基本信息
姓名：Khalil Ur Rahman
最后学历：博士
工作单位：山东大学土建与水利学院 职位：副教授
邮箱：
khalil_rahman@sdu.edu.cn；engr.khalil0598@gmail.com
研究领域
水文与水资源、遥感应用、气候变化、干旱和GRACE卫星应用等
研究方向
水文与水资源：
1.水文模型（地表水和地下水）。
2.非饱和带模拟。
3.雨水收集及其对水资源的影响。
4.机器学习和数理统计技术在水文与水资源管理中的应用。
遥感应用：
1.评估遥感技术在水文与水资源中的应用。
2.卫星降水数据集的开发和评估。
3.Google Earth Engine 应用程序。
4.土地利用影响评估。
气候变化：
1.气候变化对水资源的影响评估。
2.气候模式的降尺度化和效果评估。
干旱：
1.干旱特征描述（干旱情况估计和干旱传播过程）。
2.干旱指数的确定并在局部范围内进行验证。
3.量化气候变化和土地利用变化对干旱的影响。
GRACE卫星应用：
1.利用GRACE卫星评估总水储量的变化。
2.对GRACE卫星数据进行时空降尺度处理。
3.应用GRACE监测地下水位的实时波动。
学习经历
● 2017 – 2021，清华大学，博士学位，水利工程专业
● 2015 – 2017，沙特阿拉伯阿卜杜勒阿齐兹大学，硕士学位，水文与水资源管理专业
● 2009 – 2013，巴基斯坦白沙瓦工程技术大学，学士学位，水文与水资源专业
工作经历
● 2024.2–至今：山东大学，副教授。
● 2021.11–2023.11：清华大学，博士后（水木学者）。
科研项目
● 2023.1 - 2023.12：中国国家自然科学基金委员会（NSFC）、国际青年科学家研究基金（RFIS-I）资助“利用 GRACE 卫星监测干旱气候区地下水位的实时波动情况”（20万元，主持）。
● 2023.1 - 2023.12：中国博士后科学基金会资助“通过优化 VCI 和 TCI 权重开发和评估稳健的 VHI以适应严峻的气候和土地利用变化”（8万元，主持）。
● 2023.1 - 至今：中国国家自然科学基金委员会资助“基于遥感的春季至秋季/冬季灌溉对干旱地区前一年表层土壤水分和盐分状况的检测和分析”（参与）。
● 2021.1 - 至今：巴基斯坦高等教育委员会、中巴经济走廊（CPEC-CRG）研究基金资助“基于巴基斯坦气候变化和土地利用情况的水资源收集的经济和环境影响研究”（参与）。
社会学术兼职
● 国际冰川学会（IGS）会员
● 青年水文学家协会（YHS）会员
● 巴基斯坦工程委员会（PEC）会员
● 国际工程地质与环境协会（IAEG）会员
● HydroSensing社区创始人（www.hydrosensing4u.com）
发表论文（*通讯作者）
2024:
1. Rahman, K.U., Ejaz, N., Shang, S.*, Balkhair, K.S., Alghamdi, K.M., Zaman, K., Khan, M.A. and Hussain, A., 2024. A robust integrated agricultural drought index under climate and land use variations at the local scale in Pakistan. Agricultural Water Management, 295, p.108748.
2. Ejaz, N., Khan, A.H., Shahid, M., Zaman, K., Balkhair, K.S., Alghamdi, K.M., Rahman, K.U.* and Shang, S., 2024. Superiority of Dynamic Weights against Fixed Weights in Merging Multi-Satellite Precipitation Datasets over Pakistan. Water, 16(4), p.597.
3. Rahman, K.U., Ejaz, N., Saleem, M.W., Mao, D., Balkhair, K.S., Khan, K.U.J., and Shang, S.*, 2024. Global Assessment of novel and robust Vegetation Health Indices: Bridging Climate Change and Land Use variations using PCA-weighted drought framework. Remote Sensing of Environment (Under Review).
4. Jing, L., Chen, C., Xinmin, M., Shiliang, L., and Rahman, K.U., Mao, D., 2024. Utilizing the electrical resistivity tomography to map contamination in a quarry. Journal of Environmental Management (Under Review).
5. Khan, A.H., Ejaz, N., Ali, M.Z., Rahman, K.U.*, Jadoon, K.Z., and Shang, S., 2024. Unraveling Groundwater Dynamics in The Depleted Aquifer of Indus Basin Using GRACE Satellite and In-Situ Observations. Science of the Total Environment (Under Review).
6. Masud, T., Khan, A., Khan, M., Ajmal, M., and Rahman, K.U.*, 2024. Impact of Climate Change on Streamflow Projections Over Chenab River 2 Basin Under CMIP6 Scenarios. Journal of Hydrology: Regional Studies (Under Review).
7. Shahid, M., Waseem, M., Rahman, K.U.*, Haider, S., and Gabriel, H.F., 2024. An Innovative conceptual framework to identify the potential sites for rainwater harvesting in arid regions. Applied Water Science (Under Review).
8. Rahman, K.U., Shang, S., Balkhair, K.S., Gabriel, H.F., Jadoon, K.Z., and Zaman, K., 2024. Catchment scale assessment of drought impact on environmental flow in the Indus Basin, Pakistan. Natural Hazards and Earth System Sciences (Under Review).
2023:
1. Qian, X., Qi, H., Shang, S., Wan, H., Rahman, K.U. and Wang, R., 2023. Deep Learning-based Near-real-time Monitoring of Autumn Irrigation Extent at Sub-pixel Scale in a large Irrigation District. Agricultural Water Management, 284, p.108335.
2. Ashraf, M.S., Shahid, M., Waseem, M., Azam, M. and Rahman, K.U.*, 2023. Assessment of Variability in Hydrological Droughts Using the Improved Innovative Trend Analysis Method. Sustainability, 15(11), p.9065.
3. Zahran, H., Ali, M.Z., Jadoon, K.Z., Yousafzai, H.U.K., Rahman, K.U.* and Sheikh, N.A., 2023. Impact of Urbanization on Groundwater and Surface Temperature Changes: A Case Study of Lahore City. Sustainability, 15(8), p.6864.
4. Rahman, K.U., Shang, S., Balkhair, K. and Nusrat, A., 2023. Catchment-Scale Drought Propagation Assessment in the Indus Basin of Pakistan Using a Combined Approach of Principal Components and Wavelet Analyses. Journal of Hydrometeorology, 24(4), pp.601-624.
5. Ejaz, N., Bahrawi, J., Alghamdi, K.M., Rahman, K.U. and Shang, S., 2023. Drought Monitoring Using Landsat Derived Indices and Google Earth Engine Platform: A Case Study from Al-Lith Watershed, Kingdom of Saudi Arabia. Remote Sensing, 15(4), p.984.
6. Ejaz, N., Elhag, M., Bahrawi, J., Zhang, L., Gabriel, H.F. and Rahman, K.U.*, 2023. Soil Erosion Modelling and Accumulation Using RUSLE and Remote Sensing Techniques: Case Study Wadi Baysh, Kingdom of Saudi Arabia. Sustainability, 15(4), p.3218.
7. Rahman, K.U., Hussain, A., Ejaz, N., Shang, S., Balkhair, K.S., Khan, K.U.J., Khan, M.A. and Rehman, N.U., 2023. Analysis of production and economic losses of cash crops under variable drought: A case study from Punjab province of Pakistan. International Journal of Disaster Risk Reduction, 85, p.103507.
8. Hussain, A., Jadoon, K.Z., Rahman, K.U., Shang, S., Shahid, M., Ejaz, N. and Khan, H., 2023. Analyzing the impact of drought on agriculture: evidence from Pakistan using standardized precipitation evapotranspiration index. Natural Hazards, 115(1), pp.389-408.
2022:
1. Hussain, A., Rahman, K.U., Shahid, M., Haider, S., Pham, Q.B., Linh, N.T.T. and Sammen, S.S., 2022. Investigating feasible sites for multi-purpose small dams in Swat District of Khyber Pakhtunkhwa Province, Pakistan: socioeconomic and environmental considerations. Environment, Development and Sustainability, pp.1-24.
2. Rahman, K.U., Pham, Q.B., Jadoon, K.Z., Shahid, M., Kushwaha, D.P., Duan, Z., Mohammadi, B., Khedher, K.M. and Anh, D.T., 2022. Comparison of machine learning and process-based SWAT model in simulating streamflow in the Upper Indus Basin. Applied water science, 12(8), p.178.
3. Wen, Y., Wan, H., Shang, S. and Rahman, K.U., 2022. A monthly distributed agro-hydrological model for irrigation district in arid region with shallow groundwater table. Journal of Hydrology, 609, p.127746.
4. Rahman, K.U., Hussain, A., Ejaz, N., Shahid, M., Duan, Z., Mohammadi, B., Hoai, P.N., Pham, Q.B., Khedher, K.M. and Anh, D.T., 2022. Evaluating the impact of the environment on depleting groundwater resources: a case study from a semi-arid and arid climatic region. Hydrological Sciences Journal, 67(5), pp.791-805.
5. Polong, F., Pham, Q.B., Anh, D.T., Rahman, K.U., Shahid, M. and Alharbi, R.S., 2023. Evaluation and comparison of four satellite-based precipitation products over the upper Tana River Basin. International Journal of Environmental Science and Technology, 20(1), pp.843-858.
6. Mohammadi, B., Moazenzadeh, R., Pham, Q.B., Al-Ansari, N., Rahman, K.U., Anh, D.T. and Duan, Z., 2022. Application of ERA-Interim, empirical models, and an artificial intelligence-based model for estimating daily solar radiation. Ain Shams Engineering Journal, 13(1), p.101498.
2021:
1. Wan, H., Li, J., Shang, S. and Rahman, K.U., 2021. Exploratory factor analysis-based co-kriging method for spatial interpolation of multi-layered soil particle-size fractions and texture. Journal of Soils and Sediments, 21, pp.3868-3887.
2. Shahid, M., Rahman, K.U., Haider, S., Gabriel, H.F., Khan, A.J., Pham, Q.B., Pande, C.B., Linh, N.T.T. and Anh, D.T., 2021. Quantitative assessment of regional land use and climate change impact on runoff across Gilgit watershed. Environmental Earth Sciences, 80, pp.1-18.
3. Shahid, M., Rahman, K.U., Haider, S., Gabriel, H.F., Khan, A.J., Pham, Q.B., Mohammadi, B., Linh, N.T.T. and Anh, D.T., 2021. Assessing the potential and hydrological usefulness of the CHIRPS precipitation dataset over a complex topography in Pakistan. Hydrological Sciences Journal, 66(11), pp.1664-1684.
4. Li, J., Shang, S., Jiang, H., Song, J., Rahman, K.U. and Adeloye, A.J., 2021. Simulation-based optimization for spatiotemporal allocation of irrigation water in arid region. Agricultural Water Management, 254, p.106952.
5. Linh, N.T.T., Ruigar, H., Golian, S., Bawoke, G.T., Gupta, V., Rahman, K.U., Sankaran, A. and Pham, Q.B., 2021. Flood prediction based on climatic signals using wavelet neural network. Acta Geophysica, 69(4), pp.1413-1426.
6. Rahman, K.U., Shang, S. and Zohaib, M., 2021. Assessment of merged satellite precipitation datasets in monitoring meteorological drought over Pakistan. Remote Sensing, 13(9), p.1662.
7. Elkhrachy, I., Pham, Q.B., Costache, R., Mohajane, M., Rahman, K.U., Shahabi, H., Linh, N.T.T. and Anh, D.T., 2021. Sentinel‐1 remote sensing data and Hydrologic Engineering Centres River Analysis System two‐dimensional integration for flash flood detection and modelling in New Cairo City, Egypt. Journal of Flood Risk Management, 14(2), p.e12692.
8. Shahid, M. and Rahman, K.U., 2021. Identifying the annual and seasonal trends of hydrological and climatic variables in the Indus Basin Pakistan. Asia-Pacific Journal of Atmospheric Sciences, 57, pp.191-205.
9. Balkhair, K.S. and Rahman, K.U., 2021. Development and assessment of rainwater harvesting suitability map using analytical hierarchy process, GIS and RS techniques. Geocarto International, 36(4), pp.421-448.
2020:
1. Rahman, K.U. and Shang, S., 2020. A regional blended precipitation dataset over Pakistan based on regional selection of blending satellite precipitation datasets and the dynamic weighted average least squares algorithm. Remote Sensing, 12(24), p.4009.
2. Rahman, K.U., Shang, S., Shahid, M., Wen, Y. and Khan, A.J., 2020. Development of a novel weighted average least squares-based ensemble multi-satellite precipitation dataset and its comprehensive evaluation over Pakistan. Atmospheric Research, 246, p.105133.
3. Guan, Y., Mohammadi, B., Pham, Q.B., Adarsh, S., Balkhair, K.S., Rahman, K.U., Linh, N.T.T. and Tri, D.Q., 2020. A novel approach for predicting daily pan evaporation in the coastal regions of Iran using support vector regression coupled with krill herd algorithm model. Theoretical and Applied Climatology, 142, pp.349-367.
4. Rahman, K.U., Shang, S., Shahid, M. and Wen, Y., 2020. Hydrological evaluation of merged satellite precipitation datasets for streamflow simulation using SWAT: a case study of Potohar Plateau, Pakistan. Journal of Hydrology, 587, p.125040.
5. Wen, Y., Shang, S., Rahman, K.U., Xia, Y. and Ren, D., 2020. A semi-distributed drainage model for monthly drainage water and salinity simulation in a large irrigation district in arid region. Agricultural Water Management, 230, p.105962.
6. Rahman, K.U., Shang, S., Shahid, M., Wen, Y. and Khan, Z., 2020. Application of a dynamic clustered bayesian model averaging (DCBA) algorithm for merging multisatellite precipitation products over Pakistan. Journal of Hydrometeorology, 21(1), pp.17-37.
2019:
1. Rahman, K.U., Shang, S., Shahid, M. and Wen, Y., 2019. An appraisal of dynamic bayesian model averaging-based merged multi-satellite precipitation datasets over complex topography and the diverse climate of Pakistan. Remote Sensing, 12(1), p.10.
2. Rahman, K.U., Shang, S., Shahid, M. and Wen, Y., 2019. Performance assessment of SM2RAIN-CCI and SM2RAIN-ASCAT precipitation products over Pakistan. Remote Sensing, 11(17), p.2040.
3. Wen, Y., Shang, S. and Rahman, K.U., 2019. Pre-constrained machine learning method for multi-year mapping of three major crops in a large irrigation district. Remote Sensing, 11(3), p.242.
2018:
1. Rahman, K.U., Shang, S., Shahid, M. and Li, J., 2018. Developing an ensemble precipitation algorithm from satellite products and its topographical and seasonal evaluations over Pakistan. Remote Sensing, 10(11), p.1835.
2017:
1. Balkhair, K.S. and Rahman, K.U., 2017. Sustainable and economical small-scale and low-head hydropower generation: A promising alternative potential solution for energy generation at local and regional scale. Applied Energy, 188, pp.378-391.
2. Rahman, K.U.*, Balkhair, K.S., Almazroui, M. and Masood, A., 2017. Sub-catchments flow losses computation using Muskingum–Cunge routing method and HEC-HMS GIS based techniques, case study of Wadi Al-Lith, Saudi Arabia. Modeling Earth Systems and Environment, 3, pp.1-9.
招生信息：
欢迎对遥感、水文水资源和水利工程感兴趣的学生申请攻读硕士和博士学位。请随时与我联系！
联系方式：
地址：山东省济南市历下区经十路17922号，山东大学土建与水利学院图东楼 410 室
邮箱：khalil_rahman@sdu.edu.cn; engr.khalil0598@gmail.com
Dr. Khalil Ur Rahman
BEng, MS, PhD
➢ Associate Professor in Hydraulic Engineering.
Research Area: Hydrology and Water Resources, Remote Sensing, Climate Change, Drought, and GRACE applications etc.
Email: khalil_rahman@sdu.edu.cn; engr.khalil0598@gmail.com
Education:
2017–2021, Tsinghua University, China, PhD.
Major in Hydraulic Engineering.
2015–2017, King Abdulaziz University, Saudi Arabia, MS.
Major in Hydrology and Water Resources Management.
2009–2013, University of Engineering and Technology Peshawar, Pakistan, BS.
Major in Hydrology and Water Resources.
Professional Experience:
2024-02–Continued: Shandong University, Associate Professor.
2021-11–2023-11: Tsinghua University, Postdoctoral Fellow (Shuimu Scholar).
Research Interests:
1. Hydrology and Water Resources:
a. Hydrological Modeling (both surface water and groundwater).
b. Unsaturated Zone Modeling.
c. Rainwater Harvesting and its impact on water resources.
d. Applications of machine learning and statistical techniques in hydrology and water resources management.
2. Remote Sensing applications
a. Evaluation of remote sensing techniques in hydrology and water resources.
b. Development and evaluation of merged satellite precipitation datasets.
c. Google Earth Engine applications.
d. Land use impact assessment.
3. Climate change
a. Climate change and impact assessment on water resources.
b. Downscaling and evaluation of climate models.
4. Drought
a. Drought characterization including drought estimation and drought propagation.
b. Development of drought indices and their validation at local scale.
c. Quantifying the contributions of climate change and land use variation to drought severity.
5. GRACE modeling
a. Total water storage change assessment using GRACE satellite.
b. Spatial and temporal downscaling of GRACE satellite data.
c. Application of GRACE in monitoring real-time fluctuations in groundwater table.
Research Projects:
2023-01 to 2023-12 (Principal Investigator): Application of GRACE in monitoring real-time fluctuations in groundwater table across data-scarce arid climatic region, funded by the National Natural Science Foundation of China (NSFC) under Research Fund for International Young Scientist (RFIS-I) grant (200,000 Yuan).
2023-01 to 2023-12 (Principal Investigator): Development and evaluation of a robust VHI by optimizing the weights of VCI and TCI under severe climate and land use changes, funded by the China Postdoctoral Science Foundation (80,000 Yuan).
2023-01–Continued (Participant): Remote sensing-based retrieval and analysis of the response of topsoil water and salt regime in Spring to autumn/winter irrigation in previous year for irrigation district of arid region, funded by the National Natural Science Foundation of China (NSFC).
2021-01–Continued (Participant): Economic and environmental implications of Water harvesting practices under changing climate and land use scenarios across Pakistan, funded by the Higher Education Commission of Pakistan under CPEC-CRG research grant.
Professional Membership:
➢ International Glaciological Society (IGS)
➢ Young Hydrologist Society (YHS)
➢ Pakistan Engineering Council (PEC)
➢ International Association for Engineering Geology and the Environment (IAEG)
➢ Founder of the HydroSensing community (www.hydrosensing4u.com).
Research Publications:
2024:
1. Rahman, K.U., Ejaz, N., Shang, S.*, Balkhair, K.S., Alghamdi, K.M., Zaman, K., Khan, M.A. and Hussain, A., 2024. A robust integrated agricultural drought index under climate and land use variations at the local scale in Pakistan. Agricultural Water Management, 295, p.108748.
2. Ejaz, N., Khan, A.H., Shahid, M., Zaman, K., Balkhair, K.S., Alghamdi, K.M., Rahman, K.U.* and Shang, S., 2024. Superiority of Dynamic Weights against Fixed Weights in Merging Multi-Satellite Precipitation Datasets over Pakistan. Water, 16(4), p.597.
3. Rahman, K.U., Ejaz, N., Saleem, M.W., Mao, D., Balkhair, K.S., Khan, K.U.J., and Shang, S.*, 2024. Global Assessment of novel and robust Vegetation Health Indices: Bridging Climate Change and Land Use variations using PCA-weighted drought framework. Remote Sensing of Environment (Under Review).
4. Jing, L., Chen, C., Xinmin, M., Shiliang, L., and Rahman, K.U., Mao, D., 2024. Utilizing the electrical resistivity tomography to map contamination in a quarry. Journal of Environmental Management (Under Review).
5. Khan, A.H., Ejaz, N., Ali, M.Z., Rahman, K.U.*, Jadoon, K.Z., and Shang, S., 2024. Unraveling Groundwater Dynamics in The Depleted Aquifer of Indus Basin Using GRACE Satellite and In-Situ Observations. Science of the Total Environment (Under Review).
6. Masud, T., Khan, A., Khan, M., Ajmal, M., and Rahman, K.U.*, 2024. Impact of Climate Change on Streamflow Projections Over Chenab River 2 Basin Under CMIP6 Scenarios. Journal of Hydrology: Regional Studies (Under Review).
7. Shahid, M., Waseem, M., Rahman, K.U.*, Haider, S., and Gabriel, H.F., 2024. An Innovative conceptual framework to identify the potential sites for rainwater harvesting in arid regions. Applied Water Science (Under Review).
8. Rahman, K.U., Shang, S., Balkhair, K.S., Gabriel, H.F., Jadoon, K.Z., and Zaman, K., 2024. Catchment scale assessment of drought impact on environmental flow in the Indus Basin, Pakistan. Natural Hazards and Earth System Sciences (Under Review).
2023:
1. Qian, X., Qi, H., Shang, S., Wan, H., Rahman, K.U. and Wang, R., 2023. Deep Learning-based Near-real-time Monitoring of Autumn Irrigation Extent at Sub-pixel Scale in a large Irrigation District. Agricultural Water Management, 284, p.108335.
2. Ashraf, M.S., Shahid, M., Waseem, M., Azam, M. and Rahman, K.U.*, 2023. Assessment of Variability in Hydrological Droughts Using the Improved Innovative Trend Analysis Method. Sustainability, 15(11), p.9065.
3. Zahran, H., Ali, M.Z., Jadoon, K.Z., Yousafzai, H.U.K., Rahman, K.U.* and Sheikh, N.A., 2023. Impact of Urbanization on Groundwater and Surface Temperature Changes: A Case Study of Lahore City. Sustainability, 15(8), p.6864.
4. Rahman, K.U., Shang, S., Balkhair, K. and Nusrat, A., 2023. Catchment-Scale Drought Propagation Assessment in the Indus Basin of Pakistan Using a Combined Approach of Principal Components and Wavelet Analyses. Journal of Hydrometeorology, 24(4), pp.601-624.
5. Ejaz, N., Bahrawi, J., Alghamdi, K.M., Rahman, K.U. and Shang, S., 2023. Drought Monitoring Using Landsat Derived Indices and Google Earth Engine Platform: A Case Study from Al-Lith Watershed, Kingdom of Saudi Arabia. Remote Sensing, 15(4), p.984.
6. Ejaz, N., Elhag, M., Bahrawi, J., Zhang, L., Gabriel, H.F. and Rahman, K.U.*, 2023. Soil Erosion Modelling and Accumulation Using RUSLE and Remote Sensing Techniques: Case Study Wadi Baysh, Kingdom of Saudi Arabia. Sustainability, 15(4), p.3218.
7. Rahman, K.U., Hussain, A., Ejaz, N., Shang, S., Balkhair, K.S., Khan, K.U.J., Khan, M.A. and Rehman, N.U., 2023. Analysis of production and economic losses of cash crops under variable drought: A case study from Punjab province of Pakistan. International Journal of Disaster Risk Reduction, 85, p.103507.
8. Hussain, A., Jadoon, K.Z., Rahman, K.U., Shang, S., Shahid, M., Ejaz, N. and Khan, H., 2023. Analyzing the impact of drought on agriculture: evidence from Pakistan using standardized precipitation evapotranspiration index. Natural Hazards, 115(1), pp.389-408.
2022:
1. Hussain, A., Rahman, K.U., Shahid, M., Haider, S., Pham, Q.B., Linh, N.T.T. and Sammen, S.S., 2022. Investigating feasible sites for multi-purpose small dams in Swat District of Khyber Pakhtunkhwa Province, Pakistan: socioeconomic and environmental considerations. Environment, Development and Sustainability, pp.1-24.
2. Rahman, K.U., Pham, Q.B., Jadoon, K.Z., Shahid, M., Kushwaha, D.P., Duan, Z., Mohammadi, B., Khedher, K.M. and Anh, D.T., 2022. Comparison of machine learning and process-based SWAT model in simulating streamflow in the Upper Indus Basin. Applied water science, 12(8), p.178.
3. Wen, Y., Wan, H., Shang, S. and Rahman, K.U., 2022. A monthly distributed agro-hydrological model for irrigation district in arid region with shallow groundwater table. Journal of Hydrology, 609, p.127746.
4. Rahman, K.U., Hussain, A., Ejaz, N., Shahid, M., Duan, Z., Mohammadi, B., Hoai, P.N., Pham, Q.B., Khedher, K.M. and Anh, D.T., 2022. Evaluating the impact of the environment on depleting groundwater resources: a case study from a semi-arid and arid climatic region. Hydrological Sciences Journal, 67(5), pp.791-805.
5. Polong, F., Pham, Q.B., Anh, D.T., Rahman, K.U., Shahid, M. and Alharbi, R.S., 2023. Evaluation and comparison of four satellite-based precipitation products over the upper Tana River Basin. International Journal of Environmental Science and Technology, 20(1), pp.843-858.
6. Mohammadi, B., Moazenzadeh, R., Pham, Q.B., Al-Ansari, N., Rahman, K.U., Anh, D.T. and Duan, Z., 2022. Application of ERA-Interim, empirical models, and an artificial intelligence-based model for estimating daily solar radiation. Ain Shams Engineering Journal, 13(1), p.101498.
2021:
1. Wan, H., Li, J., Shang, S. and Rahman, K.U., 2021. Exploratory factor analysis-based co-kriging method for spatial interpolation of multi-layered soil particle-size fractions and texture. Journal of Soils and Sediments, 21, pp.3868-3887.
2. Shahid, M., Rahman, K.U., Haider, S., Gabriel, H.F., Khan, A.J., Pham, Q.B., Pande, C.B., Linh, N.T.T. and Anh, D.T., 2021. Quantitative assessment of regional land use and climate change impact on runoff across Gilgit watershed. Environmental Earth Sciences, 80, pp.1-18.
3. Shahid, M., Rahman, K.U., Haider, S., Gabriel, H.F., Khan, A.J., Pham, Q.B., Mohammadi, B., Linh, N.T.T. and Anh, D.T., 2021. Assessing the potential and hydrological usefulness of the CHIRPS precipitation dataset over a complex topography in Pakistan. Hydrological Sciences Journal, 66(11), pp.1664-1684.
4. Li, J., Shang, S., Jiang, H., Song, J., Rahman, K.U. and Adeloye, A.J., 2021. Simulation-based optimization for spatiotemporal allocation of irrigation water in arid region. Agricultural Water Management, 254, p.106952.
5. Linh, N.T.T., Ruigar, H., Golian, S., Bawoke, G.T., Gupta, V., Rahman, K.U., Sankaran, A. and Pham, Q.B., 2021. Flood prediction based on climatic signals using wavelet neural network. Acta Geophysica, 69(4), pp.1413-1426.
6. Rahman, K.U., Shang, S. and Zohaib, M., 2021. Assessment of merged satellite precipitation datasets in monitoring meteorological drought over Pakistan. Remote Sensing, 13(9), p.1662.
7. Elkhrachy, I., Pham, Q.B., Costache, R., Mohajane, M., Rahman, K.U., Shahabi, H., Linh, N.T.T. and Anh, D.T., 2021. Sentinel‐1 remote sensing data and Hydrologic Engineering Centres River Analysis System two‐dimensional integration for flash flood detection and modelling in New Cairo City, Egypt. Journal of Flood Risk Management, 14(2), p.e12692.
8. Shahid, M. and Rahman, K.U., 2021. Identifying the annual and seasonal trends of hydrological and climatic variables in the Indus Basin Pakistan. Asia-Pacific Journal of Atmospheric Sciences, 57, pp.191-205.
9. Balkhair, K.S. and Rahman, K.U., 2021. Development and assessment of rainwater harvesting suitability map using analytical hierarchy process, GIS and RS techniques. Geocarto International, 36(4), pp.421-448.
2020:
1. Rahman, K.U. and Shang, S., 2020. A regional blended precipitation dataset over Pakistan based on regional selection of blending satellite precipitation datasets and the dynamic weighted average least squares algorithm. Remote Sensing, 12(24), p.4009.
2. Rahman, K.U., Shang, S., Shahid, M., Wen, Y. and Khan, A.J., 2020. Development of a novel weighted average least squares-based ensemble multi-satellite precipitation dataset and its comprehensive evaluation over Pakistan. Atmospheric Research, 246, p.105133.
3. Guan, Y., Mohammadi, B., Pham, Q.B., Adarsh, S., Balkhair, K.S., Rahman, K.U., Linh, N.T.T. and Tri, D.Q., 2020. A novel approach for predicting daily pan evaporation in the coastal regions of Iran using support vector regression coupled with krill herd algorithm model. Theoretical and Applied Climatology, 142, pp.349-367.
4. Rahman, K.U., Shang, S., Shahid, M. and Wen, Y., 2020. Hydrological evaluation of merged satellite precipitation datasets for streamflow simulation using SWAT: a case study of Potohar Plateau, Pakistan. Journal of Hydrology, 587, p.125040.
5. Wen, Y., Shang, S., Rahman, K.U., Xia, Y. and Ren, D., 2020. A semi-distributed drainage model for monthly drainage water and salinity simulation in a large irrigation district in arid region. Agricultural Water Management, 230, p.105962.
6. Rahman, K.U., Shang, S., Shahid, M., Wen, Y. and Khan, Z., 2020. Application of a dynamic clustered bayesian model averaging (DCBA) algorithm for merging multisatellite precipitation products over Pakistan. Journal of Hydrometeorology, 21(1), pp.17-37.
2019:
1. Rahman, K.U., Shang, S., Shahid, M. and Wen, Y., 2019. An appraisal of dynamic bayesian model averaging-based merged multi-satellite precipitation datasets over complex topography and the diverse climate of Pakistan. Remote Sensing, 12(1), p.10.
2. Rahman, K.U., Shang, S., Shahid, M. and Wen, Y., 2019. Performance assessment of SM2RAIN-CCI and SM2RAIN-ASCAT precipitation products over Pakistan. Remote Sensing, 11(17), p.2040.
3. Wen, Y., Shang, S. and Rahman, K.U., 2019. Pre-constrained machine learning method for multi-year mapping of three major crops in a large irrigation district. Remote Sensing, 11(3), p.242.
2018:
1. Rahman, K.U., Shang, S., Shahid, M. and Li, J., 2018. Developing an ensemble precipitation algorithm from satellite products and its topographical and seasonal evaluations over Pakistan. Remote Sensing, 10(11), p.1835.
2017:
1. Balkhair, K.S. and Rahman, K.U., 2017. Sustainable and economical small-scale and low-head hydropower generation: A promising alternative potential solution for energy generation at local and regional scale. Applied Energy, 188, pp.378-391.
2. Rahman, K.U.*, Balkhair, K.S., Almazroui, M. and Masood, A., 2017. Sub-catchments flow losses computation using Muskingum–Cunge routing method and HEC-HMS GIS based techniques, case study of Wadi Al-Lith, Saudi Arabia. Modeling Earth Systems and Environment, 3, pp.1-9.
Recruitment Information:
Students having research interests in remote sensing, hydrology and water resources, and hydraulic engineering are welcome to apply for Master and PhD studies. Please feel free to contact me!
Contacts:
Address: Office 410, School of Civil Engineering, Shandong University, 17922 Jingshi Road, Jinan 250061, China.
Email: khalil_rahman@sdu.edu.cn; engr.khalil0598@gmail.com
