scholarly journals Effects of Climate Variability on Water Storage in the Colorado River Basin

2009 ◽  
Vol 10 (5) ◽  
pp. 1257-1270 ◽  
Author(s):  
Ruud Hurkmans ◽  
Peter A. Troch ◽  
Remko Uijlenhoet ◽  
Paul Torfs ◽  
Matej Durcik

Abstract Understanding the long-term (interannual–decadal) variability of water availability in river basins is paramount for water resources management. Here, the authors analyze time series of simulated terrestrial water storage components, observed precipitation, and discharge spanning 74 yr in the Colorado River basin and relate them to climate indices that describe variability of sea surface temperature and sea level pressure in the tropical and extratropical Pacific. El Niño–Southern Oscillation (ENSO) indices in winter [January–March (JFM)] are related to winter precipitation as well as to soil moisture and discharge in the lower Colorado River basin. The low-frequency mode of the Pacific decadal oscillation (PDO) appears to be strongly correlated with deep soil moisture. During the negative PDO phase, saturated storage anomalies tend to be negative and the “amplitudes” (mean absolute anomalies) of shallow soil moisture, snow, and discharge are slightly lower compared to periods of positive PDO phases. Predicting interannual variability, therefore, strongly depends on the capability of predicting PDO regime shifts. If indeed a shift to a cool PDO phase occurred in the mid-1990s, as data suggest, the current dry conditions in the Colorado River basin may persist.

2013 ◽  
Vol 14 (3) ◽  
pp. 888-905 ◽  
Author(s):  
Rebecca A. Smith ◽  
Christian D. Kummerow

Abstract Using in situ, reanalysis, and satellite-derived datasets, surface and atmospheric water budgets of the Upper Colorado River basin are analyzed. All datasets capture the seasonal cycle for each water budget component. For precipitation, all products capture the interannual variability, though reanalyses tend to overestimate in situ while satellite-derived precipitation underestimates. Most products capture the interannual variability of evapotranspiration (ET), though magnitudes differ among the products. Variability and magnitude among storage volume change products widely vary. With regards to the surface water budget, the strongest connections exist among precipitation, ET, and soil moisture, while snow water equivalent (SWE) is best correlated with runoff. Using in situ precipitation estimates, the Max Planck Institute (MPI) ET estimates, and accumulated runoff, changes in storage are calculated and compare well with estimated changes in storage calculated using SWE, reservoir, and the Climate Prediction Center’s soil moisture. Using in situ precipitation estimates, MPI ET estimates, and atmospheric divergence estimates from the European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim) results in a long-term atmospheric storage change estimate of −73 mm. Long-term surface storage estimates combined with long-term runoff come close to balancing with long-term atmospheric convergence from ERA-Interim. Increasing the MPI ET by 5% leads to a better balance between surface storage changes, runoff, and atmospheric convergence. It also brings long-term atmospheric storage changes to a better balance at +13 mm.


2019 ◽  
Vol 50 (2) ◽  
pp. 761-777 ◽  
Author(s):  
Jun Xia ◽  
Peng Yang ◽  
Chesheng Zhan ◽  
Yunfeng Qiao

Abstract Drought is a widespread natural hazard. In this study, the potential factors affecting spatiotemporal changes of drought in the Tarim River Basin (TRB), China, were investigated using the empirical orthogonal function (EOF) and multiple hydro-meteorological indicators such as the standardized precipitation index (SPI), standardized soil moisture index (SSI), and terrestrial water storage (TWS). The following major conclusions were drawn. (1) Inconsistent variations between SPIs/SSIs and TWS in the TRB indicate a groundwater deficit in 2002–2012. (2) The results of EOF indicate that soil moisture in the TRB was significantly affected by precipitation. However, the variations between the EOFs of SSIs and those of TWS were not identical, which indicates that soil water had less effect on TWS than groundwater. (3) Drought evaluations using SPI and SSI showed that a long drought duration occurred over a long accumulation period, whereas a high frequency of drought was related to a short accumulation period. (4) Hydrological features related to extreme soil moisture conditions in the TRB could also be influenced by the El Niño–Southern Oscillation. The findings of this study are significant for use in drought detection and for making water management decisions.


2017 ◽  
Vol 21 (1) ◽  
pp. 323-343 ◽  
Author(s):  
Oliver López ◽  
Rasmus Houborg ◽  
Matthew Francis McCabe

Abstract. Advances in space-based observations have provided the capacity to develop regional- to global-scale estimates of evaporation, offering insights into this key component of the hydrological cycle. However, the evaluation of large-scale evaporation retrievals is not a straightforward task. While a number of studies have intercompared a range of these evaporation products by examining the variance amongst them, or by comparison of pixel-scale retrievals against ground-based observations, there is a need to explore more appropriate techniques to comprehensively evaluate remote-sensing-based estimates. One possible approach is to establish the level of product agreement between related hydrological components: for instance, how well do evaporation patterns and response match with precipitation or water storage changes? To assess the suitability of this consistency-based approach for evaluating evaporation products, we focused our investigation on four globally distributed basins in arid and semi-arid environments, comprising the Colorado River basin, Niger River basin, Aral Sea basin, and Lake Eyre basin. In an effort to assess retrieval quality, three satellite-based global evaporation products based on different methodologies and input data, including CSIRO-PML, the MODIS Global Evapotranspiration product (MOD16), and Global Land Evaporation: the Amsterdam Methodology (GLEAM), were evaluated against rainfall data from the Global Precipitation Climatology Project (GPCP) along with Gravity Recovery and Climate Experiment (GRACE) water storage anomalies. To ensure a fair comparison, we evaluated consistency using a degree correlation approach after transforming both evaporation and precipitation data into spherical harmonics. Overall we found no persistent hydrological consistency in these dryland environments. Indeed, the degree correlation showed oscillating values between periods of low and high water storage changes, with a phase difference of about 2–3 months. Interestingly, after imposing a simple lag in GRACE data to account for delayed surface runoff or baseflow components, an improved match in terms of degree correlation was observed in the Niger River basin. Significant improvements to the degree correlations (from  ∼  0 to about 0.6) were also found in the Colorado River basin for both the CSIRO-PML and GLEAM products, while MOD16 showed only half of that improvement. In other basins, the variability in the temporal pattern of degree correlations remained considerable and hindered any clear differentiation between the evaporation products. Even so, it was found that a constant lag of 2 months provided a better fit compared to other alternatives, including a zero lag. From a product assessment perspective, no significant or persistent advantage could be discerned across any of the three evaporation products in terms of a sustained hydrological consistency with precipitation and water storage anomaly data. As a result, our analysis has implications in terms of the confidence that can be placed in independent retrievals of the hydrological cycle, raises questions on inter-product quality, and highlights the need for additional techniques to evaluate large-scale products.


2021 ◽  
pp. 1-47
Author(s):  
Siyu Zhao ◽  
Rong Fu ◽  
Yizhou Zhuang ◽  
Gaoyun Wang

AbstractWe have developed two statistical models for extended seasonal predictions of the Upper Colorado River Basin (UCRB) natural streamflow during April–July: a stepwise linear regression (reduced to a simple regression with one predictor) and a neural network model. Monthly, basin-averaged soil moisture, snow water equivalent (SWE), precipitation, and the Pacific sea surface temperature (SST) are selected as potential predictors. Pacific SST Predictors (PSPs) are derived from a dipole pattern over the Pacific (30°S–65°N) that is correlated with the lagging streamflow. For both models, the correlation between the hindcasted and observed streamflow exceeds 0.60 for lead times less than four months using soil moisture, SWE, and precipitation as predictors. This correlation is higher than that of an autoregression model (correlation ~0.50). Since these land-surface and atmospheric variables have no statistically significant correlations with the streamflow, PSPs are then incorporated into the models. The two models have a correlation of ~0.50 using PSPs alone for lead times from six to nine months, and such skills are probably associated with stronger correlation between SST and streamflow in recent decades. The similar prediction skills between the two models suggest a largely linear system between SST and streamflow. Four predictors together can further improve short-lead prediction skills (correlation ~0.80). Therefore, our results confirm the advantage of the Pacific SST information in predicting the UCRB streamflow with a long lead time, and can provide useful climate information for water supply planning and decisions.


2007 ◽  
Vol 333 (2-4) ◽  
pp. 252-264 ◽  
Author(s):  
Julio Cañón ◽  
Javier González ◽  
Juan Valdés

2014 ◽  
Vol 27 (23) ◽  
pp. 8661-8673 ◽  
Author(s):  
Rebecca A. Bolinger ◽  
Christian D. Kummerow ◽  
Nolan J. Doesken

Abstract Previous research has shown that the temperature and precipitation variability in the Upper Colorado River basin (UCRB) is correlated with large-scale climate variability [i.e., El Niño–Southern Oscillation (ENSO) and Pacific decadal oscillation (PDO)]. But this correlation is not very strong, suggesting the need to look beyond the statistics. Looking at monthly contributions across the basin, results show that February is least sensitive to variability, and a wet October could be a good predictor for a wet season. A case study of a wet and a dry year (with similar ENSO/PDO conditions) shows that the occurrence of a few large accumulating events is what drives the seasonal variability, and these large events can happen under a variety of synoptic conditions. Looking at several physical factors that can impact the amount of accumulation in any given event, it is found that large accumulating events (>10 mm in one day) are associated with westerly winds at all levels, higher wind speeds at all levels, and greater amounts of total precipitable water. The most important difference between a large accumulating and small accumulating event is the presence of a strong (>4 m s−1) low-level westerly wind. Because much more emphasis should be given to this more local feature, as opposed to large-scale variability, an accurate seasonal forecast for the basin is not producible at this time.


2012 ◽  
Vol 25 (12) ◽  
pp. 4389-4403 ◽  
Author(s):  
Kenneth Nowak ◽  
Martin Hoerling ◽  
Balaji Rajagopalan ◽  
Edith Zagona

Abstract An analysis of annual hydroclimatic variability in the Upper Colorado River basin (UCRB) for the period of 1906–2006 was performed to understand the dominant modes of multidecadal variability. First, wavelet-based spectral analysis was employed for streamflow at Lees Ferry, Arizona (aggregate location for UCRB flow), which identified two significant modes: a “low frequency” (~64-yr period) mode and a strong “decadal” (~15-yr period) component active only in recent decades. Subsequent investigation of temperature and precipitation data for the UCRB indicated that the low-frequency variability is associated with temperature via modulation of runoff efficiency while the decadal is strongly tied to moisture delivery. Simple hydrology and climate model experiments are also provided to support the aforementioned findings. Correlation of UCRB precipitation with global sea surface temperature (SST) anomalies showed a strong link with the equatorial and northern Pacific during periods of heightened variability of the decadal mode. The correlation of UCRB temperature with global SST anomalies showed strongest values in the Atlantic consistent with the Atlantic multidecadal oscillation mode. Wavelet spectral analysis of paleo-reconstructed streamflow at Lees Ferry shows both the low-frequency and decadal flow variability features. Furthermore, the strength of the decadal mode is modulated at an ~75-yr time scale, and these are consistent with epochal variations of overall streamflow variance.


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