Evaluation of the Snowmelt Runoff Model in the Moroccan High Atlas Mountains using two snow-cover estimates

Abstract In the centre of Morocco, the High Atlas mountain range represents the most important water storage for the neighbouring arid plains through liquid and solid precipitation. In this context, we evaluated the performance of the Snowmelt Runoff Model (SRM) on the five main tributary watersheds of the High Atlas range. Due to the very low density of climate stations in the High Atlas, snowfall and snowmelt processes are difficult to monitor using meteorological data alone. In order to compensate for the lack of in situ data, snow maps are also derived from remotely-sensed data. We compared the streamflow forecasting performance when the model is driven by one or the other estimate of snow-covered area. Both estimates are generally comparable in all watersheds, and satisfactory streamflow simulations were obtained at seasonal time scales using both snow-cover products. However, significant differences can be observed for selected storms, with more accurate streamflow predictions being obtained when the remotely-sensed data are used.

[1]  E. Khazaei,et al.  A catchment water balance model for estimating groundwater recharge in arid and semiarid regions of south-east Iran , 2003 .

[2]  Helmut Rott,et al.  Assimilation of meteorological and remote sensing data for snowmelt runoff forecasting , 2008 .

[3]  Albert Rango,et al.  Operational snowmelt runoff forecasting in the Spanish Pyrenees using the snowmelt runoff model , 2002 .

[4]  John Pitlick,et al.  Relation between peak flows, precipitation, and physiography for five mountainous regions in the western USA , 1994 .

[5]  Demetris Koutsoyiannis,et al.  Dryland hydrology in Mediterranean regions—a review , 2007 .

[6]  José A. Sobrino,et al.  An integrated modelling and remote sensing approach for hydrological study in arid and semi‐arid regions: the SUDMED Programme , 2008 .

[7]  Paul R. Houser,et al.  A methodology for snow data assimilation in a land surface model , 2004 .

[8]  C. de Jong,et al.  Snowmelt and sublimation: field experiments and modelling in the High Atlas Mountains of Morocco , 2004 .

[10]  J. Martinec.  Snowmelt Runoff Models for Operational Forecasts , 1985 .

[11]  G. McCabe,et al.  Assimilation of snow covered area information into hydrologic and land-surface models , 2006 .

[12]  Keith Beven,et al.  Prophecy, reality and uncertainty in distributed hydrological modelling , 1993 .

[13]  Gilles Boulet,et al.  Understanding hydrological processes with scarce data in a mountain environment , 2008 .

[14]  David R. DeWalle,et al.  APPLICATION OF THE SNOWMELT RUNOFF MODEL USING MULTIPLE‐PARAMETER LANDSCAPE ZONES ON THE TOWANDA CREEK BASIN, PENNSYLVANIA 1 , 1998 .

[15]  M. Clark,et al.  Snow Data Assimilation via an Ensemble Kalman Filter , 2006 .

[16]  Xingong Li,et al.  Snowmelt runoff modelling in an arid mountain watershed, Tarim Basin, China , 2008 .

[17]  D. Lettenmaier,et al.  Assimilating remotely sensed snow observations into a macroscale hydrology model , 2006 .

[18]  Zoubir Makhlouf.  Complements sur le modele pluie-debit gr4j et essai d'estimation de ses parametres , 1994 .

[19]  Albert Rango,et al.  Revisiting the Degree-Day Method for Snowmelt Computations , 1995 .

[20]  E. H. Collins.  Relationship of degree‐days above freezing to runoff , 1934 .

[21]  Dennis K. McLaughlin,et al.  Opportunities for enhanced collaboration within the data assimilation community , 2005 .

[22]  M. Matson,et al.  NOAA satellite snow cover data , 1991 .

[23]  E. Morán-Tejeda,et al.  Water resources and environmental change in a Mediterranean environment: The south-west sector of the Duero river basin (Spain) , 2008 .

[24]  Thomas M. Over,et al.  A comparison of MODIS and NOHRSC snow‐cover products for simulating streamflow using the Snowmelt Runoff Model , 2005 .

[25]  Keith Beven,et al.  The future of distributed models: model calibration and uncertainty prediction. , 1992 .

[26]  Rolf Weingartner,et al.  Assessing the Hydrological Significance of the World's Mountains , 2003 .

[27]  J. Martinec,et al.  Distributed mapping of snow and glaciers for improved runoff modelling , 1999 .

[28]  K. Beven.  Environmental Modelling , 2007 .

[29]  Dong-Jun Seo,et al.  Real-Time Variational Assimilation of Hydrologic and Hydrometeorological Data into Operational Hydrologic Forecasting , 2003 .

[30]  Jaroslav Martinec,et al.  SNOWMELT - RUNOFF MODEL FOR STREAM FLOW FORECASTS , 1975 .

[31]  Dennis McLaughlin,et al.  Recent developments in hydrologic data assimilation , 1995 .

[32]  S. Bergström,et al.  THE DEVELOPMENT OF A SNOW ROUTINE FOR THE HBV-2 MODEL , 1975 .

[33]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[34]  Albert Rango,et al.  Development and testing of a Snowmelt-Runoff forecasting technique , 1990 .

[35]  G. Flerchinger,et al.  A ten-year water balance of a mountainous semi-arid watershed computed by aggregating landscape units. , 2000 .

[36]  J. Dozier.  Spectral Signature of Alpine Snow Cover from the Landsat Thematic Mapper , 1989 .

[37]  J. Martinec,et al.  Effects of climate change on water resources and runoff in an Alpine basin , 1998 .

[38]  Albert Rango,et al.  Application of a Snowmelt-Runoff Model Using Landsat Data , 1979 .

[39]  B. Duchemin,et al.  VEGETATION/SPOT: an operational mission for the Earth monitoring; presentation of new standard products , 2004 .

[40]  N. DiGirolamo,et al.  MODIS snow-cover products , 2002 .

[41]  Benoît Duchemin,et al.  Snow cover mapping using SPOT VEGETATION with high resolution data: application in the Moroccan Atlas Mountains , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[42]  Benoît Duchemin,et al.  A combined high and low spatial resolution approach for mapping snow covered areas in the Atlas mountains , 2005 .

[43]  A. Rango,et al.  Accuracy of Snowmelt Runoff Simulation , 1981 .

[44]  B. Brasnett,et al.  A Global Analysis of Snow Depth for Numerical Weather Prediction , 1999 .