Publications

Edited Books:

1. Chaitanya B. Pande; Manish Kumar; Kushwaha, N. L. (2023) Surface and Groundwater Resources Development and Managment in Semi-arid Region,  Springer Hydrogeology, Springer Nature. https://doi.org/10.1007/978-3-031-29394-823 (ISBN: 978-3-031-29393-1), Pp 427  

2. Pandey K.; Kushwaha, N. L.; Chaitanya B. Pande; Singh K.G. (2023) Artificial Intelligence and Smart Agriculture: Technology and Applications,  Advances in Geograhical and Environmental  Seciences , Springer Nature. https://doi.org/10.1007/978-981-97-0341-8 (ISBN: 978-981-97-0340-1) Pp 567

3. S. Manivannan, TBS Rajput, Sanjay Arora, V. Kasthuri Thilagam, Nand Lal Kushwaha, Mukesh Kumar, RAS Patel, Manjushree Singh, (Eds.) The Book of Abstracts, International Conference on “Sustainable Natural Resource Management under Global Climate Change”, November 7-10, 2023, Soil Conservation Society of India, New Delhi, India. (ISBN 978-81-958227-7-5), Pp 638

4. S. Manivannan, TBS Rajput, Sanjay Arora, V. Kasthuri Thilagam, Nand Lal Kushwaha, Mukesh Kumar, RAS Patel, Manjushree Singh (Eds.) Book of Invited Papers, International Conference on “Sustainable Natural Resource Management under Global Climate Change”, November 7-10, 2023, Soil Conservation Society of India, New Delhi, India. (ISBN 978-81-967847-8-2), Pp 206 

5. S. Manivannan, TBS Rajput, RAS Patel, V. Kasthuri Thilagam, Nand Lal Kushwaha, Mukesh Kumar, Manjushree Singh (Eds.). Souvenir, 5th International Conference on “Sustainable Natural Resource Management under Global Climate Change”, November 7-10, 2023, Soil Conservation Society of India, New Delhi, India. (ISBN: 978-81-967847-0-6), Pp 64 

Research Paper:

2024:

1.  Kushwaha, N.L., Kudnar, N.S., Vishwakarma, D.K., Subeesh, A., Jatav, M.S., Gaddikeri, V., Ahmed, A.A., Abdelaty, I., 2024. Stacked hybridization to enhance the performance of artificial neural networks (ANN) for prediction of water quality index in the Bagh river basin, India. Heliyon 10. https://doi.org/10.1016/j.heliyon.2024.e31085

2. Pande, C.B., Kushwaha, N.L., Alawi, O.A., Sammen, S.S., Sidek, L.M., Yaseen, Z.M., Pal, S.C., Katipoğlu, O.M., 2024. Daily scale air quality index forecasting using bidirectional recurrent neural networks: Case study of Delhi, India. Environ. Pollut. 351, 124040. https://doi.org/10.1016/j.envpol.2024.124040

3. Singh, S., Kumar, D., Vishwakarma, D.K., Kumar, R., Kushwaha, N.L., 2024. Seasonal rainfall pattern using coupled neural network-wavelet technique of southern Uttarakhand, India. Theor. Appl. Climatol. https://doi.org/10.1007/s00704-024-04940-8

4. Swain, S.S., Khura, T.K., Sahoo, P.K., Chobhe, K.A., Al-Ansari, N., Kushwaha, H.L., Kushwaha, N.L., Panda, K.C., Lande, S.D., Singh, C., 2024. Proportional impact prediction model of coating material on nitrate leaching of slow-release Urea Super Granules (USG) using machine learning and RSM technique. Sci. Rep. 14, 3053. https://doi.org/10.1038/s41598-024-53410-8

5. Tulla, P.S., Kumar, P., Vishwakarma, D.K., Kumar, R., Kuriqi, A., Kushwaha, N.L., Rajput, J., Srivastava, A., Pham, Q.B., Panda, K.C., Kisi, O., 2024. Daily suspended sediment yield estimation using soft-computing algorithms for hilly watersheds in a data-scarce situation: a case study of Bino watershed, Uttarakhand. Theor. Appl. Climatol. 155, 4023–4047. https://doi.org/10.1007/s00704-024-04862-5

6. Gaddikeri, V., Sarangi, A., Singh, D.K., Jatav, M.S., Rajput, J., Kushwaha, N.L., 2024. Trend and change-point analyses of meteorological variables using Mann–Kendall family tests and innovative trend assessment techniques in New Bhupania command (India). J. Water Clim. Change jwc2024462. https://doi.org/10.2166/wcc.2024.462

2023:

1. Kushwaha, N.L.*, Rajput, J., Suna, T., Sena, D.R., Singh, D.K., Mishra, A.K., Sharma, P.K., Mani, I., 2023. Metaheuristic approaches for prediction of water quality indices with relief algorithm-based feature selection. Ecological Informatics 75, 102122. https://doi.org/10.1016/j.ecoinf.2023.102122 (IF= 4.498)

2. Abd-Elaty, I., Kushwaha, N.L., Patel, A., 2023. Novel Hybrid Machine Learning Algorithms for Lakes Evaporation and Power Production using Floating Semitransparent Polymer Solar Cells. Water Resour. Manag. https://doi.org/10.1007/s11269-023-03565-2 (IF= 4.300)

3. Patel, A., Kethavath, A., Kushwaha, N.L., Naorem, A., Jagadale, M., K.r., S., P.s., R., 2023. Review of artificial intelligence and internet of things technologies in land and water management research during 1991–2021: A bibliometric analysis. Engineering Applications of Artificial Intelligence 123, 106335. https://doi.org/10.1016/j.engappai.2023.106335 (IF= 7.800)

4. Pande, C.B., Kushwaha, N.L., Orimoloye, I.R., Kumar, R., Abdo, H.G., Tolche, A.D., Elbeltagi, A., 2023. Comparative Assessment of Improved SVM Method under Different Kernel Functions for Predicting Multi-scale Drought Index. Water Resour Manage 37, 1367–1399. https://doi.org/10.1007/s11269-023-03440-0 (IF= 4.300)

5. Elbeltagi, A., Al-Mukhtar, M., Kushwaha, N.L., Al-Ansari, N., Vishwakarma, D.K., 2023. Forecasting monthly pan evaporation using hybrid additive regression and data-driven models in a semi-arid environment. Appl Water Sci 13, 42. https://doi.org/10.1007/s13201-022-01846-6  (IF= 5.500)

6. Cimusa Kulimushi, L., Bigabwa Bashagaluke, J., Prasad, P., Heri-Kazi, A.B., Kushwaha, N. L., Masroor, M., Choudhari, P., Elbeltagi, A., Sajjad, H., Mohammed, S., 2023. Soil erosion susceptibility mapping using ensemble machine learning models: A case study of upper Congo river sub-basin. CATENA 222, 106858. https://doi.org/10.1016/j.catena.2022.106858 (IF= 6.367)

7. Elbeltagi, A., Kumar, M., Kushwaha, N.L.*, Pande, C.B., Ditthakit, P., Vishwakarma, D.K., Subeesh, A., 2023. Drought indicator analysis and forecasting using data driven models: case study in Jaisalmer, India. Stoch Environ Res Risk Assess 37, 113–131. https://doi.org/10.1007/s00477-022-02277-0 (IF= 3.821)

8. Elbeltagi, A., Srivastava, A., Kushwaha, N.L., Juhász, C., Tamás, J., Nagy, A., 2023. Meteorological Data Fusion Approach for Modeling Crop Water Productivity Based on Ensemble Machine Learning. Water 15, 30. https://doi.org/10.3390/w15010030 (IF= 3.40)

9. Vishwakarma, D. K., Kumar, R., Abed, S. A., Al-Ansari, N., Kumar, A., Kushwaha, N. L., Yadav, D., Kumawat, A., Kuriqi, A., Alataway, A., Dewidar, A. Z., & Mattar, M. A. (2023). Modeling of soil moisture movement and wetting behavior under point-source trickle irrigation. Scientific Reports, 13(1), Article 1. https://doi.org/10.1038/s41598-023-41435-4 (IF= 4.60)

10. Vishwakarma, D.K., Kuriqi, A., Abed, S.A., Kishore, G., Al-Ansari, N., Pandey, K., Kumar, P., Kushwaha, N.L., Jewel, A., 2023. Forecasting of stage-discharge in a non-perennial river using machine learning with gamma test. Heliyon 9. https://doi.org/10.1016/j.heliyon.2023.e16290  (IF= 4.00)

2022:

1. Kushwaha, N. L., Elbeltagi, A., Mehan, S., Malik, A., Yousuf, A., 2022. Comparative study on morphometric analysis and RUSLE-based approaches for micro-watershed prioritization using remote sensing and GIS. Arab J Geosci 15, 564. https://doi.org/10.1007/s12517-022-09837-2

2. Kushwaha, N. L., Rajput, J., Sena, D.R., Elbeltagi, A., Singh, D.K., Mani, I., 2022. Evaluation of Data-driven Hybrid Machine Learning Algorithms for Modelling Daily Reference Evapotranspiration. Atmosphere-Ocean 60, 519–540. https://doi.org/10.1080/07055900.2022.2087589

3. Kushwaha, N. L., Rajput, J., Shirsath, P.B., Sena, D.R., Mani, I., 2022. Seasonal climate forecasts (SCFs) based risk management strategies: A case study of rainfed rice cultivation in India. Journal of Agrometeorology 24, 10–17. https://doi.org/10.54386/jam.v24i1.775

4. Abd-Elaty, I., Kushwaha, N.L., Grismer, M.E., Elbeltagi, A., Kuriqi, A., 2022. Cost-effective management measures for coastal aquifers affected by saltwater intrusion and climate change. Science of The Total Environment 836, 155656. https://doi.org/10.1016/j.scitotenv.2022.155656

5. Vishwakarma, D.K., Pandey, K., Kaur, A., Kushwaha, N.L., Kumar, R., Ali, R., Elbeltagi, A., Kuriqi, A., 2022. Methods to estimate evapotranspiration in humid and subtropical climate conditions. Agricultural Water Management 261, 107378. https://doi.org/10.1016/j.agwat.2021.107378

6. Abd-Elaty, I., Shoshah, H., Zeleňáková, M., Kushwaha, N.L., El-Dean, O.W., 2022. Forecasting of Flash Floods Peak Flow for Environmental Hazards and Water Harvesting in Desert Area of El-Qaa Plain, Sinai. International Journal of Environmental Research and Public Health 19, 6049. https://doi.org/10.3390/ijerph19106049

7. Elbeltagi, A., Di Nunno, F., Kushwaha, N.L., de Marinis, G., Granata, F., 2022. River flow rate prediction in the Des Moines watershed (Iowa, USA): a machine learning approach. Stoch Environ Res Risk Assess. https://doi.org/10.1007/s00477-022-02228-9

8. Elbeltagi, A., Kushwaha, N.L., Rajput, J., Vishwakarma, D.K., Kulimushi, L.C., Kumar, M., Zhang, J., Pande, C.B., Choudhari, P., Meshram, S.G., Pandey, K., Sihag, P., Kumar, N., Abd-Elaty, I., 2022. Modelling daily reference evapotranspiration based on stacking hybridization of ANN with meta-heuristic algorithms under diverse agro-climatic conditions. Stoch Environ Res Risk Assess. https://doi.org/10.1007/s00477-022-02196-0

9. Elbeltagi, A., Raza, A., Hu, Y., Al-Ansari, N., Kushwaha, N.L., Srivastava, A., Kumar Vishwakarma, D., Zubair, M., 2022. Data intelligence and hybrid metaheuristic algorithms-based estimation of reference evapotranspiration. Appl Water Sci 12, 152. https://doi.org/10.1007/s13201-022-01667-7

10. Pande, C.B., Al-Ansari, N., Kushwaha, N.L., Srivastava, A., Noor, R., Kumar, M., Moharir, K.N., Elbeltagi, A., 2022. Forecasting of SPI and Meteorological Drought Based on the Artificial Neural Network and M5P Model Tree. Land 11, 2040. https://doi.org/10.3390/land11112040

11. Dhanya, V.G., Subeesh, A., Kushwaha, N.L., Vishwakarma, D.K., Nagesh Kumar, T., Ritika, G., Singh, A.N., 2022. Deep learning based computer vision approaches for smart agricultural applications. Artificial Intelligence in Agriculture 6, 211–229. https://doi.org/10.1016/j.aiia.2022.09.007

12. Kumar, R., Manzoor, S., Vishwakarma, D.K., Al-Ansari, N., Kushwaha, N.L., Elbeltagi, A., Sushanth, K., Prasad, V., Kuriqi, A., 2022. Assessment of Climate Change Impact on Snowmelt Runoff in Himalayan Region. Sustainability 14, 1150. https://doi.org/10.3390/su14031150

13. Nazripouya, H., Meshram, S.G., Bahramloo, R., Sepehri, M., Ali, S.A., Kushwaha, N.L., Kiani-Harchegani, M., Rodrigo-Comino, J., 2022. Assessment of spatiotemporal changes of the length and starting date seasons in the west of Iran. Acta Geophys. 70, 2813–2825. https://doi.org/10.1007/s11600-022-00929-x

14. Rajput, J., Kothari, M., Bhakar, S.R., Dimple, Kushwaha, N.L., Singh, P.K., Paramaguru, P.K., Rai, A., Elbeltagi, A., Rana, L., 2022. Evaluation of water delivery performance of right main canal of Bhimsagar medium irrigation scheme, Rajasthan. ISH Journal of Hydraulic Engineering 0, 1–11. https://doi.org/10.1080/09715010.2022.2066483

15. Vishwakarma, D.K., Ali, R., Bhat, S.A., Elbeltagi, A., Kushwaha, N.L., Kumar, R., Rajput, J., Heddam, S., Kuriqi, A., 2022. Pre- and post-dam river water temperature alteration prediction using advanced machine learning models. Environ Sci Pollut Res 29, 83321–83346. https://doi.org/10.1007/s11356-022-21596-x

16. Vishwakarma, D.K., Kumar, R., Kumar, A., Kushwaha, N.L., Kushwaha, K.S., Elbeltagi, A., 2022. Evaluation and development of empirical models for wetted soil fronts under drip irrigation in high-density apple crop from a point source. Irrig Sci. https://doi.org/10.1007/s00271-022-00826-7

2021:

1. Kushwaha, N.L., Rajput, J., Elbeltagi, A., Elnaggar, A.Y., Sena, D.R., Vishwakarma, D.K., Mani, I., Hussein, E.E., 2021. Data Intelligence Model and Meta-Heuristic Algorithms-Based Pan Evaporation Modelling in Two Different Agro-Climatic Zones: A Case Study from Northern India. Atmosphere 12, 1654. https://doi.org/10.3390/atmos12121654

2. Elbeltagi, A., Aslam, M.R., Mokhtar, A., Deb, P., Abubakar, G.A., Kushwaha, N.L., Venancio, L.P., Malik, A., Kumar, N., Deng, J., 2021. Spatial and temporal variability analysis of green and blue evapotranspiration of wheat in the Egyptian Nile Delta from 1997 to 2017. Journal of Hydrology 594, 125662. https://doi.org/10.1016/j.jhydrol.2020.125662