A multimodel assessment of the climate change effect on the drought severity–duration–frequency relationship     

Joo Heon Lee  Chang Joo Kim 《水文研究》2013,27(19):2800-2813

In this study, the patterns of past and future drought occurrences in the Seoul region were analysed using observed historical data from the Seoul weather station located in the Korean Peninsula and four different types of general circulation models (GCMs), namely, GFDL:CM2_1, CONS:ECHO‐G, MRI:CGCM2_3_2 and UKMO:HADGEM1. To analyse statistical properties such as drought frequency duration and return period, the Standardized Precipitation Index was used to derive the severity–duration–frequency (SDF) curve from the drought frequency analysis. In addition, a drought spell analysis was conducted to estimate the frequency and change of drought duration for each drought classification. The results of the analysis suggested a decrease in the frequency of mild droughts and an increase in the frequency of severe and extreme droughts in the future. Furthermore, the average duration of droughts is expected to increase. A comparison of the SDF relationship derived from the observed data with that derived via the GCMs indicated that the drought severity for each return period was reduced as drought duration increased and that the drought severity derived from the GCMs was severer than the severity obtained using the observed data for the same duration and return period. Furthermore, among the four types of GCMs used in this study, the MRI model predicted the most severe future drought for the Seoul region, and the SDF curve derived using the MRI model also resulted in the highest degree of drought severity compared with the other GCMs. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

Intelligent control for modeling of real‐time reservoir operation,part II: artificial neural network with operating rule curves     

Ya‐Ting Chang  Li‐Chiu Chang  Fi‐John Chang 《水文研究》2005,19(7):1431-1444

To bridge the gap between academic research and actual operation, we propose an intelligent control system for reservoir operation. The methodology includes two major processes, the knowledge acquired and implemented, and the inference system. In this study, a genetic algorithm (GA) and a fuzzy rule base (FRB) are used to extract knowledge based on the historical inflow data with a design objective function and on the operating rule curves respectively. The adaptive network‐based fuzzy inference system (ANFIS) is then used to implement the knowledge, to create the fuzzy inference system, and then to estimate the optimal reservoir operation. To investigate its applicability and practicability, the Shihmen reservoir, Taiwan, is used as a case study. For the purpose of comparison, a simulation of the currently used M‐5 operating rule curve is also performed. The results demonstrate that (1) the GA is an efficient way to search the optimal input–output patterns, (2) the FRB can extract the knowledge from the operating rule curves, and (3) the ANFIS models built on different types of knowledge can produce much better performance than the traditional M‐5 curves in real‐time reservoir operation. Moreover, we show that the model can be more intelligent for reservoir operation if more information (or knowledge) is involved. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

Using a maximum entropy model to optimize the stochastic component of urban cellular automata models   总被引：1，自引：0，他引：1  

Haijun Wang  Chang Xia  Sanwei He  Wenting Zhang 《International journal of geographical information science》2020,34(5):924-946

ABSTRACT

The stochastic perturbation of urban cellular automata (CA) model is difficult to fine-tune and does not take the constraint of known factors into account when using a stochastic variable, and the simulation results can be quite different when using the Monte Carlo method, reducing the accuracy of the simulated results. Therefore, in this paper, we optimize the stochastic component of an urban CA model by the use of a maximum entropy model to differentially control the intensity of the stochastic perturbation in the spatial domain. We use the kappa coefficient, figure of merit, and landscape metrics to evaluate the accuracy of the simulated results. Through the experimental results obtained for Wuhan, China, the effectiveness of the optimization is proved. The results show that, after the optimization, the kappa coefficient and figure of merit of the simulated results are significantly improved when using the stochastic variable, slightly improved when using Monte Carlo methods. The landscape metrics for the simulated results and actual data are much closer when using the stochastic variable, and slightly closer when using the Monte Carlo method, but the difference between the simulated results is narrowed, reflecting the fact that the results are more reliable.  相似文献   

Transport and retention of Escherichia coli in a mixture of quartz,Al‐coated and Fe‐coated sands     

Song‐Bae Kim  Seong‐Jik Park  Chang‐Gu Lee  Hyon‐Chong Kim 《水文研究》2008,22(18):3856-3863

Transport and retention of Escherichia coli through the mixture of quartz, Al‐coated and Fe‐coated sands was examined using column experiments to investigate the effect of geochemical heterogeneity on bacteria transport. The first set of the experiments was performed in quartz, Al‐coated and Fe‐coated sand mixtures (coated sand: 0, 5, 10, 25, 50, 100%) to examine the influence of positively‐charged sand grains on bacteria transport. The second experiments were carried out to observe the impact of pH (range 6·74–8·21) on bacteria transport in the mixture of quartz 50% and Fe‐coated sand 50%. The third experiments were conducted to analyse the effect of ionic strength (0, 50, 100, 200 mM) on bacteria transport in the mixture of quartz 50% and Al‐coated sand 50%. The first experiments show that bacterial mass recoveries were in the range of 3·6–43·4%, decreasing nonlinearly as the content of Al‐ and Fe‐coated sands increased. In the second experiments, the bacterial mass recoveries were in the range of 35·5–79·2%, increasing linearly as the solution pH increased. In the third experiments, the mass recovery was 3·4% at 0 mM. As the ionic strength increased to 50mM, the mass recovery decreased to 0%. When the ionic strength increased further to 100 and 200 mM, no bacterial mass was recovered as in the case of 50 mM. It indicates that in the mixed medium of quartz 50% and Al‐coated sand 50% both positive (increment of bacterial adhesion) and negative (decrement) effects of ionic strength may be counterbalanced, minimizing the impact of ionic strength on the bacterial adhesion. This study helps to understand the role of metal oxides and solution chemistry in the transport of bacteria in geochemically heterogeneous media Copyright © 2008 John Wiley & Sons, Ltd.  相似文献   

The effects of slope shape and polyacrylamide application on runoff,erosion and nutrient loss from hillslopes under simulated rainfall     

Chang Ao  Wenzhi Zeng  Peiling Yang  Weimin Xing  Guoqing Lei  Jingwei Wu  Jiesheng Huang 《水文研究》2021,35(4):e14130

Natural hillslopes are mostly composed of complex slope shapes, which significantly affect soil erosion. However, existing studies have mainly focused on uniform slopes to simplify complex hillslopes, and the mechanisms responsible for the influence of slope shape on soil and nutrient losses are still not well understood, especially in the application of soil improvers to reduce soil loss. To investigate the effects of slope shape and polyacrylamide (PAM) application on runoff, soil erosion and nutrient loss, this study conducted artificial field rainfall experiments involving two PAM application rates and nine slope shapes. The results indicate that the average amount of soil loss from convex slopes was 1.5 and 1.3 times greater than that from concave and uniform slopes, respectively, and the average amount of ammonia nitrogen loss and phosphate loss increased by 24.0%–58.6%. Soil and nutrient losses increased as the convexity of the convex slopes increased. For runoff, there was little difference between concave and convex slopes, but the runoff amount for both slopes was greater than that for uniform slopes. After PAM application, the soil loss decreased by more than 90%, and the nutrient loss decreased by 28.2%–68.1%. The application of PAM was most effective in reducing soil erosion and nutrient loss from convex slopes, and it is recommended to appropriately increase the PAM application rate for convex slopes. A strong linear relationship between ammonia nitrogen and phosphate concentrations and sediment concentrations was found in the runoff on slopes with no PAM application. However, this linear relationship weakened for slopes with PAM application. The findings of this study may be valuable for optimizing nonpoint source pollution management in basins.  相似文献   

The Kings River Experimental Watersheds: Infrastructure and data     

Joseph W. Wagenbrenner  David N. Dralle  Mohammad Safeeq  Carolyn T. Hunsaker 《水文研究》2021,35(5):e14142

The Kings River Experimental Watersheds (KREW) were established in 2002 to expand our knowledge of catchment physical, chemical, and biological processes in Sierra Nevada headwater forests, and to better understand the impacts of prescribed burning and forest thinning on these processes. Two elevation strata (high and low) were selected for the KREW sites, with four independent catchments and one nested catchment within each stratum. Both high and low elevation study areas were instrumented for continuous measurements of meteorology, streamflow, and turbidity. Atmospheric and stream chemistry, suspended sediment concentration, and bedload sediment delivery were measured on a regular schedule. Soil chemical and physical properties and vegetation were systematically sampled before and after the initial thinning and prescribed burning treatments, which were implemented between 2012 and 2016. Post-treatment data collection continues today as we explore opportunities for the second round of possible treatments. The critical research infrastructure and long-term baseline data collection has been instrumental in building partnerships with downstream managers, end users, non-governmental organizations, academic researchers, and national research programmes. Contributions to date include fundamental understanding of magnitude and variability of nutrient deposition; carbon, nutrient, and major ion dynamics in headwater streams; aquatic algae and macroinvertebrate populations; vegetation composition and structure; and streamflow responses to precipitation in the two elevation strata. Data from the experimental watersheds also support calibration and validation of diverse hydrologic models used for water resources planning.  相似文献   

Tropical Pacific response to continental ice sheet topography     

Shih-Yu Lee  John C. H. Chiang  Ping Chang 《Climate Dynamics》2015,44(9-10):2429-2446

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Using vulnerability indicators to develop resilience networks: a similarity approach     

Stephanie E. Chang  Jackie Z. K. Yip  Shona L. van Zijll de Jong  Rebecca Chaster  Ashley Lowcock 《Natural Hazards》2015,78(3):1827-1841

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Improving soil moisture accounting and streamflow prediction in SWAT by incorporating a modified time‐dependent Curve Number method          下载免费PDF全文

Mohammad Adnan Rajib  Venkatesh Merwade 《水文研究》2016,30(4):603-624

The objective of this study is to incorporate a time‐dependent Soil Moisture Accounting (SMA) based Curve Number method (SMA_CN) in Soil and Water Assessment Tool (SWAT) and compare its performance with the existing CN method in SWAT by simulating the hydrology of two agricultural watersheds in Indiana, USA. Results show that fusion of the SMA_CN method causes decrease in runoff volume and increase in profile soil moisture content, associated with larger groundwater contribution to the streamflow. In addition, the higher amount of moisture in the soil profile slightly elevates the actual evapotranspiration. The SMA‐based SWAT configuration consistently produces improved goodness‐of‐fit scores and less uncertain outputs with respect to streamflow during both calibration and validation. The SMA_CN method exhibits a better match with the observed data for all flow regimes, thereby addressing issues related to peak and low flow predictions by SWAT in many past studies. Comparison of the calibrated model outputs with field‐scale soil moisture observations reveals that the SMA overhauling enables SWAT to represent soil moisture condition more accurately, with better response to the incident rainfall dynamics. While the results from the modification of the CN method in SWAT are promising, more studies including watersheds with various physical and climatic settings are needed to validate the proposed approach. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

Landslide susceptibility zonation using statistical and machine learning approaches in Northern Lecco,Italy     

Mehrabi  Mohammad 《Natural Hazards》2022,111(1):901-937

This study deals with landslide susceptibility mapping in the northern part of Lecco Province, Lombardy Region, Italy. In so doing, a valid landslide inventory map and thirteen predisposing factors (including elevation, slope aspect, slope degree, plan curvature, profile curvature, distance to waterway, distance to road, distance to fault, soil type, land use, lithology, stream power index, and topographic wetness index) form the spatial database within geographic information system. The used predictive models comprise a bivariate statistical approach called frequency ratio (FR) and two machine learning tools, namely multilayer perceptron neural network (MLPNN) and adaptive neuro-fuzzy inference system (ANFIS). These models first use landslide and non-landslide records for comprehending the relationship between the landslide occurrence and predisposing factors. Then, landslide susceptibility values are predicted for the whole area. The accuracy of the produced susceptibility maps is measured using area under the curve (AUC) index, according to which, the MLPNN (AUC?=?0.916) presented the most accurate map, followed by the ANFIS (AUC?=?0.889) and FR (AUC?=?0.888). Visual interpretation of the susceptibility maps, FR-based correlation analysis, as well as the importance assessment of predisposing factors, all indicated the significant contribution of the road networks to the crucial susceptibility of landslide. Lastly, an explicit predictive formula is extracted from the implemented MLPNN model for a convenient approximation of landslide susceptibility value.

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