scholarly journals On simulation improvement of the Noah_LSM by coupling with a hydrological model using a double-excess runoff production scheme in the GRAPES_Meso model

2017 ◽  
Vol 24 (3) ◽  
pp. 512-520 ◽  
Author(s):  
Lili Wang ◽  
Dehui Chen ◽  
Hongjun Bao ◽  
Ke Zhang
Keyword(s):  
Hydrological Model ◽  
Production Scheme ◽  
Runoff Production

scholarly journals Assessing the Sensitivity of SWMM to Variations in Hydrological and Hydraulic Parameters: A Case Study for the city of Istanbul

2016 ◽  
Vol 18 (4) ◽  
pp. 831-841 ◽  
Keyword(s):  
Land Use ◽  
Overland Flow ◽  
Hydrological Model ◽  
Management Model ◽  
Hydraulic Parameters ◽  
Storm Water Management Model ◽  
Parametric Sensitivity ◽  
The City ◽  
Runoff Production

<p>Overland flow is highly affected by increasing urbanization, and variations in land use and climatic variables, especially in the last few decades. This necessitates the development of modeling approaches for planning and management of catchments that play a significant role on water supply. The main objective of this study is to determine the effects of major hydrological and hydraulic parameters on runoff production in the Alibeyköy Reservoir catchment area in Istanbul. Storm Water Management Model (SWMM) is chosen to develop the catchment hydrological model and the model’s sensitivity is assessed based on the variations in eight major parameters of the model affecting runoff production. 55 years of time series precipitation data are used for model simulations. GIS-based maps including land use and land cover information are used to determine the imperviousness values required for SWMM. A one-at-a-time parametric sensitivity analysis is carried out to determine the most significant parameters affecting the model outcomes. Analysis results reveal that area of subcatchments, precipitation and conduit depth are the most significant parameters in SWMM affecting runoff production. Percent imperviousness and percent slope are the least significant parameters amongst other parameters influencing the output.</p>

Integrated Subsurface to Surface Modeling to Assess Reservoir Uncertainty Quantification to A Carbonate Reservoir

2020 ◽  
Author(s):  
A. Chaterine
Keyword(s):  
Uncertainty Quantification ◽  
Gas Production ◽  
Carbonate Reservoir ◽  
Production Volume ◽  
Production Forecast ◽  
Uncertainty Range ◽  
Field Development ◽  
Production Forecasting ◽  
Production Scheme ◽  
Rock Compressibility

This study accommodates subsurface uncertainties analysis and quantifies the effects on surface production volume to propose the optimal future field development. The problem of well productivity is sometimes only viewed from the surface components themselves, where in fact the subsurface component often has a significant effect on these production figures. In order to track the relationship between surface and subsurface, a model that integrates both must be created. The methods covered integrated asset modeling, probability forecasting, uncertainty quantification, sensitivity analysis, and optimization forecast. Subsurface uncertainties examined were : reservoir closure, regional segmentation, fluid contact, and SCAL properties. As the Integrated Asset Modeling is successfully conducted and a matched model is obtained for the gas-producing carbonate reservoir, highlights of the method are the following: 1) Up to ± 75% uncertainty range of reservoir parameters yields various production forecasting scenario using BHP control with the best case obtained is 335 BSCF of gas production and 254.4 MSTB of oil production, 2) SCAL properties and pseudo-faults are the most sensitive subsurface uncertainty that gives major impact to the production scheme, 3) EOS modeling and rock compressibility modeling must be evaluated seriously as those contribute significantly to condensate production and the field’s revenue, and 4) a proposed optimum production scenario for future development of the field with 151.6 BSCF gas and 414.4 MSTB oil that yields a total NPV of 218.7 MMUSD. The approach and methods implemented has been proven to result in more accurate production forecast and reduce the project cost as the effect of uncertainty reduction.

Estimation of Regional Parameters in a Macro Scale Hydrological Model

2001 ◽  
Vol 32 (3) ◽  
pp. 161-180 ◽  
Author(s):  
Kolbjørn Engeland ◽  
Lars Gottschalk ◽  
Lena Tallaksen
Keyword(s):  
Additional Data ◽  
Hydrological Model ◽  
Sampling Methods ◽  
Probability Distributions ◽  
Repeated Application ◽  
Landscape Characteristics ◽  
Time Period ◽  
Macro Scale ◽  
Model Element ◽  
Regular Sampling

Macro-scale hydrological modelling implies a repeated application of a model within an area using regional parameters. These parameters are based on climate and landscape characteristics, and they are used to calculate the water balance in ungauged areas. The regional parameters ought to be robust and not too dependent of the catchment and time period used for calibration. The ECOMAG model is applied for the NOPEX-region as a macro-scale hydrological model distributed on a 2×2 km2 grid. Each model element is assigned parameters according to soil and vegetation classes. A Bayesian methodology is followed. An objective function describing the fit between observed and simulated values is used to describe the likelihood of the parameters. Using Baye's theorem these likelihoods are used to update the probability distributions of the parameters using additional data, being it either an additional year of streamflow or an additional streamflow station. Two sampling methods are used, regular sampling and Metropolis-Hastings sampling. The results show that regional parameters exist according to some predefined criteria. The probability distribution of the parameters shows a decreasing variance as data from new catchments are used for updating. A few parameters do, however, not exhibit this property, and they are therefore not suitable in a regional context.

scholarly journals Modelling of the Discharge Response to Climate Change under RCP8.5 Scenario in the Alata River Basin (Mersin, SE Turkey)

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 483
Author(s):  
Ümit Yıldırım ◽  
Cüneyt Güler ◽  
Barış Önol ◽  
Michael Rode ◽  
Seifeddine Jomaa
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Hydrological Model ◽  
Baseline Period ◽  
Change Scenario ◽  
Climate Projections ◽  
Worst Case ◽  
Distributed Process ◽  
In The Beginning ◽  
Se Turkey

This study investigates the impacts of climate change on the hydrological response of a Mediterranean mesoscale catchment using a hydrological model. The effect of climate change on the discharge of the Alata River Basin in Mersin province (Turkey) was assessed under the worst-case climate change scenario (i.e., RCP8.5), using the semi-distributed, process-based hydrological model Hydrological Predictions for the Environment (HYPE). First, the model was evaluated temporally and spatially and has been shown to reproduce the measured discharge consistently. Second, the discharge was predicted under climate projections in three distinct future periods (i.e., 2021–2040, 2046–2065 and 2081–2100, reflecting the beginning, middle and end of the century, respectively). Climate change projections showed that the annual mean temperature in the Alata River Basin rises for the beginning, middle and end of the century, with about 1.35, 2.13 and 4.11 °C, respectively. Besides, the highest discharge timing seems to occur one month earlier (February instead of March) compared to the baseline period (2000–2011) in the beginning and middle of the century. The results show a decrease in precipitation and an increase in temperature in all future projections, resulting in more snowmelt and higher discharge generation in the beginning and middle of the century scenarios. However, at the end of the century, the discharge significantly decreased due to increased evapotranspiration and reduced snow depth in the upstream area. The findings of this study can help develop efficient climate change adaptation options in the Levant’s coastal areas.

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