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Scaling in situ soil water content time series data to a large spatial domain is a key element of watershed environmental monitoring and modeling. The primary method of estimating and monitoring large-scale soil water content distributions is via in situ networks. It is critical to establish the stability of in situ networks when deploying them to study hydrologic systems. Two watersheds in Oklahoma, the Little Washita River Experimental Watershed (LWREW) and the Fort Cobb Reservoir Experimental Watershed (FCREW), are two prime examples of well-equipped research watersheds that provide long-term measurements of atmospheric and soil water content from in situ networks. The soil water content measurement network on the LWREW has been in operation since 2002, with 20 stations available for investigating soil water dynamics at the watershed scale. Temporal stability analysis of the network is complicated by the changing configuration of the network, but it is possible to determine a singular long-term average for the network. The FCREW consists of 15 soil water content stations and began operation in 2007, providing detailed information across a mixed agricultural domain and was determined to be stable and representative of the region. This study reinforces the applicability of temporal stability analysis to very long time scales, which are now becoming available for soil moisture monitoring. Each of these networks is temporally stable with respect to soil water content at each depth on a spatial basis. The LWREW has a persistent pattern through the root zone profile, but the FCREW does not, which requires further investigation. [ABSTRACT FROM AUTHOR]

Physiographic data such as digital elevation models (DEMs), soils, geology, stream channel network characteristics, channel stability, and land use data are essential for understanding the complex hydrologic cycle and chemical transport processes of any given study area. We describe the physiographic data available in the Little Washita River Experimental Watershed (LWREW) and Fort Cobb Reservoir Experimental Watershed (FCREW) in Oklahoma. Specifically, we describe (i) available raw and post-processed DEM products (ftp://164.58.150.21/DEM/), (ii) available soils data (ftp://164.58.150.21/FT_Cobb_Reservoir_Watershed_2005-2012/GIS-DataSets/Physiography/Soils/ and ftp://164.58.150.21/Little_Washita_River_Research_Watershed_Other/GIS_Datasets/Physiography/Soils) and associated error analysis based on limited measured data, (iii) geologic formations in the LWREW and FCREW (ftp://164.58.150.21/FT_Cobb_Reservoir_Watershed_2005-2012/GISDataSets/Physiography/Geology/FCREW_Geology/ and ftp://164.58.150.21/Little_ Washita_River_Research_Watershed_Other/GIS_Datasets/Physiography/Geology/), and (iv) available rapid geomorphic assessment measurements (ftp://164.58.150.21/FT_Cobb_Reservoir_Watershed_2005-2012/GIS-DataSets/Physiography/ RGA/) and their uses. Data collection is a collaborative effort among USGS, NRCS, and ARS. These data sets have been used for several research applications by USDA-ARS scientists and researchers from other institutions and agencies. Plans for detailed geomorphic assessment of stream channel networks in the FCREW are underway in collaboration with Oklahoma State University in Stillwater. The collected data will enable updating of the channel stability stage condition since there have been several major rainfall events in the watershed since the last geomorphic assessment. [ABSTRACT FROM AUTHOR]

Surface and groundwater quantity and quality data are essential in many hydrologic applications and to the development of hydrologic and water quality simulation models. We describe the hydrologic data available in the Little Washita River Experimental Watershed (LWREW) of the Southern Great Plains Research Watershed (SGPRW) and Fort Cobb Reservoir Experimental Watershed (FCREW), both located in southwest Oklahoma. Specifically, we describe the flood retarding structures and corresponding stage, discharge, seepage, and consumptive use data (http://www.usbr.gov/gp-bin/arcweb_cobb.pl), stream gauges, and groundwater wells and their corresponding stream flow (http://waterdata.usgs.gov/ok/nwis/sw; LWREW ARS 522-526 stream gauges) and groundwater level data (SGPRW groundwater levels data; LWREW groundwater data; http://waterdata.usgs.gov/ok/nwis/inventory; http://nwis.waterdata. usgs.gov/ok/nwis/gwlevels), respectively. Data collection is a collaborative effort between federal and state agencies. Stage, discharge, seepage, and consumptive use data for the Fort Cobb Reservoir are available from the Bureau of Reclamation and cover a period of 1959 to present. There are 15 stream gauges in the LWREW and six in the FCREW with varying data records. There were 479 observation wells with data in the SGPRW and 80 in the LWREW, with the latest records collected in 1992. In addition, groundwater level data are available from five real-time monitoring wells and 34 historical wells within the FCREW. These data sets have been used for several research applications. Plans for detailed groundwater data collection are underway to calibrate and validate the linked Soil and Water Assessment Tool (SWAT)-MODFLOW model. Also, plans are underway to conduct reservoir bathymetric surveys to determine the current reservoir capacity as affected by land use/land cover and overland and stream channel soil erosion. [ABSTRACT FROM AUTHOR]

The presence of non-stationary conditions in long-term hydrologic observation networks is associated with natural and anthropogenic stressors or network operation problems. Detection and identification of network operation drivers is fundamental in hydrologic investigation due to changes in systematic errors that can exacerbate modeling results or bias research conclusions. We applied a data screening procedure to the USDA-ARS experimental watersheds data sets (ftp://164.58.150.21) in Oklahoma. Detection of statistically significant monotonic trends and changes in mean and variance were used to investigate non-stationary conditions with network operation drivers to assess the impact of changes in the amount of systematic error. Detection of spurious data, filling in missing data, and data screening procedures were applied to >1000 time series, and processed data were made publicly available. The SPELLmap application was used for data processing and statistical tests on watershed segregated data sets and temporally aggregated data. A test for independency (Anderson test), normality, monotonic trend (Spearman test), detection of change point (Pettitt test), and split record test (F and t-tests) were used to assess non-stationary conditions. Statistically significant (95% confidence limit) monotonic trends and changes in mean and variance were detected for annual maximum air temperature, rainfall, relative humidity, and solar radiation and in maximum and minimum soil temperature time series. Network operation procedures such as change in calibration protocols and sensor upgrades as well as natural regional weather trends were suspected as driving the detection of statistically significant trends and changes in mean and variance. We concluded that a data screening procedure that identifies changes in systematic errors and detection of false non-stationary conditions in hydrologic problems is fundamental before any modeling applications. [ABSTRACT FROM AUTHOR]

Water is central to life and earth processes, connecting physical, biological, chemical, ecological, and economic forces across the landscape. The vast scope of hydrologic sciences requires research efforts worldwide and across a wide range of disciplines. While hydrologic processes and scientific investigations related to sustainable agricultural systems are based on universal principles, research to understand processes and evaluate management practices is often site-specific to achieve a critical mass of expertise and research infrastructure to address spatially, temporally, and ecologically complex systems. In the face of dynamic climate, market, and policy environments, long-term research is required to understand and predict risks and possible outcomes of alternative scenarios. This special section describes the USDA-ARS's long-term research (1961 to present) in the Upper Washita River basin of Oklahoma. Data papers document datasets in detail (weather, hydrology, physiography, land cover, and sediment and nutrient water quality), and associated research papers present analyses based on those data. This living history of research is presented to engage collaborative scientists across institutions and disciplines to further explore complex, interactive processes and systems. Application of scientific understanding to resolve pressing challenges to agriculture while enhancing resilience of linked land and human systems will require complex research approaches. Research areas that this watershed research program continues to address include: resilience to current and future climate pressures; sources, fate, and transport of contaminants at a watershed scale; linked atmospheric-surface-subsurface hydrologic processes; high spatiotemporal resolution analyses of linked hydrologic processes; and multiple-objective decision making across linked farm to watershed scales. [ABSTRACT FROM AUTHOR]