scholarly journals Assessment of applicability of mike 11-nam hydrological module for rainfall runoff modelling in a poorly studied river basin

Vestnik MGSU ◽  
2020 ◽  
pp. 1030-1046 ◽  
Author(s):  
Anghesom A. Ghebrehiwot ◽  
Dmitriy V. Kozlov

Introduction. The need to simulate hydrological processes is caused by, among other factors, the complexity of hydrological systems and data insufficiency due to the unavailability or a small number of instrumental observations. Recently, the reanalysis of the climate data supplied by the world’s leading meteorological centres has been used quite successfully in the regions that suffer from the deficit of instrumental information. This paper assesses the applicability of climate reanalysis data to rainfall runoff (“rainfall runoff”) modelling in the poorly studied river basin in Eritrea. Materials and methods. Climate Forecast System Reanalysis (CFSR) data generated by the National Centre for Environmental Prediction (USA) were used. Besides, high-resolution topographic information, generated by the SRTM international research project, was also applied to set the drainage area boundaries and to simulate the river network using such tools as MIKE and GIS. In addition, calibration and validation (evaluation) of the hydrological model (simulation quality) were performed using the Nash-Sutcliffe efficiency criterion, the determination coefficient, and the root mean square error of volumetric and peak flow rates. Results. The results suggest that a considerable overestimation of precipitation in the reanalysis data set, which in turn has a significant effect on other variables such as potential evapotranspiration, leads to a significant discrepancy between water balance values which are simulated and registered by the hydrographs. Conclusions. The applicability of Climate Forecast System Reanalysis (CFSR) data to river flow modelling in arid and semi-arid regions such as Eritrea is questionable. The incompatibility of spatial and temporal variations of initial variables (e.g. precipitation), derived from reanalysis data sets and instrumental observations, is undoubtedly the main reason for errors. Thus, the application of reanalysis data sets and development of hydrological models for the region under study requires further intensive research aimed at identifying most effective mechanisms designated for the harmonization of differences between reanalysis data and field observations. In the course of further research, CFSR information is to be converted into more realistic data; climate reanalysis indicators, provided by other sources and designated for different time scales in the context of the “rainfall runoff” model are to be assessed, and the efficiency of other software systems is to be compared with MIKE 11-NAM.

2016 ◽  
Vol 30 (8) ◽  
pp. 2627-2640 ◽  
Author(s):  
Milad Jajarmizadeh ◽  
Lariyah Mohd Sidek ◽  
Majid Mirzai ◽  
Sina Alaghmand ◽  
Sobri Harun ◽  
...  

2016 ◽  
Vol 30 (10) ◽  
pp. 3651-3651
Author(s):  
Milad Jajarmizadeh ◽  
Lariyah Mohd Sidek ◽  
Majid Mirzaei ◽  
Sina Alaghmand ◽  
Sobri Harun ◽  
...  

Author(s):  
S. Majumdar ◽  
S. Shukla ◽  
A. Maiti

<p><strong>Abstract.</strong> The aim of this study is to explore the applicability of Agent Based Modelling (ABM) for the simulation of rainfall runoff and soil erosion used in a watershed monitoring activity. The study utilizes Landsat 8 imagery for Land Use Land Cover (LULC) map generation, ASTER DEM for obtaining elevation information and Climate Forecast System Reanalysis (CFSR) 36 year weather data of Asan watershed, Uttarakhand, India. In the proposed model, four major agents (raindrops, soil, elevation and water amount) have been defined for estimating the soil erosion in the region. Moreover, the direct runoff has been simulated using the Soil Conservation Service (SCS) method. The analysis of the entire time series using this approach shows that there have been substantial changes in the rainfall runoff pattern primarily due to the varying environmental conditions of the study area since the late 1980s. Furthermore, a rough estimate of the soil erosion and deposition in the area have been computed which is aligned with the theory of sediment transport and deposition. In order to automate the entire model workflow, an open source cross platform tool has been developed using Python, R and NetLogo libraries. The Open Agent Based Runoff and Erosion Simulation (OARES) tool incorporates a generic interface for analysing large spatio-temporal datasets in watershed studies. The overall analysis concludes that the results obtained using ABM are comparable to that of the conventional hydrological models, and henceforth, ABM could be utilized as a future potential hydrological modelling paradigm.</p>


2019 ◽  
Vol 11 (3) ◽  
pp. 800-811
Author(s):  
Chenglin Duan ◽  
Sheng Dong ◽  
Zhifeng Wang ◽  
Zhenkun Liao

Abstract In this paper, a preliminary climatic description of the long-term offshore drift ice characteristics in the northern Barents Sea has been investigated from 1987 to 2016 based on the satellite ice motion datasets from National Snow and Ice Data Center (NSIDC) and reanalysis ice thickness datasets from National Centers for Environmental Prediction (NCEP)-Climate Forecast System Reanalysis (CFSR) and Climate Forecast System Version 2 (CFSv2). Both the ice velocity and thickness conditions have been studied at the three fixed locations from west to east. Annual and monthly drift ice roses indicate that the directions from WSW to SE are primarily prevailing, particularly in winter months. Besides, the annual ice speed extremums exceeding 40 cm s–1 mostly occur in the southerly directions from November to April. For the ice thickness, results reveal that it is prominently distributed in a thicker interval between 70 and 120 cm, and a thinner interval between 20 and 70 cm. The annual thickness maxima approximately range from 90 to 170 cm, primarily occurring from May to June, and demonstrate a light decreasing trend.


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