The recent mortality of up to 20% of forests and woodlands in the southwestern United States, along with declining stream flows and projected future water shortages, heightens the need to understand how management practices can enhance forest resilience and functioning under unprecedented scales of drought and wildfire. To address this challenge, a combination of mechanical thinning and fire treatments are planned for 238,000 hectares (588,000 acres) of ponderosa pine (Pinus ponderosa) forests across central Arizona, USA. Mechanical thinning can increase runoff at fine scales, as well as reduce fire risk and tree water stress during drought, but the effects of this practice have not been studied at scales commensurate with recent forest disturbances or under a highly variable climate. Modifying a historical runoff model, we constructed scenarios to estimate increases in runoff from thinning ponderosa pine at the landscape and watershed scales based on driving variables: pace, extent and intensity of forest treatments and variability in winter precipitation. We found that runoff on thinned forests was about 20% greater than unthinned forests, regardless of whether treatments occurred in a drought or pluvial period. The magnitude of this increase is similar to observed declines in snowpack for the region, suggesting that accelerated thinning may lessen runoff losses due to warming effects. Gains in runoff were temporary (six years after treatment) and modest when compared to mean annual runoff from the study watersheds (0–3%). Nonetheless gains observed during drought periods could play a role in augmenting river flows on a seasonal basis, improving conditions for water-dependent natural resources, as well as benefit water supplies for downstream communities. Results of this study and others suggest that accelerated forest thinning at large scales could improve the water balance and resilience of forests and sustain the ecosystem services they provide.

Open science practices such as publishing data and code are transforming water science by enabling synthesis and enhancing reproducibility. However, as research increasingly bridges the physical and social science domains (e.g., socio‐hydrology), there is the potential for well‐meaning researchers to unintentionally violate the privacy and security of individuals or communities by sharing sensitive information. Here we identify the contexts in which privacy violations are most likely to occur, such as working with high‐resolution spatial data (e.g., from remote sensing), consumer data (e.g., from smart meters), and/or digital trace data (e.g., from social media). We also suggest practices for identifying and addressing privacy concerns at the individual, institutional, and disciplinary levels. We strongly advocate that the water science community continue moving toward open science and socio‐environmental research and that progress toward these goals be rooted in open and ethical data management.

Evapotranspiration (ET) comprises a major portion of the water budget in forests, yet few studies have measured or estimated ET in semi‐arid, high‐elevation ponderosa pine forests of the south‐western USA or have investigated the capacity of models to predict ET in disturbed forests. We measured actual ET with the eddy covariance (eddy) method over 4 years in three ponderosa pine forests near Flagstaff, Arizona, that differ in disturbance history (undisturbed control, wildfire burned, and restoration thinning) and compared these measurements (415–510 mm year−1 on average) with actual ET estimated from five meteorological models [Penman–Monteith (P‐M), P‐M with dynamic control of stomatal resistance (P‐M‐d), Priestley–Taylor (P‐T), McNaughton–Black (M‐B), and Shuttleworth–Wallace (S‐W)] and from the Moderate Resolution Imaging Spectroradiometer (MODIS) ET product. The meteorological models with constant stomatal resistance (P‐M, M‐B, and S‐W) provided the most accurate estimates of annual eddy ET (average percent differences ranged between 11 and −14%), but their accuracy varied across sites. The P‐M‐d consistently underpredicted ET at all sites. The more simplistic P‐T model performed well at the control site (18% overprediction) but strongly overpredicted annual eddy ET at the restoration sites (92%) and underpredicted at the fire site (−26%). The MODIS ET underpredicted annual eddy ET at all sites by at least 51% primarily because of underestimation of leaf area index. Overall, we conclude that with accurate parameterization, micrometeorological models can predict ET within 30% in forests of the south‐western USA and that remote sensing‐based ET estimates need to be improved through use of higher resolution products. Copyright © 2014 John Wiley & Sons, Ltd.

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Climate change and wildfire are interacting to drive vegetation change and potentially reduce water quantity and quality in the southwestern United States, Forest restoration is a management approach that could mitigate some of these negative outcomes. However, little information exists on how restoration combined with climate change might influence hydrology across large forest landscapes that incorporate multiple vegetation types and complex fire regimes. We combined spatially explicit vegetation and fire modeling with statistical water and sediment yield models for a large forested landscape (335,000 ha) on the Kaibab Plateau in northern Arizona, USA. Our objective was to assess the impacts of climate change and forest restoration on the future fire regime, forest vegetation, and watershed outputs. Our model results predict that the combination of climate change and high-severity fire will drive forest turnover, biomass declines, and compositional change in future forests. Restoration treatments may reduce the area burned in high-severity fires and reduce conversions from forested to non-forested conditions. Even though mid-elevation forests are the targets of restoration, the treatments are expected to delay the decline of high-elevation spruce-fir, aspen, and mixed conifer forests by reducing the occurrence of high-severity fires that may spread across ecoregions. We estimate that climate-induced vegetation changes will result in annual runoff declines of up to 10%, while restoration reduced or reversed this decline. The hydrologic model suggests that mid-elevation forests, which are the targets of restoration treatments, provide around 80% of runoff in this system and the conservation of mid- to high-elevation forests types provides the greatest benefit in terms of water conservation. We also predict that restoration treatments will conserve water quality by reducing patches of high-severity fire that are associated with high sediment yield. Restoration treatments are a management strategy that may reduce undesirable outcomes for multiple ecosystem services.