Engineering topics

Deines, Jillian M.

Publications and source records attributed to Deines, Jillian M..

8 records

DOE OSTI2025

Reviews and syntheses: Variable inundation across Earth's terrestrial ecosystems

Abstract. The structure, function, and dynamics of Earth's terrestrial ecosystems are profoundly influenced by how often (frequency) and how long (duration) they are inundated with water. A diverse array of natural and human-engineered systems experience temporally variable inundation whereby they fluctuate between inundated and non-inundated states. Variable inundation spans extreme events to predictable sub-daily cycles. Variably inundated ecosystems (VIEs) include hillslopes, non-perennial streams, wetlands, floodplains, temporary ponds, tidal systems, storm-impacted coastal zones, and human-engineered systems. VIEs are diverse in terms of inundation regimes, water chemistry and flow velocity, soil and sediment properties, vegetation, and many other properties. The spatial and temporal scales of variable inundation are vast, ranging from sub-meter to whole landscapes and from sub-hourly to multi-decadal. The broad range of system types and scales makes it challenging to predict the hydrology, biogeochemistry, ecology, and physical evolution of VIEs. Despite all experiencing the loss and gain of an overlying water column, VIEs are rarely considered together in conceptual, theoretical, modeling, or measurement frameworks and approaches. Studying VIEs together has the potential to generate mechanistic understanding that is transferable across a much broader range of environmental conditions, relative to knowledge generated by studying any one VIE type. We postulate that enhanced transferability will be important for predicting changes in VIE function in response to global change. Here we aim to catalyze cross-VIE science that studies drivers and impacts of variable inundation across Earth's VIEs. To this end, we complement expert mini-reviews of eight major VIE systems with overviews of VIE-relevant methods and challenges associated with scale. We conclude with perspectives on how cross-VIE science can derive transferable understanding via unifying conceptual models in which the impacts of variable inundation are studied across multi-dimensional environmental space.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Enhancing Grid Resilience during Wildfires in Socioeconomic Vulnerable Regions using Powered and Non-Powered Hydro Dams

In many regions around the world, wildfires have become a growing threat, exacerbated by factors such as climate change, droughts, and urban sprawl. These wildfires often wreak havoc on power infrastructure, leading to extended power outages, which can have devastating consequences for communities, especially in socioeconomically vulnerable areas. Ensuring grid resiliency in the face of these challenges is of paramount importance. One innovative approach to mitigating the impact of wildfires on the power grid is the utilization of hydropower facilities including both powered and non-powered hydro dams. While powered hydro dams along with additional infrastructure like energy storage and solar photovoltaic can provide resilience during wildfire-related outages, non-powered dams, originally constructed for purposes other than electricity generation, also offer a unique opportunity to bolster grid resilience. In this paper, we aim to explore the efficacy of hydro-dams in general to provide resiliency during wildfire-induced outages.

Wildfires, Resilience, Grid Resiliency, Hydropower↗

DOE OSTI2024

Unlocking aquifer sustainability through irrigator-driven groundwater conservation

Groundwater depletion caused by intensive pumping for irrigated agriculture is a global threat to economies, food security, and ecosystems. Pumping reductions are required to confront this threat, but their implementation is a “wicked” problem due to interlinked hydrological, social, and economic factors. In the US High Plains Aquifer, an irrigator-led conservation effort known as the Sheridan 6 Local Enhanced Management Area (SD-6 LEMA) is a rare example of successful collective action in agricultural-groundwater systems. In its first decade, the area has exceeded water use reduction goals and decreased depletion rates by over 50% without significantly affecting net income. In this Perspective, we highlight factors underlying the SD-6 LEMA’s effectiveness, and identify transferable governance tenets for other groundwater dependent regions striving for sustainable management of groundwater resources. These tenets include flexibility through multi-year allocations, regulatory oversight to support the irrigators’ plans, and a strong scientific foundation for sustainable agricultural-groundwater systems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Estimating irrigation water use from remotely sensed evapotranspiration data: Accuracy and uncertainties at field, water right, and regional scales

Irrigated agriculture is the dominant user of water globally, but most water withdrawals are not monitored or reported. As a result, it is largely unknown when, where, and how much water is used for irrigation. Here, we evaluated the ability of remotely sensed evapotranspiration (ET) data, integrated with other datasets, to calculate irrigation water withdrawals and applications in an intensively irrigated portion of the United States. We compared irrigation calculations based on an ensemble of satellite-driven ET models from OpenET with reported groundwater withdrawals from hundreds of farmer irrigation application records and a statewide flowmeter database at three spatial scales (field, water right group, and management area). At the field scale, we found that ET-based calculations of irrigation agreed best with reported irrigation when the OpenET ensemble mean was aggregated to the growing season timescale (bias = 1.6–4.9%, R 2 = 0.53–0.74), and agreement between calculated and reported irrigation was better for multi-year averages than for individual years. At the water right group scale, linking pumping wells to specific irrigated fields was the primary source of uncertainty. At the management area scale, calculated irrigation exhibited similar temporal patterns as flowmeter data but tended to be positively biased with more interannual variability. Disagreement between calculated and reported irrigation was strongly correlated with annual precipitation, and calculated and reported irrigation agreed more closely after statistically adjusting for annual precipitation. The selection of an ET model was also an important consideration, as variability across ET models was larger than the potential impacts of conservation measures employed in the region. From these results, we suggest key practices for working with ET-based irrigation data that include accurately accounting for changes in soil moisture, deep percolation, and runoff; careful verification of irrigated area and well-field linkages; and conducting application-specific evaluations of uncertainty.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Observational evidence for groundwater influence on crop yields in the United States

As climate change shifts crop exposure to dry and wet extremes, a better understanding of factors governing crop response is needed. Recent studies identified shallow groundwater—groundwater within or near the crop rooting zone—as influential, yet existing evidence is largely based on theoretical crop model simulations, indirect or static groundwater data, or small-scale field studies. Here, we use observational satellite yield data and dynamic water table simulations from 1999 to 2018 to provide field-scale evidence for shallow groundwater effects on maize yields across the United States Corn Belt. We identify three lines of evidence supporting groundwater influence: 1) crop model simulations better match observed yields after improvements in groundwater representation; 2) machine learning analysis of observed yields and modeled groundwater levels reveals a subsidy zone between 1.1 and 2.5 m depths, with yield penalties at shallower depths and no effect at deeper depths; and 3) locations with groundwater typically in the subsidy zone display higher yield stability across time. We estimate an average 3.4% yield increase when groundwater levels are at optimum depth, and this effect roughly doubles in dry conditions. Groundwater yield subsidies occur ~35% of years on average across locations, with 75% of the region benefitting in at least 10% of years. Overall, we estimate that groundwater-yield interactions had a net monetary contribution of approximately $10 billion from 1999 to 2018. This study provides empirical evidence for region-wide groundwater yield impacts and further underlines the need for better quantification of groundwater levels and their dynamic responses to short- and long-term weather conditions.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Further adoption of conservation tillage can increase maize yields in the western US Corn Belt

Conservation tillage can reduce soil erosion, increase soil health, and decrease labor and fuel input costs. Despite these benefits, potential yield impacts remain an important concern for farmers considering adoption. Previous research suggests that conservation tillage is likely to have the largest yield benefits in more arid conditions, but a lack of field-level analyses across climatic, management and soil conditions limits confidence in such predictions. Satellite imagery provides the opportunity to monitor agricultural lands at sub-field resolution across large spatial scales and wide environmental gradients. Here we investigate the maize yield impacts of conservation tillage in the semi-arid western US Corn Belt, using sub-field resolution datasets on tillage practices and crop yields derived from satellite data spanning four states (Nebraska, Kansas, South Dakota, and North Dakota) between 2008 and 2020. On these datasets, we estimate heterogenous yield outcomes for several thousand maize fields across gradients in climate, soil quality and irrigation status by using a causal forests analysis, an adaptation of the random forests machine-learning algorithm for causal inference on observational data. We find that long-term adoption of conservation tillage increased rainfed maize yields by an average of 9.9% in the region. Impacts on irrigated yields were small and not statistically significant. These results, along with an analysis of variables related to greater than average yield benefits, indicate that improved water infiltration and retention are the primary reasons for conservation tillage benefits. Despite yield benefits, many fields estimated to see increased yields under long term low till have not adopted the practice. Therefore, we identify specific counties likely to benefit most from increased levels of adoption. Our results strengthen the understanding of the impacts of conservation agriculture on crop yields and help define environments and counties most likely to benefit from conservation tillage.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Forming the Future of Agrohydrology

Agricultural water management is increasingly prioritized throughout the world as producers are tasked with meeting growing crop demand while also managing environmental resources more sustainably. Likewise, agriculture is increasingly modifying the terrestrial water cycle. In response to these dynamics, the informal research discipline of agrohydrology continues to grow, fueled by a new era of rapidly evolving research tools and big data availability. While many researchers are actively invested in agrohydrology as a research topic, there remains a gap in formalizing this valuable discipline. This article aims to: (a) identify key research themes in agrohydrology, (b) conceptualize future research topics within each theme, and (c) estimate a timeframe before topics become pressing (i.e., before a topic becomes a limiting factor in advancing water management in an agricultural context). This commentary is meant to guide the trajectory of an evolving discipline of agrohydrology, the practice of agricultural water management at multiple nested scales, and the conversation of the invested public.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Wildfire Risk Evaluation Framework for Grid Operations and Planning

The United States (US) environmental protection agency's (EPA's) climate change indicators for wildfires show a long-term trend of increased annual wildfire activity, larger wildfire size, and more variable dynamics in wildfire behavior. This has caused more frequent preemptive public safety power shutoff (PSPS) events in the regions with recognized high wildfire risk. These preemptive power shutoffs attempt to prevent the ignition of a wildfire but it nonetheless renders the transmission line non-operational, which often sheds load of downstream communities. As wildfires and PSPS events become more frequent, it is crucial to find the communities most at risk of load shedding. To that end, this paper proposes the wildfire risk evaluation of the system (WiRES) framework, which is a performance-based framework that translates extreme weather-related and PSPS event probabilities into a cumulative probability of a non-operational transmission line. This study also provides a geospatial visualization tool that breaks down the entire western electrical coordinating council (WECC) region into 50 km grid cells which can be used to 1) filter out transmission lines with higher than a threshold outage probability, and 2) graphically discover the affected regions and their biophysical and socioeconomic metrics. %such as the social vulnerability index, population density, gross domestic product, etc. Lastly, an impact assessment study is conducted which connects the results of the proposed framework to python and powerworld-based contingency analysis to highlight the applicability of the framework.

Wildfire, Resilience, Extreme Events, Grid Reslien↗