An official website of the United States government
Abstract Understanding the dominant drivers of hydrological change is essential for water resources management. Watersheds in the United States are experiencing different types of changes (e.g., wet gets wetter and dry gets drier); however, few studies have analyzed what drivers are responsible for these changes, and how the dominant drivers vary over time and as a function of the climate/water regime and land cover. This study uses a time‐varying Budyko framework to quantify the relative importance of precipitation, potential evapotranspiration, and other factors (e.g., climate seasonality, agricultural drainage, and urbanization) in 889 watersheds in the contiguous United States from 1950 to 2009. Results show that watersheds that are getting wetter are primarily due to increases in precipitation. However, watersheds in dry climates that are getting drier are primarily due to other factors, while watersheds in wet climates that are getting drier are primarily due to precipitation. The drivers causing statistically significant streamflow trends vary depending on dominant land‐use types. Temporally, the increasing effects of other factors are more pronounced after the 1980s in the Midwest. The dominant drivers of streamflow in the United States are time‐varying instead of constant. This is consistent with non‐stationary patterns of streamflow. The time‐varying drivers provide information on the processes that are increasingly important and require the most attention in water resources management.
more »
« less
Projection of Streamflow Change Using a Time‐Varying Budyko Framework in the Contiguous United States
Abstract Predicting future streamflow change is essential for water resources management and understanding the impacts of projected climate and land use changes on water availability. The Budyko framework is a useful and computationally efficient tool to model streamflow at larger spatial scales. This study predicts future streamflow changes in 889 watersheds in the contiguous United States based on projected climate and land use changes from 2040 to 2069. The temporal variability of surface water balance controls, represented by the Budykoωparameter, was modeled using multiple linear regression, random forest (RF), and gradient boosting. Results show that RF is the optimal model and can explain >85% of the variance in most watersheds. Relative cumulative moisture surplus, forest coverage, crop land and urban land are the most important variables of the time‐varyingωin most watersheds. There are statistically significant increases in mean annual precipitation, potential evapotranspiration, andωin 2040–2069, as compared to 1950–2005. This leads to a statistically significant decrease in the runoff ratio (Q/P). Streamflow is projected to decrease in the central, southwestern, and southeastern United States and increase in the northeast. These projections of water availability which are based on future climate and land use change scenarios can inform water resources management and adaptation strategies.
more »
« less
- Award ID(s):
- 2003248
- PAR ID:
- 10377150
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Water Resources Research
- Volume:
- 58
- Issue:
- 10
- ISSN:
- 0043-1397
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Understanding the process of precipitation partitioning into evapotranspiration and streamflow is fundamental for water resource planning. The Budyko framework has been widely used to evaluate the factors influencing this process. Still, its application has primarily focused on studying watersheds with minimal human influence and on a relatively small number of factors. Furthermore, there are discrepancies in the literature regarding the effects of climatic factors and land use changes on this process. To address these gaps, this study aims to quantify the influence of climate and anthropogenic activities on streamflow generation in the contiguous United States. To accomplish this, we calibrated an analytical form of the Budyko curve from 1990 to 2020 for 383 watersheds. We developed regional models of , a free parameter introduced to account for controls of precipitation partitioning not captured in the original Budyko equation, within different climate zones. We computed 49 climatic and landscape factors that were related to using correlation analysis and stepwise multiple linear regression. The findings of this study show that human activities explained a low variance of the spatial heterogeneity of compared with the watershed slope and the synchronization between precipitation and potential evapotranspiration, nevertheless, urban development emerged as a factor in temperate climates, whereas irrigated agriculture emerged in cold climates. In arid climates, mean annual precipitation explains less than 20% of the spatial variability in mean annual streamflow; furthermore, this climate is the most responsive to changes in . These results provide valuable insights into how land use and climate interact to impact streamflow generation differently in the contiguous United States contingent on the regional climate, explaining discrepancies in the literature.more » « less
-
The increase of tree canopy cover due to woody plant encroachment and tree plantations modifies both carbon and water dynamics. The tradeoffs between ecosystem net primary productivity (NPP) and water use with increasing tree cover in different climate conditions, particularly under future climate scenarios, are not well understood. Within the climate transition zone of the southern Great Plains, USA, we used the Soil and Water Assessment Tool+ (SWAT+) to investigate the combined impacts of increasing tree cover and climate change on carbon and water dynamics in three watersheds representing semiarid, subhumid, and humid climates. Model simulations incorporated two land use modifications (Baseline: existing tree cover; Forest +: increasing evergreen tree cover), in conjunction with two climate change projections (the RCP45 and the RCP85), spanning two time periods (historic: 1991-2020; future: 2070-2099). With climate change, the subhumid and humid watersheds exhibited a greater increase in evapotranspiration (ET) and a corresponding reduction in runoff compared to the semi-arid watershed, while the semi-arid and subhumid watersheds encountered pronounced losses in water availability for streams (>200 mm/year) due to increasing tree cover and climate change. With every 1 % increase in tree cover, both NPP and water use efficiency were projected to increase in all three watersheds under both climate change scenarios, with the subhumid watershed demonstrating the largest increases (>0.16 Mg/ha/year and 170 %, respectively). Increasing tree cover within grasslands, either through woody plant expansion or afforestation, boosts ecosystem NPP, particularly in subhumid regions. Nevertheless, this comes with a notable decrease in water resources, a concern made worse by future climate change. While afforestation offers the potential for greater NPP, it also brings heightened water scarcity concerns, highlighting the importance of tailoring carbon sequestration strategies within specific regions to mitigate unintended repercussions on water availability.more » « less
-
Increases in evapotranspiration (ET) from global warming are decreasing streamflow in headwater basins worldwide. However, these streamflow losses do not occur uniformly due to complex topography. To better understand the heterogeneity of streamflow loss, we use the Budyko shape parameter (ω) as a diagnostic tool. We fit ω to 37-year of hydrologic simulation output in the Upper Colorado River Basin (UCRB), an important headwater basin in the US. We split the UCRB into two categories: peak watersheds with high elevation and steep slopes, and valley watersheds with lower elevation and gradual slopes. Our results demonstrate a relationship between streamflow loss and ω. The valley watersheds with greater streamflow loss have ω higher than 3.1, while the peak watersheds with less streamflow loss have an average ω of 1.3. This work highlights the use of ω as an indicator of streamflow loss and could be generalized to other headwater basin systems.more » « less
-
Abstract. Climate warming will cause mountain snowpacks to melt earlier, reducing summer streamflow and threatening water supplies and ecosystems. Quantifying how sensitive streamflow timing is to climate change and where it is most sensitive remain key questions. Physically based hydrological models are often used for this purpose; however, they have embedded assumptions that translate into uncertain hydrological projections that need to be quantified and constrained to provide reliable inferences. The purpose of this study is to evaluate differences in projected end-of-century changes to streamflow timing between a new empirical model based on diel (daily) streamflow cycles and regional land surface simulations across the mountainous western USA. We develop an observational technique for detecting streamflow responses to snowmelt using diel cycles of incoming solar radiation and streamflow to detect when snowmelt occurs. We measure the date of the 20th percentile of snowmelt days (DOS20) across 31 western USA watersheds affected by snow, as a proxy for the beginning of snowmelt-initiated streamflow. Historic DOS20 varies from mid-January to late May among our sites, with warmer basins having earlier snowmelt-mediated streamflow. Mean annual DOS20 strongly correlates with the dates of 25 % and 50 % annual streamflow volume (DOQ25 and DOQ50, both R2=0.85), suggesting that a 1 d earlier DOS20 corresponds with a 1 d earlier DOQ25 and 0.7 d earlier DOQ50. Empirical projections of future DOS20 based on a stepwise multiple linear regression across sites and years under the RCP8.5 scenario for the late 21st century show that DOS20 will occur on average 11±4 d earlier per 1 ∘C of warming. However, DOS20 in colder watersheds (mean November–February air temperature, TNDJF<-8 ∘C) is on average 70 % more sensitive to climate change than in warmer watersheds (TNDJF>0 ∘C). Moreover, empirical projections of DOQ25 and DOQ50 based on DOS20 are about four and two times more sensitive to climate change, respectively, than those simulated by a state-of-the-art land surface model (NoahMP-WRF) under the same scenario. Given the importance of changes in streamflow timing for water resources, and the significant discrepancies found in projected streamflow sensitivity, snowmelt detection methods such as DOS20 based on diel streamflow cycles may help to constrain model parameters, improve hydrological predictions, and inform process understanding.more » « less
