A calibration-free evapotranspiration mapping technique for spatially-distributed regional-scale hydrologic modeling
Monthly evapotranspiration (ET) rates over Hungary for 2000-2008 are mapped at a spatial scale of about 1 km with the help of MODIS daytime land surface temperature as well as sunshine duration, air temperature and humidity data. Mapping is achieved by a linear transformation of MODIS daytime land surface temperature values employing the complementary relationship of evaporation. Validation of the ET rates has been performed at spatial scales spanning almost three magnitudes from a few hundred meters to about a hundred kilometers employing eddy-covariance (EC) measurements and catchment water balance closures. Typically the unbiased ET estimates are within 15% of EC values at a monthly basis, within 7% at an annual, and within only a few percent at a multi-year basis. The ET estimates yield an especially remarkable match (relative error of 0.2%, R2 = 0.95) with high-tower EC measurements at a monthly basis. The spatial distribution of the ET estimates confirm earlier, complex regional hydrologic model results and observations as well as yields a perfect estimate of the country's precipitation recycling index (the ratio of the multi-year mean ET and precipitation rates spatially aggregated for the whole country) of 89.2% vs an observed value of 89.6%. The CREMAP method is very simple, easy to implement, requires minimal data, calibration-free, and works accurately when conditions for the complementary relationship are met.
Remote-Sensing Based Groundwater Recharge Estimates in the Danube-Tisza Sand Plateau Region of Hungary
Mean annual recharge in the Danube-Tisza sand plateau region of Hungary over the 2000-2008 period was estimated at a 1-km spatial resolution as the difference of mean annual precipitation (P) and evapotranspiration (ET). The ET rates were derived from linear transformations of the MODIS daytime land surface temperature (Ts) values with the help of ancillary atmospheric data (air temperature, humidity, and sunshine duration). The groundwater under the sand plateau receives about 75 ± 50 mm of recharge annually (the plus/minus value is the associated error, resulting from an assumed 5% error in both the P and ET values), which is about 14 ± 9 % of the regional mean annual P value of 550 mm. The largest continuous region with elevated recharge rates (about 180 ± 50 mm a-1 or 30 ± 8 % of P) occur in the south-western part of the plateau due to more abundant precipitation (around 580 mm a-1), while recharge is the smallest (about 40 ± 40 mm a-1 or 7 ± 7 % of P) under forested areas. Typically, lakes, wetlands, river valleys, and certain afforested areas in the north-central part of the region act as discharge areas for groundwater.
The Bucket Wheel Excavator (BWE) is the main piece of harvesting equipment used in open-pit lignite or brown coal open-pit mines worldwide. Despite the continuous increase in size, productivity and technical sophistication in recent decades, they have not adapted to the changes of operating environment. In this respect, the increasingly frequent occurrence of hard inclusions – in terms of layers, boulders and other forms – has revealed a consistent failure of BWE-s to meet this challenge. This paper, inspired by the research project RFCR-CT-2015-00003-BEWEXMIN „Bucket wheel excavators operating under difficult mining conditions including un-mineable inclusions and geological structures with excessive mining resistance” deals with preliminary considerations and results that aim to contribute to solving this problem.
József András, József Kovács, Endre András, Ildikó Kertész and Ovidiu Bogdan Tomus
The bucket wheel excavator (BWE) is a continuous working rock harvesting device which removes the rock by means of buckets armoured with teeth, mounted on the wheel and which transfers rock on a main hauling system (generally a belt conveyor). The wheel rotates in a vertical plane and swings in the horizontal plane and raised / descended in the vertical plane by a boom. In this paper we propose a graphical-numerical method in order to calculate the power and energy requirements of the main harvesting structure (the bucket wheel) of the BWE. This approach - based on virtual models of the main working units of bucket wheel excavators and their working processes - is more convenient than those based on analytical formulas and simplification hypotheses, and leads to improved operation, reduced energy consumption, increased productivity and optimal use of available actuating power.
Viliam Nagy, Gábor Milics, Norbert Smuk, Attila József Kovács, István Balla, Márton Jolánkai, József Deákvári, Kornél D. Szalay, László Fenyvesi, Vlasta Štekauerová, Zoltán Wilhelm, Kálmán Rajkai, Tamás Németh and Miklós Neményi
A soil moisture content map is important for providing information about the distribution of moisture in a given area. Moisture content directly influences agricultural yield thus it is crucial to have accurate and reliable information about moisture distribution and content in the field. Since soil is a porous medium modified generalized Archie’s equation provides the basic formula to calculate moisture content data based on measured ECa. In this study we aimed to find a more accurate and cost effective method for measuring moisture content than manual field sampling. Locations of 25 sampling points were chosen from our research field as a reference. We assumed that soil moisture content could be calculated by measuring apparent electrical conductivity (ECa) using the Veris-3100 on-the-go soil mapping tool. Statistical analysis was carried out on the 10.791 ECa raw data in order to filter the outliers. The applied statistical method was ±1.5 interquartile (IRQ) distance approach. The visualization of soil moisture distribution within the experimental field was carried out by means of ArcGIS/ArcMAP using the inverse distance weighting interpolation method. In the investigated 25 sampling points, coefficient of determination between calculated volumetric moisture content data and measured ECa was R2 = 0.87. According to our results, volumetric moisture content can be mapped by applying ECa measurements in these particular soil types.