A demonstration study on Information Technology (IT) field monitoring was conducted in a rice field under the System of Rice Intensification (SRI) environment in Shinshiro City, Aichi Prefecture, Japan. The IT system used in this study consisted of an intelligent sensor node web-server that is equipped with in situ camera and sensor networks for agrometeorological, soil, and plant growth monitoring. Dynamic changes in soil moisture, water level, agrometeorological, and environmental conditions were measured and monitored. With this precision farming setup, understanding and easy assessment of the salient field conditions and phenomena such as cyclic soil wetting and drying as well as critical crop growth stages were made possible. Based on the findings of the demonstration experiment, the system was effective, reliable, and efficient in monitoring soil moisture parameters and agrometeorological information in remote rice field environment. The actual field conditions were captured well by a combination of images, numerical, and graphical data sets. With this precise information, the frequency of irrigation was found to be every 7 days. The rice field was irrigated up to a moisture level of 0.592 m 3 /m 3 (*600 mV) and allowed to be depleted to a moisture level of 0.417 m 3 /m 3 (*400 mV). With this alternate drying and wetting method (AWD), a 25.71% of irrigation water was saved. In this study, rice production was made more scientific and more reliable. Hence, the use of IT field monitoring system represented a viable medium for the realization of better rice productivity which leads to the ethic of sustainable agriculture.
Background/Objectives: A study on enhancing peanut production through drip irrigation (DI) technology was conducted to increase the productivity and profitability of peanut production in the Ilocos region, Philippines. It sought to develop irrigation management strategies suitable for peanut. Methods/Statistical analysis: Decision Support System for Agrotechnology Transfer (DSSAT) simulation was done, and field validation was conducted to achieve the objectives. The simulation activity led to the determination of the top three promising drip irrigation management schemes suitable for peanut production, which were then field validated through actual field setup in three different locations. The best scheme (DI S9 410mm) was then pilot-tested at the farmers' field and compared with Farmers' Practice (FP) d using t-test. Findings: Using the DI scheme, dry pod yield was increased from 1.59Tha-1 to 2.09Tha-1 or 31.45% increase as compared to the farmer's practice. This result is a little higher than the target increase in yield of 30%. Findings indicate that the DI is a much better method than FP, increasing the dry pod yield to as much as 70.21% during the dry season. Yield increase could be attributed to more even application of water and less water stress. On the other hand, water productivity was only increased by around 16% due to farmers' limited water application. In terms of seed quality based on seed size, DI and FP are comparable. Results the economic analysis showed that yield of peanut under DI were higher by about 0.84Tha-1 to 1.16Tha-1 as compared to FP with a Return of Investment (ROI) of 0.25. In the long run, the profitability of DI could be improved through water productivity and yield improvements. Water savings was not a factor in profitability due to under-irrigation by farmers. Novelty/Applications: The use of DI technology with the developed irrigation scheme substantially contributed to the goal of increasing the productivity of and profitability of peanut. It is especially useful for areas with limited water supply for irrigation.
Water plays a vital role in our daily activities. As the world's population increases, water demand increases. Water is subject to pressure due to land use and climate changes. Groundwater, tagged as the most reliable alternative resources is in no exemption and must be studied with proper technology for sustainability. SWAT and coupled SWAT-MODLFOW were used to simulate the impact of land use and climate change on the QRW groundwater hydrology and sustainability. The study aimed to: simulate the impacts of land use change using historical change, municipal land use plan, and future demand for land use conversion; simulate the impacts of climate change on groundwater; simulate the combined impacts (LUCC); and provide policy recommendation towards groundwater sustainability. The results of the study show that the SWAT model can adequately simulate the streamflow and efficiently characterize the watershed. The SWAT and SWAT-MODFLOW revealed that urban expansion decreases both the annual recharge of the watershed and the urban areas. A combination of urban, agricultural and grassland expansion, respectively, would increase the groundwater recharge while decreases the urban groundwater recharge. Simulating the 2035 and 2050 climate scenario would both increase groundwater recharge. LUCC1 and LUCC2 (LUCC projections) both increases the groundwater recharge which varies on the individual quantified impacts. Considering the extraction and different demands of water in the watershed, the groundwater recharge and storage can meet the demand for water for the next 15 years. Yet, the study revealed that wet season becomes wetter, while, dry season becomes drier. Under land use and climate changes projections, monthly groundwater supply will abruptly change. It is therefore recommended that a municipal policy should be implemented to protect the groundwater resources against overexploitation. A policy that could mitigate the effect of climate and land use changes on groundwater resources and watershed preservation for sustainability.
Objectives: This study is centered on the potential use of a dynamic seasonal climate forecast for informing climate risk management in Central Luzon, Philippines to improve rice productivity and resilience. Specifically, we seek to test the downscalibility of the seasonal climate forecasts in the region using a multi-variate spatio-temporal downscaling technique, understand and assess the predictability of rice yield at selected growing areas in the Philippines, and provide guidance on how to develop agricultural risk management strategies. Methods/statistical analysis: The coupled Global Circulation Model (GCM) CFSv2 was used to evaluate the utility of MJJA (May-June-July-August) rainfall forecasts for risk management of rice production in Central Luzon, Philippines. We used a non-homogeneous hidden Markov model (NHMM) to downscale and simulate the GCM forecasts to selected weather stations in the region. On the other hand, we evaluated the skill of the climate forecasts for predicting crop yields. The simulated rainfall was used to drive the rice models set up in DSSATv4.5. Other weather variables needed by DSSAT were generated and conditioned on the occurrence of rainfall based on NHMM rainfall simulation. Simulated rice yields obtained from these models using observed (i.e., simulated by observed weather) and conditioned rainfall (i.e., NHMM downscaling) serve as a baseline for evaluating yields. We also performed a sensitivity analysis to assess appropriate planting windows for the target season for risk management. Findings: Inter-annual variability of rainfall is moderately simulated, with a skill (r) of 0.41, suggesting that NHMM was fairly successful downscaling rainfall from the regional scale given the predictive nature of the predictor, at three months lead-Article Type: Article
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