## 1 Introduction  
Monitoring applications using a single detection device can only obtain local information. If a number of distributed sensors are used to collect data for broader monitored regions or for monitoring tasks with higher precision requirements, and to send those data and perhaps partially processed results to users via mutual collaboration and communication, the information collected by distributed sensor network systems will be more accurate and comprehensive, and the system's robustness will be stronger. This concept is an important driving force for the development of wireless sensor networks (WSNs). WSNs are intelligent network application systems that autonomously collect, integrate and transmit data. As an emerging information acquisition technology integrating the latest technological achievements in micro-electronic, network and communications, WSNs have been widely used in many fields such as the military, environmental monitoring, industrial control, and urban transportation [1]. In comparison to traditional means of environmental monitoring, WSN technology has the following advantages: (1) sensor nodes are small in size and the whole network needs to be deployed only once, so the human impact of the deployment on the monitored environment is very small, which is especially important for environments very sensitive to alien biological activities. Research on the living environment of petrels on the Great Duck Island in the United States showed that even a few minutes of researcher activity on the island would result in a 20% increase in the death rate of fledging birds [2]; (2) sensor network nodes are large in number, with a high-density distribution, while each node can detect the local environmental information and submit the details to the monitoring center. Sensor networks feature high volume and precision of data acquisition; and (3) wireless sensor nodes have a certain degree of computing power and storage capacity by themselves and can take on more complex monitoring based on changes in the physical environment. Sensor nodes can also communicate wirelessly and monitor collaboratively between nodes. WSN technology is based on, but different from, the traditional wireless _ad hoc_ network. The energy of nodes in WSNs is limited, as is their computing, communication and storage capability [3]. Energy-saving is an essential prerequisite for their reliable operation, and effective energy and resource management has become an important part of the technical issues to be considered, and consequently research on energy consumption has attracted more and more attention [4]. The design of sensor network nodes used for environmental monitoring is shown in Figure 1. The design features dedicated universal interfaces for common sensors, which can be connected to five types of sensors: water level, precipitation, evaporation, flow and water quality. The circuit of each sensor is designed to be low-power, and its processor can be directed to sleep and wake-up via radio frequency instructions. Meanwhile at the same time sensors are equipped with solar cells to extend their lifetime. With the clustering routing protocol, hydrological information parameters collected within a certain period of time by sensors in a certain number within clusters will be converged to a selected cluster head node. After the fusion treatment, the information will be sent to a sink node and then to a monitoring center via some means of long-distance communication such as GPRS. From the perspective of network resources, different protocol layers can use different strategies and techniques to meet the energy-saving goal. From the point of view of network layers, many routing protocols are designed and used to improve the network scalability and to extend its network life cyclefor WSN applications, such as the energy-based routing protocol [5], the SPIN negotiation-based routing algorithm [6], the MTE minimum transmission energy protocol [7], and the data-centric directed diffusion protocol [8].