中華民國內政部建築研究所中華民國內政部建築研究所

一、研究緣起
近年來由於氣候變遷而造成集中豪雨的增加，並伴隨急劇發展的都市化和街道化，使得建築物和道路的不透水區域面積的不斷擴大，造成都市雨水排放流量增加而使得淹水事件頻繁，面對未來這種氣候變遷之不定性與都市化的發展，國內外眾多研究針對都市雨洪之問題提出解決辦法與相關對策。
自民國102年國內頒訂「建築技術規則建築設計施工編第四條之三」規定都市計畫地區新建、增建或改建之建築物需設置雨水貯集系統，已有大量建築物雨水貯集設施興建，然國內建築師在設計的時候常把雨水貯集系統之供水與防洪二功能分開設計，有許多實務界希望能將這兩種功能能合併設計以達較佳效益；而本所於107年度計畫「創新建築物雨水貯集滯洪之智慧物聯網操作管理系統規劃」完成研提建築物雨水貯集滯洪設施供水與防洪雙目標之設計型式與操作策略，透過創新設計手法將原貯水設施可兼具供水與防洪之功能，解決國內雨水貯集系統二功能分開設計之問題。另外，為提高現有建築物雨水貯集系統在都市雨洪控制的成效，強化其應用及加值效益，國內目前已開始逐步有相關產業，針對雨水貯集系統結合物聯網及雲端運算技術進行水質、水量及設施維護之監測管理，但國內目前尚未有一套完整的智慧雨水貯集系統設計架構供參考，且尚未有雨水貯集系統作為雨洪管理及操作並連結各相關數據之平台。
本研究案執行期程為十個月，爰引內政部建研所協同研究計畫需求說明。研究計畫旨為雨水貯集系統之智慧物聯網操作管理架構設計與模擬模式建立，擬延續本所107年度計畫之雨水貯集系統雙目標（滯洪、供水）設計與操作策略成果，以及藉雨水貯集滯洪智慧物聯網操作管理系統之先期發展規劃成果作為基礎，將雨水貯集滯洪操作管理系統導入物聯網(IoT)架構進行設計，透過設備蒐集與遴選及降雨預測或預警的資訊連結，達成雨水貯集系統的智慧化雨洪操作機制，以及完成雨水貯集系統之智慧物聯網操作管理模擬模式建立，預期可為雨水貯集系統智慧化管理之發展及未來案例設置研究參考之重要範疇。
二、研究方法及過程
研究內容初步之7項研究內容，研究案之工作項目如下：
1.蒐集分析國內外物聯網通訊系統之案例及相關軟體發展現況；
2.彙整國內外降雨預報及防災預警方式之相關文獻；
3.建築物雨水貯集系統智慧化之互聯網路相關設備及其資訊蒐集，並進行設備型式探討及遴選之建議，以及系統架構之設計；
4.研提智慧雨水貯集系統使用端(如：民眾、維護管理端等)之需求項目及相關內容；
5.探討降雨致災因子進而研擬建築物雨水貯集系統之防災預警及雨水排放操作機制(如：排放時機、排放量等)，建立雨水貯集系統之智慧物聯網操作管理模擬模式；
6.利用預報或預警資訊連結實際降雨進行系統模式模擬及修正檢討；
7.綜整上述成果進行示範案例遴選、程序規劃與模式模擬操作。
三、重要發現
針對降雨量預測方法的比較，在空間尺度上，雷達預測雖有良好的降雨空間分布，但小基地需要透過程式的撰寫才能獲取特定網格區域的降雨預報資訊，而網格邊界條件問題亦會影響雷達預測模式演算；在時間尺度上，雷達預測提供最短的降雨時距之降雨量預報資料為1小時，較不適用於建築物或區域尺度的雨洪管理操作；另外，雷達、模糊理論、類神經網路三種降雨量預測方法的模式運算之輸入端需考慮許多降雨因子，然灰色理論降雨量預測方法僅需以單一變量進行預測，資料取得也較其他三種方法容易，並經多次專家諮詢會議討論，故本案選擇以灰色理論作為降雨預測方法。
本計畫將建築物雨水貯集系統智慧化之雨洪管理架構分為地面式與地下式兩種型式，其滯洪排水設計分別依排水量需求選擇適合的滯洪孔與泵浦進行裝設，並結合互聯網路技術作資訊連結及操作指令，將透過降雨預警在降雨前將儲水槽內的水預先排出，保留空間作為滯洪空間，並透過設計案例與示範案例連結實際降雨而進行模擬，探討原系統與改造為智慧管理之差異。
設計案例成果顯示，智慧雨洪管理系統於降雨後有效減少總逕流體積，並達到較高的蓄水率，且泵浦的操作時間較原系統少，對於即時的防洪操作及後續的供水效益皆呈現較佳效益。示範案例藉初步遴選而選擇台北市中山區某新建工程之雨水貯集滯洪設施，進行系統架構之程序規劃而進行模式模擬操作，其模擬成果在洪峰削減率、逕流體積削減率、蓄水率及泵浦操作時間等效益評估指標皆優於原系統，其成果可做為未來案例進行實地裝設之驗證參考。
四、主要建議事項
建議一
智慧物聯網雨水貯集系統建構與示範點測試：短中期建議
主辦機關：內政部建築研究所
協辦機關：內政部營建署
本年度已完成雨水貯集系統之智慧物聯網操作管理模擬模式建立，能夠及時掌控降雨情況並進行智慧排水，後續建議進行智慧貯水貯集系統之實際案例裝設並進行驗證，使建築物雨水貯集滯洪設施實施警戒操作，提高社區(建築)自主防災能力，提前針對豪大雨進行減災操作，減少都市淹水損失。
建議二
建立社區或區域尺度之智慧物聯網雨水貯集系統：長期建議
主辦機關：內政部建築研究所
協辦機關：內政部營建署
長期建議應強化其應用及加值效益，透過無線感測技術、雲端運算、大數據分析及降雨預警通報機制進行整合，建立社區智慧雨洪管理物聯網，提升洪災預防與應變的機能，使社區雨洪管理朝向智慧化；進而將社區智慧雨洪管理物聯網層級，逐步提升至區域層級，再往上擴充到縣市政府層級的智慧雨洪管理，提供主管機關研擬相關政策之參考及實務界設計之依據。

1.Purpose of the research
In recent years, due to climate change, the number of heavy rainfall has increased dramatically. Also with the rapid development of urbanization, the impervious area due to buildings and roads construction has been continuously expanded which leads to increase urban stormwater discharge and frequent flooding. In face of the uncertainty of future climate change and urbanization development, many studies at domestic and abroad have tried to find the solutions and related policies to solve the urban stormwater problems.
With the issue of Article 4-3 in the Architectural Design and Construction section of Building Technical Regulations in 2013, which requires that rainwater harvesting systems should be installed in newly, expanded and renovated buildings in urban areas, a large number of rainwater storage facilities have been constructed. However, architects design the rainwater harvesting systems for water supply and stormwater detention separately. Many practitioners have proposed that rainwater harvesting systems should be designed collectively to increase the benefits of rainwater harvesting. In the year of 2018, this institute has initiated the project entitled “Design of Intelligent IoT Operation Management System for Rainwater Storage and Flood Detention for Innovative Buildings”. In the research, the design and operation strategies of rainwater water harvesting system for water supply and flood control objectives of building have been studied and developed. Through this innovative design, both functions of water supply and flood control can be considered collectively and improved the effectiveness of rainwater storage system in existing building. Furthermore, to improve the effectiveness of rainwater harvesting system in urban stormwater control and strengthen its value-added benefits, application of IoT and cloud computing technologies to monitor and manage water quality, volume and maintenance of rainwater harvesting systems have been discussed and preliminarily studied. However, there is no smart rainwater harvesting system having been developed.
The purpose of this research is preliminary to develop the smart rainwater harvesting system and the research period is ten months. Through this research, the design and simulation a smart IoT operations management framework for rainwater harvesting system are developed which is linked to the results of the research in 2018. A smart rainwater operation mechanism and smart IoT operation management model for rainwater harvesting system include comparing and collection of relative IOT equipment and short-term rainfall forecasting model are developed. They will provide an important basic for the development of smart rainwater harvesting operation system for stormwater management.
2.Methodology and Procedures
Seven items are included in the research and are listed and explained as followings:
(1)Collect and analyze the existed cases of IoT communication systems application in both domestic and foreign countries and theirs related software used
(2)Collect rainfall forecasting model and disaster prevention warning methods in both domestic and foreign countries.
(3)Collect and analysis the relative IOT equipment for rainwater harvesting system including sensors, communication systems, and gateway, etc.  Compare and recommend the suitable equipment and the design of the system framework for smart rainwater harvesting system.
(4)Propose the demand items and contents for the end users (such as general public, maintenance staffs, general managers, etc.) of the smart rainwater storage system
(5)Explore the factors induced flood hazard and propose the flood disaster prevention warning mechanism and stormwater discharge operation mechanism (such as discharge time and volume) of rainwater harvesting system in buildings; and establish the smart IoT operation management model of rainwater harvesting system.
(6)Calibrate and modify the developed rainfall forecasting model using measured rainfall data.
(7)Integrate the results obtained above and apply these results in the existing rainwater storage systems for demonstration in planning and model simulation.
3.Major findings
Respect to spatial scale, radar method for rainfall forecasting will obtain spatial rainfall distribution but grid boundary condition will affect the forecasting accuracy. For those of construction site which has small area compared to the grid size, a specified site need to develop a specified program to obtain the rainfall data. Respect to time scale, radar method for rainfall forecasting will provide rainfall data interval more than one hour which is not feasibility to the construct site scale for stormwater management. For those methods including Radar, Ffuzzy theory, and Artificial Neural Network methods for rainfall forecasting need more input data. On the other hand, Grey theory applied for rainfall forecasting is superior than three methods mentioned above and needs limited input data. Through discussions and consultations, this research recommends Grey theory as rainfall forecasting model in this research.
Smart rainwater harvesting system for stormwater management can be divided into two types: above ground and underground. The drainage system need to consider the discharge outlet for above ground type but pumping system for underground type. Both types need to combine with IOT system for data input and operation instructions. Rainfall forecasting model is to forecast the rainfall amount for specified time interval and check with the storage volume in the tank. If rainfall amount forecasted is greater than the storage available, water storage in the tank need to be released. This smart operation is used at the selected demonstration site and compared between conventional and smart operation of rainwater harvesting system. The results show that the smart operation has dramatically reduced the total discharge volume, shortened the operation period of pump and increased the benefits of water supply. If indices including flood peak reduction rate, flood volume reduction rate, water storage ratio and time period of pump operation are used for performance evaluation, smart operation is superior than that of conventional operation.
4.Major recommendation items
Through this research, following recommendations are made for immediate to short-term and long-term period:
Recommendation 1
Establishment of building-scale smart rainwater harvesting system and field test: immediate to short-term
Organizer: Architecture and Building Research Institute, MOI
Co-organizer: Construction and Planning Agency, MOI.
This research has successfully developed the smart operation management model for rainwater harvesting system in building. This model can forecast rainfall advance for rainwater storage discharge operation. In the immediate to short-term, this model can be applied and examined using field sites to mitigate stormwater and reduce the flood damage in the urban areas.
Recommendation 2
Establishment of regional-scale smart rainwater harvesting system and field test: short- to long-term
Organizer: Architecture and Building Research Institute, MOI
Co-organizer: Construction and Planning Agency, MOI.
For short – to long-term, the communication technology, cloud-based data operation, data information platform, rainfall forecasting technology, AI and big-data analysis technology, etc. should be integrated and applied to regional scale such as community, district, and urban or county scale to effectively reduce stormwater discharge and flood damage. Also field test is required to improve the accuracy of smart rainwater harvesting systems in flood control.