Dataset Information

The flood pulse as the underlying driver of vegetation in the largest wetland and fishery of the Mekong Basin.

ABSTRACT: The Tonle Sap is the largest wetland in Southeast Asia and one of the world's most productive inland fisheries. The Mekong River inundates the Tonle Sap every year, shaping a mosaic of natural and agricultural habitats. Ongoing hydropower development, however, will dampen the flood pulse that maintains the Tonle Sap. This study established the current underlying relationship among hydrology, vegetation, and human use. We found that vegetation is strongly influenced by flood duration; however, this relationship was heavily distorted by fire, grazing, and rice cultivation. The expected flood pulse alteration will result in higher water levels during the dry season, permanently inundating existing forests. The reduction of the maximum flood extent will facilitate agricultural expansion into natural habitats. This study is the most comprehensive field survey of the Tonle Sap to date, and it provides fundamental knowledge needed to understand the underlying processes that maintain this important wetland.

SUBMITTER: Arias ME

PROVIDER: S-EPMC3790129 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

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The flood pulse as the underlying driver of vegetation in the largest wetland and fishery of the Mekong Basin.

Arias Mauricio E ME Cochrane Thomas A TA Norton David D Killeen Timothy J TJ Khon Puthea P

Ambio 20130723 7

The Tonle Sap is the largest wetland in Southeast Asia and one of the world's most productive inland fisheries. The Mekong River inundates the Tonle Sap every year, shaping a mosaic of natural and agricultural habitats. Ongoing hydropower development, however, will dampen the flood pulse that maintains the Tonle Sap. This study established the current underlying relationship among hydrology, vegetation, and human use. We found that vegetation is strongly influenced by flood duration; however, th ...[more]

PMID: 23877417

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Project description:Flood prediction for ungauged karst wetland is facing a great challenge. How to build a wetland hydrological model when there is a lack of basic hydrological data is the key to dealing with the above challenge. Napahai wetland is a typical ungauged karst wetland. In ungauged wetland/condition, this article used the wetland open water area (OWA) extracted from Landsat remote sensing images during 1987-2018 to characterize the hydrological characteristics of Napahai wetland. The local daily precipitation in the 1987-2018 rainy season (June-October) was used to set the variables. Based on the following hypothesis: in the rainy season, the OWA of the Napahai wetland rises when there is an increase in accumulated precipitation (AP), two data-driven models were established. The study took the area difference (AD) between two adjacent OWAs as the dependent variable, the accumulated precipitation (AP) within the acquisition time of two adjacent OWAs, and the corresponding time interval (TI) of the OWA as explanatory variables. Two data-driven models (a piecewise linear regression model and a decision tree model) were established to carry out flood forecasting simulations. The decision tree provided higher goodness of fit while the piecewise linear regression could offer a better interpretability between the variables which offset the decision tree. The results showed that: (1) the goodness of fit of the decision tree is higher than that of the piecewise linear regression model (2) the piecewise linear model has a better interpretation. When AP increased by 1 mm, the average AD increased by 2.41 ha; when TI exceeded 182 d and increased by 1 d, the average AD decreased to 3.66 ha. This article proposed an easy decision plan to help the local Napahai water managers forecast floods based on the results from the two models above. In addition, the modelling method proposed in this article, based on the idea of difference for non-equidistant time series, can be applied to karst wetland hydrological simulation problems with data acquisition difficulty.

Project description:BackgroundThe Mekong Basin Disease Surveillance cooperation (MBDS) is one of several sub-regional disease surveillance networks that have emerged in recent years as an approach to transnational cooperation for infectious disease prevention and control. Since 2003 MBDS has pioneered a unique model for local cross-border cooperation. This study examines stakeholders' perspectives of these MBDS experiences, based on a survey of local managers and semi-structured interviews with MBDS leaders and the central coordinator.ResultsFifteen managers from 12 of 20 paired cross-border sites completed a written survey. They all monitor most or all of the 17 diseases agreed upon for MBDS surveillance information sharing. Fourteen agreed or strongly agreed with statements about the core MBDS values of cooperation, mutual trust, and transparency, and their own contributions to national and regional disease control (average score of 4.4 of 5.0). Respondents felt they implemented well to very well activities related to surveillance reporting (average scores 3.4 to 3.9 of 4.0), using computers for their work (3.9/4.0), and using surveillance data for action (3.8/4.0). Respondents reported that they did worst in implementing research (2.1/4.0) and somewhat poorly for local laboratory testing (2.9/4.0) and local coordination with cross-border counterparts (2.9/4.0), although all 15 maintain a list with contact information for these counterparts and many know their counterparts. Implementation of specified activities within their collective regional action plan was uneven across the cross-border sites. Most respondents reported positive lessons learned about local cooperation, information sharing and joint problem solving, based on trusting relationships with their cross-border counterparts. They recommend expansion of cross-border sites within MBDS and consideration of the cross-border cooperation model by other sub-regional networks.ConclusionsMBDS has over a decade of experience with its model of local cross-border cooperation in disease surveillance and control. Frontline managers have documented success with this model, strongly support it and recommend its expansion within and beyond the MBDS network. The MBDS cross-border cooperation model is standing the test of time as a solid approach to building and sustaining the public health capabilities needed for disease surveillance and control from the local to national and global levels.

Dataset Information

The flood pulse as the underlying driver of vegetation in the largest wetland and fishery of the Mekong Basin.

Publications

The flood pulse as the underlying driver of vegetation in the largest wetland and fishery of the Mekong Basin.

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