99
The CARMEN model (Cause-effect Relation Model to support Environmental
Negotiations), developed by the Dutch National Institute of Public Health and
the Environment (RIVM), accounts for all diffuse and point sources of nutrients to
groundwater and surface water. The model was developed during the early 1990s, and
has been updated for an assessment on European environmental priorities by RIVM
and other partners. Indicators used are nitrogen and phosphorus concentrations in
river basins (in mg N per litre; mg P per litre). Nutrient loading from point sources
(wastewater) and non-point sources (agriculture and atmospheric deposition) is
considered by the model, and output maps allow the estimation of eutrophication
risks at a regional to continental scale. Agriculture is responsible for diffuse pollution
through runoff water carrying organic manure and mineral fertilizers (NO
3
and PO
4
),
entering into streams and groundwater. In addition, ammonia is deposited downwind
from intensive livestock enterprises, affecting fragile ecosystems. Urban households
and industrial sources are emitting nitrate and phosphate into surface water, as well
as organic substances that contribute to biological and chemical oxygen demand.
However, wastewater treatment plants are eliminating an increasing proportion of
these pollutants, thus reducing eutrophication.
Salinization
Soil salinity caused by natural or human-induced processes is a major environmental
hazard. The global extent of primary salt-affected soils is about 955 M ha, while
secondary salinization affects some 77 M ha, with 58 percent of these in irrigated
areas. Nearly 20 percent of all irrigated land is salt-affected, and this proportion tends
to increase in spite of considerable efforts dedicated to land reclamation. Soil salinity
status and variation should be monitored carefully, providing timely information to
curb degradation trends and secure sustainable land use and management. Remote
sensing methods can contribute significantly to detecting changes of salt-related surface
features with time. Airborne geophysics and ground-based electromagnetic induction
meters, combined with ground data, have shown potential for mapping salinity in
layers at different depths (Metternich and Zinck 2003) but precise estimation of salt
quantities on the basis of satellite or aerial remote sensing is still difficult.
Soil salinization is a major problem in arid and semiarid regions with a shallow
saline water table. Salinization is influenced by climate, soil type, crop, irrigation water
quality and management practice, depth to water table, and salinity of the water table.
Capillary rise and salinity of soil profiles with a shallow saline water table can be
estimated by modelling. The modified TSAM (Jorenush and Sepashkah 2003) may be
suitable for estimating short-term mean rate of capillary rise, net long-term capillary
rise and seasonal soil salinities in different soil layers. In the Canadian prairies digital
terrain modelling is used in the prediction of soil salinity (Florinski et al., 2000). In
a rice cropping system in West Africa, Van Asten et al., (2003) used the PHREEQC
2.0 model (Parkhurst and Appelo 1999) to study actual and potential development of
soil salinity and sodicity problems by simulating concentration of the irrigation water
through evaporation.
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