3. DIFERENCIAS E IGUALDADES DE LA NIC 12 IMPUESTO A LAS GANANCIAS Y
4.2. PROCEDIMIENTO DEL RECONOCIMIENTO DE PÉRDIDAS FISCALES
4.2.2. Tarifas Nominales para el Impuesto: Cálculo del Impuesto Corriente y Diferido,
To be able to model soil erosion with the LISEM model several plant and soil data are needed. Table 2.1 shows which plant and soil characteristics are needed as input for the LISEM model. For practical reasons these characteristics were measured on a number of fields that were assumed representative for the different land uses of the Danangou catchment. Both in 1998 and in 1999, 17 fields were selected to do the field
measurements on. The distribution of fields was, however, different in 1998 and 1999.
Table 4.1 gives an overview of the land use on the selected fields in 1998 and 1999. As can be seen from table 4.1 cropland was measured much more extensively than other land uses. In 1999 more care was taken to select croplands with different types of crop. Figure 4.1 shows the location of the fields that were used in 1999 to measure the LISEM input.
In 1999, a field was selected for each major crop. To get a representative input for the LISEM model care has been taken to select fields in different geographical positions (as far as the limited amount of fields allowed this). In principle, the measurements described in this section were repeated every two weeks. In 1998 all measurements were done every two weeks. The results showed that some parameters did not change much over time.
Some parameters were therefore measured less frequently in 1999. In 2000 the measurements could not be continued.
Appendix 4.1 gives the number of measurements that were performed for each parameter during each visit to the selected fields. As can be seen from the appendix, the choice for a relatively high temporal resolution and a relatively large number of fields limited, for some parameters, the number of measurements that could be performed on each field during each visit.
Table 4.1 Selected fields of 1998 and 1999
1998 1999
Land use Crop Land use Crop
1 cropland millet & soybean cropland foxtail millet
2 fallow wasteland
3 wasteland wasteland
4 cropland soybean (& maize) orchard
5 orchard woodland
6 woodland cropland pearl millet (& soybean) 7 cropland soybean (& rape seed) cropland foxtail millet
8 cropland soybean fallow
9 fallow orchard
10 wasteland woodland
11 shrubland cropland maize & soybean
12 - cropland potato
13 cropland maize, sunflower & soybean cropland soybean
14 woodland cropland foxtail millet & soybean
15 cropland fallow
16 cropland maize & soybean shrubland
17 orchard cropland buckwheat
18 cropland maize & soybean -
Plant Height
LISEM uses plant height for leaf drip calculation. The higher a crop is, the more energy dripping water will have and the more splash erosion the leaf drip can cause. Plant height was measured with tape. In the case of trees, triangulation was used.
Plant cover
LISEM uses plant coverage for the calculation of interception. It was estimated by looking straight down when plant height allowed this.
Leaf Area Index
Leaf area index (LAI) is used by LISEM to calculate water storage on the leaves. It is expressed as area of leaves per area of ground, and therefore has no dimension. It can range from 0 to about 6. There are several methods to calculate LAI. The one used here distinguished between plants and trees, but did not distinguish between different plant or tree species. The procedure followed was meant to calculate the total area of leaves on a certain area from the use of 20 representative leaves. If different species occurred, care was taken to produce a weighted estimate of average leaf area. Total area of the 20 representative leaves was determined using a scanner. The average leaf area was then multiplied by the total number of leaves (which was estimated) to give the total leaf area for a certain area. If the plant cover was below 0.1 LAI was not determined, but was assumed to be equal to plant cover.
79 Figure 4.1 Measurement locations in 1999. The 1999 land use map (figure 3.14) is used as
background.
Random Roughness
LISEM uses random roughness to calculate water storage on the soil surface and the start of overland flow. As the name suggests random roughness is considered to be random. It should therefore not be used for rills or land management operations. For the
measurement a pin meter (e.g. Wagner & Yiming Yu, 1991) was used. Because all pins have equal length, the soil surface profile is reproduced by the tops of the pins. Digital pictures were taken and pin positions were calculated with the PMPPROJ software (developed by J. Kilpelainen, Agricultural Research Centre, Jokioinen, Finland). Random roughness is defined as the standard deviation of pin positions. 294 pins were used for each field.
sampling grainsize & chemistry
Aggregate stability
Aggregate stability is used to calculate the amount of splash erosion. The test that was used here (the drip test of Low, 1954) aims at simulating the impact of falling rain on an aggregate. To be able to compare the results from different tests, the moisture content of the aggregates was standardised before measurement. The median number of drops needed to destroy the aggregates was used. In the tests at least 20 aggregates were measured for each plot.
Cohesion
LISEM uses cohesion to calculate erosion caused by overland flow. The cohesion at saturation is therefore critical and care must be taken to measure very wet soils. Cohesion was measured with a Torvane. As part of the aim of the project was to model gully erosion, cohesion of the second soil layer was also measured. A small 20 cm deep pit with was dug with a small shovel to perform these measurements.
Moisture content
The initial moisture content at the start of a LISEM simulation must be specified. As initial moisture content is very important in determining soil conductivity this is vital information for LISEM. Especially the moisture content of the upper soil layers is important in this respect. For the LISEM simulation the initial water content must be specified for each soil layer. Moisture content was measured in auger holes with a portable TDR at depths of 5, 15, 25, 45 and 75 cm.
Figure 4.2 Plant height in 1998 (May – October) and 1999 (April – September). The mean standard deviation of field averages (method 3 of appendix 4.1) was 69% of the average for
cropland and 60% for wasteland
0 10 20 30 40 50 60 70 80 90 100
15 20 25 30 35 40 45
time (week no.)
plant height (cm)
cropland 1998 cropland 1999 wasteland 1998 wasteland 1999
81 Apart from the periodical measurements discussed above LISEM needs Manning’s n for fields and channels, cohesion for channels, channel width, crust fraction and stone cover.
Only the crust fraction was determined every 2 weeks. The Manning’s n measurements will be discussed in chapter 6. Channel cohesion, channel width and stone cover were estimated or measured in the field once. No grass strips or roads were present in the area, so their width was zero.
Figure 4.3 Random Roughness in 1998 (May – October) and 1999 (April – September). The mean standard deviation of field averages (method 3 of appendix 4.1) was 22% of the average for
cropland and 46% for wasteland 4.1.2 Results
Figure 4.2 shows an example of the results of the bi-weekly measurements. It shows the plant height in 1998 and 1999 for two land uses. The chart clearly shows the effect of the growing season. In 1998 cropland also showed a clear decrease in plant height in October (week 41) due to harvesting. In 1999 the measurements stopped before harvesting.
Wasteland exhibited a much less pronounced change over time than cropland. Figure 4.2 also shows that in 1998 plant height was larger than in 1999. Part of the reason is that 1998 was a wetter year than 1999, but the 1998 field selection also contained more croplands with tall crops such as maize. Note that the differences between the different fields were large, which is reflected in large standard deviations. The other plant
characteristics (cover and leaf area index) gave similar results. Figure 4.3 shows random roughness results for 1998 and 1999. Random roughness did not show a clear trend during the year, only some variation that can probably be ascribed to the measurement itself. Apparently, random roughness was somewhat higher in 1999 than in 1998, although this difference is not statistically significant due to large standard deviations.
0.00 0.50 1.00 1.50 2.00 2.50
15 20 25 30 35 40 45
time (week no.)
random roughness (cm)
cropland 1998 cropland 1999 wasteland 1998 wasteland 1999
Generally speaking, the plant variables showed a temporal trend, while the soil surface characteristics did not. From the soil characteristics only the cropland cohesion
measurements of 1999 showed a trend. From April to June 1999 cohesion decreased because more and more of the measurement fields were ploughed during this period.
After that, cohesion increased again due to compaction of the plough layer as well as the formation of a soil crust. One would expect other soil surface characteristics to show a temporal trend as well, e.g. random roughness might be expected to show a decrease over time for croplands since crust formation can be expected to smooth the surface, but the data did not show this trend (figure 4.3).
From the gathered input data LISEM input data sets were produced on a bi-weekly basis, which means that when a storm occurred there were always data available that were collected within two weeks before the storm.
Figure 4.4 Soil moisture content in 1998 (May – October) and 1999 (April – September). The mean standard deviation of field averages (method 3 of appendix 4.1) was 30% of the average at
5 cm depth and 27% at 75 cm depth
The moisture content measurements showed a clear reaction to rainfall. Figure 4.4 shows the variation in moisture content for croplands. It shows several interesting features:
• The variation in moisture content at the surface (5 cm depth) was much larger than at 75 cm depth. This was to be expected. Nevertheless, the moisture content at 75 cm depth still showed the rainfall influence, albeit damped and maybe shifted in time. The measured variation in moisture content at the surface was more than 0.1 in both 1998 and 1999.
• The measurements at 75 cm depth showed a decrease of water content over time, both in 1998 and in 1999. The reason was probably water extraction by growing plants.
0.00 0.05 0.10 0.15 0.20 0.25 0.30
15 20 25 30 35 40 45
time (week no.)
moisture content (volume fraction)
cropland 1998, 5 cm depth cropland 1999, 5 cm depth cropland 1998, 75 cm depth cropland 1999, 75 cm depth
83
• The average moisture content increased with depth.
• Moisture contents in 1998 were clearly higher than in 1999, which was caused by the much larger amount of rain in 1998 (table 4.3). Surface moisture contents in 1999 were very low.
This study focused on the simulation of surface runoff, so that the moisture content variations in the uppermost part of the soil were much more important than those lower down.
Table 4.2 summarises the plant and soil data. To make comparison between 1998 and 1999 possible the average values of the different parameters were calculated for the period that was covered by the measurements in both years, namely week 21 to week 39 (May – September) of each year. Table 4.2 confirms the data presented in figures 4.2 to 4.4 and gives additional information regarding differences between land uses. For land use with trees (orchard and woodland) the plant characteristics are probably more
influenced by the difference in position of measurement field than by differences between the years.
Table 4.2 Yearly averages (week 21 to 39) of plant and soil characteristics in 1998 and 1999
Crop Fallow Orchard Wasteland Woodland
98 99 98 99 98 99 98 99 98 99
Plant height (cm) 50 31 33 14 344 310 37 18 739 1362
Plant cover (-) 0.21 0.12 0.14 0.12 0.29 0.27 0.44 0.25 0.78 0.44 Leaf area index (-) 1.07 0.59 0.57 0.20 2.80 1.32 1.04 0.39 5.00 1.71 Aggregate stability (-) 10.6 6.4 7.3 5.6 10.4 8.5 12.5 12.8 13.5 9.1 Dry cohesion (kg/cm2) 0.08 0.05 0.13 0.08 0.12 0.09 0.24 0.12 0.14 0.18 Wet cohesion (kg/cm2) 0.08 0.06 0.11 0.09 0.11 0.08 0.19 0.14 0.13 0.17 Cohesion at 20 cm (kg/cm2) 0.10 0.09 0.11 0.09 0.13 0.09 0.17 0.21 0.12 0.16 Random roughness (cm) 1.35 1.74 1.09 1.10 1.32 1.45 1.05 1.62 0.74 0.97 Moisture content at 5 cm (-) 0.12 0.06 0.09 0.05 0.15 0.06 0.13 0.06 0.15 0.07 Moisture content at 15 cm (-) 0.15 0.09 0.12 0.08 0.15 0.08 0.13 0.09 0.13 0.08 Moisture content at 25 cm (-) 0.16 0.11 0.13 0.10 0.16 0.09 0.13 0.09 0.14 0.09 Moisture content at 45 cm (-) 0.17 0.13 0.16 0.11 0.15 0.09 0.13 0.10 0.14 0.09 Moisture content at 75 cm (-) 0.19 0.14 0.17 0.13 0.17 0.09 0.14 0.11 0.15 0.10
4.2 Rainfall
Rainfall was measured with six calibrated tipping bucket rain gauges. The gauges had 0.2 mm accuracy. The bucket tips after every 0.2 mm of rain and the time of the tipping was recorded. These data could thus be used to calculate rainfall intensities. An additional six simple rain gauges were installed in 1999. These consist of bottle and funnel and could therefore only give rainfall totals. The position of both kinds of rain gauge is for 1999 given in figure 4.1.
Table 4.3 Monthly rainfall (mm), May to September. The values for Danangou are average values from 6 tipping bucket rain gauges
Danangou Ansai County
1971-1998
1998 1999 2000 mean stdev
May 144.7a 30.4 3.7 40.4 35.6
June 38.6 9.7 79.0 62.5 32.9
July 154.7 110.4 47.2 116.4 60.5
August 87.6 15.8 104.7 117.2 60.8
September 55.0 35.3 10.1b 76.1 47.1
May-September 480.6 201.6 244.7 412.6 96.0 a from May 5th
b until September 21st
Table 4.4 Summary of events used in this study. Maximum intensities (max I) are given in mm/h for 1-minute intervals
a) 1998
980705 980712 980715 980801 980823 Time start rain 12:15 2:26 14:12 13:43 20:41 Time end rain 14:39 3:41 15:19 14:31 21:56 Total event rain (mm) 20.8 22.3 28.7 15.1 13.0 Max I (catchment average) 41.3 59.4 66.2 69.9 47.2 Max I (single rain gauge) 60.3 71.6 108.5 107.5 70.9 Time max I 12:57 2:53 14:20 14:05 20:48
Gauge max I A C B C D
b) 1999 and 2000
990710 990720 990721 000807 000811 000829 Time start rain 14:50 13:30 2:42 10:01 18:28 21:37 Time end rain 15:15 14:30 3:00 16:09 19:35 22:06 Total event rain (mm) 10.7 15.8 3.5 18.7 11.6 16.8 Max I (catchment average) 67.7 55.6 35.8 18.2 49.5 84.9 Max I (single rain gauge) 107.5 130.0 72.4 24.1 83.6 189.1 Time max I 15:10 13:34 2:47 multiple 18:35 21:49
Gauge max I E D B multiple E D
85 Results
Monthly rainfall during the summer period is given in table 4.3. Comparison with the data of the Ansai County Meteorological Station (also in table 4.3) shows that 1998 had above average rainfall during the summer period, while 1999 and 2000 both had rainfall amounts that were far below average. Figure 4.5 shows the average daily rainfall from April to September 2000. During this period the total amount of rain was only about 250 mm, while the long-term average over this period is 438 mm.
From the event rainfall data 1-minute rainfall intensities were calculated for use in
LISEM. Summary data of the events used in this study are shown in table 4.4. The storms in table 4.4 include all the storms that are known to have produced runoff. Besides, a few storms that might have produced runoff as well as a few storms that did not produce runoff have been included. Total daily rainfall was generally a few mm higher than event rainfall. Comparison with figure 3.11 suggests that all events had recurrence intervals of less than one year. This certainly shows that much larger storms are possible. On the other hand, it can be expected that recurrence interval not only depends on rainfall total, but also on rainfall intensity. Table 4.4, for example, shows that the event of August 29th, 2000 had much higher intensities than the other events, while its total rainfall amount is not much higher. This storm was thus of very high intensity but short duration. Such a storm is likely to have a larger recurrence interval than other storms with comparable amounts of rainfall. This indicates that the available data are insufficient to determine recurrence interval with any precision.
Figure 4.5 Average daily rainfall in the Danangou catchment, April to September 2000
0
4.3 Soil physical properties