Accurate characterization of precipitation P at subdaily temporal resolution is important for a wide range of hydrological applications, yet large-scale gridded observational datasets primarily ...contain daily total P. Unfortunately, a widely used deterministic approach that disaggregates P uniformly over the day grossly mischaracterizes the diurnal cycle of P, leading to potential biases in simulated runoff Q. Here we present Precipitation Isosceles Triangle (PITRI), a two-parameter deterministic approach in which the hourly hyetograph is modeled with an isosceles triangle with prescribed duration and time of peak intensity. Monthly duration and peak time were derived from meteorological observations at U.S. Climate Reference Network (USCRN) stations and extended across the United States, Mexico, and southern Canada at 6-km resolution via linear regression against historical climate statistics. Across the USCRN network (years 2000–13), simulations using the Variable Infiltration Capacity (VIC) model, driven by P disaggregated via PITRI, yielded nearly unbiased estimates of annual Q relative to simulations driven by observed P. In contrast, simulations using the uniform method had a Q bias of 211%, through overestimating canopy evaporation and underestimating throughfall. One limitation of the PITRI approach is a potential bias in snow accumulation when a high proportion of P falls on days with a mix of temperatures above and below freezing, for which the partitioning of P into rain and snow is sensitive to event timing within the diurnal cycle. Nevertheless, the good overall performance of PITRI suggests that a deterministic approach may be sufficiently accurate for large-scale hydrologic applications.
Rapid growth in the food-energy-water (FEW) nexus literature calls for an assessment of the trajectory and impacts of this scholarship to identify key themes and future research directions. In this ...paper, we report on a bibliometric analysis of this literature that focuses on (1) examining publication trends and geographic focus of research, (2) identifying research hotspots and emerging themes, (3) assessing the integrated nature of research, and (4) reflecting on major developments and ways forward. We used Elsevier’s SCOPUS database to search for publications from January 2011 to May 2018 on the FEW nexus, and analyzed the final sample of 257 publications using BibExcel and Vosviewer software tools. The analysis showed steady growth in publications since 2011 with a sharp upturn in 2015 and 2016, coinciding with major funding calls. Thematic analysis of abstracts revealed a strong focus on quantitative resource interlinkages with limited attention to qualitative institutional capacities and intersectoral governance challenges. Term co-occurrence network map showed the term “investment” connected with a large number of frequently cited terms, while the term “governance” demonstrated much weaker links. We reflect on how these findings may help us better understand and address the enduring challenge of transitioning from nexus thinking to action.
This work addresses the impact of climate change on the hydrology of a
catchment in the Mediterranean, a region that is highly susceptible to
variations in rainfall and other components of the water ...budget. The
assessment is based on a comparison of responses obtained from five
hydrologic models implemented for the Rio Mannu catchment in southern
Sardinia (Italy). The examined models – CATchment HYdrology (CATHY), Soil
and Water Assessment Tool (SWAT), TOPographic Kinematic APproximation and
Integration (TOPKAPI), TIN-based Real time Integrated Basin Simulator
(tRIBS), and WAter balance SImulation Model (WASIM) – are all distributed
hydrologic models but differ greatly in their representation of terrain
features and physical processes and in their numerical complexity. After
calibration and validation, the models were forced with bias-corrected,
downscaled outputs of four combinations of global and regional climate models
in a reference (1971–2000) and future (2041–2070) period under a single
emission scenario. Climate forcing variations and the structure of the
hydrologic models influence the different components of the catchment
response. Three water availability response variables – discharge, soil
water content, and actual evapotranspiration – are analyzed. Simulation
results from all five hydrologic models show for the future period decreasing
mean annual streamflow and soil water content at 1 m depth. Actual
evapotranspiration in the future will diminish according to four of the five
models due to drier soil conditions. Despite their significant differences,
the five hydrologic models responded similarly to the reduced precipitation
and increased temperatures predicted by the climate models, and lend strong
support to a future scenario of increased water shortages for this region of
the Mediterranean basin. The multimodel framework adopted for this study
allows estimation of the agreement between the five hydrologic models and
between the four climate models. Pairwise comparison of the climate and
hydrologic models is shown for the reference and future periods using a
recently proposed metric that scales the Pearson correlation coefficient with
a factor that accounts for systematic differences between datasets. The
results from this analysis reflect the key structural differences between the
hydrologic models, such as a representation of both vertical and lateral
subsurface flow (CATHY, TOPKAPI, and tRIBS) and a detailed treatment of
vegetation processes (SWAT and WASIM).
Evaluating the propagation of errors associated with ensemble quantitative precipitation forecasts (QPFs) into the ensemble streamflow response is important to reduce uncertainty in operational flow ...forecasting. In this paper, a multifractal rainfall downscaling model is coupled with a fully distributed hydrological model to create, under controlled conditions, an extensive set of synthetic hydrometeorological events, assumed as observations. Subsequently, for each event, flood hindcasts are simulated by the hydrological model using three ensembles of QPFs—one reliable and the other two affected by different kinds of precipitation forecast errors—generated by the downscaling model. Two verification tools based on the verification rank histogram and the continuous ranked probability score are then used to evaluate the characteristics of the correspondent three sets of ensemble streamflow forecasts. Analyses indicate that the best forecast accuracy of the ensemble streamflows is obtained when the reliable ensemble QPFs are used. In addition, results underline (i) the importance of hindcasting to create an adequate set of data that span a wide range of hydrometeorological conditions and (ii) the sensitivity of the ensemble streamflow verification to the effects of basin initial conditions and the properties of the ensemble precipitation distributions. This study provides a contribution to the field of operational flow forecasting by highlighting a series of requirements and challenges that should be considered when hydrologic ensemble forecasts are evaluated.
Demonstrating the utility of satellite‐based soil moisture (θ) products for hydrologic modeling at high resolution is a critical component of mission design. In this study, we utilize aircraft and ...ground θdata collected during the SMEX04 experiment in Sonora (Mexico) to compare two downscaling frameworks using C‐band and L‐band sensors. We show that the L‐band framework, which mimics the disaggregation of SMAP products, has considerably better performance than the C‐band framework simulating the downscaling of AMSR‐E. Disaggregated L‐bandθ fields are able to characterize with reasonable accuracy the θvariability at multiple extent scales, including the SMAP footprint and the catchment scale, and along an elevation transect. We then test the utility of coarse and downscaled C‐ and L‐bandθestimates for hydrologic simulations through data assimilation experiments using a distributed hydrologic model. Results reveal that the model prognostic capability is significantly enhanced when using L‐bandθfields at the SMAP scale and, to a greater extent, when downscaled L‐bandθfields are assimilated. L‐band data assimilation leads to higher model fidelity relative to ground data as well as more realistic soil moisture patterns at the catchment scale. This study indicates the potential value of satellite‐based L‐band sensors for hydrologic modeling when coupled with a statistical downscaling algorithm.
Key Points
Downscaled L‐band SM products are more accurate than C‐band in a semiarid site
Downscaled L‐band SM capture small‐scale variability within multiple extents
Assimilation of downscaled L‐band SM products improves hydrologic simulations
•Available rainfall data are characterized by different time resolution, “ta”•A database involving metadata from many geographic areas is presented.•The “ta” history of rainfall data in a variety of ...rain gauges is reconstructed.•The registration methods of the rainfall data changed over the years.•Currently about 50% of rain gauge stations provide data with any “ta”
Collected rainfall records by gauges lead to key forcings in most hydrological studies. Depending on sensor type and recording systems, such data are characterized by different time-resolutions (or temporal aggregations), ta. We present an historical analysis of the time-evolution of ta based on a large database of rain gauge networks operative in many study areas. Globally, ta data were collected for 25,423 rain gauge stations across 32 geographic areas, with larger contributions from Australia, USA, Italy and Spain. For very old networks early recordings were manual with coarse time-resolution, typically daily or sometimes monthly. With a few exceptions, mechanical recordings on paper rolls began in the first half of the 20th century, typically with ta of 1 h or 30 min. Digital registrations started only during the last three decades of the 20th century. This short period limits investigations that require long time-series of sub-daily rainfall data, e.g, analyses of the effects of climate change on short-duration (sub-hourly) heavy rainfall. In addition, in the areas with rainfall data characterized for many years by coarse time-resolutions, annual maximum rainfall depths of short duration can be potentially underestimated and their use would produce errors in the results of successive applications. Currently, only 50% of the stations provide useful data at any time-resolution, that practically means ta = 1 min. However, a significant reduction of these issues can be obtained through the information content of the present database. Finally, we suggest an integration of the database by including additional rain gauge networks to enhance its usefulness particularly in a comparative analysis of the effects of climate change on extreme rainfalls of short duration available in different locations.
► We quantify the performance of a new parallelization method for a distributed model. ► Parallel model performance is found to be dependent on the hydrologic variability. ► Load balancing methods ...improve parallel performance in particular for large domains. ► A wider range of distributed applications is now possible through parallelization.
A major challenge in the use of fully-distributed hydrologic models has been the lack of computational capabilities for high-resolution, long-term simulations in large river basins. In this study, we present the parallel model implementation and real-world hydrologic assessment of the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS). Our parallelization approach is based on the decomposition of a complex watershed using the channel network as a directed graph. The resulting sub-basin partitioning divides effort among processors and handles hydrologic exchanges across boundaries. Through numerical experiments in a set of nested basins, we quantify parallel performance relative to serial runs for a range of processors, simulation complexities and lengths, and sub-basin partitioning methods, while accounting for inter-run variability on a parallel computing system. In contrast to serial simulations, the parallel model speed-up depends on the variability of hydrologic processes. Load balancing significantly improves parallel speed-up with proportionally faster runs as simulation complexity (domain resolution and channel network extent) increases. The best strategy for large river basins is to combine a balanced partitioning with an extended channel network, with potential savings through a lower TIN resolution. Based on these advances, a wider range of applications for fully-distributed hydrologic models are now possible. This is illustrated through a set of ensemble forecasts that account for precipitation uncertainty derived from a statistical downscaling model.
The diurnal cycles of surface energy fluxes are important drivers of atmospheric boundary layer development and convective precipitation, particularly in regions with heterogeneous land surface ...conditions such as those under the influence of the North American monsoon (NAM). Characterization of diurnal surface fluxes and their controls has not been well constrained due to the paucity of observations in the NAM region. In this study, we evaluate the performance of the uncoupled WRF‐Hydro modeling system in its ability to represent soil moisture, turbulent heat fluxes, and surface temperature observations and compare these to operational analyses from other commonly used land surface models (LSMs). After a rigorous model evaluation, we quantify how the diurnal cycles of surface energy fluxes vary during the warm season for the major ecosystems in a regional basin. We find that the diurnal cycle of latent heat flux is more sensitive to ecosystem type than sensible heat flux due to the response of plant transpiration to variations in soil water content. Furthermore, the peak timing of precipitation affects the shape and magnitude of the diurnal cycle of plant transpiration in water‐stressed ecosystems, inducing mesoscale heterogeneity in land surface conditions between the major ecosystems within the basin. Comparisons to other LSMs indicate that ecosystem differences in the diurnal cycle of turbulent fluxes are underestimated in these products. While this study shows how land surface heterogeneity affects the simulated diurnal cycle of turbulent fluxes, additional coupled modeling efforts are needed to identify the potential impacts of these spatial differences on convective precipitation.
Key Points
WRF‐Hydro reproduces observed soil moisture, turbulent fluxes, and land surface temperature at individual sites and as spatial patterns
Diurnal cycle of latent heat flux varies among ecosystems due to plant transpiration and is affected by the peak timing of precipitation
Stomatal control on plant transpiration induces mesoscale heterogeneity in the diurnal cycle of the turbulent fluxes within a regional basin
Phoenix, an Active Management Area in the desert Southwest US, is the 5 th most populated city in the US. Scarce local groundwater and water transported from external resources must be managed in the ...presence of different types of energy sources. Local and regional decision-makers are faced with answering challenging questions on managing water, energy supply, and demand over a few years to several decades. Prediction and planning for the interdependency of these entities can benefit from modeling the water and energy systems as well as their interactions with one another. In this paper, the integrated WEAP and LEAP tools and a modeling framework that externalizes their hidden linkage to an interaction model are described and compared using the Phoenix AMA. Loose coupling enabled by interaction modeling is a key for decision-policies that should be grounded at the nexus of the water-energy system of systems.
PDF
