Search Results (40)

Reanalysis datasets provide a reliable reanalysis of climate input data for hydrological models in regions characterized by limited weather station coverage. In this paper, the accuracy of precipitation, the maximum and minimum temperatures of four reanalysis datasets, the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS), time-expanded climate forecast system reanalysis (CFSR+), the European Centre for Medium-Range Weather Forecast Reanalysis (ERA). and the China Meteorological Forcing Dataset (CMFD), were evaluated by using data from 28 ground-based observations (OBs) in the Source of the Yangtze and Yellow Rivers (SYYR) region and were used as input data for the SWAT model for runoff simulation and performance evaluation, respectively. And, finally, the CMADS was optimized using Integrated Calibrated Multi-Satellite Retrievals for Global Precipitation Measurement (AIMERG) data. The results show that CMFD is the most representative reanalysis data for precipitation characteristics in the SYYR region among the four reanalysis datasets evaluated in this paper, followed by ERA5 and CFSR, while CMADS performs satisfactorily for temperature simulations in this region, but underestimates precipitation. And we contend that the accuracy of runoff simulations is notably contingent upon the precision of daily precipitation within the reanalysis dataset. The runoff simulations in this region do not effectively capture the extreme runoff characteristics of the Yellow River and Yangtze River sources. The refinement of CMADS through the integration of AIMERG satellite precipitation data emerges as a potent strategy for enhancing the precision of runoff simulations. This research can provide a reference for selecting meteorological data products and optimization methods for hydrological process simulation in areas with few meteorological stations. Full article

A registered trademark represents one of a company’s most valuable intellectual assets, acting as a safeguard against possible reputational damage and financial losses resulting from infringements of this intellectual property. To be registered, a mark must be unique and distinctive in relation to other trademarks which are already registered. In this paper, we describe the CMAD, an acronym for Conflicting Marks Archive Dataset. This dataset has been meticulously organized into pairs of marks (Number of pairs = 18,355) involved in copyright infringement across word, figurative and mixed marks. Organizations sought to register these marks with the National Institute of Industrial Property (INPI) in Brazil, and had their applications denied after analysis by intellectual property specialists. The robustness of this dataset is ensured by the intrinsic similarity of the conflicting marks, since the decisions were made by INPI specialists. This characteristic provides a reliable basis for the development and testing of tools designed to analyze similarity between marks, thus contributing to the evolution of practices and computer-based solutions in the field of intellectual property. Full article

Climate and land-use change significantly impact hydrological processes and water resources management. However, studies of runoff simulation accuracy and attribution analysis in large-scale basins based on multi-source data and different scenario projections are limited. This study employed the Soil and Water Assessment Tool (SWAT) model in conjunction with spatial interpolation techniques to evaluate the accuracy of Climate Forecast System Reanalysis (CFSR), China Meteorological Assimilation Driven Dataset (CMADS), and observation (OBS) in runoff simulations, and configured various scenarios using the Patch-generating Land-use Simulation (PLUS) model to analyze effects of climate and land-use changes on runoff in the Jing River Basin from 1999 to 2018. Results demonstrated the superior performance of the CMADS+SWAT model compared to than CFSR+SWAT model, as the latter underestimated peak runoff. Changes in precipitation had a stronger impact on runoff than temperature, with increased flow from farmland and strong interception effects from forestland. Integrated climate and land-use changes led to an average annual runoff reduction of 1.24 m³/s (I₂), primarily attributed to climate change (1.12 m³/s, I₃), with a small contribution from land-use change (0.12 m³/s, I₄). CMADS exhibited robust applicability under diverse scenarios, effectively enhancing runoff simulation accuracy. The findings provide invaluable guidance for water resources management in semi-arid regions. Full article

Multisource meteorological re-analyses provide the most reliable forcing data for driving hydrological models to simulate streamflow. We aimed to assess different hydrological responses through hydrological modeling in the upper Lancang-Mekong River Basin (LMRB) using two gridded meteorological datasets, Climate Forecast System Re-analysis (CFSR) and the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS). We selected the Pearson’s correlation coefficient (R), percent bias (PBIAS), and root mean square error (RMSE) indices to compare the six meteorological variables of the two datasets. The spatial distributions of the statistical indicators in CFSR and CMADS, namely, the R, PBIAS, and RMSE values, were different. Furthermore, the soil and water assessment tool plus (SWAT+) model was used to perform hydrological modeling based on CFSR and CMADS meteorological re-analyses in the upper LMRB. The different meteorological datasets resulted in significant differences in hydrological responses, reflected by variations in the sensitive parameters and their optimal values. The differences in the calibrated optimal values for the sensitive parameters led to differences in the simulated water balance components between the CFSR- and CMADS-based SWAT+ models. These findings could help improve the understanding of the strengths and weaknesses of different meteorological re-analysis datasets and their roles in hydrological modeling. Full article

Few studies have been conducted to simulate watersheds with insufficient meteorological and hydrological information. The Jiyun River watershed was selected as the study area. A suitable catchment area threshold was determined by combining the river network density method with the Soil and Water Assessment Tool (SWAT) models, which was driven using the CMADS dataset (China Meteorological Assimilation Driving Datasets for the SWAT model). Monthly runoff simulations were conducted for the basin from 2010 to 2014, and the calibration and validation of model parameters were completed with observed data. The results showed that the final expression for the density of the river network in the Jiyun River basin as a function of density (y) and the catchment area threshold (x) was obtained as y = 926.782x^−0.47717. The “inflection point” of the exponential function was the optimal catchment area threshold. The catchment area threshold had an upper and lower limit of the applicable range and was related to the percentage of the total basin area. The simulation results would be affected if the threshold values were outside the suitable scope. When the catchment area was 1.42% of the entire watershed area, increasing the threshold value had less effect on the runoff simulation results; decreasing the threshold value would cause the simulation results to be unstable. When the catchment area reached 1.42% to 2.33% of the total watershed area, the simulation results were in good agreement with the observed values; the coefficient of determination (R²) and Nash–Sutcliffe efficiency coefficient (NSE) were more significant than 0.79 and 0.78 for the calibration periods evaluation index. Both were greater than 0.77 and 0.76 for the validation period, which met the evaluation requirements of the model. The results showed that the CMADS-driven SWAT model applied to the runoff simulation and the river network density method adoption to determine the catchment area threshold provided a theoretical basis for a reasonable sub-basin division in the Jiyun River basin. Full article

Multisource meteorological precipitation products are an important way to make up for a lack of observation sites or a lack of precipitation data in areas with a complex topography. They have important value for local industrial, agricultural, and ecological water use calculations, as well as for water resource evaluation and management. The Yunnan-Kweichow Plateau is located in southwest China and has a relatively backward economy and few meteorological stations. At the same time, the terrain is dominated by mountain valleys, precipitation is greatly affected by the terrain, and meteorological data are lacking, making the calculation of local water resources difficult. In this study, the applicability of the 3-hourly merged high-quality/IR estimates (3B42) of the Tropical Rainfall Measuring Mission (TRMM), China Meteorological Forcing Dataset (CMFD), and China Meteorological Assimilation Driving Datasets (CMADS) in the Yunnan-Kweichow Plateau was analyzed using multiple evaluation indicators of different temporal scales and precipitation intensity levels as well as the spatial distribution of the indicators based on measured daily precipitation data from 59 national meteorological basic stations in the study area in 2008–2018. The results showed that (1) the three products had performed well and could be applied to the calculation of local water resources with CMFD performing the best; (2) the performance of precipitation products was slightly worse on the daily scale, and the overall performance of the yearly, quarterly, and monthly scales was better; (3) good results were achieved in most regions, but there were also some regions with prominent overestimation and underestimation; (4) the three precipitation products had the highest probabilities of detection and the lowest false alarm rates for no rain and light rain, and the probability of detection gradually decreased with an increase in the precipitation intensity; and (5) the mean absolute error of precipitation products in rainy months is large, so the accuracy of products in the calculation of heavy rain and flood will be limited. Full article

In order to solve the problem of H₂S corrosion in biogas utilization, it is necessary to understand the characteristics and mechanisms of H₂S production in chicken manure anaerobic digestion (CMAD) and vegetable waste anaerobic digestion (VWAD). In this study, lab-scale batch tests of CMAD and VWAD were conducted for 67 days at 35 °C. The results showed that sulfide was found to be the major form of sulfur in CMAD (accounting for 90%) and VWAD (70%). The average concentration of H₂S was 198 ± 79 ppm in CMAD and 738 ± 210 ppm in VWAD. Moreover, 81% of total H₂S was produced at 20 days of methane production in CMAD, but 80% of total H₂S was produced in the first day in VWAD because of the rapid production of biogas and fermentation acidification. The sulfide ion equilibrium model could universally and feasibly predict the H₂S production in CMAD and VWAD. The abundance of Firmicutes, Bacteroidetes, Proteobacteria and Euryarchaeota accounted for about 95% of the total microbes in both CMAD and VWAD; the influence of the fermentation stage on the microbial community was greater than that of the difference between CM and VW; the abundance of SRB was 0.01~0.07%, while that concerning organosulfur compounds fermentation was 22.8~30.5%. This study indicated that the H₂S concentration of CMAD biogas was more than five times that of VWAD because CM is alkalescent but VW is acidic. Full article

This study assessed the performance of two well-known gridded meteorological datasets, CFSR (Climate Forecast System Reanalysis) and CMADS (China Meteorological Assimilation Driving Datasets), and three satellite-based precipitation datasets, TRMM (Tropical Rainfall Measuring Mission), CMORPH (Climate Prediction Center morphing technique), and CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), in driving the SWAT (Soil and Water Assessment Tool) model for streamflow simulation in the Fengle watershed in the middle–lower Yangtze Plain, China. Eighteen model scenarios were generated by forcing the SWAT model with different combinations of three meteorological datasets and six precipitation datasets. Our results showed that (1) the three satellite-based precipitation datasets (i.e., TRMM, CMORPH, and CHIRPS) generally provided more accurate precipitation estimates than CFSR and CMADS. CFSR and CMADS agreed fairly well with the gauged measurements in maximum temperature, minimum temperature, and relative humidity, but large discrepancies existed for the solar radiation and wind speed. (2) The impact of precipitation data on simulated streamflow was much larger than that of other meteorological variables. Satisfactory simulations were achieved using the CMORPH precipitation data for daily streamflow simulation and the TRMM and CHIRPS precipitation data for monthly streamflow simulation. This suggests that different precipitation datasets can be used for optimal simulations at different temporal scales. Full article

Precipitation has been recognized as the most critical meteorological parameter in hydrological studies. Recent developments in space technology provide cost-effective alternative ground-based observations to simulate the hydrological process. Here, this paper aims to evaluate the performance of satellite-based datasets in the hydrological modeling of a sensitive area in terms of water quality and safety watershed. Three precipitation products, i.e., rain gauge observations (RO), the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS), and Tropical Rainfall Measuring Mission Multi-satellite (TRMM) products, were used to develop the Soil and Water Assessment Tool (SWAT) model to simulate the streamflow in the Danjiang River Basin (DRB). The results show that: (1) these three precipitation products have a similar performance with regard to monthly time scale compared with the daily scale; (2) CMADS and TRMM performed better than RO in the runoff simulations. CMADS is a more accurate dataset when combined with satellite-based and ground-based data; (3) the results indicate that the CMADS dataset provides reliable results on both monthly and daily scales, and CMADS is a possible alternative climate product for developing a SWAT model for the DRB. This study is expected to serve as a reference for choosing the precipitation products for watersheds similar to DRB where the rain gauge data are limited. Full article

From 15 to 20 September 2016, precipitation extremes occurred in the middle and lower reaches of the Jinsha River, causing immense direct economic losses due to floods. The current research on extreme climate characteristics and the relationship between climate extremes and runoff extremes are based on a single data source. This is due to the uneven distribution of precipitation and temperature stations, which make it difficult to fully capture extreme climate events. In this paper, various internationally popular reanalysis datasets were introduced. Extreme climate indexes were computed using the merged datasets versus the meteorological station observations. The results showed that: (1) Comparative analysis of the extreme climate indexes of the reanalysis dataset and the data of traditional meteorological observation stations showed that most of the extreme precipitation indexes calculated by the various reanalysis of combined data exhibited good performances. Among the reanalyzed combined products, CMPA-H, CMADS, and GPM (IMERG) exhibited good performance while the performance of TRMM (TMPA) was slightly worse. The extreme temperature indexes, TXx and TNn, calculated based on the reanalysis of combined data showed a better consistency than the indexes calculated based on the observational data of meteorological stations. The CMADS temperature dataset exhibited a higher consistency with the data obtained from meteorological stations as well as the best accuracy (84% of the stations with the error value of TXx calculated from the CMADS dataset and observed data less than 3 °C). (2) The response of typical flood events to precipitation extremes were analyzed and evaluated; the spatial distribution of the precipitation in the combined dataset was used to quantitatively analyze the response of occurrence of typical flood events to precipitation extremes, and the typical flood events were found to be mainly caused by certain factors, such as lagging flood propagation in the upstream of the basin outlet. This study indicates that it is feasible to use the reanalyzed combined data products to calculate the extreme climate indexes of the Jinsha River Basin, especially in the upper reaches of the Yangtze River where there is a lack of meteorological observation stations. Full article

To improve knowledge of this matter, the potential application of two gridded meteorological products (GMPs), the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) and Climate Forecast System Reanalysis (CFSR), are compared for the first time with data from ground-based meteorological stations over 6 years, from 2008 to 2013, over the Cau River basin (CRB), northern Vietnam. Statistical indicators and the Soil and Water Assessment Tool (SWAT) model are employed to investigate the hydrological performances of the GMPs against the data of 17 rain gauges distributed across the CRB. The results show that there are strong correlations between the temperature reanalysis products in both CMADS and CFSR and those obtained from the ground-based observations (the correlation coefficients range from 0.92 to 0.97). The CFSR data overestimate precipitation (percentage bias approximately 99%) at both daily and monthly scales, whereas the CMADS product performs better, with obvious differences (compared to the ground-based observations) in high-terrain areas. Regarding the simulated river flows, CFSR-SWAT produced “unsatisfactory”, while CMADS-SWAT (R² > 0.76 and NSE > 0.78) performs better than CFSR-SWAT on the monthly scale. This assessment of the applicative potential of GMPs, especially CMADS, may further provide an additional rapid alternative for water resource research and management in basins with similar hydro-meteorological conditions. Full article

It is of great convenience to map daily evapotranspiration (ET) by remote sensing for agricultural water management without computing each surface energy component. This study used the operational simplified surface energy balance (SSEBop) and the remote sensing-based Penman–Monteith and Priestly–Taylor (RSPMPT) models to compute continuous daily ET over irrigated fields with the MODIS and CMADS data. The estimations were validated with eddy covariance (EC) measurements. Overall, the performance of RSPMPT with locally calibrated parameters was slightly better than that of SSEBop, with higher NSE (0.84 vs. 0.78) and R² (0.86 vs. 0.81), lower RMSE (0.78 mm·d⁻¹ vs. 0.90 mm·d⁻¹), although it had higher bias (0.03 mm·d⁻¹ vs. 0.01 mm·d⁻¹) and PBias (1.41% vs. 0.59%). Due to the consideration of land surface temperature, the SSEBop was more sensitive to ET’s change caused by irrigation before sowing in March and had a lower PBias (6.7% vs. 39.8%) than RSPMPT. On cloudy days, the SSEBop is more likely to overestimate ET than the RSPMPT. To conclude, driven by MODIS and CMADS data, the two simple models can be easily applied to map daily ET over cropland. The SSEBop is more practical in the absence of measured data to optimize the RSPMPT model parameters. Full article

Identification of reliable alternative climate input data for hydrological modelling is important to manage water resources and reduce water-related hazards in ungauged or poorly gauged basins. This study aims to evaluate the capability of the National Centers for Environmental Prediction Climate Forecast System Reanalysis (NCEP-CFSR) and China Meteorological Assimilation Driving Dataset for the Soil and Water Assessment Tool (SWAT) model (CMADS) for simulating streamflow in the Muda River Basin (MRB), Malaysia. The capability was evaluated in two perspectives: (1) the climate aspect—validation of precipitation, maximum and minimum temperatures from 2008 to 2014; and (2) the hydrology aspect—comparison of the accuracy of SWAT modelling by the gauge station, NCEP-CFSR and CMADS products. The results show that CMADS had a better performance than NCEP-CFSR in the climate aspect, especially for the temperature data and daily precipitation detection capability. For the hydrological aspect, the gauge station had a “very good” performance in a monthly streamflow simulation, followed by CMADS and NCEP-CFSR. In detail, CMADS showed an acceptable performance in SWAT modelling, but some improvements such as bias correction and further SWAT calibration are needed. In contrast, NCEP-CFRS had an unacceptable performance in validation as it dramatically overestimated the low flows of MRB and contains time lag in peak flows estimation. Full article

The lack of meteorological observation data limits the hydro-climatic analysis and modeling, especially for the ungauged or data-limited regions, while satellite and reanalysis products can provide potential data sources in these regions. In this study, three daily products, including two satellite products (Tropic Rainfall Measuring Mission Multi-Satellite Precipitation Analysis, TMPA 3B42 and 3B42RT) and one reanalysis product (China Meteorological Assimilation Driving Datasets for the SWAT Model, CMADS), were used to assess the capacity of hydro-climatic simulation based on the statistical method and hydrological model in Ganjiang River Basin (GRB), a humid basin of southern China. CAMDS, TMPA 3B42 and 3B42RT precipitation were evaluated against ground-based observation based on multiple statistical metrics at different temporal scales. The similar evaluation was carried out for CMADS temperature. Then, eight scenarios were constructed into calibrating the Soil and Water Assessment Tool (SWAT) model and simulating streamflow, to assess their capacity in hydrological simulation. The results showed that CMADS data performed better in precipitation estimation than TMPA 3B42 and 3B42RT at daily and monthly scales, while worse at the annual scale. In addition, CMADS can capture the spatial distribution of precipitation well. Moreover, the CMADS daily temperature data agreed well with observations at meteorological stations. For hydrological simulations, streamflow simulation results driven by eight input scenarios obtained acceptable performance according to model evaluation criteria. Compared with the simulation results, the models driven by ground-based observation precipitation obtained the most accurate streamflow simulation results, followed by CMADS, TMPA 3B42 and 3B42RT precipitation. Besides, CMADS temperature can capture the spatial distribution characteristics well and improve the streamflow simulations. This study provides valuable insights for hydro-climatic application of satellite and reanalysis meteorological products in the ungauged or data-limited regions. Full article

As a key factor in the water cycle and climate change, the quality of precipitation data directly affects the hydrological processes of the river basin. Although many precipitation products with high spatial and temporal resolutions are now widely used, it is meaningful and necessary to investigate and evaluate their merits and demerits in hydrological applications. In this study, two satellite-based precipitation products (Tropical Rainfall Measurement Mission, TRMM; Integrated Multi-satellite Retrievals for GPM, IMERG) and one reanalysis precipitation product (China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model, CMADS) are studied to compare their streamflow simulation performance in the Qujiang River Basin, China, using the SWAT model with gauged rainfall data as a reference. The main conclusions are as follows: (1) CMADS has stronger precipitation detection capabilities compared to gauged rainfall, while TRMM results in the most obvious overestimation in the four sub-basins. (2) In daily and monthly streamflow simulations, CMADS + SWAT mode offers the best performance. CMADS and IMERG can provide high quality precipitation data for data-scarce areas, and IMERG can effectively avoid the overestimation of streamflow caused by TRMM, especially on a daily scale. (3) The runoff projections of the three modes under RCP (Representative Concentration Pathway) 4.5 was higher than that of RCP 8.5 on the whole. IMERG + SWAT overestimates the surface water resources of the basin compared to CMADS + SWAT, while TRMM + SWAT provides the most stable uncertainty. These findings contribute to the comparison of the differences among the three precipitation products and provides a reference for the selection of precipitation data in similar regions. Full article