More Like this

1. Identifying uncertainties in hydrologic fluxes and seasonality from hydrologic model components for climate change impact assessments

   https://doi.org/10.5194/hess-24-2253-2020  

   Feng, Dongmei ; Beighley, Edward ( January 2020 , Hydrology and Earth System Sciences)

   Abstract. Assessing impacts of climate change on hydrologic systemsis critical for developing adaptation and mitigation strategies for waterresource management, risk control, and ecosystem conservation practices. Suchassessments are commonly accomplished using outputs from a hydrologic modelforced with future precipitation and temperature projections. The algorithmsused for the hydrologic model components (e.g., runoff generation) canintroduce significant uncertainties into the simulated hydrologic variables.Here, a modeling framework was developed that integrates multiple runoffgeneration algorithms with a routing model and associated parameteroptimizations. This framework is able to identify uncertainties from bothhydrologic model components and climate forcings as well as associatedparameterization. Three fundamentally different runoff generationapproaches, runoff coefficient method (RCM, conceptual), variableinfiltration capacity (VIC, physically based, infiltration excess), andsimple-TOPMODEL (STP, physically based, saturation excess), were coupledwith the Hillslope River Routing model to simulate surface/subsurface runoffand streamflow. A case study conducted in Santa Barbara County, California,reveals increased surface runoff in February and March but decreasedrunoff in other months, a delayed (3 d, median) and shortened (6 d,median) wet season, and increased daily discharge especially for theextremes (e.g., 100-year flood discharge, Q100). The Bayesian modelaveraging analysis indicates that the probability of such an increase can be up to85 %. For projected changes in runoff and discharge, general circulationmodels (GCMs) and emission scenariosmore »are two major uncertainty sources,accounting for about half of the total uncertainty. For the changes inseasonality, GCMs and hydrologic models are two major uncertaintycontributors (∼35 %). In contrast, the contribution ofhydrologic model parameters to the total uncertainty of changes in thesehydrologic variables is relatively small (<6 %), limiting theimpacts of hydrologic model parameter equifinality in climate change impactanalysis. This study provides useful information for practices associatedwith water resources, risk control, and ecosystem conservation and forstudies related to hydrologic model evaluation and climate change impactanalysis for the study region as well as other Mediterranean regions.« less
2. Human amplified changes in precipitation–runoff patterns in large river basins of the Midwestern United States

   https://doi.org/10.5194/hess-21-5065-2017  

   Kelly, Sara A. ; Takbiri, Zeinab ; Belmont, Patrick ; Foufoula-Georgiou, Efi ( January 2017 , Hydrology and Earth System Sciences)

   Complete transformations of land cover from prairie, wetlands, and hardwood forests to row crop agriculture and urban centers are thought to have caused profound changes in hydrology in the Upper Midwestern US since the 1800s. In this study, we investigate four large (23 000–69 000 km²) Midwest river basins that span climate and land use gradients to understand how climate and agricultural drainage have influenced basin hydrology over the last 79 years. We use daily, monthly, and annual flow metrics to document streamflow changes and discuss those changes in the context of precipitation and land use changes. Since 1935, flow, precipitation, artificial drainage extent, and corn and soybean acreage have increased across the region. In extensively drained basins, we observe 2 to 4 fold increases in low flows and 1.5 to 3 fold increases in high and extreme flows. Using a water budget, we determined that the storage term has decreased in intensively drained and cultivated basins by 30–200 % since 1975, but increased by roughly 30 % in the less agricultural basin. Storage has generally decreased during spring and summer months and increased during fall and winter months in all watersheds. Thus, the loss of storage and enhanced hydrologic connectivity and efficiency imparted by artificialmore »agricultural drainage appear to have amplified the streamflow response to precipitation increases in the Midwest. Future increases in precipitation are likely to further intensify drainage practices and increase streamflows. Increased streamflow has implications for flood risk, channel adjustment, and sediment and nutrient transport and presents unique challenges for agriculture and water resource management in the Midwest. Better documentation of existing and future drain tile and ditch installation is needed to further understand the role of climate versus drainage across multiple spatial and temporal scales.« less
3. Predicting the Geographic Range of an Invasive Livestock Disease across the Contiguous USA under Current and Future Climate Conditions

   https://doi.org/10.3390/cli9110159  

   Burruss, Dylan ; Rodriguez, Luis L. ; Drolet, Barbara ; Geil, Kerrie ; Pelzel-McCluskey, Angela M. ; Cohnstaedt, Lee W. ; Derner, Justin D. ; Peters, Debra P. ( November 2021 , Climate)

   Vesicular stomatitis (VS) is the most common vesicular livestock disease in North America. Transmitted by direct contact and by several biting insect species, this disease results in quarantines and animal movement restrictions in horses, cattle and swine. As changes in climate drive shifts in geographic distributions of vectors and the viruses they transmit, there is considerable need to improve understanding of relationships among environmental drivers and patterns of disease occurrence. Multidisciplinary approaches integrating pathology, ecology, climatology, and biogeophysics are increasingly relied upon to disentangle complex relationships governing disease. We used a big data model integration approach combined with machine learning to estimate the potential geographic range of VS across the continental United States (CONUS) under long-term mean climate conditions over the past 30 years. The current extent of VS is confined to the western portion of the US and is related to summer and winter precipitation, winter maximum temperature, elevation, fall vegetation biomass, horse density, and proximity to water. Comparison with a climate-only model illustrates the importance of current processes-based parameters and identifies regions where uncertainty is likely to be greatest if mechanistic processes change. We then forecast shifts in the range of VS using climate change projections selected frommore »CMIP5 climate models that most realistically simulate seasonal temperature and precipitation. Climate change scenarios that altered climatic conditions resulted in greater changes to potential range of VS, generally had non-uniform impacts in core areas of the current potential range of VS and expanded the range north and east. We expect that the heterogeneous impacts of climate change across the CONUS will be exacerbated with additional changes in land use and land cover affecting biodiversity and hydrological cycles that are connected to the ecology of insect vectors involved in VS transmission.« less
4. Diel streamflow cycles suggest more sensitive snowmelt-driven streamflow to climate change than land surface modeling does

   https://doi.org/10.5194/hess-26-3393-2022  

   Krogh, Sebastian A. ; Scaff, Lucia ; Kirchner, James W. ; Gordon, Beatrice ; Sterle, Gary ; Harpold, Adrian ( January 2022 , Hydrology and Earth System Sciences)

   Abstract. Climate warming will cause mountain snowpacks to melt earlier, reducing summer streamflow and threatening water supplies and ecosystems. Quantifying how sensitive streamflow timing is to climate change and where it is most sensitive remain key questions. Physically based hydrological models are often used for this purpose; however, they have embedded assumptions that translate into uncertain hydrological projections that need to be quantified and constrained to provide reliable inferences. The purpose of this study is to evaluate differences in projected end-of-century changes to streamflow timing between a new empirical model based on diel (daily) streamflow cycles and regional land surface simulations across the mountainous western USA. We develop an observational technique for detecting streamflow responses to snowmelt using diel cycles of incoming solar radiation and streamflow to detect when snowmelt occurs. We measure the date of the 20th percentile of snowmelt days (DOS20) across 31 western USA watersheds affected by snow, as a proxy for the beginning of snowmelt-initiated streamflow. Historic DOS20 varies from mid-January to late May among our sites, with warmer basins having earlier snowmelt-mediated streamflow. Mean annual DOS20 strongly correlates with the dates of 25 % and 50 % annual streamflow volume (DOQ25 and DOQ50, both R2=0.85), suggesting that a 1 d earlier DOS20more »corresponds with a 1 d earlier DOQ25 and 0.7 d earlier DOQ50. Empirical projections of future DOS20 based on a stepwise multiple linear regression across sites and years under the RCP8.5 scenario for the late 21st century show that DOS20 will occur on average 11±4 d earlier per 1 ∘C of warming. However, DOS20 in colder watersheds (mean November–February air temperature, TNDJF<-8 ∘C) is on average 70 % more sensitive to climate change than in warmer watersheds (TNDJF>0 ∘C). Moreover, empirical projections of DOQ25 and DOQ50 based on DOS20 are about four and two times more sensitive to climate change, respectively, than those simulated by a state-of-the-art land surface model (NoahMP-WRF) under the same scenario. Given the importance of changes in streamflow timing for water resources, and the significant discrepancies found in projected streamflow sensitivity, snowmelt detection methods such as DOS20 based on diel streamflow cycles may help to constrain model parameters, improve hydrological predictions, and inform process understanding.« less
5. Climatic and anthropogenic drivers of a drying Himalayan river

   https://doi.org/10.5194/hess-26-375-2022  

   Penny, Gopal ; Dar, Zubair A. ; Müller, Marc F. ( January 2022 , Hydrology and Earth System Sciences)

   Abstract. Streamflow regimes are rapidly changing in many regions of the world. Attribution of these changes to specific hydrological processes and their underlying climatic and anthropogenic drivers is essential to formulate an effective water policy. Traditional approaches to hydrologic attribution rely on the ability to infer hydrological processes through the development of catchment-scale hydrological models. However, such approaches are challenging to implement in practice due to limitations in using models to accurately associate changes in observed outcomes with corresponding drivers. Here we present an alternative approach that leverages the method of multiple hypotheses to attribute changes in streamflow in the Upper Jhelum watershed, an important tributary headwater region of the Indus basin, where a dramatic decline in streamflow since 2000 has yet to be adequately attributed to its corresponding drivers. We generate and empirically evaluate a series of alternative and complementary hypotheses concerning distinct components of the water balance. This process allows a holistic understanding of watershed-scale processes to be developed, even though the catchment-scale water balance remains open. Using remote sensing and secondary data, we explore changes in climate, surface water, and groundwater. The evidence reveals that climate, rather than land use, had a considerably stronger influence on reductionsmore »in streamflow, both through reduced precipitation and increased evapotranspiration. Baseflow analyses suggest different mechanisms affecting streamflow decline in upstream and downstream regions, respectively. These findings offer promising avenues for future research in the Upper Jhelum watershed, and an alternative approach to hydrological attribution in data-scarce regions.« less