Hydrologic Modeling of Boreal Forest Ecosystems

This study focused on the hydrologic response, including vegetation water use, of two test regions within the Boreal-Ecosystem-Atmosphere Study (BOREAS) region in the Canadian boreal forest, one north of Prince Albert, Saskatchewan, and the other near Thompson, Manitoba. Fluxes of moisture and heat were studied using a spatially distributed hydrology soil-vegetation-model (DHSVM)

Methane emissions from western Siberian wetlands: heterogeneity and sensitivity to climate change

The prediction of methane emissions from high-latitude wetlands is important given concerns about their sensitivity to a warming climate. As a basis for the prediction of wetland methane emissions at regional scales, we coupled the variable infiltration capacity macroscale hydrological model (VIC) with the biosphere–energy-transfer–hydrology terrestrial ecosystem model (BETHY) and a wetland methane emissions model to make large-scale estimates of methane emissions as a function of soil temperature, water table depth, and net primary productivity (NPP), with a parameterization of the sub-grid heterogeneity of the water table depth based on TOPMODEL. We simulated the methane emissions from a 100 km × 100 km region of western Siberia surrounding the Bakchar Bog, for a retrospective baseline period of 1980–1999 and have evaluated their sensitivity to increases in temperature of 0–5 °C and increases in precipitation of 0–15%. The interactions of temperature and precipitation, through their effects on the water table depth, played an important role in determining methane emissions from these wetlands. The balance between these effects varied spatially, and their net effect depended in part on sub-grid topographic heterogeneity. Higher temperatures alone increased methane production in saturated areas, but caused those saturated areas to shrink in extent, resulting in a net reduction in methane emissions. Higher precipitation alone raised water tables and expanded the saturated area, resulting in a net increase in methane emissions. Combining a temperature increase of 3 °C and an increase of 10% in precipitation to represent climate conditions that may pertain in western Siberia at the end of this century resulted in roughly a doubling in annual emissions

Predicting Hydrological Drought: Relative Contributions of Soil Moisture and Snow Information to Seasonal Streamflow Prediction Skill

in this study we examine how knowledge of mid-winter snow accumulation and soil moisture conditions contribute to our ability to predict streamflow months in advance. A first "synthetic truth" analysis focuses on a series of numerical experiments with multiple sophisticated land surface models driven with a dataset of observations-based meteorological forcing spanning multiple decades and covering the continental United States. Snowpack information by itself obviously contributes to the skill attained in streamflow prediction, particularly in the mountainous west. The isolated contribution of soil moisture information, however, is found to be large and significant in many areas, particularly in the west but also in region surrounding the Great Lakes. The results are supported by a supplemental, observations-based analysis using (naturalized) March-July streamflow measurements covering much of the western U.S. Additional forecast experiments using start dates that span the year indicate a strong seasonality in the skill contributions; soil moisture information, for example, contributes to kill at much longer leads for forecasts issued in winter than for those issued in summer

SWOT data assimilation for operational reservoir management on the upper Niger River Basin

International audienceThe future Surface Water and Ocean Topography (SWOT) satellite mission will provide two-dimensional maps of water elevation for rivers with width greater than 100 m globally. We describe a mod-eling framework and an automatic control algorithm that prescribe optimal releases from the Selingue dam in the Upper Niger River Basin, with the objective of understanding how SWOT data might be used to the benefit of operational water management. The modeling framework was used in a twin experiment to simulate the ''true'' system state and an ensemble of corrupted model states. Virtual SWOT observations of reservoir and river levels were assimilated into the model with a repeat cycle of 21 days. The updated state was used to initialize a Model Predictive Control (MPC) algorithm that computed the optimal reservoir release that meets a minimum flow requirement 300 km downstream of the dam. The data assimilation results indicate that the model updates had a positive effect on estimates of both water level and discharge. The ''per-sistence,'' which describes the duration of the assimilation effect, was clearly improved (greater than 21 days) by integrating a smoother into the assimilation procedure. We compared performances of the MPC with SWOT data assimilation to an open-loop MPC simulation. Results show that the data assimilation resulted in substantial improvements in the performances of the Selingue dam management with a greater ability to meet environmental requirements (the number of days the target is missed falls to zero) and a minimum volume of water released from the dam

Seasonal hydrologic prediction in the United States: understanding the role of initial hydrologic conditions and seasonal climate forecast skill

Seasonal hydrologic forecasts derive their skill from knowledge of initial hydrologic conditions and climate forecast skill associated with seasonal climate outlooks. Depending on the type of hydrological regime and the season, the relative contributions of initial hydrologic conditions and climate forecast skill to seasonal hydrologic forecast skill vary. We seek to quantify these contributions on a relative basis across the Conterminous United States. We constructed two experiments – Ensemble Streamflow Prediction and reverse-Ensemble Streamflow Prediction – to partition the contributions of the initial hydrologic conditions and climate forecast skill to overall forecast skill. In ensemble streamflow prediction (first experiment) hydrologic forecast skill is derived solely from knowledge of initial hydrologic conditions, whereas in reverse-ensemble streamflow prediction (second experiment), it is derived solely from atmospheric forcings (i.e. perfect climate forecast skill). Using the ratios of root mean square error in predicting cumulative runoff and mean monthly soil moisture of each experiment, we identify the variability of the relative contributions of the initial hydrologic conditions and climate forecast skill spatially throughout the year. We conclude that the initial hydrologic conditions generally have the strongest influence on the prediction of cumulative runoff and soil moisture at lead-1 (first month of the forecast period), beyond which climate forecast skill starts to have greater influence. Improvement in climate forecast skill alone will lead to better seasonal hydrologic forecast skill in most parts of the Northeastern and Southeastern US throughout the year and in the Western US mainly during fall and winter months; whereas improvement in knowledge of the initial hydrologic conditions can potentially improve skill most in the Western US during spring and summer months. We also observed that at a short lead time (i.e. lead-1) contribution of the initial hydrologic conditions in soil moisture forecasts is more extensive than in cumulative runoff forecasts across the Conterminous US

Estimating spatiotemporally continuous snow water equivalent from intermittent satellite observations: an evaluation using synthetic data

Accurate estimates of snow water equivalent (SWE) based on remote sensing have been elusive, particularly in mountain areas. However, there now appears to be some potential for direct satellite-based SWE observations along ground tracks that only cover a portion of a spatial domain (e.g., watershed). Fortunately, spatiotemporally continuous meteorological and surface variables could be leveraged to infer SWE in the gaps between satellite ground tracks. Here, we evaluate statistical and machine learning (ML) approaches to performing track-to-area (TTA) transformations of SWE observations in California's upper Tuolumne River watershed using synthetic data. The synthetic SWE measurements are designed to mimic a potential future P-band Signals of Opportunity (P-SoOP) satellite mission with a (along-track) spatial resolution of about 500 m. We construct relationships between multiple meteorological and surface variables and synthetic SWE observations along observation tracks, and we then extend these relationships to unobserved areas between ground tracks to estimate SWE over the entire watershed. Domain-wide, SWE inferred on 1 April using two synthetic satellite tracks (∼4.5 % basin coverage) led to percent errors of basin-averaged SWE (PEBAS) of 24.5 %, 4.5 % and 6.3 % in an extremely dry water year (WY2015), a normal water year (WY2008) and an extraordinarily wet water year (WY2017), respectively. Assuming a 10 d overpass interval, percent errors of basin-averaged SWE during both snow accumulation and snowmelt seasons were mostly less than 10 %. We employ a feature sensitivity analysis to overcome the black-box nature of ML methods and increase the explainability of the ML results. Our feature sensitivity analysis shows that precipitation is the dominant variable controlling the TTA SWE estimation, followed by net long-wave radiation (NetLong). We find that a modest increase in the accuracy of SWE estimation occurs when more than two ground tracks are leveraged. The accuracy of 1 April SWE estimation is only modestly improved for track repeats more often than about 15 d.</p

Modeling the effect of glacier recession on streamflow response using a coupled glacio-hydrological model

We describe an integrated spatially distributed hydrologic and glacier dynamic model, and use it to investigate the effect of glacier recession on streamflow variations for the upper Bow River basin, a tributary of the South Saskatchewan River, Alberta, Canada. Several recent studies have suggested that observed decreases in summer flows in the South Saskatchewan River are partly due to the retreat of glaciers in the river's headwaters. Modeling the effect of glacier changes on streamflow response in river basins such as the South Saskatchewan is complicated due to the inability of most existing physically based distributed hydrologic models to represent glacier dynamics. We compare predicted variations in glacier extent, snow water equivalent (SWE), and streamflow discharge with satellite estimates of glacier area and terminus position, observed glacier mass balance, observed streamflow and snow water-equivalent measurements, respectively over the period of 1980–2007. Observations of multiple hydroclimatic variables compare well with those simulated with the coupled hydrology-glacier model. Our results suggest that, on average, the glacier melt contribution to the Bow River flow upstream of Lake Louise is approximately 22% in summer. For warm and dry years, however, the glacier melt contribution can be as large as 47% in August, whereas for cold years, it can be as small as 15% and the timing of the glacier melt signature can be delayed by a month. The development of this modeling approach sets the stage for future predictions of the influence of warming climate on streamflow in partially glacierized watersheds

Detection of intensification of the global water cycle: the potential role of FRIEND

Diagnostic studies of 14-year, 2 — 2°, Variable Infiltration Capacity (VIC) model off-line simulations of the global terrestrial water budget suggest that, given the annual variability in the major components of continental hydrological cycles (precipitation, evaporation, and runoff), several decades to perhaps centuries of measurements may be needed to detect with high confidence the intensification predicted by recent global climate model (GCM) studies simulating plausible global warming scenarios. Furthermore, these measurements may need to originate from a wider geographic expanse than is currently investigated within large-scale hydrological assessment programmes, such as the Global Energy and Water Experiment (GEWEX). Smaller, geographically dispersed basins, including many of those participating in the International Flow Regimes from International Experimental and Network Data (FRIEND) programme, could therefore play important roles in detection of an intensification in the global water cycle

GCIP water and energy budget synthesis (WEBS)

As part of the World Climate Research Program\u27s (WCRPs) Global Energy and Water-Cycle Experiment (GEWEX) Continental-scale International Project (GCIP), a preliminary water and energy budget synthesis (WEBS) was developed for the period 1996–1999 from the “best available” observations and models. Besides this summary paper, a companion CD-ROM with more extensive discussion, figures, tables, and raw data is available to the interested researcher from the GEWEX project office, the GAPP project office, or the first author. An updated online version of the CD-ROM is also available at http://ecpc.ucsd.edu/gcip/webs.htm/. Observations cannot adequately characterize or “close” budgets since too many fundamental processes are missing. Models that properly represent the many complicated atmospheric and near-surface interactions are also required. This preliminary synthesis therefore included a representative global general circulation model, regional climate model, and a macroscale hydrologic model as well as a global reanalysis and a regional analysis. By the qualitative agreement among the models and available observations, it did appear that we now qualitatively understand water and energy budgets of the Mississippi River Basin. However, there is still much quantitative uncertainty. In that regard, there did appear to be a clear advantage to using a regional analysis over a global analysis or a regional simulation over a global simulation to describe the Mississippi River Basin water and energy budgets. There also appeared to be some advantage to using a macroscale hydrologic model for at least the surface water budgets

Birthing practices of traditional birth attendants in South Asia in the context of training programmes

Traditional Birth Attendants (TBA) training has been an important component of public health policy interventions to improve maternal and child health in developing countries since the 1970s. More recently, since the 1990s, the TBA training strategy has been increasingly seen as irrelevant, ineffective or, on the whole, a failure due to evidence that the maternal mortality rate (MMR) in developing countries had not reduced. Although, worldwide data show that, by choice or out of necessity, 47 percent of births in the developing world are assisted by TBAs and/or family members, funding for TBA training has been reduced and moved to providing skilled birth attendants for all births. Any shift in policy needs to be supported by appropriate evidence on TBA roles in providing maternal and infant health care service and effectiveness of the training programmes. This article reviews literature on the characteristics and role of TBAs in South Asia with an emphasis on India. The aim was to assess the contribution of TBAs in providing maternal and infant health care service at different stages of pregnancy and after-delivery and birthing practices adopted in home births. The review of role revealed that apart from TBAs, there are various other people in the community also involved in making decisions about the welfare and health of the birthing mother and new born baby. However, TBAs have changing, localised but nonetheless significant roles in delivery, postnatal and infant care in India. Certain traditional birthing practices such as bathing babies immediately after birth, not weighing babies after birth and not feeding with colostrum are adopted in home births as well as health institutions in India. There is therefore a thin precarious balance between the application of biomedical and traditional knowledge. Customary rituals and perceptions essentially affect practices in home and institutional births and hence training of TBAs need to be implemented in conjunction with community awareness programmes