Technical Note: The impact of spatial scale in bias correction of climate model output for hydrologic impact studies

Statistical downscaling is a commonly used technique for translating large-scale climate model output to a scale appropriate for assessing impacts. To ensure downscaled meteorology can be used in climate impact studies, downscaling must correct biases in the large-scale signal. A simple and generally effective method for accommodating systematic biases in large-scale model output is quantile mapping, which has been applied to many variables and shown to reduce biases on average, even in the presence of non-stationarity. Quantile-mapping bias correction has been applied at spatial scales ranging from hundreds of kilometers to individual points, such as weather station locations. Since water resources and other models used to simulate climate impacts are sensitive to biases in input meteorology, there is a motivation to apply bias correction at a scale fine enough that the downscaled data closely resemble historically observed data, though past work has identified undesirable consequences to applying quantile mapping at too fine a scale. This study explores the role of the spatial scale at which the quantile-mapping bias correction is applied, in the context of estimating high and low daily streamflows across the western United States. We vary the spatial scale at which quantile-mapping bias correction is performed from 2° ( ∼  200 km) to 1∕8° ( ∼  12 km) within a statistical downscaling procedure, and use the downscaled daily precipitation and temperature to drive a hydrology model. We find that little additional benefit is obtained, and some skill is degraded, when using quantile mapping at scales finer than approximately 0.5° ( ∼  50 km). This can provide guidance to those applying the quantile-mapping bias correction method for hydrologic impacts analysis

Characterizing the Variability of Physical and Chemical Properties across the Soil Individuals Mapped as Amy Silt Loam Soils in Southeastern Arkansas

Knowledge of physical and chemical properties of soil is relevant for landowners, researchers, and foresters, so that appropriate crop species and management practices to maximize site productivity can be selected. In addition to issues of plant productivity, the need for assessing soil properties has been expanded due to public interest in determining the consequences of management practices on soil quality relative to sustainability of crop ecosystem functions. The USDA-Natural Resources Conservation Service (NRCS) delineated soil mapping units to provide information about physical and chemical properties of soil in each soil series. However, soil mapping units do not provide details about the variability of soil properties within a single soil series. To determine the variability of physical and chemical properties within Amy soil series, 200 soil samples were collected to a depth of 0–15cm and 15–30cm from soil individuals mapped as the Amy silt loam soils in five different locations in southeastern Arkansas. Comparisons of soil texture, bulk density, carbon, nitrogen, Mehlich III extractable macronutrients, and micronutrients revealed significant differences among soil individuals/ locations for both depth increments. Additionally, all nutrients except potassium, magnesium, and copper differed between the two soil depths. The results suggest inherent variation in biogeochemical and geochemical cycling in the surface horizons of soils mapped as the Amy series

Effects of Light Regime and Season of Clipping on the Growthof Cherrybark Oak, White Oak, Persimmon, and Sweetgum Sprouts

A mixture of cherrybark oak (Quercus pagoda Raf.), white oak (Q. alba L.), persimmon (Diospyros virginiana L.), and sweetgum (Liquidambar styraciflua L.) seedlings was grown in shadehouses to simulate light conditions beneath a canopy. After the first growing season, two release treatments were implemented (released and not released), and treatments were conducted during two seasons (winter and spring). All seedlings were clipped at 2.5 em from the groundline in height when treatments were imposed. Survival of persimmon and sweetgum was 100% following clipping. There appeared to be a weak seasonal effect on oak survival, especially for white oak; survival was 100% for winter clipping and 93% for spring clipping. The oaks were considerably smaller in height, diameter, and above-ground biomass than their competitors, and the competitors also produced more stems per rootstock than the oaks. Cherrybark oak was more productive than white oak especially in the released treatment. The oaks tended to have a higher percentage of their total biomass in foliage when compared with their competitors. Stem wood density of the oaks was considerably greater than that of their competitors. Leaf characteristics of all species were very responsive to the treatments; specific leaf area was consistently greater for the no-release treatment for all species. Results of this study suggest that for oak sprouts to grow faster than their competitors they must begin with an initial size advantage

Evaluation of experimental epoxy monomers

Future generation aircraft need higher performance polymer matrices to fully achieve the weight savings possible with composite materials. New resins are being formulated in an effort to understand basic polymer behavior and to develop improved resins. Some polymer/curing agent combinations that could be useful are difficult to process. In the area of epoxies, a major problem is that some components have physical properties which make them difficult to utilize as matrix resins. A previous study showed that the use of ultrasonic energy can be advantageous in the mixing of curing agents into a standard epoxy resin, such as MY 720 (Ciba-Geigy designation). This work is expanded to include three novel epoxides

Technical Note: The impact of spatial scale in bias correction of climate model output for hydrologic impact studies

Statistical downscaling is a commonly used technique for translating large-scale climate model output to a scale appropriate for assessing impacts. To ensure downscaled meteorology can be used in climate impact studies, downscaling must correct biases in the large-scale signal. A simple and generally effective method for accommodating systematic biases in large-scale model output is quantile mapping, which has been applied to many variables and shown to reduce biases on average, even in the presence of non-stationarity. Quantile-mapping bias correction has been applied at spatial scales ranging from hundreds of kilometers to individual points, such as weather station locations. Since water resources and other models used to simulate climate impacts are sensitive to biases in input meteorology, there is a motivation to apply bias correction at a scale fine enough that the downscaled data closely resemble historically observed data, though past work has identified undesirable consequences to applying quantile mapping at too fine a scale. This study explores the role of the spatial scale at which the quantile-mapping bias correction is applied, in the context of estimating high and low daily streamflows across the western United States. We vary the spatial scale at which quantile-mapping bias correction is performed from 2° ( ∼  200 km) to 1∕8° ( ∼  12 km) within a statistical downscaling procedure, and use the downscaled daily precipitation and temperature to drive a hydrology model. We find that little additional benefit is obtained, and some skill is degraded, when using quantile mapping at scales finer than approximately 0.5° ( ∼  50 km). This can provide guidance to those applying the quantile-mapping bias correction method for hydrologic impacts analysis

Climate Change Impacts on Streamflow and Subbasin- Scale Hydrology in the Upper Colorado River Basin

In the Upper Colorado River Basin (UCRB), the principal source of water in the southwestern U.S., demand exceeds supply in most years, and will likely continue to rise. While General Circulation Models (GCMs) project surface temperature warming by 3.5 to 5.6uC for the area, precipitation projections are variable, with no wetter or drier consensus. We assess the impacts of projected 21st century climatic changes on subbasins in the UCRB using the Soil and Water Assessment Tool, for all hydrologic components (snowmelt, evapotranspiration, surface runoff, subsurface runoff, and streamflow), and for 16 GCMs under the A2 emission scenario. Over the GCM ensemble, our simulations project median Spring streamflow declines of 36% by the end of the 21st century, with increases more likely at higher elevations, and an overall range of 2100 to +68%. Additionally, our results indicated Summer streamflow declines with median decreases of 46%, and an overall range of 2100 to +22%. Analysis of hydrologic components indicates large spatial and temporal changes throughout the UCRB, with large snowmelt declines and temporal shifts in most hydrologic components. Warmer temperatures increase averageannual evapotranspiration by ,23%, with shifting seasonal soil moisture availability driving these increases in late Winter and early Spring. For the high-elevation water-generating regions, modest precipitation decreases result in an even greater water yield decrease with less available snowmelt. Precipitation increases with modest warming do not translate into the same magnitude of water-yield increases due to slight decreases in snowmelt and increases in evapotranspiration. For these basins, whether modest warming is associated with precipitation decreases or increases, continued rising temperatures may make drier futures. Subsequently, many subbasins are projected to turn from semi-arid to arid conditions by the 2080 s. In conclusion, water availability in the UCRB could significantly decline with adverse consequences for water supplies, agriculture, and ecosystem health

Quantifying Soil Chemical Properties Using Near Infrared Reflectance Spectroscopy

Methodologies for determining soil chemical properties have evolved dramatically during the past century. Early geochemical analyses were conducted exclusively through the use of wet chemistry techniques that were relatively reliable but painstaking and subject to errors at various stages of analysis. Near infrared reflectance spectroscopy (NIRS) has emerged as a new approach for rapidly analyzing a variety of materials including soils. In this study soil samples were taken from eight study areas across the Ozark Highlands of Arkansas, and NIRS calibration models were developed to determine the accuracy of using NIRS to analyze soils compared with standard soil chemical analysis protocols. Multivariate regression models were highly effective for analyzing several important elements. C and N models explained 92% and 88% of their variation, respectively, and Ca, Mg, P, and Mn models explained 72-88% of the variability in these elements. Models for C:N and pH explained 82% and 86% of their variability, respectively. Models for micronutrients Cu and Zn did not fit as well with 22% and 40% of their variability explained, respectively. Our findings suggest that additional NIRS calibration and modeling is promising for rapidly analyzing the chemical composition of soils, and it is desirable to develop model libraries that are calibrated for the soils of a given region

Development and application of a hydroclimatological stream temperature model within the Soil and Water Assessment Tool

We develop a stream temperature model within the Soil and Water Assessment Tool (SWAT) that reflects the combined influence of meteorological (air temperature) and hydrological conditions (streamflow, snowmelt, groundwater, surface runoff, and lateral soil flow) on water temperature within a watershed. SWAT currently uses a linear air-stream temperature relationship to determine stream temperature, without consideration of watershed hydrology. As SWAT uses stream temperature to model various in-stream biological and water quality processes, an improvement of the stream temperature model will result in improved accuracy in modeling these processes. The new stream temperature model is tested on seven coastal and mountainous streams throughout the western United States for which high quality flow and water temperature data were available. The new routine does not require input data beyond that already supplied to the model, can be calibrated with a limited number of calibration parameters, and achieves improved representation of observed daily stream temperature. For the watersheds modeled, the Nash-Sutcliffe (NS) coefficient and mean error (ME) for the new stream temperature model averaged 0.81 and −0.69°C, respectively, for the calibration period and 0.82 and −0.63°C for the validation period. The original SWAT stream temperature model averaged a NS of −0.27 and ME of 3.21°C for the calibration period and a NS of −0.26 and ME of 3.02°C for the validation period. Sensitivity analyses suggest that the new stream temperature model calibration parameters are physically reasonable and the model is better able to capture stream temperature changes resulting from changes in hydroclimatological conditions

Effect of Seedling Stock on the Early Stand Development and Physiology of Improved Loblolly Pine (Pinus taeda L.) Seedlings

This study assessed the effects of spacing and genotype on the growth and physiology of improved loblolly pine (Pinus taeda L.) seedlings from three distinct genotypes planted in Drew County, Arkansas (USA). Genotype had a significant effect on survival and height. Clone CF Var 1 showed greater height and survival compared to other seedlings. Genotype had significant effects on uniformity in height both years and ground line diameter (GLD) first year. However, genotype had no significant effects on leaf water potential and coefficient variation of leaf water potential. These growth and physiology should be further studied to assess potential genetic differences among seedlings and to determine if they can be identified early for improved growth at later ages

Natural and Managed Watersheds Show Similar Responses to Recent Climate Change

Changes in climate are driving an intensification of the hydrologic cycle and leading to alterations of natural streamflow regimes. Human disturbances such as dams, land-cover change, and water diversions are thought to obscure climate signals in hydrologic systems. As a result, most studies of changing hydroclimatic conditions are limited to areas with natural streamflow. Here, we compare trends in observed streamflow from natural and human-modified watersheds in the United States and Canada for the 1981–2015 water years to evaluate whether comparable responses to climate change are present in both systems. We find that patterns and magnitudes of trends in median daily streamflow, daily streamflow variability, and daily extremes in human-modified watersheds are similar to those from nearby natural watersheds. Streamflow in both systems show negative trends throughout the southern and western United States and positive trends throughout the northeastern United States, the northern Great Plains, and southern prairies of Canada. The trends in both natural and human-modified watersheds are linked to local trends in precipitation and reference evapotranspiration, demonstrating that water management and land-cover change have not substantially altered the effects of climate change on human-modified watersheds compared with nearby natural watersheds