Trends of extreme flows of the Krishna river at a barrage, India

References

• Anderson, R. L. (1942). Distribution of the serial correlation coefficient. The Annals of Mathematical Statistics, 13(1), 1–13. https://doi.org/10.1214/aoms/1177731638
   Google Scholar
• Coulibaly, P., & Shi, X. (2005). Identification of the effect of climate change on future design standards of drainage infrastructure in Ontario, final report. Department of Civil Engineering, McMaster University.
   Google Scholar
• Das, A., & Panchal, M. (2018). Krishna river basin. In D. S. Singh (Ed.), The Indian rivers, springer hydrogeology, 339–351. https://doi.org/10.1007/978-981-10-2984-4_27.
   Google Scholar
• Gaur, A., McCornick, P. G., Turral, H., & Acharya, S. (2007). Implications of drought and water regulation in the Krishna Basin, India. International Journal of Water Resources Development, 23(4), 583–594. https://doi.org/10.1080/07900620701488513.
   Web of Science ®Google Scholar
• Goel, M. K., Jain S. K., Rani D., Subrahmanyam G. V., Visweswararao M. (2020). Developing operation procedures for individual reservoirs in a large multistate river basin in context of tribunal awards. Journal of Water Resources Planning and Management, 146(8), Article 05020013. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001253
   Web of Science ®Google Scholar
• Gopala Rao, J., Sharma, G., & Kumar, S. (2019). Analysis of precipitation for improve watershed to Krishna river. In International conference on innovative trends in Civil Engineering for sustainable development.
   Google Scholar
• Hamed, K. H. (2009). Enhancing the effectiveness of prewhitening in trend analysis of hydrologic data. Journal of Hydrology, 368(1), 143–155. https://doi.org/10.1016/j.jhydrol.2009.01.040
   Web of Science ®Google Scholar
• Harshavardhan, P. L., Nayak, P. C., & Kumar, S. (2020). Spatio-temporal rainfall variability and trend analysis for Krishna river basin in India. Indian Journal Ecology, 47(11), 54–59.
   Google Scholar
• Kendall, M. G., & Stuart, A. (1968). The advanced theory of statistics: Design and analysis, and time-series. Charles Griffin & Company.
   Google Scholar
• Lacombe, G., Mccartney, M., & Forkuor, G. (2012). Drying climate in Ghana over the period 1960-2005: Evidence from the resampling-based Mann-Kendall test at local and regional levels. Hydrological Sciences Journal, 57(8), 1594–1609. https://doi.org/10.1080/02626667.2012.728291
   Web of Science ®Google Scholar
• Mahajan, D. R., Dodamani, B. M. & Mannina G. (Reviewing Editor) (2016). Spatial and temporal drought analysis in the Krishna river basin of Maharashtra, India. Cogent Engineering, 3(1), 1185926. http://doi.org/10.1080/23311916.2016.1185926
   Web of Science ®Google Scholar
• Mujiburrehman, K. (2017). Frequency analysis of flood flow in Krishna river using Gumbell distribution at Vijayawada station, Andhra Pradesh, India. International Journal of Research in Engineering and Innovation, 1(3), 61–64.
   Google Scholar
• Nikam, B. R., Garg V., Jeyaprakash K., Gupta P. K., Srivastav S. K., Thakur P. K., & Aggarwal S. P. (2018). Analyzing future water availability and hydrological extremes in the Krishna basin under changing climatic conditions. Arabian Journal of Geosciences, 11(19), 581. https://doi.org/10.1007/s12517-018-3936-1.
   Web of Science ®Google Scholar
• Ninu Krishnan, M. V., Prasanna M. V., & Vijith H. (2019). Statistical analysis of trends in monthly precipitation at the Limbang River Basin, Sarawak (NW Borneo), Malaysia. Meteorology and Atmospheric Physics, 131, 883–896. https://doi.org/10.1007/s00703-018-0611-8
   Google Scholar
• Patakamuri, S. K., & O’Brien, N. (2020). modifiedmk: Modified versions of Mann Kendall and Spearman’s Rho trend tests (R package version 1.5.0). https://CRAN.R-project.org/package=modifiedmk
   Google Scholar
• R Core Team. (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/
   Google Scholar
• Raje, D., Priya, P., & Krishnan, R. (2014). Macroscale hydrological modelling approach for study of large scale hydrologic impacts under climate change in Indian river basins. Hydrological Processes, 28(4), 1874–1889. https://doi.org/10.1002/hyp.9731
   Web of Science ®Google Scholar
• Rehana, S., Monish, N. T., & Sireesha Naidu, G. (2020). Estimation of annual regional drought index considering the joint effects of climate and water budget for Krishna river basin, India. Environmental Monitoring and Assessment, 192(7), 427. https://doi.org/10.1007/s10661-020-08379-y.
   PubMed Web of Science ®Google Scholar
• Sai Krishna, G., & Veerendra, G. T. N. (2015). Flood frequency analysis of Prakasam barrage reservoir Krishna district, Andhra Pradesh using Weibull, Gringorten and L-moments formula. International Journal of Civil, Structural, Environmental and Infrastructure Engineering Research and Development, 5(2), 57–62.
   Google Scholar
• Salas, J. D., Delleur, J. W., Yevjevich, V. M., & Lane, W. L. (1980). Applied modeling of hydrologic time series. Water Resources Publications.
   Google Scholar
• Sarma, A. A. L. N., & Srinivas, S. (2006). Anomalies in terrestrial hydrological cycle – India. Mausam, 57(4), 639–652. https://doi.org/10.54302/mausam.v57i4.503.
   Google Scholar
• Sathe, B. K., Khir, M. V., & Sankhua, R. N. (2012). Rainfall analysis and design flood estimation for Upper Krishna river basin Catchment in India. International Journal of Scientific & Engineering Research, 3(8).
   Google Scholar
• Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall’s Tau. Journal of the American Statistical Association, 63(324), 1379–1389. https://doi.org/10.1080/01621459.1968.10480934.
   Web of Science ®Google Scholar
• Singh, G. R., Jain, M. K., & Gupta, V. (2019). Spatiotemporal assessment of drought hazard, vulnerability and risk in the Krishna river basin, India. Natural Hazards, 99, 611–635. https://doi.org/10.1007/s11069-019-03762-6.
   Google Scholar
• Tirupathi, C., Shashidhar, T., & Srinivasan, R. (2018). Analysis of rainfall extremes and water yield of Krishna river basin under future climate scenarios. Journal of Hydrology: Regional Studies, 19, 287–306. https://doi.org/10.1016/j.ejrh.2018.10.004.
   Google Scholar
• Uday Kumar, A., & Jayakumar, K. V. (2018). Assessment of environmental flows using hydrological methods for Krishna river, India. Advances in Environmental Research, 7(3), 161–175. https://doi.org/10.12989/aer.2018.7.3.161.
   Google Scholar
• Uday Kumar, A., & Jayakumar, K. V. (2020). Hydrological alterations due to anthropogenic activities in Krishna river basin, India. Ecological Indicators, 108, 105663. https://doi.org/10.1016/j.ecolind.2019.10566.
   Web of Science ®Google Scholar
• Wickham, H., & Bryan, J. (2019). readxl: Read Excel Files (R package version 1.3.1). https://CRAN.R-project.org/package=readxl
   Google Scholar
• Yee, M. S., George, B. A., Nawarathna, B., Malano, H. M., & Parthasaradhi, G. (2009, July). Assessing water security across the Krishna River basin. In 18th World IMACS Congress and MODSIM09 International Congress on modeling and simulation. Modeling and Simulation Society of Australia and New Zealand and International Association for Mathematics and Computers in Simulation, Cairns, Australia, 3879–3885.
   Google Scholar
• Yue, S., & Pilon, P. (2004). A comparison of the power of the t test, Mann-Kendall and bootstrap tests for trend detection. Hydrological Sciences Journal, 49(1), 21–37. https://doi.org/10.1623/hysj.49.1.21.53996.
   Web of Science ®Google Scholar