In the context of global research in snow-affected regions, research in the Australian Alps has been steadily catching up to the more established research environments in other countries. One area that holds immense potential for growth is hydrological modelling. Future hydrological modelling could be used to support a range of management and planning issues, such as to better characterise the contribution of the Australian Alps to flows in the agriculturally important Murray-Darling Basin despite its seemingly small footprint. The lack of recent hydrological modelling work in the Australian Alps has catalysed this review, with the aim to summarise the current state and to provide future directions for hydrological modelling, based on advances in knowledge of the Australian Alps from adjacent disciplines and global developments in the field of hydrologic modelling. Future directions proffered here include moving beyond the previously applied conceptual models to more physically based models, supported by an increase in data collection in the region, and modelling efforts that consider non-stationarity of hydrological response, especially that resulting from climate change.

Understanding and simulating the hydrological cycle, especially in a context of climate change, is crucial for quantitative water risk assessment and basin management. The hydrological cycle is complex as it is a combination of non-linear natural processes and anthropogenic influences that alter landforms and water flows. Human-induced changes of relevance, including changes in land uses, construction of dams and artificial reservoirs, and diversion of the river course, lead to changes in water flows throughout the basin. These should be explicitly accounted for a realistic representation of the anthropogenically altered hydrological cycle. Such a realistic representation of the hydrological cycle is a necessary input for the water risk assessment in a particular region. In this paper, we present a hydrological digital twin (HDT) model of a large anthropized alpine basin: the Adige basin located in the northeast of Italy.Most catchments model often overlook land-uses changes over time and forget to model reservoir operation and their influence over time on water flow. Yet, for example, the Adige basin has>30 reservoirs affecting the water flow. We therefore use the GEOframe modeling framework to demonstrate the ability to create a hydrological twin model accounting for these anthropogenic changes.Specifically, we model each component of the water cycle over 39 years (1980-2018) at daily timescale through calibration of the Adige HDT with a multi-site approach using discharge data of 33 stations, based on a high-resolution (1 km) temperature and precipitation dataset and a calculated crop potential evapotranspiration (PETc) dataset, which accounts for human-induced change of the land cover over time. The modeling system also includes the simulation of artificial reservoirs and dams by the dynamically zoned target release (DZTR) reservoir model.The Adige HDT is assessed/validated/compared through a variety of hydrological processes (i.e., river and reservoir discharges, PETc and actual evapotranspiration, snow, and soil moisture) and data sources (i.e., observations and remote sensing data).Overall, the HDT reproduces well the measured discharge in space and time with a Kling Gupta Efficiency (KGE) above 0.7 (0.8) for 30 (23) of the 33 gauge-stations. For 7 artificial reservoirs with available data, the reservoir turbinated discharges are successfully reproduced with an average KGE of 0.92. A comparison between modeled and MODIS remote sensing snow data showed an average error of < 10% across the entire basin; the model also presented a good spatio-temporal agreement both with GLEAMS potential (and actual evapotranspiration) with an average KGE of 0.63 (0.60) and a high-level of correlation (0.5 on average) with the ASCAT satellite retrieved soil moisture.The findings of this paper demonstrate the potential of the open-source, component-based, GEOframe system to build a HDT, to provide a reliable and long term (39 years) estimation of all the water cycle components in a complex anthropized river basin at high spatial resolution. Spatially detailed HDT models results of this type can be used to inform basin-wise adaptation policy decisions and better water management practices in a time of changing climate.

This study diagnoses the impact of projected changes in climate and glacier cover on the hydrology of several natural flowing Bow River headwater basins in the Canadian Rockies: the Bow River at Lake Louise (-420.7 km2), the Pipestone River near Lake Louise (-304.2 km2), the Bow River at Banff (-2192.2 km2) all of which drain the high elevation, snowy, partially glaciated Central Range, and the Elbow River at Calgary (-1191.9 km2), which drains the drier Front Ranges and foothills, using models created using the modular, flexible, physically based Cold Regions Hydrological Modelling platform (CRHM). Hydrological models were constructed and parameterised in CRHM from local research results to include relevant streamflow generation processes for Canadian Rockies headwater basins, such as blowing snow, avalanching, snow interception and sublimation, energy budget snow and glacier melt, infiltration to frozen and unfrozen soils, hillslope sub-surface water redistribution, wetlands, lakes, evapotranspiration, groundwater flow, surface runoff and open channel flow. Surface layer outputs from Weather Research and Forecasting (WRF) model simulations for the current climate and for the late 21st century climate under a business-as-usual scenario, Representative Concentration Pathway 8.5 (RCP8.5) at 4-km resolution, were used to force model simulations to examine the climate change impact. A projected glacier cover under a business-as-usual scenario (RCP8.5) was incorporated to assess the impact of concomitant glacier cover decline. Uncalibrated model simulations for the current climate and glacier coverage showed useful predictions of snow accumulation, snowmelt, and streamflow when compared to surface obser-vations from 2000 to 2015. Under the RCP8.5 climate change scenario, the basins of the Bow River at Banff and Elbow River at Calgary will warm up by 4.7 and 4.5 degrees C respectively and receive 12% to 15% more precipitation annually, with both basins experiencing a greater proportion of precipitation as rainfall. Peak snow accumulation in Bow River Basin will slightly rise by 3 mm, whilst it will drop by 20 mm in Elbow River Basin, and annual snowmelt volume will increase by 43 mm in Bow River Basin but decrease by 55 mm in Elbow River Basin. Snowcovered periods will decline by 37 and 46 days in Bow and Elbow river basins respectively due to sup-pressed snow redistribution by wind and gravity and earlier melt. The shorter snowcovered period and warmer, wetter climate will increase evapotranspiration and glacier melt, if the glaciers were held constant, and decrease sublimation, lake levels, soil moisture and groundwater levels. The hydrological responses of the basins will differ despite similar climate changes because of differing biophysical characteristics, climates and hydrological processes generating runoff. Climate change with concomitant glacier decline is predicted to increase the peak discharge and mean annual water yield by 12.23 m3 s-1 (+11%) and 11% in the higher elevation basins of the Bow River but will decrease the mean annual peak discharge by 3.58 m3 s-1 (-9%) and increase the mean annual water yield by 18% in the lower elevation basin of the Elbow River. This shows complex and compensatory hydrological process responses to climate change with the reduced glacier contribution reducing the impact of higher precipitation in high elevation headwaters and drier soil conditions and lower spring snowpacks reducing peak discharges despite increased precipitation during spring runoff in the Front Range and foothills headwaters under a warmer climate.

This research paper presents a systematic literature review on the use of remotely sensed and/or global datasets in distributed hydrological modelling. The study aims to investigate the most commonly used datasets in hydrological models and their performance across different geographical scales of catchments, including the micro-scale (1000 km(2)). The analysis included a search for the relation between the use of these datasets to different regions and the geographical scale at which they are most widely used. Additionally, co-authorship analysis was performed on the articles to identify the collaboration patterns among researchers. The study further categorized the analysis based on the type of datasets, including rainfall, digital elevation model, land use, soil distribution, leaf area index, snow-covered area, evapotranspiration, soil moisture and temperature. The research concluded by identifying knowledge gaps in the use of each data type at different scales and highlighted the varying performance of datasets across different locations. The findings underscore the importance of selecting the right datasets, which has a significant impact on the accuracy of hydrological models. This study provides valuable insights into the use of remote sensed and/or global datasets in hydrological modelling, and the identified knowledge gaps can inform future research directions.

This study investigates the impacts of climate change on the hydrology and soil thermal regime of 10 sub-arctic watersheds (northern Manitoba, Canada) using the Variable Infiltration Capacity (VIC) model. We utilize statistically downscaled and biascorrected forcing datasets based on 17 general circulation model (GCM) - representative concentration pathways (RCPs) scenarios from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to run the VIC model for three 30-year periods: a historical baseline (1981-2010: 1990s), and future projections (2021-2050: 2030s and 2041-2070: 2050s), under RCPs 4.5 and 8.5. Future warming increases the average soil column temperature by similar to 2.2 C in the 2050s and further analyses of soil temperature trends at three different depths show the most pronounced warming in the top soil layer (1.6 degrees C 30-year(-1) in the 2050s). Trend estimates of mean annual frozen soil moisture fraction in the soil column show considerable changes from 0.02 30-year(-1) (1990s) to 0.11 30-year(-1) (2050s) across the study area. Soil column water residence time decreases significantly (by 5 years) during the 2050s when compared with the 1990s as soil thawing intensifies the infiltration process thereby contributing to faster conversion to baseflow. Future warming results in 40%-50% more baseflow by the 2050s, where it increases substantially by 19.7% and 46.3% during the 2030s and 2050s, respectively. These results provide crucial information on the potential future impacts of warming soil temperatures on the hydrology of sub-arctic watersheds in north-central Canada and similar hydro-climatic regimes.

The Variable Infiltration Capacity (VIC) hydrologic model was adopted for investigating spatial and temporal variability of hydrologic impacts of climate change over the Nenjiang River Basin (NRB) based on a set of gridded forcing dataset at 1/12th degree resolution from 1970 to 2013. Basin-scale changes in the input forcing data and the simulated hydrological variables of the NRB, as well as station-scale changes in discharges for three major hydrometric stations were examined, which suggested that the model was performed fairly satisfactory in reproducing the observed discharges, meanwhile, the snow cover and evapotranspiration in temporal and spatial patterns were simulated reasonably corresponded to the remotely sensed ones. Wetland maps produced by multi-sources satellite images covering the entire basin between 1978 and 2008 were also utilized for investigating the responses and feedbacks of hydrological regimes on wetland dynamics. Results revealed that significant decreasing trends appeared in annual, spring and autumn streamflow demonstrated strong affection of precipitation and temperature changes over the study watershed, and the effects of climate change on the runoff reduction varied in the sub-basin area over different time scales. The proportion of evapotranspiration to precipitation characterized several severe fluctuations in droughts and floods took place in the region, which implied the enhanced sensitiveness and vulnerability of hydrologic regimes to changing environment of the region. Furthermore, it was found that the different types of wetlands undergone quite unique variation features with the varied hydro-meteorological conditions over the region, such as precipitation, evapotranspiration and soil moisture. This study provided effective scientific basis for water resource managers to develop effective eco-environment management plans and strategies that address the consequences of climate changes.

The frost table depth is a critical state variable for hydrological modelling in cold regions as frozen ground controls runoff generation, subsurface water storage and the permafrost regime. Calculation of the frost table depth is typically performed using a modified version of the Stefan equation, which is driven with the ground surface temperature. Ground surface temperatures have usually been estimated as linear functions of air temperature, referred to as n-factors' in permafrost studies. However, these linear functions perform poorly early in the thaw season and vary widely with slope, aspect and vegetation cover, requiring site-specific calibration. In order to improve estimation of the ground surface temperature and avoid site-specific calibration, an empirical radiative-conductive-convective (RCC) approach is proposed that uses air temperature, net radiation and antecedent frost table position as driving variables. The RCC algorithm was developed from forested and open sites on the eastern slope of the Coastal Mountains in southern Yukon, Canada, and tested at a high-altitude site in the Canadian Rockies, and a peatland in the southern Northwest Territories. The RCC approach performed well in a variety of land types without any local calibration and particularly improved estimation of ground temperature compared with linear functions during the first month of the thaw season, with mean absolute errors <2 degrees C in seven of the nine sites tested. An example of the RCC approach coupled with a modified Stefan thaw equation suggests a capability to represent frozen ground conditions that can be incorporated into hydrological and permafrost models of cold regions. Copyright (c) 2015 John Wiley & Sons, Ltd.