The main objective of this paper is to report on the preliminary validation results of the Global Assessment of Soil Degradation (GLASOD) as a tool for mapping sediment sources in Tanzania. This study was carried out in a well studied catchment, the Nyumba Ya Mungu (NYM) reservoir catchment located in the upstream of Pangani River Sub-basin. Previous studies in the same catchment used quantitative approach that entailed comprehensive sediment sampling programme and numerical modelling to identify sediment sources and erosion processes. Although previous researchers’ findings were satisfactory, the methods used were demanding in terms of resources (time, funding, and personnel) and impractical to a large ungauged catchment. The quest to validate GLASOD map is evident as it was qualitatively developed through collating expert judgments of many soil scientists to produce a world map of human-induced soil degradation at a scale 1:10,000,000. In the current study sediment sources mapped from qualitative method (GLASOD) plus supplement field visit observations and quantitative approaches are compared and discussed in detail. Preliminary results suggest that the paired information on sediment sources, field based data versus GLASOD, for upper catchments or upland locations are more strongly correlated than lower reaches. The results of this study have further emphasized the fact that GLASOD map is satisfactory to depict large regional differences in soil degradation but it is not capable of explaining local degradation. Besides, GLASOD map does not capture erosion processes dynamics compared to comprehensive sediment sampling programme. Notwithstanding, GLASOD map might be a useful tool for sediment sources and erosion processes identification scoping studies in the study area. Based on this study, it is therefore recommended to complement the GLASOD map with field based data for detailed study initiatives.
An ideal way to identify sediment sources and erosion processes as suggested in literature would be to collect the sediment flow data spatially, at least from each of the river tributaries. Such a research project would definitely be demanding in terms of resources (i.e., time, funding and personnel) and logistical issues [
A number of indirect and direct methods exist for evaluating sediment sources and erosion processes. As an example of indirect method, it may be possible to estimate the total sheet and rill erosions within a drainage basin using a soil loss equation, such as the Universal Soil Loss Equation (USLE), and to estimate the downstream yield from this source by applying a sediment delivery ratio. Subtraction of the calculated soil erosion loss, corrected for sediment delivery, from the measured yield, gives an estimate of the contribution from other sources such as gully and channel erosions. The reliability of the results from the latter approach has been doubted by many scientists including [
Another more elaborative indirect method available to date applied by many workers is the fingerprinting technique. This method is based on the principle that sediments in suspension maintain some of the geochemical properties of their source material, and that these properties can thus be used as tracers [
A basic relationship between concentration of suspended sediment (C) and water discharge (Q) during single hydrologic events has been used by [
In the case of the direct approach, as critically reviewed by [
With the background thereof, one could deduce that there are no compelling methods on sediment sources identification. In response to the deadlock, researchers in Tanzania and the region have been continuously testing various complementary study frameworks such as hydrological variable mapping technique [
It should be noted that a Global Assessment of Soil Degradation (GLASOD) map was developed in late 1980’s in ad-hoc manner, on a basis of incomplete knowledge, as a matter of urgency [
This study uses a case study approach to adequately validate the readily available GLASOD map [
The case study area, Nyumba Ya Mungu reservoir catchment, is located in the upstream of Pangani River Basin (PRB), in the North-eastern part of Tanzania and covers an area of about 12,000 km2 [
The main sub-catchments in the study area are Weruweru, Kikafu, Sanya, Upper Kikuletwa, Rau, Mue, Himo, Lake Jipe, and Mount Meru slopes. This area has an average annual rainfall of about 1000 mm. The rainfall pattern is bimodal with two distinct rainy seasons, the main rainy season from March to June and the shorter rainy season from October to December. The altitude in the study area ranges between 700 and 5825 m.a.s.l. with Mount Killimanjaro peak as the highest ground. However, the lowlands terrain dominates with coverage of about 73% [
Global Assessment of Soil Degradation (GLASOD) mapping was first carried out by the International Soil Reference and Information Centre (ISRIC) [
Types | Soil Degradation |
---|---|
Mapped units with human-induced soil degradation | |
W: Water Erosion | Wt: Loss of topsoil |
Wd: Terrain definition/mass movement | |
C: Chemical Deterioration | Cn: Loss of nutrients and/or organic matter |
Cs: Salinization | |
Ca: Acidification | |
Cp: Pollution | |
Mapped units without Human-Induced Soil Degradation | |
S: Stable terrain | SN: Stable terrain under natural conditions |
SA: Stable terrain with permanent agriculture | |
SR: Terrain stabilized by human intervention | |
SR: Terrain stabilized by human intervention |
Symbol | Causal Factor |
---|---|
f | Deforestation and removal of the natural vegetation |
g | Overgrazing |
a | Agricultural activities |
e | Overexploitation of vegetation for domestic use |
i | Industrial activities |
erosion; chemical deterioration; and physical deterioration). However, in this work only groups that are common for Nyumba Ya Mungu reservoir catchment and the region are described (
The causative factors for soil degradation as stipulated in GLASOD are land use (socio-economic activities) related [
To date a number of limitations on use of GLASOD map are perceived as follows: it is not appropriate for national breakdowns; it is qualitative and subjective; limited number of attributes due to cartographic restrictions; the map only indicates human-induced soil degradation; visual exaggeration; extent classes rather than percentages; complex legend-combined extent and degree (severity) for four major degradation types (water and wind erosion, physical and chemical deterioration); only “dominant” main type of degradation is shown; and degradation sub-types only shown by codes [
The GLASOD map sourced from [
Multi-approaches were adopted to identify the sediment sources and erosion processes. The methods herein are: analyses of single hydrological events as sampled from continuous sediment pumping sampler and water levels recording data logger; fingerprinting-organic matter contents and particle size distribution of the transported sediment by rivers or those deposited in the downstream reservoirs (infer the origin and processes of sediment in the catchment); mapping of hydrological variables-rainfall in spatial and temporal domain correlated to sediment transport characteristics at the outlet of the catchment; and numerical modelling. The methods are explained in detail in sections 2.3.1 through 2.3.4 below.
The details on the sampling programme design and data processing are reported in [
The fingerprint techniques involved use of sediment properties as a natural tracer. Sediment origin was determined using natural properties of soil, reservoir bed substrate and suspended matter to fingerprint sediment sources. This study adopted a loss-on-ignition technique in estimating the soil organic matter content. The correlation between organic matter content and streamflow discharge was conducted and strength of correlation was determined as recommended in [
Correlation technique was adopted to indicate the responsiveness of sediment concentrations in rivers to the spatial rainfall intensities [
A semi-distributed, physics-based watershed model, Soil and Water Assessment Tool (SWAT: [
Despite the fact that it was intended to validate GLASOD map with previous findings of the quantitative approach, in addition the map performance was verified by location-based sediment yield rates. It should be noted that the latter are limited in terms of coverage and details. A validated Pacific Southwest Inter-Agency Committee (PSIAC) model [
Computed Sediment yields for surveyed locations geographically matching with GLASOD map features within the study area were analyzed and reclassified percentiles to represent four (4) severity levels. The percentiles are scaled as 0% - 25% for severity of 1; 25% - 50% for severity of 2; 50% - 75% for severity of 3; and 75% - 100% for severity of 4. Field data and GLASOD map severities were correlated. A Student’s t-distribu- tion table was used to confirm the strength of correlation. The correlation was considered strong if a computed t value is greater than table value at 5% level of significance as recommended by [
In this section of the paper a detailed explanation on the identified sediment sources and erosion processes based on extracted attributes from GLASOD map is provided. For this purpose,
referred to
For clarity purpose, the characteristics in
Loss of top soil through water erosion (sheet erosion) degradation type is found in the upstream parts of the catchment. As farming activity in the study area is practiced on the upper sub-catchments, slopes of Mts. Kilimanjaro and Meru, it is perceived that topsoil is rich in nutrients. Therefore, a relatively large amount of nutrients may be lost together with the topsoil. Such degradation type may lead to an impoverishment of the soil. In this context, on very steep slopes of Mts. Kilimanjaro and Meru, natural loss of topsoil may occur frequently. Unfortunately, this “geologic erosion” could not be indicated on the GLASOD map. Degree of degradation in the Lake Jipe sub-catchment is very strong and besides it experiences both sheet erosion and mass movement degradation types. In general the principal external dynamic agent of erosion is the hydrospheric forces of water, i.e., rainfall, runoff, and stream flows. The data from table also suggest that soil degradation is caused mainly through removal of natural vegetation and overgrazing. The latter is practised in major parts of the study area with coverage of 85 percent. The terrain in the overgrazed area could be characterized as low lands and sparsely vegetated. The two causative factors, removal of the natural vegetation and overgrazing are interrelated and have interplay role in triggering erosion. According to [