Spatially distributed long-term hydrologic simulation using a continuous SCS CN method-based hybrid hydrologic model

2018 ◽  
Vol 32 (7) ◽  
pp. 904-922 ◽  
Author(s):  
Younghyun Cho ◽  
Bernard A. Engel
Keyword(s):  
Hydrologic Model ◽  
Hydrologic Simulation ◽  
Spatially Distributed ◽  
Scs Cn

scholarly journals NEXRAD Quantitative Precipitation Estimations for Hydrologic Simulation Using a Hybrid Hydrologic Model

2016 ◽  
Vol 18 (1) ◽  
pp. 25-47 ◽  
Author(s):  
Younghyun Cho ◽  
Bernard A. Engel
Keyword(s):  
Model Simulation ◽  
Model Performance ◽  
Stage Iv ◽  
Rain Gauge ◽  
Hydrologic Model ◽  
Feature Model ◽  
Coefficient Of Determination ◽  
Hydrologic Simulation ◽  
Direct Runoff ◽  
Spatially Distributed

Abstract A hybrid hydrologic model (lumped conceptual and distributed feature model), Distributed-Clark, is introduced to perform hydrologic simulations using spatially distributed NEXRAD quantitative precipitation estimations (QPEs). In Distributed-Clark, spatially distributed excess rainfall estimated with the Soil Conservation Service (SCS) curve number method and a GIS-based set of separated unit hydrographs are utilized to calculate a direct runoff flow hydrograph. This simple approach using few modeling parameters reduces calibration complexity relative to physically based distributed (PBD) models by only focusing on integrated flow estimation at watershed outlets. Case studies assessed the quality of NEXRAD stage IV QPEs for hydrologic simulation compared to gauge-only analyses. NEXRAD data validation against rain gauge observations and performance evaluation with model simulation result comparisons for inputs of spatially distributed stage IV and spatially averaged gauged data for four study watersheds were conducted. Results show significant differences in NEXRAD QPEs and gauged rainfall amounts, with NEXRAD data overestimated by 7.5% and 9.1% and underestimated by 15.0% and 11.4% accompanied by spatial variability. These differences affect model performance in hydrologic applications. Rainfall–runoff flow simulations using spatially distributed NEXRAD stage IV QPEs demonstrate relatively good fit [direct runoff: Nash–Sutcliffe efficiency ENS = 0.85, coefficient of determination R2 = 0.89, and percent bias (PBIAS) = 3.92%; streamflow: ENS = 0.91, R2 = 0.93, and PBIAS = 1.87%] against observed flow as well as better fit (ENS of 3.7% and R2 of 6.0% increase in direct runoff) than spatially averaged gauged rainfall for the same model calibration approach, enabling improved estimates of flow volumes and peak rates that can be underestimated in hydrologic simulations for spatially averaged rainfall.

Long-term hydrologic simulation using SCS-CN-based improved soil moisture accounting procedure

2010 ◽  
Vol 25 (4) ◽  
pp. 561-579 ◽  
Author(s):  
Dilip G. Durbude ◽  
Manoj K. Jain ◽  
Surendra K. Mishra
Keyword(s):  
Soil Moisture ◽  
Hydrologic Simulation ◽  
Soil Moisture Accounting ◽  
Scs Cn ◽  
Accounting Procedure

Modifications to SCS-CN Method for Long-Term Hydrologic Simulation

2007 ◽  
Vol 133 (5) ◽  
pp. 475-486 ◽  
Author(s):  
K. Geetha ◽  
S. K. Mishra ◽  
T. I. Eldho ◽  
A. K. Rastogi ◽  
R. P. Pandey
Keyword(s):  
Hydrologic Simulation ◽  
Scs Cn

Discussion of “Modifications to SCS-CN Method for Long-Term Hydrologic Simulation” by K. Geetha, S. K. Mishra, T. I. Eldho, A. K. Rastogi, and R. P. Pandey

2010 ◽  
Vol 136 (6) ◽  
pp. 444-446 ◽  
Author(s):  
Donald E. Woodward ◽  
Claudia C. Hoeft ◽  
Richard H. Hawkins ◽  
Joe Van Mullem ◽  
Tim J. Ward
Keyword(s):  
Hydrologic Simulation ◽  
Scs Cn

scholarly journals CO2 dynamics and heterogeneity in a cave atmosphere: role of ventilation patterns and airflow pathways

2021 ◽  
Author(s):  
Lovel Kukuljan ◽  
Franci Gabrovšek ◽  
Matthew D. Covington ◽  
Vanessa E. Johnston
Keyword(s):  
Temporal Variations ◽  
Observation Point ◽  
Spatially Distributed ◽  
Combined Action ◽  
Karst Systems ◽  
The Relationship ◽  
Co2 Dynamics ◽  
Global Carbon

AbstractUnderstanding the dynamics and distribution of CO2 in the subsurface atmosphere of carbonate karst massifs provides important insights into dissolution and precipitation processes, the role of karst systems in the global carbon cycle, and the use of speleothems for paleoclimate reconstructions. We discuss long-term microclimatic observations in a passage of Postojna Cave, Slovenia, focusing on high spatial and temporal variations of pCO2. We show (1) that the airflow through the massif is determined by the combined action of the chimney effect and external winds and (2) that the relationship between the direction of the airflow, the geometry of the airflow pathways, and the position of the observation point explains the observed variations of pCO2. Namely, in the terminal chamber of the passage, the pCO2 is low and uniform during updraft, when outside air flows to the site through a system of large open galleries. When the airflow reverses direction to downdraft, the chamber is fed by inlets with diverse flow rates and pCO2, which enter via small conduits and fractures embedded in a CO2-rich vadose zone. If the spatial distribution of inlets and outlets produces minimal mixing between low and high pCO2 inflows, high and persistent gradients in pCO2 are formed. Such is the case in the chamber, where vertical gradients of up to 1000 ppm/m are observed during downdraft. The results presented in this work provide new insights into the dynamics and composition of the subsurface atmosphere and demonstrate the importance of long-term and spatially distributed observations.

scholarly journals Impacts of Polarimetric Radar Observations on Hydrologic Simulation

2010 ◽  
Vol 11 (3) ◽  
pp. 781-796 ◽  
Author(s):  
Jonathan J. Gourley ◽  
Scott E. Giangrande ◽  
Yang Hong ◽  
Zachary L. Flamig ◽  
Terry Schuur ◽  
...  
Keyword(s):  
Pearson Correlation ◽  
Extreme Rainfall ◽  
Rain Gauge ◽  
Hydrologic Model ◽  
Laboratory Research ◽  
Model Parameters ◽  
Polarimetric Radar ◽  
Storm Events ◽  
Hydrologic Simulation ◽  
Radar Observations

Abstract Rainfall estimated from the polarimetric prototype of the Weather Surveillance Radar-1988 Doppler [WSR-88D (KOUN)] was evaluated using a dense Micronet rain gauge network for nine events on the Ft. Cobb research watershed in Oklahoma. The operation of KOUN and its upgrade to dual polarization was completed by the National Severe Storms Laboratory. Storm events included an extreme rainfall case from Tropical Storm Erin that had a 100-yr return interval. Comparisons with collocated Micronet rain gauge measurements indicated all six rainfall algorithms that used polarimetric observations had lower root-mean-squared errors and higher Pearson correlation coefficients than the conventional algorithm that used reflectivity factor alone when considering all events combined. The reflectivity based relation R(Z) was the least biased with an event-combined normalized bias of −9%. The bias for R(Z), however, was found to vary significantly from case to case and as a function of rainfall intensity. This variability was attributed to different drop size distributions (DSDs) and the presence of hail. The synthetic polarimetric algorithm R(syn) had a large normalized bias of −31%, but this bias was found to be stationary. To evaluate whether polarimetric radar observations improve discharge simulation, recent advances in Markov Chain Monte Carlo simulation using the Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM) were used. This Bayesian approach infers the posterior probability density function of model parameters and output predictions, which allows us to quantify HL-RDHM uncertainty. Hydrologic simulations were compared to observed streamflow and also to simulations forced by rain gauge inputs. The hydrologic evaluation indicated that all polarimetric rainfall estimators outperformed the conventional R(Z) algorithm, but only after their long-term biases were identified and corrected.

scholarly journals How does water yield respond to mountain pine beetle infestation in a semiarid forest?

2021 ◽  
Vol 25 (9) ◽  
pp. 4681-4699
Author(s):  
Jianning Ren ◽  
Jennifer C. Adam ◽  
Jeffrey A. Hicke ◽  
Erin J. Hanan ◽  
Christina L. Tague ◽  
...  
Keyword(s):  
Mountain Pine Beetle ◽  
Tree Mortality ◽  
Hydrologic Model ◽  
Water Yield ◽  
Driving Mechanisms ◽  
Mountain Pine ◽  
Pine Beetle ◽  
Interannual Climate Variability ◽  
Hydrologic Responses

Abstract. Mountain pine beetle (MPB) outbreaks in the western United States result in widespread tree mortality, transforming forest structure within watersheds. While there is evidence that these changes can alter the timing and quantity of streamflow, there is substantial variation in both the magnitude and direction of hydrologic responses, and the climatic and environmental mechanisms driving this variation are not well understood. Herein, we coupled an eco-hydrologic model (RHESSys) with a beetle effects model and applied it to a semiarid watershed, Trail Creek, in the Bigwood River basin in central Idaho, USA, to examine how varying degrees of beetle-caused tree mortality influence water yield. Simulation results show that water yield during the first 15 years after beetle outbreak is controlled by interactions between interannual climate variability, the extent of vegetation mortality, and long-term aridity. During wet years, water yield after a beetle outbreak increased with greater tree mortality; this was driven by mortality-caused decreases in evapotranspiration. During dry years, water yield decreased at low-to-medium mortality but increased at high mortality. The mortality threshold for the direction of change was location specific. The change in water yield also varied spatially along aridity gradients during dry years. In wetter areas of the Trail Creek basin, post-outbreak water yield decreased at low mortality (driven by an increase in ground evaporation) and increased when vegetation mortality was greater than 40 % (driven by a decrease in canopy evaporation and transpiration). In contrast, in more water-limited areas, water yield typically decreased after beetle outbreaks, regardless of mortality level (although the driving mechanisms varied). Our findings highlight the complexity and variability of hydrologic responses and suggest that long-term (i.e., multi-decadal mean) aridity can be a useful indicator for the direction of water yield changes after a disturbance.

scholarly journals Ensemble long-term soil moisture forecast using hydrological modeling

RBRH ◽  
2020 ◽  
Vol 25 ◽  
Author(s):  
Bibiana Rodrigues Colossi ◽  
Carlos Eduardo Morelli Tucci
Keyword(s):  
Soil Moisture ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Computing Time ◽  
Ensemble Member ◽  
Lead Times ◽  
Hydrologic Simulation ◽  
The Mean ◽  
Group B

ABSTRACT Long-term soil moisture forecasting allows for better planning in sectors as agriculture. However, there are still few studies dedicated to estimate soil moisture for long lead times, which reflects the difficulties associated with this topic. An approach that could help improving these forecasts performance is to use ensemble predictions. In this study, a soil moisture forecast for lead times of one, three and six months in the Ijuí River Basin (Brazil) was developed using ensemble precipitation forecasts and hydrologic simulation. All ensemble members from three climatologic models were used to run the MGB hydrological model, generating 207 soil moisture forecasts, organized in groups: (A) for each model, the most frequent soil moisture interval predicted among the forecasts made with each ensemble member, (B) using each model’s mean precipitation, (C) considering a super-ensemble, and (D) the mean soil moisture interval predicted among group B forecasts. The results show that long-term soil moisture based on precipitation forecasts can be useful for identifying periods drier or wetter than the average for the studied region. Nevertheless, estimation of exact soil moisture values remains limited. Forecasts groups B and D performed similarly to groups A and C, and require less data management and computing time.

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