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.     

Reliability of reanalysis and remotely sensed precipitation products for hydrological simulation over the Sefidrood River Basin,Iran

ABSTRACT

Hydrological models require different inputs for the simulation of processes, among which precipitation is essential. For hydrological simulation, four different precipitation products – Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE); European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim); Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) real time (RT); and Precipitation Estimation from Remotely Sensed Information using Arti?cial Neural Networks (PERSIANN) – are compared against ground-based datasets. The variable infiltration capacity (VIC) model was calibrated for the Sefidrood River Basin (SRB), Iran. APHRODITE and ERA-Interim gave better rainfall estimates at daily time scale than other products, with Nash-Sutcliffe efficiency (NSE) values of 0.79 and 0.63, and correlation coefficient (CC) of 0.91 and 0.82, respectively. At the monthly time scale, the CC between all rainfall datasets and ground observations is greater than 0.9, except for TMPA-RT. Hydrological assessment indicates that PERSIANN is the best rainfall dataset for capturing the streamflow and peak flows for the studied area (CC: 0.91, NSE: 0.80).     

Capabilities of satellite precipitation datasets to estimate heavy precipitation rates at different temporal accumulations

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.     

Temporal analysis of Soil and Water Assessment Tool (SWAT) performance based on remotely sensed precipitation products

No study has systematically evaluated streamflow modelling between monthly and daily time scales. This study examines streamflow from seven watersheds across the USA where five different precipitation products were used as primary input into the Soil and Water Assessment Tool (SWAT) to generate simulated streamflow. Time scales examined include monthly, dekad (10 days), pentad (5 days), triad (3 days), and daily. The seven basins studied are the San Pedro (Arizona), Cimarron (north‐central Oklahoma), mid‐Nueces (south Texas), mid‐Rio Grande (south Texas and northern Mexico), Yocano (northern Mississippi), Alapaha (south Georgia), and mid‐St. Francis (eastern Arkansas). The precipitation products used to drive simulations include rain gauge, NWS Multisensor Precipitation Estimator, Tropical Rainfall Measurement Mission (TRMM), Multi‐Satellite Precipitation Analysis, TRMM 3B42‐V6, and Climate Prediction Center Morphing Method (CMORPH). Understanding how streamflow varies at sub‐monthly time scales is important because there are a host of hydrological applications such a flood forecast guidance and reservoir inflow forecasts that reside in a temporal domain between monthly and daily time scales. The major finding of this study is the quantification of a strong positive correlation between performance metrics and time step at which model performance deteriorates. Better performing simulations, with higher Nash–Sutcliffe values of 0.80 and above can support modeling at finer time scales to at least daily and perhaps beyond into the sub‐daily realm. These findings are significant in that they clearly document the ability of SWAT to support modeling at sub‐monthly time steps, which is beyond the capability for which SWAT was initially designed. Copyright © 2012 John Wiley & Sons, Ltd.     

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.     

Correction of TRMM 3B43 monthly precipitation data over the mountainous areas of Peru during the period 1998–2007

In an attempt to estimate the spatial and temporal behaviour of rainfall over the mountainous areas of the Peruvian Andes, a new in situ monthly rainfall dataset has been collected (1998–2007) and compared with Tropical Rainfall Measuring Mission (TRMM) 3B43 monthly precipitation data for regions located above 3000 m. The reliability of the TRMM 3B43 data varies depending on the root mean squared error ratio (%RMSE) and correlation coefficient. Because of the discrepancy between the two datasets, the use of additive and multiplicative correction models is proposed for the TRMM 3B43 data. In the Peruvian mountain ranges, these correction models better approximate TRMM rainfall monthly values, as already verified for annual values. Copyright © 2011 John Wiley & Sons, Ltd.     

Evaluation and hydrologic validation of TMPA satellite precipitation product downstream of the Pearl River Basin,China

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.     

Impact of climate change on streamflow in the arid Shiyang River Basin of northwest China

Climate change may significantly affect the hydrological cycle and water resource management, especially in arid and semi‐arid regions. In this paper, output from the Providing Regional Climates for Impacts Studies (PRECIS) regional climate model were used in conjunction with the Soil and Water Assessment Tool (SWAT) to analyse the effects of climate change on streamflow of the Xiying and Zamu rivers in the Shiyang River basin, an important arid region in northwest China. After SWAT model calibration and validation, streamflow in the Shiyang River Basin was simulated using the PRECIS climate model data for greenhouse gas emission scenarios A2 (high emission rate) and B2 (low emission rate) developed by Intergovernmental Panel on Climate Change. Monthly streamflow and hydrological extremes were compared for present‐day years (1961–1990), the 2020s (2011–2040), 2050s (2041–2070) and 2080s (2071–2100). The results show that mean monthly streamflow in Shiyang River Basin generally increased in the 2020s, 2050s and 2080s between 0.7–6.1% at the Zamu gauging station and 0.1–4.8% at the Xiying gauging station. The monthly minimum streamflow increased persistently, but the maximum monthly streamflows increased in the 2020s and slightly decreased in the 2050s and 2080s. This study provides valuable information for guiding future water resource management in the Shiyang River Basin and other arid and semi‐arid regions in China. Copyright © 2011 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.     

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.     

Pre-processing of data-driven river flow forecasting models by singular value decomposition (SVD) technique

ABSTRACT

An appropriate streamflow forecasting method is a prerequisite for implementation of efficient water resources management in the water-limited, arid regions that occupy much of Iran. In the current research, monthly streamflow forecasting was combined with three data-driven methods based on large input datasets involving 11 precipitation stations, a natural streamflow, and four climate indices through a long period. The major challenges of rainfall–runoff modelling are generally attributed to complex interacting processes, the large number of variables, and strong nonlinearity. The sensitivity of data-driven methods to the dimension of input/output datasets would be another challenge, so large datasets should be compressed into independently standardized principal components. In this study, three pre-processing techniques were applied: singular value decomposition (SVD) provided more efficient forecasts in comparison to principal component analysis (PCA) and average values of inputs in all networks. Among the data-driven methods, the multi-layer perceptron (MLP) with 1-month lag-time outperformed radial basis and fuzzy-based networks. In general, an increase in monthly lag-time of streamflow forecasting resulted in a decline in forecasting accuracy. The results reveal that SVD was highly effective in pre-processing of data-driven evaluations.     

Multiscale variability of streamflow changes in the Pearl River basin,China

The Pearl River basin bears the heavy responsibility for the water supply for the neighboring cities such as Macau, Hong Kong and others. Therefore, effective water resource management is crucial for sustainable use of water resource. However, good knowledge of changing properties of streamflow changes is the first step into the effective water resource management. With this in mind, stability and variability of streamflow changes in the Pearl River basin is thoroughly analyzed based on monthly streamflow data covering last half century using Mann–Kendall trend test and scanning t- and F-test techniques. The results indicate: (1) significant increasing monthly streamflow is observed mainly in January–April, June and October–December. Monthly streamflow during May–September is in not significant changes. Besides, stations characterized by significant monthly streamflow changes are located in the middle and the lower Pearl River basin; (2) changing points of monthly streamflow series are detected mainly during mid-1960s, early 1970s, mid-1970s, early 1980s and early 1990s and these periods are roughly in good agreement with those of annual, winter and summer precipitation across the Pearl River basin, implying tremendous influences of precipitation changes on streamflow variations; (3) abrupt behaviors tend to be ambiguous from the upper to the lower Pearl River basin, which should be due to enhancing combined effects of abrupt changes of precipitation. The streamflow comes to be lower stability in recent decades. However, high stability of streamflow changes are observed at hydrological stations in the lower Pearl River basin. The results of this study will be of great scientific and practical merits in terms of effective water resource management in the Pearl River basin under the influences of climate changes and human activities.     

Effects of land use and climate variability on the main stream of the Songhua River Basin,Northeast China

ABSTRACT

In this study, three representative concentration pathways (RCPs) and 15 general circulation models of the Coupled Model Intercomparison Project Phase 5 were used to assess the behaviour of precipitation (P) and surface air temperature (SAT) over part of the Songhua River Basin. The Water Evaluation and Planning (WEAP) model linked with SAT and P was used for monthly simulation of streamflow to assess the influence of land use/land cover and climate change on the streamflow. The results suggest that, under RCP2.6, RCP4.5 and RCP8.5, the SAT over the study area may increase in the 21st century by 1.12, 2.44 and 5.82°C, respectively. Moreover, by the middle of the 21st century, streamflow in the basin may have decreased by 19%. The decrease in streamflow may be due to changed land use conditions and water withdrawal, having critical implications for management and future planning of water resources in the basin.     

黄河流域气候与农业种植面积变化对径流的影响

根据黄河流域1960—2005年5个水文站逐日流量、77个气象站1959—2013年逐日降水数据,结合流域内主要农作物种植面积及大型水库资料,全面探讨气候与农业面积变化及人类活动对黄河流域径流变化的影响.研究表明:黄河流域所有流量分位数总体呈下降趋势,并于1980s中后期到1990s中期发生突变.降水变化是黄河流域径流变化的主要影响因素.在考虑不同流量分位数情况下,农作物种植面积变化对不同分位数径流变化的影响也有差异性.花园口站农作物种植面积变化对径流量量级和可变性均有显著影响;其余4站各项气候变化与农作物种植指标参数较大,虽均未达到10%的显著性水平,但仍会对径流的量级变化产生影响.对唐乃亥站,农作物耕作面积的下降减少了灌溉用水,在0.5流量分位数时有高达60%增加径流量的间接作用.对于头道拐站,农作物耕作面积的增加使得流域总蒸发量增加,灌溉用水增加,在0.3流量分位数时有高达40%减少径流量的间接作用.该研究为气候变化与人类活动影响下黄河流域水资源优化配置提供重要理论依据.     

River Discharge and Water Level Changes in the Mekong River: Droughts in an Era of Mega-Dams

While 1992 marked the first major dam – Manwan – on the main stem of the Mekong River, the post-2010 era has seen the construction and operationalisation of mega dams such as Xiaowan (started operations in 2010) and Nuozhadu (started operations in 2014) that were much larger than any dams built before. The scale of these projects implies that their operations will likely have significant ecological and hydrological impacts from the Upper Mekong Basin to the Vietnamese Delta and beyond. Historical water level and water discharge data from 1960 to 2020 were analysed to examine the changes to streamflow conditions across three time periods: 1960–1991 (pre-dam), 1992–2009 (growth) and 2010–2020 (mega-dam). At Chiang Saen, the nearest station to the China border, monthly water discharge in the mega-dam period has increased by up to 98% during the dry season and decreased up as much as −35% during the wet season when compared to pre-dam records. Similarly, monthly water levels also rose by up to +1.16 m during the dry season and dropped by up to −1.55 m during the wet season. This pattern of hydrological alterations is observed further downstream to at least Stung Treng (Cambodia) in our study, showing that Mekong streamflow characteristics have shifted substantially in the post-2010 era. In light of such changes, the 2019–2020 drought – the most severe one in the recent history in the Lower Mekong Basin – was a consequent of constructed dams reducing the amount of water during the wet season. This reduction of water was exacerbated by the decreased monsoon precipitation in 2019. Concurrently, the untimely operationalisation of the newly opened Xayaburi dam in Laos coincided with the peak of the 2019–2020 drought and could have aggravated the dry conditions downstream. Thus, the mega-dam era (post-2010) may signal the start of a new normal of wet-season droughts.     

Plausible impact of global climate change on water resources in the Tarim River Basin

Combining the temperature and precipitation data from 77 climatological stations and the climatic and hydrological change data from three headstreams of the Tarim River: Hotan, Yarkant, and Aksu in the study area, the plausible association between climate change and the variability of water resources in the Tarim River Basin in recent years was investigated, the long-term trend of the hydrological time series including temperature, precipitation, and stream-flow was detected, and the possible association between the El Nino/Southern Oscillation (ENSO) and these three kinds of time series was tested. The results obtained in this study show that during the past years, the temperature experienced a significant monotonic increase at the speed of 5%, nearly 1℃rise; the precipitation showed a significant decrease in the 1970s, and a significant increase in the 1980s and 1990s, the average annual precipitation was increased with the magnitude of 6.8 mm per decade. A step change occurred in both temperature and     

Hydro-climatological changes in the Colorado River Basin over a century

This study evaluates changes in streamflow, temperature and precipitation over a time span of 105 years (1906–2010) in the Colorado River Basin (CRB). Monthly precipitation and temperature data for 29 climate divisions, and streamflow data for 29 naturalized gauges were analyzed. Two variations of the Mann-Kendall test, considering lag-1 auto correlation and long-term persistence, and the Pettitt test were employed to assess trends and shifts, respectively. Results indicated that streamflow increased during the winter–spring months and decreased during the summer– autumn period. Decreasing trends in winter precipitation were identified over snow-dominated regions in the upper basin. Significant increases in temperature were detected over several months. Major shifts were noticed in 1964, 1968 and in the late 1920s. Increasing temperature while decreasing streamflow and precipitation were noticed after major shifts in the 1930s, and these shifts coincided with coupled phases of El Niño Southern Oscillation and Pacific Decadal Oscillation.

EDITOR A. Castellarin; ASSOCIATE EDITOR R. Hirsch     

Sensitivity of hydrological variables to climate change in the Haihe River basin,China

Using the defined sensitivity index, the sensitivity of streamflow, evapotranspiration and soil moisture to climate change was investigated in four catchments in the Haihe River basin. Climate change contained three parts: annual precipitation and temperature change and the change of the percentage of precipitation in the flood season (P_f). With satisfying monthly streamflow simulation using the variable infiltration capacity model, the sensitivity was estimated by the change of simulated hydrological variables with hypothetical climatic scenarios and observed climatic data. The results indicated that (i) the sensitivity of streamflow would increase as precipitation or P_f increased but would decrease as temperature increased; (ii) the sensitivity of evapotranspiration and soil moisture would decrease as precipitation or temperature increased, but it to P_f varied in different catchments; and (iii) hydrological variables were more sensitive to precipitation, followed by P_f, and then temperature. The nonlinear response of streamflow, evapotranspiration and soil moisture to climate change could provide a reference for water resources planning and management under future climate change scenarios in the Haihe River basin. Copyright © 2011 John Wiley & Sons, Ltd.     

Influence of Three Gorges Dam on streamflow and sediment load of the middle Yangtze River, China

Using updated hydrological datasets from three stations, including Cuntan, Yichang and Hankou, covering the period of January 1992–December 2008, the influence of Three Gorges Dam (TGD) on streamflow and sediment load of the Yangtze River was investigated. Results indicated that TGD did not seem to exert a significant influence on streamflow occurring at three stations and changes in streamflow can be mainly attributed to streamflows of tributaries. However, a sharp decrease in the sediment load after the impoundment of TGD was observed. Clear water after the impoundment caused erosion of riverbed and resulted in more sediment at the Hankou station than at the Yichang station. No distinct changes in the annual and monthly maximum sediment loads were observed before and after the impoundment. Therefore, annual and monthly maximum sediment load changes should be subjected mainly to river hydraulics. This study has practical relevance for understanding the influence of large hydraulic structures on the hydrological processes of large rivers.     

Hydrological evaluation of the LPX dynamic global vegetation model for small river catchments in the UK

Assessments of water resources by using macro‐scale models tend to be conducted at the continental or large catchment scale. However, security of freshwater supplies is a local issue and thus necessitates study at such a scale. This research aims to evaluate the suitability of the Land Processes and eXchanges dynamic global vegetation model (LPX‐DGVM) for simulating runoff for small catchments in the UK. Simulated annual and monthly runoff is compared against the National River Flow Archive streamflow observations from 12 catchments of varying size (500–10 000 km²) and climate regimes. Results show that LPX reproduces observed inter‐annual and intra‐annual runoff variability successfully in terms of both flow timings and magnitudes. Inter‐annual variability in flow timings is simulated particularly well (as indicated by Willmott's index of agreement values of ≥0.7 for the majority of catchments), whereas runoff magnitudes are generally slightly overestimated. In the densely populated Thames catchment, these overestimations are partly accounted for by water consumption. Seasonal variability in runoff is also modelled well, as shown by Willmott's index of agreement values of ≥0.9 for all but one catchment. Absence of river routing and storage from the model, in addition to precipitation uncertainties, is also suggested as contributing to simulated runoff discrepancies. Overall, the results show that the LPX‐DGVM can successfully simulate runoff processes for small catchments in the UK. This study offers promising insights into the use of global‐scale models and datasets for local‐scale studies of water resources, with the eventual aim of providing local‐scale projections of future water distributions. Copyright © 2013 John Wiley & Sons, Ltd.