Investigating the Long-Term Hydrologic Impacts of Land Use Change on Annual Runoff in the Ziyarat Basin

Land use change has a significant impact on water resources. At a watershed scale, land use change can increase runoff, flooding, and nonpoint source pollution and can degrade downstream water bodies. Thus it is important to assess the potential hydrologic impacts of land-use change prior to watershed development. To evaluate the hydrologic impacts of LULC change, many hydrological models have been developed. Some of these models mentioned above require many types of data inputs and parameter estimation that are usually not readily available for land-use planners. Therefore, it is necessary to develop a much easier to use model to evaluate hydrological effects of the land-use changes. The Long-Term Hydrologic Impact Assessment (L-THIA) model is developed by Purdue University as a tool to assess how land-use change affects annual average runoff in a watershed. The model uses only readily available data, such as daily rainfall, land uses, and hydrologic soil group. The objectives of this paper are: 1) to derive LULC classification maps of the study area; 2) to quantitatively assess the effects of LULC change on direct runoff using the L-THIA model.

The Ziarat River Basin is located between 54°23' to 54°31' E longitude and 36°36' to 36°43' N latitude. It has an area of 9923 hectares.The basin has experienced dramatic urbanization in the past decade, resulting extensive land use changes. Therefore, it is important to assess hydrologic response to land use changes for future land use planning and management purposes.

L-THIA has been developed as a straightforward analysis tool that provides estimates of changes in runoff, recharge and non-point source pollution resulting from past or proposed land use changes. It gives long-term average annual runoff for a land use configuration, based on actual long-term climate data for that area. L-THIA results can be used to generate community awareness of potential long term problems and to support physical planning aimed at minimizing disturbance of critical areas. Recent concern over urban sprawl has focused on several land use change issues, including the failure to account for hydrologic aspects of land use change that can result in flooding, stream degradation, and erosion. L-THIA is based on computations of daily runoff obtained from long term climate records, soil data, CN value and land use of the area.

In order to investigate changes in land use, land use maps were generated from Landsat images in 1994 (TM) and 2015 (OLI). The images were geometrically corrected and Ortho-rectified using Ground Control Points and Digital Elevation model. In next stage, Training samples were collected for image classification, using field works, digital topographic maps and interpretation of false color composite. Finally, Image classification was done using supervised classification maximum likelihood. Based on this method, five land use category such as agriculture land, forest, city, grassland and water bodies were defined. Also, the digital soil data were reclassified into hydrologic soil groups A (Sand, loamy sand, or sandy loam); B (Silt loam or loam); C (Sandy clay loam) and D (Clay loam, silt clay loam, sandy clay, silt clay, or clay) according to rules of hydrologic groups classification for the L-THIA application. Once the land use and soil grids are prepared, the Curve Number can be calculated by using the Calculate the CN option from the L-THIA menu. The comparison between the land-use map and the CN layer was determined that most of the areas with curved number of 80 located in agricultural and urban land uses. After, the generation of CN layer, the L-THIA model was used to estimate annual depth and volume runoff using daily rainfall data with different LULC maps of 1994 and 2015.

Land use change is the most important human intervention in hydrological cycle of each watershed area. This paper investigates the hydrological effects of land use change in Ziarat basin in north of Iran, based on the Long-Term Hydrologic Impact Assessment (L-THIA) model. This is a hydrological model that requires the meteorological data, land use pattern and soil hydrology map. In this way, the Landsat satellite images of TM (1994) and OLI (2015) sensors; and techniques of remote sensing, such as supervised classification and Image difference were applied to identify and monitor the land use changes. The Classification results show five land use types, including residential areas, agricultural lands, rangelands, forests and water areas. The result of land use changes indicate an increase in the area of residential (96.3%), and agricultural (37.8%) lands, and a decrease in the area of rangelands (6.35%), forests (1.2%) and water surfaces (4.2%). Besides, the land use change during the last 21 years, has led to a 14.2 mm increase in the average amount of runoff depth, of which the portion of residential areas and agriculture lands were 37.26 and 28.91 percent, respectively. The results indicate that the L-THIA model have a good ability to assess the effects of land use and land cover change in the depth and volume of runoff. This model could provide the possibility of identifying accident prone areas, flood zones and flood management by spatial distribution map of runoff.

Keywords: Land use change, Runoff depth, Hydrological models, L-THIA.