Global ENSO-streamflow teleconnection,streamflow forecasting and interannual variability

Abstract

El Niño Southern Oscillation (ENSO) has been linked to climate anomalies throughout the world. This paper presents an overview of global ENSO-streamflow teleconnection and identifies regions where the relationship may be exploited to forecast streamflow several months ahead. The teleconnection is investigated by fitting a first harmonic to 24-month El Niño streamflow composites from 581 catchments worldwide and the potential for forecasting is investigated by calculating the lag correlation between streamflow and two indicators of ENSO. The analyses indicate clear ENSO-streamflow teleconnections in many catchments, some of which are consistent across large geographical regions. Strong and regionally consistent ENSO-streamflow teleconnections are identified in Australia and New Zealand, South and Central America, and weaker signals are identified in some parts of Africa and North America. The results suggest that the ENSO-streamflow relationship and the serial correlation in streamflow can be used to successfully forecast streamflow. The streamflow forecasts can be used to help manage water resources, particularly in systems with high interannual variability in Australia, southern and drier parts of Africa and some areas of North America.     

Rainfall and streamflow response to El Niño Southern Oscillation: a case study in a semiarid catchment,Australia

Abstract

This paper aims to compare the shift in frequency distribution and skill of seasonal climate forecasting of both streamflow and rainfall in eastern Australia based on the Southern Oscillation Index (SOI) Phase system. Recent advances in seasonal forecasting of climate variables have highlighted opportunities for improving decision making in natural resources management. Forecasting of rainfall probabilities for different regions in Australia is available, but the use of similar forecasts for water resource supply has not been developed. The use of streamflow forecasts may provide better information for decision-making in irrigation supply and flow management for improved ecological outcomes. To examine the relative efficacy of seasonal forecasting of streamflow and rainfall, the shift in probability distributions and the forecast skill were evaluated using the Wilcoxon rank-sum test and the linear error in probability space (LEPS) skill score, respectively, at three river gauging stations in the Border Rivers Catchment of the Murray-Darling Basin in eastern Australia. A comparison of rainfall and streamflow distributions confirms higher statistical significance in the shift of streamflow distribution than that in rainfall distribution. Moreover, streamflow distribution showed greater skill of forecasting with 0–3 month lead time, compared to rainfall distribution.     

Data mining methods for hydroclimatic forecasting

Skillful streamflow forecasts at seasonal lead times may be useful to water managers seeking to provide reliable water supplies and maximize hydrosystem benefits. In this study, a class of data mining techniques, known as tree-structured models, is investigated to address the nonlinear dynamics of climate teleconnections and screen promising probabilistic streamflow forecast models for river–reservoir systems. In a case study of the Lower Colorado River system in central Texas, a number of potential predictors are evaluated for forecasting seasonal streamflow, including large-scale climate indices related to the El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and others. Results show that the tree-structured models can effectively capture the nonlinear features hidden in the data. Skill scores of probabilistic forecasts generated by both classification trees and logistic regression trees indicate that seasonal inflows throughout the system can be predicted with sufficient accuracy to improve water management, especially in the winter and spring seasons in central Texas.     

Using large‐scale climatic patterns for improving long lead time streamflow forecasts for Gunnison and San Juan River Basins

In a water‐stressed region, such as the western United States, it is essential to have long lead times for streamflow forecasts used in reservoir operations and water resources management. Current water supply forecasts provide a 3‐month to 6‐month lead time, depending on the time of year. However, there is a growing demand from stakeholders to have forecasts that run lead times of 1 year or more. In this study, a data‐driven model, the support vector machine (SVM) based on the statistical learning theory, was used to predict annual streamflow volume with a 1‐year lead time. Annual average oceanic–atmospheric indices consisting of the Pacific decadal oscillation, North Atlantic oscillation (NAO), Atlantic multidecadal oscillation, El Niño southern oscillation (ENSO), and a new sea surface temperature (SST) data set for the ‘Hondo’ region for the period of 1906–2006 were used to generate annual streamflow volumes for multiple sites in the Gunnison River Basin and San Juan River Basin, both located in the Upper Colorado River Basin. Based on the performance measures, the model showed very good forecasts, and the forecasts were in good agreement with measured streamflow volumes. Inclusion of SST information from the Hondo region improved the model's forecasting ability; in addition, the combination of NAO and Hondo region SST data resulted in the best streamflow forecasts for a 1‐year lead time. The results of the SVM model were found to be better than the feed‐forward, back propagation artificial neural network and multiple linear regression. The results from this study have the potential of providing useful information for the planning and management of water resources within these basins. Copyright © 2012 John Wiley & Sons, Ltd.     

Problems of water protection against adverse impact of irrigated agriculture and approaches to their solution in arid zones

The current practice of water resources use in irrigated agriculture in the Republic of Azerbaijan has some specific features and causes problems in the management of irrigation systems of different levels, associated with the existing land use and cropping patterns in the country. This article substantiates the need to implement a system of measures for improving water resources management in irrigation aimed to prevent the further depletion of their reserves through modernization of irrigation–reclamation systems and improvement of agricultural practices. The article proposes principles for protection of water resources and measures to mitigate the aftereffects of intense irrigation under anticipated increase in the internal consumption of freshwater and a decrease in transboundary river inflow into the Republic of Azerbaijan in the context of increasing water intake in the countries in Kura–Aras basin and global climate changes.     

A stochastic model for optimal operation of inter-basin water allocation systems: a case study

This paper presents a new methodology for optimal operation of inter-basin water transfer systems by conjunctive use of surface water resources in water donor basin and groundwater resources in water receiving basin. To incorporate the streamflow uncertainty, an integrated stochastic dynamic programming (ISDP) model is developed. In the ISDP, the monthly inflow to the reservoir in the water donor basin, the water storage of the reservoir, and the water storage of the aquifer in the water receiving basin are considered as state variables. A water allocation optimization model is embedded in the main structure of ISDP and a new ensemble streamflow prediction model based on K-nearest-neighbourhood algorithm is also developed and linked to the ISDP. By using a new reoptimization process, the ISDP model provides monthly policies for water allocation to users in water donor and receiving basins. As water users can form a coalition to increase their benefits, several solution concepts in cooperative game theory, namely Nash–Harsanyi, Shapley, Nucleolus, Weak Nucleolus, Proportional Nucleolus, Separable Costs Remaining Benefits (SCRBs) and Minimum Costs Remaining Savings are utilized to determine the profit of each water user. In the last step, stakeholders make negotiation over these solution concepts using the Fallback bargaining theory to reach a unanimous agreement on the final distribution of the total benefit. The methodology is applied to an inter-basin water transfer project and the results show that the Shapley and SCRB solutions concepts can provide better distributions for the total benefit and the total benefit of water users is increased by a factor of 1.6 when they participate in a grand coalition.     

Ungaged inflow and loss patterns in urban and agricultural sub-reaches of the Logan River Observatory

Streams in semi-arid urban and agricultural environments are often heavily diverted for anthropogenic purposes. However, they simultaneously receive substantial inflows from a variety of ungaged sources including stormwater returns, tile drainage, and irrigation runoff that help sustain flow during dry periods. Due to the inability to identify sources or directly gage many of these inflows, there is a clear need for methods to understand source origination while quantifying potential gains and losses over highly impacted reaches. In the context of the Logan River Observatory, historical gage data illustrate the importance of ungaged and unidentified inflows on maintaining or enhancing flows in both urban and agricultural reaches containing large diversions. To understand the inflows in this portion of the Logan River, we first analysed water samples for ions collected from a subset of representative inflow sources and applied clustering analyses to establish inflow source classifications and associated ion concentration ranges. These representative concentration ranges, combined with mainstem flow and river ion samples taken at sub-reach scales, allow for the application of flow and mass balances to quantify inflow rates from different sources as well as any losses. These calculations demonstrate significant gains and losses occurring in many sub-reaches during three sampling events. The dominant land use (urban or agriculture) and flow regime at the time of sampling were the primary drivers of gains and losses. These exchanges were found to be most important below large diversions during low flow conditions. This highlights the need to classify inflow sources (urban or agriculture, surface or groundwater) and estimate their contributions to anticipate instream consequences of land use and water management decisions. As irrigation and water conveyance practices become more efficient, a portion of these ungaged inflows could be diminished or eliminated, thus further depleting streamflow during dry periods.     

Aquifer responses to El Niño-Southern Oscillation, Southwest British Columbia

We used climatological composite analysis to investigate El Ni?o-Southern Oscillation (ENSO) signals in long-term shallow ground water level observations from four wells in the lower Fraser Valley of British Columbia. Significance of differences between warm-phase, cold-phase, and neutral climate states was assessed with a Monte Carlo bootstrap technique. We also considered time series of local precipitation and streamflow for comparison. Composite annual hyetographs suggest that ENSO precipitation impacts are largely limited to winter and spring, with higher and lower rainfall occurring, respectively, under cold-phase and warm-phase episodes. This is consistent with prior work in the region and is found to be directly reflected in both streamflow and ground water level data. The mean magnitude of ENSO terrestrial hydrologic anomalies can be up to approximately 50% of the average seasonal cycle amplitude. ENSO does not appear to systematically affect annual hydrometeorological cycle timing in this study area. However, relative to the surface hydrologic systems considered, aquifers are observed to retain a stronger memory of seasonal ENSO-related precipitation anomalies, with changes potentially extending through the following summer, presumably reflecting storage effects. Most responses appear to be somewhat nonlinear.     

Regime-dependent streamflow sensitivities to Pacific climate modes cross the Georgia–Puget transboundary ecoregion

The Georgia Basin–Puget Sound Lowland region of British Columbia (Canada) and Washington State (USA) presents a crucial test in environmental management due to its combination of abundant salmonid habitat, rapid population growth and urbanization, and multiple national jurisdictions. It is also hydrologically complex and heterogeneous, containing at least three streamflow regimes: pluvial (rainfall-driven winter freshet), nival (melt-driven summer freshet), and hybrid (both winter and summer freshets), reflecting differing elevation ranges within various watersheds. We performed bootstrapped composite analyses of river discharge, air temperature, and precipitation data to assess El Niño–Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) impacts upon annual hydrometeorological cycles across the study area. Canadian and American data were employed from a total of 21 hydrometric and four meteorological stations. The surface meteorological anomalies showed strong regional coherence. In contrast, the seasonal impacts of coherent modes of Pacific circulation variability were found to be fundamentally different between streamflow regimes. Thus, ENSO and PDO effects can vary from one stream to the next within this region, albeit in a systematic way. Furthermore, watershed glacial cover appeared to complicate such relationships locally; and an additional annual streamflow regime was identified that exhibits climatically driven non-linear phase transitions. The spatial heterogeneity of seasonal flow responses to climatic variability may have substantial implications to catchment-specific management and planning of water resources and hydroelectric power generation, and it may also have ecological consequences due to the matching or phase-locking of lotic and riparian biological activity and life cycles to the seasonal cycle. The results add to a growing body of literature suggesting that assessments of the streamflow impacts of ocean–atmosphere circulation modes must accommodate local hydrological characteristics and dynamics. Copyright © 2007 John Wiley & Sons, Ltd. The copyright in Paul H. Whitfield's contribution belongs to the Crown in right of Canada and such copyright material is reproduced with the permission of Environment Canada.     

High-resolution simulation of the spatial pattern of water use in continental China

ABSTRACT

High-resolution data on the spatial pattern of water use are a prerequisite for appropriate and sustainable water management. Based on one well-validated hydrological model, the Distributed Time Variant Gains Model (DTVGM), this paper obtains reliable high-resolution spatial patterns of irrigation, industrial and domestic water use in continental China. During the validation periods, ranges of correlation coefficient (R) and Nash-Sutcliffe efficiency (NSE) coefficient are 0.67–0.96 and 0.51–0.84, respectively, between the observed and simulated streamflow of six hydrological stations, indicating model applicability to simulate the distribution of water use. The simulated water use quantities have relative errors (RE) less than 5% compared with the observed. In addition, the changes in streamflow discharge were also correctly simulated by our model, such as the Zhangjiafen station in the Hai River basin with a dramatic decrease in streamflow, and the Makou station in the Pearl River basin with no significant changes. These changes are combined results of basin available water resources and water use. The obtained high-resolution spatial pattern of water use could decrease uncertainty of hydrological simulation and guide water management efficiently.

Editor M.C. Acreman; Associate editor X. Fang     

Modeling river/reservoir system management, water allocation, and supply reliability

The state of Texas has implemented a modeling system for assessing the availability and reliability of water resources that consists of a generalized simulation model called the Water Rights Analysis Package (WRAP) and input datasets for the state's 23 river basins. Reservoir/river system management and water allocation practices are simulated using historical naturalized monthly streamflow sequences to represent basin hydrology. Institutional systems for allocating streamflow and reservoir storage resources among numerous water users are considered in detail in evaluating basinwide impacts of water management decisions. The generalized WRAP model is a flexible tool that may be applied to river basins anywhere. The Texas experience in implementing a statewide modeling system illustrates issues that are relevant to water management in many other regions of the world.     

Large-scale climate teleconnections with South Korean streamflow variability

ABSTRACT

Leading patterns of observed seasonal extreme and mean streamflow on the Korean peninsula were estimated using an empirical orthogonal teleconnection (EOT) technique. In addition, statistical correlations on a seasonal basis were calculated using correlation and regression analyses between the leading streamflow patterns and various climate indices based on atmospheric–ocean circulation. The spatio-temporal patterns of the leading EOT modes for extreme and mean streamflow indicate an upstream mode for the Han River, with increasing trends in summer, and a downstream mode for the Nakdong River, with oscillations mainly on inter-decadal time scales in winter. The tropical ENSO (El Niño Southern Oscillation) forcing for both extreme and mean streamflow is coherently associated with summer to winter streamflow patterns. The western North Pacific monsoon has a negative correlation with winter streamflow variability, and tropical cyclone indices also exhibit significant positive correlation with autumn streamflow. Leading patterns of autumn and winter streamflow time series show predictability up to two seasons in advance from the Pacific sea-surface temperatures.     

Hydrological implications of the Southern Oscillation: variability of the rainfall-runoff relationship

Abstract

A connection between El Niño Southern Oscillation (ENSO) and weather phenomena in eastern Australia has been recognized for several decades. However, little work has been devoted to addressing how this correlation affects hydrological system behaviour within regional-scale catchments. In this study, spatially distributed ENSO effects are evaluated in terms of monthly rainfall, evaporation, streamflow and runoff characteristics for a 1300 km² catchment. The catchment is located in southeastern Australia where previous studies have indicated only modest ENSO influences on rainfall variability. Spatial and temporal analysis indicates that strongest ENSO-induced rainfall variability occurs during summer months. Additionally, the strength of the relationship is variable in space indicating that topographic controls may affect ENSO influences on rainfall totals and intensities. However, analysis of runoff shows substantially magnified ENSO-induced variability in comparison to the induced variability in rainfall. This may be attributable to the nonlinearity of runoff generation. Differences in antecedent moisture storage conditions will exist but may also be enhanced by complementary ENSO influences on daily rainfall intensities and mean monthly evaporation and temperature totals. The degree of the nonlinearity displayed by the hydrometeorological processes presented demonstrates that the significance of ENSO forecasts for surface water resource management should be assessed with direct regard to streamflow generation rather than on the basis of rainfall totals alone.     

Reservoir operation using El Niño forecasts—case study of Daule Peripa and Baba,Ecuador

Abstract

Reservoir operation is studied for the Daule Peripa and Baba system in Ecuador, where El Niño events cause anomalously heavy precipitation. Reservoir inflow is modelled by a Markov-switching model using El Niño–Southern Oscillation (ENSO) indices as input. Inflow is forecast using 9-month lead time ENSO forecasts. Monthly reservoir releases are optimized with a genetic algorithm, maximizing hydropower production during the forecast period and minimizing deviations from storage targets. The method is applied to the existing Daule Peripa Reservoir and to a planned system including the Baba Reservoir. Optimized operation is compared to historical management of Daule Peripa. Hypothetical management scenarios are used as the benchmark for the planned system, for which no operation policy is known. Upper bounds for operational performance are found via dynamic programming by assuming perfect knowledge of future inflow. The results highlight the advantages of combining inflow forecasts and storage targets in reservoir operation.

Editor D. Koutsoyiannis; Associate editor I. Nalbantis     

Collective action for water harvesting irrigation in the Lerma-Chapala Basin,Mexico

Water and watersheds are difficult to separate for management purposes. Providing irrigation as a supplement to rainfall for crop production requires considerable collective action at the watershed level to mobilize labor and other resources, as well as to make decisions and implement the distribution of benefits. Small-scale water harvesting irrigation systems in Mexico have endured for centuries. They now face considerable challenges with changes in the ejido property rights over land and water, the growing importance of alternative sources of livelihoods, and increasing scarcity and competition for water within the river basins.     

Evaluation of ocean-atmospheric indices as predictors for summer streamflow of the Yangtze River based on ROC analysis

Antecedent anomalies of sea surface temperature and atmospheric circulation are important signals for making long-term streamflow forecasts. In this study, four groups of ocean-atmospheric indices, i.e, El Niño Southern Oscillation (ENSO), the Northern Hemisphere atmospheric circulation, the Southern Hemisphere atmospheric circulation (SAC), and the Western Pacific and Indian Ocean SST (WPI), are evaluated for forecasting summer streamflow of the Yangtze River. The gradient boosting regression tree (GBRT) is used to forecast streamflow based on each group of indices. The score based on receiver operating characteristics (ROC) curves, i.e., area under the ROC curve (AUC), is used to evaluate skills of models for identifying the high category and the low category of summer streamflow. It is found that the ENSO group and the SAC group show higher AUC values. Furthermore, both AUC values of GBRT models and individual indices show that the low flow years are easier to be identified than the high flow years. The result of this study highlights the skill from the Southern Hemisphere circulation systems for forecasting summer streamflow of the Yangtze River. Results of relative influences of predictors in GBRT models and AUC of individual indices indicate some key ocean-atmospheric indices, such as the Multivariate ENSO Index and the 500-hPa height of the east of Australia.     

Management of an aquifer with artificial recharge using water balance

Abstract

This study considers the management of an aquifer with artificial recharge whose water resources are mainly used for irrigation and where the irrigation return flows and natural discharge are considerable. These two variables are dependent on the use and increase of water resources. The interaction between some inflow and outflow variables is taken into account in the computation of the actual volume of water available, there being a pre-established artificial recharge of the aquifer. Conversely, the artificial recharge for a given water demand may be calculated. The most important inflow and outflow variables are used in an equation system (the water balance for each period of time) for these interactions and the total inflow and outflow. An iterative procedure is developed that solves the equation and with it the computation of the actual availability of water and storage.     

Streamflow drought time series forecasting

Drought is considered to be an extreme climatic event causing significant damage both in the natural environment and in human lives. Due to the important role of drought forecasting in water resources planning and management and the stochastic behavior of drought, a multiplicative seasonal autoregressive integrated moving average (SARIMA) model is applied to the monthly streamflow forecasting of the Zayandehrud River in western Isfahan province, Iran. After forecasting 12 leading month streamflow, four drought thresholds including streamflow mean, monthly streamflow mean, 2-, 5-, 10- and 20-year return period monthly drought and standardized streamflow index were chosen. Both observed and forecasted streamflow showed a drought period with different severity in the lead-time. This study also demonstrates the usefulness of SARIMA models in forecasting, water resources planning and management.     

Radiance data assimilation for operational snow and streamflow forecasting

Estimation of seasonal snowpack, in mountainous regions, is crucial for accurate streamflow prediction. This paper examines the ability of data assimilation (DA) of remotely sensed microwave radiance data to improve snow water equivalent prediction, and ultimately operational streamflow forecasts. Operational streamflow forecasts in the National Weather Service River Forecast Center (NWSRFC) are produced with a coupled SNOW17 (snow model) and SACramento Soil Moisture Accounting (SAC-SMA) model. A comparison of two assimilation techniques, the ensemble Kalman filter (EnKF) and the particle filter (PF), is made using a coupled SNOW17 and the microwave emission model for layered snow pack (MEMLS) model to assimilate microwave radiance data. Microwave radiance data, in the form of brightness temperature (TB), is gathered from the advanced microwave scanning radiometer-earth observing system (AMSR-E) at the 36.5 GHz channel. SWE prediction is validated in a synthetic experiment. The distribution of snowmelt from an experiment with real data is then used to run the SAC-SMA model. Several scenarios on state or joint state-parameter updating with TB data assimilation to SNOW-17 and SAC-SMA models were analyzed, and the results show potential benefit for operational streamflow forecasting.