Journal of Hydrology X最新文献

A unified framework for simulating various transport processes in the environment is presented. It consists in a single set of partial differential equations. The main feature of this model framework is its exchange layer, which allows to treat several types of transfer between the soil and the surface water.

The model framework equations, termed transfer equations, is shown to reproduce three independently-published models developed for soil erosion, river bedload, and chemical transport respectively. By allowing the different processes to be represented within a single model framework, the transfer equations are therefore unifying the representation of particles and chemical fluxes in the environment. The transfer equations are implemented into the open-source software FullSWOF_1D. The code is verified against the approximation of an exact solution, assuring its proper functioning. A good adequacy is found between our numerical results and those published in the literature, attesting the capability of the transfer equations to unify modeling of soil erosion, river bedload, and chemical transport. Hence, the transfer equations can decrease the number of models to be used for simulating transfer of materials in the environment, and limit the number of computer codes to be developed and maintained. The transfer equations could also help in drawing parallels between different fields of hydrology.

The operational hydrologists of the United States’ National Weather Service (NWS) develop river forecasts as guidance for those at risk of flood damage and update those flood forecasts in real-time as more information becomes available. To do so they rely on experience and intuition to adjust the inputs, state variables, and parameters of hydrologic models. NWS hydrologists use the term “modifiers” to refer collectively to these adjustments. This paper demonstrates the development and application of tools (statistical and graphical) to aid operational hydrologists in the achievement of accurate flood forecasts. Analysis of variance (ANOVA) identifies the relative contribution to forecast uncertainty of each modifier. Heat map visualizations illustrate for operational hydrologists the basin, lead-time, and season-specific effects of their modifiers choices. The tools provide operational hydrologists with insight into which of three commonly applied modifiers (precipitation, soil moisture, and unit hydrograph shape) are most likely to provide improvement in flood forecast accuracy. The tools are demonstrated for a case study of four watersheds within in the Ohio River Valley, using data for flood events sampled from 1990 to 2018. The findings of this research show that operational hydrologists in the Ohio River Basin would do well apply no modifiers in the winter (leaving hydrologic input variables and parameters at baseline values). And though the forecast might be improved by real-time adjustments to the unit hydrograph in summer months, recommendations for particular unit hydrograph modification levels cannot be made with confidence. These findings call into question the modifier adjustment program as a standard process. In the evaluated cases, modifiers do not systematically improve flood forecasts. Improvement may be more efficiently achieved through better calibration of hydrologic models or techniques for reduction of precipitation uncertainty.

Climate change will have both quantitative and qualitative effects on groundwater resources. These impacts differ for aquifers in solid and unconsolidated rock, in urban or rural locations, and in the principal processes of groundwater recharge.

Having knowledge about the intrinsic key parameters (aquifer geometries, storage properties, groundwater renewal rates, residence times, etc.), the principal groundwater recharge processes, and the temperature imprinting makes it possible to compare and forecast the sensitivity of individual aquifers to climate change.

The sensitivity of future groundwater temperature development for selected climate projections was qualitatively investigated for representative Swiss unconsolidated rock groundwater resources in the Central Plateau as well as the Jura and Alpine region.

For non-urban and rural areas, climate change is expected to have a strong overall impact on groundwater temperatures. In urban areas, however, direct anthropogenic influences are likely to dominate. Increased thermal subsurface use and waste heat from underground structures, as well as adaptation strategies to mitigate global warming, increase groundwater temperatures. Likewise, measurements for the city of Basel show that groundwater temperatures increased by an average of 3.0 ± 0.7 °C in the period from 1993 to 2016, and that they can exceed 18 °C, especially in densely urbanized areas. Similarly, regarding shallow aquifers with low groundwater saturated zone thicknesses, such as in Davos (Canton Grisons), groundwater temperatures will strongly be influenced by changes in groundwater recharge regimes. In contrast, groundwater temperature changes within deep aquifers with large groundwater saturated zone thicknesses, such as in Biel/Bienne (Canton Bern), or in some cases in aquifers with large distances from the land surface to the groundwater table and extended unsaturated zones, such as in Winterthur (Canton Zurich), are strongly attenuated and can only be expected over long time periods.

In the context of the presented research we hypothesized that quantitative groundwater recharge and the associated temperature imprinting of aquifers is primarily determined by infiltrating surface waters (i.e. “river-fed aquifers”). We show that seasonal shifts in groundwater recharge processes could be an important factor affecting future groundwater temperatures. Moreover, the interaction with surface waters and increased groundwater recharge during high runoff periods are likely to strongly influence groundwater temperatures. Accordingly, for the “business as usual” climate change scenario and for the end of the century, a shift in precipitation and river flood events from summer to winter months could be accompanied by an increase in groundwater recharge in comparatively cool seasons, which would be accompanied by a tendency to “cool down” groundwater resources.

Society and the environment in the arid southwestern United States depend on reliable water availability, yet current water use outpaces supply. Water demand is projected to grow in the future and climate change is expected to reduce supply. To adapt, water managers need robust estimates of future regional water supply to support management decisions. To address this need, we estimate future streamflow in seven water resource regions in the southwestern U.S. using a new SPAtially Referenced Regressions On Watershed attributes (SPARROW) streamflow model. We present streamflow projections corresponding to input data from seven climate models and two greenhouse gas Representative Concentration Pathways (RCP4.5 and 8.5) for three, thirty-year intervals centered on the 2030s, 2050s, and 2080s, and for a historical thirty year interval centered on the 1990s. Across water resource regions, about half of the RCP4.5 models (51%) and two thirds of the RCP8.5 models (67%) indicate decreases in streamflow in the 2080s relative to the historical period. Models project maximum decreases in streamflow of 36–80% in all water resource regions for all periods and RCPs relative to historical streamflow, and maximum streamflow decreases of up to 20–45% in the 2080s at sites along the Colorado River used for measuring compliance with interstate and international water agreements. Headwaters are projected to experience the greatest declines, with substantial downstream implications. Among these estimates, the streamflows from models forced with RCP8.5 tend to be lower than those forced with RCP4.5. Not all climate models, times, and RCPs project widespread streamflow declines. The most ubiquitous streamflow increases are projected to occur in the 2030s under RCP4.5. Later time periods and enhanced greenhouse gas forcings indicate smaller regions of streamflow increase and lower accumulated streamflows, suggesting that limiting or reducing greenhouse gas concentrations could support future water availability. Although some possible streamflow increases are promising, the modest and spatially limited increases in streamflow projected for later time periods are still unlikely to be sufficient to meet the projected water demand. These results inform the likelihood of future water agreement compliance, and support developing strategies to balance water supply and demand.

Krypton-85 and other radioactive noble gases are widely used for groundwater dating purposes. ⁸⁵Kr analysis require large volumes of water to reach the analytical requirements. Conventionally, this water is pumped to the surface to be degassed with a gas extraction system. The large pumping rate may disturb the natural flow field and requires substantial field logistics. Hence, we propose a new in-situ degassing method, in which membrane contactors are used to degas the groundwater directly in the well and gas is collected at the surface. This way, field work is facilitated, groundwater system disturbance is minimized, and the gas sample is collected at a specific depth. We demonstrate the tightness of the system regarding atmospheric air contamination for a collection times of 24 h, which is sufficient for both low-level counting and laser-based counting methods for ⁸⁵Kr. The minimal borehole diameter is 7.5 cm for the prototype presented in this research but can easily be reduced to smaller diameters. In a case study, we compare the results obtained with the new passive method with those from a conventional packer setup sampling. Additionally, ³H/³He samples were collected for both sampling regimes and the dating results were compared with those from ⁸⁵Kr. A good agreement between tracer ages is demonstrated and the age stratigraphy is consistent with the expected age distribution for a porous unconfined aquifer. In addition, our study emphasizes the differences between the age information sampled with various methods. In conclusion, we demonstrate that the new in situ quasi-passive method provides a more representative age stratigraphy with depth in most cases.

Anthropogenic activities are altering flood frequency-magnitude distributions along many of the world’s large rivers. Yet isolating the impact of any single factor amongst the multitudes of competing anthropogenic drivers is a persistent challenge. The Usumacinta River in southeastern Mexico provides an opportunity to study the anthropogenic driver of tropical forest conversion in isolation, as the long meteorological and discharge records capture the river’s response to large-scale agricultural expansion without interference from development activities such as dams or channel modifications. We analyse continuous daily time series of precipitation, temperature, and discharge to identify long-term trends, and employ a novel approach to disentangle the signal of deforestation by normalising daily discharges by 90-day mean precipitation volumes from the contributing area in order to account for climatic variability. We also identify an anthropogenic signature of tropical forest conversion at the intra-annual scale, reproduce this signal using a distributed hydrological model (VMOD), and demonstrate that the continued conversion of tropical forest to agricultural land use will further exacerbate large-scale flooding. We find statistically significant increasing trends in annual minimum, mean, and maximum discharges that are not evident in either precipitation or temperature records, with mean monthly discharges increasing between 7% and 75% in the past decades. Model results demonstrate that forest cover loss is responsible for raising the 10-year return peak discharge by 25%, while the total conversion of forest to agricultural use would result in an additional 18% rise. These findings highlight the need for an integrated basin-wide approach to land management that considers the impacts of agricultural expansion on increased flood prevalence, and the economic and social costs involved.

Stable isotopes of hydrogen (δ²H) and oxygen (δ¹⁸O) provide important quantitative measures of lake hydrology and water balance, particularly in lakes where monitoring of fluxes is incomplete. However, little is known of the relative effects of seasonal variation in water isotopes on estimates of lake hydrology, particularly over decadal scales. To address this gap, we measured water isotopes bi-weekly May-September during 2003–2016 in seven riverine lakes within the 52,000 km² Qu’Appelle River drainage basin of the Canadian Prairies. Analyses revealed that within-year variation in δ¹⁸O values routinely exceeded that among years, reflecting rapid changes in water source, particularly in lakes with water residence times <1 year. Isotopic variation was greatest during spring following snowmelt, except in large deep lakes which exhibited limited differences among seasons or years. In contrast, large hydrological events (e.g., 1-in-140-year flood in 2011) homogenized isotopic values, even among riverine lakes separated by over 150 km, and exerted particularly strong legacy effects on large lakes. Overall, study lakes exhibited a strongly positive moisture balance (evaporation < inflow), despite regional precipitation deficits of 30 cm yr⁻¹, with greater reliance on rainfall (vs. snow) and possibly evaporation in downstream lakes within more humid regions. We conclude that seasonal samples of water isotopes are required to characterize the hydrology of shallow lakes, or those with unknown reliance on snowmelt waters, as well as to better quantify lake susceptibility to climate variability.

The classification of characteristics of flood events, like peak, volume, duration and baseflow components is essential for many hydrological applications such as multivariate flood statistics, the validation of rainfall-runoff models and comparative hydrology in general. The basis for estimations of these characteristics is formed by flood event separation. It requires an indicator for the time when a flood peak occurs as well as the definition of the beginning and end of a flood event and a subdivision of the total volume into direct and baseflow components. However, the variable nature of runoff and the multiple processes and impacts that determine rainfall-runoff relationships make a separation difficult, especially an automation of it. We propose a new statistics-based flood event separation that was developed to analyse long series of daily discharges automatically to obtain flood events for flood statistics. Moreover, the related flood-inducing precipitation is identified, allowing the estimation of the flood-inducing rainfall and the runoff coefficient. With an additional tool to manually check the separation results easily and quickly, expert knowledge can be included without much effort. The algorithm was applied to seven basins in Germany, covering alpine, mountainous and flatland catchments with different runoff processes. In a sensitivity analysis, the impact of chosen parameters was evaluated. The results show that the algorithm delivers reasonable results for all catchments and only needs manual adjustment for long timeslots with increasing or high baseflow. It reliably separates flood events only instead of all runoff events and the estimated beginning and end of an event was shifted in mean by less than one day compared to manual separation.