scholarly journals Global-scale evaluation of 23 precipitation datasets using gauge observations and hydrological modeling

2017 ◽  
Author(s):  
Hylke E. Beck ◽  
Noemi Vergopolan ◽  
Ming Pan ◽  
Vincenzo Levizzani ◽  
Albert I. J. M. van Dijk ◽  
...  
Keyword(s):  
Conceptual Model ◽  
Hydrological Modeling ◽  
Daily Precipitation ◽  
Comprehensive Evaluation ◽  
Global Scale ◽  
Scale Evaluation

Abstract. We undertook a comprehensive evaluation of 23 gridded (quasi-)global (sub-)daily precipitation (P) datasets for the period 2000–2016. Thirteen non-gauge-corrected P datasets were evaluated using daily P gauge observations from 76 086 gauges worldwide. Another ten gauge-corrected datasets were evaluated using hydrological modeling, by calibrating the conceptual model HBV against streamflow records for each of 9053 small to medium-sized (

scholarly journals Supplementary material to "Global-scale evaluation of 23 precipitation datasets using gauge observations and hydrological modeling"

2017 ◽  
Author(s):  
Hylke E. Beck ◽  
Noemi Vergopolan ◽  
Ming Pan ◽  
Vincenzo Levizzani ◽  
Albert I. J. M. van Dijk ◽  
...  
Keyword(s):  
Hydrological Modeling ◽  
Global Scale ◽  
Scale Evaluation ◽  
Supplementary Material

scholarly journals A framework to regionalize conceptual model parameters for global hydrological modeling

2020 ◽  
Author(s):  
Wenyan Qi ◽  
Jie Chen ◽  
Lu Li ◽  
Chong-yu Xu ◽  
Jingjing Li ◽  
...  
Keyword(s):  
Water Resources ◽  
Conceptual Model ◽  
Hydrological Modeling ◽  
Global Scale ◽  
Spatial Proximity ◽  
Model Parameters ◽  
Hydrological Models ◽  
Physical Similarity ◽  
Similarity Method ◽  
Global Water

Abstract. To provide an accurate estimate of global water resources and help to formulate water allocation policies, global hydrological models (GHMs) have been developed. However, it is difficult to obtain parameter values for GHMs, which results in large uncertainty in estimation of the global water balance components. In this study, a framework is developed for building GHMs based on parameter regionalization of catchment scale conceptual hydrological models. That is, using appropriate global scale regionalization scheme (GSRS) and conceptual hydrological models to simulate runoff at the grid scale globally and the Network Response Routing (NRF) method to converge the grid runoff to catchment streamflow. To achieve this, five regionalization methods (i.e. the global mean method, the spatial proximity method, the physical similarity method, the physical similarity method considering distance, and the regression method) are first tested for four conceptual hydrological models over thousands medium-sized catchments (2500–50000 km2) around the world to find the appropriate global scale regionalization scheme. The selected GSRS is then used to regionalize conceptual model parameters for global land grids with 0.5°×0.5° resolution on latitude and longitude. The results show that: (1) Spatial proximity method with the Inverse Distance Weighting (IDW) method and the output average option (SPI-OUT) offers the best regionalization solution, and the greatest gains of the SPI-OUT method were achieved with mean distance between the donor catchments and the target catchment is no more than 1500 km. (2) It was found the Kling-Gupta efficiency (KGE) value of 0.5 is a good threshold value to select donor catchments. And (3) Four different GHMs established based on framework were able to produce reliable streamflow simulations. Overall, the proposal framework can be used with any conceptual hydrological model for estimating global water resources, even though uncertainty exists in terms of using difference conceptual models.

Global-Scale Evaluation of 22 Precipitation Datasets Using Gauge Observations and Hydrological Modeling

2020 ◽  
pp. 625-653 ◽  
Author(s):  
Hylke E. Beck ◽  
Noemi Vergopolan ◽  
Ming Pan ◽  
Vincenzo Levizzani ◽  
Albert I. J. M. van Dijk ◽  
...  
Keyword(s):  
Hydrological Modeling ◽  
Global Scale ◽  
Scale Evaluation

scholarly journals Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling

2017 ◽  
Vol 21 (12) ◽  
pp. 6201-6217 ◽  
Author(s):  
Hylke E. Beck ◽  
Noemi Vergopolan ◽  
Ming Pan ◽  
Vincenzo Levizzani ◽  
Albert I. J. M. van Dijk ◽  
...  
Keyword(s):  
Hydrological Modeling ◽  
Comprehensive Evaluation ◽  
Microwave Remote Sensing ◽  
Global Scale ◽  
Estimation Accuracy ◽  
Near Surface ◽  
Temporal Correlations ◽  
Gauge Data ◽  
Spatio Temporal ◽  
Thermal Infrared Imagery

Abstract. We undertook a comprehensive evaluation of 22 gridded (quasi-)global (sub-)daily precipitation (P) datasets for the period 2000–2016. Thirteen non-gauge-corrected P datasets were evaluated using daily P gauge observations from 76 086 gauges worldwide. Another nine gauge-corrected datasets were evaluated using hydrological modeling, by calibrating the HBV conceptual model against streamflow records for each of 9053 small to medium-sized ( <  50 000 km2) catchments worldwide, and comparing the resulting performance. Marked differences in spatio-temporal patterns and accuracy were found among the datasets. Among the uncorrected P datasets, the satellite- and reanalysis-based MSWEP-ng V1.2 and V2.0 datasets generally showed the best temporal correlations with the gauge observations, followed by the reanalyses (ERA-Interim, JRA-55, and NCEP-CFSR) and the satellite- and reanalysis-based CHIRP V2.0 dataset, the estimates based primarily on passive microwave remote sensing of rainfall (CMORPH V1.0, GSMaP V5/6, and TMPA 3B42RT V7) or near-surface soil moisture (SM2RAIN-ASCAT), and finally, estimates based primarily on thermal infrared imagery (GridSat V1.0, PERSIANN, and PERSIANN-CCS). Two of the three reanalyses (ERA-Interim and JRA-55) unexpectedly obtained lower trend errors than the satellite datasets. Among the corrected P datasets, the ones directly incorporating daily gauge data (CPC Unified, and MSWEP V1.2 and V2.0) generally provided the best calibration scores, although the good performance of the fully gauge-based CPC Unified is unlikely to translate to sparsely or ungauged regions. Next best results were obtained with P estimates directly incorporating temporally coarser gauge data (CHIRPS V2.0, GPCP-1DD V1.2, TMPA 3B42 V7, and WFDEI-CRU), which in turn outperformed the one indirectly incorporating gauge data through another multi-source dataset (PERSIANN-CDR V1R1). Our results highlight large differences in estimation accuracy, and hence the importance of P dataset selection in both research and operational applications. The good performance of MSWEP emphasizes that careful data merging can exploit the complementary strengths of gauge-, satellite-, and reanalysis-based P estimates.

Groundwater phosphorus concentrations: global trends and links with agricultural and oil and gas activities

2021 ◽  
Author(s):  
Jessica Warrack ◽  
Mary Kang ◽  
Christian von Sperber
Keyword(s):  
Oil And Gas ◽  
Comprehensive Evaluation ◽  
Significant Risk ◽  
Surface Water Quality ◽  
The United States ◽  
Global Scale ◽  
Anthropogenic Sources ◽  
High Concentration ◽  
Oil And Gas Development ◽  
Global Trends

&lt;p&gt;Although observations show that anthropogenic phosphorus (P) can reach groundwater supplies, there has been no comprehensive evaluation of P in groundwater at the global scale. Additionally, there have been minimal studies on distributed sources, such as agriculture, and the effects of oil and gas activities on P contamination in groundwater are poorly understood. We compile and analyze 181,653 groundwater P concentrations from 13 government agencies and 8 individual research studies in 11 different countries in order to determine the extent of P pollution at the global scale. We find that every country with data has groundwater P concentrations that pose a significant risk of eutrophication to surface waters. In Canada and the United States, we study the relationship between land use, focusing on crop/pastureland, and increased P concentrations in groundwater. In Ontario and Alberta, two Canadian provinces with different histories of oil and gas development, we find areas with a high concentration of P groundwater pollution to coincide with regions of intense oil and gas activity. Understanding the effects of anthropogenic sources on phosphorus contamination of groundwater and identifying all possible pathways through which contamination can occur will assist regulators in planning and implementing effective strategies to manage groundwater and surface water quality and sustain ecosystem health.&lt;/p&gt;

scholarly journals Significant uncertainty in global scale hydrological modeling from precipitation data errors

2015 ◽  
Vol 529 ◽  
pp. 1095-1115 ◽  
Author(s):  
Frederiek C. Sperna Weiland ◽  
Jasper A. Vrugt ◽  
Rens (L.) P.H. van Beek ◽  
Albrecht H. Weerts ◽  
Marc F.P. Bierkens
Keyword(s):  
Hydrological Modeling ◽  
Global Scale ◽  
Precipitation Data ◽  
Data Errors

scholarly journals Global Increasing Trends in Annual Maximum Daily Precipitation

2013 ◽  
Vol 26 (11) ◽  
pp. 3904-3918 ◽  
Author(s):  
Seth Westra ◽  
Lisa V. Alexander ◽  
Francis W. Zwiers
Keyword(s):  
Surface Temperature ◽  
Daily Precipitation ◽  
Global Scale ◽  
Extreme Value Analysis ◽  
Trend Test ◽  
Precipitation Data ◽  
Annual Maximum ◽  
Value Analysis ◽  
Near Surface ◽  
Increasing Trends

Abstract This study investigates the presence of trends in annual maximum daily precipitation time series obtained from a global dataset of 8326 high-quality land-based observing stations with more than 30 years of record over the period from 1900 to 2009. Two complementary statistical techniques were adopted to evaluate the possible nonstationary behavior of these precipitation data. The first was a Mann–Kendall nonparametric trend test, and it was used to evaluate the existence of monotonic trends. The second was a nonstationary generalized extreme value analysis, and it was used to determine the strength of association between the precipitation extremes and globally averaged near-surface temperature. The outcomes are that statistically significant increasing trends can be detected at the global scale, with close to two-thirds of stations showing increases. Furthermore, there is a statistically significant association with globally averaged near-surface temperature, with the median intensity of extreme precipitation changing in proportion with changes in global mean temperature at a rate of between 5.9% and 7.7% K−1, depending on the method of analysis. This ratio was robust irrespective of record length or time period considered and was not strongly biased by the uneven global coverage of precipitation data. Finally, there is a distinct meridional variation, with the greatest sensitivity occurring in the tropics and higher latitudes and the minima around 13°S and 11°N. The greatest uncertainty was near the equator because of the limited number of sufficiently long precipitation records, and there remains an urgent need to improve data collection in this region to better constrain future changes in tropical precipitation.

scholarly journals Study on Evaluation of Timber Security in China Based on the PSR Conceptual Model

Forests ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 517
Author(s):  
Qiujuan Li ◽  
Shaozhi Chen ◽  
Rong Zhao
Keyword(s):  
Conceptual Model ◽  
Comprehensive Evaluation ◽  
Entropy Method ◽  
The State ◽  
High Tech ◽  
Key Factors ◽  
Factors Affecting ◽  
State Response ◽  
State Evaluation ◽  
Changing Trend

In case of a shortage of China’s domestic timber, the research of China’s timber security has become increasingly more important. Using the pressure-state–response (PSR) conceptual model and the entropy method, the timber security of China during 1997–2017 was evaluated and analyzed to understand and master the situation of timber security in this paper. The results showed that: (1) The pressure of timber security in China during 1997–2017 was increasing in waves, with the condition of timber imports as the main factor; (2) the state of timber security in China presented a downward-then-upward tendency during 1997–2017, the main influencing factors of which were the domestic timber supply and forest resources condition; (3) responses to ensure the timber security of China almost indicated a steep rising trend, because both the timber industry technical progress index and the waste paper recovery rate improved the safety of timber in China; and (4) the changing trend of the comprehensive evaluation of timber security in China approximately agrees with that of the state evaluation, which showed that state indicators were key factors affecting the timber security of China. The pressures influencing the timber security of China are rising, while the state of timber security and the responses of the high-tech industry have been improving at a higher range than the pressures, which has led to an improvement of China’s timber security.

scholarly journals Value of river discharge data for global-scale hydrological modeling

2007 ◽  
Vol 4 (6) ◽  
pp. 4125-4173 ◽  
Author(s):  
M. Hunger ◽  
P. Döll
Keyword(s):  
Correction Factor ◽  
River Discharge ◽  
Hydrological Modeling ◽  
Model Performance ◽  
Flow Characteristics ◽  
Global Scale ◽  
The Other ◽  
Station Correction ◽  
Discharge Data

Abstract. This paper investigates the value of observed river discharge data for global-scale hydrological modeling of a number of flow characteristics that are required for assessing water resources, flood risk and habitat alteration of aqueous ecosystems. An improved version of WGHM (WaterGAP Global Hydrology Model) was tuned in a way that simulated and observed long-term average river discharges at each station become equal, using either the 724-station dataset (V1) against which former model versions were tuned or a new dataset (V2) of 1235 stations and often longer time series. WGHM is tuned by adjusting one model parameter (γ) that affects runoff generation from land areas, and, where necessary, by applying one or two correction factors, which correct the total runoff in a sub-basin (areal correction factor) or the discharge at the station (station correction factor). The study results are as follows. (1) Comparing V2 to V1, the global land area covered by tuning basins increases by 5%, while the area where the model can be tuned by only adjusting γ increases by 8% (546 vs. 384 stations). However, the area where a station correction factor (and not only an areal correction factor) has to be applied more than doubles (389 vs. 93 basins), which is a strong drawback as use of a station correction factor makes discharge discontinuous at the gauge and inconsistent with runoff in the basin. (2) The value of additional discharge information for representing the spatial distribution of long-term average discharge (and thus renewable water resources) with WGHM is high, particularly for river basins outside of the V1 tuning area and for basins where the average sub-basin area has decreased by at least 50% in V2 as compared to V1. For these basins, simulated long-term average discharge would differ from the observed one by a factor of, on average, 1.8 and 1.3, respectively, if the additional discharge information were not used for tuning. The value tends to be higher in semi-arid and snow-dominated regions where hydrological models are less reliable than in humid areas. The deviation of the other simulated flow characteristics (e.g. low flow, inter-annual variability and seasonality) from the observed values also decreases significantly, but this is mainly due to the better representation of average discharge but not of variability. (3) The optimal sub-basin size for tuning depends on the modeling purpose. On the one hand, small basins between 9000 and 20 000 km2 show a much stronger improvement in model performance due to tuning than the larger basins, which is related to the lower model performance (with and without tuning), with basins over 60 000 km2 performing best. On the other hand, tuning of small basins decreases model consistency, as almost half of them require a station correction factor.

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