Global Institute for Water Security

Permanent URI for this collection

https://hdl.handle.net/10388/13701

Browse

Now showing 1 - 20 of 20

Adsorption of Pb2+ by Activated Carbon Produced by Microwave-Assisted K2CO3 Activation of Date Palm Leaf Sheath Fibres
(MDPI, 2023-11-08) aloud, saud; Kobrossy, Bassim; Mohamad Yusop, Mohamad Firdaus; Alharbi, Hattan; Giesy, John; Alotaibi, Khaled D.
Date palm trees generate large amounts of various types of waste, including leaf sheath fibres, which can be used as a low-cost precursor for the production of biochar, including activated carbon (AC), which can be employed for the adsorption of contaminants. In the current study, activated carbon was produced from leaf sheath fibres of date palms (LSDPFAC) by the use of chemical activation with K2CO3 combined with microwave irradiation, and it was characterised and evaluated for its adsorptive capacity of lead ions (Pb2+). The Brunauer–Emmett–Teller (BET) surface area, Langmuir surface area, total pore volume and average pore diameter of the LSDPFAC were 560.20 m2/g, 744.31 m2/g, 0.29 cm3/g and 2.47 nm, respectively. A greater adsorption of Pb2+ was observed when its concentration was higher in the solution, and the greatest adsorption capacity of 5.67 mg Pb/g was observed at the highest pH. The results of isotherm and kinetic studies demonstrated that the adsorption of Pb2+ onto the LSDPFAC was best described by the Freundlich isotherm and pseudo-second-order (PSO) models. The Langmuir ΔG° and Ea were 6.39 kJ/mol, 0.12 kJ/mol K, −31.28 kJ/mol and 15.90 kJ/mol, respectively, which demonstrated that the adsorption of Pb2+ by the LSDPFAC was endothermic, spontaneous and governed by physisorption.
On Robustness of the Explanatory Power of Machine Learning Models: Insights From a New Explainable AI Approach Using Sensitivity Analysis
(Wiley, American Geophysical Union, 2025-03-18) Panigrahi, Banamali; Razavi, Saman; Doig, Lorne E.; Cordell, Blanchard; Gupta, Hoshin V.; Liber, Karsten
Machine learning (ML) is increasingly considered the solution to environmental problems where limited or no physico-chemical process understanding exists. But in supporting high-stakes decisions, where the ability to explain possible solutions is key to their acceptability and legitimacy, ML can fall short. Here, we develop a method, rooted in formal sensitivity analysis, to uncover the primary drivers behind ML predictions. Unlike many methods for explainable artificial intelligence (XAI), this method (a) accounts for complex multi-variate distributional properties of data, common in environmental systems, (b) offers a global assessment of the input-output response surface formed by ML, rather than focusing solely on local regions around existing data points, and (c) is scalable and data-size independent, ensuring computational efficiency with large data sets. We apply this method to a suite of ML models predicting various water quality variables in a pilot-scale experimental pit lake. A critical finding is that subtle alterations in the design of some ML models (such as variations in random seed, functional class, hyperparameters, or data splitting) can lead to different interpretations of how outputs depend on inputs. Further, models from different ML families (decision trees, connectionists, or kernels) may focus on different aspects of the information provided by data, despite displaying similar predictive power. Overall, our results underscore the need to assess the explanatory robustness of ML models and advocate for using model ensembles to gain deeper insights into system drivers and improve prediction reliability.
The hysteretic and gatekeeping depressions model − A new model for variable connected fractions of prairie basins
(Elsevier, 2025-06) Shook, Kevin; Pomeroy, John W.
The Prairie Pothole Region of western North America has unusual hydrology and hydrography. Its level, post-glacial topography means that many drainage basins are dominated by internally drained depressions, rather than having conventional dendritic drainage networks of stream channels. Modelling the hydrology of these regions is difficult because the relationship between depressional storage and the connected fraction of a basin is hysteretic. Existing models are either computationally intensive and require high-resolution Digital Elevation Model (DEM) data which may not exist or require calibration and cannot reproduce the hysteresis between the basin connected fraction and depressional storage. The Hysteretic and Gatekeeping Depressions Model (HGDM) has been developed to simplify modelling of prairie basins with variable connected/contributing fractions. The model uses “meta” depressions to model the hysteretic responses of small depressions and a discrete model of large depressions, which cause “gatekeeping”, meaning that they prevent upstream flows from reaching the outlet until the depressions are filled. The HGDM was added to the Cold Regions Hydrological Modelling (CRHM) platform which is one of the few models that has successfully simulated land surface hydrology in the Canadian Prairies. CRHM + HGDM is tested by modelling streamflows at Smith Creek, a basin in southeastern Saskatchewan, Canada. It is demonstrated that CRHM + HGDM can reproduce the relationship between the connected/contributing fractions of sub-basins and their depressional storage at least as well as existing models. Importantly, it appears that HGDM can be used with coarse-resolution DEMs, which may permit its use in the many locations where higher-resolution data is unavailable. The simplicity and limited parameterization needs of HGDM may allow for broader representation of depressions and variable contributing area in prairie hydrology.
Insights into freeze–thaw and infiltration in seasonally frozen soils from field observations
(Vadose Zone Journal, 2025-02) Sanchez-Rodriguez, Ines; Ireson, Andrew; Brannen, Rosa; Brauner, Haley
Snowmelt infiltration into frozen soils in seasonally frozen landscapes is a critically important hydrological process, with consequences for agriculture, water resources, and flooding. The partitioning of snowmelt between infiltration and runoff in any given location and in any given year is highly uncertain. While it is intuitive to expect lower infiltration capacities in frozen soils, extensive past field research has shown that infiltration is often the dominant flux over runoff during this process, and this is attributed to infiltration into air-filled macropores. Despite this understanding, we still lack models that can predict frozen soil infiltration reliably. In this study, we examine detailed field observations from the seasonally frozen Canadian Prairies to determine the controls on soil freeze/thaw, snowmelt partitioning, and groundwater recharge. We show how soil moisture, water table depth, snow water equivalent, and air temperature are all significant and confounding factors that determine soil freezing depth and snowmelt partitioning. Plain Language Summary Infiltration of snowmelt into seasonally frozen soil plays a key role in agriculture, water supply, and flood risk. However, predicting how much snowmelt will infiltrate into the soil versus runoff is uncertain. While it seems logical that frozen soils would absorb less water, research shows infiltration often dominates due to water entering air-filled channels called macropores. Despite this, reliable models to predict frozen soil infiltration are still lacking. This study uses data from the Canadian Prairies to explore what affects soil freezing, snowmelt behavior, and groundwater recharge. Our findings highlight that soil moisture, water table depth, snow amount, and air temperature all influence soil freezing and how snowmelt is split between infiltration and runoff.
Modeling the lagged and nonlinear effects of weather conditions on abundance of Culex tarsalis mosquitoes in Saskatchewan, Western Canada using a bi-dimensional distributed lag nonlinear model
(Elsevier, 2024-12-24) Gizaw, Zemichael; Vidrio-Sahagún, Cuauhtémoc Tonatiuh; Pietroniro, Alain; Schuster Wallace, Corinne
The establishment of West Nile Virus (WNV) competent vectors continues to pose a major public health challenge in Canada, especially in the south. While studies have examined the association between weather conditions and the abundance of mosquitoes over trap weeks, there is limited research on the effects of weather conditions on the abundance of Culex tarsalis (Cx. tarsalis) mosquitoes for a lapse of time beyond the trap week in Saskatchewan, Western Canada. To address this gap, we analyzed provincially available weekly mosquito trap and co-incident meteorological station data in Saskatchewan from 2010 to 2021 using a bi-dimensional distributed lag and nonlinear model. Data indicate that 171,141 Cx. tarsalis mosquitoes were trapped across much of Saskatchewan, from 2010 to 2021. Cx. tarsalis were found to be most abundant between weeks 26 and 35 (July and August) and peaked in weeks 30 and 31. Based on the WNV-positive pools, mosquito infection rates increased from week 23 to 36. While weekly average maximum air temperatures between 20 °Cand 30 °C were associated with more Cx. tarsalis across all lags (0 – 8 weeks), higher weekly average minimum air temperatures had a strong and immediate effect that diminished over longer lags. Higher weekly average rainfall amounts (> 20 mm) were associated with fewer Cx. tarsalis mosquitoes across all lags, while average weekly rainfall between 8 and 20 mm was strongly associated with a high abundance of Cx. tarsalis mosquitoes over longer lags (5 -7 weeks). Additionally, increasing wind speed was associated with lower abundance of Cx. tarsalis across all lags. Findings identified nonlinear lag associations for weekly average maximum air temperature and rainfall, but linear associations for weekly average minimum air temperature and wind speed. Identified lags and thresholds for temperature, rainfall, and wind speed at which mosquito abundance peaked could help to inform public health authorities in timing of vector control measures to prevent WNV transmission.
Principles, barriers, and challenges of Indigenous water governance around the world
(Elsevier, 2025-01-02) Bharadwaj, Lalita; Bataebo, Sonia; Schuster Wallace, Corinne
Globally, Indigenous Nations are disproportionately faced with water challenges. This is partly because current approaches to water governance continue to systematically exclude Indigenous peoples and their worldviews from contemporary water governance structures. Given the need to reform current water governance systems to redress injustices and secure water resources for Indigenous peoples, this paper presents the findings of a scoping review designed to identify the principles, values, challenges/problems, and existing models of Indigenous water governance around the globe. Findings indicate that “water is life” is a fundamental principle of Indigenous water governance frameworks, as is “water as an interconnected whole” that forms a greater part of a community’s life and identity. The “Living Water, First Law” model and the Kistihtamahwin framework are examples of Indigenous water governance models identified. Colonization and the relegation of Indigenous knowledge remain a critical challenge to effective implementation of existing models of Indigenous water governance systems. This requires reform of contemporary water governance structures or formation of new systems that unsettle colonial legacies and privilege Indigenous worldviews and governance frameworks. These must focus on the overall health of the rivers, lakes, or freshwater entity and the holistic health of communities and be preceded by genuine nation-to-nation relationships.
Converting land use–land cover to E. coli contamination potential classes for improved management of groundwater wells: a case study in Ontario, Canada
(Springer, 2024-12-19) White, Katie; Schuster Wallace, Corinne; Dickson-Anderson, Sarah
Land use-land cover (LULC) types have been used as a proxy for Escherichia Coli (E. coli) sources and transport mechanisms. This study aims to advance the understanding of the relationship between LULC and E. coli presence in wells for the 11 major LULC categories. This represents a novel approach for assessing the broad potential for well contamination and informing groundwater management strategies. The approach combines insights gained from regression analyses conducted using a combination of large datasets with the Intergovernmental Panel on Climate Change (IPCC) method for consistent treatment of uncertainties within literature. Generalized Additive Models for Location, Shape, and Scale (GAMLSS) regression analyses were used to identify and support relationships between a large dataset of E. coli presence in wells and LULC data, identifying potential risk classes. A raster dataset for Ontario, Canada identifying areas of low to very high potential for E. coli presence in wells was created. Notably, the pastoral/agricultural LULC category was found to be in the very high-risk class, urban and aggregate mines in the high-risk class, forest in the moderate risk class, and water and grasslands in the low-risk class. However, gaps in understanding the relationship between some LULC categories and the presence of E. coli in wells remain in the disturbance, bedrock, and scrubland LULCs due to data limitations in both the study area and literature. These results provide private well users, who may lack technical expertise, with an accessible source of information on the potential for E. coli contamination.
Analyzing water uptake of apple trees using isotopic techniques in the Shandong Peninsula, China
(Elsevier, 2025-01-03) Pang, Tianze; Zhao, Ying; Poca, Maria; Wang, Jianjun; Li, Hongchen; Liu, Jinzhao
Study region The hilly area of Shandong Peninsula is a pivotal apple-producing region in China. However, the precise water sources utilized by the apple trees for transpiration remain poorly understood in this region. Study focus Here we quantify the water sources used by apple trees in this area using stable isotopic tracing methods. Through on-field studies in a representative apple orchard and subsequent isotopic assessments, the primary water sources tapped by the apple trees were identified in three plots with contrasting soil characteristics and through 5 days of sub daily sampling. New hydrological insights for the region Our results show that apple trees have a marked preference for soil water centered at the 60 cm depth, with more deep water use at plots without weathered layers. Notably, the isotopic compositions of the xylem water leaned more towards signatures of soil water, rather than immediate irrigation water or groundwater. Given the irrigation water used to be the dominant water source recharging into soil, the weak contribution of irrigation water to plant would be attributed to the high soil evaporation rates during the growth phase, which strongly alter the isotopic composition of irrigation water in shallow soil layers. These insights boosted our comprehension of water sourcing mechanisms in the sloped orchard ecosystems in the Shandong Peninsula and lay the groundwork for deeper exploration into the irrigation ratio to rainwater utilized by apple trees in comparable regions.
Observations and management implications of crop and water interactions in cold water-limited regions
(Journal of Hydrology, 2024-11) Harder, Phillip; Helgason, Warren D; Johnson, Bruce; Pomeroy, John W.
Crop and water interactions strongly influence crop production in water-limited dryland agricultural systems in cold regions, such as the Canadian Prairies. A water balance approach was used to quantify crop water use, identify the source of water and corresponding hydrological processes, and evaluate the effectiveness of management techniques to increase agricultural productivity. Detailed water balance observations for 19 site-years were collected at four sites. Crop water use was consistently greater than or equal to growing season precipitation and displayed substantial interannual variation. On average, growing season precipitation provided 66% of crop water use whilst antecedent soil moisture from water surpluses in shoulder and winter seasons and preceding wet years supplied the remainder. Up to 70% of crop water use was derived from non-growing season water sources when high precipitation winters preceded dry growing seasons. Observations of soil moisture, snow accumulation, precipitation, and evaporative fluxes showed substantial spatial and temporal variability in antecedent soil moisture contributions to crop growth, which has implications for agricultural management. The relative importance of antecedent soil water to crop growth decreased with increased growing season precipitation. The water balance observations were used to constrain the water-limited yield potential associated with the optimisation of stubble and crop residue management practices. Increasing retention of snowfall with stubble management and suppression of soil evaporation with increased crop residue cover was estimated to increase potential crop water availability on average by 20% but, depended on seasonal dynamics, ranging between 4 and 48%. These results articulate the complex interactions between cold and warm season hydrological processes that drive dryland agricultural production in Western Canada and constrain the potential for stubble and residue management practices to mitigate crop water extremes.
Prairie Wetland Drainage Infographic
(Global Water Futures: Prairie Water Project. University of Saskatchewan, 2022) Morrison, Alasdair; Whitfield, Colin; Spence, Christopher
‘Shallow or deep?’ Groundwater Infographic
(Global Water Futures: Prairie Water Project. University of Saskatchewan, 2024) Johnson, Connor; Miranda, Lauren
Biodiversity & Wetlands Infographic
(Global Water Futures: Prairie Water Project. University of Saskatchewan, 2022) Morrison, Alasdair; Clark, Bob
‘Do you know your prairie watershed?’ Infographic
(Global Water Futures: Prairie Water Project, University of Saskatchewan, 2024) Morrison, Alasdair
The Prairie ecozone has over 4000 sub-basins approximately 100 sq.km in area. We identified 7 classes of watershed, based on 35 biophysical characteristics. We use this classification to understand how water behaves on the prairies.
Integrated Hydrological and Hydraulic Modeling for River Freezing Simulation: Impacts of a Changing Climate on the Freeze-Up of the Exploits River in Newfoundland
(Springer Nature, 2024-10-12) Ghoreishi, Mohammad; Lindenschmidt, Karl-Erich; Barrette, Paul; Khan, Amir Ali
Frazil ice, a major component of winter river dynamics, poses hazards through ice jam formation, particularly in regions like Newfoundland, Canada. This study employs an integrated hydrological and river ice hydraulic modeling approach to predict future freeze-up ice jamming events in the Exploits River under climate change scenarios. Focusing on the naturally flowing lower subbasin, the study simulates streamflow and frazil ice generation by integrating HEC-HMS and RIVICE models. Climate scenarios from the Coupled Model Intercomparison Project (CMIP) phase 6 are incorporated using the delta change method. This study aims to evaluate the generation and accumulation of frazil ice and predict future trends in freeze-up ice jamming events. Our study reveals significant insights into the future dynamics of ice cover extents along the Exploits River, particularly in relation to the town of Badger. Notably, our findings indicate a trend toward shorter ice cover durations and later arrivals of the ice cover front at Badger, potentially mitigating flood risk, particularly during milder winter seasons. Moreover, in some scenarios, the projected ice cover may not even reach Badger during these milder winters, further reducing the town’s vulnerability to flooding events. This research is crucial for ensuring infrastructure resilience and community safety in regions where frazil ice dynamics play a critical role in riverine hazards.
Peering into Agricultural Rebound Phenomenon Using a Global Sensitivity Analysis Approach
(Elsevier, 2021-11) Ghoreishi, Mohammad; Sheikholeslami, Razi; Elshorbagy, Amin; Razavi, Saman; Belcher, Kenneth; Belcher, Ken
Modernizing traditional irrigation systems has long been recognized as a means to reduce water losses. However, empirical evidence shows that this practice may not necessarily reduce water use in the long run; in fact, in many cases, the converse is true—a concept known as the rebound phenomenon. This phenomenon is at the heart of a fundamental research gap in the explicit evaluation of co-evolutionary dynamics and interactions among socio-economic and hydrologic factors in agricultural systems. This gap calls for the application of systems-based methods to evaluate such dynamics. To address this gap, we use a previously developed Agent-Based Agricultural Water Demand (ABAD) model, applied to the Bow River Basin (BRB) in Canada. We perform a time-varying variance-based global sensitivity analysis (GSA) on the ABAD model to examine the individual effect of factors, as well as their joint effect, that may give rise to the rebound phenomenon in the BRB. Our results show that economic factors dominantly control possible rebounds. Although social interaction among farmers is found to be less influential than the irrigation expansion factor, its interaction effect with other factors becomes more important, indicating the highly interactive nature of the underlying socio-hydrological system. Based on the insights gained via GSA, we discuss several strategies, including community participation and water restrictions, that can be adopted to avoid the rebound phenomenon in irrigation systems. This study demonstrates that a time-varying variance-based GSA can provide a better understanding of the co-evolutionary dynamics of the socio-hydrological systems and can pave the way for better management of water resources.
Crop models and their use in assessing crop production and food security: A review
(Wiley Open Access [Commercial Publisher], Association of Applied Biologists [Society Publisher], 2023) Gavasso-Rita, Yohanne Larissa; Papalexiou, Simon Michael; Li, Yanping; Elshorbagy, Amin; Li, Zhenhua; Schuster Wallace, Corinne
Agriculture is directly related to food security as it determines the global food supply. Research in agriculture to predict crop productivity and losses helps avoid high food demand with little supply and price spikes. Here, we review ten crop models and one intercomparison project used for simulating crop growth and productivity under various impacts from soil–crop– atmosphere interactions. The review outlines food security and production assessments using numerical models for maize, wheat, and rice production. A summary of reviewed studies shows the following: (1) model ensembles provide smaller modeling errors compared to single models, (2) single models show better results when coupled with other types of models, (3) the ten reviewed crop models had improvements over the years and can accurately predict crop growth and yield for most of the locations, management conditions, and genotypes tested, (4) APSIM and DSSAT are fast and reliable in assessing broader output variables, (5) AquaCrop is indicated to investigate water footprint, quality and use efficiency in rainfed and irrigated systems, (6) all models assess nitrogen dynamics and use efficiency efficiently, excluding AquaCrop and WOFOST, (7) JULES specifies in evaluating food security vulnerability, (8) ORYZA is the main crop model used to evaluate paddy rice production, (9) grain filling is usually assessed with APSIM, DAISY, and DSSAT, and (10) the ten crop models can be used as tools to evaluate food production, availability, and security.
Developing spring wheat in the Noah-MP land surface model (v4.4) for growing season dynamics and responses to temperature stress
(European Geosciences Union [Society Publisher], Copernicus Publications [Commercial Publisher], 2023) Zhang, Zhe; Li, Yanping; Chen, Fei; Harder, Philip; Helgason, Warren D.; Famiglietti, James; Valayamkunnath, Prasanth; He, Cenlin; Li, Zhenhua
The US Northern Great Plains and the Canadian Prairies are known as the world’s breadbaskets for their large spring wheat production and exports to the world. It is essential to accurately represent spring wheat growing dynamics and final yield and improve our ability to predict food production under climate change. This study attempts to incorporate spring wheat growth dynamics into the Noah-MP crop model for a long time period (13 years) and fine spatial scale (4 km). The study focuses on three aspects: (1) developing and calibrating the spring wheat model at a point scale, (2) applying a dynamic planting and harvest date to facilitate large-scale simulations, and (3) applying a temperature stress function to assess crop responses to heat stress amid extreme heat. Model results are evaluated using field observations, satellite leaf area index (LAI), and census data from Statistics Canada and the United States Department of Agriculture (USDA). Results suggest that incorporating a dynamic planting and harvest threshold can better constrain the growing season, especially the peak timing and magnitude of wheat LAI, as well as obtain realistic yield compared to prescribing a static province/state-level map. Results also demonstrate an evident control of heat stress upon wheat yield in three Canadian Prairies Provinces, which are reasonably captured in the new temperature stress function. This study has important implications in terms of estimating crop yields, modeling the land–atmosphere interactions in agricultural areas, and predicting crop growth responses to increasing temperatures amidst climate change.
Poor correlation between large-scale environmental flow violations and freshwater biodiversity: implications for water resource management and the freshwater planetary boundary
(2022) Mohan, Chinchu; Gleeson, Tom; Famiglietti, James S.; Virkki, Vili; Kummu, Matti; Porkka, Miina; Wang-Erlandsson, Lan; Huggins, Xander; Gerten, Dieter; Jähnig, Sonja C.
The freshwater ecosystems around the world are degrading, such that maintaining environmental flow1 (EF) in river networks is critical to their preservation. The relationship between streamflow alterations (subsequent EF violations2) and the freshwater biodiversity response is well established at the scale of stream reaches or small basins (~<100 km2). However, it is unclear if this relationship is robust at larger scales, even though there are large-scale initiatives to legalize the EF requirement. Moreover, EFs have been used in assessing a planetary boundary3 for freshwater. Therefore, this study intends to conduct an exploratory evaluation of the relationship between EF violation and freshwater biodiversity at globally aggregated scales and for freshwater ecoregions. Four EF violation indices (severity, frequency, probability of shifting to a violated state, and probability of staying violated) and seven independent freshwater biodiversity indicators (calculated from observed biota data) were used for correlation analysis. No statistically significant negative relationship between EF violation and freshwater biodiversity was found at global or ecoregion scales. These findings imply the need for a holistic bio-geo-hydro-physical approach in determining the environmental flows. While our results thus suggest that streamflow and EF may not be the only determinant of freshwater biodiversity at large scales, they do not preclude the existence of relationships at smaller scales or with more holistic EF methods (e.g., including water temperature, water quality, intermittency, connectivity, etc.) or with other biodiversity data or metrics.
Hotspots for social and ecological impacts from freshwater stress and storage loss
(Nature Portfolio, 2022) Huggins, Xander; Gleeson, Tom; Kummu, Matti; Zipper, Sam; Wada, Yoshihide; Troy, Tara; Famiglietti, James S.
Humans and ecosystems are deeply connected to, and through, the hydrological cycle. However, impacts of hydrological change on social and ecological systems are infrequently evaluated together at the global scale. Here, we focus on the potential for social and ecological impacts from freshwater stress and storage loss. We find basins with existing freshwater stress are drying (losing storage) disproportionately, exacerbating the challenges facing the water stressed versus non-stressed basins of the world. We map the global gradient in social-ecological vulnerability to freshwater stress and storage loss and identify hotspot basins for prioritization (n = 168). These most-vulnerable basins encompass over 1.5 billion people, 17% of global food crop production, 13% of global gross domestic product, and hundreds of significant wetlands. There are thus substantial social and ecological benefits to reducing vulnerability in hotspot basins, which can be achieved through hydro-diplomacy, social adaptive capacity building, and integrated water resources management practices.
Diagnosing Hydrological Process Controls in Streamflow Generation and Variability in a 1 Glacierized Alpine Headwater Basin
(Wiley Online Library, 2022) Aubry-Wake, Caroline; Pradhananga, Dhiraj; Pomeroy, John
Mountain glacierized headwaters are currently witnessing a transient shift in their hydrological and glaciological systems in response to rapid climate change. To characterize these changes, a robust understanding of the hydrological processes operating in the basin and their interactions is needed. Such an investigation was undertaken in the Peyto Glacier Research Basin, Canadian Rockies over 32 years (1988–2020). A distributed, physically based, uncalibrated glacier hydrology model was developed using the modular, object-oriented Cold Region Hydrological Modelling Platform to simulate both on and off-glacier high mountain processes and streamflow generation. The hydrological processes that generate streamflow from this alpine basin are characterized by substantial inter-annual variability over the 32 years. Snowmelt runoff always provided the largest fraction of annual streamflow (44% to 89%), with smaller fractional contributions occurring in higher streamflow years. Ice melt runoff provided 10% to 45% of annual streamflow volume, with higher fractions associated with higher flow years. Both rainfall and firn melt runoff contributed less than 13% of annual streamflow. Years with high streamflow were on average 1.43°C warmer than low streamflow years, and higher streamflow years had lower seasonal snow accumulation, earlier snowmelt and higher summer rainfall than years with lower streamflow. Greater ice exposure in warmer, low snowfall (high rainfall) years led to greater streamflow generation. The understanding gained here provides insight into how future climate and increased meteorological variability may impact glacier meltwater contributions to streamflow and downstream water availability as alpine glaciers continue to retreat.

Browse

Recent Submissions