@article{singh_sinha_sankarasubramanian_2015, title={Impacts of near-term climate change and population growth on within-year reservoir systems}, volume={141}, number={6}, journal={Journal of Water Resources Planning and Management}, author={Singh, H. and Sinha, T. and Sankarasubramanian, A.}, year={2015} }
 @article{li_sankarasubramanian_ranjithan_sinha_2015, title={Role of multimodel combination and data assimilation in improving streamflow prediction over multiple time scales}, volume={30}, ISSN={1436-3240 1436-3259}, url={http://dx.doi.org/10.1007/s00477-015-1158-6}, DOI={10.1007/s00477-015-1158-6}, number={8}, journal={Stochastic Environmental Research and Risk Assessment}, publisher={Springer Science and Business Media LLC}, author={Li, Weihua and Sankarasubramanian, A. and Ranjithan, R. S. and Sinha, Tushar}, year={2015}, month={Sep}, pages={2255–2269} }
 @article{sinha_sankarasubramanian_mazrooei_2014, title={Decomposition of Sources of Errors in Monthly to Seasonal Streamflow Forecasts in a Rainfall-Runoff Regime}, volume={15}, ISSN={["1525-7541"]}, DOI={10.1175/jhm-d-13-0155.1}, abstractNote={Abstract
               Despite considerable progress in developing real-time climate forecasts, most studies have evaluated the potential in seasonal streamflow forecasting based on ensemble streamflow prediction (ESP) methods, utilizing only climatological forcings while ignoring general circulation model (GCM)-based climate forecasts. The primary limitation in using GCM forecasts is their coarse resolution, which requires spatiotemporal downscaling to implement land surface models. Consequently, multiple sources of errors are introduced in developing real-time streamflow forecasts utilizing GCM forecasts. A set of error decomposition metrics is provided to address the following questions: 1) How are errors in monthly streamflow forecasts attributed to various sources such as temporal disaggregation, spatial downscaling, imprecise initial hydrologic conditions (IHCs), climatological forcings, and imprecise forecasts? and 2) How do these errors propagate with lead time over different seasons? A calibrated Variable Infiltration Capacity model is used over the Apalachicola River at Chattahoochee in the southeastern United States. The model is forced with a combination of daily precipitation forcings (temporally disaggregated observed precipitation, spatially downscaled and temporally disaggregated observed precipitation, ESP, ECHAM4.5 forecasts, and observed) and IHCs [simulated and climatological ensemble reverse ESP (RESP)] but with observed air temperature and wind speed at ⅛° resolution. Then, errors in forecasting monthly streamflow at up to a 3-month lead time are decomposed by comparing the forecasted streamflow to simulated streamflow under observed forcings. Results indicate that the errors due to temporal disaggregation are much higher than the spatial downscaling errors. During winter and early spring, the increasing order of errors at a 1-month lead time is spatial downscaling, model, temporal disaggregation, RESP, large-scale precipitation forecasts, and ESP.}, number={6}, journal={JOURNAL OF HYDROMETEOROLOGY}, author={Sinha, Tushar and Sankarasubramanian, A. and Mazrooei, Amirhossein}, year={2014}, month={Dec}, pages={2470–2483} }
 @article{oh_sinha_sankarasubramanian_2014, title={The role of retrospective weather forecasts in developing daily forecasts of nutrient loadings over the southeast US}, volume={18}, number={8}, journal={Hydrology and Earth System Sciences}, author={Oh, J. and Sinha, T. and Sankarasubramanian, A.}, year={2014}, pages={2885–2898} }
 @article{sinha_arumugam_2013, title={Role of climate forecasts and initial conditions in developing streamflow and soil moisture forecasts in a rainfall-runoff regime}, volume={17}, journal={Hydrology and Earth System Sciences}, author={Sinha, T. and Arumugam, S.}, year={2013}, pages={721–733} }
 @article{sabo_bestgen_graf_sinha_wohl_2012, title={Dams in the Cadillac Desert: downstream effects in a geomorphic context}, volume={1249}, journal={Year in ecology and conservation biology}, author={Sabo, J. L. and Bestgen, K. and Graf, W. and Sinha, T. and Wohl, E. E.}, year={2012}, pages={227–246} }
 @article{sinha_cherkauer_2010, title={Impacts of future climate change on soil frost
in the midwestern United States}, volume={115}, journal={Journal of Geophysical Research. Atmospheres (Online)}, author={Sinha, T. and Cherkauer, K. A}, year={2010}, pages={1–16} }
 @article{sabo_sinha_bowling_schoups_wallender_campana_cherkauer_fuller_graf_hopmans_et al._2010, title={Reclaiming sustainable watersheds in the Cadillac Desert}, volume={107}, number={50}, journal={Proceedings of the National Academy of Sciences of the United States of America}, author={Sabo, J. L. and Sinha, T. and Bowling, L. C. and Schoups, G. H. W. and Wallender, W. W. and Campana, M. E. and Cherkauer, K. A. and Fuller, P. L. and Graf, W. L. and Hopmans, J. W. and et al.}, year={2010}, pages={21263–21269} }
 @article{graf_wohl_sinha_sabo_2010, title={Sedimentation and sustainability of western American reservoirs}, volume={46}, journal={Water Resources Research}, author={Graf, W. L. and Wohl, E. and Sinha, T. and Sabo, J. L.}, year={2010} }
 @article{sinha_cherkauer_2008, title={Time Series Analysis of Soil Freeze and Thaw Processes in Indiana}, volume={9}, ISSN={["1525-7541"]}, DOI={10.1175/2008jhm934.1}, abstractNote={Abstract
               Seasonal cycles of freezing and thawing influence surface energy and water cycle fluxes. Specifically, soil frost can lead to the reduction in infiltration and an increase in runoff response, resulting in a greater potential for soil erosion. An increase in the number of soil freeze–thaw cycles may reduce soil compaction, which could affect various hydrologic processes. In this study, the authors test for the presence of significant trends in soil freeze–thaw cycles and soil temperatures at several depths and compare these with other climatic variables including air temperature, snowfall, snow cover, and precipitation. Data for the study were obtained for three research stations located in northern, central, and southern Indiana that have collected soil temperature observations since 1966. After screening for significant autocorrelations, testing for trends is conducted at a significance level of 5% using Mann–Kendall’s test. Observations from 1967 to 2006 indicate that air temperatures during the cold season are increasing at all three locations, but there is no significant change in seasonal and annual average precipitation. At the central and southern Indiana sites, soil temperatures are generally warming under a bare soil surface, with significant reductions in the number of days with soil frost and freeze–thaw cycles for some depths. Meanwhile, 5-cm soils at the northernmost site are experiencing significant decreases in cold season temperatures, as an observed decrease in annual snowfall at the site is counteracting the increase in air temperature. Seasonal mean maximum soil temperatures under grass cover are increasing at the southernmost site; however, at the central site, it appears that seasonal minimum soil temperatures are decreasing and the number of freeze–thaw cycles is increasing.}, number={5}, journal={JOURNAL OF HYDROMETEOROLOGY}, author={Sinha, Tushar and Cherkauer, Keith A.}, year={2008}, month={Oct}, pages={936–950} }