Multiple Indicators of Extreme Changes in Snow-Dominated Streamflow Regimes, Yakima River Basin Region, USA

Snow plays a major role in the hydrological cycle. Variations in snow duration and timing can have a negative impact on water resources. Excluding predicted changes in snowmelt rates and amounts could result in deleterious infrastructure, military mission, and asset impacts at military bases across the US. A change in snowpack can also lead to water shortages, which in turn can affect the availability of irrigation water. We performed trend analyses of air temperature, snow water equivalent (SWE) at 22 SNOTEL stations, and streamflow extremes for selected rivers in the snow-dependent and heavily irrigated Yakima River Basin (YRB) located in the Pacific Northwest US. There was a clear trend of increasing air temperature in this study area over a 30 year period (water years 1991–2020). All stations indicated an increase in average air temperatures for December (0.97 °C/decade) and January (1.12 °C/decade). There was also an upward trend at most stations in February (0.28 °C/decade). In December–February, the average air temperatures were 0.82 °C/decade. From these trends, we estimate that, by 2060, the average air temperatures for December–February at most (82%) stations will be above freezing. Furthermore, analysis of SWE from selected SNOTEL stations indicated a decreasing trend in historical SWE, and a shift to an earlier peak SWE was also assumed to be occurring due of the shorter snow duration. Decreasing trends in snow duration, rain-on-snow, and snowmelt runoff also resulted from snow modeling simulations of the YRB and the nearby area. We also observed a shift in the timing of snowmelt-driven peak streamflow, as well as a statistically significant increase in winter maximum streamflow and decrease in summer maximum and minimum streamflow trends by 2099. From the streamflow trends and complementary GEV analysis, we show that the YRB basin is a system in transition with earlier peak flows, lower snow-driven maximum streamflow, and higher rainfall-driven summer streamflow. This study highlights the importance of looking at changes in snow across multiple indicators to develop future infrastructure and planning tools to better adapt and mitigate changes in extreme events.

Peak water in observed glacier-fed streamflow time series

<p>Glacier peak water describes the initial increasing and subsequent decreasing trend of glacier melt water as a response to global warming. The phenomenon might encourage excessive water use that cannot be sustained in the long-term. Knowing magnitude and time scale of its effect on streamflow trends and changes in partly glacierized catchments is therefore needed. This comparative regional study examined August streamflow records from 1976-2015 in the European Alps, Norway, Western Canada, and Alaska. It aimed to detect whether and when a peak was reached or passed and how strong decreasing post-peak streamflow trends were. A one-peak hypothesis could not be confirmed in many of the records and the variability of individual series' detected peaks and trends is large. Some common patterns in the timing of peaks and general trend directions in the records could be generalized. These suggest: a peak early in the period in Western Canada followed by mostly declining streamflow trends, pre-peak conditions in Alaska resulting in mostly positive streamflow trends, variable peaks in Norway and the Alps from the mid-1990s on with differences for low and highly glacierized catchments. Trends and peaks in climate-variability corrected August streamflow broadly related to phases of regional glacier retreat, but local variability is more complex.  Only weak systematic deviations were found related to catchment characteristics. This multi-record and multi-region comparison of streamflow observations suggests that knowledge on a regional phenomenon will need to be complemented with local monitoring and modelling to provide useful information for water resources planning.</p>

An Analysis of Streamflow Trends in the Southern and Southeastern US from 1950–2015

In this article, the mean daily streamflow at 139 streamflow-gaging stations (sites) in the southern and southeastern United States are analyzed for spatial and temporal patterns. One hundred and thirty-nine individual time-series of mean daily streamflow were reduced to five aggregated time series of Z scores for clusters of sites with similar temporal variability. These aggregated time-series correlated significantly with a time-series of several climate indices for the period 1950–2015. The mean daily streamflow data were subset into six time periods—starting in 1950, 1960, 1970, 1980, 1990, and 2000, and each ending in 2015, to determine how streamflow trends at individual sites acted over time. During the period 1950–2015, mean monthly and seasonal streamflow decreased at many sites based on results from traditional Mann–Kendall trend analyses, as well as results from a new analysis (Quantile-Kendall) that summarizes trends across the full range of streamflows. A trend departure index used to compare results from non-reference with reference sites identified that streamflow trends at 88% of the study sites have been influenced by non-climatic factors (such as land- and water-management practices) and that the majority of these sites were located in Texas, Louisiana, and Georgia. Analysis of the results found that for sites throughout the study area that were influenced primarily by climate rather than human activities, the step increase in streamflow in 1970 documented in previous studies was offset by subsequent monotonic decreases in streamflow between 1970 and 2015.

Highly-resolved hydro-meteorological trends in Norway: impacts of observed climate change on snowmelt- and rainfall dominated streamflow in Western vs. Eastern Norway

<p>Mountainous and Nordic regions are experiencing more rapid temperature increases as compared to regions at lower altitudes and latitudes. This will impact the hydrology in these regions.  For Norway, there is increasing evidence for gradually increasing temperatures and recent changes in the amount, intensity, and frequency of precipitation as well as in the number of days with snow cover. The most pronounced differences regarding their hydro-meteorological regime can be found between Western and Eastern Norway (Vestlandet vs. Østlandet). Most catchments in these regions are characterized by mixed snowmelt/rainfall streamflow regimes with peak flows during spring (dominant in Østlandet) and autumn (dominant in Vestlandet). Changes in the hydro-meteorological drivers will have direct implications on the snow regime, and thus, also on streamflow via their direct effect on the relative importance of snowmelt vs. rainfall for streamflow generation.</p><p>In this study, we analyze daily-resolved streamflow trends for 112 catchments in Western vs. Eastern Norway for the period 1983-2012 and compare them with daily-resolved trends in the hydro-meteorological drivers. We also estimate the relative contribution of snowmelt and rainfall on daily streamflow for each catchment and identify trends therein. This process-orientated approach at high temporal resolution allows for a better identification of (in)consistencies with changes in the hydro-meteorological drivers than simple seasonal comparisons. Lastly, we aim to attribute observed changes in daily streamflow to the most dominant hydro-meteorological drivers by applying seasonal multiple-regressions. The major findings of this study are as follows:</p><ul><li>The high-resolution trend analysis allows for in-depth seasonal-specific insights into the hydrological response of catchments with different hydrological regimes to changes in the hydro-meteorological drivers.</li> <li>Increasing (decreasing) contributions of rainfall (snowmelt) to streamflow generally agree with prior expectations. The trends, however, show differences in magnitude and timing, depending on the geographical location (Vestlandet vs. Østlandet) and altitude.</li> <li>The seasonal multiple regression approach suggests that daily streamflow changes can be explained best by adding temperature as an additional predictor to snowmelt and rainfall, which may indicate the changing relevance of evapotranspiration particularly during summer.</li> </ul>

Achieving Net Zero: Understanding the Potential Hydrological Impacts of Changing Climate and Land Cover in the UK

<p>Climate change is set to increase the magnitude and frequency of fluvial flooding in many regions across the world, making it a growing risk to billions of people living near rivers. Changing drainage basin land cover and hydrological connectivity further complicates how these streamflow extremes may evolve. Engineered solutions to mitigate the risk of future high magnitude runoff events to populations may no longer be suitable to meet these needs due to these changes in climate and land cover.</p><p>By reducing the level of global CO<sub>2</sub> emissions, climate models predict that we can reduce the severity of climate change impacts upon communities. To achieve the goals set by the Paris Agreement to limit global warming, the UK has proposed a range of policies to reach net zero carbon emissions by 2050. One of these proposals includes widespread afforestation across the UK. Where to plant this woodland and the scale of impact it may have on the future hydrological cycle is currently unquantified. This project seeks to investigate three aspects of how future streamflow trends my change due to afforestation in respect to: woodland location, differing afforestation rates, and the hydrological responsiveness of drainage basins to land cover changes.</p><p>Physics-based models provide the possibility to explore the relative importance of climate and land cover on future streamflow trends, both together and separately. The Joint UK Land Environment Simulator (JULES) is used to explore catchment responses across the UK to potential extreme weather events with theoretical changes in land cover at a 1 km resolution. Theoretical land cover scenarios of afforestation were generated according to proximity to existing land cover, drainage basin structure and proposed afforestation sites. An extreme precipitation scenario (the winter of 2013/14) is explored to comprehend streamflow regime response to high magnitude precipitation events caused by changing climate and land cover using the Weather@home perturbed model ensembles and CHESS-met datasets. This approach provides the potential to explore how increasing afforestation could change the discharge dynamics of landscapes across the UK and thus its potential benefits and drawbacks to flood risk management. </p><p>Results show how potential land cover changes will impact streamflow response to storms across the UK. These results help provide a clearer picture of how changing landscape systems impact river response to external climatic forcing and may provide evidence for management and policy strategies tailored to the requirements of individual drainage basins to reduce the risk of flooding upon downstream populations.</p>