Sustainable agriculture management typically requires detailed characterization of physical, chemical, and biological aspects of soil properties. These properties are essential for agriculture and should be determined before any decision for crop type selection and cultivation practices. Moreover, the implementation of soil characterization at the beginning could avoid unsustainable soil management that might lead to gradual soil degradation. This is the only way to develop appropriate agricultural practices that will ensure the necessary soil treatment in an accurate and targeted way. Remote sensing and geophysical surveys have great opportunities to characterize agronomic soil attributes non-invasively and efficiently from point to field scale. Remote sensing can provide information about the soil surface (or even a few centimeters below), while near-surface geophysics can characterize the subsoil. Results from the methods mentioned above can be used as an input model for soil and/or soil/water interaction modeling. The soil modeling can offer a better explanation of complex physicochemical processes in the vadose zone. Considering their potential to support sustainable agriculture in the future, this paper aims to explore different methods and approaches, such as the applications of remote sensing, geophysics, and modeling in soil studies.

Water scarcity threatens agriculture and food security in arid regions like Saudi Arabia. The nation produces significant quantities of municipal wastewater, which, with adequate treatment, could serve as an alternative water source for irrigation, thereby reducing reliance on fossil and non-renewable groundwater. This study assessed the appropriateness of using treated wastewater (TWW) for irrigation in a dry coastal agricultural region in Eastern Saudi Arabia and its impact on groundwater resources. Field investigations were conducted in Qatif to collect water samples and field measurements. A multi-criteria approach was applied to evaluate the TWW's suitability for irrigation, including complying with Saudi Standards, the Irrigation Water Quality Index (IWQI), the National Sanitation Foundation water quality index (NSFWQI), and the individual irrigation indices. In addition, the impact of TWW on groundwater was assessed through hydrogeological and isotope approaches. The results indicate that the use of TWW in the study area complied with the Saudi reuse guidelines except for nitrate, aluminum, and molybdenum. However, irrigation water quality indices classify TWW as having limitations that necessitate the use for salt-tolerant crops on permeable and well-drained soils. Stable isotopic analysis (δ²H, δ¹⁸O) revealed that long-term irrigation with TWW affected the shallow aquifer, while deep aquifers were minimally impacted due to the presence of aquitard layer. The application of TWW irrigation has successfully maintained groundwater sustainability in the study area, as evidenced by increased groundwater levels up to 2.3 m. Although TWW contributes to crop productivity, long term agricultural sustainability could be enhanced by improving effluent quality, regulating irrigation practices, implementing buffer zones, and monitoring shallow groundwater. An integrated approach that combines advanced wastewater treatment methods, community involvement, regulatory oversight, and targeted monitoring is recommended to be implemented.

Food and water security are considered the most critical issues globally due to the projected population growth placing pressure on agricultural systems. Because agricultural activity is known to be the largest consumer of freshwater, the unsustainable irrigation water use required by crops to grow might lead to rapid freshwater depletion. Precision agriculture has emerged as a feasible concept to maintain farm productivity while facing future problems such as climate change, freshwater depletion, and environmental degradation. Agriculture is regarded as a complex system due to the variability of soil, crops, topography, and climate, and its interconnection with water availability and scarcity. Therefore, understanding these variables’ spatial and temporal behavior is essential in order to support precision agriculture by implementing optimum irrigation water use. Nowadays, numerous cost- and time-effective methods have been highlighted and implemented in order to optimize on-farm productivity without threatening the quantity and quality of the environmental resources. Remote sensing can provide lateral distribution information for areas of interest from the regional scale to the farm scale, while geophysics can investigate non-invasively the sub-surface soil (vertically and laterally), mapping large spatial and temporal domains. Likewise, agro-hydrological modelling can overcome the insufficient on-farm physicochemical dataset which is spatially and temporally required for precision agriculture in the context of irrigation water scheduling.

Objective - Income smoothing is a form of earnings manipulation to show that the company's performance is good. Income smoothing can be detrimental to investors, because investors do not know the real financial position and fluctuations of the company. Management of the company engage in income smoothing because investors tend to focus only on the amount of profit reported without regard to the process of generating profits. The purpose of this research is to obtain empirical evidence about the effect of firm value and size on income smoothing. Methodology/Technique - The sample of the research includes manufacturing companies listed on the Indonesian Stock Exchange from 2014-2016. The samples were determined using a purposive sampling method and there are 51 companies that meet the criteria used. This research uses a logistic regression method for data analysis. Findings - The results of the research show that the effect of firm value on income smoothing is positive and significant. Meanwhile, the effect of firm size on income smoothing is negative and significant. Companies that create value in the eyes of investors will try to retain their investors by engaging in income smoothing. Income smoothing will convince investors to invest in the company. Meanwhile, large companies that are convinced that investors will continue to invest do not typically engage in income smoothing. Novelty – This study proves that, in the context of agency theory, the principal's desires are not often aligned with the wishes of management which can give rise to agency costs, one of which occurs as a result of income smoothing. Further, firm size can minimize opportunist income smoothing actions. Type of Paper - Empirical. Keywords: Income Smoothing; Firm Value; Firm Size; Agency Theory. JEL Classification: G32, M41, M49. DOI: https://doi.org/10.35609/jfbr.2019.4.1(1)

The purpose of the research is to provide empirical evidence about the effect of board of commissioner, board independence and audit quality on relationship between free cash flow and earnings management. This research used 290 data from manufacturing companies listed in Indonesia Stock Exchange, selected using purposive sampling method, during 2012 until 2014. Earnings management calculated using Modified Jones (1991) Model include ROA from Kothari et al. (2005). Data for the research were analyzed using multiple regression analysis. The results of the research showed that the effect of board of commissioner, board independence and audit quality on relationship between free cash flow and earnings management is negative and significant. Board of commissioners, board independence and audit quality can reduce earnings management problems arising from free cash flow. Board of commissioners, board independence and audit quality oversee the opportunistic behavior of managers that arises from free cash flow problem.