scholarly journals Hydrologic Setting and Conceptual Hydrologic Model of the Walker River Basin, West-Central Nevada

2009 ◽  
Author(s):  
Thomas J. Lopes ◽  
Kip K. Allander
Keyword(s):  
River Basin ◽  
Hydrologic Model ◽  
West Central ◽  
Walker River

scholarly journals Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau

2016 ◽  
Author(s):  
Xiaomang Liu ◽  
Tiantian Yang ◽  
Koulin Hsu ◽  
Changming Liu ◽  
Soroosh Sorooshian
Keyword(s):  
Tibetan Plateau ◽  
River Basin ◽  
Yangtze River ◽  
Yellow River ◽  
Yangtze River Basin ◽  
Information Source ◽  
Hydrologic Model ◽  
The Tibetan Plateau ◽  
Climate Data ◽  
Streamflow Simulation

Abstract. On the Tibetan Plateau, the limited ground-based rainfall information owing to a harsh environment has brought great challenges to hydrological studies. Satellite-based rainfall products, which allow a better coverage than both radar network and rain gauges on the Tibetan Plateau, can be suitable observation alternatives for investigating the hydrological processes and climate change. In this study, a newly developed daily satellite-based precipitation product, termed Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR), is used as input of a hydrologic model to simulate streamflow in the upper Yellow and Yangtze River Basin on the Tibetan Plateau. The results show that the simulated streamflow using PERSIANN-CDR precipitation is closer to observation than that using limited gauge-based precipitation interpolation in the upper Yangtze River Basin. The simulated streamflow using gauge-based precipitation are higher than the streamflow observation during the wet season. In the upper Yellow River Basin, PERSIANN-CDR precipitation and gauge-based precipitation have similar good performance in simulating streamflow. The evaluation of streamflow simulation capability in this study partly indicates that PERSIANN-CDR rainfall product has good potentials to be a reliable dataset and an alternative information source besides the sparse gauge network for conducting long term hydrological and climate studies on the Tibetan Plateau.

scholarly journals Comparing bias correction methods in downscaling meteorological variables for hydrologic impact study in an arid area in China

2014 ◽  
Vol 11 (11) ◽  
pp. 12659-12696 ◽  
Author(s):  
G. H. Fang ◽  
J. Yang ◽  
Y. N. Chen ◽  
C. Zammit
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Bias Correction ◽  
Meteorological Data ◽  
Hydrologic Model ◽  
Temperature Correction ◽  
Arid Area ◽  
Tarim River ◽  
Tarim River Basin ◽  
Impact Study

Abstract. Water resources are essential to the ecosystem and social economy in the desert and oasis of the arid Tarim River Basin, Northwest China, and expected to be vulnerable to climate change. Regional Climate Models (RCM) have been proved to provide more reliable results for regional impact study of climate change (e.g. on water resources) than GCM models. However, it is still necessary to apply bias correction before they are used for water resources research due to often considerable biases. In this paper, after a sensitivity analysis on input meteorological variables based on Sobol' method, we compared five precipitation correction methods and three temperature correction methods to the output of a RCM model with its application to the Kaidu River Basin, one of the headwaters of the Tarim River Basin. Precipitation correction methods include Linear Scaling (LS), LOCal Intensity scaling (LOCI), Power Transformation (PT), Distribution Mapping (DM) and Quantile Mapping (QM); and temperature correction methods include LS, VARIance scaling (VARI) and DM. These corrected precipitation and temperature were compared to the observed meteorological data, and then their impacts on streamflow were also compared by driving a distributed hydrologic model. The results show: (1) precipitation, temperature, solar radiation are sensitivity to streamflow while relative humidity and wind speed are not, (2) raw RCM simulations are heavily biased from observed meteorological data, which results in biases in the simulated streamflows, and all bias correction methods effectively improved theses simulations, (3) for precipitation, PT and QM methods performed equally best in correcting the frequency-based indices (e.g. SD, percentile values) while LOCI method performed best in terms of the time series based indices (e.g. Nash–Sutcliffe coefficient, R2), (4) for temperature, all bias correction methods performed equally well in correcting raw temperature. (5) For simulated streamflow, precipitation correction methods have more significant influence than temperature correction methods and the performances of streamflow simulations are consistent with these of corrected precipitation, i.e. PT and QM methods performed equally best in correcting flow duration curve and peak flow while LOCI method performed best in terms of the time series based indices. The case study is for an arid area in China based on a specific RCM and hydrologic model, but the methodology and some results can be applied to other area and other models.

scholarly journals Spatial disaggregation of bias-corrected GCM precipitation for improved hydrologic simulation: Ping River Basin, Thailand

2007 ◽  
Vol 11 (4) ◽  
pp. 1373-1390 ◽  
Author(s):  
D. Sharma ◽  
A. Das Gupta ◽  
M. S. Babel
Keyword(s):  
River Basin ◽  
Bias Correction ◽  
Hydrological Modeling ◽  
Correction Method ◽  
Hydrologic Model ◽  
Global Climate Models ◽  
Model Parameters ◽  
Bias Correction Method ◽  
Spatial Disaggregation ◽  
Grid Nodes

Abstract. Global Climate Models (GCMs) precipitation scenarios are often characterized by biases and coarse resolution that limit their direct application for basin level hydrological modeling. Bias-correction and spatial disaggregation methods are employed to improve the quality of ECHAM4/OPYC SRES A2 and B2 precipitation for the Ping River Basin in Thailand. Bias-correction method, based on gamma-gamma transformation, is applied to improve the frequency and amount of raw GCM precipitation at the grid nodes. Spatial disaggregation model parameters (β,σ2), based on multiplicative random cascade theory, are estimated using Mandelbrot-Kahane-Peyriere (MKP) function at q=1 for each month. Bias-correction method exhibits ability of reducing biases from the frequency and amount when compared with the computed frequency and amount at grid nodes based on spatially interpolated observed rainfall data. Spatial disaggregation model satisfactorily reproduces the observed trend and variation of average rainfall amount except during heavy rainfall events with certain degree of spatial and temporal variations. Finally, the hydrologic model, HEC-HMS, is applied to simulate the observed runoff for upper Ping River Basin based on the modified GCM precipitation scenarios and the raw GCM precipitation. Precipitation scenario developed with bias-correction and disaggregation provides an improved reproduction of basin level runoff observations.

Integrated numerical model for irrigated area water resources management

2019 ◽  
Vol 11 (4) ◽  
pp. 980-991 ◽  
Author(s):  
Aidi Huo ◽  
Xiaofan Wang ◽  
Yan Liang ◽  
Cheng Jiang ◽  
Xiaolu Zheng
Keyword(s):  
River Basin ◽  
Water Resource Management ◽  
Assessment Tool ◽  
Swat Model ◽  
Hydrologic Model ◽  
Heihe River Basin ◽  
Irrigation District ◽  
Heihe River ◽  
Model Parameters ◽  
Long Term Effects

Abstract The likelihood of future global water shortages is increasing and further development of existing operational hydrologic models is needed to maintain sustainable development of the ecological environment and human health. In order to quantitatively describe the water balance factors and transformation relations, the objective of this article is to develop a distributed hydrologic model that is capable of simulating the surface water (SW) and groundwater (GW) in irrigation areas. The model can be used as a tool for evaluating the long-term effects of water resource management. By coupling the Soil and Water Assessment Tool (SWAT) and MODFLOW models, a comprehensive hydrological model integrating SW and GW is constructed. The hydrologic response units for the SWAT model are exchanged with cells in the MODFLOW model. Taking the Heihe River Basin as the study area, 10 years of historical data are used to conduct an extensive sensitivity analysis on model parameters. The developed model is run for a 40-year prediction period. The application of the developed coupling model shows that since the construction of the Heihe reservoir, the average GW level in the study area has declined by 6.05 m. The model can accurately simulate and predict the dynamic changes in SW and GW in the downstream irrigation area of Heihe River Basin and provide a scientific basis for water management in an irrigation district.

scholarly journals Assessing the impacts of hydrologic and land use alterations on water temperature in the Farmington River basin in Connecticut

2019 ◽  
Vol 23 (11) ◽  
pp. 4491-4508 ◽  
Author(s):  
John R. Yearsley ◽  
Ning Sun ◽  
Marisa Baptiste ◽  
Bart Nijssen
Keyword(s):  
Land Use ◽  
Water Temperature ◽  
River Basin ◽  
Land Surface ◽  
Canopy Cover ◽  
River System ◽  
Stream Temperature ◽  
Hydrologic Model ◽  
Riparian Buffers ◽  
Connecticut River

Abstract. Aquatic ecosystems can be significantly altered by the construction of dams and modification of riparian buffers, and the effects are often reflected in spatial and temporal changes to water temperature. To investigate the implications for water temperature of spatially and temporally varying riparian buffers and dam-induced hydrologic alterations, we have implemented a modeling system (DHSVM-RBM) within the framework of the state-space paradigm that couples a spatially distributed land surface hydrologic model, DHSVM, with the distributed stream temperature model, RBM. The basic modeling system has been applied previously to several similar-sized watersheds. However, we have made enhancements to DHSVM-RBM that simulate spatial heterogeneity and temporal variation (i.e., seasonal changes in canopy cover) in riparian vegetation, and we included additional features in DHSVM-RBM that provide the capability for simulating the impacts of reservoirs that may develop thermal stratification. We have tested the modeling system in the Farmington River basin in the Connecticut River system, which includes varying types of watershed development (e.g., deforestation and reservoirs) that can alter the streams' hydrologic regime and thermal energy budget. We evaluated streamflow and stream temperature simulations against all available observations distributed along the Farmington River basin. Results based on metrics recommended for model evaluation compare well to those obtained in similar studies. We demonstrate the way in which the model system can provide decision support for watershed planning by simulating a limited number of scenarios associated with hydrologic and land use alterations.

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