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Spatial patterns in thunderstorm rainfall events and their coupling with watershed hydrological response 总被引：1，自引：0，他引：1
Efrat Morin David C. Goodrich Robert A. Maddox Xiaogang Gao Hoshin V. Gupta Soroosh Sorooshian 《Advances in water resources》2006
Weather radar systems provide detailed information on spatial rainfall patterns known to play a significant role in runoff generation processes. In the current study, we present an innovative approach to exploit spatial rainfall information of air mass thunderstorms and link it with a watershed hydrological model. Observed radar data are decomposed into sets of rain cells conceptualized as circular Gaussian elements and the associated rain cell parameters, namely, location, maximal intensity and decay factor, are input into a hydrological model. Rain cells were retrieved from radar data for several thunderstorms over southern Arizona. Spatial characteristics of the resulting rain fields were evaluated using data from a dense rain gauge network. For an extreme case study in a semi-arid watershed, rain cells were derived and fed as input into a hydrological model to compute runoff response. A major factor in this event was found to be a single intense rain cell (out of the five cells decomposed from the storm). The path of this cell near watershed tributaries and toward the outlet enhanced generation of high flow. Furthermore, sensitivity analysis to cell characteristics indicated that peak discharge could be a factor of two higher if the cell was initiated just a few kilometers aside. 相似文献
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Precipitation is a key input variable for hydrological and climate studies. Rain gauges can provide reliable precipitation measurements at a point of observations. However, the uncertainty of rain measurements increases when a rain gauge network is sparse. Satellite-based precipitation estimations SPEs appear to be an alternative source of measurements for regions with limited rain gauges. However, the systematic bias from satellite precipitation estimation should be estimated and adjusted. In this study, a method of removing the bias from the precipitation estimation from remotely sensed information using artificial neural networks-cloud classification system (PERSIANN-CCS) over a region where the rain gauge is sparse is investigated. The method consists of monthly empirical quantile mapping of gauge and satellite measurements over several climate zones as well as inverse-weighted distance for the interpolation of gauge measurements. Seven years (2010–2016) of daily precipitation estimation from PERSIANN-CCS was used to test and adjust the bias of estimation over Saudi Arabia. The first 6 years (2010–2015) are used for calibration, while 1 year (2016) is used for validation. The results show that the mean yearly bias is reduced by 90%, and the yearly root mean square error is reduced by 68% during the validation year. The experimental results confirm that the proposed method can effectively adjust the bias of satellite-based precipitation estimations. 相似文献
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Pari-Sima?Katiraie-BoroujerdyEmail author Hamed?Ashouri Kuo-lin?Hsu Soroosh?Sorooshian 《Theoretical and Applied Climatology》2017,130(1-2):249-260
In this study, satellite-based daily precipitation estimation data from precipitation estimation from remotely sensed information using artificial neural networks (PERSIANN)-climate data record (CDR) are being evaluated in Iran. This dataset (0.25°, daily), which covers over three decades of continuous observation beginning in 1983, is evaluated using rain-gauge data for the period of 1998–2007. In addition to categorical statistics and mean annual amount and number of rainy days, ten standard extreme indices were calculated to observe the behavior of daily extremes. The results show that PERSIANN-CDR exhibits reasonable performance associated with the probability of detection and false-alarm ratio, but it overestimates precipitation in the area. Although PERSIANN-CDR mostly underestimates extreme indices, it shows relatively high correlations (between 0.6316–0.7797) for intensity indices. PERSIANN-CDR data are also used to calculate the trend in annual amounts of precipitation, the number of rainy days, and precipitation extremes over Iran covering the period of 1983–2012. Our analysis shows that, although annual precipitation decreased in the western and eastern regions of Iran, the annual number of rainy days increased in the northern and northwestern areas. Statistically significant negative trends are identified in the 90th percentile daily precipitation, as well as the mean daily precipitation from wet days in the northern part of the study area. The positive trends of the maximum annual number of consecutive dry days in the eastern regions indicate that the dry periods became longer in these arid areas. 相似文献
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Yen-Ming Chiang Kuo-Lin Hsu Fi-John Chang Yang Hong Soroosh Sorooshian 《Journal of Hydrology》2007,340(3-4):183-196
We investigated the effectiveness of combining gauge observations and satellite-derived precipitation on flood forecasting. Two data merging processes were proposed: the first one assumes that the individual precipitation measurement is non-bias, while the second process assumes that each precipitation source is biased and both weighting factor and bias parameters are to be calculated. Best weighting factors as well as the bias parameters were calculated by minimizing the error of hourly runoff prediction over Wu-Tu watershed in Taiwan. To simulate the hydrologic response from various sources of rainfall sequences, in our experiment, a recurrent neural network (RNN) model was used.
The results demonstrate that the merged method used in this study can efficiently combine the information from both rainfall sources to improve the accuracy of flood forecasting during typhoon periods. The contribution of satellite-based rainfall, being represented by the weighting factor, to the merging product, however, is highly related to the effectiveness of ground-based rainfall observation provided gauged. As the number of gauge observations in the basin is increased, the effectiveness of satellite-based observation to the merged rainfall is reduced. This is because the gauge measurements provide sufficient information for flood forecasting; as a result the improvements added on satellite-based rainfall are limited. This study provides a potential advantage for extending satellite-derived precipitation to those watersheds where gauge observations are limited. 相似文献
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Sajjad Abbasi Behnam Keshavarzi Farid Moore Hossein Delshab Naghmeh Soltani Armin Sorooshian 《Environmental Earth Sciences》2017,76(23):798
This study aimed to (1) investigate microrubbers (MRs) for the first time and identify microplastics (MPs) in street dust, (2) determine the physicochemical and mineralogical characteristics and morphology of dust particles, (3) understand the concentration and the possible source(s) of heavy metals/metalloids, (4) identify the chemical speciation and mobility potential of trace metals in urban street dusts, and (5) determine adverse health effects of street dust on children and adults living in the city of Bushehr in southwestern Iran. Generally, twenty four street dust samples were collected and analyzed. Calculated enrichment factors indicate high levels of contamination. Statistical analysis reveals that the two main sources of trace elements include road traffic emissions (Cu, Zn, Sb, Hg, Pb, Mo) and re-suspended soil particles (Al, Mn, Ni, Ti, Cd, Co). BCR sequential extraction results indicated that As, Zn, Cu, and Pb mainly occur in the exchangeable fraction and hence are highly bioavailable. X-ray powder diffraction analysis revealed the presence of calcite, dolomite, quartz, and magnetite. The size distribution of dust particles was also investigated using a scanning electron microscope (SEM), while elemental distribution was analyzed using an attached energy dispersive X-ray spectrometer (SEM–EDS) unit. Dust particles from heavy traffic areas are much finer compared with other investigated areas. MPs and MRs, mostly fibers and fragments, were detected in all samples [ranging from 210 to 1658 (MPs) and 44 to 782 (MRs) items/10 g dust] using fluorescence microscopy. The hazard index for As is higher than 10?4 for children and adults indicative of high risk. According to the calculated potential ecological risk index, Hg indicated moderate ecological risk in the street dust of the study area. 相似文献
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Operational snow modeling: Addressing the challenges of an energy balance model for National Weather Service forecasts 总被引：1，自引：0，他引：1
Prediction of snowmelt has become a critical issue in much of the western United States given the increasing demand for water supply, changing snow cover patterns, and the subsequent requirement of optimal reservoir operation. The increasing importance of hydrologic predictions necessitates that traditional forecasting systems be re-evaluated periodically to assure continued evolution of the operational systems given scientific advancements in hydrology. The National Weather Service (NWS) SNOW17, a conceptually based model used for operational prediction of snowmelt, has been relatively unchanged for decades. In this study, the Snow–Atmosphere–Soil Transfer (SAST) model, which employs the energy balance method, is evaluated against the SNOW17 for the simulation of seasonal snowpack (both accumulation and melt) and basin discharge. We investigate model performance over a 13-year period using data from two basins within the Reynolds Creek Experimental Watershed located in southwestern Idaho. Both models are coupled to the NWS runoff model [SACramento Soil Moisture Accounting model (SACSMA)] to simulate basin streamflow. Results indicate that while in many years simulated snowpack and streamflow are similar between the two modeling systems, the SAST more often overestimates SWE during the spring due to a lack of mid-winter melt in the model. The SAST also had more rapid spring melt rates than the SNOW17, leading to larger errors in the timing and amount of discharge on average. In general, the simpler SNOW17 performed consistently well, and in several years, better than, the SAST model. Input requirements and related uncertainties, and to a lesser extent calibration, are likely to be primary factors affecting the implementation of an energy balance model in operational streamflow prediction. 相似文献
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Numerical modeling of free-surface flow over a mobile bed with predominantly bedload sediment transport can be done by solving the shallow water and Exner equations using coupled and splitting approaches.The coupled method uses a coupling of the governing equations at the same time step leading to a non-conservative solution.The splitting method solves the Exner and the shallow water equations in a separate manner,and is only capable of modeling weak free-surface and bedload interactions.In the current study,an extended version of a Godunov-type wave propagation algorithm is presented for modeling of morphodynamic systems using both coupled and splitting approaches.In the introduced coupled method the entire morphodynamic system is solved in the form of a conservation law.For the splitting technique,a new wave Riemann decomposition is defined which enables the scheme to be utilized for mild and strong interactions.To consider the bedload sediment discharge within the Exner equation,the Smart and Meyer-Peter&Müller formulae are used.It was found that the coupled solution gives accurate predictions for all investigated flow regimes including propagation over a dry-state using a Courant-Friedrichs-Lewy(CFL)number equal to 0.6.Furthermore,the splitting method was able to model all flow regimes with a lower CFL number of 0.3. 相似文献