Most Nile water originates in Ethiopia but there is no agreement on how land degradation or climate change affects the future flow in downstream countries. The objective of this paper is to improve season flow. The difference in response was likely due to weir construction in the nineties at the Lake Tana outlet that affected significantly the upper Blue Nile discharge but only affected less than 10% of the discharge at the Sudan border. The rainfall runoff model reproduced the observed trends, assuming that an additional ten percent of the hillsides were eroded in the 40 year time span and generated overland flow instead of interflow and base flow. Models concerning future trends in the Nile cannot assume that the landscape runoff processes will remain static.

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Please cite this article as: Z.K. Tesemma , Y. Wei , M.C. Peel , A.W. Western , The effect of yearto-year variability of leaf area index on Variable Infiltration Capacity model performance and simulation of runoff, Advances in Water Resources (2015),1 Highlights  The study assesses the impact of using year-to-year variable monthly LAI to calibrate VIC model and its performance.  VIC model efficiency can be improved when the year-to-year variable monthly LAI is used to calibrate the model.  Leaf area index elasticity of runoff is strongly related with catchment characteristics. Uses of long-term mean monthly LAI in VIC model tend to underestimate simulate runoff in dry period and overestimate in wet period. AbstractThis study assessed the effect of using observed monthly leaf area index (LAI) on hydrological model performance and the simulation of runoff using the Variable Infiltration Capacity (VIC) hydrological model in the Goulburn-Broken catchment of Australia, which has heterogeneous vegetation, soil and climate zones. VIC was calibrated with both observed monthly LAI and long-term mean monthly LAI, which were derived from the Global Land Surface Satellite (GLASS) leaf area index dataset covering the period from 1982 to 2012.The model performance under wet and dry climates for the two different LAI inputs was assessed using three criteria, the classical Nash-Sutcliffe efficiency, the logarithm transformed flow Nash-Sutcliffe efficiency and the percentage bias. Finally, the deviation of the simulated monthly runoff using the observed monthly LAI from simulated runoff using long-term mean monthly LAI was computed. The VIC model predicted monthly runoff in the selected sub-catchments with model efficiencies ranging from 61.5% to 95.9% during calibration (1982-1997) and 59% to 92.4% during validation (1998-2012). Our results suggest systematic improvements, from 4% to 25% in Nash-Sutcliffe efficiency, in sparsely forested sub-catchments when the VIC model was calibrated with observed monthly LAI instead of long-term mean monthly LAI. There was limited systematic improvement in tree dominated sub-catchments. The results also suggest that the model overestimation or underestimation of runoff during wet and dry periods can be reduced to 25 mm and 35 mm respectively by including the year-to-year variability of LAI in the model, thus reflecting the responses of vegetation to fluctuations in climate and other factors. Hence, the year-to-year ACCEPTED MANUSCRIPT A C C E P T E D M A N U S C R I P T 3 variability in LAI should not be neglected; rather it should be included in model calibration as well as simulation of monthly water balance.

Cold regions provide water resources for half the global population yet face rapid change. Their hydrology is dominated by snow, ice and frozen soils, and climate warming is having profound effects. Hydrological models have a key role in predicting changing water resources but are challenged in cold regions. Ground‐based data to quantify meteorological forcing and constrain model parameterization are limited, while hydrological processes are complex, often controlled by phase change energetics. River flows are impacted by poorly quantified human activities. This paper discusses the scientific and technical challenges of the large‐scale modelling of cold region systems and reports recent modelling developments, focussing on MESH, the Canadian community hydrological land surface scheme. New cold region process representations include improved blowing snow transport and sublimation, lateral land‐surface flow, prairie pothole pond storage dynamics, frozen ground infiltration and thermodynamics, and improved glacier modelling. New algorithms to represent water management include multistage reservoir operation. Parameterization has been supported by field observations and remotely sensed data; new methods for parameter identification have been used to evaluate model uncertainty and support regionalization. Additionally, MESH has been linked to broader decision‐support frameworks, including river ice simulation and hydrological forecasting. The paper also reports various applications to the Saskatchewan and Mackenzie River basins in western Canada (0.4 and 1.8 million km2). These basins arise in glaciated mountain headwaters, are partly underlain by permafrost, and include remote and incompletely understood forested, wetland, agricultural and tundra ecoregions. These illustrate the current capabilities and limitations of cold region modelling, and the extraordinary challenges to prediction, including the need to overcoming biases in forcing data sets, which can have disproportionate effects on the simulated hydrology.