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Initial Environmental Evaluation, Northeast Regional Water Management Plan, Bangladesh Flood Action Plan 6



This chapter describes the specific methods used to assess impacts and key assumptions underlying the assessment.

Methods consist of:

  • Tools used to plan and understand localized hydrologic impacts;
  • Regional surface water model used to understand regional hydrologic impacts;
  • Morphological impact assessment methodology;
  • Agricultural impact assessment methodology;
  • Fisheries production impact model;
  • Wetland and grazing land impact model; and
  • Qualitative ranking methodology


7.2.1 Hydrology
Data sources
Data used in the engineering analyses included existing topographic maps, historic climatological and hydrological records, river and khal cross-sections surveyed by BWDB Morphology Directorate and by SWMC, BWDB reports, MPO reports, personal field observations, and interviews with project area residents, and the recommendations of local representatives and BWDB officials.
Localized impacts
Many or most of the impacts of an FCD project stem from the primary changes the project induces in water levels and flow rates. Some of these impacts affect the project area; some the adjacent external rivers or floodplains; and others more remote downstream and sometimes upstream areas.

The impact of FCD projects on flooding in the internal project area is assessed by comparing the area's future-without-project (FWO) and future-with-project (FW) hydrological conditions. Areas under different depths of pre-monsoon and monsoon flooding are derived from superimposing corresponding FW and FWO water levels on the area-elevation curve. The differential areas are used as the basis for identifying potential improvements in agriculture, flood damage to homesteads, roads, and other infrastructure, and potential impacts on fisheries, wetlands, navigation channel depths, and so on.

Another key indicator is improvement or closure of existing water channels, which can have profound impacts on drainage, water quality, fisheries, and navigation.

The impact of FCD projects on dry season water levels is more difficult to predict. These are estimated based on structure designs, physical changes to the drainage channels, and external water levels; and assumptions about how structures will be operated and how the project will affect pumping, redistribution, and consumption of water.

Regional impacts
Regional hydrologic impacts were assessed using the Northeast Regional Model, which was developed by the Surface Water Modelling Centre (SWMC) and the NERP modelling team. It has been calibrated to the 1991 and 1992 water year observed levels and flows.

The 1991 water year was used as the basis for the simulations. This year was selected because it was a relatively severe year, and because it had been used during model development and calibration. The 1991 floods had return periods ranging from two to 25 years; conditions were especially severe during the pre-15 May pre-monsoon season.

Three scenarios were modelled: present conditions, future without Plan (FWO), and future with Plan (FW). Both future scenarios reflected the major changes expected to occur by 2015: implementation of the Tipaimukh Dam/Cachar Plain irrigation project in India, and expected morphological changes in the Kalni, Baulai, Khowai, and Someswari-Shibganjdhala Rivers. The FW scenario also included all the Plan FCD projects.

A number of limitations of this exercise should be kept in mind. Regional hydraulic and hydrologic processes are extremely complex, as is the model itself. Information on Tipaimukh Dam/Cachar Plain irrigation design and operation is sketchy. Changes in river morphology are difficult to predict accurately. Channel beds are assumed to be fixed, so the model does not capture interactions between river morphology and water levels and discharges. Pre-feasibility information was used for Plan FCD project design and operation characteristics. Further, the model approximates individual project's characteristics well enough for regional impact assessment, but not for assessment of individual projects' impacts. Datum corrections were undertaken based on information from the NERP/SOB second-order levelling program.

Therefore, the modelling results should be considered to be indicative of the changes which are to be expected rather than being absolutely correct.

Tipaimukh Dam break impacts
Modelling of a potential dam break is commonly done as part of the design of a large dam (in all likelihood a more detailed analysis has already been completed by the Indian authorities). In this study, the DAMBREAK module of the MIKE-11 computer model was used here to create model waves for illustrative purposes only. DAMBREAK simulates the dynamic behaviour of a flood wave given the dimensions of the reservoir and of the valley downstream of the dam and the dimensions and rate of formation of the breech. Previous experience demonstrates that modelling can reproduce dambreak flood wave characteristics reasonably well if the failure mode is adequately calibrated. We cannot and do not claim adequate calibration for these illustrative calculations.
7.2.2 Morphology
Some kinds of morphologic responses are reasonably predictable, but many others arise from stochastic processes whose predictability is intrinsically limited. For example, the long-term response of overall channel geometry (width and depth) to increased flood discharges can be estimated using empirical regime equations. But, if the river responds by avulsing and developing a new course or new channel pattern, these adjustments will be of secondary importance.

Other examples of unpredictability are provided by the instabilities of river systems on alluvial fans or aggrading river channels. In these settings, even small, local interventions can induce major perturbations. These disturbances can then propagate many kilometres downstream, initiating new impacts and new channel changes along the system.

These kinds of processes, which can greatly effect FCD infrastructure, are largely unpredictable over the time span considered by the Regional Plan, except in terms of general hazard identification and risk assessment.

Therefore, future morphologic characteristics in the region were assessed primarily qualitatively, using results of case histories from past project impacts, interpretive assessments using geomorphic methods and from simple regime theory calculations. General principles of river response prediction are based on information provided by Lacey (1929), Simons and Albertson (1960), Henderson (1963), de Vries (1971), and Joglekar (1971). In a few cases (such as on the Khowai, Kalni, and Someswari-Kangsha Rivers), additional computations were made using sediment transport predictors, or by conducting test calculations with a one-dimensional morphologic model (HEC-6). The hydrometric, hydraulic, and sediment transport data in the Northeast Region is simply inadequate for reliable region-wide assessments based on morphologic simulations using numerical models.

7.2.3 Agriculture
A description of current, FWO, and FW agricultural conditions for each project were prepared on the basis of secondary data, augmented by some primary data collected during brief field visits. Secondary agricultural data sources included the Land Resources Appraisal for Agricultural Development in Bangladesh (Agroecological Zone Reports) for soils, Water Resources Planning Organization data on agricultural input, maps, and area-elevation curves and water levels derived by NERP engineers from BWDB data.

The steps followed to predict changes in agricultural production were:

  1. Determine changes in land type from the engineering analysis by superimposing current, FW, and FWO water levels on the area elevation curve;
  2. Use the present crop distribution on each land type as the basis for future crop distribution on each land type; and
  3. Establish future yields on the basis of existing yields under conditions where no flood damage occurred.
All of the above steps were carried out in consultation with a cross-section of farmers. It is considered that this analytical approach is quite conservative. Greater increases in agriculture production than those suggested are technically possible.

Primary data on cropping patterns as a function of land type and crop damage, and on agricultural trends, was collected using Rapid Rural Appraisal (RRA) techniques. An experienced professional agronomist, accompanied by a multi-disciplinary team, followed several traverses cutting across different land types in the project area and interviewed groups of farmers on each land type, collecting information on yields and on cropping patterns and crop damage using an anna (one-eighth of a Taka) unit familiar to farmers. These farmer estimates were then converted to percentages of land types under each cropping pattern and percentage of each land type/cropping pattern combination damaged. For FWO and FW assessments, pre-project conditions were used as a guide: it was assumed that current associations between cropping pattern and hydrologic conditions would hold true in the future (that farmers' current and future cropping choices for a particular hydrologic regime would be the same).

7.2.4 Water Quality
Secondary data on water quality data for the region is extremely limited, and NERP did not undertake any water quality field measurements. Thus, the approach taken here is limited to qualitative characterization of incremental changes in biological and chemical contaminant inputs. For example, it is recognized that FCD-led intensification of agriculture will increase the amounts of pesticides and fertilizers used; that urban water supply will greatly increase urban sewage drainage volumes; that wastewater treatment will reduce effluent contaminant loadings; and so on.
7.2.5 Openwater Fisheries
Data sources
Both primary and secondary data were used. Secondary data sources included existing topographic maps, BFRSS data, and previous studies and reviews of the openwater fishery in Bangladesh, in particular Ali (1991), Azadi (1985), BCAS (1989), SLI/NHC Joint Venture (1989, 1990), Chong et al. (1991), Rahman (1989), Tsai and Ali (1985), and World Bank (1991).

Primary data was collected during case history field studies of FCD project and non-FCD areas; and long-term monitoring of fisheries at a partial flood protection project (Shanir Haor) and at a full flood protection project with pumped drainage and irrigation (Manu River Irrigation Project) (Fisheries Specialist Study, 1993). A fisheries specialist also participated in rapid appraisals of proposed project sites as a member of the multi-disciplinary teams.

FWO trends in fish production
Observations of past fish production indicate that production is declining by 1% to 3% per year overall. Conversely, estimates of future fish production taking into account interventions to improve biological management of the fishery suggest that great increases in fish production are possible. To assess project fish impacts (FW production minus FWO production), some assumption must be made about FWO trends. If the FWO trend is assumed to be negative, project negative impacts on fish production will be of significantly smaller magnitude than if the FWO trend is assumed to be positive.

Lacking any way to decide between these two scenarios, impacts of all the projects should be assessed assuming that FWO production is equal to present production. The high estimate `worst case' (FWO increasing trend) should fall within the range covered by the fish production impacts sensitivity test of the economic model.

Production model
Initial model. In a few of the earlier FCD pre-feasibility studies, a simple flooded-area model was used:

Impact = FW - FWO production =

[ ( R1 - R0 ) * PR0 ] + [ ( B1 - B0 ) * PB0 ] + [ ( W1 - W0 ) * PW0 ]

sub-0 and sub-1 refer to FWO and FW respectively

R, B, and W are river/channel, beel, and floodplain (F1+F2+F3) areas, in hectares

P is the unit FWO production in kg ha-1 for the respective habitats. Estimated regional average values are 175, 410, and 44 for river, beel, and floodplain respectively.

The pre-feasibility teams found this model difficult to use, in particular because it lacks provision to estimate impacts on migration access and water quality. While keeping in mind that our qualitative and quantitative understanding of fishery impact processes is very limited, it was felt to be desirable to develop a slightly more sophisticated fisheries impact model, which at the very least would be easier to use.

Improved model -- introduction. A slightly more complicated model was used for the later studies. It was developed based on the following thinking. First, the model should incorporate system processes and parameters/parameter groups about which we have some information and understanding: it should include all that we do know. Second, it should exclude processes/parameters that are purely speculative or uncharacterizable: it should exclude all that we do not know. Third, it should be flexible enough to reflect real, known variations between projects and project areas. Fourth, it should be uniform across projects with regard to parameters/processes about which we know very little. In summary, optimal complexity and optimal generality/specificity are desirable. (Thus, as understanding of the system improves, the model should also be improved.) The pre-feasibility studies identify issues needing further investigation in the feasibility study (that is, weaknesses in our current understanding).

System processes. The major system elements at this level of understanding appear to be (Table 7.1):

Migration access and timing. It seems to be accepted that:

  • A multiplicity of access points is desirable (i.e. that closing any or some channels is still deleterious),
  • The most important channels are those at the downstream end (that with flood onset, fish mainly migrate upstream and onto the floodplain, and downstream out of the beels into the river), and
  • Delay of flooding, as in partial flood control schemes, is highly disruptive
Overwintering (dry season) habitat. Numerical models of tropical openwater fishery systems show that total system production is far more sensitive to dry season habitat than to wet season habitat.

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