Limitations of Water Resources Infrastructure for Reducing Community Vulnerabilities to Extremes and Uncertainty of Flood and Drought

Debate and deliberation surrounding climate change has shifted from mitigation toward adaptation, with much of the adaptation focus centered on adaptive practices, and infrastructure development. However, there is little research assessing expected impacts, potential benefits, and design challenges that exist for reducing vulnerability to expected climate impacts. The uncertainty of design requirements and associated government policies, and social structures that reflect observed and projected changes in the intensity, duration, and frequency of water-related climate events leaves communities vulnerable to the negative impacts of potential flood and drought. The results of international research into how agricultural infrastructure features in current and planned adaptive capacity of rural communities in Argentina, Canada, and Colombia indicate that extreme hydroclimatic events, as well as climate variability and unpredictability are important for understanding and responding to community vulnerability. The research outcomes clearly identify the need to deliberately plan, coordinate, and implement infrastructures that support community resiliency.Fil: McMartin, Dena W.. University of Regina; CanadáFil: Hernani Merino, Bruno H.. University of Regina; CanadáFil: Bonsal, Barrie. Environment Canada; CanadáFil: Hurlbert, Margot. University of Regina; CanadáFil: Villalba, Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Regional de Investigaciones Cientifícas y Tecnológicas; ArgentinaFil: Ocampo, Olga L.. Universidad Autónoma de Manizales; ColombiaFil: Upegui, Jorge Julián Vélez. Universidad Nacional de Colombia; ColombiaFil: Poveda, Germán. Universidad Nacional de Colombia; ColombiaFil: Sauchyn, David J.. University of Regina; Canad

Comparative Therapeutic Effects of Velaglucerase Alfa and Imiglucerase in a Gaucher Disease Mouse Model

Gaucher disease type 1 is caused by the defective activity of the lysosomal enzyme, acid β-glucosidase (GCase). Regular infusions of purified recombinant GCase are the standard of care for reversing hematologic, hepatic, splenic, and bony manifestations. Here, similar in vitro enzymatic properties, and in vivo pharmacokinetics and pharmacodynamics (PK/PD) and therapeutic efficacy of GCase were found with two human GCases, recombinant GCase (CHO cell, imiglucerase, Imig) and gene-activated GCase (human fibrosarcoma cells, velaglucerase alfa, Vela), in a Gaucher mouse, D409V/null. About 80+% of either enzyme localized to the liver interstitial cells and <5% was recovered in spleens and lungs after bolus i.v. injections. Glucosylceramide (GC) levels and storage cell numbers were reduced in a dose (5, 15 or 60 U/kg/wk) dependent manner in livers (60–95%) and in spleens (∼10–30%). Compared to Vela, Imig (60 U/kg/wk) had lesser effects at reducing hepatic GC (p = 0.0199) by 4 wks; this difference disappeared by 8 wks when nearly WT levels were achieved by Imig. Anti-GCase IgG was detected in GCase treated mice at 60 U/kg/wk, and IgE mediated acute hypersensitivity and death occurred after several injections of 60 U/kg/wk (21% with Vela and 34% with Imig). The responses of GC levels and storage cell numbers in Vela- and Imig-treated Gaucher mice at various doses provide a backdrop for clinical applications and decisions

Flood and drought hydrologic monitoring: the role of model parameter uncertainty

Land surface modeling, in conjunction with numerical weather forecasting and satellite remote sensing, is playing an increasing role in global monitoring and prediction of extreme hydrologic events (i.e., floods and droughts). However, uncertainties in the meteorological forcings, model structure, and parameter identifiability limit the reliability of model predictions. This study focuses on the latter by assessing two potential weaknesses that emerge due to limitations in our global runoff observations: (1) the limits of identifying model parameters at coarser timescales than those at which the extreme events occur, and (2) the negative impacts of not properly accounting for model parameter equifinality in the predictions of extreme events. To address these challenges, petascale parallel computing is used to perform the first global-scale, 10 000 member ensemble-based evaluation of plausible model parameters using the VIC (Variable Infiltration Capacity) land surface model, aiming to characterize the impact of parameter identifiability on the uncertainty in flood and drought predictions. Additionally, VIC's global-scale parametric sensitivities are assessed at the annual, monthly, and daily timescales to determine whether coarse-timescale observations can properly constrain extreme events. Global and climate type results indicate that parameter uncertainty remains an important concern for predicting extreme events even after applying monthly and annual constraints to the ensemble, suggesting a need for improved prior distributions of the model parameters as well as improved observations. This study contributes a comprehensive evaluation of land surface modeling for global flood and drought monitoring and suggests paths forward to overcome the challenges posed by parameter uncertainty

An initial assessment of SMAP soil moisture retrievals using high-resolution model simulations and in situ observations

At the end of its first year of operation, we compare soil moisture retrievals from the Soil Moisture Active Passive (SMAP) mission to simulations from a land surface model with meteorological forcing downscaled from observations/reanalysis and in situ observations from sparse monitoring networks within continental United States (CONUS). The radar failure limits the duration of comparisons for the active and combined products (~3 months). Nevertheless, the passive product compares very well against in situ observations over CONUS. On average, SMAP compares to the in situ data even better than the land surface model and provides significant added value on top of the model and thus good potential for data assimilation. At large scale, SMAP is in good agreement with the model in most of CONUS with less-than-expected degradation over mountainous areas. Lower correlation between SMAP and the model is seen in the forested east CONUS and significantly lower over the Canadian boreal forests

Multi-site evaluation of terrestrial evaporation models using FLUXNET data

We evaluated the performance of four commonly applied land surface evaporation models using a high-quality dataset of selected FLUXNET towers. The models that were examined include an energy balance approach (Surface Energy Balance System; SEBS), a combination-type technique (single-source Penman–Monteith; PM), a complementary method (advection-aridity; AA) and a radiation based approach (modified Priestley–Taylor; PT-JPL). Twenty FLUXNET towers were selected based upon satisfying stringent forcing data requirements and representing a wide range of biomes. These towers encompassed a number of grassland, cropland, shrubland, evergreen needleleaf forest and deciduous broadleaf forest sites. Based on the mean value of the Nash–Sutcliffe efficiency (NSE) and the root mean squared difference (RMSD), the order of overall performance of the models from best to worst were: ensemble mean of models (0.61, 64), PT-JPL (0.59, 66), SEBS (0.42, 84), PM (0.26, 105) and AA (0.18, 105) [statistics stated as (NSE, RMSD in W m−2)]. Although PT-JPL uses a relatively simple and largely empirical formulation of the evaporative process, the technique showed improved performance compared to PM, possibly due to its partitioning of total evaporation (canopy transpiration, soil evaporation, wet canopy evaporation) and lower uncertainties in the required forcing data. The SEBS model showed low performance over tall and heterogeneous canopies, which was likely a consequence of the effects of the roughness sub-layer parameterization employed in this scheme. However, SEBS performed well overall. Relative to PT-JPL and SEBS, the PM and AA showed low performance over the majority of sites, due to their sensitivity to the parameterization of resistances. Importantly, it should be noted that no single model was consistently best across all biomes. Indeed, this outcome highlights the need for further evaluation of each model's structure and parameterizations to identify sensitivities and their appropriate application to different surface types and conditions. It is expected that the results of this study can be used to inform decisions regarding model choice for water resources and agricultural management, as well as providing insight into model selection for global flux monitoring efforts

Validation of SMAP soil moisture for the SMAPVEX15 field campaign using a hyper-resolution model

Accurate global mapping of soil moisture is the goal of the Soil Moisture Active Passive (SMAP) mission, which is expected to improve the estimation of water, energy, and carbon exchanges between the land and the atmosphere. Like other satellite products, the SMAP soil moisture retrievals need to be validated, with the validation relying heavily on in situ measurements. However, a one-to-one comparison is ill advised due to the spatial mismatch of the large SMAP footprint (∼40 km) and the point scale in situ measurements. This study uses a recently developed hyper-resolution land surface model—HydroBlocks—as a tool to upscale in situ soil moisture measurements for the SMAPVEX15 (SMAP Validation Experiment 2015) field campaign during 2–18 August 2015. Calibrated against in situ observation, HydroBlocks shows a satisfactory Kling-Gupta efficiency (KGE) of 0.817 and RMSE of 0.019 m /m for the calibration period. These results indicate that HydroBlocks can be used to upscale in situ measurements for this site. Different from previous studies, here in situ measurements are upscaled using a land surface model without bias correction. The upscaled soil moisture is then used to evaluate SMAP (passive) soil moisture products. The comparison of the upscaled network to SMAP shows that the retrievals are generally able to capture the areal-averaged soil moisture temporal variations. However, SMAP appears to be oversensitive to summer precipitation. We expect these findings can be used to improve the SMAP soil moisture product and thus facilitate its usage in studying the water, energy, and carbon cycles. 3

Validation of SMAP soil moisture for the SMAPVEX15 field campaign using a hyper-resolution model

Accurate global mapping of soil moisture is the goal of the Soil Moisture Active Passive (SMAP) mission, which is expected to improve the estimation of water, energy, and carbon exchanges between the land and the atmosphere. Like other satellite products, the SMAP soil moisture retrievals need to be validated, with the validation relying heavily on in situ measurements. However, a one-to-one comparison is ill advised due to the spatial mismatch of the large SMAP footprint (∼40 km) and the point scale in situ measurements. This study uses a recently developed hyper-resolution land surface model—HydroBlocks—as a tool to upscale in situ soil moisture measurements for the SMAPVEX15 (SMAP Validation Experiment 2015) field campaign during 2–18 August 2015. Calibrated against in situ observation, HydroBlocks shows a satisfactory Kling-Gupta efficiency (KGE) of 0.817 and RMSE of 0.019 m3/m3 for the calibration period. These results indicate that HydroBlocks can be used to upscale in situ measurements for this site. Different from previous studies, here in situ measurements are upscaled using a land surface model without bias correction. The upscaled soil moisture is then used to evaluate SMAP (passive) soil moisture products. The comparison of the upscaled network to SMAP shows that the retrievals are generally able to capture the areal-averaged soil moisture temporal variations. However, SMAP appears to be oversensitive to summer precipitation. We expect these findings can be used to improve the SMAP soil moisture product and thus facilitate its usage in studying the water, energy, and carbon cycles

Governance of water-energy-food nexus: A social network analysis approach to understanding agency behaviour

Research seeks to treat each resource embedded in the nexus as connected to the other resources. This approach is unique from other natural resource research agendas where the primary focus is on system efficiencies or examinations of a single resource. The nexus by emphasizing trade-offs places a premium on coordination. From a governance perspective coordination is not limited to decisions involving finances and allocation of trained human resources among different agencies organized both vertically and horizontally within a multi-level governance framework. Coordination could also be extended to include uses of data between public agencies, private sector and individuals. Due to nexus interconnectivity, we suggest here that social network analysis (SNA) is an appropriate tool that can divulge and highlight the relational complexities that exist within the nexus and among stakeholders that work with the singular elements of the nexus. We suggest that in the cases of organisations with a high institutional capacity by means of expertise, resources, and other assets, the Water-Energy-Food (WEF) network will be highly connected between resource areas in the overall network. Two network tie characteristics—density and centrality—are particularly important to understand a critical mass of interests within a multi-level governance framework. The paper concludes by arguing for the organisation of data covering different dimensions of the Water-Energy-Food nexus through the mechanism of an observatory that could potentially improve our understanding of thresholds of environmental resource use and the incentives required for public agencies to act in support of sustainable development