Hemp currently regains certain importance as fiber, oil and medical crop not least because of its modest requirements of biocides, fertilizer and water. During recent years, crops were exposed to a combination of drought and heat, even in northern Central-Europe. Dynamic responses of photosynthesis and stomatal conductance to these stresses and their persistent effects had been studied, if at all, in controlled environment experiments. Comprehensive field studies on diurnal and long-term net photosynthesis and gas exchange, and yield properties of hemp during a drought prone, high-temperature season in northern Central-Europe are obviously missing. Thus, in whole season field trails, the essential actual physiological (rates of net photosynthesis and transpiration, stomatal conductance, water use efficiencies, ambient and internal CO₂ concentrations) and the yield performance of modern high-yielding multi-purpose hemp cultivars, ‘Ivory’ and ‘Santhica 27’, were evaluated under extreme environmental conditions and highly limited soil water supply. This provides comprehensive information on the usability of these cultivars under potential future harsh production conditions. Plants of both cultivars differentially cope with the prevailing climatic and soil water conditions. While ‘Ivory’ plants developed high rates of CO₂ gain and established large leaf area per plant in the mid-season, those of ‘Santhica 27’ utilized lower CO₂ uptake rates at lower leaf area per plant most time. This and the higher germination success of ‘Santhica 27’ resulted in nearly twice the yield compared to ‘Ivory’. Although stomatal control of CO₂ gain was pronounced in both cultivars, higher stomatal limitations in ‘Ivory’ plants resulted in higher overall intrinsic water use efficiency. Cultivation of both hemp cultivars with only basic irrigation during seed germination was successful and without large effects on yield and quality. This was valid even under extremely hot and dry climatic conditions in northern Central Europe.

The working group "Adaptation to Climate Change" at the Leibniz-Institute for Agricultural Engineering Potsdam-Bornim (ATB) is introduced. This group calculates the water footprint for agricultural processes and farms, distinguished into green water footprint, blue water footprint, and dilution water footprint. The green and blue water demand of a dairy farm plays a pivotal role in the regional water balance. Considering already existing and forthcoming climate change effects there is a need to determine the water cycle in the field and in housing for process chain optimisation for the adaptation to an expected increasing water scarcity. Resulting investments to boost water productivity and to improve water use efficiency in milk production are two pathways to adapt to climate change effects. In this paper the calculation of blue water demand for dairy farming in Brandenburg (Germany) is presented. The water used for feeding, milk processing, and servicing of cows over the time period of ten years was assessed in our study. The preliminary results of the calculation of the direct blue water footprint shows a decreasing water demand in the dairy production from the year 1999 with 5.98×10⁹ L/yr to a water demand of 5.00×10⁹ L/yr in the year 2008 in Brandenburg because of decreasing animal numbers and an improved average milk yield per cow. Improved feeding practices and shifted breeding to greater-volume producing Holstein-Friesian cow allow the production of milk in a more water sustainable way. The mean blue water consumption for the production of 1 kg milk in the time period between 1999 to 2008 was 3.94±0.29 L. The main part of the consumed water seems to stem from indirect used green water for the production of feed for the cows.

Water is used in dairy farming for producing feed, watering the animals, and cleaning and disinfecting barns and equipment. The objective of this study was to investigate the drinking and cleaning water use in a dairy cow barn. The water use was measured on a well-managed commercial dairy farm in North-East Germany. Thirty-eight water meters were installed in a barn with 176 cows and two milking systems (an automatic milking system and a herringbone parlour). Their counts were logged hourly over 806 days. On average, the cows in the automatic milking system used 91.1 (SD 14.3) L drinking water per cow per day, while those in the herringbone parlour used 54.4 (SD 5.3) L per cow per day. The cows drink most of the water during the hours of (natural and artificial) light in the barn. Previously published regression functions of drinking water intake of the cows were reviewed and a new regression function based on the ambient temperature and the milk yield was developed (drinking water intake (L per cow per day) = −27.937 + 0.49 × mean temperature + 3.15 × milk yield (R² = 0.67)). The cleaning water demand had a mean of 28.6 (SD 14.8) L per cow per day in the automatic milking system, and a mean of 33.8 (SD 14.1) L per cow per day in the herringbone parlour. These findings show that the total technical water use in the barn makes only a minor contribution to water use in dairy farming compared with the water use for feed production.

Indicators for water use at farm scale can assist farmers in understanding the water flows on their farms and in optimizing water use by adapting agronomic measures and farm management. The objective of this work is to develop a methodology to estimate water flows at the farm scale, to derive indicators for farm water use, and to apply them in a first case study. After the spatial and temporal boundaries of the farm system and the water flows are defined, three indicators to assess water use at the farm scale are developed: farm water productivity, degree of water utilization, and specific inflow of technical water. Farm water productivity describes the ratio of farm output to water input, where the water input is the total of those water inflows into the farm system that can be assigned to the generation of farm output. Farm output is expressed on a mass basis, food energy basis, and monetary basis. The degree of water utilization characterizes the relationship between productive water to the total water inflow into the farm system, where productive water comprises those water flows that directly contribute to biomass generation via plant and animal metabolism. The specific technical water inflow quantifies the water inflow into the system by technical means relative to the farm area. The application of the methodology in a first case study for a mixed crop‐livestock farm with 2869 ha in Germany results in a farm water productivity of 2.30 kg fresh mass per , 1.03 kg dry mass per , 5.96 GJ , and 0.25 € . The degree of water utilization is 0.56. The specific technical water inflow is 36.5 m³ ha⁻¹ year⁻¹. Factors that mainly effect these indicators and general approaches to optimize water use in farms are discussed as well as the further research required for practical implementation.

In this study, the split window (SW) method was applied for land surface temperature (LST) retrieval using Landsat 8 in two apple orchards (Glindow, Altlandsberg). Four images were acquired during high demand of irrigation water from July to August 2018. After pre-processing images, the normalized difference vegetation index (NDVI) and LST were calculated by red, NIR, and thermal bands. The results were validated by interpolated infrared thermometer (IRT) measurements using the inverse distance weighting (IDW) method. In the next step, the temperature vegetation index (TVDI) was calculated based on the trapezoidal NDVI/LST space to determine the water status of apple trees in the case studies. Results show good agreement between interpolated LST using IRT measurements and remotely sensed LST calculation using SW in all satellite overpasses, where the absolute mean error was between 0.08 to 4.00 K and root mean square error (RMSE) values ranged between 0.71 and 4.23 K. The TVDI spatial distribution indicated that the trees suffered from water stress on 7 and 23 July and 8 August 2018 in Glindow apple orchard with the mean value of 0.69, 0.57, and 0.73, whereas in the Altlandsberg orchard on 17 August, the irrigation system compensated the water deficit as indicated by the TVDI value of 0.34. Moreover, a negative correlation between TVDI and vegetation water content (VWC) with correlation coefficient (r) of −0.81 was observed. The corresponding r for LST and VWC was equal to −0.89, which shows the inverse relation between water status and temperature-based indices. The results indicate that the LST and/or TVDI calculation using the proposed methods can be effectively applied for monitoring tree water status and support irrigation management in orchards using Landsat 8 satellite images without requiring ground measurements.