Raghavan Srinivasan

Global and Planetary Change · 2002–2017

A researcher in the Science corpus: 10 papers; trusts 32 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Global and Planetary Change — 28 citations into it; #5,688 of 10,225 by trust here, #6,088 by citations
• Water Science and Technology — 28 citations into it; #405 of 1,711 by trust here, #700 by citations
• Environmental Engineering — 22 citations into it; #2,738 of 5,479 by trust here, #2,361 by citations
• Ocean Engineering — 5 citations into it

Whom Raghavan Srinivasan trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Keith Beven
2. Hans-Martin Gutmann
3. Jing Yang
4. K. C. Abbaspour
5. Qingyun Duan
6. Jasper A. Vrugt
7. A. Binley
8. Adrian E. Raftery
9. George A. Kuczera
10. Bryan Tolson

Who trusts Raghavan Srinivasan overall

1. Saman Razavi
2. Samuel C. Zipper
3. Xuesong Zhang
4. M. Quintero
5. Philippe C. Baveye
6. Mahyat Shafapour Tehrany
7. Chen Wang

Papers from Raghavan Srinivasan's perspective

Ordered by how strongly the researchers Raghavan Srinivasan trusts endorse each paper. Same corpus, a different order for every researcher.

1. Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology
2. Effective and efficient global optimization for conceptual rainfall‐runoff models
3. The future of distributed models: model calibration and uncertainty prediction.
4. Towards a Bayesian total error analysis of conceptual rainfall-runoff models: Characterising model error using storm-dependent parameters
5. A manifesto for the equifinality thesis
6. Bayesian analysis of input uncertainty in hydrological modeling: 1. Theory
7. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence
8. Multi-model ensemble hydrologic prediction using Bayesian model averaging
9. Hydrological modelling of the Chaohe Basin in China: Statistical model formulation and Bayesian inference
10. Maximum likelihood Bayesian averaging of uncertain model predictions

Their papers

• Introduction to SWAT+, A Completely Restructured Version of the Soil and Water Assessment Tool (2017) — 473 citations
• Using the Soil and Water Assessment Tool (SWAT) to model ecosystem services: A systematic review (2016) — 305 citations
• Applications of the SWAT Model Special Section: Overview and Insights. (2014) — 589 citations
• Calibration and uncertainty analysis of the SWAT model using Genetic Algorithms and Bayesian Model Averaging (2009) — 230 citations
• Approximating SWAT Model Using Artificial Neural Network and Support Vector Machine 1 (2009) — 132 citations
• A modeling approach to evaluate the impacts of water quality management plans implemented in a watershed in Texas (2006) — 372 citations
• Estimation of managed loblolly pine stand age and density with Landsat ETM+ data (2006) — 71 citations
• Advances in the application of the SWAT model for water resources management (2005) — 334 citations
• Development and evaluation of Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) for agricultural drought monitoring (2005) — 804 citations
• Using Satellite and Field Data with Crop Growth Modeling to Monitor and Estimate Corn Yield in Mexico (2002) — 121 citations