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Raghavan Srinivasan 0001
Person information
- affiliation: Texas A&M University, Department of Ecosystem Science and Management, TX, USA
Other persons with the same name
- Raghavan Srinivasan — disambiguation page
- Srinivasan Raghavan 0002 — Indian Institute of Science, Centre for Nano Science and Engineering (CeNSE), Bangalore, India
- Srinivasan Raghavan 0003 — teradata Labs, Santa Clara, CA, USA
- Srinivasan Raghavan 0004 — LNK Corporation Inc., Riverdale, MD, USA
- Srinivasan Raghavan 0005 — University of Windsor, ON, Canada
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2020 – today
- 2022
- [j25]Tam V. Nguyen
, Jörg Dietrich
An interactive graphical interface tool for parameter calibration, sensitivity analysis, uncertainty analysis, and visualization for the Soil and Water Assessment Tool. Environ. Model. Softw. 156: 105497 (2022) - 2021
- [j24]Javier Senent-Aparicio
Introducing a new post-processing tool for the SWAT+ model to evaluate environmental flows. Environ. Model. Softw. 136: 104944 (2021) - 2020
- [j23]Rodrigo de Queiroga Miranda
Realistic and simplified models of plant and leaf area indices for a seasonally dry tropical forest. Int. J. Appl. Earth Obs. Geoinformation 85 (2020) - [j22]Yong Chen, Gary W. Marek, Thomas H. Marek, Dana Porter, Jerry E. Moorhead, Kevin R. Heflin, David K. Brauer, Raghavan Srinivasan:
Watershed scale evaluation of an improved SWAT auto-irrigation function. Environ. Model. Softw. 131: 104789 (2020) - [j21]Celray James Chawanda
User-friendly workflows for catchment modelling: Towards reproducible SWAT+ model studies. Environ. Model. Softw. 134: 104812 (2020) - [j20]Kha Dang Dinh
Evaluation of Grid-Based Rainfall Products and Water Balances over the Mekong River Basin. Remote. Sens. 12(11): 1858 (2020) - [j19]Yeganantham Dhanesh, V. M. Bindhu, Javier Senent-Aparicio
A Comparative Evaluation of the Performance of CHIRPS and CFSR Data for Different Climate Zones Using the SWAT Model. Remote. Sens. 12(18): 3088 (2020)
2010 – 2019
- 2019
- [j18]Abeyou W. Worqlul
Effect of climate change on land suitability for surface irrigation and irrigation potential of the shallow groundwater in Ghana. Comput. Electron. Agric. 157: 110-125 (2019) - [j17]Yong Chen, Gary W. Marek, Thomas H. Marek, Prasanna H. Gowda, Qingwu Xue, Jerry E. Moorhead, David K. Brauer, Raghavan Srinivasan, Kevin R. Heflin:
Multisite evaluation of an improved SWAT irrigation scheduling algorithm for corn (Zea mays L.) production in the U.S. Southern Great Plains. Environ. Model. Softw. 118: 23-34 (2019) - [j16]Spencer McDonald, Ibrahim Nourein Mohammed
Web-based decision support system tools: The Soil and Water Assessment Tool Online visualization and analyses (SWATOnline) and NASA earth observation data downloading and reformatting tool (NASAaccess). Environ. Model. Softw. 120 (2019) - [j15]Tian Guo
Development and improvement of the simulation of woody bioenergy crops in the Soil and Water Assessment Tool (SWAT). Environ. Model. Softw. 122 (2019) - [j14]Chelsea Dandridge, Venkat Lakshmi, John D. Bolten, Raghavan Srinivasan
Evaluation of Satellite-Based Rainfall Estimates in the Lower Mekong River Basin (Southeast Asia). Remote. Sens. 11(22): 2709 (2019) - 2018
- [j13]Yong Chen, Gary W. Marek, Thomas H. Marek, David K. Brauer, Raghavan Srinivasan
Improving SWAT auto-irrigation functions for simulating agricultural irrigation management using long-term lysimeter field data. Environ. Model. Softw. 99: 25-38 (2018) - [j12]Ibrahim Nourein Mohammed
Improved Hydrological Decision Support System for the Lower Mekong River Basin Using Satellite-Based Earth Observations. Remote. Sens. 10(6): 885 (2018) - [j11]Joseph Spruce, John D. Bolten
Developing Land Use Land Cover Maps for the Lower Mekong Basin to Aid Hydrologic Modeling and Basin Planning. Remote. Sens. 10(12): 1910 (2018) - 2016
- [j10]Yihun T. Dile
Introducing a new open source GIS user interface for the SWAT model. Environ. Model. Softw. 85: 129-138 (2016) - 2015
- [j9]Jorge A. Guzman, Daniel N. Moriasi, Prasanna H. Gowda, Jean L. Steiner, Patrick J. Starks, Jeffrey G. Arnold, Raghavan Srinivasan
A model integration framework for linking SWAT and MODFLOW. Environ. Model. Softw. 73: 103-116 (2015) - [j8]Monireh Faramarzi
Setting up a hydrological model of Alberta: Data discrimination analyses prior to calibration. Environ. Model. Softw. 74: 48-65 (2015) - 2013
- [j7]Xuesong Zhang, Peter Beeson
Efficient multi-objective calibration of a computationally intensive hydrologic model with parallel computing software in Python. Environ. Model. Softw. 46: 208-218 (2013) - 2012
- [j6]Elham Rouholahnejad
A parallelization framework for calibration of hydrological models. Environ. Model. Softw. 31: 28-36 (2012) - [j5]Naresh Pai, Dharmendra Saraswat
Field_SWAT: A tool for mapping SWAT output to field boundaries. Comput. Geosci. 40: 175-184 (2012) - 2010
- [j4]Xuesong Zhang, Raghavan Srinivasan:
GIS-based spatial precipitation estimation using next generation radar and raingauge data. Environ. Model. Softw. 25(12): 1781-1788 (2010)
2000 – 2009
- 2006
- [j3]C. Santhi, Raghavan Srinivasan, Jeffrey G. Arnold, Jimmy R. Williams:
A modeling approach to evaluate the impacts of water quality management plans implemented in a watershed in Texas. Environ. Model. Softw. 21(8): 1141-1157 (2006) - 2004
- [j2]Mauro Di Luzio, Raghavan Srinivasan, Jeffrey G. Arnold:
A GIS-Coupled Hydrological Model System for the Watershed Assessment of Agricultural Nonpoint and Point Sources of Pollution. Trans. GIS 8(1): 113-136 (2004) - 2002
- [j1]Pei-yu Chen, Raghavan Srinivasan, Gunar Fedosejevs, Alma Delia Báez-González
Assessment of NDVI Composites Using Merged NOAA-14 and NOAA-15 AVHRR Data. Ann. GIS 8(1): 31-38 (2002)
Coauthor Index
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