How Low Can You Go?: Widespread Challenges in Measuring Low Stream Discharge and a Path Forward

Low flows pose unique challenges for accurately quantifying streamflow. Current field methods are not optimized to measure these conditions, which in turn, limits research and management. In this essay, we argue that the lack of methods for measuring low streamflow is a fundamental challenge that must be addressed to ensure sustainable water management now and into the future, particularly as climate change shifts more streams to increasingly frequent low flows. We demonstrate the pervasive challenge of measuring low flows, present a decision support tool (DST) for navigating best practices in measuring low flows, and highlight important method developmental needs

Quantifying Earth system interactions for sustainable food production via expert elicitation

Several safe boundaries of critical Earth system processes have already been crossed due to human perturbations; not accounting for their interactions may further narrow the safe operating space for humanity. Using expert knowledge elicitation, we explored interactions among seven variables representing Earth system processes relevant to food production, identifying many interactions little explored in Earth system literature. We found that green water and land system change affect other Earth system processes strongly, while land, freshwater and ocean components of biosphere integrity are the most impacted by other Earth system processes, most notably blue water and biogeochemical flows. We also mapped a complex network of mechanisms mediating these interactions and created a future research prioritization scheme based on interaction strengths and existing knowledge gaps. Our study improves the understanding of Earth system interactions, with sustainability implications including improved Earth system modelling and more explicit biophysical limits for future food production

Too many streams and not enough time or money? New analytical depletion functions for rapid and accurate streamflow depletion estimates

Groundwater pumping can cause streamflow depletion by reducing groundwater discharge to streams and/or inducing surface water infiltration. Analytical and numerical models are two standard methods to predict streamflow depletion. Numerical models require extensive data and efforts to develop robust estimates, while analytical models are easy to implement with low data and experience requirements but are limited by numerous simplifying assumptions. We have pioneered a new approach that balances the shortcomings of analytical and numerical models: analytical depletion functions, which include more empirical functions expanding the applicability of analytical models for real-world settings with complex hydrogeologic landscapes and stream networks. Specifically, analytical depletion functions combine analytical models with stream proximity criteria used to determine which stream segments are most likely to be affected by a pumping well and a depletion apportionment equation which is a geometric method to distribute depletion among the affected stream segments. The accuracy of analytical depletion functions has been tested by comparing against a variety of numerical models from simplified, archetypal models to sophisticated, calibrated models in both steady-state to transient conditions. Estimates of streamflow depletion from analytical depletion function generally agree with estimates from numerical models, suggesting analytical depletion functions are an accurate tool for the streamflow depletion assessment over diverse hydrogeological landscapes and scales. Analytical depletion functions are rapidly and easily implemented and have low data requirements like analytical models but have significant advantages of better agreement with numerical models and better representation of complex stream geometries. Relative to numerical models, analytical depletion functions have limited ability to explore non-pumping related impacts and incorporate subsurface heterogeneity. Analytical depletion functions can be used as a stand-alone tool or part of decision-support tools as preliminary screening of potential groundwater pumping impacts when issuing new and existing water licenses while ensuring streamflow meets environmental flow needs

Groundwater effects on net primary productivity and soil organic carbon: a global analysis

Groundwater affects ecosystem services (ES) by altering critical zone ecohydrological and biogeochemical processes. Previous research has demonstrated significant and nonlinear impacts of shallow groundwater on ES regionally, but it remains unclear how groundwater affects ES at the global scale and how such effects respond to environmental factors. Here, we investigated global patterns of groundwater relationships with two ES indicators—net primary productivity (NPP) and soil organic carbon (SOC)—and analyzed underlying factors that mediated groundwater influences. We quantitatively compared multiple high-resolution (∼1 km) global datasets to characterize water table depth (WTD), NPP and SOC, and performed spatial simultaneous autoregressive modeling to test how selected predictors altered WTD-NPP and WTD-SOC relationships. Our results show widespread significant WTD-NPP correlations (61.5% of all basins globally) and WTD-SOC correlations (64.7% of basins globally). Negative WTD-NPP correlations, in which NPP decreased with rising groundwater, were more common than positive correlations (62.4% vs. 37.6%). However, positive WTD-SOC relationships, in which SOC increased with rising groundwater, were slightly more common (53.1%) than negative relationships (46.9%). Climate and land use (e.g., vegetation extent) were dominant factors mediating WTD-NPP and WTD-SOC relationships, whereas topography, soil type and irrigation were also significant factors yet with lesser effects. Climate also significantly constrained WTD-NPP and WTD-SOC relationships, suggesting stronger WTD-NPP and WTD-SOC relationships with increasing temperature. Our results highlight that the relationship of groundwater with ES such as NPP and SOC are spatially extensive at the global scale and are likely to be susceptible to ongoing and future climate and land-use changes

Groundwater pumping impacts on real stream networks: testing the performance of simple management tools

Quantifying reductions in streamflow due to groundwater pumping (‘streamflow depletion’) is essential for conjunctive management of groundwater and surface water resources. Analytical models are widely used to estimate streamflow depletion but include potentially problematic assumptions such as simplified stream-aquifer geometry and rely on largely untested depletion apportionment equations to distribute depletion from a well among different stream reaches. Here, we use archetypal numerical models to evaluate the sensitivity of five depletion apportionment equations to stream networks with varying drainage densities, topographic relief, and groundwater recharge rates; and statistically evaluate the sources of error for each equation. We introduce a new depletion apportionment equation called web squared which considers stream network geometry, and find that it performs the best under most conditions tested. For all depletion apportionment equations, performance decreases with increases in drainage density, relief, or recharge rates, and all equations struggle to estimate depletion in short stream reaches. Poorly performing apportionment equations tend to underestimate streamflow depletion relative to numerical model results, leading to a negative bias and underpredicted variability, while error in the best performing apportionment equations tends to be due to imperfect correlation. From a management perspective, apportionment equations with error due to bias and variability are preferable as they correctly identify which reaches will be affected and can be statistically corrected. Overall, these results indicate that the web squared method introduced here, which explicitly considers stream geometry, performs the best over a range of real-world conditions, and will be most accurate in flatter and drier environments

Presentations and Publications

Publications and Presentations using EPSCoR AIMS data

AIMS' vision and mission

AIMS’ vision is a society that recognizes and values intermittent streams as important for controlling water quality. AIMS’ mission is to understand stream intermittency and its implications for downstream water quality, which requires untangling the hydrologic, biogeochemical, and microbiome controls at the interface of terrestrial and aquatic ecosystems. We will develop resources and tools to study intermittent streams, provide training and education in data science, mentor scientists from the undergraduate to the early career level, and generate insights for evidence-based policy making and land management

Implementation Plan

Implementation Plan for the AIMS project

Rapid and accurate estimates of streamflow depletion caused by groundwater pumping using analytical depletion functions (data and code)

Evaluating analytical depletion functions as a tool for estimating streamflow depletion caused by groundwater pumping. Includes data and code associated with the Zipper et al. (2019) 'Rapid and accurate estimates of streamflow depletion caused by groundwater pumping using analytical depletion functions'. Published in Water Resources Research at http://doi.org/10.1029/2018WR02440