Scenario 4 Scenario-based land use modeling by using CLUE-S model

42 The selection of driving factors that has significant effect to land use change was conducted by using logistic regression analysis. In case of forest, the quantitative analysis of driving factors of land use change by using logistic regression showed that the driving factors that significantly influence forest area were population density, elevation, distance to main road, distance to public facility and distance to education facility. Based on the calculation results, it can be concluded that the most significant driving factor of forest area was distance to education facility and followed by distance to public facility, elevation, distance to main road, and population density. The relationship between driving factors and land use change showed that distance to primary road, distance to public facility and education facility have positive effect to forest area to change which means that the higher the value of these factors, the higher the probability of land use to change. In contrast, population density, and elevation have negative effect that implies that the higher the value of these factors, the decrease the probability of land uses to change. The goodness of the statistical measurement revealed that ROC values for urban water area, grassland area, estate area, settlement area and forest area were 0.903, 0.701, 0.780, 0.813 and 0.994, which indicated that the probability of land uses built from these models were capable to represent land use changes and empirical analysis by using logistic regression method was satisfactory to examine the relationship between driving factors and land use change in study area. In order to improve the utility of scenario regarding to the deficiency of data and methods, this research has conducted several approaches, includes reducing the uncertainty of data classification and combining qualitative and quantitative approach in driving factors selection. 43

CHAPTER III IMPACT OF LAND USE CHANGES ON WATER YIELD IN UPSTREAM

CISADANE WATERSHED USING HEC-HMS MODEL

3.1. Introduction

3.2.1. Background

Runoff is one of the most important hydrologic variables used in most of the water resources applications. Sound information on quantity and rate of runoff from land surface into streams and rivers is vital for integrated water resource management. This information is needed in dealing with many watershed development and management problems. Physically distributed hydrologic models for prediction of river discharge require considerable hydrological and meteorological data. However, traditional data collection is expensive, error prone, time consuming and a difficult process. To alleviate this problem remote sensing and geographic information systems geo-informatics are sound technologies. The use of hydrological modeling systems for water resources planning and management is becoming increasingly popular. Since these hydrological models mostly deal with land phase of hydrological cycle, data related to topography and physical parameters of watershed are a necessary pre-requisite for these models. Computer based geographic information system furnish this requirement efficiently. These systems link land use data to topographic data and to other information related to geographic locations. When applied to hydrologic systems, non-topographic information can include description of soils, land use, ground cover, ground water conditions, as well as man-made systems and their characteristics on or below the land surface. Flow estimation at a point in a river is vital for a number of hydrologic applications including flood forecasting, water resource management, and for development applications. This chapter presents the result of a watershed scale rainfall-runoff modeling on gaged part of Upstream Cisadane Watershed using the hydrologic model in a GIS environment. The watersheds were modeled using HEC-