Climate change impacts on water demand and salinity in California\u27s irrigated agriculture

This paper examines potential regional-scale impacts of climate change on sustainability of irrigated agriculture, focusing on the western San Joaquin Valley in California. We consider potential changes in irrigation water demand and supply, and quantify impacts on the hydrologic system, soil and groundwater salinity with associated crop yield reductions. Our analysis is based on archived output from General Circulation Model (GCM) climate projections through 2100, which were downscaled to the 1,400 km2 study area. We account for uncertainty in GCM climate projections by considering two different GCM\u27s, each using three greenhouse gas emission scenarios. Significant uncertainty in projected precipitation creates large uncertainty in surface water supply, ranging from a decrease of 26% to an increase of 14% in 2080-2099. Changes in projected irrigation water demand ranged from a decrease of 13% to an increase of 3% at the end of the 21st century. Greatest demand reductions were computed for the dry and warm scenarios, because of increased land fallowing with corresponding decreased total crop water requirements. A decrease in seasonal crop ET by climate warming, despite an increase in evaporative demand, was attributed to faster crop development with increasing temperatures. Simulations of hydrologic response to climate-induced changes suggest that the salt-affected area will be slightly expanded. However, irrespective of climate change, salinity is expected to increase in downslope areas, thereby limiting crop production to mostly upslope areas of the simulation domain. Results show that increasing irrigation efficiency may be effective in controlling salinization, by reducing groundwater recharge and improving soil drainage, and in mitigating climate warming effects, by reducing the need for groundwater pumping to satisfy crop water requirements

Stable water isotopes and tritium tracers tell the same tale: no evidence for underestimation of catchment transit times inferred by stable isotopes in StorAge Selection (SAS)-function models

Stable isotopes (δ18O) and tritium (3H) are frequently used as tracers in environmental sciences to estimate age distributions of water. However, it has previously been argued that seasonally variable tracers, such as δ18O, generally and systematically fail to detect the tails of water age distributions and therefore substantially underestimate water ages as compared to radioactive tracers such as 3H. In this study for the Neckar River basin in central Europe and based on a &gt;20-year record of hydrological, δ18O and 3H data, we systematically scrutinized the above postulate together with the potential role of spatial aggregation effects in exacerbating the underestimation of water ages. This was done by comparing water age distributions inferred from δ18O and 3H with a total of 21 different model implementations, including time-invariant, lumped-parameter sine-wave (SW) and convolution integral (CO) models as well as StorAge Selection (SAS)-function models (P-SAS) and integrated hydrological models in combination with SAS functions (IM-SAS). We found that, indeed, water ages inferred from δ18O with commonly used SW and CO models are with mean transit times (MTTs) of ∼ 1–2 years substantially lower than those obtained from 3H with the same models, reaching MTTs of ∼10 years. In contrast, several implementations of P-SAS and IM-SAS models not only allowed simultaneous representations of storage variations and streamflow as well as δ18O and 3H stream signals, but water ages inferred from δ18O with these models were, with MTTs of ∼ 11–17 years, also much higher and similar to those inferred from 3H, which suggested MTTs of ∼ 11–13 years. Characterized by similar parameter posterior distributions, in particular for parameters that control water age, P-SAS and IM-SAS model implementations individually constrained with δ18O or 3H observations exhibited only limited differences in the magnitudes of water ages in different parts of the models and in the temporal variability of transit time distributions (TTDs) in response to changing wetness conditions. This suggests that both tracers lead to comparable descriptions of how water is routed through the system. These findings provide evidence that allowed us to reject the hypothesis that δ18O as a tracer generally and systematically “cannot see water older than about 4 years” and that it truncates the corresponding tails in water age distributions, leading to underestimations of water ages. Instead, our results provide evidence for a broad equivalence of δ18O and 3H as age tracers for systems characterized by MTTs of at least 15–20 years. The question to which degree aggregation of spatial heterogeneity can further adversely affect estimates of water ages remains unresolved as the lumped and distributed implementations of the IM-SAS model provided inconclusive results. Overall, this study demonstrates that previously reported underestimations of water ages are most likely not a result of the use of δ18O or other seasonally variable tracers per se. Rather, these underestimations can largely be attributed to choices of model approaches and complexity not considering transient hydrological conditions next to tracer aspects. Given the additional vulnerability of time-invariant, lumped SW and CO model approaches in combination with δ18O to substantially underestimate water ages due to spatial aggregation and potentially other still unknown effects, we therefore advocate avoiding the use of this model type in combination with seasonally variable tracers if possible and instead adopting SAS-based models or time-variant formulations of CO models.</p

A Multiproxy Database of Western North American Holocene Paleoclimate Records

Holocene climate reconstructions are useful for understanding the diverse features and spatial heterogeneity of past and future climate change. Here we present a database of western North American Holocene paleoclimate records. The database gathers paleoclimate time series from 184 terrestrial and marine sites, including 381 individual proxy records. The records span at least 4000 of the last 12 000 years (median duration of 10 725 years) and have been screened for resolution, chronologic control, and climate sensitivity. Records were included that reflect temperature, hydroclimate, or circulation features. The database is shared in the machine readable Linked Paleo Data (LiPD) format and includes geochronologic data for generating site-level time-uncertain ensembles. This publicly accessible and curated collection of proxy paleoclimate records will have wide research applications, including, for example, investigations of the primary features of ocean-atmospheric circulation along the eastern margin of the North Pacific and the latitudinal response of climate to orbital changes. The database is available for download at https://doi.org/10.6084/m9.figshare.12863843.v1 (Routson and McKay, 2020)

Future changes in annual, seasonal and monthly runoff signatures in contrasting Alpine catchments in Austria

Hydrological regimes of alpine catchments are expected to be strongly affected by climate change, mostly due to their dependence on snow and ice dynamics. While seasonal changes have been studied extensively, studies on changes in the timing and magnitude of annual extremes remain rare. This study investigates the effects of climate change on runoff patterns in six contrasting Alpine catchments in Austria using a process-based, semi-distributed hydrological model and projections from 14 regional and global climate model combinations for two representative concentration pathways, namely RCP4.5 and RCP8.5. The study catchments represent a spectrum of different hydrological regimes, from pluvial–nival to nivo-glacial, as well as distinct topographies and land forms, characterizing different elevation zones across the eastern Alps to provide a comprehensive picture of future runoff changes. The climate projections are used to model river runoff in 2071–2100, which are then compared to the 1981–2010 reference period for all study catchments. Changes in the timing and magnitude of annual maximum and minimum flows, as well as in monthly runoff and snowmelt, are quantified and analyzed. Our results indicate a substantial shift to earlier occurrences in annual maximum flows by 9 to 31 d and an extension of the potential flood season by 1 to 3 months for high-elevation catchments. For low-elevation catchments, changes in the timing of annual maximum flows are less pronounced. Magnitudes of annual maximum flows are likely to increase by 2 %–18 % under RCP4.5, while no clear changes are projected for four catchments under RCP8.5. The latter is caused by a pronounced increase in evaporation and decrease in snowmelt contributions, which offset increases in precipitation. In the future, minimum annual runoff will occur 13–31 d earlier in the winter months for high-elevation catchments, whereas for low-elevation catchments a shift from winter to autumn by about 15–100 d is projected, with generally larger changes for RCP8.5. While all catchments show an increase in mean magnitude of minimum flows by 7–30% under RCP4.5, this is only the case for four catchments under RCP8.5. Our results suggest a relationship between the elevation of catchments and changes in the timing of annual maximum and minimum flows. For the magnitude of the extreme flows, a relationship is found between catchment elevation and annual minimum flows, whereas this relationship is lacking between elevation and annual maximum flow

Supporting data and code for the publication: Organic pollution of rivers: Combined threats of urbanization, livestock farming and global climate change.

Code and data for 'Organic pollution of rivers: Combined threats of urbanization, livestock farming and global climate change

Supporting data for the publication: Global impacts of meat trade on in-stream organic river pollution: importance of spatially distributed hydrological conditions'

Data for paper 'Global impacts of meat trade on in-stream organic river pollution: importance of spatially distributed hydrological conditions