Peer-reviewed
[8]. Takhellambam, B. S., Srivastava, P., Lamba, J., Zhao, W., Kumar, H., Tian, D., & Molinari, R. (2024). Artificial neural network-empowered projected future rainfall intensity-duration-frequency curves under changing climate. Atmospheric Research, 297, 107122. DOI
[7]. Kumar, H., Srivastava, P., Lamba, J., Lena, B., Diamantopoulos, E., Ortiz, B., Takhellambam, B.S., Morata, G., Bondesan, L., 2023. A methodology to optimize site-specific field capacity and irrigation thresholds. Agricultural Water Management 286, 108385. DOI
[6]. Zhao, W., Abhishek, A., Takhellambam, B.S., Zhang, J., Zhao, Y., Kinouchi, T., 2023. Spatiotemporal variability of current and future sub-daily rainfall in Japan using state-of-the-art high-quality datasets. Water Resource Research 59, e2022WR03430. DOI
[5]. Takhellambam, B.S., Srivastava, P., Lamba, J., McGehee, R.P., Kumar, H., Tian, D., 2022. Projected mid-century rainfall erosivity under climate change over the southeastern United States. Science of The Total Environment. 161119. DOI
[4]. Takhellambam, B.S., Srivastava, P., Lamba, J., McGehee, R.P., Kumar, H., Tian, D., 2022. Temporal disaggregation of hourly precipitation under changing climate over the Southeast United States. Scientific Data 9, 11. DOI
[3]. Kumar, H., Srivastava, P., Lamba, J., Diamantopoulos, E., Ortiz, B., Morata, G., Takhellambam, B.S., Bondesan, L., 2022. Site-specific irrigation scheduling using one-layer soil hydraulic properties and inverse modeling. Agricultural Water Management 273, 107877.DOI
[2]. Kumar, H., Srivastava, P., Lamba, J., Ortiz, B.V., Way, T.R., Sangha, L., Takhellambam, B.S., Morata, G., Molinari, R., 2022. Within-field variability in nutrients for site-specific agricultural management in irrigated cornfield. Journal of ASABE,65, 865–880. DOI
[1]. Kumar, H., Srivastava, P., Ortiz, B.V., Morata, G., Takhellambam, B.S., Lamba, J., Bondesan, L., 2021. Field-scale spatial and temporal soil water variability in irrigated croplands. Transactions of the ASABE,1277–1294. DOI
Other publications
[2]. Takhellambam, B.S., Srivastava, P., Lamba, J., McGehee, R.P., Kumar, H., Tian, D., 2022. Projected rainfall erosivity under climate change in the southeastern united states, in: ASABE Paper No. 2200176. Presented at the Annual International Meeting, ASABE, St. Joseph, MI, p. 1.DOI
[1]. Takhellambam, B.S., Srivastava, P., Lamba, J., Zhao, W., Kumar, H., Tian, D., 2022. Assessment of projected change in Intensity-duration-frequency (IDF) curves for Southeastern, United States using Artificial Neural Networks., in: ASABE Paper No. 2200175. Presented at the Annual International Meeting, ASABE, St. Joseph, MI, p. 1. DOI
Submitted/ Under Review/In Preparation
[1]. Takhellambam, B.S., Srivastava, P., Lamba, J., Kumar, H., Molinari, R., 2023. Uncertainty Quantification of Rainfall Intensity Duration Frequency Curves.