How Can We Represent Seasonal Land Use Dynamics in SWAT and SWAT+ Models for African Cultivated Catchments?

Albert Nkwasa,Anna Msigwa,Ann van Griensven,Hans C. Komakech,Boud Verbeiren,Celray James Chawanda

doi:10.3390/w12061541

Abstract

In SWAT and SWAT+ models, the variations in hydrological processes are represented by Hydrological Response Units (HRUs). In the default models, agricultural land cover is represented by a single growing cycle. However, agricultural land use, especially in African cultivated catchments, typically consists of several cropping seasons, following dry and wet seasonal patterns, and are hence incorrectly represented in SWAT and SWAT+ default models. In this paper, we propose a procedure to incorporate agricultural seasonal land-use dynamics by (1) mapping land-use trajectories instead of static land-cover maps and (2) linking these trajectories to agricultural management settings. This approach was tested in SWAT and SWAT+ models of Usa catchment in Tanzania that is intensively cultivated by implementing dominant dynamic trajectories. Our results were evaluated with remote-sensing observations for Leaf Area Index (LAI), which showed that a single growing cycle did not well represent vegetation dynamics. A better agreement was obtained after implementing seasonal land-use dynamics for cultivated HRUs. It was concluded that the representation of seasonal land-use dynamics through trajectory implementation can lead to improved temporal patterns of LAI in default models. The SWAT+ model had higher flexibility in representing agricultural practices, using decision tables, and by being able to represent mixed cropping cultivations.

Highlights

Agricultural land-use area and production has more than trebled around the globe since 1961 [1].In Sub-Saharan African countries like Tanzania, intensive agriculture that depends on the alternation between rainfed and irrigation serves as the main land use for both food security and economic growth [2]
The precipitation in the Soil and Water Assessment Tool (SWAT)+ model in Table 9 was slightly different from the precipitation in the SWAT model in Table 8, even though the same parameters were used during the different model setups
In SWAT, precipitation stations are allocated based on the sub-basins, while in SWAT+, this is done based on the landscape units

Summary

Introduction

Agricultural land-use area and production has more than trebled around the globe since 1961 [1]. In Sub-Saharan African countries like Tanzania, intensive agriculture that depends on the alternation between rainfed and irrigation serves as the main land use for both food security and economic growth [2]. The alternations in land use throughout the year, usually relying on the weather conditions, is referred to as land-use dynamics [3]. Land-use dynamics in agriculture often occur as multiple cropping cycles accompanied by different management practices, such as irrigation and fertilization. In African cultivated catchments, agricultural land-use dynamics are usually attributed to the high variability in seasonal weather patterns (wet and dry seasons) throughout the year [3].

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Conclusion