scholarly journals Multi-station calibration strategy for evaluation and sensitivity analysis of the snowmelt runoff model using MODIS satellite images

2021 ◽  
Author(s):  
Vahid Nourani ◽  
Amin Afkhaminia ◽  
Soghra Andaryani ◽  
Yongqiang Zhang
Keyword(s):  
River Flow ◽  
Model Performance ◽  
Surface Flow ◽  
Snowmelt Runoff ◽  
Single Station ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Increasing Temperature ◽  
Calibration Techniques ◽  
Runoff Model ◽  
Calibration Parameters

Abstract In this study, the snowmelt runoff model (SRM) was employed to estimate the effect of snow on the surface flow of Aji-Chay basin, northwest Iran. Two calibration techniques were adopted to enhance the calibration. The multi-station calibration (MSC) and single-station calibration (SSC) strategies applied to investigate their effects on the modeling accuracy. The runoff coefficients (cs and cr) were selected as calibration parameters because of their uncertainty in such an extended basin. To determine the most substantial input of the model which is the snow-covered area (SCA) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor imagery, MOD10A2 images were collected with spatial and temporal resolutions of 500 meters and 8 days, respectively. The results show an average of 15% improvement in the model performance in the MSC strategy from the data period of 2008–2012. Also, an appropriate agreement with physical characteristics of the study area could be seen for the calibration parameters. The contribution of snowmelt in the river flow reaches its peak in April and May, then with increasing temperature, the contribution decreased gradually. Furthermore, analysis of parameters indicates that the SRM is sensitive to recession coefficient and runoff coefficients.

scholarly journals Application of the Snowmelt Runoff Model in the Salang River Basin, Afghanistan Using MODIS Satellite Data

2016 ◽  
Vol 9 (1) ◽  
pp. 109-118
Author(s):  
Hedayatullah Arian ◽  
Rijan B. Kayastha ◽  
Bikas C. Bhattarai ◽  
Ahuti Shresta ◽  
Hafizullah Rasouli ◽  
...  
Keyword(s):  
River Basin ◽  
River Flow ◽  
Snowmelt Runoff ◽  
Annual Average ◽  
Temperature And Precipitation ◽  
Promising Tool ◽  
Daily Discharge ◽  
Input Variables ◽  
The Impact ◽  
Runoff Model

This study is carried out on the Salang River basin, which is located at the northern part of the Kabul River basin, and in the south facing slope of the Hindu Kush Mountains. The basin drains through the Salang River, which is one of the tributaries of the Panjshir River. The basin covers an area of 485.9km2 with a minimum elevation of 1653 m a.s.l. and a maximum elevation of 4770 m a.s.l. The Salang River sustains a substantial flow of water in summer months due to the melting of snow. In this study, we estimate daily discharge of Salang River from 2009 to 2011 using the Snowmelt Runoff Model (SRM, Version 1.12, 2009), originally developed by J. Martinec in 1975. The model uses daily observed precipitation, air temperature and snow cover data as input variables from which discharge is computed. The model is calibrated for the year 2009 and validated for 2010 and 2011. The observed and calculated annual average discharges for the calibration year 2009 are 11.57m3s-1 and 10.73m3s-1, respectively. Similarly, the observed and calculated annual average discharges for the validation year 2010 are 11.55m3s-1 and 10.07m3s-1, respectively and for 2011, the discharges are 9.05 m3s-1 and 9.6m3s-1, respectively. The model is also tested by changing temperature and precipitation for the year 2009. With an increase of 1°C in temperature and 10% in precipitation, the increases in discharge for winter, summer and annually are 21.8%, 13.5% and 14.8%, respectively. With an increase of 2°C in temperature and 20% in precipitation, the increases are 48.5%, 43.3% and 44.1%, respectively. The results obtained suggest that the SRM can be used as a promising tool to estimate the river discharge of the snow fed mountainous river basins of Afghanistan and to study the impact of climate change on river flow pattern of such basins.Journal of Hydrology and Meteorology, Vol. 9(1) 2015, p.109-118

scholarly journals Remote Sensing of Snow Cover Variability and Its Influence on the Runoff of Sápmi’s Rivers

Geosciences ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 130
Author(s):  
Sebastian Rößler ◽  
Marius S. Witt ◽  
Jaakko Ikonen ◽  
Ian A. Brown ◽  
Andreas J. Dietz
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Air Temperature ◽  
Kendall Test ◽  
The Arctic ◽  
Boreal Winter ◽  
Snowmelt Runoff ◽  
River Catchment ◽  
Catchment Areas ◽  
Runoff Model

The boreal winter 2019/2020 was very irregular in Europe. While there was very little snow in Central Europe, the opposite was the case in northern Fenno-Scandia, particularly in the Arctic. The snow cover was more persistent here and its rapid melting led to flooding in many places. Since the last severe spring floods occurred in the region in 2018, this raises the question of whether more frequent occurrences can be expected in the future. To assess the variability of snowmelt related flooding we used snow cover maps (derived from the DLR’s Global SnowPack MODIS snow product) and freely available data on runoff, precipitation, and air temperature in eight unregulated river catchment areas. A trend analysis (Mann-Kendall test) was carried out to assess the development of the parameters, and the interdependencies of the parameters were examined with a correlation analysis. Finally, a simple snowmelt runoff model was tested for its applicability to this region. We noticed an extraordinary variability in the duration of snow cover. If this extends well into spring, rapid air temperature increases leads to enhanced thawing. According to the last flood years 2005, 2010, 2018, and 2020, we were able to differentiate between four synoptic flood types based on their special hydrometeorological and snow situation and simulate them with the snowmelt runoff model (SRM).

scholarly journals Forecasting carbon monoxide on a global scale for the ATom-1 aircraft mission: insights from airborne and satellite observations and modeling

2018 ◽  
Vol 18 (15) ◽  
pp. 10955-10971 ◽  
Author(s):  
Sarah A. Strode ◽  
Junhua Liu ◽  
Leslie Lait ◽  
Róisín Commane ◽  
Bruce Daube ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Optical Thickness ◽  
Chemical Reactivity ◽  
Model Performance ◽  
Global Scale ◽  
Satellite Observations ◽  
Aerosol Optical Thickness ◽  
Boreal Summer ◽  
Large Contribution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. The first phase of the Atmospheric Tomography Mission (ATom-1) took place in July–August 2016 and included flights above the remote Pacific and Atlantic oceans. Sampling of atmospheric constituents during these flights is designed to provide new insights into the chemical reactivity and processes of the remote atmosphere and how these processes are affected by anthropogenic emissions. Model simulations provide a valuable tool for interpreting these measurements and understanding the origin of the observed trace gases and aerosols, so it is important to quantify model performance. Goddard Earth Observing System Model version 5 (GEOS-5) forecasts and analyses show considerable skill in predicting and simulating the CO distribution and the timing of CO enhancements observed during the ATom-1 aircraft mission. We use GEOS-5's tagged tracers for CO to assess the contribution of different emission sources to the regions sampled by ATom-1 to elucidate the dominant anthropogenic influences on different parts of the remote atmosphere. We find a dominant contribution from non-biomass-burning sources along the ATom transects except over the tropical Atlantic, where African biomass burning makes a large contribution to the CO concentration. One of the goals of ATom is to provide a chemical climatology over the oceans, so it is important to consider whether August 2016 was representative of typical boreal summer conditions. Using satellite observations of 700 hPa and column CO from the Measurement of Pollution in the Troposphere (MOPITT) instrument, 215 hPa CO from the Microwave Limb Sounder (MLS), and aerosol optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS), we find that CO concentrations and aerosol optical thickness in August 2016 were within the observed range of the satellite observations but below the decadal median for many of the regions sampled. This suggests that the ATom-1 measurements may represent relatively clean but not exceptional conditions for lower-tropospheric CO.

scholarly journals IMPACTS OF SNOWMELT AND CLIMATE CHANGE ON HIMALAYAN RIVERS: THE CASE OF DATA-SCARCE DUDHKOSHI RIVER IN EASTERN NEPAL

2021 ◽  
Vol 5 (12) ◽  
Author(s):  
Sudeep Pokhrel ◽  
Saraswati Thapa
Keyword(s):  
Maximum Temperature ◽  
Climate Projections ◽  
Snow Melt ◽  
Snow Hydrology ◽  
Statistical Downscaling Model ◽  
Snowmelt Runoff ◽  
Annual Average ◽  
Temperature And Precipitation ◽  
Increasing Trends ◽  
Runoff Model

Water from snow-melt is crucial to provide ecosystem services in downstream of the Himalayas. To study the fate of snow hydrology, an integrated modeling system has been developed coupling Statistical Downscaling Model (SDSM) outputs with Snowmelt Runoff Model (SRM) in the Dudhkoshi Basin, Nepal. The SRM model is well-calibrated in 2011 and validated in 2012 and 2014 using MODIS satellite data. The annual average observed and simulated discharges for the calibration year are 177.89 m3 /s and 181.47 m3 /s respectively. To assess future climate projections for the periods 2020s, 2050s, and 2080s, the SDSM model is used for downscaling precipitation, maximum temperature, and minimum temperature from the Canadian GCM model (CanESM2) under three different scenarios RCP2.6, RCP4.5 and RCP8.5. All considered scenarios are significant in predicting increasing trends of maximumminimum temperature and precipitation and the storehouse of freshwater in the mountains is expected to deplete rapidly if global warming continues.

Development and application of a spatially distributed snowmelt runoff model for limited data condition

2019 ◽  
Vol 12 (15) ◽  
Author(s):  
S. Rajkumari ◽  
N. Chiphang ◽  
Liza G. Kiba ◽  
A. Bandyopadhyay ◽  
A. Bhadra
Keyword(s):  
Snowmelt Runoff ◽  
Limited Data ◽  
Spatially Distributed ◽  
Runoff Model

scholarly journals A Test of Snowmelt-Runoff Model for a Major River Basin in Western Himalayas

1989 ◽  
Vol 20 (3) ◽  
pp. 167-178 ◽  
Author(s):  
B. Dey ◽  
V. K. Sharma ◽  
A. Rango
Keyword(s):  
River Basin ◽  
Lapse Rate ◽  
Western Himalayas ◽  
Rainfall Runoff ◽  
Snowmelt Runoff ◽  
Major River ◽  
Updating Procedure ◽  
Runoff Model ◽  
Kabul River

In the Snowmelt-Runoff Model (SRM), the estimate of discharge volume is based on temperature condition in the form of degree days which are used to melt the snowpack in the area of the basin covered by snow as observed from satellites. Precipitation input is used to add any rainfall runoff to the snowmelt component. When SRM was applied to the large, international Kabul River basin, initial simulations were much above the observed stream flow values. Close inspection revealed several problems in the application of SRM to the Kabul Basin that were easily corrected. Foremost among the corrections were determination of an appropriate lapse rate, substitution of a more representative mean elevation for extrapolation of temperature data, and use of an automatic streamflow updating procedure. These improvements led to a simulation for 1976 that was comparable to other simulations on large, inaccessible basins. As SRM is applied to more basins similar to the Kabul River, the determination of suitable parameters for new basin will be enhanced. Additional improvements in simulations would result from installation of climate stations at the mean elevation of basins and work to assure delivery of timely and reliable satellite snow cover data.

scholarly journals Ideal point error for model assessment in data-driven river flow forecasting

2012 ◽  
Vol 16 (8) ◽  
pp. 3049-3060 ◽  
Author(s):  
C. W. Dawson ◽  
N. J. Mount ◽  
R. J. Abrahart ◽  
A. Y. Shamseldin
Keyword(s):  
River Flow ◽  
Ideal Point ◽  
Model Performance ◽  
Model Assessment ◽  
River Flow Forecasting ◽  
The Individual ◽  
Measure Of Performance ◽  
Individual Metrics ◽  
Naive Model ◽  
The Ideal

Abstract. When analysing the performance of hydrological models in river forecasting, researchers use a number of diverse statistics. Although some statistics appear to be used more regularly in such analyses than others, there is a distinct lack of consistency in evaluation, making studies undertaken by different authors or performed at different locations difficult to compare in a meaningful manner. Moreover, even within individual reported case studies, substantial contradictions are found to occur between one measure of performance and another. In this paper we examine the ideal point error (IPE) metric – a recently introduced measure of model performance that integrates a number of recognised metrics in a logical way. Having a single, integrated measure of performance is appealing as it should permit more straightforward model inter-comparisons. However, this is reliant on a transferrable standardisation of the individual metrics that are combined to form the IPE. This paper examines one potential option for standardisation: the use of naive model benchmarking.

scholarly journals The HYDROMED model and its application to semi-arid Mediterranean catchments with hill reservoirs 2: Rainfall-runoff model applications to three Mediterranean hill reservoirs

2001 ◽  
Vol 5 (4) ◽  
pp. 554-562 ◽  
Author(s):  
R. Ragab ◽  
D. Moidinis ◽  
J. Albergel ◽  
J. Khouri ◽  
A. Drubi ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Model Performance ◽  
Limited Information ◽  
Rainfall Runoff ◽  
Significant Events ◽  
Reliable Parameter ◽  
Rainfall Runoff Model ◽  
Parameter Values ◽  
Runoff Model

Abstract. The objective of this work was to assess the performance of the newly developed HYDROMED model. Three catchments with hill reservoirs were selected. They are El-Gouazine and Kamech in Tunisia and Es Sindiany in Syria. The rainfall, the spillway flow and volume of water in the reservoirs were used as input to the model. Events that generated spillway flow were preferred for calibration. The results confirmed that the HYDROMED model is capable of reproducing the runoff volume at all the three sites. In calibrating single events, the model performance was high as measured by the Nash-Sutcliffe criterion for goodness of fit. In some events this value was as high as 98%. In simulation mode, the highest Nash-Sutcliffe criterion value was close to 70% in the El-Gouazine and Kamech catchments and close to 50% in the Es Sindiany catchment. Given the limited information available, especially on the unrecorded releases in the three catchments, the hydrological impact of site geology (e.g. Kamech), the unrecorded operator intervention during the spillway flow (e.g. Es Sindiany) and other unaccounted factors (e.g siltation, evaporation, etc.), these results are by and large very encouraging. However, they could be further improved as and when more information on the unrecorded parameters becomes available. Additionally, the results of this work highlighted the need for long term records with a large number of significant events that are able to generate spillway flow to obtain more consistent and reliable parameter values. It also highlights the need for more accurately recorded releases for irrigation and other uses. As these results are encouraging, more tests on those three and other sites are planned. Keywords: HYDROMED, rainfall-runoff model, Mediterranean, conceptual model

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