scholarly journals Integrated hydrologic model of Pajaro Valley, Santa Cruz and Monterey Counties, California

2014 ◽  
Author(s):  
Randall T. Hanson ◽  
Wolfgang Schmid ◽  
Claudia C. Faunt ◽  
Jonathan Lear ◽  
Brian Lockwood
Keyword(s):  
Hydrologic Model ◽  
Santa Cruz ◽  
Integrated Hydrologic Model

scholarly journals Determining the impact of a severe dry to wet transition on watershed hydrodynamics in California, USA with an integrated hydrologic model

2020 ◽  
Vol 580 ◽  
pp. 124358 ◽  
Author(s):  
Fadji Z. Maina ◽  
Erica R. Siirila-Woodburn ◽  
Michelle Newcomer ◽  
Zexuan Xu ◽  
Carl Steefel
Keyword(s):  
Hydrologic Model ◽  
Integrated Hydrologic Model ◽  
The Impact

scholarly journals Assessing the impact of model spin-up on surface water-groundwater interactions using an integrated hydrologic model

2014 ◽  
Vol 50 (3) ◽  
pp. 2636-2656 ◽  
Author(s):  
Hoori Ajami ◽  
Matthew F. McCabe ◽  
Jason P. Evans ◽  
Simon Stisen
Keyword(s):  
Surface Water ◽  
Hydrologic Model ◽  
Integrated Hydrologic Model ◽  
The Impact

scholarly journals Assessment of the Timing of Daily Peak Streamflow during the Melt Season in a Snow-Dominated Watershed

2016 ◽  
Vol 17 (8) ◽  
pp. 2225-2244 ◽  
Author(s):  
Xing Chen ◽  
Mukesh Kumar ◽  
Rui Wang ◽  
Adam Winstral ◽  
Danny Marks
Keyword(s):  
Water Flux ◽  
Subsurface Flow ◽  
Hydrologic Model ◽  
Daily Streamflow ◽  
Penn State ◽  
Integrated Hydrologic Model ◽  
Interseasonal Variability ◽  
Peak Streamflow ◽  
Surface And Subsurface Flow ◽  
Temporal Shifts

Abstract Previous studies have shown that gauge-observed daily streamflow peak times (DPTs) during spring snowmelt can exhibit distinct temporal shifts through the season. These shifts have been attributed to three processes: 1) melt flux translation through the snowpack or percolation, 2) surface and subsurface flow of melt from the base of snowpacks to streams, and 3) translation of water flux in the streams to stream gauging stations. The goal of this study is to evaluate and quantify how these processes affect observed DPTs variations at the Reynolds Mountain East (RME) research catchment in southwest Idaho, United States. To accomplish this goal, DPTs were simulated for the RME catchment over a period of 25 water years using a modified snowmelt model, iSnobal, and a hydrology model, the Penn State Integrated Hydrologic Model (PIHM). The influence of each controlling process was then evaluated by simulating the DPT with and without the process under consideration. Both intra- and interseasonal variability in DPTs were evaluated. Results indicate that the magnitude of DPTs is dominantly influenced by subsurface flow, whereas the temporal shifts within a season are primarily controlled by percolation through snow. In addition to the three processes previously identified in the literature, processes governing the snowpack ripening time are identified as additionally influencing DPT variability. Results also indicate that the relative dominance of each control varies through the melt season and between wet and dry years. The results could be used for supporting DPTs prediction efforts and for prioritization of observables for DPT determination.

scholarly journals Assessing Groundwater Withdrawal Sustainability in the Mexican Portion of the Transboundary Santa Cruz River Aquifer

Water ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 233
Author(s):  
Elia M. Tapia-Villaseñor ◽  
Eylon Shamir ◽  
Mary-Belle Cruz-Ayala ◽  
Sharon B. Megdal
Keyword(s):  
The United States ◽  
Hydrologic Model ◽  
Border Region ◽  
Groundwater Withdrawal ◽  
Water Withdrawal ◽  
Balance Model ◽  
Santa Cruz ◽  
Precipitation Record ◽  
Santa Cruz River ◽  
The Impact

The impact of climate uncertainties is already evident in the border communities of the United States and Mexico. This semi-arid to arid border region has faced increased vulnerability to water scarcity, propelled by droughts, warming atmosphere, population growth, ecosystem sensitivity, and institutional asymmetries between the two countries. In this study, we assessed the annual water withdrawal, which is essential for maintaining long-term sustainable conditions in the Santa Cruz River Aquifer in Mexico, which is part of the U.S.–Mexico Transboundary Santa Cruz Aquifer. For this assessment, we developed a water balance model that accounts for the water fluxes into and out of the aquifer’s basin. A central component of this model is a hydrologic model that uses precipitation and evapotranspiration demand as input to simulate the streamflow into and out of the basin, natural recharge, soil moisture, and actual evapotranspiration. Based on the precipitation record for the period 1954–2020, we found that the amount of groundwater withdrawal that maintains sustainable conditions is 23.3 MCM/year. However, the record is clearly divided into two periods: a wet period, 1965–1993, in which the cumulative surplus in the basin reached ~380 MCM by 1993, and a dry period, 1994–2020, in which the cumulative surplus had been completely depleted. Looking at a balanced annual groundwater withdrawal for a moving average of 20-year intervals, we found the sustainable groundwater withdrawal to decline from a maximum of 36.4 MCM/year in 1993 to less than 8 MCM/year in 2020. This study underscores the urgency for adjusted water resources management that considers the large inter-annual climate variability in the region.

scholarly journals Examining cross-scale influences of forcing resolutions in a hillslope-resolving, integrated hydrologic model

2020 ◽  
Author(s):  
Miguel A. Aguayo ◽  
Alejandro N. Flores ◽  
James P. McNamara ◽  
Hans-Peter Marshall ◽  
Jodi Mead
Keyword(s):  
Hydrologic Modeling ◽  
Snow Water Equivalent ◽  
Spatial Scales ◽  
Water Storage ◽  
Hydrologic Model ◽  
Atmospheric Forcing ◽  
Hydrologic Models ◽  
Snow Water ◽  
Integrated Hydrologic Model ◽  
The Impact

Abstract. Water management in semiarid regions of the western United States requires accurate and timely knowledge of runoff generated by snowmelt. This information is used to plan reservoir releases for downstream users and hydrologic models play an important role in estimating the volume of snow stored in mountain watersheds that serve as source waters for downstream reservoirs. Physically based, integrated hydrologic models are used to develop spatiotemporally dynamic estimates of hydrologic states and fluxes based on understanding of the underlying biophysics of hydrologic response. Yet this class of models are associated with many issues that give rise to significant uncertainties in key hydrologic variables of interest like snow water storage and streamflow. Underlying sources of uncertainty include difficulties in parameterizing processes associated with nonlinearities of some processes, as well as from the large variability in the characteristic spatial and temporal scale of atmospheric forcing and land-surface water and energy balance and groundwater processes. Scale issues, in particular, can introduce systematic biases in integrated atmospheric and hydrologic modeling. Reconciling these discrepancies while maintaining computational tractability remains a fundamental challenge in integrated hydrologic modeling. Here we investigate the hydrologic impact of discrepancies between distributed meteorological forcing data exhibiting a range of spatial scales consistent with a variety of numerical weather prediction models when used to force an integrated hydrologic model associated with a corresponding range of spatial resolutions characteristic of distributed hydrologic modeling. To achieve this, we design and conduct a total of twelve numerical modeling experiments that seek to quantify the impact of applied resolution of atmospheric forcings on simulated hillslope-scale hydrologic state variables. The experiments are arranged in such way to assess the impact of four different atmospheric forcing resolutions (i.e., interpolated 30 m, 1 km, 3 km and 9 km) on two hydrologic variables, snow water equivalent and soil water storage, arranged in three hydrologic spatial resolution (i.e., 30 m, 90 m and 250 m). Results show spatial patterns in snow water equivalent driven by atmospheric forcing in hillslope-scale simulations and patterns mostly driven by topographical characteristics (i.e., slope and aspect) on coarser simulations. Similar patterns are observed in soil water storage however, in addition to that, large errors are encountered primarily in riparian areas of the watershed on coarser simulations. The Weather Research Forecasting (WRF) model is used to develop the environmental forcing variables required as input to the integrated hydrologic model. WRF is an open source, community supported coupled land-atmosphere model capable of capturing spatial scales that permit convection. The integrated hydrologic modeling framework used in this work coincides with the ParFlow open-source surface-subsurface hydrology model. This work has important implications for the use of atmospheric and integrated hydrologic models in remote and ungauged areas. In particular, this work has potential ramifications for the design and development of observing system simulation experiments (OSSEs) in complex and snow-dominated landscapes. OSSEs are critical in constraining the performance characteristics of Earth-observing satellites.

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