Preface

Water resources are highly influenced by the hydrologic cycle and play a role in the agri‐ culture economic development. However, as it is shown by the intergovernmental panel on climate change report, the phenomenon of changing climate has set way to exacerbate an already serious situation of water supply for various users. In this context, the scientif‐ ic investigations on the issue of sustainable use of water are timely and important. Im‐ provement of water management involves the accurate estimation of consumptive uses. One of the techniques is the assessment of evapotranspiration, as a major component of the hydrologic cycle.

As is known, some of the meteorological parameters necessary to estimate evapotranspira‐ tion are frequently missing or hard to collect, and the maintenance of meteorological sta‐ tions is costly. Therefore, the study presented in the first chapter aimed to estimate evapotranspiration using a limited number of meteorological parameters. With the interna‐ tionally accepted Penman-Monteith method as the standard, the estimation formulas of ra‐ diation-based methods were compared with those of temperature-based methods in the hope of discovering a simple estimation formula to solve the issue of lacking or missing me‐ teorological data.

In order to anticipate the necessary action for water management, researchers from Europe and South America have developed a model to forecast evapotranspiration based on an arti‐ ficial neural network. The predicted output and final results are compared for two different input parameters of evapotranspiration calculated with scintillometry and micrometeorolo‐ gy data. The goal of the study is to find which input data can be reliable to obtain evapo‐ transpiration forecast performances. Moreover, the optimal number of predicted days to obtain a correct final performance and the optimal number of input days of data to obtain a correct prediction are tested.

Given the same limitations—time and resources—data required to model evapotranspira‐ tion are not always available for a study site. But, North American specialists consider that off-site data from meteorological networks may be a suitable substitute. In their study, sen‐ sitivity to mixtures of on-site and off-site data inputs of three widely used models for calcu‐ lating evapotranspiration for a ponderosa pine forest where evapotranspiration was measured previously by eddy covariance was investigated.

Northern latitudes have been identified as a region where global climate change will have earlier and stronger impacts than in other regions of the world. All these changes will poten‐ tially alter the exchange of surface energy, water, and carbon cycles in high latitude ecosys‐ tems and consequently the response at the regional level to the atmosphere system. Accordingly, an interesting study, based on current numerical model outputs and compari‐

sons with field experimental observations, allowed to identify new challenges in northern agroecosystems.

Moisture evaporation from porous media is studied by its importance in drying of foods and building materials and biological products such as biopesticides. An exciting foray into the current state of knowledge in the frame of physics of moisture evaporation process from porous media is the subject of the last chapter. Further, the authors aim to establish theoreti‐ cal support for designing biopesticides able to ensure efficient and effective fight against harmful insects in agricultural crops.

#### **Prof. Dr. Daniel Bucur,**

University of Applied Life Sciences and Environment in Iasi, Romania
