题

1. 主持国家自然科学基金项目《多源遥感与作物-水盐耦合模型同化的盐渍化农田水盐反演方法研究》（52379049，2024-2027）。

2.主持国家博士后科学基金特别资助项目《盐渍化农田土壤水盐多源遥感数据同化与反演研究》（2023T160552，2023-2024）。

3. 主持国家自然科学基金项目《基于无人机遥感数据与作物模型同化的冬油菜生长监测与估产方法研究》（51909228，2020-2022）。

4.主持国家博士后科学基金面上项目《基于低空无人机遥感的冬油菜生长监测与产量估算模型研究》（2020M671623，2020-2022）。

5. 主持扬州大学教学改革研究课题《面向“新工科”建设的水利类课程群教学改革研究与实践》（YZUJX2021-D16，2022-2023）。

四、开设课程

长期致力于农业水利工程、水利水电工程学科的教学工作，承担本科生《水资源规划及利用》、《土力学》、《工程地质与水文地质》等课程教学。

五、代表性学术著作

[1]Deng M,Zhang C*, Tang M, Liao C, Hu Y, Zhang Z, Feng S, Zheng Z. (2025). Stacking ensemble learning coupled with multi-source remote sensing data: enhancing soil salinity inversion accuracy in barley-cultivated salinized soils. Agricultural Water Management, 322, 109959.

[2]Zheng, Z., He, Y., He, Y., Zhan, J., Shi, C., Xu, Y., ... &Zhang, C*. (2025). Micro-nano bubble water subsurface drip irrigation affects strawberry yield and quality by modulation of microbial communities. Agricultural Water Management, 307, 109228.

[3]Luo Z, Deng M, Tang M, Liu R, Feng S,Zhang C*& Zheng Z. (2025). Estimating soil profile salinity under vegetation cover based on UAV multi-source remote sensing. Scientific reports, 15, 2713.

[4]骆振海,张超*, 冯绍元, 唐敏, 刘锐, 孔纪迎. (2024). 土壤盐渍化光学遥感监测方法研究进展. 自然资源遥感, 36(4), 9-22.

[5]Ding D, Yang Z, Wu L, Zhao Y, Zhang X, Chen X, Feng H*,Zhang C*, Wendroth O. (2024). Optimizing nitrogen-fertilizer management by using RZWQM2 with consideration of precipitation can enhance nitrogen utilization on the Loess Plateau. Agricultural Water Management, 299C, 108890.

[6]Ding D, Li T, Wu L, Zhang X, Zhao Y, Feng H*,Zhang C*, Wendroth O. (2024). Energy Compensation for Crop Growth under Plastic Mulching: Theories, Models, and Limitations. Agronomy, 14(5), 1005.

[7]Chen Z, Xu Y,Zhang C*, Tang M. (2024). Prediction of Glass Chemical Composition and Type Identification Based on Machine Learning Algorithms. Applied Sciences, 14(10), 4017.

[8]Kong J., Luo Z.,Zhang C*, Tang M, Liu R, Xie Z., Feng S. (2023). Identification of Robust Hybrid Inversion Models on the Crop Fraction of Absorbed Photosynthetically Active Radiation Using PROSAIL Model Simulated and Field Multispectral Data. Agronomy, 13(8), 2147.

[9]Tang, M., Liu, R., Li, H., Gao, X., Wu, P.,Zhang, C*. (2023). Optimizing Soil Moisture Conservation and Temperature Regulation in Rainfed Jujube Orchards of China’s Loess Hilly Areas using Straw and Branch Mulching. Agronomy, 13(8), 2121.

[10]Zhang, C., Kong, J., Tang, M., Lin, W., Ding, D., & Feng, H. (2023). Improving maize growth and development simulation by integrating temperature compensatory effect under plastic film mulching into the AquaCrop model. The Crop Journal.

[11]Xie, Z., Kong, J., Tang, M., Luo, Z., Li, D., Liu, R., Feng, S., &Zhang, C*. (2023). Modelling Winter Rapeseed (Brassica napus L.) Growth and Yield under Different Sowing Dates and Densities Using AquaCrop Model. Agronomy, 13(2), 367.

[12]协子昂,张超*, 冯绍元, 张富仓, 蔡焕杰, 唐敏, 孔纪迎. (2023). 植被物候遥感监测研究进展. 遥感技术与应用, 38(1), 1-14.

[13]Zhang, C., Xie, Z., Shang, J., Liu, J., Dong, T., Tang, M., Feng, S., & Cai, H. (2022). Detecting winter canola (Brassica napus) phenological stages using an improved shape-model method based on time-series UAV spectral data. The Crop Journal, 10(5), 1353-1362.

[14]Zhang, C., Xie, Z., Wang Q., Tang, M., Feng, S., Cai, H. (2022). AquaCrop modeling to explore optimal irrigation of winter wheat for improving grain yield and water productivity. Agricultural Water Management, 266, 107580.

[15]Zhang, C., Tang, M., Gao, X., Ling, Q., & Wu, P. (2022). Sloping land use affects the complexity of soil moisture and temperature changes in the loess hilly region of China. PloS one, 17(1), e0262445.

[16]Tang, M., Li, W., Gao, X., Wu, P., Li, H., Ling, Q., &Zhang, C*. (2022). Land use affects the response of soil moisture and soil temperature to environmental factors in the loess hilly region of China. PeerJ, 10, e13736.

[17]Tang, M., Gao, X., Wu, P., Li, H., &Zhang, C*. (2022). Effects of Living Mulch and Branches Mulching on Soil Moisture, Temperature and Growth of Rain-Fed Jujube Trees. Plants, 11(19), 2654.

[18]王巧娟,何虹,李亮,张超*,蔡焕杰*. (2022). 基于AquaCrop模型的大豆灌溉制度优化研究. 中国农业科学, 55(17), 3365-3379.

[19]Zhang, C., Liu, J., Shang, J., Dong, T., Tang, M., Feng, S., & Cai, H. (2021). Improving winter wheat biomass and evapotranspiration simulation by assimilating leaf area index from spectral information into a crop growth model. Agricultural Water Management, 255, 107057.

[20]Tang, M., Li, H.,Zhang, C.*, Zhao, X., Gao, X., & Wu, P. (2021). Mulching Measures Improve Soil Moisture in Rain-Fed Jujube (Ziziphus jujuba Mill.) Orchards in the Loess Hilly Region of China. Sustainability, 13(2), 610.

[21]Tang, M., Gao, X.,Zhang, C.*, Zhao, X., & Wu, P. (2020). Sloping Land Use Affects Soil Moisture and Temperature in the Loess Hilly Region of China. Agronomy, 10(6), 774.

[22]Zhang, C., Liu, J., Dong, T., Shang, J., Tang, M., Zhao, L., & Cai, H. (2019). Evaluation of the simple algorithm for yield estimate model in winter wheat simulation under different irrigation scenarios. Agronomy Journal, 111(6), 2970-2980.

[23]Zhang, C., Liu, J., Dong, T., Pattey, E., Shang, J., Tang, M., ... & Saddique, Q. (2019). Coupling Hyperspectral Remote Sensing Data with a Crop Model to Study Winter Wheat Water Demand. Remote Sensing, 11(14), 1684.

[24]Zhang, C., Liu, J., Shang, J., & Cai, H. (2018). Capability of crop water content for revealing variability of winter wheat grain yield and soil moisture under limited irrigation. Science of the Total Environment, 631, 677-687.

[25]Zhang, C., Pattey, E., Liu, J., Cai, H., Shang, J., & Dong, T. (2018). Retrieving leaf and canopy water content of winter wheat using vegetation water indices. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(1), 112-126.

[26]张超, 蔡焕杰, 李志军. 高光谱特征参量的冬小麦吸收性光合有效辐射分量估算模型.光谱学与光谱分析, 2015, 35(9): 2644-2649.

六、专利与软著

[1]张超，邓梅华，唐敏，胡宇杰，张政，张志鹏. 一种混合特征优选的的土壤盐分遥感反演方法及系统. CN202511750355.7.

[2]张超, 骆振海, 唐敏, 邓梅华, 张政, 胡宇杰. 一种基于特征提取和机器学习估算土壤盐分的方法及系统. CN202411037393.3.

[3]张超, 邓梅华, 唐敏, 丁奠元, 骆振海, 孔纪迎. 基于积温补偿算法的玉米生长模拟改进方法及系统. CN202410235053.5.

[4]张超, 孔纪迎, 骆振海, 唐敏, 刘锐, 协子昂. 基于改进PROSAIL模型的冬油菜冠层混合反演处理方法及系统, CN202311615358.0.

[5]骆振海,张超, 协子昂, 唐敏, 孔纪迎, 刘锐. 一种基于改进形状模型的冬油菜物候监测方法, CN202310722938.3.

[6]张超，王颖，邓梅华，胡皓，俞伟豪，曹驿方，王教毅. SHAP-RF特征工程分析与表型估算可视化系统, 2025SR2046075.

[7]张超，胡宇杰，张政，薄濠豪. 基于高斯过程回归模型和SHAP的特征重要性分析系统, 2025SR0802442.

[8]张超，邓梅华，胡宇杰，张志鹏. 基于支持向量机模型和SHAP的特征重要性分析系统, 2025SR0798874.

[9]张超，邓梅华，廖超宇，薄豪濠. 一种基于高斯过程回归的特征选择软件, 2025SR0798840.

[10]张超，张政，薄豪濠，张志鹏.一种基于决策树和SHAP的特征重要性的分析系统, 2025SR0929011.

[11]张超，邓梅华，张政，骆振海. 一种基于随机森林算法的特征选择软件, 2025SR0798916.

[12]骆振海，张超，唐敏，邓梅华，廖超宇，冯绍元. 一种基于随机森林算法的土壤盐分估算软件, 2024SR1700655.

[13]张超，骆振海，协子昂，唐敏，孔纪迎，刘锐，陈铭铭. 一种基于图像识别的油菜种子自动计数软件, 2023SR0676788.

七、招生方向

学术/专业学位：082802农业水土工程；085902土木水利硕士(水利工程)

八、联系方式

通讯地址：江苏省扬州市邗江区江阳中路131号扬州大学江阳路南校区

邮编：225009

邮箱：zhangc1700@yzu.edu.cn