Abstract In field observations from a sinuous estuary, the drag coefficientbased on the momentum balance was in the range of, much greater than expected from bottom friction alone.also varied at tidal and seasonal timescales.was greater during flood tides than ebbs, most notably during spring tides. The ebb tidewas negatively correlated with river discharge, while the flood tideshowed no dependence on discharge. The large values ofare explained by form drag from flow separation at sharp channel bends. Greater water depths during flood tides corresponded with increased values of, consistent with the expected depth dependence for flow separation, as flow separation becomes stronger in deeper water. Additionally, the strength of the adverse pressure gradient downstream of the bend apex, which is indicative of flow separation, correlated withduring flood tides. Whilegenerally increased with water depth,decreased for the highest water levels that corresponded with overbank flow. The decrease inmay be due to the inhibition of flow separation with flow over the vegetated marsh. The dependence ofduring ebbs on discharge corresponds with the inhibition of flow separation by a favoring baroclinic pressure gradient that is locally generated at the bend apex due to curvature‐induced secondary circulation. This effect increases with stratification, which increases with discharge. Additional factors may contribute to the high drag, including secondary circulation, multiple scales of bedforms, and shallow shoals, but the observations suggest that flow separation is the primary source.
more »
« less
Multi‐Proxy, Multi‐Season Streamflow Reconstruction With Mass Balance Adjustment
Abstract Despite having offered important hydroclimatic insights, streamflow reconstructions still see limited use in water resources operations, because annual reconstructions are not suitable for decisions at finer time scales. The few attempts toward sub‐annual reconstructions have relied on statistical disaggregation, which uses none or little proxy information. Here, we develop a novel framework that optimizes proxy combinations to simultaneously produce seasonal and annual reconstructions. Importantly, the framework ensures that total seasonal flow matches annual flow closely. This mass balance criterion is necessary to avoid misguiding water management decisions, such as the allocation of water rights or dam release decisions. Using the framework, and leveraging a multi‐species network of ring width and celluloseO in Southeast Asia, we reconstruct seasonal and annual inflow to Thailand's largest reservoir. The reconstructions are statistically skillful. Furthermore, they preserve the mass balance well: the differences are mostly within 10% of the mean annual flow. As a result, the reconstructions provide more reliable estimates of the seasonal and annual surface water availability. This work is one step closer toward operational usability of streamflow reconstruction in water resources management.
more »
« less
- Award ID(s):
- 2001949
- PAR ID:
- 10367927
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Water Resources Research
- Volume:
- 57
- Issue:
- 8
- ISSN:
- 0043-1397
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Predicting the proportion of the water year a given stream will remain at or above various flow thresholds is critically important for making sound water management decisions. Flow duration curves (FDCs) succinctly capture this information using all data available over some historical period, while annual flow duration curves (AFDCs) instead use data from each individual water year. Analyzing the population of AFDCs, and in particular the tails of this distribution, can allow water managers to better prepare for years with extreme streamflow conditions. However, long time series of observations are necessary to capture interannual streamflow variations and are problematic to obtain in rapidly changing and poorly gauged catchments. By incorporating a process‐based model to construct AFDCs based on daily rainfall statistics and flow recession characteristics, the proposed approach is a first step toward addressing this challenge. Results indicate that prediction performance varies substantially across flow quantiles and that the current model fails to properly capture the interannual variability of low flows. Numerical analyses attributed these errors to nonlinearity in storage‐discharge relation, rather than cross‐scale streamflow correlations and non‐Poissonian rainfall, explaining the origin of commonly observed heavy‐tailed behavior in low flow quantiles. We present a case study on hydroelectric power generation, showing that faithfully capturing both interannual streamflow variability and recession nonlinearity has important implications for installation profitability.more » « less
-
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
-
Abstract The temporal variability of precipitation and potential evapotranspiration affects streamflow from daily to long‐term scales, but the relative roles of different climate variabilities on streamflow at daily, monthly, annual, and mean annual scales have not been systematically investigated in the literature. This paper developed a new daily water balance model, which provides a unified framework for water balance across timescales. The daily water balance model is driven by four climate forcing scenarios (observed daily climate and observed daily climate with its intra‐monthly, intra‐annual, and inter‐annual variability removed) and applied to 78 catchments. Daily streamflow from the water balance model is aggregated to coarser timescales. The relative roles of intra‐monthly, intra‐annual, and inter‐annual climate variability are evaluated by comparing the modeled streamflow forced with the climate forcings at two consecutive timescales. It is found that daily, monthly, and annual streamflow is primarily controlled by the climate variability at the same timescale. Intra‐monthly climate variability plays a small role in monthly and annual streamflow variability. Intra‐annual climate variability has significant effects on streamflow at all the timescales, and the relative roles of inter‐annual climate variability are also significant to the monthly and mean annual streamflow, which is often disregarded. The quantitative evaluation of the roles of climate variability reveals how climate controls streamflow across timescales.more » « less
-
null (Ed.)Seasonal reconstructions of streamflow are valuable because they provide water planners, policy makers, and stakeholders with information on the range and variability of water resources before the observational period. In this study, we used streamflow data from five gages near the Alabama-Florida border and centuries-long tree-ring chronologies to create and analyze seasonal flow reconstructions. Prescreening methods included correlation and temporal stability analysis of predictors to ensure practical and reliable reconstructions. Seasonal correlation analysis revealed that several regional tree-ring chronologies were significantly correlated (p ≤ 0.05) with March–October streamflow, and stepwise linear regression was used to create the reconstructions. Reconstructions spanned 1203–1985, 1652–1983, 1725–1993, 1867–2011, and 1238–1985 for the Choctawhatchee, Conecuh, Escambia, Perdido, and Pascagoula Rivers, respectively, all of which were statistically skillful (R2 ≥ 0.50). The reconstructions were statistically validated using the following parameters: R2 predicted validation, the sign test, the variance inflation factor (VIF), and the Durbin–Watson (D–W) statistic. The long-term streamflow variability was analyzed for the Choctawhatchee, Conecuh, Escambia, and Perdido Rivers, and the recent (2000s) drought was identified as being the most severe in the instrumental record. The 2000s drought was also identified as being one of the most severe droughts throughout the entire reconstructed paleo-record developed for all five rivers. This information is vital for the consideration of present and future conditions within the system.more » « less
An official website of the United States government
