Diagnosing the impacts of permafrost on catchment hydrology: field measurements and model experiments in a mountainous catchment in western China

Increased attention directed at permafrost hydrology has been prompted by climate change. In spite of an increasing number of field measurements and modeling studies, the impacts of permafrost on hydrological processes at the catchment scale are still unclear. Permafrost hydrology models at the catchment scale were mostly developed based on a “bottom-up” approach, hence by aggregating prior knowledge at the spot/field scales. In this study, we followed a “top-down” approach to learn from field measurement data to understand permafrost hydrology at the catchment scale. In particular, we used a stepwise model development approach to examine the impact of permafrost on streamflow response in the Hulu catchment in western China. We started from a simple lumped model (FLEX-L), and step-wisely included additional complexity by accounting for topography (i.e. FLEX-D) and landscape heterogeneity (i.e. FLEX-Topo). The final FLEX-Topo model, was then analyzed using a dynamic identifiability analysis (DYNIA) to investigate parameters’ temporal variation. By enabling temporal dynamics on several parameters, we diagnosed the physical relationships between parameter variation and permafrost impacts. We found that in the Hulu catchment: 1) the improvement associated to the model modifications suggest that topography and landscape heterogeneity are dominant controls on catchment response; 2) baseflow recession in permafrost regions is the result of a linear reservoir, and slower than non-permafrost regions; 3) parameters variation infers seasonally non-stationary precipitation-runoff relationships in permafrost catchment; 4) permafrost impacts on streamflow response mostly at the beginning of the melting season; 5) allowing the temporal variations of frozen soil related parameters, i.e. the unsaturated storage capacity and the splitter of fast and slow streamflow, improved model performance. Our findings provide new insights on the impact of permafrost on catchment hydrology in vast mountain regions of western China. More generally, they help to understand the effect of climate change on permafrost hydrology.

Tile drainage causes flashy streamflow response in Ohio watersheds

Artificial subsurface (tile) drainage is used to increase trafficability and crop yield in much of the Midwest due to soils with naturally poor drainage. Tile drainage has been researched extensively at the field scale, but knowledge gaps remain on how tile drainage influences the streamflow response at the watershed scale. The purpose of this study is to analyze the effect of tile drainage on the streamflow response for 59 Ohio watersheds with varying percentages of tile drainage and explore patterns between the Western Lake Erie Bloom Severity Index to streamflow response in heavily tile-drained watersheds. Daily streamflow was downloaded from 2010-2019 and used to calculated mean annual peak daily runoff, mean annual runoff ratio, the percent of observations in which daily runoff exceeded mean annual runoff (TQmean), baseflow versus stormflow percentages, and the streamflow recession constant. Heavily-drained watersheds (> 40 % of watershed area) consistently reported flashier streamflow behavior compared to watersheds with low percentages of tile drainage (< 15% of watershed area) as indicated by significantly lower baseflow percentages, TQmean, and streamflow recession constants. The mean baseflow percent for watersheds with high percentages of tile drainage was 20.9 % compared to 40.3 % for watersheds with low percentages of tile drainage. These results are in contrast to similar research regionally indicating greater baseflow proportions and less flashy hydrographs (higher TQmean) for heavily-drained watersheds. Stormflow runoff metrics in heavily-drained watersheds were significantly positively correlated to western Lake Erie algal bloom severity. Given the recent trend in more frequent large rain events and warmer temperatures in the Midwest, increased harmful algal bloom severity will continue to be an ecological and economic problem for the region if management efforts are not addressed at the source. Management practices that reduce the streamflow response time to storm events, such as buffer strips, wetland restoration, or drainage water management, are likely to improve the aquatic health conditions of downstream communities by limiting the transport of nutrients following storm events.

Assessing annual streamflow response to forest disturbance in the western US: A large-sample hydrology approach

&lt;p&gt;Forested watersheds across the western US have experienced recent widespread disturbance and tree mortality due to a combination of heat, drought, and epidemic insect and disease outbreaks. Hydrologic response has included both increases and decreases in the fraction of annual precipitation that is partitioned to streamflow versus evapotranspiration (ET). We used a large-sample hydrology approach to address two questions: First, how have water budget components changed during this period of high forest disturbance, and second, does streamflow response vary with disturbance severity, incoming solar radiation, and/or aridity? From previous studies, streamflow and runoff ratio are expected to increase with forest disturbance due to reduced ET, and conversely increases in forest density are expected to reduce streamflow. We statistically evaluated whether these expectations were met, and where and why contradictory responses occurred, using trend and regression analysis. We constructed annual water budgets for 211 watersheds in the western US from daily observations in the CAMELS dataset, which includes streamflow and climate data as well as watershed characteristics such as mean incoming solar radiation and aridity (i.e., ratio of mean annual potential ET to mean annual precipitation, or PET/P). Forest disturbance was quantified as percentage change in live tree volume and mean annual rate of tree mortality, using data collected by the US Forest Service&amp;#8217;s Forest Inventory and Analysis program. While most water budget components and forcing variables did not exhibit consistent trends, many watersheds experienced significant increases in temperature and PET. Unexpected trends in runoff ratio occurred in two scenarios: First, runoff ratio decreased following forest disturbance in many water-limited watersheds (i.e., PET/P&gt;1) of the southwestern US; and second, both runoff ratios and forest densities increased in some energy-limited watersheds of the Pacific Northwest. Water-limited watersheds and those with high solar radiation experienced more forest disturbance than energy-limited watersheds. We used hydrologic time trend analysis to quantify the magnitude of streamflow change. A linear regression model including precipitation and temperature as inputs was calibrated and validated using the pre-disturbance time period (1980-2006, odd years and even years, respectively; r&lt;sup&gt;2&lt;/sup&gt;&lt;sub&gt;val&lt;/sub&gt;=0.954), and then applied to the post-disturbance time period (2007-2019), where model residuals are assumed to represent change in streamflow due to factors not included in the model, i.e., forest change. Among the 65 watersheds with significant streamflow change, the magnitude of change was moderately correlated with both disturbance severity and solar radiation. Decreased post-disturbance streamflow occurred mainly in watersheds with low to moderate tree mortality and high incoming solar radiation. We used multiple linear regression to identify important predictors of streamflow change. Pre-disturbance streamflow, change in precipitation and PET, solar radiation, and the interaction of solar radiation and tree mortality were all highly significant predictors (p&lt;/p&gt;

Projecting future streamflow under changing climate and urban land cover across the UK

&lt;p&gt;Changes in precipitation and land cover are important drivers of change in catchment streamflow, yet quantifying their influence remains a major challenge. This work aims to understand how streamflow may evolve under different scenarios of future precipitation and urbanization across the UK. A collection of catchments from the National River Flow Archive (NRFA) that have experienced significant changes in flows and urbanization were selected. Both historical observations and future projections of precipitation and urban land cover were extracted within each study catchment, for different emissions and socio-economic scenarios including Representative Concentration Pathways (RCPs) and Shared Socio-Economic Pathways (SSPs). Distributional regression models &amp;#8211; Generalised Additive Models for Location Scale and Shape (GAMLSS) &amp;#8211; were developed using historical precipitation, land cover, and streamflow, and employed to project future streamflow using bias-corrected projections of precipitation and land cover. The results improve our understanding of streamflow response to climate and land cover changes and provide further insights for water resources management and land use development.&lt;/p&gt;

Monitoring and forecasting Kenya’s fluctuating hydro-climate

This study reviews Kenya’s fluctuating hydro-climate (3S-4N, 35-40E) and evaluates products that describe its area-averaged daily rainfall 2008-2018, monthly evaporation 2000-2018, and catchment hydrology via gauge, satellite, and model hindcast/forecast.Using the correlation of rainfall as a metric of skill we found: daily satellite vs model hindcasts achieved 75%; while model forecasts at 2- to 6-day lead achieved 55-58%. The daily satellite vs model soil moisture had a significant correlation (84%); and model run-off vs gauge streamflow reached 61%. A two day delay was noted between rainfall and streamflow response in recent flood events; however long-range predictability was found to be poor (35%).These outcomes were considered at a local workshop, and ways to sustainably improve the real-time reporting of key hydro-climate parameters for operational data assimilation were suggested as steps toward better monitoring and forecast services in Kenya