scholarly journals Integrated simulation of snow and glacier melt in water and energy balance-based, distributed hydrological modeling framework at Hunza River Basin of Pakistan Karakoram region

2015 ◽  
Vol 120 (10) ◽  
pp. 4889-4919 ◽  
Author(s):  
Maheswor Shrestha ◽  
Toshio Koike ◽  
Yukiko Hirabayashi ◽  
Yongkang Xue ◽  
Lei Wang ◽  
...  
Keyword(s):  
Energy Balance ◽  
River Basin ◽  
Hydrological Modeling ◽  
Modeling Framework ◽  
Integrated Simulation ◽  
Glacier Melt ◽  
Distributed Hydrological Modeling ◽  
Hunza River

scholarly journals Evaluation of Quantitative Precipitation Estimations through Hydrological Modeling in IFloodS River Basins

2017 ◽  
Vol 18 (2) ◽  
pp. 529-553 ◽  
Author(s):  
Huan Wu ◽  
Robert F. Adler ◽  
Yudong Tian ◽  
Guojun Gu ◽  
George J. Huffman
Keyword(s):  
Real Time ◽  
River Basin ◽  
Hydrological Modeling ◽  
Research Quality ◽  
Quality Data ◽  
Time Data ◽  
Modeling Framework ◽  
Precipitation Estimation ◽  
Precipitation Bias

Abstract A multiple-product-driven hydrologic modeling framework (MMF) is utilized for evaluation of quantitative precipitation estimation (QPE) products, motivated by improving the utility of satellite QPE in global flood modeling. This work addresses the challenge of objectively determining the relative value of various QPEs at river basin/subbasin scales. A reference precipitation dataset is created using a long-term water-balance approach with independent data sources. The intercomparison of nine QPEs and corresponding hydrologic simulations indicates that all products with long-term (2002–13) records have similar merits as over the short-term (April–June 2013) Iowa Flood Studies period. The model performance in calculated streamflow varies approximately linearly with precipitation bias, demonstrating that the model successfully translated the level of precipitation quality to streamflow quality with better streamflow simulations from QPEs with less bias. Phase 2 of the North American Land Data Assimilation System (NLDAS-2) has the best streamflow results for the Iowa–Cedar River basin, with daily and monthly Nash–Sutcliffe coefficients and mean annual bias of 0.81, 0.88, and −2.1%, respectively, for the long-term period. The evaluation also indicates that a further adjustment of NLDAS-2 to form the best precipitation estimation should consider spatial–temporal distribution of bias. The satellite-only products have lower performance (peak and timing) than other products, while simple bias adjustment can intermediately improve the quality of simulated streamflow. The TMPA research product (TMPA-RP; research-quality data) can generate results approaching those of the ground-based products with only monthly gauge-based adjustment to the TMPA real-time product (TMPA-RT; near-real-time data). It is further noted that the streamflow bias is strongly correlated to precipitation bias at various time scales, though other factors may play a role as well, especially on the daily time scale.

scholarly journals Techno-Economic Analysis of a Novel Hydrogen-Based Hybrid Renewable Energy System for Both Grid-Tied and Off-Grid Power Supply in Japan: The Case of Fukushima Prefecture

2020 ◽  
Vol 10 (12) ◽  
pp. 4061 ◽  
Author(s):  
Naoto Takatsu ◽  
Hooman Farzaneh
Keyword(s):  
Renewable Energy ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Economic Assessment ◽  
Energy System ◽  
Modeling Framework ◽  
Integrated Simulation ◽  
Hybrid Renewable Energy System ◽  
Renewable Energy System ◽  
Hybrid Renewable Energy

After the Great East Japan Earthquake, energy security and vulnerability have become critical issues facing the Japanese energy system. The integration of renewable energy sources to meet specific regional energy demand is a promising scenario to overcome these challenges. To this aim, this paper proposes a novel hydrogen-based hybrid renewable energy system (HRES), in which hydrogen fuel can be produced using both the methods of solar electrolysis and supercritical water gasification (SCWG) of biomass feedstock. The produced hydrogen is considered to function as an energy storage medium by storing renewable energy until the fuel cell converts it to electricity. The proposed HRES is used to meet the electricity demand load requirements for a typical household in a selected residential area located in Shinchi-machi in Fukuoka prefecture, Japan. The techno-economic assessment of deploying the proposed systems was conducted, using an integrated simulation-optimization modeling framework, considering two scenarios: (1) minimization of the total cost of the system in an off-grid mode and (2) maximization of the total profit obtained from using renewable electricity and selling surplus solar electricity to the grid, considering the feed-in-tariff (FiT) scheme in a grid-tied mode. As indicated by the model results, the proposed HRES can generate about 47.3 MWh of electricity in all scenarios, which is needed to meet the external load requirement in the selected study area. The levelized cost of energy (LCOE) of the system in scenarios 1 and 2 was estimated at 55.92 JPY/kWh and 56.47 JPY/kWh, respectively.

Estimation of mass and energy balance of glaciers using a distributed energy balance model over the Chandra river basin (Western Himalaya)

2021 ◽  
Vol 35 (2) ◽  
Author(s):  
Akansha Patel ◽  
Ajanta Goswami ◽  
Jaydeo K. Dharpure ◽  
Meloth Thamban ◽  
Parmanand Sharma ◽  
...  
Keyword(s):  
Energy Balance ◽  
River Basin ◽  
Western Himalaya ◽  
Energy Balance Model ◽  
Balance Model ◽  
Distributed Energy

scholarly journals Extensive Evaluation of a Continental-Scale High-Resolution Hydrological Model Using Remote Sensing and Ground-Based Observations

2021 ◽  
Vol 13 (7) ◽  
pp. 1247
Author(s):  
Bowen Zhu ◽  
Xianhong Xie ◽  
Chuiyu Lu ◽  
Tianjie Lei ◽  
Yibing Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Hydrological Modeling ◽  
Infiltration Capacity ◽  
Modeling Framework ◽  
Large Domain ◽  
Continental Scale ◽  
Extensive Evaluation ◽  
Mean Differences ◽  
Fine Resolution

Extreme hydrologic events are getting more frequent under a changing climate, and a reliable hydrological modeling framework is important to understand their mechanism. However, existing hydrological modeling frameworks are mostly constrained to a relatively coarse resolution, unrealistic input information, and insufficient evaluations, especially for the large domain, and they are, therefore, unable to address and reconstruct many of the water-related issues (e.g., flooding and drought). In this study, a 0.0625-degree (~6 km) resolution variable infiltration capacity (VIC) model developed for China from 1970 to 2016 was extensively evaluated against remote sensing and ground-based observations. A unique feature in this modeling framework is the incorporation of new remotely sensed vegetation and soil parameter dataset. To our knowledge, this constitutes the first application of VIC with such a long-term and fine resolution over a large domain, and more importantly, with a holistic system-evaluation leveraging the best available earth data. The evaluations using in-situ observations of streamflow, evapotranspiration (ET), and soil moisture (SM) indicate a great improvement. The simulations are also consistent with satellite remote sensing products of ET and SM, because the mean differences between the VIC ET and the remote sensing ET range from −2 to 2 mm/day, and the differences for SM of the top thin layer range from −2 to 3 mm. Therefore, this continental-scale hydrological modeling framework is reliable and accurate, which can be used for various applications including extreme hydrological event detections.

Atmospheric-hydrological modeling of severe precipitation and floods in the Huaihe River Basin, China

2006 ◽  
Vol 330 (1-2) ◽  
pp. 249-259 ◽  
Author(s):  
Charles A. Lin ◽  
Lei Wen ◽  
Guihua Lu ◽  
Zhiyong Wu ◽  
Jianyun Zhang ◽  
...  
Keyword(s):  
River Basin ◽  
Hydrological Modeling ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
The Huaihe River
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