Comparison of three data-driven techniques in modelling the evapotranspiration process.

Evapotranspiration is one of the main components of the hydrological cycle as it accounts for more than two-thirds of the precipitation losses at the global scale. Reliable estimates of actual evapotranspiration are crucial for effective watershed modelling and water resource management, yet direct measurements of the evapotranspiration losses are difficult and expensive. This research explores the utility and effectiveness of data-driven techniques in modelling actual evapotranspiration measured by an eddy covariance system. The authors compare the Evolutionary Polynomial Regression (EPR) performance to Artificial Neural Networks (ANNs) and Genetic Programming (GP). Furthermore, this research investigates the effect of previous states (time lags) of the meteorological input variables on characterizing actual evapotranspiration. The models developed using the EPR, based on the two case studies at the Mildred Lake mine, AB, Canada provided comparable performance to the models of GP and ANNs. Moreover, the EPR provided simpler models than those developed by the other data-driven techniques, particularly in one of the case studies. The inclusion of the previous states of the input variables slightly enhanced the performance of the developed model, which in turn indicates the dynamic nature of the evapotranspiration process

Uncertainties In Future Projections Of Extreme Rainfall: The Role Of Climate Model, Emission Scenario And Randomness

Climate change has resulted in substantial variations in annual extreme rainfall quantiles in different durations and return periods. Predicting the future changes in extreme rainfall quantiles is essential for various water resources design, assessment, and decision making purposes. Current Predictions of future rainfall extremes, however, exhibit large uncertainties. According to extreme value theory, rainfall extremes are rather random variables, with changing distributions around different return periods; therefore there are uncertainties even under current climate conditions. Regarding future condition, our large-scale knowledge is obtained using global climate models, forced with certain emission scenarios. There are widely known deficiencies with climate models, particularly with respect to precipitation projections. There is also recognition of the limitations of emission scenarios in representing the future global change. Apart from these large-scale uncertainties, the downscaling methods also add uncertainty into estimates of future extreme rainfall when they convert the larger-scale projections into local scale. The aim of this research is to address these uncertainties in future projections of extreme rainfall of different durations and return periods. We plugged 3 emission scenarios with 2 global climate models and used LARS-WG, a well-known weather generator, to stochastically downscale daily climate models’ projections for the city of Saskatoon, Canada, by 2100. The downscaled projections were further disaggregated into hourly resolution using our new stochastic and non-parametric rainfall disaggregator. The extreme rainfall quantiles can be consequently identified for different durations (1-hour, 2-hour, 4-hour, 6-hour, 12-hour, 18-hour and 24-hour) and return periods (2-year, 10-year, 25-year, 50-year, 100-year) using Generalized Extreme Value (GEV) distribution. By providing multiple realizations of future rainfall, we attempt to measure the extent of total predictive uncertainty, which is contributed by climate models, emission scenarios, and downscaling/disaggregation procedures. The results show different proportions of these contributors in different durations and return periods

Reconstruction Of Paleo-Hydrologic Data For Vulnerability Assessment Of Water Resources Systems

Tree-ring chronologies are a rich source of information of past climate-driven non-stationarities in hydrologic variables. They are typically directly related to available water in respective years, thereby providing a basis for paleo-hydrology reconstruction. This study investigates the time series of tree-ring chronologies, with the objective of identifying the spatiotemporal patterns and extents of non-stationarities, which are essentially representations of past “climate changes”. This study also generates ensembles of moving-average streamflow time series for the centuries prior to the period of observational record. The major headwater tributaries of the Saskatchewan River basin (SaskRB), the main source of surface water in the Canadian Prairie Provinces, are used as the case study. This extended abstract gives a brief summary of the methodology and some examples of the results. The analyses and results show how the reconstruction of paleo-hydrology broadens the understanding of hydrologic characteristics of a basin beyond the limited observational records, and therefore, provides a basis for more reliable assessment and management of available water resources

Topography- and nightlight-based national flood risk assessment in Canada

Abstract. In Canada, flood analysis and water resource management, in general, are tasks conducted at the provincial level; therefore, unified national-scale approaches to water-related problems are uncommon. In this study, a national-scale flood risk assessment approach is proposed and developed. The study focuses on using global and national datasets available with various resolutions to create flood risk maps. First, a flood hazard map of Canada is developed using topography-based parameters derived from digital elevation models, namely, elevation above nearest drainage (EAND) and distance from nearest drainage (DFND). This flood hazard mapping method is tested on a smaller area around the city of Calgary, Alberta, against a flood inundation map produced by the city using hydraulic modelling. Second, a flood exposure map of Canada is developed using a land-use map and the satellite-based nightlight luminosity data as two exposure parameters. Third, an economic flood risk map is produced, and subsequently overlaid with population density information to produce a socioeconomic flood risk map for Canada. All three maps of hazard, exposure, and risk are classified into five classes, ranging from very low to severe. A simple way to include flood protection measures in hazard estimation is also demonstrated using the example of the city of Winnipeg, Manitoba. This could be done for the entire country if information on flood protection across Canada were available. The evaluation of the flood hazard map shows that the topography-based method adopted in this study is both practical and reliable for large-scale analysis. Sensitivity analysis regarding the resolution of the digital elevation model is needed to identify the resolution that is fine enough for reliable hazard mapping, but coarse enough for computational tractability. The nightlight data are found to be useful for exposure and risk mapping in Canada; however, uncertainty analysis should be conducted to investigate the effect of the overglow phenomenon on flood risk mapping

National water, food, and trade modeling framework: The case of Egypt

This paper introduces a modeling framework for the analysis of real and virtual water flows at national scale. The framework has two components: (1) a national water model that simulates agricultural, industrial and municipal water uses, and available water and land resources; and (2) an international virtual water trade model that captures national virtual water exports and imports related to trade in crops and animal products. This National Water, Food & Trade (NWFT) modeling framework is applied to Egypt, a water-poor country and the world's largest importer of wheat. Egypt's food and water gaps and the country's food (virtual water) imports are estimated over a baseline period (1986–2013) and projected up to 2050 based on four scenarios. Egypt's food and water gaps are growing rapidly as a result of steep population growth and limited water resources. The NWFT modeling framework shows the nexus of the population dynamics, water uses for different sectors, and their compounding effects on Egypt's food gap and water self-sufficiency. The sensitivity analysis reveals that for solving Egypt's water and food problem non-water-based solutions like educational, health, and awareness programs aimed at lowering population growth will be an essential addition to the traditional water resources development solution. Both the national and the global models project similar trends of Egypt's food gap. The NWFT modeling framework can be easily adapted to other nations and regions

A stochastic reconstruction framework for analysis of water resource system vulnerability to climate-induced changes in river flow regime

Assessments of potential impacts of climate change on water resources systems are generally based on the use of downscaled climate scenarios to force hydrological and water resource systems models and hence quantify potential changes in system response. This approach, however, has several limitations. The uncertainties in current climate and hydrological models can be large, such analyses are rapidly outdated as new scenarios become available, and limited insight into system response is obtained. Here, we propose an alternative methodology in which system vulnerability is analyzed directly as a function of the potential variations in flow characteristics. We develop a stochastic reconstruction framework that generates a large ensemble of perturbed flow series at the local scale to represent a range of potential flow responses to climate change. From a theoretical perspective, the proposed reconstruction scheme can be considered as an extension of both the conventional resampling and the simple delta-methods. By the use of a two-parameter representation of regime change (i.e., the shift in the timing of the annual peak and the shift in the annual flow volume), system vulnerability can be visualized in a two-dimensional map. The methodology is applied to the current water resource system in southern Alberta, Canada, to explore the system's vulnerability to potential changes in the streamflow regime. Our study shows that the system is vulnerable to the expected decrease in annual flow volume, particularly when it is combined with an earlier annual peak. Under such conditions, adaptation will be required to return the system to the feasible operational mode. © 2013. American Geophysical Union. All Rights Reserved

Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan

“Panta Rhei – Everything Flows” is the science plan for the International Association of Hydrological Sciences scientific decade 2013–2023. It is founded on the need for improved understanding of the mutual, two-way interactions occurring at the interface of hydrology and society, and their role in influencing future hydrologic system change. It calls for strategic research effort focussed on the delivery of coupled, socio-hydrologic models. In this paper we explore and synthesize opportunities and challenges that socio-hydrology present for data-driven modelling. We highlight the potential for a new era of collaboration between data-driven and more physically-based modellers that should improve our ability to model and manage socio-hydrologic systems. Crucially, we approach data-driven, conceptual and physical modelling paradigms as being complementary rather than competing; positioning them along a continuum of modelling approaches that reflects the relative extent to which hypotheses and / or data are available to inform the model development process

Adaptation of water resources systems to changing society and environment: a statement by the International Association of Hydrological Sciences

Hydrol. Sci. J.-J. Sci. Hydrol.ISI Document Delivery No.: EB2CDTimes Cited: 0Cited Reference Count: 153Ceola, Serena Montanari, Alberto Krueger, Tobias Dyer, Fiona Kreibich, Heidi Westerberg, Ida Carr, Gemma Cudennec, Christophe Elshorbagy, Amin Savenije, Hubert Van der Zaag, Pieter Rosbjerg, Dan Aksoy, Hafzullah Viola, Francesco Petrucci, Guido MacLeod, Kit Croke, Barry Ganora, Daniele Hermans, Leon Polo, Maria J. Xu, Zongxue Borga, Marco Helmschrot, Jorg Toth, Elena Ranzi, Roberto Castellarin, Attilio Hurford, Anthony Brilly, Mitija Viglione, Alberto Bloeschl, Guenter Sivapalan, Murugesu Domeneghetti, Alessio Marinelli, Alberto Di Baldassarre, GiulianoPeople Programme (Marie Curie Actions) of the European Union [329762]; IRI THESys; German Excellence Initiative; EU [603587]IW acknowledges the support of the People Programme (Marie Curie Actions) of the European Union's 7th Framework Programme FP7/2007-2013/(grant agreement no. 329762). TK is funded, through IRI THESys, by the German Excellence Initiative. SC, AM, AC, and ET acknowledge financial support from the EU funded project SWITCHON (603587).Taylor & francis ltdAbingdonWe explore how to address the challenges of adaptation of water resources systems under changing conditions by supporting flexible, resilient and low-regret solutions, coupled with on-going monitoring and evaluation. This will require improved understanding of the linkages between biophysical and social aspects in order to better anticipate the possible future co-evolution of water systems and society. We also present a call to enhance the dialogue and foster the actions of governments, the international scientific community, research funding agencies and additional stakeholders in order to develop effective solutions to support water resources systems adaptation. Finally, we call the scientific community to a renewed and unified effort to deliver an innovative message to stakeholders. Water science is essential to resolve the water crisis, but the effectiveness of solutions depends, inter alia, on the capability of scientists to deliver a new, coherent and technical vision for the future development of water systems