Decision Support System and GIS as Tools for Integrated Management of the Laguna De Bay Basin

Transcription

1 Sengupta, M. and Dalwani, R. (Editors) Proceedings of Taal 2007: The 12th World Lake Conference: Decision Support System and GIS as Tools for Integrated Management of the Laguna De Bay Basin Oliver B. Barbosa 1, Emiterio C. Hernandez 2, and Adelina Santos-Borja 3 Laguna Lake Development Authority, Rizal Provincial Capitol Compound, 1601 Pasig City, Philippines 1 Remote Sensing and GIS Consultant, LLDA, Philippines 2 Integrated Water Resources Management Division, LLDA, Philippines 3 Research and Development Division, LLDA, Philippines oliverbarbosa@yahoo.com, emitzky@yahoo.com, lennieborja@yahoo.com ABSTRACT The Laguna Lake Development Authority (LLDA) was established in 1966 as a quasi-government agency that leads, promotes and accelerates sustainable development in the Laguna de Bay Region. Regulatory and law-enforcement functions are carried out with provisions on environmental management, particularly on water quality monitoring, conservation of natural resources, and community-based natural resource management. In 2000, the LLDA Decision Support System (DSS), containing an integrated set of mathematical modeling tools and a comprehensive stakeholder s analysis module, was set-up for the whole Laguna de Bay Basin with financial and technical support from the Royal Dutch Government. It provides discussion platforms aimed to enable scientists and managers to reach a common perspective on managing the lake. Through the DSS, the LLDA is able to integrate research efforts in scientific disciplines, translate the results to the management level, increase the understanding of the relations between users of a water system and the system itself, provide a common and user-friendly framework for the analysis and comparison of management decisions, and facilitate the comparison of many different management options and measures. Further on, the LLDA Geodesk was created, aimed towards an enterprise Geogrpahic Information System (GIS) to be utilized to every detailed concerns in the basin that will take benefit from the mapping technology. The long-term strategy is that with GIS being operated by each concerned units and catering to the details of their mapping and spatial analysis needs, appreciation and extensive use of the more advanced DSS will follow. Complemented by the ongoing re-engineering of the LLDA, this completes the institutionalization of an Integrated Water Resources Management (IWRM) approach by the LLDA, as it evolved into a technologically advanced lake basin management authority that exercises and performs its mandate more effectively. Keywords: integrated lake basin management, modeling, decision support system (DSS), mathematical modeling modular system (MMMS), geodesk, enterprise GIS. INTRODUCTION Laguna de Bay is the only lake in the Philippines managed by a special agency of the Philippine Government, the Laguna Lake Development Authority (LLDA). LLDA was established in 1966 as a quasi-government agency that leads, promotes and accelerates sustainable development in the Laguna de Bay Region. Regulatory and lawenforcement functions are carried out with provisions on environmental management, particularly on water quality monitoring, conservation of natural resources, and communitybased natural resource management. Routine monitoring programs is being conducted by LLDA since the 1970 s. Particularly on water quality, voluminous data has been collected on technical information about the lake covering different locations, time periods, and parameters. The traditional assessment of environmental quality in the Laguna Lake is based upon a quick assessment using monitoring results. However, monitoring programs is limited in their extent of coverage, both spatially and temporally if the size of the study area and the costs involved is significant. In addition, despite existing monitoring programs, the spatial behavior of substances and knowledge of significant processes is considered to still be limited. It is therefore recognized that the applications of GIS and mathematical models can help by providing a means of integrating existing knowledge on physical, chemical and biological processes with monitoring data in both space and time, and by doing so adequate strategies to manage coastal environments can be prepared in a sustainable way. (SDLBE, 2000) This paper intends to describe the integration of GIS and modeling tools in Laguna Lake

2 Development Authority, and the creation of the Geodesk mandated to thoroughly make use of these tools to support the regular planning of the organization within its recently adapted lake basin management approach. The Lake Basin With a total area of 3730 km2, approximately 1.3% of the country s total land area, the Laguna Lake basin covers 6 provinces, 49 municipalities and 12 cities. It spans 2,656 barangays of which 187 are all within lakeshore towns in Southern Tagalog in the Luzon Province. The lake also holds the distinction of being the largest among the 216 lakes in the Philippines, and one of the five largest inland body of water in Southeast Asia (Santos-Borja 2001). Figure 2: The Laguna de Bay basin delineation (white) overlain in the Landsat somposite satellite image of 2002 to emphasize the industrial expansion around the lake (light blue areas). Documented root causes of rapid deterioration of the resources in the lake and its upper watershed include intensified economic activities, open access to natural resources use, lack of economic resource pricing policies, and a lack of a common policy objective for management and development of the resources of the lake and its watershed (Santos- Borja and Nepomuceno 2006). Implementing the Lake Basin Management Approach Figure 1 The Laguna de Bay basin delineation (red) overlain in the Landsat true-color satellite image of Many publications about the lake being a multi-use resource have been published. (SDLBE 2000, Santos-Borja 1994,2001,2006). Uses include aquaculture and fisheries, water for irrigation, transport route, power generation, waste sink, industrial cooling, recreation, domestic water supply and a habitat for various species of birds and organisms. It is also a convenient transport route for people and products, a receptacle for floodwaters coming from Metropolitan Manila, and a sink for treated and untreated liquid waste. Its dominant use at present is for fishery, both open water fishing and aquaculture. The integrated water resources management (IWRM) approach was institutionalized in LLDA in the year 2000 through The Sustainable Development of the Laguna de Bay Environment (SLDBE), a bilateral cooperation project between The Philippines and The Royal Dutch Government. The general objectives were to restore and/or to maintain aquatic ecosystem integrity and, at the same time, to optimize the sustainable use of water resources, quantitatively and qualitatively, for different, sometimes conflicting functions like drinking water supply, fisheries, irrigation, power generation, transport, recreation and cooling and process water for industry (Nauta 2003). 2213

3 The Decision Support System (DSS) Figure 3: LLDA and the IWRM process The IWRM, dealing with the integration between the system, its users and their managers (see Figure III) requires a basin approach: water bodies are connected and upstream processes determine to a high extent downstream problems, making a water basin or catchment approach necessary. Thus, the Decision Support System (DSS) has been set-up for the whole Laguna de Bay catchment. With the gains from this project, most especially the added technical capability of the LLDA staff and with the more determined approach to continually espouse the sustainable development of the Laguna de Bay Basin, the LLDA embarked on another project, the Laguna de Bay Institutional Strengthening and Community Participation (L1SCOP) Project which is presently being implemented over a five year period ( It is financed from loan proceeds from the World Bank and an equivalent grant from the Netherlands Government. With this nitiative, the LLDA hopes to be able to optimize the level of interactions between the environmental, economic, and Institutional dimensions of resource use and management, via a combination of strategic Interventions which also form the integral components of the LISCOP, i.e., (a) Co-managed Investments for watershed development; and (b) strengthening institutions and Instruments. Among the continued application of the IWRM approach and the DSS within the LISCOP Project is through the Laguna de Bay Environmental Action Planning (LEAP) for each of the 24 Laguna de Bay Microwatersheds. The goal is to identify projects within each microwatershed that can be financed through LISCOP and mainly implemented by the local government units (LGUs). Simply put, this activity when undertaken for each microwatershed will provide all the essential support to the LGUs to identify projects that will address major problems in the specific localities within each microwatershed concerned, leading to the improvement of the environment and quality of life of the LGU communities along with the Laguna Lake condition. The DSS provides discussion platforms aimed to enable scientists and managers to reach a common perspective on managing the lake. Through the DSS, the LLDA is able to integrate research efforts in scientific disciplines, translate the results to the management level, increase the understanding of the relations between users of a water system and the system itself, provide a common and userfriendly framework for the analysis and comparison of management decisions, and facilitate the comparison of many different management options and measures (Nauta et al 2001). Figure 4: Outline of the Decision Support System The technical modules of the DSS are powerful combinations of the GIS, Modular Mathematical Modeling Systems (MMMS), and the Environmental Action Planning. For purposes of discussion of the method and approach in this article, it will suffice to assume generic softwares performing for the said modules. The couplings are illustrated in figure 5. Figure 5: The Modular Mathematical Modeling Systems (MMMS). (Adapted from Delft3D manual) 2214

4 The Mathematical Modeling Modular Systems (MMMS) The mathematical modeling modular systems simulate natural dynamics and scenarios within the basin. Within the DSS of LLDA, these are the coupled mathematical models for hydrology, waste load, hydrodynamics, water quality, and ecology module. Platform for file pre-processing, postprocessing, display and storage is through the GIS. Each module of the MMMS addresses a specific domain of interest, such as flow, near-field and far-field water quality, wave generation and propagation, morphology and sediment transport and ecology, together with pre-processing and postprocessing modules. All modules are dynamically interfaced to exchange data and results where process formulations require (Barbosa and Hernandez 2007). The MMMS are capable of simulating basin water balance, pollution loads, flows due to tide, wind, density gradients and waves induced currents, propagation of directionally spreading short waves over uneven bathymetries, including wave-current interaction, advection and dispersion processes, water quality and ecological phenomena, initial and/or dynamic (time varying) 2Dmorphological changes, including the effects of waves on sediment stirring and bed-load transport. The Hydrology Module As part of modeling inputs for waste load, hydrodynamics and water quality modeling activities, a catchment model (i.e. hydrology model) to generate data on runoff is being undertaken. This work is an important contribution towards better knowledge and documentation of the hydrology of the area, by incorporating the main physical processes that play a role in the transformation of rainfall into runoff. Figure 6: Comprehensive illustration of the River Hydrology module and related sets of input-output data. The team makes use of all the collected input datasets in combination with a simple but straightforward spreadsheet hydrologic model. Later on, a comprehensive user-friendly hydrological information system (HYMOS) that easily couples to the waste load modeling and the Delft3D hydrodynamic module was incorporated as part of this module. The module considers a simple rainfall-runoff model to simulate runoff from a catchment in response to rainfall. It does so by assuming that part of the rainfall is lost to the atmosphere and that the remaining part is divided over a number of fractions that are redistributed in time in a predictable way. Hereto three fractions were chosen, to represent three characteristic runoff components: The quickflow or direct surface runoff, the interflow, and the baseflow. The sum of these three components forms total runoff. Figure I Set-up of water balance for the Laguna de Bay. In summary, this module provides information on the water quantity flowing to the lake from a sub-basin perspective. It also provides computation of water allocation and distribution. It simulates the hydrology (occurrence, circulation and distribution of water) with focus on the transformation of rainfall input into channel inflows and its corresponding catchment water balance. The Waste Load Module Intended to provide LLDA with a detailed overviews on pollution loads and to allow for future waste load scenario generation, this network model was set-up to describe the various tributary catchments separately. By appointing the different industrial, domestic and agricultural activities to each of these catchments and by considering the estimated water discharges, pollution loads to the study area are estimated. This module provides input for the water quality model, which consists of two major functional elements, viz. a Waste Load Production Module and a Waste Load Treatment Module. In the Waste Load Production Module it is specified how, where and what kind of waste loads are produced in the study area. Different methods are optional to calculate the production of waste loads. 2215

5 Most of these produced waste loads do not enter the surface water system before some treatment has taken place. The kind of treatment is specified in the Waste Load Treatment. Based on the information and relations indicated, the model calculates the waste loads on surface water (Barbosa et al. 2005). variations, flow velocity, saltwater intrusion, thermal pollution caused by industrial discharge extent of accidental spills, among others. This module also provides understanding of the water balance of the Laguna de Bay in relation to the different forcing functions (changes in meteorology, bathymetry, catchment discharges, gate operations, etc.) The output of the model also serve as input for sediment transport, water quality and ecological modeling and can also be used to determine future changes in the lake water especially with respect to the projected infrastructure development. The Sediment Transport and Water Quality Module Figure 8: Comprehensive illustration of the Waste Load module and related sets of input-output data. The Hydrodynamics Module The transport of substances in the water system can be described by the so-called advection-diffusion equation. In order to model waste loads and water quality processes the advection-diffusion equation is extended with an extensive water quality library of source/sink terms. The model is capable of describing any combination of constituents and is not limited with respect to the number and complexity of the water quality processes. The hydrodynamic module is a multi-dimensional hydrodynamic simulation program that calculates non-steady flow and transport phenomena resulting from tidal and meteorological forcing on a curvilinear, boundary-fitted grid. Figure 10: Comprehensive illustration of the Water Quality module and related sets of input-output data. Figure 9: Comprehensive illustration of the Hydrodynamics module and related sets of inputoutput data. In 3D simulations, the hydrodynamic module applies the so-called sigma co-ordinate transformation in the vertical, which results in a smooth representation of the bottom topography. It also results in a high computing efficiency because of the constant number of vertical layers over the whole computational domain. In summary, this module provides predictions on water circulation, flooding events, water level In this module, the following phenomena are dealt with: spreading of conservative and first-order decaying substances (including age and fraction of water determinations); basic parameters as salinity (chloride), ph, temp, etc. bacterial pollution; organic matter / DO / BOD nutrients and primary production (diatoms, greens and blue-greens) toxics (heavy metals and organic micropollutants) and dissolved oils; depending on the data availability. 2216

6 number for a certain habitat. The sum of all scores per gridcell yields the weighted area of suitable habitat. The data collected on distribution of key habitats and functions are mapped in GIS. Figure 11: Modeling processes within the water quality model (Delft3D WAQ Manual) In summary, this module provides understanding of the ecological and water quality processes. It calculates the concentrations of a number of substances relevant for water quality (e.g. salinity, BOD, nutrients, algae, oxygen, suspended sediment, heavy metals, etc.) throughout the entire lake, as influenced by water movement and by physical, chemical or biological processes. The output of the model will serve as input for sediment transport, water quality and ecological modeling and can also be used to determine future changes in the lake water especially with respect to the projected infrastructure developments. The Ecology Module The models are used to predict changes in the suitability in response to changes in environmental factors such as stream flow, water depth, substrate type and location, inundation frequency or duration, vegetation cover and water quality. In this module, the results of the other MMMS are interpreted using the Habitat Evaluation Procedures (HEP). A Habitat Evaluation Procedure (HEP) is a collection of analytical methods and habitat suitability index models for faunal and floral species, communities and ecological functions. The habitat suitability requirements are derived from life history studies, field observations, frequency analyses of environmental factors characterizing habitats and functions. The overall habitat suitability is determined by the suitability index rating of the environmental factor, which most limits the suitability per species or community (a number between 0 (unsuitable) and 1 (optimal)), the areal extent of suitable habitat or function quality. In this study the weighted suitable area is used to express the effects of the lake management options on key functions and sensitive local habitats. For each management option the potential impact on habitat suitability or function quality is computed. For each gridcell its surface area is multiplied with the suitability index Figure 12: Ecology module output data showing suitability of aquaculture areas with and without salinity intrusion. Typical Laguna Lake setting of HEP is to relate the water quality module simulation results to the DENR DAO 35 classification for freshwater systems. In this scheme, portions of the lake is classified as falling within classes A to E, where A is suitability for drinking, B for recreation, C for fishery, D for irrigation, and a separate assumed class for areas worst than class D (Bongco et al 2003). In summary, this module provides necessary information about the status of Laguna de Bay for human use and natural values. It also provides understanding of the changes in the lake s suitability for varied uses in response to changes in environmental factors and water quality. Model Calibration and Validation The starting point for modeling is to keep the model as robust as possible, i.e. local adjustments of model parameters and the use of empirical descriptions was to be avoided. The initial model results is compared with the necessary calibration data applicable for the study area (for example, historical water quality data), and when necessary, model parameters should be adjusted when significant deviations in the model results are evident. This model calibration assures that the models behave correctly under a range of different scenarios. In case additional data would become available, model validation is undertaken wherein an improved match with field data may be obtained without affecting the predicted trends as a result of different scenarios. The model should be able to reproduce the main phenomena, processes and concentrations patterns in the Laguna de Bay with respect to water quality parameters under consideration. 2217

7 The Environmental Action Planning Module The ultimate stage of the decision making process for Integrated Water Resources Management and Sustainable Development is the actual choice of measures: what measures to prioritize to meet the targets. Good decision-making requires a vision on what to establish (what are the targets) and a straightforward, transparent and participatory approach to select the measures to meet the targets. Individual decision makers may learn from their own mistakes, but it is important that lessons be learned in a more formal and systematic way, and communicated to others, so that they can support future decisions. Figure 15: Ranked environmental program priorities resulting from the MCA (SDLBE 2003) In summary, this module establishes comanagement approach to resource management and development. This module also emphasizes Involvement of as much representation of all involved stakeholder group form project conceptualization, prioritization, implementation, and management. The Geodesk Figure 14:II The Multi-Criteria Analysis (MCA) approach to Environmental Action Planning. Multi-criteria analysis (MCA) techniques can be used to identify a single most preferred measure, to rank measures, to short-list a limited number of measures for subsequent detailed appraisal, or simply to distinguish acceptable from unacceptable developments. An MCA approach makes the selected measures and their contribution to the different criteria explicit, and requires the exercise of systematic (expert) judgment. The main role of MCA is to deal with the difficulties that human decision-makers encounter in handling large amounts of complex information in a consistent way. The present practice of LLDA on the stakeholders analysis involves representatives from five interest groups, namely: Legislators; Government Agencies and Local Government Officials, Non-Government Organizations and People s Organizations, Fishermen, Farmers, and Industries. Further on, the LLDA Geodesk was created, aimed towards an enterprise Geographic Information System (GIS) to be utilized to every detailed concerns in the basin that will take benefit from the mapping technology (Barbosa 2004). GeoDesk is an inter-division unit housed within the Integrated Water Resources Management Division (IWRMD) and works closely together with all other LLDA divisions. Every division has one or more representatives in the GeoDesk. Depending on the actual work, GeoDesk organizes meetings with the concerned divisions. This platform enables LLDA to know what the ideas and concerns are with the divisions regarding spatial data and its interaction with other sorts of information and data, and in this way can make the work with geo-information very efficient. Moreover, it makes non-gis experts more aware of how powerful GIS is. In order to make the people in LLDA also aware of the available spatial data a geo-metadatabase was created. This application in internet explorer serves as a catalogue with the technical descriptions and access constraints of all spatial data in the LLDA. For the distribution of the data in and outside the LLDA, GeoDesk created standard agreements for the use of spatial data. In this way, data distribution can be established effectively. The long-term strategy is that with GIS being operated by each concerned units and catering to the details of their mapping and spatial analysis needs, appreciation and extensive use of the more advanced DSS will follow. 2218

8 Much thanks also to the IWRM staff, Neil, Ernie, Sam, Josie, Flor, Alvin and Carol. They are instrumental for running and promoting the applications of this DSS within the organization. REFERENCES Figure 16: The Geodesk within LLDA Existing Challenges Among the existing challenges for LLDA wherein management decisions should be backed-up by technically-sound information and analysis are the identified conflicts among users of the basin and the lake. Previously reported case studies reflecting the root causes of conflicts among the lake users (Santos-Borja 2001, Santos-Borja and Nepomuceno 2006), which is also being served by the DSS include development projects to improve the use of lake water for irrigation, power generation, domestic water supply and aquaculture. The impacts of quarry operations around the lake and in its watershed, and the effects of the growing informal settlers who typically cluster in flood and pollution-prone locations are also being addressed by the DSS. The decision tools being used by LLDA are being improved further to cover other details leading to their deeper integration to the LLDA business processes. Corresponding management decisions on the different problems and issues within the lake basin are continuously worked on within the context of an integrated lake basin management approach. Acknowledgements The principal and secondary authors would like to thank Ms. Adelina Santos-Borja for her invaluable support and input in writing this paper and her support and confidence in pushing us to write more papers regarding the DSS, Ms. Alicia Bongco for her constant support for practice and enhancement of our Modeling and GIS expertise, and also to Ms. Dolora Nepomuceno, our Officer-in-Charge and Assistant General Manager, for her constant support for the technological advancement of the organization. Barbosa, Oliver, E. Hernandez and G. Chua The LLDA Decision Support System in Disaster Management. NAMRIA GIS-Link March Issue. Philippines. Barbosa, Oliver A Decision Support System for the Laguna de Bay Watershed. Watertech 2006 Proceedings. Barbosa, Oliver, Neil Varcas and Allan Kalaw RS andgis Research and Applications in LLDA s Decision Support System: Preprocessing population distribution using the Rurban Method for Input to the Waste Load Model. NAMRIA GIS-Link November Issue. Philippines. Barbosa, Oliver Applications of Geographic Information System (GIS) and Remote Sensing (RS) within the Laguna Lake Watershed, Philippines: The Laguna Lake Development Authority Perspective. Internal Paper. Laguna Lake Development Authority. Philippines. Bongco, I.G., A.C. Santos-Borja and Tjitte A. Nauta Application of habitat evaluation procedure for impact assessment studies in Laguna de Bay, Philippines. Hydrobiologia : LLDA, Laguna de Bay Institutional Strengthening and Community Participation (LISCOP) Project Component 2, Improving Regulatory Instruments and Approaches, Strengthening of Policy and Planning, Quarterly Progress Report, October- December, Laguna Lake Development Authority, Philippines. Nauta, Albert A Sustainable Development of the Laguna de Bay Environment (SDLBE). Final Report. Laguna Lake Development Authority, Philippines. Nauta, T.A., A.E. Bongco and A.C. Santos-Borja. Set up of a DSS to Support Sustainable Development of the Laguna de Bay. 5th International Conference on the Environmental Management of Enclosed Coastal Seas. November 2001, Japan. Santos-Borja, A.C. and D.N.Nepomuceno. Laguna de Bay: Institutional development and change for lake basin management Lakes & Reservoirs, Research & Management Journal. 11 (4): Santos-Borja, A.C Setting Priorities for Biodiversity Conservation in Philippine Inland Waters. Final Report, Inland Water Technical Working Group. Conservation International, Quezon City, Philippines. Santos-Borja, A.C. Building Partnerships for Sustainable Lake Management, the Laguna de Bay Experience. IETC Freshwater Management Series No.3, UNEP International Environmental Technology Centre, Osaka/Shiga Santos-Borja, A.C The Control of Saltwater Intrusion into Laguna de Bay: Socioeconomic and ecological significance. Lake and Reservoir Management Journal. 10 (2) :