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1.
Risk assessment plays an important role in disaster risk management. Existing multi-hazard risk assessment models are often qualitative or semi-quantitative in nature and used for comparative study of regional risk levels. They cannot estimate directly probability of disaster losses from the joint impact of several hazards. In this paper, a quantitative approach of multi-hazard risk assessment based on vulnerability surface and joint return period of hazards is put forward to assess the risk of crop losses in the Yangtze River Delta region of China. The impact of strong wind and flood, the two most prominent agricultural hazards in the area, is analyzed. The multi-hazard risk assessment process consists of three steps. First, a vulnerability surface, which denotes the functional relationship between the intensity of the hazards and disaster losses, was built using the crop losses data for losses caused by strong wind and flood in the recent 30 years. Second, the joint probability distribution of strong wind and flood was established using the copula functions. Finally, risk curves that show the probability of crop losses in this multi-hazard context at four case study sites were calculated according to the joint return period of hazards and the vulnerability surface. The risk assessment result of crop losses provides a useful reference for governments and insurance companies to formulate agricultural development plans and analyze the market of agricultural insurance. The multi-hazard risk assessment method developed in this paper can also be used to quantitatively assess multi-hazard risk in other regions.  相似文献   

2.
Climatic and technological factors are two remarkable aspects that are thought to contribute to crop yield change. However, the most significant factors and their contribution rate remain debatable. Selecting Hunan Province, which is one of the largest paddy rice producing regions in China as the research area, the marginal contributions of climatic and technological factors to late paddy yield change are estimated using a county-level panel data regression model with explicit consideration of technological variables during 2000–2011. The results indicate that the mean daily temperature and adoption rate of hybrid rice have significant positive impacts on late paddy rice yield. During the research period, 1 °C temperature increase will cause 7.220 t/km2 increase in late paddy rice yield, and 1 % increase in the adoption rate of hybrid rice will cause 0.212 t/km2 increase. Climatic factors, especially their annual variability, exhibit a stronger overall linkage to changes in late paddy rice yield in the study area compared with the technological factors. Climatic factors accounted for 67.645 and 74.585 % of the trend and variability in late paddy rice yield, respectively. The results of this study can provide valuable information for stakeholders to adjust the input on late paddy rice production and better adapt to the effect of climate change.  相似文献   

3.
Assessing the response of flood risk caused by climate change and social development is very important in terms of determining high risk areas in different periods as well as making disaster mitigating plans. We establish a flood risk assessment model based on geographic information system and natural disaster risk assessment theory. In order to compare the index value in different periods and spaces, we utilize the spatial and temporal standardization method to standardized index. To avoid one-sidedness caused by using one weight calibration method only, we employ the least square method to synthesize weights determine by the Analytic Hierarchy Process (AHP) method and the Entropy weight method. We adopt the observed data of the Huaihe River basin from 1960 to 2010 to assess the changing of flood risk between period I (1960–1980) and period II (1980–2010). After pre-processing the atmosphere–ocean coupled global circulation models (AOGCM) data, including bias correction and downscaling, we use the corrected data to predict the flood risk during future period III (2010–2040). The results show that high risk areas and moderate to high risk areas during period I take up 17.68 and 33.88 % of the total area of the Huaihe River basin, respectively. During period II, the high risk areas show an increasing percent change of 1.93 % and a decreasing trend in moderate to high risk areas of 3.8 %. Compared with period II, the high risk areas and the moderate to high risk areas during period III show an increasing trend of 8.02 and 0.77 %, which is the result of the combined effects of climate change and social development. The results presented here can provide useful information for decision-makers.  相似文献   

4.
Water resources and soil erosion are the most important environmental concerns in the Yangtze River basin, where soil erosion and sediment yield are closely related to rainfall erosivity. The present study explores the spatial and temporal changing patterns of the rainfall erosivity in the Yangtze River basin of China during 1960–2005 at annual, seasonal and monthly scales. The Mann–Kendall test is employed to detect the trends during 1960–2005, and the T test is applied to investigate possible changes between 1991–2005 and 1960–1990. Meanwhile the Rescaled Range Analysis is used for exploring future trend of rainfall erosivity. Moreover the continuous wavelet transform technique is using studying the periodicity of the rainfall erosivity. The results show that: (1) The Yangtze River basin is an area characterized by uneven spatial distribution of rainfall erosivity in China, with the annual average rainfall erosivity range from 131.21 to 16842 MJ mm ha?1 h?1. (2) Although the directions of trends in annual rainfall erosivity at most stations are upward, only 22 stations have significant trends at the 90 % confidence level, and these stations are mainly located in the Jinshajiang River basin and Boyang Lake basin. Winter and summer are the seasons showing strong upward trends. For the monthly series, significant increasing trends are mainly found during January, June and July. (3) Generally speaking, the results detected by the T test are quite consistent with those detected by the Mann–Kendall test. (4) The rainfall erosivity of Yangtze River basin during winter and summer will maintain a detected significant increasing trend in the near future, which may bring greater risks to soil erosion. (5) The annual and seasonal erosivity of Yangtze River basin all have one significant periodicity of 2–4 years.  相似文献   

5.
Stochastic optimization methods are used for optimal design and operation of surface water reservoir systems under uncertainty. Chance-constrained (CC) optimization with linear decision rules (LDRs) is an old approach for determining the minimum reservoir capacity required to meet a specific yield at a target level of reliability. However, this approach has been found to overestimate the reservoir capacity. In this paper, we propose the reason for this overestimation to be the fact that the reliability constraints considered in standard CC LDR models do not have the same meaning as in other models such as reservoir operation simulation models. The simulation models have fulfilled a target reliability level in an average sense (i.e., annually), whereas the standard CC LDR models have met the target reliability level every season of the year. Mixed integer nonlinear programs are presented to clarify the distinction between the two types of reliability constraints and demonstrate that the use of seasonal reliability constraints, rather than an average reliability constraint, leads to 80–150 % and 0–32 % excess capacity for SQ-type and S-type CC LDR models, respectively. Additionally, a modified CC LDR model with an average reliability constraint is proposed to overcome the reservoir capacity overestimation problem. In the second stage, we evaluate different operating policies and show that for the seasonal (average) reliability constraints, open-loop, S-type, standard operating policy, SQ-type, and general SQ-type policies compared to a model not using any operation rule lead to 190–460 % (200–550 %), 100–200 % (80–300 %), 0–90 % (0–60 %), 30–90 % (0–20 %), and 10–90 % (0–10 %) excess capacity, respectively.  相似文献   

6.
Geological lineaments, depths to the basement, uranium concentrations, and remobilization in parts of the Upper Benue Trough, covering about 55 × 55 km2 (longitudes 11°30′–12°00′E and 10°30′–10°30′N), Northeastern Nigeria were investigated using integrated High-Resolution Aeromagnetic Data (HRAD) and radiometric data. This was with a view to identifying the potential zones of uranium occurrence in the area. The HRAD was processed to accentuate anomalies of interest and depths estimate of 150–1941 m were obtained from source parameter imaging technique. The results from the superposition of the horizontal gradient magnitude, analytical signal amplitude, first vertical derivative, and 3D Euler solutions of the HRAD revealed that the study area was dissected by linear structures that trend ENE–WSW, NE–SW, E–W, NNE–SSW, WNW–ESE, and NW–SE; among which the ENE–WSW and NE–SW trends dominated. Analyses of radiometric data showed that uranium ores in the study area were possibly remobilized epigenetically from the granitic rocks, and were later deposited into sedimentary rocks (Bima formation). Burashika group (Bongna hills) and Wawa area of the study area showed vein-type deposits, while the anatectic migmatite in the northeastern region and the uranium rich Bima formation showed both fault/fracture and contact types of deposition. It was also observed the northwesterly and southeasterly, dominant dip direction, dipping faults dip in the same direction as the paleocurrent direction (direction of depositions of sediments), and trend in a direction perpendicular to the hypothetical direction of uranium deposition. The study concluded that the studied area is dissected by several linear structures and the studied area possibly contains deposits of uranium ore, which are likely to be found in: the Bima Sandstones of Wade, Shinga, Bima hill, Wuyo, Teli, Bryel, Dali, Barkan, Gasi, Kunkun, Boragara, Deba, and Gberundi localities; the anatectic migmatite at Kubuku, Whada, and Hyama; and the Bongna hills and agglomerates around Burashika, Kawaba, and Galu.  相似文献   

7.
Water temperature has a significant influence on aquatic organisms, including stenotherm fish such as salmonids. It is thus of prime importance to build reliable tools to forecast water temperature. This study evaluated a statistical scheme to model average water temperature based on daily average air temperature and average discharge at the Sainte-Marguerite River, Northern Canada. The aim was to test a non-parametric water temperature generalized additive model (GAM) and to compare its performance to three previously developed approaches: the logistic, residuals regression and linear regression models. Due to its flexibility, the GAM was able to capture some of the nonlinear response between water temperature and the two explanatory variables (air temperature and flow). The shape of these effects was determined by the trends shown in the collected data. The four models were evaluated annually using a cross-validation technique. Three comparison criteria were calculated: the root mean square error (RMSE), the bias error and the Nash-Sutcliffe coefficient of efficiency (NSC). The goodness of fit of the four models was also compared graphically. The GAM was the best among the four models (RMSE = 1.44°C, bias = ?0.04 and NSC = 0.94).  相似文献   

8.
Abstract

Statistically significant FAO-56 Penman-Monteith (FAO-56 PM) and adjusted Hargreaves (AHARG) reference evapotranspiration (ET0) trends at monthly, seasonal and annual time scales were analysed by using linear regression, Mann-Kendall and Spearman’s Rho tests at the 1 and 5% significance levels. Meteorological data were used from 12 meteorological stations in Serbia, which has a humid climate, for the period 1980–2010. Web-based software for conducting the trend analyses was developed. All of the trends significant at the 1 and 5% significance levels were increasing. The FAO-56 PM ET0 trends were almost similar to the AHARG trends. On the seasonal time scale, for the majority of stations significant increasing trends occurred in summer, while no significant positive or negative trends were detected by the trend tests in autumn for the AHARG series. Moreover, 70% of the stations were characterized by significant increasing trends for both annual ET0 series.

Editor Z.W. Kundzewicz; Associate editor S. Grimaldi

Citation Gocic, M. and Trajkovic, S., 2013. Analysis of trends in reference evapotranspiration data in a humid climate. Hydrological Sciences Journal, 59 (1), 165–180.  相似文献   

9.
Identification of sub-trends from hydro-meteorological series   总被引：1，自引：1，他引：0  
In hydro-meteorological trend analysis, an alteration in the given variable is detected by considering the long-term series as a whole. Whereas the long-term trend may be absent, the significance of hidden (short-durational) sub-trends in the series may be important for environmental management practices. In this paper, a graphical approach of identifying trend or sub-trends using nonparametric cumulative rank difference (CRD) was proposed. To confirm the significance of the visualized trend, the CRD was translated from the graphical to a statistical metric. To assess its capability, the performance of the CRD method was compared with that of the well-known Mann–Kendall (MK) test. The graphical and statistical CRD techniques were applied to detect trends and sub-trends in the annual rainfall of 10 River Nile riparian countries (RNRCs). The co-occurrence of the trend evolutions in the rainfall with those of the large-scale ocean–atmosphere interactions was analyzed. The power of the CRD method was shown to closely agree with that of the MK test under the various circumstances of sample sizes, variations, linear trend slopes, and serial correlations. At the level of significance α = 5 %, the long-term trends were found present in 30 % of the RNRCs. However at α = 5 %, the main downward (upward) sub-trends were found significant in 30 (60 %) of the RNRCs. Generally at α = 1 %, linkages of the trend evolutions in the rainfall of the RNRCs were found to those of the influences from the Atlantic and Indian Oceans. At α = 5 %, influences from the Pacific Ocean on the rainfall trends of some countries were also evident.  相似文献   

10.
Conventional geostatistics often relies on the assumption of second order stationarity of the random function (RF). Generally, local means and local variances of the random variables (RVs) are assumed to be constant throughout the domain. Large scale differences in the local means and local variances of the RVs are referred to as trends. Two problems of building geostatistical models in presence of mean trends are: (1) inflation of the conditional variances and (2) the spatial continuity is exaggerated. Variance trends on the other hand cause conditional variances to be over-estimated in certain regions of the domain and under-estimated in other areas. In both cases the uncertainty characterized by the geostatistical model is improperly assessed. This paper proposes a new approach to identify the presence and contribution of mean and variance trends in the domain via calculation of the experimental semivariogram. The traditional experimental semivariogram expression is decomposed into three components: (1) the mean trend, (2) the variance trend and (3) the stationary component. Under stationary conditions, both the mean and the variance trend components should be close to zero. This proposed approach is intended to be used in the early stages of data analysis when domains are being defined or to verify the impact of detrending techniques in the conditioning dataset for validating domains. This approach determines the source of a trend, thereby facilitating the choice of a suitable detrending method for effective resource modeling.  相似文献   

11.
Detrending is a key step in the study of the scaling behaviors using Detrended Fluctuation Analysis (DFA) to explore the long‐range correlation of hydrological series. However, the irregular periodicity and various trends within hydrological series as a result of integrated influences of human activities such as construction of water reservoirs and human withdrawal of freshwater and climate changes such as alterations of precipitation changes in both space and time make difficult the selection of detrending methods. In this study, we attempt to address the detrending problem due to the important theoretical and practical merits of detrending in DFA‐based scaling analysis. In this case, with focus on the irregularity of the periodic trends, a modified DFA, varying parameter DFA (VPDFA), and its combination with adaptive detrending algorithm (ADA) are employed to eliminate the influences of irregular cycles on DFA‐based scaling results. The results indicate that, for streamflow series with no more than 20 cycles, VPDFA is recommended; otherwise, the combined method has to be employed. Comparison study indicates that the scaling behavior of the detrended observed streamflow series by average removed method, when compared to those by DFA, VPDFA, and ADA, is the one of the periodic residues around the averaged annual cycle for the entire series rather than that excluding all annual cycles. However, although the result by VPDFA for short observed streamflow record can well correspond to that for numerically simulated series, the scaling behavior obtained by combined method analyzing long record looks strange and is different from that by numerical analysis. We attribute this difference to the complicated hydrological structure and the possible hydrological alternation due to the increasing integrated impacts of human activities and human activities with the extending record. How to include the most of the important factors into the detrending procedure is still a challenging task for further study in the analysis of the scaling behavior of hydrological processes. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

12.
Based on the hydrologic and meteorological data in the Yarkand River Basin during 1957–2008, the nonlinear hydro-climatic process was analyzed by a comprehensive method, including the Mann–Kendall trend test, wavelet analysis, wavelet regression analysis and correlation dimension. The main findings are as following: (1) The annual runoff, annual average temperature and annual precipitation showed an increasing trend during the period of 1957–2008, and the average increase extent in runoff, temperature and precipitation was 2.234 × 108 m3/10 year, 0.223 °C/10 year, and 4.453 mm/10 year, respectively. (2) The nonlinear pattern of runoff, temperature and precipitation was scale-dependent with time. In other words, the annual runoff, annual average temperature and annual precipitation at five time scales resulted in five patterns of nonlinear variations respectively. (3) Although annual runoff, annual average temperature and annual precipitation presented nonlinear variations at different time scales, the runoff has a linear correlation with the temperature and precipitation. (4) The hydro-climatic process of the Yarkand River is chaotic dynamic system, in which the correlation dimension of annual runoff, annual average temperature and annual precipitation is 3.2118, 2.999 and 2.992 respectively. None of the correlation dimensions is an integer, and it indicates that the hydro-climatic process has the fractal characteristics.  相似文献   

13.
Abstract

Field observations and geodetic measurements suggest that in the Karakoram Mountains, glaciers are either stable or have expanded since 1990, in sharp contrast to glacier retreats that are prevalently observed in the Himalayas and adjoining high-altitude terrains of central Asia. Decreased discharge in the rivers originating from this region is cited as a supporting evidence for this somewhat anomalous phenomenon. Here, we show that river discharge during the melting season of the glaciers in the eastern and western Karakoram, respectively, exhibits rising and falling trends. We have implemented a statistical procedure involving non-parametric tests combined with a benchmark smoothing technique that has proven to be a powerful method for separating the stochastic component from the trend component in a time series. Precipitation patterns determined from ERA-40 and GPCP data indicate that summer-monsoonal precipitation has increased over the Karakoram Mountains in recent decades. Increasing flows in June and July in the eastern Karakoram are due to an increase in summer-monsoonal precipitation. The rising trend of August discharge is due to an increase in the loss of glacier storage at an approximate average rate of 0.186–0.217 mm d-1 year-1 during the period 1973–2010. Moreover, this rate is higher than the rate of increase in monsoonal snowfall during the months of August and September. Therefore, most plausibly, glacier mass balance in the eastern Karakoram is negative. In the western Karakoram, river flows show declining trends for all summer months for the period 1966–2010, corresponding to a rate of increase of glacier storage by approximately 0.552–0.644 mm d-1 year-1, which is also higher than the rate of increase in summer-monsoonal precipitation. The gain of the cryospheric mass in the western Karakoram is in the form of increased thickness of the glaciers and perennial snowpacks instead of areal expansion. This investigation shows two contrasting patterns of trends of river flows that signify both negative and positive mass balance of the Karakoram glaciers. Trends of river flows are spatially and temporally integrated responses of a watershed to changing climate and thereby are important signals of the conditions of the cryospheric component of a watershed where it is highly significant. However, they cannot unequivocally provide indications of the state and fate of the glaciers in the complex hydrometeorological setting of the Karakoram. Extreme caution and care must be exercised in interpreting trends of river discharge in conjunction with climatic data.  相似文献   

14.
ABSTRACT

This study analysed long-term rainfall data (1851–2006) over seven climatic zones of India at seasonal and annual scales based on three techniques: (i) linear regression, (ii) multifractal detrended fluctuation analysis (MFDFA) and (iii) Bayesian algorithm. The linear regression technique was used for trend analysis of short-term (30 years) and long-term (156 years) rainfall data. The MFDFA revealed small- and large-scale fluctuations, whereas the Bayesian algorithm helped in quantifying the uncertainty in break-point detection from the rainfall time series. Major break points years identified through Bayesian algorithm were 1888, 1904 and 1976. The MFDFA technique identified that high fluctuation years were between 1871–1890, 1891–1910 and 1951–1970. Linear regression-based analysis revealed 1881–1910 and 1971–2006 as break-point periods in the North Mountainous Indian region. A similar analysis was carried out for India as a whole, as well as its seven climatic zones.  相似文献   

15.
This paper addresses the role of meteorological forcing on mean sea level (MSL) variability at the tide gauge of Cuxhaven over a period from 1871 to 2008. It is found that seasonal sea level differs significantly from annual means in both variability and trends. The causes for the observed differences are investigated by comparing to changes in wind stress, sea level pressure and precipitation. Stepwise regression is used to estimate the contribution of the different forcing factors to sea level variability. The model validation and sensitivity analyses showed that a robust and timely independent estimation of regression coefficients becomes possible if at least 60 to 80 years of data are available. Depending on the season, the models are able to explain between 54 % (spring, April to June) and 90 % (winter, January to March) of the observed variability. Most parts of the observed variability are attributed to changes in zonal wind stress, whereby the contribution of sea level pressure, precipitation and meridional wind stress is rather small but still significant. On decadal timescales, the explanatory power of local meteorological forcing is considerable weaker, suggesting that the remaining variability is attributed to remote forcing over the North Atlantic. Although meteorological forcing contributes to linear trends in some sub-periods of seasonal time series, the annual long-term trend is less affected. However, the uncertainties of trend estimation can be considerably reduced, when removing the meteorological influences. A standard error smaller than 0.5 mm/year requires 55 years of data when using observed MSL at Cuxhaven tide gauge. In contrast, a similar standard error in the meteorologically corrected residuals is reached after 32 years.  相似文献   

16.
Climate change analysis is essential, considering the numerous economic and ecological implications of this critical global environmental issue. This paper analyzes the spatial and temporal trends of mean air temperature in Romania’s most important agricultural area, the south and south-eastern region, between 1961 and 2009. In this respect, multiannual (the entire period) and multidecadal (1961–1990, 1971–2000, 1981–2009) trends were analyzed using the Mann–Kendall test and Sen’s slope method at 23 weather stations, annually, seasonally and for the growing season of the region’s main agricultural crops (maize and wheat). Multiannually, the results showed statistically significant temperature increases, on all temporal scales (maximum rate of 0.06 °C/year recorded in summer, equivalent to a net temperature rise of 2.82 °C), except for the autumn season (cooling without statistical significance). Multidecadally, the 1961–1990 period is marked by a general cooling, especially in autumn (maximum values of ?0.07 °C/year or over 2 °C net cooling). In the 1971–2000 and 1981–2009 periods, a general warming was observed (maximum in summer for both multidecades, when positive rates peaked at 0.09 °C/year, or 2.5–3 °C net warming), but the warming of the last three decades is the most prominent in terms of spatial average magnitude and trend significance. Upon analysis of the impact of climate warming on agricultural yields (maize) through linear regression, in the 1991–2000 decade, considered as case study, it was found that in 32 % of the total analyzed area there are evident relationships between the two variables (p value <0.05). In this case, a dependency of 33–50 % (40 %, on average) of maize to climate was found, and a sensitivity (loss) ranging between 0.9 and 1.5 t/ha/year (1.2 t/ha/year, on average) for a 1 °C temperature rise. At the same time, significant losses (of up to 1.7 t/ha/year) of maize for a 1 °C temperature rise were identified in 51 % of the area, but with little p value significance (between 0.05 and 0.1). It is however necessary to analyse the agro-climatic results cautiously, considering that only one decade of climate-agriculture relationship was studied. The results can be useful first and foremost for mitigating the climate change impact on agricultural systems, by prioritizing future adaptation strategies enforced by policy makers.  相似文献   

17.
Abstract

The process-based Soil and Water Assessment Tool (SWAT) model and the data-driven radial basis neural network (RBNN) model were evaluated for simulating sediment load for the Nagwa watershed in Jharkhand, India, where soil erosion is a severe problem. The SWAT model calibration and uncertainty analysis were performed with the Sequential Uncertainty Fitting algorithm version 2 and the bootstrap technique was applied on the RBNN model to analyse uncertainty in model output. The percentage of data bracketed by the 95% prediction uncertainty (95PPU) and the r factor were the two measures used to assess the goodness of calibration. Comparison of the results of the two models shows that the value of r factor (r = 0.41) in the RBNN model is less than that of SWAT model (r = 0.79), which means there is a wider prediction interval for the SWAT model results. More values of observed sediment yield were bracketed by the 95PPU in the RBNN model. Thus, the RBNN model estimates the sediment yield values more accurately and with less uncertainty.

Editor D. Koutsoyiannis; Associate editor H. Aksoy

Citation Singh, A., Imtiyaz, M., Isaac, R.K., and Denis, D.M., 2014. Assessing the performance and uncertainty analysis of the SWAT and RBNN models for simulation of sediment yield in the Nagwa watershed, India. Hydrological Sciences Journal, 59 (2), 351–364.  相似文献   

18.
ABSTRACT

This paper presents an analysis of trends in six drought variables at 566 stations across India over the period 1901–2002. Six drought variables were computed using standardized precipitation index (SPI). The Mann-Kendall (MK) trend test and Sen’s slope estimator were used for trend analysis of drought variables. Discrete wavelet transform (DWT) was used to identify the dominant periodic components in trends, whereas the significance of periodic components was examined using continuous wavelet transform (CWT) based global wavelet spectrum (GWS). Our results show an increasing trend in droughts in eastern, northeastern and extreme southern regions, and a decreasing trend in the northern and southern regions of the country. The periodic component influencing the trend was 2–4 years in south, 4–8 years in west, east and northeast, 8–64 years in central parts and 32–128 years in the north; however, most of the periodic components were not statistically significant.  相似文献   

19.
Climate change significantly impact on agriculture in recent year, the accurate estimation of crop yield is of great importance for the food security. In this study, a process-based mechanism model was modified to estimate yield of C4 crop by modifying the carbon metabolic pathway in the photosynthesis sub-module of the RS–P–YEC (Remote-Sensing–Photosynthesis–Yield estimation for Crops) model. The yield was calculated by multiplying net primary productivity (NPP) and the harvest index (HI) derived from the ratio of grain to stalk yield. The modified RS–P–YEC model was used to simulate maize yield in the Northeast China Plain during the period 2002–2011. The 111 statistical data of maize yield from study area was used to validate the simulated results at county-level. The results showed that the Pearson correlation coefficient (R) was 0.827 (p < 0.01) between the simulated yield and the statistical data, and the root mean square error (RMSE) was 712 kg/ha with a relative error (RE) of 9.3%. From 2002 to 2011, the yield of maize planting zone in the Northeast China Plain was increasing with smaller coefficient of variation (CV). The spatial pattern of simulated maize yield was consistent with the actual distribution in the Northeast China Plain, with an increasing trend from the northeast to the southwest. Hence the results demonstrated that the modified process-based model coupled with remote sensing data was suitable for yield prediction of maize in the Northeast China Plain at the spatial scale.  相似文献   

20.
Various types of neural networks have been proposed in previous papers for applications in hydrological events. However, most of these applied neural networks are classified as static neural networks, which are based on batch processes that update action only after the whole training data set has been presented. The time variate characteristics in hydrological processes have not been modelled well. In this paper, we present an alternative approach using an artificial neural network, termed real‐time recurrent learning (RTRL) for stream‐flow forecasting. To define the properties of the RTRL algorithm, we first compare the predictive ability of RTRL with least‐square estimated autoregressive integrated moving average models on several synthetic time‐series. Our results demonstrate that the RTRL network has a learning capacity with high efficiency and is an adequate model for time‐series prediction. We also investigated the RTRL network by using the rainfall–runoff data of the Da‐Chia River in Taiwan. The results show that RTRL can be applied with high accuracy to the study of real‐time stream‐flow forecasting networks. Copyright © 2002 John Wiley & Sons, Ltd.  相似文献   

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