Dry Creek Experimental Watershed Research Articles

Topographically moderated soil water seasons impact vegetation dynamics in semiarid mountain catchments: Illustrations from the Dry Creek Experimental Watershed, Idaho, USA

AbstractWater stored in soils, in part, controls vegetation productivity and the duration of growing seasons in wildland ecosystems. Soil water is the dynamic product of precipitation, evapotranspiration and soil properties, all of which vary across complex terrain making it challenging to decipher the specific controls that soil water has on growing season dynamics. We assess how soil water use by plants varies across elevations and aspects in the Dry Creek Experimental Watershed in southwest Idaho, USA, a mountainous, semiarid catchment that spans low elevation rain to high elevation snow regimes. We compare trends in soil water and soil temperature with corresponding trends in insolation, precipitation and vegetation productivity, and we observe trends in the timing, rate and duration of soil water extraction by plants across ranges in elevation and aspect. The initiation of growth‐supporting conditions, indicated by soil warming, occurs 58 days earlier at lower, compared with higher, elevations. However, growth‐supporting conditions also end earlier at lower elevations due to the onset of soil water depletion 29 days earlier than at higher elevations. A corresponding shift in peak NDVI timing occurs 61 days earlier at lower elevations. Differences in timing also occur with aspect, with most threshold timings varying by 14–30 days for paired north‐ and south‐facing sites at similar elevations. While net primary productivity nearly doubles at higher elevations, the duration of the warm‐wet period of active water use does not vary systematically with elevation. Instead, the greater ecosystem productivity is related to increased soil water storage capacity, which supports faster soil water use and growth rates near the summer solstice and peak insolation. Larger soil water storage does not appear to extend the duration of the growing season, but rather supports higher growing season intensity when wet‐warm soil conditions align with high insolation. These observations highlight the influence of soil water storage capacity in dictating ecological function in these semiarid steppe climatic regimes.

The Utility of Information Flow in Formulating Discharge Forecast Models: A Case Study From an Arid Snow‐Dominated Catchment

AbstractStreamflow forecasts often perform poorly because of improper representation of hydrologic response timescales in underlying models. Here, we use transfer entropy (TE), which measures information flow between variables, to identify dominant drivers of discharge and their timescales using sensor data from the Dry Creek Experimental Watershed, ID, USA. Consistent with previous mechanistic studies, TE revealed that snowpack accumulation and partitioning into melt, recharge, and evaporative loss dominated discharge patterns and that snow‐sourced baseflow reduced the greatest amount of uncertainty in discharge. We hypothesized that machine learning models (MLMs) specified in accordance with the dominant lag timescales, identified via TE, would outperform timescale‐agnostic models. However, while lagged‐variable random forest regressions captured the dominant process—seasonal snowmelt—they ultimately did not perform as well as the unlagged models, provided those models were specified with input data aggregated over a range of timescales. Unlagged models, not constrained by timescales of the dominant processes, more effectively represented variable interactions (e.g., rain‐on‐snow events) playing a critical role in translating precipitation into streamflow over long, intermediate, and short timescales. Meanwhile, long short‐term memory (LSTM) models were effective in internally identifying the key lag and aggregation scales for predicting discharge. Parsimonious specification of LSTM models, using only daily unlagged precipitation and temperature data, produced the highest performing predictions. Our findings suggest that TE can identify dominant streamflow controls and the relative importance of different mechanisms of streamflow generation, useful for establishing process baselines and fingerprinting watersheds. However, restricting MLMs based on dominant timescales undercuts their skill at learning these timescales internally.

Doing Hydrology Backwards—Analytic Solution Connecting Streamflow Oscillations at the Basin Outlet to Average Evaporation on a Hillslope

The concept of doing hydrology backwards, introduced in the literature in the last decade, relies on the possibility to invert the equations relating streamflow fluctuations at the catchment outlet to estimated hydrological forcings throughout the basin. In this work, we use a recently developed set of equations connecting streamflow oscillations at the catchment outlet to baseflow oscillations at the hillslope scale. The hillslope-scale oscillations are then used to infer the pattern of evaporation needed for streamflow oscillations to occur. The inversion is illustrated using two conceptual models of movement of water in the subsurface with different levels of complexity, but still simple enough to demonstrate our approach. Our work is limited to environments where diel oscillations in streamflow are a strong signal in streamflow data. We demonstrate our methodology by applying it to data collected in the Dry Creek Experimental Watershed in Idaho and show that the hydrology backwards principles yield results that are well within the order of magnitude of daily evapotranspiration fluctuations. Our analytic results are generic and they encourage the development of experimental campaigns to validate integrated hydrological models and test implicit parameterization assumptions.

Water Flow Modeling with Dry Bulk Density Optimization to Determine Hydraulic Properties in Mountain Soils

Core Ideas The GEOtop model was used to calculate water flow in mountain soils. Dry soil bulk density was optimized to determine soil hydraulic properties. Soil water contents for two watersheds were used to test the optimization procedure. A new method for determining profile‐average and depth‐wise hydraulic properties in heterogeneous mountain soils is presented using the GEOtop watershed model in 1‐D vertical mode. Dry soil bulk density–converted volumetric soil water retention data are used to determine van Genuchten soil water retention parameters, and the Kozeny–Carman equation is used to determine saturated soil hydraulic conductivity. Optimum dry soil bulk densities are identified by minimizing the sum of squared error between measured and calculated soil water content time series. The new method was tested using soil moisture data from soil profiles at the Dry Creek Experimental Watershed, Boise, ID, and the Libby Creek Experimental Watershed, Laramie, WY. Results of different scenarios showed that the optimization of a single profile‐average dry soil bulk density is a good option for describing soil water flow in the heterogeneous mountain soils. Soil water content modeling efficiency (ME) values of 0.084 ≤ ME ≤ 0.745 and –2.443 ≤ ME ≤ 0.373 were found for the Dry Creek and Libby Creek sites, respectively. Relatively low ME values for the deepest sensor depths for some scenarios were attributed to the overestimation of soil water freezing and uncertainty in the soil water retention function near saturation. The resulting calibration procedure is computationally efficient because only one parameter (dry soil bulk density) is optimized.

Form and function relationships revealed by long‐term research in a semiarid mountain catchment

Fifteen years of cumulative research in the Dry Creek Experimental Watershed in southwest Idaho, USA, has revealed relationships between catchment form and function that would not have been possible through independent short‐term projects alone. The impacts of aspect and elevation on incident energy and water, coupled with climate seasonality, have produced tightly connected landform properties and hydrologic processes. North‐facing hillslopes have steeper slope angles, thicker soil mantles, finer soil texture, and higher water holding capacities than their south‐facing counterparts. This trend is modulated by elevation and vegetation; higher elevation sites, where aspect differences in vegetation are less evident, exhibit less distinct hydrologic properties. The storage of water first as snow, then as soil moisture determines how upland ecosystems survive the seasonal and persistent water stress that happens each year, and sustains streamflow throughout the year. The cumulative body of local knowledge has improved general understanding of catchment science, serves as a resource for conceptual and numerical evaluation of process‐based models, and for data‐driven hydrologic education. WIREs Water 2018, 5:e1267. doi: 10.1002/wat2.1267This article is categorized under: Science of Water > Hydrological Processes Science of Water > Water and Environmental Change

Assessing a Multi-Platform Data Fusion Technique in Capturing Spatiotemporal Dynamics of Heterogeneous Dryland Ecosystems in Topographically Complex Terrain

Water-limited ecosystems encompass approximately 40% of terrestrial land mass and play a critical role in modulating Earth’s climate and provisioning ecosystem services to humanity. Spaceborne remote sensing is a critical tool for characterizing ecohydrologic patterns and advancing the understanding of the interactions between atmospheric forcings and ecohydrologic responses. Fine to medium scale spatial and temporal resolutions are needed to capture the spatial heterogeneity and the temporally intermittent response of these ecosystems to environmental forcings. Techniques combining complementary remote sensing datasets have been developed, but the heterogeneous nature of these regions present significant challenges. Here we investigate the capacity of one such approach, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm, to map Normalized Difference Vegetation Index (NDVI) at 30 m spatial resolution and at a daily temporal resolution in an experimental watershed in southwest Idaho, USA. The Dry Creek Experimental Watershed captures an ecotone from a sagebrush steppe ecosystem to evergreen needle-leaf forests along an approximately 1000 m elevation gradient. We used STARFM to fuse NDVI retrievals from the MODerate-resolution Imaging Spectroradiometer (MODIS) and Landsat during the course of a growing season (April to September). Specifically we input to STARFM a pair of Landsat NDVI retrievals bracketing a sequence of daily MODIS NDVI retrievals to yield daily estimates of NDVI at resolutions of 30 m. In a suite of data denial experiments we compared these STARFM predictions against corresponding Landsat NDVI retrievals and characterized errors in predicted NDVI. We investigated how errors vary as a function of vegetation functional type and topographic aspect. We find that errors in predicting NDVI were highest during green-up and senescence and lowest during the middle of the growing season. Absolute errors were generally greatest in tree-covered portions of the watershed and lowest in locations characterized by grasses/bare ground. On average, relative errors in predicted average NDVI were greatest in grass/bare ground regions, on south-facing aspects, and at the height of the growing season. We present several ramifications revealed in this study for the use of multi-sensor remote sensing data for the study of spatiotemporal ecohydrologic patterns in dryland ecosystems.

An evaluation of the ecohydrological separation hypothesis in a semiarid catchment

The ecohydrological separation hypothesis states that transpiration through plants and drainage to streams and groundwater are sourced from separate soil water pools, which possess distinct isotopic signatures. Evidence for ecohydrological separation has relied on the globally ubiquitous observation that plant water and draining water are isotopically distinct. We evaluated the ecohydrological separation hypothesis in the Dry Creek Experimental Watershed in the semiarid, snow-dominated landscape of southwest Idaho, USA. We found that plant water is indeed isotopically distinct from streams and groundwater. However, we were unable to track those waters to subsurface soil waters, nor were we able to relate soil water mobility to isotopic composition. Soil waters of different mobility can be isotopically similar, and isotopic distinction in soil water can occur for reasons not related to mobility. We suggest that isotopic distinction between root-absorbed and draining waters may not be an appropriate indicator of ecohydrological separation of soil waters, and that hydrologic explanations for such isotopic distinction may not be sufficient.

On the propagation of diel signals in river networks using analytic solutions of flow equations

Abstract. Several authors have reported diel oscillations in streamflow records and have hypothesized that these oscillations are linked to evapotranspiration cycles in the watershed. The timing of oscillations in rivers, however, lags behind those of temperature and evapotranspiration in hillslopes. Two hypotheses have been put forth to explain the magnitude and timing of diel streamflow oscillations during low-flow conditions. The first suggests that delays between the peaks and troughs of streamflow and daily evapotranspiration are due to processes occurring in the soil as water moves toward the channels in the river network. The second posits that they are due to the propagation of the signal through the channels as water makes its way to the outlet of the basin. In this paper, we design and implement a theoretical model to test these hypotheses. We impose a baseflow signal entering the river network and use a linear transport equation to represent flow along the network. We develop analytic streamflow solutions for the case of uniform velocities in space over all river links. We then use our analytic solution to simulate streamflows along a self-similar river network for different flow velocities. Our results show that the amplitude and time delay of the streamflow solution are heavily influenced by transport in the river network. Moreover, our equations show that the geomorphology and topology of the river network play important roles in determining how amplitude and signal delay are reflected in streamflow signals. Finally, we have tested our theoretical formulation in the Dry Creek Experimental Watershed, where oscillations are clearly observed in streamflow records. We find that our solution produces streamflow values and fluctuations that are similar to those observed in the summer of 2011.

Hydrologic controls on equilibrium soil depths

This paper deals with modeling the mutual feedbacks between runoff production and geomorphological processes and attributes that lead to patterns of equilibrium soil depth. Our primary goal is an attempt to describe spatial patterns of soil depth resulting from long‐term interactions between hydrologic forcings and soil production, erosion, and sediment transport processes under the framework of landscape dynamic equilibrium. Another goal is to set the premises for exploiting the role of soil depths in shaping the hydrologic response of a catchment. The relevance of the study stems from the massive improvement in hydrologic predictions for ungauged basins that would be achieved by using directly soil depths derived from geomorphic features remotely measured and objectively manipulated. Hydrological processes are here described by explicitly accounting for local soil depths and detailed catchment topography. Geomorphological processes are described by means of well‐studied geomorphic transport laws. The modeling approach is applied to the semiarid Dry Creek Experimental Watershed, located near Boise, Idaho. Modeled soil depths are compared with field data obtained from an extensive survey of the catchment. Our results show the ability of the model to describe properly the mean soil depth and the broad features of the distribution of measured data. However, local comparisons show significant scatter whose origins are discussed.

Bedrock infiltration and mountain block recharge accounting using chloride mass balance

AbstractMountain front catchment net groundwater recharge (NR) represents the upper end of mountain block recharge (MBR) groundwater flow paths. Using environmental chloride in precipitation, streamflow and groundwater, we apply chloride mass balance (CMB) to estimate NR at multiple catchment scales within the 27 km2 Dry Creek Experimental Watershed (DCEW) on the Boise Front, southwestern Idaho. The estimate for average annual precipitation partitioning to NR is approximately 14% for DCEW. In contrast, as much as 44% of annual precipitation routes to NR in ephemeral headwater catchments. NR in headwater catchments is likely routed to downgradient springs, baseflow, and MBR, while downgradient streamflow losses contribute further to MBR. A key assumption in the CMB approach is that the change in stored chloride during the study period is zero. We found that this assumption is violated in some individual years, but that a 5‐year integration period is sufficient. Copyright © 2011 John Wiley & Sons, Ltd.

Modeling Runoff Generation in a Small Snow‐Dominated Mountainous Catchment

Snowmelt in mountainous areas is an important contributor to river water flows in the western United States. We developed a distributed model that calculates solar radiation, canopy energy balance, surface energy balance, snow pack dynamics, soil water flow, snow–soil–bedrock heat exchange, soil water freezing, and lateral surface and subsurface water flow. The model was applied to describe runoff generation in a subcatchment of the Dry Creek Experimental Watershed near Boise, ID. Calibration was achieved by optimizing the soil water field capacity (a trigger for lateral subsurface flow), lateral saturated soil hydraulic conductivity, and vertical saturated hydraulic conductivity of the bedrock. Validation results show that the model can successfully calculate snow dynamics, soil water content, and soil temperature. Modeled streamflow for the validation period was underestimated by 53%. The timing of the streamflow was captured reasonably well (modeling efficiency was 0.48 for the validation period). The model calculations suggest that 50 to 53% of the yearly incoming precipitation in the subcatchment is consumed by evapotranspiration. The model results further suggest that 34 to 36% of the incoming precipitation is transformed into deep percolation into the bedrock, while only 11 to 16% is transformed into streamflow.

Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho1

Stratton, Benjamin T., Venakataramana Sridhar, Molly M. Gribb, James P. McNamara, and Balaji Narasimhan, 2009. Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho. Journal of the American Water Resources Association (JAWRA) 45(6):1390‐1408.Abstract: The distributed Soil Water Assessment Tool (SWAT) hydrologic model was applied to a research watershed, the Dry Creek Experimental Watershed, near Boise Idaho to investigate its water balance components both temporally and spatially. Calibrating and validating SWAT is necessary to enable our understanding of the water balance components in this semiarid watershed. Daily streamflow data from four streamflow gages were used for calibration and validation of the model. Monthly estimates of streamflow during the calibration phase by SWAT produced satisfactory results with a Nash Sutcliffe coefficient of model efficiency 0.79. Since it is a continuous simulation model, as opposed to an event‐based model, it demonstrated the limited ability in capturing both streamflow and soil moisture for selected rain‐on‐snow (ROS) events during the validation period between 2005 and 2007. Especially, soil moisture was generally underestimated compared with observations from two monitoring pits. However, our implementation of SWAT showed that seasonal and annual water balance partitioning of precipitation into evapotranspiration, streamflow, soil moisture, and drainage was not only possible but closely followed the trends of a typical semiarid watershed in the intermountain west. This study highlights the necessity for better techniques to precisely identify and drive the model with commonly observed climatic inversion‐related snowmelt or ROS weather events. Estimation of key parameters pertaining to soil (e.g., available water content and saturated hydraulic conductivity), snow (e.g., lapse rates, melting), and vegetation (e.g., leaf area index and maximum canopy index) using additional field observations in the watershed is critical for better prediction.

Modeling the Water and Energy Balance of Vegetated Areas with Snow Accumulation

The ability to quantify soil–atmosphere water and energy exchange is important in understanding agricultural and natural ecosystems, as well as the earth's climate. We developed a one‐dimensional vertical model that calculates solar radiation, canopy energy balance, surface energy balance, snowpack dynamics, soil water flow, and snow–soil–bedrock heat exchange, including soil water freezing. The processes are loosely coupled (solved sequentially) to limit the computational burden. The model was applied to describe water and energy dynamics for a northeast‐facing mountain slope in the Dry Creek Experimental Watershed near Boise, ID. Calibration was achieved by optimizing the saturated soil hydraulic conductivity. Validation results showed that the model can successfully calculate seasonal dynamics in snow height, soil water content, and soil temperature. Both the calibration and validation years confirmed earlier results that evapotranspiration on the northeast‐facing slope consumes approximately 60% of yearly precipitation, while deep percolation from the soil profile constitutes about 40% of yearly precipitation.

Modeling soil depth from topographic and land cover attributes

Soil depth is an important input parameter in hydrological and ecological modeling. Presently, the soil depth data available in national soil databases (STATSGO and SSURGO) from the Natural Resources Conservation Service are provided as averages within generalized land units (map units). Spatial uncertainty within these units limits their applicability for distributed modeling in complex terrain. This work reports statistical models for prediction of soil depth in a semiarid mountainous watershed that are based upon the relationship between soil depth and topographic and land cover attributes. Soil depth was surveyed by driving a rod into the ground until refusal at locations selected to represent the topographic and land cover variation in the Dry Creek Experimental Watershed near Boise, Idaho. The soil depth survey consisted of a model calibration set, measured at 819 locations over 8 subwatersheds representing topographic and land cover variability and a model testing set, measured at 130 more broadly distributed locations in the watershed. Many model input variables were developed for regression to the field data. Topographic attributes were derived from a digital elevation model. Land cover attributes were derived from Landsat remote sensing images and high‐resolution aerial photographs. Generalized additive and random forests models were developed to predict soil depth over the watershed. They were able to explain about 50% of the soil depth spatial variation, which is an important improvement over the soil depth extracted from the SSURGO national soil database.

Application of time-lapse ERT imaging to watershed characterization

Time-lapse electrical resistivity tomography (ERT) has many practical applications to the study of subsurface properties and processes. When inverting time-lapse ERT data, it is useful to proceed beyond straightforward inversion of data differences and take advantage of the time-lapse nature of the data. We assess various approaches for inverting and interpreting time-lapse ERT data and determine that two approaches work well. The first approach is model subtraction after separate inversion of the data from two time periods, and the second approach is to use the inverted model from a base data set as the reference model or prior information for subsequent time periods. We prefer this second approach. Data inversion methodology should be consideredwhen designing data acquisition; i.e., to utilize the second approach, it is important to collect one or more data sets for which the bulk of the subsurface is in a background or relatively unperturbed state. A third and commonly used approach to time-lapse inversion, inverting the difference between two data sets, localizes the regions of the model in which change has occurred; however, varying noise levels between the two data sets can be problematic. To further assess the various time-lapse inversion approaches, we acquired field data from a catchment within the Dry Creek Experimental Watershed near Boise, Idaho, U.S.A. We combined the complimentary information from individual static ERT inversions, time-lapse ERT images, and available hydrologic data in a robust interpretation scheme to aid in quantifying seasonal variations in subsurface moisture content.

Spatially distributed temperatures at the base of two mountain snowpacks measured with fiber-optic sensors

AbstractSnowpack base temperatures vary during accumulation and diurnally. Their measurement provides insight into physical, biological and chemical processes occurring at the snow/soil interface. Recent advances in Raman-spectra instruments, which use the scattered light in a standard telecommunications fiber-optic cable to infer absolute temperature along the entire length of the fiber, offer a unique opportunity to obtain basal snow temperatures at resolutions of 1 m, 10 s and 0.1°C. Measurements along a 330 m fiber over 24 hours during late-spring snowmelt at Mammoth Mountain, California, USA, showed basal snow temperatures of 0 ± 0.2°C using 10 s averages. Where the fiber-optic cable traversed bare ground, surface temperatures approached 40°C during midday. The durability of the fiber optic was excellent; no major damage or breaks occurred through the winter of burial. Data from the Dry Creek experimental watershed in Idaho across a small stream valley showed little variability of temperature on the northeast-facing, snow-covered slope, but clearly showed melting patterns and the effects of solar heating on southwest-facing slopes. These proof-of-concept experiments show that the technology enables more detailed spatial and temporal coverage than traditional point measurements of temperature.