Propagation of uncertainties in interpolated rainfields to runoff errors

Conditional daily rainfields were generated using collocated raingauge radar data by a kriging interpolation method, and disaggregated into hourly rainfields using variants of the method of fragments. A geographic information system (GIS)-based distributed rainfall–runoff model was used to convert the hourly rainfields into hydrographs. Using the complete radar rainfall as input, the rainfall–runoff model was calibrated based on storm events taken from nested catchments. Performance statistics were estimated by comparing the observed and the complete radar rainfall simulated hydrographs. Degradation in the hydrograph performance statistics by the simulated hourly rainfields was used to identify runoff error propagation. Uncertainty in daily rainfall amounts alone caused higher errors in runoff (depth, peak, and time to peak) than those caused by uncertainties in the hourly proportions alone. However, the degradation, which reduced with runoff depth, caused by the combined uncertainties was not significantly different from that caused by the uncertainty of amounts alone.     

Hydrological appraisal of rainfall estimates from radar,satellite, raingauge and satellite–gauge combination on the Qinhuai River Basin,China

ABSTRACT

Multisource rainfall products can be used to overcome the absence of gauged precipitation data for hydrological applications. This study aims to evaluate rainfall estimates from the Chinese S-band weather radar (CINRAD-SA), operational raingauges, multiple satellites (CMORPH, ERA-Interim, GPM, TRMM-3B42RT) and the merged satellite–gauge rainfall products, CMORPH-GC, as inputs to a calibrated probability distribution model (PDM) on the Qinhuai River Basin in Nanjing, China. The Qinhuai is a middle-sized catchment with an area of 799 km². All sources used in this study are capable of recording rainfall at high spatial and temporal resolution (3 h). The discrepancies between satellite and radar data are analysed by statistical comparison with raingauge data. The streamflow simulation results from three flood events suggest that rainfall estimates using CMORPH-GC, TRMM-3B42RT and S-band radar are more accurate than those using the other rainfall sources. These findings indicate the potential to use satellite and radar data as alternatives to raingauge data in hydrological applications for ungauged or poorly gauged basins.     

V: Daily catchment rainfall estimated from meteosat

Meteosat data for 1986 to 1988 have been used to estimate the daily rainfall over catchments of tributaries of the river Senegal in Mail and Guinea. The technique uses the methodology of the TAMSAT group of the University of Reading, which involves the selection of an appropriate cloud top temperature threshold to determine whether the cloud is producing rain and the rainfall is estimated from the period during which storm clouds remain over a site. After calibration against all available raingauges in the catchments, the daily rainfall estimates derived by this technique were used as inputs to rainfall-runoff models. The results indicate that the streamflow models, which had themselves been calibrated using raingauge data, performed as well or better when the satellite derived estimates were used as inputs than when gauge data were used. An economical, automated operational system is described.     

Evaluating the performance of ground-based and remotely sensed near real-time rainfall fields from a hydrological perspective

Abstract

The South African Weather Service (SAWS) issues routine experimental, near real-time rainfall maps from daily raingauge networks, radar networks and satellite images, as well as merged rainfall fields. These products are potentially useful for near real-time forecasting, especially in areas of fast hydrological response, and also to simulate the “now state” of various hydrological state variables such as soil moisture content, streamflow, and reservoir inflows. The purpose of this paper is to evaluate their skill as inputs to hydrological simulations and, in particular, the skill of the merged field in terms of better hydrological results relative to the individual products. Rainfall fields derived from raingauge, radar, satellite, conditioned satellite and the merged (gauge/radar/satellite) were evaluated for two selected days with relatively high amounts of rainfall, as well as for a continuous period of 90 days in the Mgeni catchment, South Africa. Streamflows simulated with the ACRU model indicate that the use of raingauge as well as merged fields of satellite/raingauge and satellite/radars/raingauge provides relatively realistic rainfall results, without much difference in their hydrological outputs, whereas the radar and raw satellite information by themselves cannot be used in operational hydrological application in their current status.

Citation Ghile, Y., Schulze, R. & Brown, C. (2010) Evaluating the performance of ground-based and remotely sensed near real-time rainfall fields from a hydrological perspective. Hydrol. Sci. J. 55(4), 497–511.     

Analysis of radar and raingauge measurements for a critical meteorological event in Tuscany

In this paper, some considerations are given to the employment of C-band polarimetric weather radars for rainfall estimates. The most common error sources are discussed, such as ground clutter and propagation attenuation effects, together with decorrelation in the sampling at the ground between radar and raingauge measurements, which can be quite significant in radar systems located in hilly regions, as is the case of the Arno basin in Tuscany. Since the main objective from a hydrological point of view is the estimate of rainfall at ground, integrations and comparisons are needed between radar and raingauge data, which are characterized by different time and space sampling. The paper is then focussed mainly on this problem and a technique is presented in order to improve radar based rainfall estimates through the integration with raingauge data, in order to enhance the correlation between the two types of measurements. Such a method is finally applied to a serious meteorological event which affected the Arno basin on October 1992.     

Application of a land surface model for simulating rainfall streamflow hydrograph: 2. Comparison with hydrological models

Rainfall runoff hydrographs for 12 river basins ∼10³ km² in area, simulated using land surface model SWAP, are compared with analogous hydrographs obtained using hydrological models that took part in the International Model Parameter Estimation Experiment project and demonstrated the best results. All models were calibrated against data on daily river runoff from each basin over a 20-year period (1960–1979). Optimized model parameters were used to simulate runoff hydrographs for the following 19 years (1980–1998). The comparison of the modeled hydrographs for 12 basins in different calculational periods demonstrated that the SWAP model can simulate river runoff with an accuracy comparable with that of hydrological models.     

Correcting the TRMM rainfall product for hydrological modelling in sparsely-gauged mountainous basins

This study developed a correction approach to improve the rainfall field estimation using the TRMM rainfall product in a sparsely-gauged mountainous basin. First, Thiessen polygons were generated to define the measurement domain of each raingauge. Second, the rainfall of TRMM pixels in each Thiessen polygon was corrected using a benchmark method based on the difference between the monthly rainfall estimated by a raingauge and the TRMM pixel that possessed a gauge station (referred to as a gauged pixel). Third, the rainfall values in the gauged pixels were adjusted to the weighted average value of the gauge rainfall and corrected pixel rainfall. Finally, the rainfall in the non-gauged TRMM pixels was corrected as the sum of two terms. The first term is the adjusted rainfall in the corresponding gauged pixel in the same Thiessen polygon, and the second term is the rainfall (after benchmark correction) difference between the current pixel and the gauged pixel. Our results indicate that the corrected rainfall data outperforms the original TRMM product in the simulations of moderate and low flows and outperforms the sparse raingauges in the simulations of both peak and low flows.

EDITOR A. Castellarin; ASSOCIATE EDITOR S. Huang     

Water resources and climate change impact modelling on a daily time scale in the Peruvian Andes

Abstract

Estimating water resources is important for adequate water management in the future, but suitable data are often scarce. We estimated water resources in the Vilcanota basin (Peru) for the 1998–2009 period with the semi-distributed hydrological model PREVAH using: (a) raingauge measurements; (b) satellite rainfall estimates from the TRMM Multi-satellite Precipitation Analysis (TMPA); and (c) ERA-Interim re-analysis data. Multiplicative shift and quantile mapping were applied to post-process the TMPA estimates and ERA-Interim data. This resulted in improved low-flow simulations. High-flow simulations could only be improved with quantile mapping. Furthermore, we adopted temperature and rainfall anomalies obtained from three GCMs for three future periods to make estimations of climate change impacts (Delta-change approach) on water resources. Our results show more total runoff during the rainy season from January to March, and temporary storages indicate that less water will be available in this Andean region, which has an effect on water supply, especially during dry season.

Editor Z.W. Kundzewicz; Associate editor D. Gerten     

Satellite-based rainfall estimation for river flow forecasting in Africa. I: Rainfall estimates and hydrological forecasts

Abstract

Reliable, real-time river flow forecasting in Africa on a time scale of days can provide enormous humanitarian and economic benefits. This study investigates the feasibility of using daily rainfall estimates based on cold cloud duration (CCD) derived from Meteosat thermal infrared imagery as input to a simple rainfall—runoff model and also whether such estimates can be improved by the inclusion of information from numerical weather prediction (NWP) analysis models. The Bakoye catchment in Mali, West Africa has been used as a test area. The data available for the study covered the main months of the rainy season for three years. The rainfall estimates were initially validated against gauge data. Improvements in quality were observed when information relating to African Easterly Wave phase and storm type was included in a multiple linear regression (MR) algorithm. The estimates were also tested by using them as input to a rainfall—runoff model. When contemporaneous calibrations from raingauges were available for calibration, both CCD-only and MR rainfall estimates gave more accurate river flow forecasts than when using raingauge data alone. In the absence of contemporaneous calibrations, the performance was reduced but the MR did better than the CCDonly input in all years. The use of satellite-derived vegetation index did not improve the quality of the river flow forecasts.     

Appropriate Spatial Sampling of Rainfall or Flow Simulation/Echantillonnage Spatial de la Pluie Approprié pour la Simulation D'écoulements

Abstract

The objective of this study is to find the appropriate number and location of raingauges for a river basin for flow simulation by using statistical analyses and hydrological modelling. First, a statistical method is used to identify the appropriate number of raingauges. Herein the effect of the number of raingauges on the cross-correlation coefficient between areally averaged rainfall and discharge is investigated. Second, a lumped HBV model is used to investigate the effect of the number of raingauges on hydrological modelling performance. The Qingjiang River basin with 26 raingauges in China is used for a case study. The results show that both cross-correlation coefficient and modelling performance increase hyperbolically, and level off after five raingauges (therefore identified to be the appropriate number of rain-gauges) for this basin. The geographical locations of raingauges which give the best and worst hydrological modelling performance are identified, which shows that there is a strong dependence on the local geographical and climatic patterns.     

Analysis and modeling of spatial correlation structure in small-scale rainfall in Central Oklahoma

Spatial correlation structure in small-scale rainfall is analyzed based on a dense cluster of raingauges in Central Oklahoma. This cluster, called the EVAC PicoNet, consists of 53 gauges installed in 25 measurement stations covering an area of about 3 km by 3 km. Two raingauges are placed in 24 stations and five in the central station. Three aspects of the estimated spatial correlation functions are discussed: dependence on time-scale ranging from 1 min to 24 h, inter-storm variability, and dependence on rainfall intensity. The results show a regular dependence of the correlogram parameters on the averaging time-scale, large differences of the correlograms in the individual storms, and the dominance of storms with high spatial variability on the average large sample characteristics. The authors also demonstrate and discuss the ambiguities in correlation estimates conditioned on rainfall intensities. The findings of this study have implications for raingauge network design, rainfall modeling, and conclusive evaluation of radar and satellite estimates of rainfall.     

Sensitivity analysis of the hydrological response of the Gaping River basin to radar-raingauge quantitative precipitation estimates

Abstract

The generation of reliable quantitative precipitation estimations (QPEs) through use of raingauge and radar data is an important issue. This study investigates the impacts of radar QPEs with different densities of raingauge networks on rainfall–runoff processes through a semi-distributed parallel-type linear reservoir rainfall–runoff model. The spatial variation structures of the radar QPE, raingauge QPE and radar-gauge residuals are examined to review the current raingauge network, and a compact raingauge network is identified via the kriging method. An analysis of the large-scale spatial characteristics for use with a hydrological model is applied to investigate the impacts of a raingauge network coupled with radar QPEs on the modelled rainfall–runoff processes. Since the precision in locating the storm centre generally represents how well the large-scale variability is reproduced; the results show not only the contribution of kriging to identify a compact network coupled with radar QPE, but also that spatial characteristics of rainfalls do affect the hydrographs.

Editor Z.W. Kundzewicz; Guest editor R.J. Moore

Citation Pan, T.-Y., Li, M.-Y., Lin, Y.-J., Chang, T.-J., Lai, J.-S., and Tan, Y.-C., 2014. Sensitivity analysis of the hydrological response of the Gaping River basin to radar-raingauge quantitative precipitation estimates. Hydrological Sciences Journal, 59 (7), 1335–1352. http://dx.doi.org/10.1080/02626667.2014.923969     

Evaluation and hydrological application of precipitation estimates derived from PERSIANN‐CDR,TRMM 3B42V7, and NCEP‐CFSR over humid regions in China

Satellite‐based and reanalysis quantitative precipitation estimates are attractive for hydrologic prediction or forecasting and reliable water resources management, especially for ungauged regions. This study evaluates three widely used global high‐resolution precipitation products [Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks‐Climate Data Record (PERSIANN‐CDR), Tropical Rainfall Measuring Mission 3B42 Version 7 (TRMM 3B42V7), and National Centers for Environment Prediction‐Climate Forecast System Reanalysis (NCEP‐CFSR)] against gauge observations with seven statistical indices over two humid regions in China. Furthermore, the study investigates whether the three precipitation products can be reliably utilized as inputs in Soil and Water Assessment Tool, a semi‐distributed hydrological model, to simulate streamflows. Results show that the precipitation estimates derived from TRMM 3B42V7 outperform the other two products with the smallest errors and bias, and highest correlation at monthly scale, which is followed by PERSIANN‐CDR and NCEP‐CFSR in this rank. However, the superiority of TRMM 3B42V7 in errors, bias, and correlations is not warranted at daily scale. PERSIANN‐CDR and 3B42V7 present encouraging potential for streamflow prediction at daily and monthly scale respectively over the two humid regions, whilst the performance of NCEP‐CFSR for hydrological applications varies from basin to basin. Simulations forced with 3B42V7 are the best among the three precipitation products in capturing daily measured streamflows, whilst PERSIANN‐CDR‐driven simulations underestimate high streamflows and high streamflow simulations driven by NCEP‐CFSR mostly are overestimated significantly. In terms of extreme events analysis, PERSIANN‐CDR often underestimates the extreme precipitation, so do extreme streamflow simulations forced with it. NCEP‐CFSR performs just the reverse, compared with PERSIANN‐CDR. The performance pattern of TRMM 3B42V7 on extremes is not certain, with coexisting underestimation and overestimation. Copyright © 2016 John Wiley & Sons, Ltd.     

Distributed hydrological modelling using weather radar in gauged and ungauged basins

Distributed hydrological modelling using space–time estimates of rainfall from weather radar provides a natural approach to area-wide flood forecasting and warning at any location, whether gauged or ungauged. However, radar estimates of rainfall may lack consistent, quantitative accuracy. Also, the formulation of hydrological models in distributed form may be problematic due to process complexity and scaling issues. Here, the aim is to first explore ways of improving radar rainfall accuracy through combination with raingauge network data via integrated multiquadric methods. When the resulting gridded rainfall estimates are employed as input to hydrological models, the simulated river flows show marked improvements when compared to using radar data alone. Secondly, simple forms of physical–conceptual distributed hydrological model are considered, capable of exploiting spatial datasets on topography and, where necessary, land-cover, soil and geology properties. The simplest Grid-to-Grid model uses only digital terrain data to delineate flow pathways and to control runoff production, the latter by invoking a probability-distributed relation linking terrain slope to soil absorption capacity. Model performance is assessed over nested river basins in northwest England, employing a lumped model as a reference. When the distributed model is used with the gridded radar-based rainfall estimators, it shows particular benefits for forecasting at ungauged locations.     

Evaluation of remote‐sensing‐based rainfall products through predictive capability in hydrological runoff modelling

The emergence of regional and global satellite‐based rainfall products with high spatial and temporal resolution has opened up new large‐scale hydrological applications in data‐sparse or ungauged catchments. Particularly, distributed hydrological models can benefit from the good spatial coverage and distributed nature of satellite‐based rainfall estimates (SRFE). In this study, five SRFEs with temporal resolution of 24 h and spatial resolution between 8 and 27 km have been evaluated through their predictive capability in a distributed hydrological model of the Senegal River basin in West Africa. The main advantage of this evaluation methodology is the integration of the rainfall model input in time and space when evaluated at the sub‐catchment scale. An initial data analysis revealed significant biases in the SRFE products and large variations in rainfall amounts between SRFEs, although the spatial patterns were similar. The results showed that the Climate Prediction Center/Famine Early Warning System (CPC‐FEWS) and cold cloud duration (CCD) products, which are partly based on rain gauge data and produced specifically for the African continent, performed better in the modelling context than the global SRFEs, Climate Prediction Center MORPHing technique (CMORPH), Tropical Rainfall Measuring Mission (TRMM) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). The best performing SRFE, CPC‐FEWS, produced good results with values of R²_NS between 0·84 and 0·87 after bias correction and model recalibration. This was comparable to model simulations based on traditional rain gauge data. The study highlights the need for input specific calibration of hydrological models, since major differences were observed in model performances even when all SRFEs were scaled to the same mean rainfall amounts. This is mainly attributed to differences in temporal dynamics between products. Copyright © 2009 John Wiley & Sons, Ltd.     

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

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.     

Evaluation of precipitation products over complex mountainous terrain: A water resources perspective

The availability of in situ measurements of precipitation in remote locations is limited. As a result, the use of satellite measurements of precipitation is attractive for water resources management. Combined precipitation products that rely partially or entirely on satellite measurements are becoming increasingly available. However, these products have several weaknesses, for example their failure to capture certain types of precipitation, limited accuracy and limited spatial and temporal resolution. This paper evaluates the usefulness of several commonly used precipitation products over data scarce, complex mountainous terrain from a water resources perspective. Spatially averaged precipitation time series were generated or obtained for 16 sub-basins of the Paute river basin in the Ecuadorian Andes and 13 sub-basins of the Baker river basin in Chilean Patagonia. Precipitation time series were generated using the European Centre for Medium Weather Range Forecasting (ECMWF) 40 year reanalysis (ERA-40) and the subsequent ERA-interim products, and the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis dataset 1 (NCEP R1) hindcast products, as well as precipitation estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). The Tropical Rainfall Measurement Mission (TRMM) 3B42 is also used for the Ecuadorian Andes. These datasets were compared to both spatially averaged gauged precipitation and river discharge. In general, the time series of the remotely sensed and hindcast products show a low correlation with locally observed precipitation data. Large biases are also observed between the different products. Hydrological verification based on river flows reveals that water balance errors can be extremely high for all evaluated products, including interpolated local data, in basins smaller than 1000 km². The observations are consistent over the two study regions despite very different climatic settings and hydrological processes, which is encouraging for extrapolation to other mountainous regions.     

Flood simulation using different sources of rainfall in the Huong River,Vietnam / Simulation d'inondation à l'aide de différentes sources d'information pluviométrique dans le bassin de la Rivière Huong,Vietnam

Abstract

The possibility of simulating flooding in the Huong River basin, Vietnam, was examined using quantitative precipitation forecasts at regional and global scales. Raingauge and satellite products were used for observed rainfall. To make maximum use of the spatial heterogeneity of the different types of rainfall data, a distributed hydrological model was set up to represent the hydrological processes. In this way, streamflow simulated using the rainfall data was compared with that observed in situ. The forecast on a global scale showed better performance during normal flow peak simulations than during extreme events. In contrast, it was found that during an extreme flood peak, the use of regional forecasts and satellite data gives results that are in close agreement with results using raingauge data. Using the simulated overflow volumes recorded at the control point downstream, inundation areas were then estimated using topographic characteristics. This study is the first step in developing a future efficient early warning system and evacuation strategy.     

Flood modelling using the distributed event-based SCS-LR model in the Mediterranean Real Collobrier catchment

ABSTRACT

Event-based models are often used for flood prediction because they require fewer data than more complex models and account for a small number of parameters. We present the performance of such a model in simulating Mediterranean floods, with a focus on the initialization and on the impact of the rainfall uncertainties on the calibration of the model. The distributed event-based parsimonious Soil Conservation Service Lag-and-Route (SCS-LR) model was applied in the Real Collobrier catchment, France, which has a very high density of raingauges. The initial condition of the model was highly correlated with predictors, such as baseflow or soil water content. A reduction in the raingauge density can markedly change the calibration of the model. As the density of raingauges is generally low in most catchments, the uncertainties associated with rainfall measurement are thus expected either to mask the actual accuracy of the model, or to alter the model parameters.     

Differentiating between rain,snow, and glacier contributions to river discharge in the western Himalaya using remote-sensing data and distributed hydrological modeling

Rivers draining the southern Himalaya provide most of the water supply for the densely populated Indo-Gangetic plains. Despite the importance of water resources in light of climate change, the relative contributions of rainfall, snow and glacier melt to discharge are not well understood, due to the scarcity of ground-based data in this complex terrain. Here, we quantify discharge sources in the Sutlej Valley, western Himalaya, from 2000 to 2012 with a distributed hydrological model that is based on daily, ground-calibrated remote-sensing observation. Based on the consistently good model performance, we analyzed the spatiotemporal distribution of hydrologic components and quantified their contribution to river discharge. Our results indicate that the Sutlej River's annual discharge at the mountain front is sourced to 55% by effective rainfall (rainfall reduced by evapotranspiration), 35% by snow melt and 10% by glacier melt. In the high-elevation orogenic interior glacial runoff contributes ∼30% to annual river discharge. These glacier melt contributions are especially important during years with substantially reduced rainfall and snowmelt runoff, as during 2004, to compensate for low river discharge and ensure sustained water supply and hydropower generation. In 2004, discharge of the Sutlej River totaled only half the maximum annual discharge; with 17.3% being sourced by glacier melt. Our findings underscore the importance of calibrating remote-sensing data with ground-based data to constrain hydrological models with reasonable accuracy. For instance, we found that TRMM (Tropical Rainfall Measuring Mission) product 3B42 V7 systematically overestimates rainfall in arid regions of our study area by a factor of up to 5. By quantifying the spatiotemporal distribution of water resources we provide an important assessment of the potential impact of global warming on river discharge in the western Himalaya. Given the near-global coverage of the utilized remote-sensing datasets this hydrological modeling approach can be readily transferred to other data-sparse regions.