a b s t r a c t
Land use planning is an important element of the integrated watershed management approach. It not
only influences the environmental processes such as soil and stream bed erosion, sediment and nutrient
concentrations in streams, quality of surface and ground waters in a watershed, but also affects social and
economic development in that region. Although its importance in achieving sustainable development
has long been recognized, a land use planning methodology based on a systems approach involving
realistic computational modeling and meta-heuristic optimization is still lacking in the current practice
of integrated watershed management. The present study proposes a new approach which attempts to
combine computational modeling of upland watershed processes, fluvial processes and modern heuristic
optimization techniques to address the water-land use interrelationship in its full complexity. The best
land use allocation is decided by a multi-objective function that minimizes sediment yields and nutrient
concentrations as well as the total operation/implementation cost, while the water quality and the
production benefits from agricultural exploitation are maximized. The proposed optimization strategy
considers also the preferences of land owners. The runoff model AnnAGNPS (developed by USDA), and
the channel network model CCHE1D (developed by NCCHE), are linked together to simulate sediment/
pollutant transport process at watershed scale based on any assigned land use combination. The greedy
randomized adaptive Tabu search heuristic is used to flip the land use options for finding an optimum
combination of land use allocations. The approach is demonstrated by applying it to a demonstrative case
study involving USDA Goodwin Creek experimental watershed located in northern Mississippi. The
results show the improvement of the tradeoff between benefits and costs for the watershed, after
implementing the proposed optimal land use planning.
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