BNPP/ASB Functional Value of Biodiversity Project – Phase II 

Appendix 4. Input parameters for GenRiver and SpatRain  

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Input parameters for SpatRain and GenRiver

The following parameters need to be derived from the ‘virtual watersheds’ that are supposed to represent the different strata in the global sampling scheme.

1. Climate

1.1 Rainfall

A number of formats are possible, as long as they allow a reconstruction of monthly exceedance curves of daily rainfall intensity:

30 (or at least 20) years of daily rainfall records for a station that can represent the area (or multiple stations if these are supposed to be similar), or

any ‘rainfall simulator’ equation with the appropriate parameters that can be used to generate a 30 year dataset for the site (e.g. MarkSim?)

1.2 Rainfall intensity

Data on rain duration and amount for a sampling period that is deemed representative to estimate the mean and coefficient of variation of rainfall depth per hour

1.3 Rainfall spatial correlation

An indication of the degree of spatial correlation in rainfall (correlation coefficient of daily rainfall as function of distance between stations), or of the generic nature of rainfall (frontal rains with high spatial correlation or convective storms that are ‘patchy’ and show low correlation)

1.4 Potential evaporation

Average values per month, derived from open pan evaporation measurements or from equation such as Penman’s that is calibrated on such data

 

2. Landform

Coarse DEM that allows for derivation of overall difference in elevation within the subcatchment, and a delineation of subsubcatchments. If there is a generic ‘language’ for the shape of the subcatchments relative to the main channel, we may use this.

3. Soils

Mean soil depth (till major restriction for root development)

Average texture (or soil type in a way that allows texture to be estimated) as input to ‘pedotransfer’ functions to estimate soil water retention curve (saturation, field capacity, wilting point)

Estimated bulk density relative to the reference value for soils under agricultural use, to estimate saturated hydraulic conductivity and potential infiltration

4. Geology

We need to estimate the ‘differential storage’ in ‘active groundwater’ as well as a ‘groundwater release’ fraction. So far these parameters were ‘tuned’ to the recession phase of actual riverflow during periods without rainfall. In the absence of such data we will need to ‘guesstimate’. If data on the seasonal variation in depth of groundwater table are available, we can use those.

5. Vegetation and Land cover

Fractions of total land cover that are

·      deciduous (reducing LAI in dry season to near 0),

·      semi deciduous (reducing LAI in dry season to less than 0.5 (??) of value in wet season),

·      evergreen maintaining LAI at over 0.5 of the maximum value

·      bare soil or build-up areas

·      open surface water

For more detailed assessments in the Sumberjaya and Mae Chaem areas we will use the actual time course of change. On that basis we might do with an estimate whether the actual change in the ‘virtual’ subcatchments has been ‘rapid’ (like 60 - > 10% forest cover in 25 years), ‘extremely rapid (faster than that), or slower (…)

6. Actual river debit

If available, river debit data for any period of time (expressed in m³ s^-1 in the river or mm day^-1 over the whole contributing catchment) will be valuable in ‘constraining’ the simulations. If not available, we will simply have to ‘believe’ the model predictions as such.

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Last updated: 28 November, 2003     ©2003 ASB. All rights reserved.