Assessing placement bias of the global river gauge network.

Knowing where and when rivers flow is paramount to managing freshwater ecosystems. Yet stream gauging stations are distributed sparsely across rivers globally and may not capture the diversity of fluvial network properties and anthropogenic influences. Here we evaluate the placement bias of a global stream gauge dataset on its representation of socioecological, hydrologic, climatic and physiographic diversity of rivers. We find that gauges are located disproportionally in large, perennial rivers draining more human-occupied watersheds. Gauges are sparsely distributed in protected areas and rivers characterized by non-perennial flow regimes, both of which are critical to freshwater conservation and water security concerns. Disparities between the geography of the global gauging network and the broad diversity of streams and rivers weakens our ability to understand critical hydrologic processes and make informed water-management and policy decisions. Our findings underscore the need to address current gauge placement biases by investing in and prioritizing the installation of new gauging stations, embracing alternative water-monitoring strategies, advancing innovation in hydrologic modelling, and increasing accessibility of local and regional gauging data to support human responses to water challenges, both today and in the future.

River ecosystem conceptual models and non-perennial rivers: A critical review.

Conceptual models underpin river ecosystem research. However, current models focus on continuously flowing rivers and few explicitly address characteristics such as flow cessation and drying. The applicability of existing conceptual models to nonperennial rivers that cease to flow (intermittent rivers and ephemeral streams, IRES) has not been evaluated. We reviewed 18 models, finding that they collectively describe main drivers of biogeochemical and ecological patterns and processes longitudinally (upstream-downstream), laterally (channel-riparian-floodplain), vertically (surface water-groundwater), and temporally across local and landscape scales. However, perennial rivers are longitudinally continuous while IRES are longitudinally discontinuous. Whereas perennial rivers have bidirectional lateral connections between aquatic and terrestrial ecosystems, in IRES, this connection is unidirectional for much of the time, from terrestrial-to-aquatic only. Vertical connectivity between surface and subsurface water occurs bidirectionally and is temporally consistent in perennial rivers. However, in IRES, this exchange is temporally variable, and can become unidirectional during drying or rewetting phases. Finally, drying adds another dimension of flow variation to be considered across temporal and spatial scales in IRES, much as flooding is considered as a temporally and spatially dynamic process in perennial rivers. Here, we focus on ways in which existing models could be modified to accommodate drying as a fundamental process that can alter these patterns and processes across spatial and temporal dimensions in streams. This perspective is needed to support river science and management in our era of rapid global change, including increasing duration, frequency, and occurrence of drying.

Zero or not? Causes and consequences of zero-flow stream gage readings.

Streamflow observations can be used to understand, predict, and contextualize hydrologic, ecological, and biogeochemical processes and conditions in streams. Stream gages are point measurements along rivers where streamflow is measured, and are often used to infer upstream watershed-scale processes. When stream gages read zero, this may indicate that the stream has fully dried; however, zero-flow readings can also be caused by a wide range of other factors. Our ability to identify whether or not a zero-flow gage reading indicates a dry fluvial system has far reaching environmental implications. Incorrect identification and interpretation by the data user can lead to hydrologic, ecological, and/or biogeochemical predictions from models and analyses. Here, we describe several causes of zero-flow gage readings: frozen surface water, flow reversals, instrument error, and natural or human-driven upstream source losses or bypass flow. For these examples, we discuss the implications of zero-flow interpretations. We also highlight additional methodss for determining flow presence, including direct observations, statistical methods, and hydrologic models, which can be applied to interpret causes of zero-flow gage readings and implications for reach- and watershed-scale dynamics. Such efforts are necessary to improve our ability to understand and predict surface flow activation, cessation, and connectivity across river networks. Developing this integrated understanding of the wide range of possible meanings of zero-flows will only attain greater importance in a more variable and changing hydrologic climate.

Topographic controls of soil organic carbon on soil-mantled landscapes.

Large uncertainties in global carbon (C) budgets stem from soil carbon estimates and associated challenges in distributing soil organic carbon (SOC) at local to landscape scales owing to lack of information on soil thickness and controls on SOC storage. Here we show that 94% of the fine-scale variation in total profile SOC within a 1.8 km2 semi-arid catchment in Idaho, U.S.A. can be explained as a function of aspect and hillslope curvature when the entire vertical dimension of SOC is measured and fine-resolution (3 m) digital elevation models are utilized. Catchment SOC stocks below 0.3 m depth based on our SOC-curvature model account for >50% of the total SOC indicating substantial underestimation of stocks if sampled at shallower depths. A rapid assessment method introduced here also allows for accurate catchment-wide total SOC inventory estimation with a minimum of one soil pit and topographic data if spatial distribution of total profile SOC is not required. Comparison of multiple datasets shows generality in linear SOC-curvature and -soil thickness relationships at multiple scales. We conclude that mechanisms driving variations in carbon storage in hillslope catchment soils vary spatially at relatively small scales and can be described in a deterministic fashion given adequate topographic data.

Predicting soil thickness on soil mantled hillslopes.

Soil thickness is a fundamental variable in many earth science disciplines due to its critical role in many hydrological and ecological processes, but it is difficult to predict. Here we show a strong linear relationship (r2 = 0.87, RMSE = 0.19 m) between soil thickness and hillslope curvature across both convergent and divergent parts of the landscape at a field site in Idaho. We find similar linear relationships across diverse landscapes (n = 6) with the slopes of these relationships varying as a function of the standard deviation in catchment curvatures. This soil thickness-curvature approach is significantly more efficient and just as accurate as kriging-based methods, but requires only high-resolution elevation data and as few as one soil profile. Efficiently attained, spatially continuous soil thickness datasets enable improved models for soil carbon, hydrology, weathering, and landscape evolution.