Capabilities of satellite precipitation datasets to estimate heavy precipitation rates at different temporal accumulations          下载免费PDF全文

Ali Mehran  Amir AghaKouchak 《水文研究》2014,28(4):2262-2270

The importance of satellite datasets as alternative sources of precipitation information has been argued in numerous studies. Future developments in satellite precipitation algorithms as well as utilization of satellite data in operational applications rely on a more in‐depth understanding of satellite errors and biases across different spatial and temporal scales. This paper investigates the capability of satellite precipitation data sets with respect to detecting heavy precipitation rates over different temporal accumulations. In this study, the performance of Tropical Rainfall Measuring Mission real time (TRMM‐RT), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks and CPC MORPHing (CMORPH) is compared against radar‐based gauge‐adjusted Stage IV data. The results show that none of the high temporal resolution (3‐h) datasets are ideal for detecting heavy precipitation rates. In fact, the detection skill of all products drops as the precipitation thresholds (i.e. 75 and 90 percentiles) increase. At higher temporal accumulations (6, 12 and 24 h), the detection skill improves for all precipitation products, with CMORPH showing a better detection skill compared to all other products. On the other hand, all precipitation products exhibit high false alarm ratios above the heavy precipitation thresholds, although TRMM‐RT lead to a relatively smaller level of false alarms. These results indicate that further efforts are necessary to improve the precipitation algorithms so that they can capture heavy precipitation rates more reliably. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

Evaluation and hydrologic validation of TMPA satellite precipitation product downstream of the Pearl River Basin,China   总被引：1，自引：0，他引：1       下载免费PDF全文

Zhaoli Wang  Ruida Zhong  Chengguang Lai 《水文研究》2017,31(23):4169-4182

With high spatio‐temporal resolution and wide coverage, satellite‐based precipitation products can potentially fill the deficiencies of traditional in situ gauge precipitation observations and provide an alternative data source for ungauged areas. However, due to the relatively poor accuracy and high uncertainty of satellite‐based precipitation products, it remains necessary to assess the quality and applicability of the products for each investigated area. This study evaluated the accuracy and error of the latest Tropical Rainfall Measuring Mission Multi‐satellites Precipitation Analysis 3B42‐V7 satellite‐based precipitation product and validated the applicability of the product for the Beijiang and Dongjiang River Basins, downstream of the Pearl River Basin in China. The study first evaluated the accuracy, error, and bias of the 3B42‐V7 product during 1998–2006 at daily and monthly scale via comparison with in situ observations. The study further validated the applicability of the product via hydrologic simulation using the variable infiltration capacity hydrological model for three hydrological stations in the Beijiang River Basin, considering two scenarios: a streamflow simulation with gauge‐calibrated parameters (Scenario I) and a simulation after recalibration with the 3B42‐V7 product (Scenario II). The results revealed that (a) the 3B42‐V7 product produced acceptable accuracy both at the daily scale and high accuracy at the monthly scale while generally tending to overestimate precipitation; (b) the product clearly overestimated the frequency of no rainfall events at the grid cell scale and light rainfall (<1 mm/day) events at the region scale and also overestimated the amount of heavy rain (25–50 mm/day) and hard rain (≥50 mm/day) events; (c) under Scenario I, the 3B42‐V7 product performed poorly at three stations with gauge‐calibrated parameters; under Scenario II, the recalibrated model provided significantly improved performance of streamflow simulation with the 3B42‐V7 product; (d) the variable infiltration capacity model has the ability to reveal the hydrological characteristics of the karst landform in the Beijiang Basin when using the 3B42‐V7 product.  相似文献   

Merging multi-source precipitation products or merging their simulated hydrological flows to improve streamflow simulation     

Qian Zhu  Xichao Gao  Ye Tian 《水文科学杂志》2019,64(8):910-920

Satellite and reanalysis precipitation products are widely utilized for streamflow simulation, which is one critical hydrological application, especially for ungauged regions. Possible ways to improve streamflow simulation are investigated in this study by merging multi-source precipitation products, or directly merging streamflow simulated with different precipitation products. Two satellite-based precipitation products, Tropical Rainfall Measuring Mission (3B42 Version 7) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and one reanalysis precipitation product, National Centers for Environment Prediction-Climate Forecast System Reanalysis (NCEP-CFSR) are selected. Bayesian model averaging (BMA) is used to merge multi-source precipitation estimates and streamflow simulations. The results show that merging multi-source precipitation products made little difference to improve streamflow simulation. Merging multi-source streamflow simulations using the BMA generally achieved better performance on streamflow simulation, indicating that this approach is more efficient than merging multi-source precipitation products.  相似文献   

Geospatial blending to improve spatial mapping of precipitation with high spatial resolution by merging satellite‐based and ground‐based data          下载免费PDF全文

Baik Jongjin  Park Jongmin  Ryu Dongryeol  Choi Minha 《水文研究》2016,30(16):2789-2803

Estimating accurate spatial distribution of precipitation is important for understanding the hydrologic cycle and various hydro‐environmental applications. Satellite‐based precipitation data have been widely used to measure the spatial distribution of precipitation over large extents, but an improvement in accuracy is still needed. In this study, three different merging techniques (Conditional Merging, Geographical Differential Analysis and Geographical Ratio Analysis) were used to merge precipitation estimations from Communication, Ocean and Meteorological Satellite (COMS) Rainfall Intensity data and ground‐based measurements. Merged products were evaluated with varying rain‐gauge network densities and accumulation times. The results confirmed that accuracy of detecting quantitative rainfall was improved as the accumulation time and network density increased. Also, the impact of spatial heterogeneity of precipitation on the merged estimates was investigated. Our merging techniques reproduced accurate spatial distribution of rainfall by adopting the advantages of both gauge and COMS estimates. The efficacy of the merging techniques was particularly pronounced when the spatial heterogeneity of hourly rainfall, quantified by variance of rainfall, was greater than 10 mm²/accumulation time². Among the techniques analysed, Conditional Merging performed the best, especially when the gauge density was low. This study demonstrates the utility of the COMS Rainfall Intensity product, which has a shorter latency time (1 h) and higher spatio‐temporal resolution (hourly, 4 km by 4 km) than other widely used satellite precipitation products in estimating precipitation using merging techniques with ground‐based point measurements. The outcome has important implications for various hydrologic modelling approaches, especially for producing near real‐time products. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

Effects of temporal scales and space mismatches on the TRMM 3B42 v7 precipitation product in a remote mountainous area          下载免费PDF全文

Shiva Ebrahimi  Cheng Chen  Qiuwen Chen  Yinsheng Zhang  Ning Ma  Qammerul Zaman 《水文研究》2017,31(24):4315-4327

The accurate measurement of precipitation is essential to understanding regional hydrological processes and hydrological cycling. Quantification of precipitation over remote regions such as the Tibetan Plateau is highly unreliable because of the scarcity of rain gauges. The objective of this study is to evaluate the performance of the satellite precipitation product of tropical rainfall measuring mission (TRMM) 3B42 v7 at daily, weekly, monthly, and seasonal scales. Comparison between TRMM grid precipitation and point‐based rain gauge precipitation was conducted using nearest neighbour and bilinear weighted interpolation methods. The results showed that the TRMM product could not capture daily precipitation well due to some rainfall events being missed at short time scales but provided reasonably good precipitation data at weekly, monthly, and seasonal scales. TRMM tended to underestimate the precipitation of small rainfall events (less than 1 mm/day), while it overestimated the precipitation of large rainfall events (greater than 20 mm/day). Consequently, TRMM showed better performance in the summer monsoon season than in the winter season. Through comparison, it was also found that the bilinear weighted interpolation method performs better than the nearest neighbour method in TRMM precipitation extraction.  相似文献   

A multi-sensor evaluation of precipitation uncertainty for landslide-triggering storm events     

Elsa S. Culler  Andrew M. Badger  Justin Toby Minear  Kristy F. Tiampo  Spencer D. Zeigler  Ben Livneh 《水文研究》2021,35(7):e14260

Extreme precipitation can have profound consequences for communities, resulting in natural hazards such as rainfall-triggered landslides that cause casualties and extensive property damage. A key challenge to understanding and predicting rainfall-triggered landslides comes from observational uncertainties in the depth and intensity of precipitation preceding the event. Practitioners and researchers must select from a wide range of precipitation products, often with little guidance. Here we evaluate the degree of precipitation uncertainty across multiple precipitation products for a large set of landslide-triggering storm events and investigate the impact of these uncertainties on predicted landslide probability using published intensity–duration thresholds. The average intensity, peak intensity, duration, and NOAA-Atlas return periods are compared ahead of 177 reported landslides across the continental United States and Canada. Precipitation data are taken from four products that cover disparate measurement methods: near real-time and post-processed satellite (IMERG), radar (MRMS), and gauge-based (NLDAS-2). Landslide-triggering precipitation was found to vary widely across precipitation products with the depth of individual storm events diverging by as much as 296 mm with an average range of 51 mm. Peak intensity measurements, which are typically influential in triggering landslides, were also highly variable with an average range of 7.8 mm/h and as much as 57 mm/h. The two products more reliant upon ground-based observations (MRMS and NLDAS-2) performed better at identifying landslides according to published intensity–duration storm thresholds, but all products exhibited hit ratios of greater than 0.56. A greater proportion of landslides were predicted when including only manually verified landslide locations. We recommend practitioners consider low-latency products like MRMS for investigating landslides, given their near-real time data availability and good performance in detecting landslides. Practitioners would be well-served considering more than one product as a way to confirm intense storm signals and minimize the influence of noise and false alarms.  相似文献   

A comparison of gauge and radar precipitation data for simulating an extreme hydrological event in the Severn Uplands,UK     

Eloise M. Biggs  Peter M. Atkinson 《水文研究》2011,25(5):795-810

This paper provides a comparison of gauge and radar precipitation data sources during an extreme hydrological event. November–December 2006 was selected as a time period of intense rainfall and large river flows for the Severn Uplands, an upland catchment in the United Kingdom. A comparison between gauge and radar precipitation time‐series records for the event indicated discrepancies between data sources, particularly in areas of higher elevation. The HEC‐HMS rainfall‐runoff model was selected to assess the accuracy of the precipitation to simulate river flows for the extreme event. Gauge, radar and gauge‐corrected radar rainfall were used as model inputs. Universal cokriging was used to geostatistically interpolate gauge data with radar and elevation data as covariates. This interpolated layer was used to calculate the mean‐field bias and correct the radar composites. Results indicated that gauge‐ and gauge‐corrected radar‐driven models replicated flows adequately for the extreme event. Gauge‐corrected flow predictions produced an increase in flow prediction accuracy when compared with the raw radar, yet predictions were comparative in accuracy to those using the interpolated gauge network. Subsequent investigations suggested this was due to an adequate spatial and temporal resolution of the precipitation gauge network within the Severn Uplands. Results suggested that the six rain gauges could adequately represent precipitation variability of the Severn Uplands to predict flows at an approximately equal accuracy to that obtained by radar. Temporally, radar produced an increase in flow prediction accuracy in mountainous reaches once the gauge time step was in excessive of an hourly interval. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

Prediction of river temperature surges is dependent on precipitation method     

Danny Croghan  Anne F. Van Loon  Jon P. Sadler  Chris Bradley  David M. Hannah 《水文研究》2019,33(1):144-159

Urban river systems are particularly sensitive to precipitation‐driven water temperature surges and fluctuations. These result from rapid heat transfer from low‐specific heat capacity surfaces to precipitation, which can cause thermally polluted surface run‐off to enter urban streams. This can lead to additional ecological stress on these already precarious ecosystems. Although precipitation is a first‐order driver of hydrological response, water temperature studies rarely characterize rain event dynamics and typically rely on single gauge data that yield only partial estimates of catchment precipitation. This paper examines three precipitation measuring methods (a statutory automatic weather station, citizen science gauges, and radar estimates) and investigates relationships between estimated rainfall inputs and subhourly surges and diurnal fluctuations in urban river water temperature. Water temperatures were monitored at 12 sites in summer 2016 in the River Rea, in Birmingham, UK. Generalized additive models were used to model the relationship between subhourly water temperature surges and precipitation intensity and subsequently the relationship between daily precipitation totals and standardized mean water temperature. The different precipitation measurement sources give highly variable precipitation estimates that relate differently to water temperature fluctuations. The radar catchment‐averaged method produced the best model fit (generalized cross‐validation score [GCV] = 0.30) and was the only model to show a significant relationship between water temperature surges and precipitation intensity (P < 0.001, R² = 0.69). With respect to daily metrics, catchment‐averaged precipitation estimates from citizen science data yielded the best model fit (GCV score = 0.20). All precipitation measurement and calculation methods successfully modelled the relationship between standardized mean water temperature and daily precipitation (P < 0.001). This research highlights the potential for the use of alternative precipitation datasets to enhance understanding of event‐based variability in water quality studies. We conclude by recommending the use of spatially distributed precipitation data operating at high spatial (<1 km²) and temporal (<15 min) resolutions to improve the analysis of event‐based water temperature and water quality studies.  相似文献   

Scale-recursive assimilation of precipitation data     

Ida Primus Gorenburg  Dennis McLaughlin  Dara Entekhabi   《Advances in water resources》2001,24(9-10)

This paper presents a new statistical method for assimilating precipitation data from different sensors operating over a range of scales. The technique is based on a scale-recursive estimation algorithm which is computationally efficient and able to account for the nested spatial structure of precipitation fields. The version of the algorithm described here relies on a static multiplicative cascade model which relates rainrates at different scales. Bayesian estimation techniques are used to condition rainrate estimates on measurements. The conditioning process is carried out recursively in two sweeps: first from fine to coarse scales and then from coarse to fine scales. The complete estimation algorithm is similar to a fixed interval smoother although it processes data over scale rather than time. We use this algorithm to assimilate radar and satellite microwave data collected during the tropical ocean–global atmosphere coupled ocean–atmosphere response experiment (TOGA-COARE). The resulting rainrate estimates reproduce withheld radar measurements to within the level of accuracy predicted by the assimilation algorithm.  相似文献   

Comparison of radar and gauge precipitation data in watershed models across varying spatial and temporal scales          下载免费PDF全文

Katie Price  S. Thomas Purucker  Stephen R. Kraemer  Justin E. Babendreier  Chris D. Knightes 《水文研究》2014,28(9):3505-3520

Precipitation is a key control on watershed hydrologic modelling output, with errors in rainfall propagating through subsequent stages of water quantity and quality analysis. Most watershed models incorporate precipitation data from rain gauges; higher‐resolution data sources are available, but they are associated with greater computational requirements and expertise. Here, we investigate whether the Multisensor Precipitation Estimator (MPE or Stage IV Next‐Generation Radar) data improve the accuracy of streamflow simulations using the Soil and Water Assessment Tool (SWAT), compared with rain gauge data. Simulated flows from 2002 to 2010 at five timesteps were compared with observed flows for four nested subwatersheds of the Neuse River basin in North Carolina (21‐, 203‐, 2979‐, and 10 100‐km² watershed area), using a multi‐objective function, informal likelihood‐weighted calibration approach. Across watersheds and timesteps, total gauge precipitation was greater than radar precipitation, but radar data showed a conditional bias of higher rainfall estimates during large events (>25–50 mm/day). Model parameterization differed between calibrations with the two datasets, despite the fact that all watershed characteristics were the same across simulation scenarios. This underscores the importance of linking calibration parameters to realistic processes. SWAT simulations with both datasets underestimated median and low flows, whereas radar‐based simulations were more accurate than gauge‐based simulations for high flows. At coarser timesteps, differences were less pronounced. Our results suggest that modelling efforts in watersheds with poor rain gauge coverage can be improved with MPE radar data, especially at short timesteps. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.  相似文献   

Continuous daily hydrograph simulation using duration curves of a precipitation index     

V. Yu. Smakhtin  B. Masse 《水文研究》2000,14(6):1083-1100

The paper describes a parsimonious approach for generating continuous daily stream‐flow time‐series from observed daily rainfall data in a catchment. The key characteristic in the method is a duration curve. It is used to convert the daily rainfall information from source rain gauges into a continuous daily hydrograph at the destination river site. For each source rain gauge a time‐series of rainfall related ‘current precipitation index’ is generated and its duration curve is established. The current precipitation index reflects the current catchment wetness and is defined as a continuous function of precipitation, which accumulates on rainy days and exponentially decays during the periods of no rainfall. The process of rainfall‐to‐runoff conversion is based on the assumption that daily current precipitation index values at rainfall site(s) in a catchment and the destination site's daily flows correspond to similar probabilities on their respective duration curves. The method is tested in several small catchments in South Africa. The method is designed primarily for application at ungauged sites in data‐poor regions where the use of more complex and information consuming techniques of data generation may not be justified. Copyright © 2000 John Wiley & Sons, Ltd.  相似文献   

Copula‐based uncertainty modelling: application to multisensor precipitation estimates     

Amir AghaKouchak  Andrs Brdossy  Emad Habib 《水文研究》2010,24(15):2111-2124

The multisensor precipitation estimates (MPE) data, available in hourly temporal and 4 km × 4 km spatial resolution, are produced by the National Weather Service and mosaicked as a national product known as Stage IV. The MPE products have a significant advantage over rain gauge measurements due to their ability to capture spatial variability of rainfall. However, the advantages are limited by complications related to the indirect nature of remotely sensed precipitation estimates. Previous studies confirm that efforts are required to determine the accuracy of MPE and their associated uncertainties for future use in hydrological and climate studies. So far, various approaches and extensive research have been undertaken to develop an uncertainty model. In this paper, an ensemble generator is presented for MPE products that can be used to evaluate the uncertainty of rainfall estimates. Two different elliptical copula families, namely, Gaussian and t‐copula are used for simulations. The results indicate that using t‐copula may have significant advantages over the well‐known Gaussian copula particularly with respect to extremes. Overall, the model in which t‐copula was used for simulation successfully generated rainfall ensembles with similar characteristics to those of the ground reference measurements. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

The impact of climate change on extreme precipitation in Sicily,Italy          下载免费PDF全文

Angelo Forestieri  Elisa Arnone  Stephen Blenkinsop  Angela Candela  Hayley Fowler  Leonardo V. Noto 《水文研究》2018,32(3):332-348

Increasing precipitation extremes are one of the possible consequences of a warmer climate. These may exceed the capacity of urban drainage systems, and thus impact the urban environment. Because short‐duration precipitation events are primarily responsible for flooding in urban systems, it is important to assess the response of extreme precipitation at hourly (or sub‐hourly) scales to a warming climate. This study aims to evaluate the projected changes in extreme rainfall events across the region of Sicily (Italy) and, for two urban areas, to assess possible changes in Depth‐Duration‐Frequency (DDF) curves. We used Regional Climate Model outputs from Coordinated Regional Climate Downscaling Experiment for Europe area ensemble simulations at a ~12 km spatial resolution, for the current period and 2 future horizons under the Representative Concentration Pathways 8.5 scenario. Extreme events at the daily scale were first investigated by comparing the quantiles estimated from rain gauge observations and Regional Climate Model outputs. Second, we implemented a temporal downscaling approach to estimate rainfall for sub‐daily durations from the modelled daily precipitation, and, lastly, we analysed future projections at daily and sub‐daily scales. A frequency distribution was fitted to annual maxima time series for the sub‐daily durations to derive the DDF curves for 2 future time horizons and the 2 urban areas. The overall results showed a raising of the growth curves for the future horizons, indicating an increase in the intensity of extreme precipitation, especially for the shortest durations. The DDF curves highlight a general increase of extreme quantiles for the 2 urban areas, thus underlining the risk of failure of the existing urban drainage systems under more severe events.  相似文献   

基于REOF的两种卫星降水产品(IMERG和MSWEP)在金沙江流域降水分区尺度精度评估     

薄会娟  林青霞  李璐  魏冲  龚成麒 《湖泊科学》2024,36(2):620-633

高时空分辨率降水产品的精度评估是卫星降水用于水文气象干旱等研究的前提。本研究提出在降水分区尺度下评估IMERG和MSWEP两种卫星降水产品的精度,并与不分区尺度(即流域尺度)进行比较。首先采用旋转经验正交函数(REOF)对金沙江流域(JSB)进行降水分区,通过贡献率得出8个分区较为适合。然后识别降水的空间分布特征,发现2种降水产品都可以很好地捕捉降水呈现出的从上游到下游逐渐增加的趋势。最后在日尺度、降水发生概率和极端降水探测能力3个方面对降水产品在分区尺度和不分区尺度的性能进行评估。结果表明,在日尺度上,MSWEP的精度在多数降水分区优于IMERG,被推荐5次(1、3、6、7和8区),集中在流域的中游。同时流域尺度也推荐MSWEP。在降水事件发生概率方面,MSWEP能再现不同等级降水强度的概率密度分布,但过高估计0.1~1 mm/d降水事件的发生概率;而IMERG过高估计小于0.1 mm/d降水事件的概率。在极端降水探测能力方面,流域尺度的KGE值都是正值,且IMERG优于MSWEP,但分区尺度上,KGE值在部分降水分区中存在负值,表明IMERG和MSWEP均不能很好地探测出该区的极端降水事件。本研究成果表明降水分区尺度是必需的,能够更加精细地评估降水产品。研究结果可为具有类似气候条件的卫星降水评估提供参考。  相似文献   

Merging multiple precipitation sources for flash flood forecasting   总被引：3，自引：0，他引：3  

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   

Long-term diagnostics of precipitation estimates and the development of radar hardware monitoring within a radar product data quality management system     

Dawn Harrison  Selena Georgiou  Nicolas Gaussiat  Adam Curtis 《水文科学杂志》2014,59(7):1277-1292

Abstract

Quality is key to ensuring that the potential offered by weather radar networks is realized. To achieve optimum quality, a comprehensive radar data quality management system, designed to monitor the end-to-end radar data processing chain and evaluate product quality, is being developed at the UK Met Office. Three contrasting elements of this system are described: monitoring of key radar hardware performance indicators; generation of long-term integrations of radar products; and monitoring of radar reflectivity factor using synthesized observations from numerical weather prediction model fields. Examples of each component are presented and ways in which the different types of monitoring information have been used to both identify issues with the radar product data quality and help formulate solutions are given.