| dc.description.abstract | The agroecosystems of irrigated area are experiencing frequent and pronounced water imbalances such as water deficit which is more serious in rain-feed area as a consequence of global climate change.
Taiwan average annual rainfall is approximately 2,500 mm. In particular, 80% of the rainfall occurs in summer, and most of the heavy rainfall is caused by typhoons. The situation is worsening as climate change results in uneven rainfall, both in spatial and temporal terms. Moreover, climate change has resulted the variations in the seasonal rainfall pattern of Taiwan, thereby aggravating the problem of drought and flooding. However, due to increasing demands and continuous competition for high quality water resources in the agricultural-industrial-domestic triangle, it is unrealistic to expect further expansion of agricultural irrigation. But it’s possible to enhance the flexibility of water regulation by increasing the accuracy of water use under limited water resources. Since the irrigation water distribution system is mostly manually operated, which produces difficulty with regard to the accurate calculation of conveyance losses of channels and fields. Therefore, making agricultural water usage more efficient in the fields and increasing operational accuracy by using modern irrigation systems can ensure appropriate irrigation and sufficient yield during droughts. If agricultural water, which accounts for 70% of the nation’s total water usage, can be allocated more precisely and efficiently, it can improve the efficacy of water resource allocation.
In this study, a system dynamic model was used to establish an irrigation water management model for a companion and intercropping field in Central Taiwan. In addition to rainfall replenishment, both surface water and groundwater were considered as water sources for irrigation use. The intelligent irrigation management system established in this study can automatically calculate the water requirement of intercroping fields through the field monitoring equipment to obtain the current water depth and related hydrological parameters and automatically determine whether the channel water sources are sufficient and choose to use open channels or groundwater sources for irrigation. The precise irrigation system effectively improved the accuracy and the performance of field irrigation management in the mixed cropping area in the study region.
The model simulated two scenarios by reducing 30% and 50% of the planned irrigation water in year 2013. Results indicated that the field storage in the end block of the study area was lower than the wilting point under the 50% reduced irrigation water scenario. The original irrigation plan can be reduced to be more efficient in water usage, and a 50% reduction of irrigation can be applied as a solution of water shortage when drought occurs. However, every block should be irrigated in rotation, by adjusting all water gates more frequently to ensure that the downstream blocks can receive the allocated water to get through the drought event.
In addition, this study simulated the hydrological conditions of the 2nd crop season in year 2015. It shows that if the water supply in the upstream irrigation area is controlled by the model and some of the water supplied by the groundwater, the amount of water used from channel can be relatively reduced. In other words, to reach the water allocation for downstream irrigation use, groundwater sources for the upstream area can be appropriately used for irrigation, which enabling each rotation block to pass through the water shortage period. The historical data of groundwater level monitoring wells in the upstream and downstream location of the study area are extended to be discussed in this study. The changes of local groundwater level are analyzed and compared. The results show that the volume of the pumping water is still within a reasonable range for the local groundwater level. Therefore, if the groundwater is properly used as a supplementary irrigation source after assessment and monitoring of the groundwater level changes in the upstream irrigated area, groundwater can be used more reasonably and effectively to solve the problem of water allocation during the drought period. At the same time, the smart irrigation management system established in this research can be operated effectively to use the big data collected from field monitoring. After cloud computing via the Internet of Things (IoT), it will automatically calculate and provide decision-making references for the selection of farmland irrigation water and water sources. The results will help to improve field irrigation management performance and achieve the goal of improving irrigation and water conservation. | en_US |