ALBERT

Description: The changes of runoff in the middle reaches of the Yellow River basin of China have received considerable attention owing to their sharply decline during recent decades. In this paper, the impacts of rainfall characteristics and land use and cover change on water yields in the Jingle sub-basin of the middle reaches of the Yellow River basin were investigated using a combination of statistical analysis and hydrological simulations. The Levenberg Marquardt and Analysis of Variance methods were used to construct multivariate, nonlinear, model equations between runoff coefficient and rainfall intensity and vegetation coverage. The land use changes from 1971 to 2017 were ascertained using transition matrix analysis. The impact of land use on water yields was estimated using the M-EIES hydrological model. The results show that the runoff during flood season (July to September) decreased significantly after 2000, whereas slightly decreasing trend was detected for precipitation. Furthermore, there were increase in short, intense, rainfall events after 2000 and this rainfall events were more conducive to flood generation. The “Grain for Green” project was carried out in 1999, and the land use in the middle reaches of the Yellow River improved significantly, which make the vegetation coverage (Vc) of the Jingle sub-basin increased by 13%. When Vc approaches 48%, the runoff coefficient decreased to the lowest, and the vegetation conditions have the greatest effect on reducing runoff. Both land use and climate can change the water yield in the basin, but for areas where land use has significantly improved, the impact of land use change on water yield plays a dominant role. The results acquired in this study provide a useful reference for water resources planning and soil and water conservation in the erodible areas of the middle reaches of the Yellow River basin.

Description: Recently water resources reanalysis (WRR) global streamflow products are emerging from high- resolution global models as a means to provide long and consistent global streamflow products for assessment of global challenge such as climate change. Like any other products, the newly developed global streamflow products have limitations accurately represent the dynamics of local streamflow hydrographs. There is a need to locally evaluate and apply correction factors for better representation and make use of the data. This research focuses on the evaluation and correction of the bias embedded in the global streamflow product (WRR, 0.25°) developed by WaterGAP3 hydrological model in the upper Blue Nile basin part of Ethiopia. Three spatiotemporal dynamical bias correction schemes (temporal-spatial variable, temporal-spatial constant and spatial variable) tested in twelve watersheds of the basin. The temporal-spatial variable dynamical bias correction scheme significantly improves the streamflow estimation. The Nash-Sutcliffe coefficient (NSCE) improves by 30% and bias decreases by 19% for the twelve streamflow gauging stations applying leave one out cross-validation approach in turn. Therefore, the temporal-spatial variable scheme is applicable and can use as one method for the bias correction to use the global data for local applications in the upper Blue Nile basin.

Description: Variable rate technology (VRT) in nutrient management has been developed in order to apply crop inputs according to the required amount of fertilizers. Meteorological conditions rarely differ within one field; however, differences in soil conditions responding to precipitation or evaporation results within field variations. These variations in soil properties such as moisture content, evapotranspiration ability, etc. requires site-specific treatments for the produced crops. There is an ongoing debate among experts on how to define management zones as well as how to define the required amount of fertilizers for phosphorus and nitrogen replenishment for winter wheat (Triticum aestivum L.) production. For management zone delineation, vegetation based or soil based data collection is applied, where various sensor technology or remote sensing is in help for the farmers. The objective of the study reported in this paper was to investigate the effect of soil moisture data derived from Sentinel-2 satellite images moisture index and variable rate phosphorus and nitrogen fertilizer by means of variable rate application (VRA) in winter wheat in Mezőföld, Hungary. Satellite based moisture index variance at the time of sowing has been derived, calculated and later used for data comparison. Data for selected points showed strong correlation (R2 = 0.8056; n = 6) between moisture index and yield, however generally for the whole field correlation does not appear. Vegetation monitoring has been carried out by means of NDVI data calculation. On the field level, as indicated earlier neither moisture index values at sowing nor vegetation index data was sufficient to determine yield. Winter wheat production based on VRA treatment resulted significant increase in harvested crop: 5.07 t/h in 2013 compared to 8.9 t/ha in 2018. Uniformly managed (control) areas provided similar yield as VRA treated areas (8.82 and 8.9 t/ha, respectively); however, the input fertilizer was reduced by 108 kg/ha N and increased by 37 kg/ha P.

Description: The knowledge of spatio-temporal dynamics of soil moisture within the catchment is very important for rainfall–runoff modelling in flood forecasting. In this study the comparison between remotely sensed soil moisture and soil moisture estimated from the SHETRAN hydrological model was performed for small and flashy Jičinka River catchment (75.9 km2) in the Czech Republic. Due to a relatively coarse spatial resolution of satellite data, the satellite soil moisture data were downscaled, by applying the method developed by Qu et al. (2015). The sub-grid variability of soil moisture was estimated on the basis of the mean soil moisture for the grid cell and the known hydraulic soil properties. The SHETRAN model was calibrated and verified to the observed streamflow hydrographs at the catchment outlet. The good correlation between the two different soil moisture information was obtained according to the majority of applied criteria. The results of the evaluation criteria indicate that the downscaled remotely sensed soil moisture data can be used as additional criteria for the calibration and validation of hydrological models for small catchments and can contribute to a better estimation of parameters, to reduce uncertainties of hydrological models and improve runoff simulations.

Description: It was shown that the use of biochar provides many benefits to agriculture by improving the whole complex of soil properties, including soil structure. However, the diverse range of biochar effects depends on its physicochemical properties, its application rates, soil initial properties etc. The impacts of biochar, mainly its reapplication to soils and its interaction with nitrogen in relation to water-stable aggregates (WSA) did not receive much attention to date. The aims of the study were: (1) to evaluate the effect of initial application (in spring 2014) and reapplication (in spring 2018) of different biochar rates (B0, B10 and B20 t ha−1) as well as application of biochar with N-fertilizer (40 to 240 kg N ha−1 depending on the requirement of the cultivated crop) on the content of WSA as one of the most important indicators of soil structure quality, (2) to assess the interrelationships between the contents of soil organic matter (SOM) and WSA. The study was conducted in 2017–2019 as part of the field experiment with biochar on Haplic Luvisol at the experimental station of SUA in Nitra, Slovakia. Results showed that initial application as well as reapplication of biochar improved soil structure. The most favorable changes in soil structure were found in N0B20B treatment (with biochar reapplication) at which a significantly higher content of water-stable macro-aggregates (WSAma) (+15%) as well as content of WSAma size fractions of 〉 5 mm, 5–3 mm, 3–2 mm and 2–1 mm (+72%, +65%, +57% and +64%, respectively) was observed compared to the control. An increase in SOM content, due to both, initial biochar application and its reapplication, significantly supported the stability of soil aggregates, while organic matter including humic substances composition did not.

Description: Analyses based on precipitation data may be limited by the quality of the data, the size of the available historical series and the efficiency of the adopted methodologies; these factors are especially limiting when conducting analyses at the daily scale. Thus, methodologies are sought to overcome these barriers. The objective of this work is to develop a hybrid model through the maximum overlap discrete wavelet transform (MODWT) to estimate daily rainfall in homogeneous regions of the Tocantins-Araguaia Hydrographic Region (TAHR) in the Amazon (Brazil). Data series from the Climate Prediction Center morphing (CMORPH) satellite products and rainfall data from the National Water Agency (ANA) were divided into seasonal periods (dry and rainy), which were adopted to train the model and for model forecasting. The results show that the hybrid model had a good performance when forecasting daily rainfall using both databases, indicated by the Nash–Sutcliffe efficiency coefficients (0.81–0.95), thus, the hybrid model is considered to be potentially useful for modelling daily rainfall.

Description: In this study, the value of proxy data was explored for calibrating a conceptual hydrologic model for small ungauged basins, i.e. ungauged in terms of runoff. The study site was a 66 ha Austrian experimental catchment dominated by agricultural land use, the Hydrological Open Air Laboratory (HOAL). The three modules of a conceptual, lumped hydrologic model (snow, soil moisture accounting and runoff generation) were calibrated step-by-step using only proxy data, and no runoff observations. Using this stepwise approach, the relative runoff volume errors in the calibration and first and second validation periods were –0.04, 0.19 and 0.17, and the monthly Pearson correlation coefficients were 0.88, 0.71 and 0.64, respectively. By using proxy data, the simulation of state variables improved compared to model calibration in one step using only runoff data. Using snow and soil moisture information for model calibration, the runoff model performance was comparable to the scenario when the model was calibrated using only runoff data. While the runoff simulation performance using only proxy data did not considerably improve compared to a scenario when the model was calibrated on runoff data, the more accurately simulated state variables imply that the process consistency improved.

Description: Large debris transported by flood affects scour features at bridge piers and increases the risks of structural failure. Geometric characteristics of the debris and the relative position of the pier with respect to the river bank are important parameters for the scour process. The interaction between the water flow and debris accumulation increases the shear stress, turbulence and consequently enhances the scour depth at the pier. This paper aims at analyzing such effects on scour evolution at bridge piers. To this end, two series of tests were carried out under clear water condition with different debris geometries and percentage blockage ratios. Experimental evidences showed that the pier position only influences scour evolution and equilibrium morphology for low water depths. Conversely, its effect becomes negligible for scour at bridge piers with debris accumulation and higher water depths. Useful practical relationships have been derived, with satisfactory prediction capability of the scour evolution for all the tested configurations.

Description: The study aimed to determine the linkage between soil exchangeable potassium (K+) concentration and stream water K+ concentration during rainfall and snowmelt events in small catchments with different land use (Carpathian Foothills, Poland). The complementary geochemical and hydrochemical approach used in the study produced new information on the role of particular soil horizons and contributing areas such as hillslope or riparian areas in K+ delivery to stream channels during events. Horizons lying above the nearly impermeable fragipan (Btx) play the most important role in the process of K+ influx to streams during most event types except snowmelts with frozen soils, in all the studied catchments. In the woodland catchment, rapid flushing of K+ from the topsoil Ah horizon with higher hydraulic conductivity (Ksat) and higher exchangeable K+ concentrations than in the lying lower E horizon resulted in a clockwise hysteresis of K+ in stream water during most events. In agricultural catchments, changes in stream water K+ concentration during events were determined by distinct differences between soil exchangeable K+ concentrations on hillslopes and in riparian areas.