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1. Can Managed Aquifer Recharge Overcome Multiple Droughts?

   https://doi.org/10.3390/w13162278  

   Zhao, Mengqi ; Boll, Jan ; Adam, Jennifer C. ; Beall King, Allyson ( August 2021 , Water)

   null (Ed.)

   Frequent droughts, seasonal precipitation, and growing agricultural water demand in the Yakima River Basin (YRB), located in Washington State, increase the challenges of optimizing water provision for agricultural producers. Increasing water storage through managed aquifer recharge (MAR) can potentially relief water stress from single and multi-year droughts. In this study, we developed an aggregated water resources management tool using a System Dynamics (SD) framework for the YRB and evaluated the MAR implementation strategy and the effectiveness of MAR in alleviating drought impacts on irrigation reliability. The SD model allocates available water resources to meet instream target flows, hydropower demands, and irrigation demand, based on system operation rules, irrigation scheduling, water rights, and MAR adoption. Our findings suggest that the adopted infiltration area for MAR is one of the main factors that determines the amount of water withdrawn and infiltrated to the groundwater system. The implementation time frame is also critical in accumulating MAR entitlements for single-year and multi-year droughts mitigation. In addition, adoption behaviors drive a positive feedback that MAR effectiveness on drought mitigation will encourage more MAR adoptions in the long run. MAR serves as a promising option for water storage management and a long-term strategy for MAR implementation can improve system resilience to unexpected droughts. 

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2. Unprecedented Drought Challenges for Texas Water Resources in a Changing Climate: What Do Researchers and Stakeholders Need to Know?

   https://doi.org/10.1029/2020EF001552  

   Nielsen‐Gammon, John W. ; Banner, Jay L. ; Cook, Benjamin I. ; Tremaine, Darrel M. ; Wong, Corinne I. ; Mace, Robert E. ; Gao, Huilin ; Yang, Zong‐Liang ; Gonzalez, Marisa Flores ; Hoffpauir, Richard ; et al ( August 2020 , Earth's Future)

   Long‐range water planning is complicated by factors that are rapidly changing in the 21st century, including climate, population, and water use. Here, we analyze climate factors and drought projections for Texas as an example of a diverse society straddling an aridity gradient to examine how the projections can best serve water stakeholder needs. We find that climate models are robust in projecting drying of summer‐season soil moisture and decreasing reservoir supplies for both the eastern and western portions of Texas during the 21st century. Further, projections indicate drier conditions during the latter half of the 21st century than even the most arid centuries of the last 1,000 years that included megadroughts. To illustrate how accounting for drought nonstationarity may increase water resiliency, we consider generalized case studies involving four key stakeholder groups: agricultural producers, large surface water suppliers, small groundwater management districts, and regional water planning districts. We also examine an example of customized climate information being used as input to long‐range water planning. We find that while stakeholders value the quantitative capability of climate model outputs, more specific climate‐related information better supports resilience planning across multiple stakeholder groups. New suites of tools could provide necessary capacity for both short‐ and long‐term, stakeholder‐specific adaptive planning.

    

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3. Learning and flexibility for water supply infrastructure planning under groundwater resource uncertainty

   https://doi.org/10.1088/1748-9326/ab4664  

   Fletcher, Sarah ; Strzepek, Kenneth ; Alsaati, Adnan ; de Weck, Olivier ( November 2019 , Environmental Research Letters)

   Water supply infrastructure planning in groundwater-dependent regions is often challenged by uncertainty in future groundwater resource availability. Many major aquifer systems face long-term water table decline due to unsustainable withdrawals. However, many regions, especially those in the developing world, have a scarcity of groundwater data. This creates large uncertainties in groundwater resource predictions and decisions about whether to develop alternative supply sources. Developing infrastructure too soon can lead to unnecessary and expensive irreversible investments, but waiting too long can threaten water supply reliability. This study develops an adaptive infrastructure planning framework that applies Bayesian learning on groundwater observations to assess opportunities to learn about groundwater availability in the future and adapt infrastructure plans. This approach allows planners in data scarce regions to assess under what conditions a flexible infrastructure planning approach, in which initial plans are made but infrastructure development is deferred, can mitigate the risk of overbuilding infrastructure while maintaining water supply reliability in the face of uncertainty. This framework connects engineering options analysis from infrastructure planning to groundwater resources modeling. We demonstrate a proof-of-concept on a desalination planning case for the city of Riyadh, Saudi Arabia, where poor characterization of a fossil aquifer creates uncertainty in how long current groundwater resources can reliably supply demand. We find that a flexible planning approach reduces the risk of over-building infrastructure compared to a traditional static planning approach by 40% with minimal reliability risk (<1%). This striking result may be explained by the slow-evolving nature of groundwater decline, which provides time for planners to react, in contrast to more sudden risks such as flooding where tradeoffs between cost and reliability risk are heightened. This Bayesian approach shows promise for many civil infrastructure domains by providing a method to quantify learning in environmental modeling and assess the effectiveness of adaptive planning.

    

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4. Water shortage risks from perennial crop expansion in California’s Central Valley

   https://doi.org/10.1088/1748-9326/ab4035  

   Mall, Natalie K. ; Herman, Jonathan D. ( October 2019 , Environmental Research Letters)

   California’s Central Valley is one of the world’s most productive agricultural regions. Its high-value fruit, vegetable, and nut crops rely on surface water imports from a vast network of reservoirs and canals as well as groundwater, which has been substantially overdrafted to support irrigation. The region has undergone a shift to perennial (tree and vine) crops in recent decades, which has increased water demand amid a series of severe droughts and emerging regulations on groundwater pumping. This study quantifies the expansion of perennial crops in the Tulare Lake Basin, the southern region of the Central Valley with limited natural water availability. A gridded crop type dataset is compiled on a 1 mi²spatial resolution from a historical database of pesticide permits over the period 1974–2016 and validated against aggregated county-level data. This spatial dataset is then analyzed by irrigation district, the primary spatial scale at which surface water supplies are determined, to identify trends in planting decisions and agricultural water demand over time. Perennial crop acreage has nearly tripled over this period, and currently accounts for roughly 60% of planted area and 80% of annual revenue. These trends show little relationship with water availability and have been driven primarily by market demand. From this data, we focus on the increasing minimum irrigation needs each year to sustain perennial crops. Results indicate that under a range of plausible future regulations on groundwater pumping ranging from 10% to 50%, water supplies may fail to consistently meet demands, increasing losses by up to 30% of annual revenues. More broadly, the datasets developed in this work will support the development of dynamic models of the integrated water-agriculture system under uncertain climate and regulatory changes to understand the combined impacts of water supply shortages and intensifying irrigation demand.

    

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5. Hydrologic functioning of the deep critical zone and contributions to streamflow in a high‐elevation catchment: Testing of multiple conceptual models

   https://doi.org/10.1002/hyp.13363  

   Dwivedi, Ravindra ; Meixner, Thomas ; McIntosh, Jennifer C. ; Ferré, P. A. Ty ; Eastoe, Christopher J. ; Niu, Guo‐Yue ; Minor, Rebecca L. ; Barron‐Gafford, Greg A. ; Chorover, Jon ( January 2019 , Hydrological Processes)

   High‐elevation mountain catchments are often subject to large climatic and topographic gradients. Therefore, high‐density hydrogeochemical observations are needed to understand water sources to streamflow and the temporal and spatial behaviour of flow paths. These sources and flow paths vary seasonally, which dictates short‐term storage and the flux of water in the critical zone (CZ) and affect long‐term CZ evolution. This study utilizes multiyear observations of chemical compositions and water residence times from the Santa Catalina Mountains Critical Zone Observatory, Tucson, Arizona to develop and evaluate competing conceptual models of seasonal streamflow generation. These models were tested using endmember mixing analysis, baseflow recession analysis, and tritium model “ages” of various catchment water sources. A conceptual model involving four endmembers (precipitation, soil water, shallow, and deep groundwater) provided the best match to observations. On average, precipitation contributes 39–69% (55 ± 16%), soil water contributes 25–56% (41 ± 16%), shallow groundwater contributes 1–5% (3 ± 2%), and deep groundwater contributes ~0–3% (1 ± 1%) towards annual streamflow. The mixing space comprised two principal planes formed by (a) precipitation‐soil water‐deep groundwater (dry and summer monsoon season samples) and (b) precipitation‐soil water‐shallow groundwater (winter season samples). Groundwater contribution was most important during the wet winter season. During periods of high dynamic groundwater storage and increased hydrologic connectivity (i.e., spring snowmelt), stream water was more geochemically heterogeneous, that is, geochemical heterogeneity of stream water is storage‐dependent. Endmember mixing analysis and³H model age results indicate that only 1.4 ± 0.3% of the long‐term annual precipitation becomes deep CZ groundwater flux that influences long‐term deep CZ development through both intercatchment and intracatchment deep groundwater flows.

    

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