Applying the SAC-SMA hydrologic model to a tropical watershed in Brazil

AbstractUncertainties in hydrologic model outputs can arise for many reasons such as structural, parametric and input uncertainty. Identification of the sources of uncertainties and the quantification of their impacts on model results are important to appropriately reproduce hydrodynamic processes in karst aquifers and to support decision-making. The present study investigates the time-dependent relevance of model input uncertainties, defined as the conceptual uncertainties affecting the representation and parameterization of processes relevant for groundwater recharge, i.e. interception, evapotranspiration and snow dynamic, on the lumped karst model LuKARS. A total of nine different models are applied, three to compute interception (DVWK, Gash and Liu), three to compute evapotranspiration (Thornthwaite, Hamon and Oudin) and three to compute snow processes (Martinec, Girons Lopez and Magnusson). All the input model combinations are tested for the case study of the Kerschbaum spring in Austria. The model parameters are kept constant for all combinations. While parametric uncertainties computed for the same model in previous studies do not show pronounced temporal variations, the results of the present work show that input uncertainties are seasonally varying. Moreover, the input uncertainties of evapotranspiration and snowmelt are higher than the interception uncertainties. The results show that the importance of a specific process for groundwater recharge can be estimated from the respective input uncertainties. These findings have practical implications as they can guide researchers to obtain relevant field data to improve the representation of different processes in lumped parameter models and to support model calibration.

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Initial abstraction ratio and Curve Number estimation using rainfall and runoff data from a tropical watershed

RBRH ◽

10.1590/2318-0331.241920170199 ◽

2019 ◽

Vol 24 ◽

Cited By ~ 2

Author(s):

Luiz Claudio Galvão do Valle Junior ◽

Dulce Buchala Bicca Rodrigues ◽

Paulo Tarso Sanches de Oliveira

Keyword(s):

Conversion Factor ◽

Poor Performance ◽

Curve Number ◽

Storm Events ◽

Rainfall Runoff ◽

Initial Abstraction ◽

Rainfall Depth ◽

Standard Value ◽

Tropical Watershed ◽

Runoff Events

ABSTRACT The Curve Number (CN) method is extensively used for predict surface runoff from storm events. However, remain some uncertainties in the method, such as in the use of an initial abstraction (λ) standard value of 0.2 and on the choice of the most suitable CN values. Here, we compute λ and CN values using rainfall and runoff data to a rural basin located in Midwestern Brazil. We used 30 observed rainfall-runoff events with rainfall depth greater than 25 mm to derive associated CN values using five statistical methods. We noted λ values ranging from 0.005 to 0.455, with a median of 0.045, suggesting the use of λ = 0.05 instead of 0.2. We found a S0.2 to S0.05 conversion factor of 2.865. We also found negative values of Nash-Sutcliffe Efficiency (to the estimated and observed runoff). Therefore, our findings indicated that the CN method was not suitable to estimate runoff in the studied basin. This poor performance suggests that the runoff mechanisms in the studied area are dominated by subsurface stormflow.

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Evaluation of a Distributed Streamflow Forecast Model at Multiple Watershed Scales

Water ◽

10.3390/w12051279 ◽

2020 ◽

Vol 12 (5) ◽

pp. 1279

Author(s):

Tyler Madsen ◽

Kristie Franz ◽

Terri Hogue

Keyword(s):

Local Population ◽

Model Performance ◽

Forecast Model ◽

Hydrologic Model ◽

Laboratory Research ◽

Discharge Data ◽

Distributed Hydrologic Model ◽

Verification Period ◽

Silver Spring

Demand for reliable estimates of streamflow has increased as society becomes more susceptible to climatic extremes such as droughts and flooding, especially at small scales where local population centers and infrastructure can be affected by rapidly occurring events. In the current study, the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) (NOAA/NWS, Silver Spring, MD, USA) was used to explore the accuracy of a distributed hydrologic model to simulate discharge at watershed scales ranging from 20 to 2500 km2. The model was calibrated and validated using observed discharge data at the basin outlets, and discharge at uncalibrated subbasin locations was evaluated. Two precipitation products with nominal spatial resolutions of 12.5 km and 4 km were tested to characterize the role of input resolution on the discharge simulations. In general, model performance decreased as basin size decreased. When sub-basin area was less than 250 km2 or 20–40% of the total watershed area, model performance dropped below the defined acceptable levels. Simulations forced with the lower resolution precipitation product had better model evaluation statistics; for example, the Nash–Sutcliffe efficiency (NSE) scores ranged from 0.50 to 0.67 for the verification period for basin outlets, compared to scores that ranged from 0.33 to 0.52 for the higher spatial resolution forcing.

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The Assessment of Urbanization Effect and Sustainable Drainage Solutions on Flood Hazard by GIS

Sustainability ◽

10.3390/su13042293 ◽

2021 ◽

Vol 13 (4) ◽

pp. 2293

Author(s):

Seda Ertan ◽

Rahmi Nurhan Çelik

Keyword(s):

Information System ◽

Geographic Information System ◽

Green Infrastructure ◽

Evaluation System ◽

Flood Hazard ◽

Green Roof ◽

Geographic Information ◽

Hydrologic Model ◽

Land Use Patterns ◽

Urbanization Effect

Rapid and uncontrolled changes in land use patterns due to urbanization negatively affect urban rainfall-runoff processes and flood hazard. In this study, a method that included different sustainable drainage solutions, such as green infrastructure (GI) usage for flood hazard mitigation with various scenarios on a geographic information system (GIS) platform within a 1653 ha catchment of the Kağıthane Stream in İstanbul, Turkey is presented. Developed scenarios are as follows: scenario one (SN1) is the current situation; scenario two (SN2) used green roof application for buildings and a permeable surface for roads; scenario three (SN3) used only green roof application for buildings; scenario four (SN4) used a rainwater barrel for collecting roof water, a swale canal for collecting road water, and added additional structures to open areas to observe urbanization; scenario five (SN5) considered multiple GI implementations; and scenario six (SN6) considered full urbanization. The results indicate that greener infrastructure implementation provides benefits in reducing both the runoff coefficient and the peak flowrate, and the flood inundation area and number of structures affected by flood risk were decreased. The integrated evaluation system, which consisted of the geographic information system and the assessment of the 1D HEC-RAS hydrologic model, was applied to evaluate the GI usage and flood mitigation.

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Analyzing the Variability of Remote Sensing and Hydrologic Model Evapotranspiration Products in a Watershed in Michigan

JAWRA Journal of the American Water Resources Association ◽

10.1111/1752-1688.12849 ◽

2020 ◽

Vol 56 (4) ◽

pp. 738-755

Author(s):

Matthew R. Herman ◽

A. Pouyan Nejadhashemi ◽

Juan Sebastian Hernandez‐Suarez ◽

Ali M. Sadeghi

Keyword(s):

Remote Sensing ◽

Hydrologic Model

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