Improving interpolation of daily precipitation for hydrologic modelling: spatial patterns of preferred interpolators

Kurtzman, Daniel; Navon, Shilo; Morin, Efrat

doi:10.1002/hyp.7442

Cited by 93 publications

(57 citation statements)

References 23 publications

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“…The higher exponents perform better closer to the coast line and lower exponents are preferred closer to the mountain crest [42]. In general, p values are 1, 2 or 3 in mountainous areas [33].…”

Section: Inverse Distance Weightingmentioning

confidence: 95%

Performance Assessment of Spatial Interpolation of Precipitation for Hydrological Process Simulation in the Three Gorges Basin

Cheng

Wang

Engel

et al. 2017

Water

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Accurate assessment of spatial and temporal precipitation is crucial for simulating hydrological processes in basins, but is challenging due to insufficient rain gauges. Our study aims to analyze different precipitation interpolation schemes and their performances in runoff simulation during light and heavy rain periods. In particular, combinations of different interpolation estimates are explored and their performances in runoff simulation are discussed. The study was carried out in the Pengxi River basin of the Three Gorges Basin. Precipitation data from 16 rain gauges were interpolated using the Thiessen Polygon (TP), Inverse Distance Weighted (IDW), and Co-Kriging (CK) methods. Results showed that streamflow predictions employing CK inputs demonstrated the best performance in the whole process, in terms of the Nash-Sutcliffe Coefficient (NSE), the coefficient of determination (R 2 ), and the Root Mean Square Error (RMSE) indices. The TP, IDW, and CK methods showed good performance in the heavy rain period but poor performance in the light rain period compared with the default method (least sophisticated nearest neighbor technique) in Soil and Water Assessment Tool (SWAT). Furthermore, the correlation between the dynamic weight of one method and its performance during runoff simulation followed a parabolic function. The combination of CK and TP achieved a better performance in decreasing the largest and lowest absolute errors compared to any single method, but the IDW method outperformed all methods in terms of the median absolute error. However, it is clear from our findings that interpolation methods should be chosen depending on the amount of precipitation, adaptability of the method, and accuracy of the estimate in different rain periods.

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Section: Inverse Distance Weightingmentioning

confidence: 95%

Performance Assessment of Spatial Interpolation of Precipitation for Hydrological Process Simulation in the Three Gorges Basin

Cheng

Wang

Engel

et al. 2017

Water

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“…The mean annual precipitation (MAP) of each rain gauge was interpolated using the inverse distance weighting (IDW) technique with a 0.01° grid mesh for visualization purposes ( Figure 2). This technique was selected as it is widely used because of its simplicity and reliability [33,34].…”

Section: Rain Gaugesmentioning

confidence: 99%

Evaluation of Six High-Resolution Satellite and Ground-Based Precipitation Products over Malaysia

et al. 2015

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Satellite precipitation products (SPPs) potentially constitute an alternative to sparse rain gauge networks for assessing the spatial distribution of precipitation. However, applications of these products are still limited due to the lack of robust quality assessment. This study compares daily, monthly, seasonal, and annual rainfall amount at 342 rain gauges over Malaysia to estimations using five SPPs (3B42RT, 3B42V7, GPCP-1DD, PERSIANN-CDR, and CMORPH) and a ground-based precipitation product (APHRODITE). The performance of the precipitation products was evaluated from 2003 to 2007 using continuous (RMSE, R 2 , ME, MAE, and RB) and categorical (ACC, POD, FAR, CSI, and HSS) statistical approaches. Overall, 3B42V7 and APHRODITE performed the best, while the worst performance was shown by GPCP-1DD. 3B42RT, 3B42V7, and PERSIANN-CDR slightly overestimated observed precipitation by 2%, 4.7%, and 2.1%, respectively. By contrast, APHRODITE and CMORPH significantly underestimated precipitations by 19.7% and 13.2%, respectively, whereas GPCP-1DD only slightly underestimated by 2.8%. All six precipitation products performed better in the northeast monsoon than in the southwest OPEN ACCESSRemote Sens. 2015, 7 1505 monsoon. The better performances occurred in eastern and southern Peninsular Malaysia and in the north of East Malaysia, which receives higher rainfall during the northeast monsoon, whereas poor performances occurred in the western and dryer Peninsular Malaysia. All precipitation products underestimated the no/tiny (<1 mm/day) and extreme (≥20 mm/day) rainfall events, while they overestimated low (1-20 mm/day) rainfall events. 3B42RT and 3B42V7 showed the best ability to detect precipitation amounts with the highest HSS value (0.36). Precipitations during flood events such as those which occurred in late 2006 and early 2007 were estimated the best by 3B42RT and 3B42V7, as shown by an R 2 value ranging from 0.49 to 0.88 and 0.52 to 0.86, respectively. These results on SPPs' uncertainties and their potential controls might allow sensor and algorithm developers to deliver better products for improved rainfall estimation and thus improved water management.

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“…Catchment-representative rainfall is usually obtained by interpolation of point rainfall measured at rain gauges (e.g. Rogelis and Werner, 2013;Verworn and Haberlandt, 2011;Zhang and Srinivasan, 2009;Kurtzman et al, 2009). However, even in densely monitored regions, precipitation data are highly uncertain (Tian and Peters-Lidard, 2010;Woldemeskel et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile

Zambrano‐Bigiarini

Nauditt²,

Birkel

et al. 2017

Hydrol. Earth Syst. Sci.

233

153

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Abstract. Accurate representation of the real spatiotemporal variability of catchment rainfall inputs is currently severely limited. Moreover, spatially interpolated catchment precipitation is subject to large uncertainties, particularly in developing countries and regions which are difficult to access. Recently, satellite-based rainfall estimates (SREs) provide an unprecedented opportunity for a wide range of hydrological applications, from water resources modelling to monitoring of extreme events such as droughts and floods.This study attempts to exhaustively evaluate -for the first time -the suitability of seven state-of-the-art SRE products (TMPA 3B42v7, CHIRPSv2, CMORPH, PERSIANN-CDR, PERSIAN-CCS-Adj, MSWEPv1.1, and PGFv3) over the complex topography and diverse climatic gradients of Chile. Different temporal scales (daily, monthly, seasonal, annual) are used in a point-to-pixel comparison between precipitation time series measured at 366 stations (from sea level to 4600 m a.s.l. in the Andean Plateau) and the corresponding grid cell of each SRE (rescaled to a 0.25 • grid if necessary). The modified Kling-Gupta efficiency was used to identify possible sources of systematic errors in each SRE. In addition, five categorical indices (PC, POD, FAR, ETS, fBIAS) were used to assess the ability of each SRE to correctly identify different precipitation intensities.Results revealed that most SRE products performed better for the humid South (36.4-43.7 • S) and Central Chile (32.18-36.4 • S), in particular at low-and mid-elevation zones (0-1000 m a.s.l.) compared to the arid northern regions and the Far South. Seasonally, all products performed best during the wet seasons (autumn and winter; MAM-JJA) compared to summer (DJF) and spring (SON). In addition, all SREs were able to correctly identify the occurrence of no-rain events, but they presented a low skill in classifying precipitation intensities during rainy days. Overall, PGFv3 exhibited the best performance everywhere and for all timescales, which can be clearly attributed to its bias-correction procedure using 217 stations from Chile. Good results were also obtained by the research products CHIRPSv2, TMPA 3B42v7 and MSWEPv1.1, while CMORPH, PERSIANN-CDR, and the real-time PERSIANN-CCS-Adj were less skillful in representing observed rainfall. While PGFv3 (currently available up to 2010) might be used in Chile for historical analyses and calibration of hydrological models, the high spatial resolution, low latency and long data records of CHIRPS and TMPA 3B42v7 (in transition to IMERG) show promising potential to be used in meteorological studies and water resource assessments. We finally conclude that despite improvements of most SRE products, a site-specific assessment is still needed before any use in catchment-scale hydrological studies.

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Improving interpolation of daily precipitation for hydrologic modelling: spatial patterns of preferred interpolators

Cited by 93 publications

References 23 publications

Performance Assessment of Spatial Interpolation of Precipitation for Hydrological Process Simulation in the Three Gorges Basin

Performance Assessment of Spatial Interpolation of Precipitation for Hydrological Process Simulation in the Three Gorges Basin

Evaluation of Six High-Resolution Satellite and Ground-Based Precipitation Products over Malaysia

Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile

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