**5. Conclusion**

Starting from the results of the critical analysis, some drawbacks and potential improvements for the TIZIANO monitoring program have been identified and discussed in the following sections.

Monitoring Information Systems to Support Adaptive Water Management 443

 Learning process in monitoring activities: as widely discussed in the scientific literature, the design of a monitoring system cannot be considered as a linear process. It is rather a cycle of design – implementation – evaluation – adaptation. The information needs can change due to several reasons. Adaptive monitoring system should be able to follow these changes. To this aim an evaluation phase should be formally included in the monitoring program. The evaluation should be based on the interaction between policy and decision makers (information users) and monitoring system managers (information

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knowledge allowed to enhance the reliability of local knowledge.

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http://www.ecologyandsociety.org/vol11/iss2/art9/

23 September 1994, Beekbergen, The Netherlands.

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and Sons, New York.

producers).

**6. References** 

the literature review on this issue allowed us gain some hints. The key to guarantee the long term involvement of local community members in monitoring is to keep the monitoring activities as simple and similar to the traditional methods for environmental assessment as possible. Moreover, the involvement in monitoring is easier if the monitoring activities are incorporated in the community members' daily activities. The key to guarantee the actual usability of local knowledge in monitoring activities is: 1) fully integrating local knowledge into existing traditional institutions; and 2) structuring local knowledge so that it is transformed into meaningful and relevant information for decision-making. The integration between local and scientific

#### **5.1 Main drawbacks**

According to the results of the critical analysis, we can infer that the TIZIANO groundwater monitoring network cannot be considered as adaptive and it is not suitable to support the adaptive management. Firstly, the excessive cost for collecting and analyzing data have a strongly negative impact on the long term sustainability of the program. This, in turn, would reduce the capability of the monitoring system to detect the long term unintended consequences of the groundwater management policies.

Secondly, the monitoring system is not integrated in a wider program aiming to analyze the different potential impacts of the policies – e.g. socio-economic impacts. The TIZIANO monitoring program is based on the sectorial approach to environmental resources management which is still common is socio-institutional contexts characterized by a centralized and command-and-control regime. A more holistic and systemic approach is required.

Thirdly, there is no integration between different sources of information. This has a negative impact on the flexibility of the monitoring program. In fact, if the data collection is based only on traditional "static" devices – i.e. monitoring stations – then the adaptation of the monitoring program to modified information needs would be difficult: changing sensor is not always easy and/or cheap, the position of the station cannot be modified easily, even the time schedule for data collection cannot be changed easily. Although remote sensing data are mentioned in the program, the integration of this source of data with the traditional information sources is still far from being achieved.

Finally, an adaptive monitoring system requires an evaluation phase. That is, a critical analysis of the suitability of the designed monitoring system is crucial. This phase has not been considered in the current monitoring program. This means that the revision of the program depends exclusively on the political willing of the local authorities and on the availability of further funds.

#### **5.2 Potential improvements**

Some improvements to make the TIZIANO monitoring program more suitable to support the adaptive water management were defined:


the literature review on this issue allowed us gain some hints. The key to guarantee the long term involvement of local community members in monitoring is to keep the monitoring activities as simple and similar to the traditional methods for environmental assessment as possible. Moreover, the involvement in monitoring is easier if the monitoring activities are incorporated in the community members' daily activities. The key to guarantee the actual usability of local knowledge in monitoring activities is: 1) fully integrating local knowledge into existing traditional institutions; and 2) structuring local knowledge so that it is transformed into meaningful and relevant information for decision-making. The integration between local and scientific knowledge allowed to enhance the reliability of local knowledge.

 Learning process in monitoring activities: as widely discussed in the scientific literature, the design of a monitoring system cannot be considered as a linear process. It is rather a cycle of design – implementation – evaluation – adaptation. The information needs can change due to several reasons. Adaptive monitoring system should be able to follow these changes. To this aim an evaluation phase should be formally included in the monitoring program. The evaluation should be based on the interaction between policy and decision makers (information users) and monitoring system managers (information producers).

#### **6. References**

442 Environmental Monitoring

According to the results of the critical analysis, we can infer that the TIZIANO groundwater monitoring network cannot be considered as adaptive and it is not suitable to support the adaptive management. Firstly, the excessive cost for collecting and analyzing data have a strongly negative impact on the long term sustainability of the program. This, in turn, would reduce the capability of the monitoring system to detect the long term unintended

Secondly, the monitoring system is not integrated in a wider program aiming to analyze the different potential impacts of the policies – e.g. socio-economic impacts. The TIZIANO monitoring program is based on the sectorial approach to environmental resources management which is still common is socio-institutional contexts characterized by a centralized and command-and-control regime. A more holistic and systemic approach is

Thirdly, there is no integration between different sources of information. This has a negative impact on the flexibility of the monitoring program. In fact, if the data collection is based only on traditional "static" devices – i.e. monitoring stations – then the adaptation of the monitoring program to modified information needs would be difficult: changing sensor is not always easy and/or cheap, the position of the station cannot be modified easily, even the time schedule for data collection cannot be changed easily. Although remote sensing data are mentioned in the program, the integration of this source of data with the traditional

Finally, an adaptive monitoring system requires an evaluation phase. That is, a critical analysis of the suitability of the designed monitoring system is crucial. This phase has not been considered in the current monitoring program. This means that the revision of the program depends exclusively on the political willing of the local authorities and on the

Some improvements to make the TIZIANO monitoring program more suitable to support

 Monitoring costs: the current monitoring costs could be reduced only if an intelligent redistribution of activities within public institutions will be put in place. This means that the outsourcing activities have to be strongly reduced. Moreover, since the costs are mainly related to laboratories analysis, the integration of different sources of

 Systemic analysis of the policy impacts: the increasing awareness of the complexity of the real world forces us to adopt a system dynamic approach to monitor and analyze the different and interrelated policy impacts. Although the aim of the TIZIANO network is to collect data about the physical and chemical state of the groundwater, it has to be integrated in a more systemic monitoring program, able to detect even the

 Integration between different sources of information: The integration of different sources of knowledge seems particularly useful to design a multi – variate and multi – scale monitoring system for adaptive management. The Use of alternative sources of information increases the flexibility of monitoring program and reduce the costs. Among the alternative sources of information, local knowledge is increasingly considered as crucial (see as example the Hyogo Framework for Action). The analysis of

information would have a positive impact on monitoring costs.

**5.1 Main drawbacks** 

required.

consequences of the groundwater management policies.

information sources is still far from being achieved.

the adaptive water management were defined:

availability of further funds.

**5.2 Potential improvements** 

socio-economical impacts.


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**25** 

Akihide Utani *Tokyo City University,* 

*Japan* 

**Autonomous Decentralized Control Scheme for Long-Term Operation of Large Scale and Dense** 

**Wireless Sensor Networks with Multiple Sinks** 

Various communication services have been provided. They include environmental monitoring and/or control, ad-hoc communication between mobile nodes, and inter-vehicle communication in intelligent transport systems. As a means of facilitating the above advanced communication services, autonomous decentralized networks, such as wireless sensor networks (Akyildiz et al., 2002; Rajagopalan & Varshney, 2006), mobile ad-hoc networks (Perkins & Royer, 1999; Johnson et al., 2003; Clausen & Jaquet, 2003; Ogier et al., 2003), and wireless mesh networks (Yamamoto et al., 2009), have been intensively researched with great interests. Especially, a wireless sensor network, which is a key network to construct ubiquitous information environments, has great potential as a means of realizing a wide range of applications, such as natural environmental monitoring, environmental control in residential spaces or plants, object tracking, and precision agriculture (Akyildiz et al., 2002). Recently, there is growing expectation for a new network service by a wireless sensor network consisting of a lot of static sensor nodes arranged in a service area and a few mobile robots as a result of the strong desire for the development of advanced systems that can flexibly function in dynamic-

In this chapter, a large scale and dense wireless sensor network made up of many static sensor nodes with global positioning system, which is a representative network to actualize the above-mentioned sensor applications, is assumed. In a large scale and dense wireless sensor network, generally, hundreds or thousands of static sensor nodes limited resources, which are compact and inexpensive, are placed in a service area, and sensing data of each node is gathered to a sink node by inter-node wireless multi-hop communication. Each sensor node consists of a sensing function to measure the status (temperature, humidity, motion, etc.) of an observation point or object, a limited function of information processing, and a simplified wireless communication function, and it generally operates on a resource with a limited power-supply capacity such as a battery. Therefore, a data gathering scheme and/or a routing protocol capable of meeting the following requirements is mainly needed to prolong the lifetime of a large scale and dense wireless sensor network composed of hundreds or thousands

**1. Introduction** 

ally changing environments (Matsumoto et al., 2009).

of static sensor nodes limited resources. 1. Efficiency of data gathering

3. Adaptability to network topology changes

2. Balance of communication load among sensor nodes

A, van Delden, H, Gaddis, E, Assaf, H. (2006). Bridging the gaps between design and use: developing tools to support management and policy. In print.

