As an analytical process for ecological planning, the identification of Landscape Security Pattern (SP) is very comprehensive and complicated. Focusing on water security pattern, this study explores the importance of local knowledge in solving water problems at specific locations. The study area locates at Shichuan and Longxing Township in Yulin Watershed, Chongqing. Confronting to seasonal flooding and water shortage in this area, the pond_chongchong paddy field system created by local people is a comprehensive water resource management and utilization system. Local knowledge and ecological wisdom is inherently embedded in local landscape. To demonstrate the importance of local knowledge in contemporary ecological planning, "Google Map+supplemental questionnaires" are used to collect information about local water processes identified by local knowledge (including flooding, irrigation, drinking and fishing). The field investigation covers 30 villages in the study area and involves almost 100 stakeholders including local officers, motorists, businessmen, fishermen and farmers. Each interview lasts half to one hour. The primary focuses of data analysis are to compare local knowledge with scientific knowledge, to integrate them together for local water security pattern (including rainstorm SP, underground water SP and aquatic SP), and to synthesize the role of local knowledge in the identification process. The analysis confirms the importance of local knowledge in identifying water security pattern and synthesizes its roles in two conditions: abundant or lack of scientific data. In conditions with abundant scientific data, some key processes identified by local knowledge are much similar to results from scientific analyses. In addition, local knowledge can offer complementary evaluation and model adjustments. For instance, local knowledge can identify similar elements as those from scientific methods, but also offer specific justification for hierarchical levels of runoff and runoff intersections for rainwater SP. Local knowledge can also provide verification data in the identification of stormwater SP and underground water SP. In conditions with minimal scientific data, local knowledge can serve as critical data and contribute to pattern identification. For instance local knowledge can rapidly identify underground water level and underground rivers' spatial distribution by interviewing local people and summarizing their opinions. For aquatic SP, local knowledge can also rapidly identify habitats and spawn places of fishes together with micro-adjustment suggestions for reducing the influence of reservoirs. In general, the effective role of local knowledge in identifying rainwater SP can be either independent with limited scientific data or supplementary to scientific methods. However, local knowledge also has constraints, like locality with limited cognition range and limited generalization potentials. This research serves as a beginning exploration of the scientific system for local knowledge to contribute to landscape security pattern as well as future collaborative ecological planning in China.