Seshadri Rajagopal

Scenario development for water resources planning and watershed management: Methodology and semi-arid region case study

Utilizing the scenario development framework from Mahmoud et al. (2009), a set of scenarios were developed for and applied in the Verde River Watershed in Arizona, USA. Through a scenario definition exercise, three dimensions of future change with respective axis extremes were identified: climate change (periodic droughts vs. sustained drought), demographics (water-conservative population vs. water-consumptive population), and the economy (booming economy vs. poor economy). In addition to the various combinations of dimension extremes, each scenario was given a unique event or theme that was characteristic of the combination of dimension extremes it possessed. The scenarios were then fleshed out into narrative forms that expanded on the details of each scenarios internal temporal evolution. The scenarios were analyzed by a water supply and demand model that was specifically constructed for their simulation. Following the analysis of scenario results, assessment narratives were provided to outline the impact of each scenario on the Verde River Watershed and management operations in that basin.

Characterizing the water extremes of the new century in the US South-west: A comprehensive assessment from state-of-the-art climate model projections

The impact of climate change scenarios in the hydrology of the Verde River basin (Arizona) is analyzed using an ensemble of downscaled climate model results, SPI analysis, and two hydrologic models of different complexity. To assess model uncertainty, 47 ensemble members combining simulations from 16 global climate models and 3 emission scenarios were used to provide an uncertainty envelope in the hydrologic variables. The analysis shows that simple lumped models and more complex distributed runoff models can yield similar results. Results show that under all scenarios, the distribution functions of hydrologic states will shift towards lower values and droughts will progressively become more frequent, longer and more intense.

Annually‐resolved late holocene paleohydrology of the southern Sierra Nevada and Tulare Lake, California

Here we present 2000 year long, annually resolved records of streamflow for the Kings, Kaweah, Tule, and Kern Rivers in the southwestern Sierra Nevada of California and consequent lake-level fluctuations at Tulare Lake in the southern San Joaquin Valley. The integrated approach of using moisture-sensitive tree ring records from the Living Blended Drought Atlas to reconstruct annual discharge and then routing this discharge to an annual Tulare Lake water balance model highlights the differences between these two types of paleoclimate records, even when subject to the same forcing factors. The reconstructed streamflow in the southern Sierra responded to yearly changes in precipitation and expressed a strong periodicity in the 2–8 year range over most of the reconstruction. The storage capacity of Tulare Lake caused it to fluctuate more slowly, masking the 2–8 year streamflow periodicity and instead expressing a strong periodicity in the 32–64 year range over much of the record. Although there have been longer droughts, the 2015 water year represents the driest in the last 2015 years and the 2012–2015 drought represents the driest 4 year period in the record. Under natural conditions, simulated Tulare Lake levels would now be at about 60 m, which is not as low as what occurred multiple times over the last 2000 years. This long-term perspective of fluctuations in climate and water supply suggests that different drought scenarios that vary in terms of severity and duration can produce similar lake-level responses in closed lake basins.

Relative Humidity Has Uneven Effects on Shifts From Snow to Rain Over the Western U.S.

Predicting the phase of precipitation is fundamental to water supply and hazard forecasting.Phaseprediction methods (PPMs) are used to predict snow fraction, or the ratio of snowfall to total precipitation. Common temperature-based regression (Dai method) and threshold at freezing (0 C)PPMs had comparable accuracyto a humidity-based PPM (TRHmethod)using 6- and 24-hour observations. Using a daily climate dataset from 1980-2015,the TRHmethodestimates14% and 6% greater precipitation-weighted snow fraction than the 0Cand Dai methods, respectively. The TRH method predicts four times less area with declining snow fraction than the Dai method (2.1% and 8.1% of the study domain, respectively) from 1980-2015, with the largest differences in the Cascade and Sierra Nevada mountains and Southwestern U.S. Future RCP8.5 projections suggest warming temperatures of 4.2°C and declining relative humidity of 1% over the 21st century. The TRHmethod predicts a smaller reduction in snow fraction than temperature-only PPMs by 2100, consistent withlower humidity bufferingdeclines insnow fraction caused byregional warming.

Physical Mechanisms Related to Climate-Induced Drying of Two Semiarid Watersheds in the Southwestern United States

AbstractWater managers across the United States face the need to make informed policy decisions regarding long-term impacts of climate change on water resources. To provide a scientifically informed basis for this, the evolution of important components of the basin-scale water balance through the end of the twenty-first century is estimated. Bias-corrected and spatially downscaled climate projections, from phase 3 of the Coupled Model Intercomparison Project (CMIP3) of the World Climate Research Programme, were used to drive a spatially distributed Variable Infiltration Capacity (VIC) model of hydrologic processes in the Salt–Verde basin in the southwestern United States. From the suite of CMIP3 models, the authors select a five-model subset, including three that best reproduce the historical climatology for the study region, plus two others to represent wetter and drier than model average conditions, so as to represent the range of GCM prediction uncertainty. For each GCM, data for three emission scenari...