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Aim: As climate change increases the frequency and severity of droughts in many regions, conservation during drought is becoming a major challenge for ecologists. Droughts are multidimensional climate events whose impacts may be moderated by changes in temperature, water availability or food availability, or some combination of these. Simultaneously, other stressors such as extensive anthropogenic landscape modification may synergize with drought. Useful observational models for guiding conservation decision‐making during drought require multidimensional, dynamic representations to disentangle possible drought impacts, and consequently, they will require large, highly resolved data sets. In this paper, we develop a two‐stage predictive framework for assessing how drought impacts vary with species, habitats and climate pathways. Location: Central Valley, California, USA. Methods: We used a two‐stage counterfactual analysis combining predictive linear mixed models and N‐mixture models to characterize the multidimensional impacts of drought on 66 bird species. We analysed counts from the eBird participatory science data set between 2010 and 2019 and produced species‐ and habitat‐specific estimates of the impact of drought on relative abundance. Results: We found that while fewer than a quarter (16/66) of species experienced abundance declines during drought, nearly half of all species (27/66) changed their habitat associations during drought. Among species that shifted their habitat associations, the use of natural habitats declined during drought while use of developed habitat and perennial agricultural habitat increased. Main Conclusions: Our findings suggest that birds take advantage of agricultural and developed land with artificial irrigation and heat‐buffering microhabitat structure, such as in orchards or parks, to buffer drought impacts. A working lands approach that promotes biodiversity and mitigates stressors across a human‐induced water gradient will be critical for conserving birds during drought. [ABSTRACT FROM AUTHOR]

The spatial heterogeneity related to complex topography in California demands high-resolution (< 5 km) modeling, but global convection-permitting climate models are computationally too expensive to run multi-decadal simulations. We developed a 3.25 km California climate modeling framework by leveraging regional mesh refinement (CARRM) using the U.S. Department of Energy (DOE)'s global Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) version 0. Four 5-year time periods (2015–2020, 2029–2034, 2044–2049, and 2094–2099) were simulated by nudging CARRM outside California to 1° coupled simulation of E3SMv1 under the Shared Socioeconomic Pathways (SSP)5-8.5 future scenario. The 3.25 km grid spacing adds considerable value to the prediction of the California climate changes, including more realistic high temperatures in the Central Valley and much improved spatial distributions of precipitation and snowpack in the Sierra Nevada and coastal stratocumulus. Under the SSP5-8.5 scenario, CARRM simulation predicts widespread warming of 6–10 °C over most of California, a 38 % increase in statewide average 30 d winter–spring precipitation, a near-complete loss of the alpine snowpack, and a sharp reduction in shortwave cloud radiative forcing associated with marine stratocumulus by the end of the 21st century. We note a climatological wet precipitation bias for the CARRM and discuss possible reasons. We conclude that SCREAM RRM is a technically feasible and scientifically valid tool for climate simulations in regions of interest, providing an excellent bridge to global convection-permitting simulations. [ABSTRACT FROM AUTHOR]

Water allocation institutions globally must operate within legal and political contexts established by precedent and codified in operating rules, even as they flex and adjust to climate change. California's Central Valley Water System (CVS) is a prime example. Recent global, national, regional, and local climate change assessments have highlighted climate-change-driven impacts on the CVS; however, these previous studies have not discussed the relative likelihood of performance decline, making it difficult to use the information for planning. In response, this paper presents a systematic climate change stress test that utilizes a physically based hydrologic model linked with a water resources system model representing the infrastructure, operations, and policy constraints of the interconnected system of natural river channels and man-made facilities that comprise the CVS. The results provide a summary of the sensitivity of the system to climate change, indicating the specific climate changes that cause performance of the system to decline below historical norms, and an estimation of the General Circulation Model (GCM) informed probability of those changes by 2050. Degraded performance is especially likely for State Water Project (SWP) deliveries (> 85%), and September carryover/drought storage in the Oroville Reservoir (the SWP's largest reservoir, ~ 95% likely to degrade). A decline in Net Delta Outflow is likely in all seasons except summer and early fall (when regulations require supplemental releases to combat salinity from sea level rise). For most of these metrics, the modeled performance drop is more severe in dry years than in wet years. [ABSTRACT FROM AUTHOR]

A three‐dimensional variably saturated flow model was developed for assessing future global water resources and parameterized for groundwater pumping. We applied this model to an actual watershed to verify its validity as an Earth System Model. For global applicability, the parameterization method for multi‐layered groundwater pumping was developed and verified through comparison with observations and MODFLOW results. The parameterization proposed in this study is applicable even when multiple groundwater pumping wells are present within one horizontal computational grid and when the well spans multiple vertical grids. This method can be applied at the global scale without parameters such as the well radius, for which data may be difficult to obtain. The parameterization recreated seasonal and annual variations in the observed values. Furthermore, the results were comparable to those of MODFLOW. However, the calculation results were overestimated relative to the observed values. This overestimation was likely to be due to active groundwater pumping in the Central Valley before the start of the unsteady‐state calculation. Therefore, the groundwater level at the beginning of the unsteady‐state calculation was calculated using observed values, improving reproducibility. Furthermore, as observed groundwater levels are unlikely to be available at the global scale, steady‐state calculations were conducted over 15 and 60 years considering groundwater pumping. However, the results were not as reproducible as those obtained using observed groundwater levels. These results suggest that the groundwater level set at the beginning of the calculation is important for global‐scale groundwater flow calculation. Plain Language Summary: Water resources are expected to become strained in the future due to climate change and population growth. The main focus of water resource assessments conducted to date has been on river water. Although groundwater is an important component of water resources, it has generally not been considered. This is largely due to the lack of groundwater models that can be applied at a global scale. Therefore, we developed a new groundwater model that was parameterized for groundwater pumping and validated in plains. The results of this study indicate that parameterization of groundwater pumping can produce reasonable results relative to observed values, and that the groundwater level set at the beginning of the calculation is important for the evaluation and prediction of global water resources. In particular, collection of observed groundwater levels or estimation of groundwater pumping are key steps toward more realistic prediction. Key Points: A three‐dimensional variably saturated flow model for use as an Earth System Model was developed and parameterized for groundwater pumpingThe validation results reproduced observations to some extent and were comparable to those of MODFLOW in the Central ValleyThe results show that setting the groundwater level at the beginning of the unsteady‐state simulation is important for global‐scale [ABSTRACT FROM AUTHOR]

An extreme precipitation event produced catastrophic debris flows in central Chile during 29–31 January 2021 (austral summer). Our study focuses on the triggering factors and dynamic behavior of hail-debris flows affecting the small commune of Malloa (Central Valley), which caused 200 injured individuals and 73 damaged houses. We carried out a post-event detailed field mapping of the local geology, the erosional features on the ravines, and its related hail-debris flow deposits. In parallel, the study involved a socio-cultural analysis of vulnerability to debris flows, with a particular focus on the disaster experience of the local community. Our results indicate that these hail-debris flows were likely conditioned by extended drought, local geomorphology, bedrock weathering/alteration, and water-oversaturated soil by two antecedent precipitation pulses. Soil erosion triggered by a hailstorm during a third precipitation pulse initiated hail-debris flows from small basins (< 1.2 km2). Basin concentration times were estimated in 6–8 min, while hail reduced flow resistance by interparticle lubrication, promoting peak flow velocities near 2.4 to 5.5 m/s. Debris flow risk management should focus on developing suitable infrastructure and installing capacities at the local level as an essential condition for implementing subsequent inter-sectoral actions (for prevention, mitigation, and design risk scenarios). [ABSTRACT FROM AUTHOR]

People seek reliable natural resources despite climate change. Diverse habitats and biologies stabilize productivity against disturbances like climate, prompting arguments to promote climate‐resilient resources by prioritizing complex, less‐modified ecosystems. These arguments hinge on the hypothesis that simplifying and degrading ecosystems will reduce resources' climate resilience, a process liable to be cryptically evolving across landscapes and human generations, but rarely documented. Here, we examined the industrial era (post 1848) of California's Central Valley, chronicling the decline of a diversified, functional portfolio of salmon habitats and life histories and investigating for empirical evidence of lost climate resilience in its fishery. Present perspectives indicate that California's dynamic, warming climate overlaid onto its truncated, degraded habitat mosaic severely constrains its salmon fishery. We indeed found substantial climate constraints on today's fishery, but this reflected a shifted ecological baseline. During the early stages of a stressor legacy that transformed the landscape and ‐‐ often consequently ‐‐ compressed salmon life history expression, the fishery diffused impacts of dry years across a greater number of fishing years and depended less on cool spring‐summer transitions. The latter are important given today's salmon habitats, salmon life histories, and resource management practices, but are vanishing with climate change while year‐to‐year variation in fishery performance is rising. These findings give empirical weight to the idea that human legacies influence ecosystems' climate resilience across landscapes and boundaries (e.g., land/sea). They also raise the question of whether some contemporary climate effects are recent and attributable not only to increasing climate stress, but to past and present human actions that erode resilience. In general, it is thus worth considering that management approaches that prioritize complex, less‐modified ecosystems may stabilize productivity despite increasing climate stress and such protective actions may be required for some ecological services to persist into uncertain climate futures. [ABSTRACT FROM AUTHOR]

Groundwater depletion is a major threat to agricultural and municipal water supply in California's Central Valley. Recent droughts during 2007–2009 and 2012–2016 exacerbated chronic groundwater depletion. However, it is unclear how much groundwater storage recovered from drought‐related overdrafts during post‐drought years, and how climatic conditions and water management affected recovery times. We estimated groundwater storage change in the Central Valley for April 2002 through September 2019 using four methods: GRACE satellite data, a water balance approach, a hydrologic simulation model, and monitoring wells. We also evaluated the sensitivity of drought recovery to different climate scenarios (recent climate ± droughts and future climate change scenarios: 20 GCMs and 2 RCPs) using water balance method and statistical sampling of historical climate data. Estimated Central Valley groundwater loss during the two droughts ranged from 19 km3 (2007–2009) to 28 km3 (2012–2016) (median of four methods). Median aquifer storage recovery was 34% and 19% of the overdraft during the 2010–2011 and 2017–2019 post‐drought years, respectively. Numerical experiments show that recovery times are sensitive to climate forcing, with longer recovery times for a future climate scenario that replicate historical climatology relative to historical forcing with no droughts. Overdraft recovery times decrease by ∼2× with implementation of pumping restrictions (30th to 50th percentiles of historical groundwater depletion) to constrain groundwater depletion relative to no restrictions with a no‐drought future climatology. This study highlights the importance of considering water management implications for future drought recoveries within the context of climate change scenarios. Plain Language Summary: California's Central Valley has experienced chronic groundwater depletion over the past few decades, the rate of which was amplified by droughts in 2007–2009 and 2012–2016. There is limited knowledge as to how much of the drought‐caused groundwater depletion has recovered during post‐drought years and how climate and water management affect overdraft recovery times. We address these issues by estimating groundwater storage changes using four methods and conducting numerical experiments with varying climatic conditions and water management options. We find that less than one‐third of the groundwater overdraft from the most recent droughts was recovered during post‐drought years. Projected overdraft recovery times vary greatly depending on the climate scenarios and water management strategies, and future droughts are likely to cause overdrafts from which recovery is unlikely given the current level of groundwater extractions. However, management measures such as capping groundwater pumping could reduce recovery times by a factor of two or more depending on the groundwater extraction cap and post‐drought climate. Key Points: Groundwater storage recovery during post‐drought periods ranged from 34% (2007–2009 drought) to 19% (2012–2016 drought)Projected drought recovery times decrease by a factor of 3.6–7.8 with post‐drought periods containing no drought years or wet years onlyOverdraft recovery time decreased by a factor of 2 with implementation of modest pumping restrictions under no‐drought post‐drought climate [ABSTRACT FROM AUTHOR]

Climate variability and changing cropping patterns are two main factors directly influencing catchment hydrological processes and agricultural productivity. Assessing the response of hydrological processes and agricultural production to the combined impacts is of great importance for enhancing water resources management, water productivity and agriculture sustainability. SWAT (Soil and Water Assessment Tools) models embedded with 2007 and 2018 land use were built for the San Joaquin watershed (SJWS) in California's Central Valley. Global sensitivity analysis were conducted to select parameters that have the largest influence on evapotranspiration (ET) processes. The model was calibrated and validated produced good agreement for monthly ET from remote sensing and yield of 8 major crops using county level reported yields during the periods of 2001–2009 and 2010–2018. Based on the outputs of the calibrated SJWS SWAT model, regional ET showed a significant increase, which was caused by rises in temperature and changing cropping patterns associated with increase in area under nut crop production. Seven major crop yields increased excluding alfalfa, implying that the impacts of increasing temperature and small decreases in precipitation were not dominant factors in explaining observed changes in yield. From periods 2001–2009–2010–2018, total water productivity (WP) increased slightly from 2.11 to 2.15 kg/m3, associated with more water-intensive permanent crop production systems. Total economic water productivity (EWP) increased significantly by 111% from 0.55 to 1.16 US$/m3, which also indicated the substantial economic benefit brought to the SJWS by expanding the land area under high-EWP crops such as nut crops and vegetables. Nutritional water productivity (NWP) for energy, protein and fat were reduced from 1211 kcal/m3, 183 g/m3 and 105 g/m3 to 1141 kcal/m3, 111 g/m3 and 88 g/m3 during the period 2010–2018 mostly due to high water use. Total NWP for calcium was increased from 114 to 145 mg/m3, respectively. This study provides initial insights into the response of WP, EWP and NWP to the changing cropping patterns and climate variability for major crops in the SJWS, which could be used by a wide range of stakeholders including farmers, commodity boards, irrigation districts, groundwater sustainability basins, environmental justice groups and policy makers to optimize water resources planning and management. We recommend creating a comprehensive index that incorporates WP, EWP and NWP for making sustainable water resources planning and management decisions. • Climate variability and cropping patterns change were analyzed from 1999 to 2018. • Regional evapotranspiration significantly increased over the past twenty years. • Total WP only increased slightly for the low WP of nut trees and its extended area. • Total EWP increased significantly by 111% from 0.55 to 1.16 US$/m3. • The paper also explores changes in NWP for various crops grown in the watershed. [ABSTRACT FROM AUTHOR]

High-temperature events can influence insect population dynamics and could be especially important for predicting the potential spread and establishment of invasive insects. The interaction between temperature and environmental humidity on insect populations is not well understood but can be a key factor that determines habitat range and population size. The brown marmorated stink bug, Halyomorpha halys (Stål), is an invasive agricultural pest in the United States and Europe, which causes serious economic damage to a wide range of crops. This insect's range continues to expand. It has recently invaded the Central Valley of California, which has a hotter and drier climate compared with the Eastern United States where this insect is established. We investigated how high-temperature events and relative humidity would impact the survival and reproduction of H. halys. Using incubators and humidity chambers, we evaluated the impact of humidity and short-term (2 d) high-temperature exposure on the survival and development of H. halys eggs, nymphs, and adults. We found that high temperatures significantly reduced H. halys survival. The impact of humidity on H. halys survival was dependent on temperature and life stage. Low humidity decreased first-instar survival but not third- to fourth-instar survival. High humidity increased first instar survival but decreased third- to fourth-instar survival. Humidity did not influence adult or egg survival. We also found that high temperatures decreased H. halys reproduction. Our findings have important implications for understanding the invasive ecology of H. halys and may be used to improve models predicting H. halys range expansion. [ABSTRACT FROM AUTHOR]

In California's Central Valley, tule fog frequency increased 85% from 1930 to 1970, then declined 76% in the last 36 winters. Throughout these changes, fog frequency exhibited a consistent north‐south trend, with maxima in southern latitudes. We analyzed seven decades of meteorological data and five decades of air pollution data to determine the most likely drivers changing fog, including temperature, dew point depression, precipitation, wind speed, and NOx (oxides of nitrogen) concentration. Climate variables, most critically dew point depression, strongly influence the short‐term (annual) variability in fog frequency; however, the frequency of optimal conditions for fog formation show no observable trend from 1980 to 2016. NOx concentration, which has a decreasing north‐south concentration gradient, declined continuously over this period, consistent with the long‐term temporal and spatial trends in fog. As development in the Central Valley increased direct particle and other pollutant emissions from 1930 to 1970, fog frequency increased. Following the Clean Air Act, particle emissions quickly declined, and NOx emissions declined steadily, reducing the cloud condensation nuclei (CCN) available for fog formation. As a precursor of ammonium nitrate aerosols, which are efficient CCN, we used NOx measurements and emission trends as a proxy for the CCN trend. We conclude that while the short‐term fog variability is dominantly driven by climate fluctuations, the longer‐term temporal and spatial changes in fog have been driven by changes in air pollution. For conditions close to the dew point, a decrease in fog of 5 days/year per 10 parts per billion NOx decrease occurred across the Central Valley. Plain Language Summary: California's Central Valley is known for dense wintertime ground fog, called tule fog, which dramatically reduces visibility, causing weather‐related accidents, while also helping provide the "winter chill" required to improve productivity of fruit and nut trees. Fog frequency changed dramatically over the past century, increasing 85% from 1930 to 1970 then decreasing by ~75% since 1980. We found that climate variables, most importantly dew point depression (a measure of how low the temperature must drop for water droplets to form) is the main controller of short‐term (year‐to‐year) changes in fog frequency. However, changing air pollution is the main driver of the long‐term trends in fog frequency because it provides water‐attracting particles on which fog droplets form. Air pollution increased in the Central Valley of California prior to 1970 due to development with lack of emissions regulation, then decreased since 1980 due to effective air pollution control, matching the observed long‐term trend in fog frequency. Key Points: Central Valley fog frequency increased 85% from 1930 to 1970, then declined 76% in the last 36 winters, with large short‐term variabilityShort‐term fog variability is dominantly driven by climate fluctuationsLong‐term temporal and spatial trends in fog are dominantly driven by changes in air pollution [ABSTRACT FROM AUTHOR]

Ongoing (2014-16) drought in the state of California has played a major role in the depletion of groundwater. Within California's Central Valley, home to one of the world's most productive agricultural regions, drought and increased groundwater depletion occurs almost hand in hand, but this relationship appears to have changed over the last decade. Data derived from 497 wells have revealed a continued depletion of groundwater lasting a full year after drought, a phenomenon that was not observed in earlier records before the twenty-first century. Possible causes include 1) lengthening of drought associated with amplification in the 4-6-yr drought and El Niño frequency since the late 1990s and 2) intensification of drought and increased pumping that enhances depletion. Altogether, the implication is that current groundwater storage in the Central Valley will likely continue to diminish even further in 2016, regardless of the drought status. [ABSTRACT FROM AUTHOR]

California Central Valley (CCV) heat waves are grouped into two types based on the temporal and spatial evolution of the large-scale meteorological patterns (LSMPs) prior to onset. The k-means clustering of key features in the anomalous temperature and zonal wind identifies the two groups. Composite analyses show different evolution prior to developing a similar ridge-trough-ridge pattern spanning the North Pacific at the onset of CCV hot spells. Backward trajectories show adiabatic heating of air enhanced by anomalous sinking plus horizontal advection as the main mechanisms to create hot lower-tropospheric air just off the Northern California coast, although the paths differ between clusters. The first cluster develops the ridge at the west coast on the day before onset, consistent with wave activity flux traveling across the North Pacific. Air parcels that arrive at the maximum temperature anomaly (just off the Northern California coast) tend to travel a long distance across the Pacific from the west. The second cluster has the ridge in place for several days prior to extreme CCV heat, but this ridge is located farther north, with heat anomaly over the northwestern United States. This ridge expands south as air parcels at midtropospheric levels descend from the northwest while lower-level parcels over land tend to bring hot air from directions ranging from the hot area to the northeast to the desert areas to the southeast. These two types reveal unexpected dynamical complexity, hint at different remote associations, and expand the assessment needed of climate models' simulations of these heat waves. [ABSTRACT FROM AUTHOR]

In this study, the Weather Research and Forecasting (WRF) model was applied to dynamically downscale the Parallel Climate Model (PCM) projection for the climate change impact on regional meteorological conditions in California. Comparisons were made for meteorological fields that strongly influence regional air quality between the current (2000--06) and future (2047--53) downscaling results to infer potential air pollution changes in California. Changes in both the meteorological fields and the implied future air quality vary by region and season. Analyses showed that the normalized number of stagnation days (NNSD) integrating all stagnation events, during which most of the air pollution episodes occur, in California's San Joaquin Valley (SJV) will increase and the intensity of stagnation will be stronger in the future for the two main air pollution seasons (i.e., summer and winter). Increases in surface wind and planetary boundary layer height (PBLH) were observed for the coastal part of Los Angeles County (LAC) during summer, suggesting stronger ventilation in this region. Contrary situations were seen in other parts of the South Coast Air Basin (SoCAB) and SJV. Although a surface wind change was not evident in SJV during winter, there was a significant PBLH decrease. Climatechangeinduced variations in surface wind and PBLH were only statistically significant in coastal SoCAB and the southern portion of SJV relative to the corresponding interannual variability; changes in temperature are significant throughout the regions studied. The sea breeze along the coast of California plays an important role in the state's climate and air quality, especially during summertime owing to the stronger intensity compared to wintertime. Analysis of the land--sea temperature contrast and the southwesterly wind along the California coastline indicated that the summertime sea breeze will be stronger in the Central Valley (CV) but weaker for the SoCAB region in the future. [ABSTRACT FROM AUTHOR]

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The study explores the potential changes in water year types and hydrological droughts as well as runoff, based on which the former two metrics are calculated in the Central Valley of California, United States, in the 21st century. The latest operative projections from four representative climate models under two greenhouse-gas emission scenarios are employed for this purpose. The study shows that the temporal distribution of annual runoff is expected to change in terms of shifting more volume to the wet season (October–March) from the snowmelt season (April–July). Increases in wet season runoff volume are more noticeable under the higher (versus lower) emission scenario, while decreases in snowmelt season runoff are generally more significant under the lower (versus higher) emission scenario. In comparison, changes in the water year types are more influenced by climate models rather than emission scenarios. When comparing two regions in the Central Valley, the rain-dominated Sacramento River region is projected to experience more wet years and less critical years than the snow-dominated San Joaquin River region due to their hydroclimatic and geographic differences. Hydrological droughts in the snowmelt season and wet season mostly exhibit upward and downward trends, respectively. However, the uncertainty in the direction of the trend on annual and multi-year scales tends to be climate-model dependent. Overall, this study highlights non-stationarity and long-term uncertainty in these study metrics. They need to be considered when developing adaptive water resources management strategies, some of which are discussed in the study. [ABSTRACT FROM AUTHOR]