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1.
Drought is a climatic event that can cause significant damage both in natural environment and in human lives. Drought forecasting is an important issue in water resource planning. Due to the stochastic behaviour of droughts, a multiplicative seasonal autoregressive integrated moving average model was applied to forecast monthly streamflow in a small watershed in Galicia (NW Spain). A better streamflow forecast obtained when the Martone index was included in the model as explanatory variable. After forecasting 12 leading month streamflow, three drought thresholds: streamflow mean, monthly streamflow mean and standardized streamflow index were chosen. Both observed and forecasted streamflow showed no drought evidence in this basin.  相似文献   

2.
ABSTRACT

An appropriate streamflow forecasting method is a prerequisite for implementation of efficient water resources management in the water-limited, arid regions that occupy much of Iran. In the current research, monthly streamflow forecasting was combined with three data-driven methods based on large input datasets involving 11 precipitation stations, a natural streamflow, and four climate indices through a long period. The major challenges of rainfall–runoff modelling are generally attributed to complex interacting processes, the large number of variables, and strong nonlinearity. The sensitivity of data-driven methods to the dimension of input/output datasets would be another challenge, so large datasets should be compressed into independently standardized principal components. In this study, three pre-processing techniques were applied: singular value decomposition (SVD) provided more efficient forecasts in comparison to principal component analysis (PCA) and average values of inputs in all networks. Among the data-driven methods, the multi-layer perceptron (MLP) with 1-month lag-time outperformed radial basis and fuzzy-based networks. In general, an increase in monthly lag-time of streamflow forecasting resulted in a decline in forecasting accuracy. The results reveal that SVD was highly effective in pre-processing of data-driven evaluations.  相似文献   

3.
Egypt is almost totally dependent on the River Nile for satisfying about 95% of its water requirements. The River Nile has three main tributaries: White Nile, Blue Nile, and River Atbara. The Blue Nile contributes about 60% of total annual flow reached the River Nile at Aswan High Dam. The goal of this research is to develop a reliable stochastic model for the monthly streamflow of the Blue Nile at Eldiem station, where the Grand Ethiopian Renaissance Dam (GERD) is currently under construction with a storage capacity of about 74 billion m3. The developed model may help to carry out a reliable study on the filling scenarios of GERD reservoir and to minimize its expected negative side effects on Sudan and Egypt. The linear models: Deseasonalized AutoRegressive Moving Average (DARMA) model, Periodic AutoRegressive Moving Average (PARMA) model and Seasonal AutoRegressive Integrated Moving Average (SARIMA) model; and the nonlinear Artificial Neural Network (ANN) model are selected for modeling monthly streamflow at Eldiem station. The performance of various models during calibration and validation were evaluated using the statistical indices: Mean Absolute Error, Root Mean Square Error and coefficient of determination (R2) which indicate the strength of fitting between observed and forecasted values. The results show that the performance of the nonlinear model (ANN) was much better than all investigated linear models (DARMA, PARMA and SARIMA) in forecasting the monthly flow discharges at Eldiem station.  相似文献   

4.
Information on regional drought characteristics provides critical information for adequate water resource management. This study introduces a method to calculate the probability of a specific area to be affected by a drought of a given severity and demonstrates its potential for calculating both meteorological and hydrological drought characteristics. The method is demonstrated using Denmark as a case study. The calculation procedure was applied to monthly precipitation and streamflow series separately, which were linearly transformed by the Empirical Orthogonal Functions (EOF) method. Denmark was divided into 260 grid-cells of 14×17 km, and the monthly mean and the EOF-weight coefficients were interpolated by kriging. The frequency distributions of the first two (streamflow) or three (precipitation) amplitude functions were then derived. By performing Monte Carlo simulations, amplitude functions corresponding to 1000 years of data were generated. Based on these simulated functions as well as interpolated mean and weight coefficients, long time series of precipitation and streamflow were simulated for each grid-cell. The probability distribution functions of the area covered by a drought and the drought deficit volumes were then derived and combined to produce drought severity-area-frequency curves. These curves allowed an estimation of the probability of an area of a certain extent to have a drought of a given severity, and thereby return periods could be assigned to historical drought events. A comparison of drought characteristics showed that streamflow droughts are less homogeneous over the region, less frequent and last for longer time periods than precipitation droughts.  相似文献   

5.
The optimal operation of dam reservoirs can be programmed and managed by predicting the inflow to these structures more accurately. To this end, there are various linear and nonlinear models. However, some hydrological problems like inflow with extreme seasonal variation are not purely linear or nonlinear. To improve the forecasting accuracy of this phenomenon, a linear Seasonal Auto Regressive Integrated Moving Average (SARIMA) model is combined with a nonlinear Artificial Neural Network (ANN) model. This new model is used to predict the monthly inflow to the Jamishan dam reservoir in West Iran. A comparison of the SARIMA and ANN models with the proposed hybrid model’s results is provided accordingly. More specifically, the models’ performance in forecasting base and flood flows is evaluated. The effect of changing the forecasting period length on the models’ accuracy is studied. The results of increasing the number of SARIMA model parameters up to five are investigated to achieve more accurate forecasting. The hybrid model predicts peak flood flows much better than the individual models, but SARIMA outperforms the other models in predicting base flow. The obtained results indicate that the hybrid model reduces the overall forecast error more than the ANN and SARIMA models. The coefficient of determination of the hybrid, ANN and SARIMA models were 0.72, 0.64 and 0.58, and the root mean squared error values were 1.02, 1.16 and 1.27 respectively, during the forecast period. Changing the forecasting length also indicated that these models can be used in the long term without increasing the forecast error.  相似文献   

6.
L. Ribeiro 《水文科学杂志》2013,58(10):1840-1852
Abstract

Today, more than ever, there is a need to implement robust statistical methods to ensure the proper evaluation of water resources data to support decision makers in water resources planning and management. Graphing or mapping data for visualization is the easiest way to communicate trends, especially to a non-technical audience. This paper describes the use of an approach that combines the Mann-Kendall test, Sen slope test and principal component analysis to detect and map the monthly trends of piezometric time series and their magnitude in the period 1979–2008. The data were obtained in 23 shallow wells in the alluvial aquifers of the Elqui River basin in central Chile, an area characterized by scarce water resources and intense agricultural and mining activities. The results show significant downward trends at the majority of the wells. Because groundwater in these shallow wells is highly dependent on the water in the river and its tributaries, the reasons for these downward trends are mainly related to a decrease of streamflow observed in the Elqui River. The streamflow is derived from mountain snowmelt rather than from rainfall, which showed no flow trend during the same period.  相似文献   

7.
Hydrological drought analysis is very important in the design of hydrotechnical projects and water resources management and planning. In this study, a methodology is proposed for the analysis of streamflow droughts using the threshold level approach. The method has been applied to Yermasoyia semiarid basin in Cyprus based on 30‐year daily discharge data. Severity was defined as the accumulated water deficit volume occurring during a drought event, in respect with a target threshold. Fixed and variable thresholds (seasonal, monthly, and daily) were employed to derive the drought characteristics. The threshold levels were determined based on the Q50 percentiles of flow extracted from the corresponding flow duration curves for each threshold. The aim is to investigate the sensitivity of these thresholds in the estimation of maximum drought severities for various return periods and the derivation of severity–duration–frequency curves. The block maxima and the peaks over threshold approaches were used to perform the extreme value analysis. Three pooling procedures (moving average, interevent time criterion, and interevent time and volume criterion) were employed to remove the dependent and minor droughts. The application showed that the interevent time and volume criterion is the most unbiased pooling method. Therefore, it was selected to estimate the drought characteristics. The results of this study indicate that monthly and daily variable thresholds are able to capture abnormal drought events that occur during the whole hydrological year whereas the other two, only the severe ones. They are also more sensitive in the estimation of maximum drought severities and the derivation of the curves because they incorporate better the effect of drought durations.  相似文献   

8.
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.  相似文献   

9.
Since the Three Gorges Reservoir (TGR) was put into operation in June 2003, the effects of the TGR on downstream hydrology and water resources have become the focus of public attention. This article examines the effects of the TGR on the hydrological droughts at the downstream Yichang hydrological station during 2003–2011. The two‐parameter monthly water balance model was used to generate the monthly discharges at the Yichang station for the period of 2003–2011 to represent the unregulated flow regime and thus to provide a comparison benchmark for the observed flow series at the Yichang station after the operation of the TGR. To provide a reference series for the observed monthly discharge series of the entire study period of 1951–2011, we constructed the naturalized monthly discharge series at the Yichang station by joining the observed monthly discharge at the Yichang station for the period of 1951–2002 and the two‐parameter monthly water balance simulated monthly runoff at the Yichang station for the period of 2003–2011. For both the observed and naturalized monthly discharge series of 1951–2011, the hydrological drought index series were calculated using the standardized streamflow index method. By comparing the drought indices of these two monthly discharge series, we investigated the effects of the TGR on the hydrological droughts at the downstream Yichang station during 2003–2011. The results show that the hydrological droughts at the downstream Yichang station are slightly aggravated by the TGR's initial operation from 2003 to 2011. The river flow reduction at the Yichang station after impoundment of the TGR might account for the downstream drought aggravation. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

10.
Predicting the streamflow of rivers can have a significant economic impact, as this can help in agricultural water management and in providing protection from water shortages and possible flood damage. In this study, two statistical models have been used; Deseasonalized Autoregressive moving average model (DARMA) and Artificial Neural Network (ANN) to predict monthly streamflow which important for reservoir operation policy using different time scale, monthly and 1/3 monthly (ten-days) flow data for River Nile basin at five key stations. The streamflow series is deseasonalized at different time scale and then an appropriate nonseasonal stochastic DARMA (p, q) models are built by using the plots of Partial Auto Correlation Function (PACF) to determine the order (p) of DARMA model. Then the deseasonalized data for key stations are used as input to ANN models with lags equals to the order (p) of DARMA model. The performance of ANN and DARMA models are compared using statistical methods. The results show that the developed model (using 1/3 monthly (ten-days) and ANN) has the best performance to predict monthly streamflow at all key stations. The results also show that the relative error in the developed model result did not exceed 9% while in the traditional models reach to 68% in the flood months in the testing period. The result also indicates that ANN has considerable potential for river flow forecasting.  相似文献   

11.
通过对青海湖流域布哈河和沙柳河50年来的河川径流量分析发现,布哈河和沙柳河年径流量50年来没有显著的变化趋势,这两条河流的河川径流量对青海湖水位下降所起的作用不明显;布哈河月平均流量的年际变化在1月、2月和3月有减少的趋势,沙柳河月平均流量的年际变化在1月、2月、4月和5月亦有减少的趋势;布哈河的径流量大于沙柳河的径流量,在55%-91%频率范围内,布哈河的径流量小于沙柳河的径流量,在其它频率范围内,布哈河的径流量显著大于沙柳河的径流量,在一年中,布哈河和沙柳河的月径流量具有显著的差异;布哈河来水丰沛期是20世纪60年代,贫乏期是90年代,70和80年代为平水期;沙柳河月径流量从20世纪60年代到90年代一直比较稳定,没有发生显著的变化.  相似文献   

12.
Drought forecasting using stochastic models   总被引：8，自引：4，他引：8  
Drought is a global phenomenon that occurs virtually in all landscapes causing significant damage both in natural environment and in human lives. Due to the random nature of contributing factors, occurrence and severity of droughts can be treated as stochastic in nature. Early indication of possible drought can help to set out drought mitigation strategies and measures in advance. Therefore drought forecasting plays an important role in the planning and management of water resource systems. In this study, linear stochastic models known as ARIMA and multiplicative Seasonal Autoregressive Integrated Moving Average (SARIMA) models were used to forecast droughts based on the procedure of model development. The models were applied to forecast droughts using standardized precipitation index (SPI) series in the Kansabati river basin in India, which lies in the Purulia district of West Bengal state in eastern India. The predicted results using the best models were compared with the observed data. The predicted results show reasonably good agreement with the actual data, 1–2 months ahead. The predicted value decreases with increase in lead-time. So the models can be used to forecast droughts up to 2 months of lead-time with reasonably accuracy.  相似文献   

13.
《水文科学杂志》2013,58(6):1006-1020
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.  相似文献   

14.
In this research, a dynamic linear spatio-temporal model (DLSTM) was developed and evaluated for monthly streamflow forecasting. For parameter estimation, coupled expectation–maximization (EM) algorithm and Kalman filter was adopted. This combination enables the model to estimate the state vector and parameters concurrently. Different forecast scenarios including various combinations of upstream stations were considered for downstream station streamflow forecasting. Several statistical criteria, nonparametric and visual tests were used for model evaluation. Results indicated that the spatio-temporal model performed acceptably in almost all scenarios. The dynamic model was able to capitalize on coupled spatial and temporal information provided that there is spatial connectivity in the studied hydrometric stations network. Moreover, threshold level method was used for model evaluation in drought and wet periods. Results indicated that, in validation phase, the model was able to forecast the drought duration and volume deficit/over threshold, although volume deficit/over threshold could not be accurately simulated.  相似文献   

15.
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.  相似文献   

16.
ABSTRACT

Ten notable meteorological drought indices were compared on tracking the effect of drought on streamflow. A 730-month dataset of precipitation, temperature and evapotranspiration for 88 catchments in Oregon, USA, representing pristine conditions, was used to compute the drought indices. These indices were correlated with the monthly streamflow datasets of the minimum, maximum and mean discharge, and the discharge monthly fluctuation; it was revealed that the 3-month Z-score drought index (Z3) has the best association with the four streamflow variables. The Mann-Kendall trend detection test applied to the latter index time series mainly highlighted a downward trend in the autumn and winter drought magnitude (DM) and an upward trend in the spring and summer DM (p = 0.05). Finally, the Pettitt test indicated an abrupt decline in the annual and autumn DM, which began in 1984 and 1986, respectively.  相似文献   

17.
Multiscale variability of streamflow changes in the Pearl River basin,China   总被引：1，自引：1，他引：0  
The Pearl River basin bears the heavy responsibility for the water supply for the neighboring cities such as Macau, Hong Kong and others. Therefore, effective water resource management is crucial for sustainable use of water resource. However, good knowledge of changing properties of streamflow changes is the first step into the effective water resource management. With this in mind, stability and variability of streamflow changes in the Pearl River basin is thoroughly analyzed based on monthly streamflow data covering last half century using Mann–Kendall trend test and scanning t- and F-test techniques. The results indicate: (1) significant increasing monthly streamflow is observed mainly in January–April, June and October–December. Monthly streamflow during May–September is in not significant changes. Besides, stations characterized by significant monthly streamflow changes are located in the middle and the lower Pearl River basin; (2) changing points of monthly streamflow series are detected mainly during mid-1960s, early 1970s, mid-1970s, early 1980s and early 1990s and these periods are roughly in good agreement with those of annual, winter and summer precipitation across the Pearl River basin, implying tremendous influences of precipitation changes on streamflow variations; (3) abrupt behaviors tend to be ambiguous from the upper to the lower Pearl River basin, which should be due to enhancing combined effects of abrupt changes of precipitation. The streamflow comes to be lower stability in recent decades. However, high stability of streamflow changes are observed at hydrological stations in the lower Pearl River basin. The results of this study will be of great scientific and practical merits in terms of effective water resource management in the Pearl River basin under the influences of climate changes and human activities.  相似文献   

18.
水文干旱多变量联合设计及水库影响评估   总被引：2，自引：1，他引：1  
基于东江流域博罗站月径流数据,采用游程理论提取水文干旱事件.选用Meta-Gaussian Copula函数,统计模拟水文干旱指标的多变量联合分布.采用Kendall联合重现期和最大可能权函数,设计给定联合超越重现期的水文干旱指标组合值,并定量评估水库径流调节作用对水文干旱多变量联合特征的影响.结果表明:东江流域水文干旱历时、强度和峰值的统计优选分布均为韦布尔分布.干旱指标之间具有较高的正相关性,Meta-Gaussian Copula能够很好地模拟水文干旱指标两变量和三变量联合分布.基于任意两个变量联合设计和三变量联合设计,干旱指标设计组合值位于同频位置附近,且同一个干旱指标设计值在不同变量组合之间差别较小.水库径流调节作用对于缓解东江流域水文干旱效果明显,同一组干旱指标的多变量联合超越重现期在水库影响下明显变大.联合超越重现期越小,水库对联合设计值的影响程度越大.根据目前水库运行模式,若要满足河道内最小管理流量目标,联合超越重现期10 a一遇的干旱历时、强度和峰值依然达到了约3.89~4.04月、7.20~7.97亿m3和2.99~3.12亿m3.  相似文献   

19.
In recent years, the Xitiaoxi river basin in China has experienced intensified human activity, including city expansion and increased water demand. Climate change also has influenced streamflow. Assessing the impact of climate variability and human activity on hydrological processes is important for water resources planning and management and for the sustainable development of eco‐environmental systems. The non‐parametric Mann–Kendall test was employed to detect the trends of climatic and hydrological variables. The Mann–Kendall–Sneyers test and the moving t‐test were used to locate any abrupt change of annual streamflow. A runoff model, driven by precipitation and potential evapotranspiration, was employed to assess the impact of climate change on streamflow. A significant downward trend was detected for annual streamflow from 1975 to 2009, and an abrupt change occurred in 1999, which was consistent with the change detected by the double mass curve test between streamflow and precipitation. The annual precipitation decreased slightly, but upward trends of annual mean temperature and potential evapotranspiration were significant. The annual streamflow during the period 1999–2009 decreased by 26.19% compared with the reference stage, 1975–1998. Climate change was estimated to be responsible for 42.8% of the total reduction in annual streamflow, and human activity accounted for 57.2%. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

20.
ABSTRACT

In this study, three representative concentration pathways (RCPs) and 15 general circulation models of the Coupled Model Intercomparison Project Phase 5 were used to assess the behaviour of precipitation (P) and surface air temperature (SAT) over part of the Songhua River Basin. The Water Evaluation and Planning (WEAP) model linked with SAT and P was used for monthly simulation of streamflow to assess the influence of land use/land cover and climate change on the streamflow. The results suggest that, under RCP2.6, RCP4.5 and RCP8.5, the SAT over the study area may increase in the 21st century by 1.12, 2.44 and 5.82°C, respectively. Moreover, by the middle of the 21st century, streamflow in the basin may have decreased by 19%. The decrease in streamflow may be due to changed land use conditions and water withdrawal, having critical implications for management and future planning of water resources in the basin.  相似文献   

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