Water Management of Czech Crop Production in 1961–2019

This study aims to evaluate the water balance of the crop mix of the Czech Republic and the tendencies of its development during the period 1961–2019. For calculating water deficits, methodology from ČSN 750434 (Czech technical standards) was used and on its basis, the deficits of the ten most frequently represented crops of the Czech Republic were calculated. These results were then put into the context of the development of precipitation totals and the development of average annual temperatures in the observed period. Furthermore, statistical tools were used for the identification of relationships between the observed variables and the tested hypotheses to verify the statistical significance of the observed changes. The results show that the overall irrigation deficit nearly doubled in Czech agriculture when comparing the averages for the periods 1961–1970 and 2010–2019. This change was evaluated as statistically significant. Furthermore, there were also statistically significant increases in water deficits in the cases of wheat, barley, rye, oats, legumes, and rapeseed. The sowing areas of the observed crops recorded statistically significant change in all cases. Only in the case of wheat, maize and rapeseed were there increases in sowing area, specifically 146%, 642.4%, and 1132.7%, respectively. For other crops, a decrease in sowing areas was observed. This finding points to decreasing commodity diversity in Czech agriculture, which, in combination with a high degree of intensification and selected agrotechnical practices, contributes to a lower retention capacity for the soil and landscape to retain water, which in turn influences the overall water balance of the Czech agrarian sector.

A GIS based application of Benfratello's method to estimate the irrigation deficit in a semiarid climate

<p>Benfratello's <em>Contribution to the study of the water balance of an agricultural soil</em> (<em>Contributo allo studio del bilancio idrologico del terreno agrario</em>) was firstly published sixty years ago, in 1961. The paper provides a practical conceptual and lumped method to determine the irrigation deficit in agricultural disctricts. Since then, it has been used in many areas in Southern Italy.</p><p>According to the method, percolation and capillary rise from the groundwater table are absent, and surface runoff happens only when the soil capability of storing water is exceeded. The method is therefore suitable for semiarid (and eventually arid) climates. Dry and wet seasons are defined on a climatic basis, as the season during which potential evapotranspiration is greater than precipitations (and the stored soil--water decreases), and that during which precipitations exceed potential evapotranspiration (and the stored soil--water inccreases).</p><p>With these hypotheses, Benfratello proposed to adopt a power--relationship (with power <em>m</em> greater or equal to 0) to assess the ratio between the actual and the potential soil--water loss, as a function of the ratio between the stored soil--water and the maximum available storage. The solution provides, in a simple closed form, the actual soil--water loss as a function of the potential loss (which is a climatic characteristic), and generalizes previous approaches, viz Thorthwaite (1948) and Thornthwaite and Mather (1955) ones, for which <em>m</em> = 0 and <em>m</em> = 1, respectively.</p><p>In this contribution we present a GIS based application of Benfratello's method to assess the soil water balance and the irrigation deficit of the semiarid Capitanata plane (4550 <em>km</em><sup>2</sup>, Southern Italy), one of the most important agricultural districts in Italy. A comparison between the method and previous results for the same region will be provided as well. Due to its simplicity and to the small number of needed parameters, Benfratello's method might be regarded to as an effective tool to assess the effects of climatic, landuse and anthropogenic change scenarios on the soil water balance and on the irrigation deficit.</p>

Assessments of Humic Substances Application and Deficit Irrigation in Triploid Watermelon

Soil organic matter degradation and water limitation caused by intense farming activities are some of the major threats affecting agricultural production. Accordingly, the concepts of sustainable agricultural systems with optimized irrigation and improved soil quality can be adapted to address these issues. During this 2-year field study, two management factors—humic substances (HS) as organic inputs (HS vs. control) and deficit irrigation as the irrigation method (50% vs. 100% based on evapotranspiration)—were evaluated based on triploid watermelon (Citrullus lanatus cv. Fascination) yield and soil property changes. HS application increased watermelon early yield by 38.6% and total yield by 11.8% compared with the control; the early yield mainly increased under deficit irrigation. Compared with full irrigation, deficit irrigation increased water use efficiency (WUE) without significantly affecting total yield. In addition, HS application significantly increased the soil organic carbon (SOC) content, which was found to be positively correlated with crop WUE. These results indicate that soil organic inputs with HS and deficit irrigation are valuable strategies to establish sustainable systems for watermelon production, which will not only increase yield and WUE but also significantly improve soil quality and save irrigation water.

Growth and Yield Response of Different Brinjal Cultivars to Irrigation Deficit Conditions

Brinjal is an important vegetable crop having low fat content and high nutritional value. Brinjal is considered moderately sensitive to water deficit conditions. A study was conducted to investigate growth and yield potential of different brinjal cultivars i.e. ‘Black Long’, ‘Nirala’, ‘Bemisal’ and ‘Purple Queen’ in response to various levels of water stress by providing 100, 80 and 60% of the required irrigation. The results revealed that growth and yield characteristics of brinjal cultivars varied to a great extent in response to water stress. As expected, 100% irrigation level showed the highest plant growth and fruit yield, while a gradual decrease in growth and yield of brinjal was observed with increasing water stress, the lowest being at 60% irrigation level. ‘Black Long’ and ‘Nirala’ produced significantly better results for most of the parameters such as plant height, number of leaves, root length, number of flowers and fruits, fruit length and fruit yield per plant in response to varying degree of water stress. It is concluded from the results that ‘Black Long’ and ‘Nirala’ are best suited for arid areas which are facing water deficit conditions during most of the time in the year, but full potential of the crop can be achieved by managing the irrigation.

Water Stress Permanently Alters Shoot Architecture in Common Bean Plants

The effects of water stress on crop yield through modifications of plant architecture are vital to crop performance such as common bean plants. To assess the extent of this effect, an outdoor experiment was conducted in which common bean plants received five treatments: fully irrigated, and irrigation deficits of 30% and 50% applied in flowering or pod formation stages onwards. Evapotranspiration, number and length of pods, shoot biomass, grain yield and harvest index were assessed, and architectural traits (length and thickness of internodes, length of petioles and petiolules, length and width of leaflet blades and angles) were recorded and analyzed using regression models. The highest irrigation deficit in the flowering stage had the most pronounced effect on plant architecture. Stressed plants were shorter, leaves were smaller and pointing downward, indicating that plants permanently altered their exposure to sunlight. The combined effect of irrigation deficit and less exposure to light lead to shorter pods, less shoot biomass and lower grain yield. Fitted empirical models between water deficit and plant architecture can be included in architectural simulation models to quantify plant light interception under water stress, which, in turn, can supply crop models adding a second order of water stress effects on crop yield simulation.