Research and applications of distributed hydrological model based on determination of slope directions for snowmelt runoff

2014 ◽  
Author(s):  
Z. Li ◽  
X.Y. Li ◽  
J. Sun
Keyword(s):  
Hydrological Model ◽  
Distributed Hydrological Model ◽  
Snowmelt Runoff ◽  
Model Based

scholarly journals Improving the snow physics of WEB-DHM and its point evaluation at the SnowMIP sites

2010 ◽  
Vol 14 (12) ◽  
pp. 2577-2594 ◽  
Author(s):  
M. Shrestha ◽  
L. Wang ◽  
T. Koike ◽  
Y. Xue ◽  
Y. Hirabayashi
Keyword(s):  
Snow Depth ◽  
Hydrological Model ◽  
Snow Water Equivalent ◽  
Phase 1 ◽  
Forest Site ◽  
Distributed Hydrological Model ◽  
Snowmelt Runoff ◽  
Runoff Generation ◽  
Basin Scale ◽  
Snow Physics

Abstract. In this study, the snow physics of a distributed biosphere hydrological model, referred to as the Water and Energy Budget based Distributed Hydrological Model (WEB-DHM) is significantly improved by incorporating the three-layer physically based energy balance snowmelt model of Simplified Simple Biosphere 3 (SSiB3) and the Biosphere-Atmosphere Transfer Scheme (BATS) albedo scheme. WEB-DHM with improved snow physics is hereafter termed WEB-DHM-S. Since the in-situ observations of spatially-distributed snow variables with high resolution are currently not available over large regions, the new distributed system (WEB-DHM-S) is at first rigorously tested with comprehensive point measurements. The stations used for evaluation comprise the four open sites of the Snow Model Intercomparison Project (SnowMIP) phase 1 with different climate characteristics (Col de Porte in France, Weissfluhjoch in Switzerland, Goose Bay in Canada and Sleepers River in USA) and one open/forest site of the SnowMIP phase 2 (Hitsujigaoka in Japan). The comparisons of the snow depth, snow water equivalent, surface temperature, snow albedo and snowmelt runoff at the SnowMIP1 sites reveal that WEB-DHM-S, in general, is capable of simulating the internal snow process better than the original WEB-DHM. Sensitivity tests (through incremental addition of model processes) are performed to illustrate the necessity of improvements over WEB-DHM and indicate that both the 3-layer snow module and the new albedo scheme are essential. The canopy effects on snow processes are studied at the Hitsujigaoka site of the SnowMIP2 showing that the snow holding capacity of the canopy plays a vital role in simulating the snow depth on ground. Through these point evaluations and sensitivity studies, WEB-DHM-S has demonstrated the potential to address basin-scale snow processes (e.g., the snowmelt runoff), since it inherits the distributed hydrological framework from the WEB-DHM (e.g., the slope-driven runoff generation with a grid-hillslope scheme, and the flow routing in the river network).

scholarly journals Assessment of distributed hydrological model performance for simulation of multi-heavy-metal transport in Harrach River, Algeria

2019 ◽  
Vol 80 (1) ◽  
pp. 11-24 ◽  
Author(s):  
Saadia Bouragba ◽  
Katsuaki Komai ◽  
Keisuke Nakayama
Keyword(s):  
Heavy Metals ◽  
Hydrological Model ◽  
Model Performance ◽  
Distributed Hydrological Model ◽  
Data Quality Control ◽  
Object Oriented Design ◽  
Model Based ◽  
Monitoring Strategies ◽  
Geophysical Flow ◽  
Multiple Heavy Metals

Abstract This paper aims to assess the performance of a distributed hydrological model for simulating the transport of various heavy metals in rivers, to enhance and support environmental monitoring strategies for rivers in developing countries. In this context, we evaluated the performance of the Geophysical flow Circulation (GeoCIRC) model based on Object-Oriented Design (OOD) for the simulation of contamination from multiple heavy metals (Pb, Hg, Cr, and Zn) in Harrach River in Algeria. The results of the case study were in good agreement with the observations. Methodology for the assessment of data quality control and the improvement of monitoring procedures was proposed by using the hydrological model to simulate different scenarios. The GeoCIRC-model-based OOD allowed the prediction of the concentrations of heavy metals with minimal input data. Also, various heavy metals could be numerically treated simultaneously because the OOD increases the model's flexibility to allow the handling of many transportable materials. Therefore, the GeoCIRC model is a powerful tool for the monitoring of environmental contamination in rivers by various heavy metals.

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