SCS-CN MODEL FOR QUANTIFYING SURFACE RUNOFF POTENTIAL IN THE ECOREGION SEGMENTATION OF BANTUL REGENCY

ABSTRACT


INTRODUCTION
Runoff constitutes an integral component within the hydrological cycle by controlling precipitation and water flow in water systems (Sitterson et. al., 2018.)Surface runoff, or overland flow, comprises rainfall that flows over the soil surface, transporting substances and soil particles (Appels et. al., 2017) occurs when rainfall intensity exceeds the soil's infiltration capacity (David, 2016).
Upon reaching saturation, when higher infiltration water, water fills depressions on the soil surface (Zhao et. al., 2018).
Once these depressions are filled with water, runoff occurs over the soil surface.
Runoff water is classified into two types, sheet surface runoff and rill surface runoff.However, when this water flow enters the stream or river channel system, it is referred to as streamflow runoff (Asdak, 2020).
Over time, the dynamics of population growth have continued to unfold within Bantul Regency.The rise in population is accompanied by an increase in the demand to fulfill human needs (Hemathilake and Gunathilake, 2022).
The high intensity of social and economic activities necessitates a substantial amount of water resources, especially in facing water scarcity caused by climate change (Larraz et. al., 2024).A region experiencing development tends to undergo changes in land area or land use conversion (Sitorus et al., 2011).Land use conversion impacts the low infiltration capacity of built-up areas (Permatasari et al., 2017).This will affect the availability of water in Bantul Regency in the year 2020.The availability of water represents the quantity of water reserves accessible for both domestic and non-domestic needs (Pratiknyo, 2016).Surface water availability can serve as an initial investment for development, thus underlining the importance of policy formulation aimed at better management of water availability in terms of both quality and quantity (Borisova et. al., 2020).This research aims to estimate the Furthermore, investigations into surface runoff based on ecoregion segmentation remain exceedingly rare in Indonesia.

Study Area
The study was conducted within Bantul

Data Analysis
The data analysis (     Bulit up areas are non-vegetated land. The absence of vegetation results in nothing that can reduce the velocity of surface runoff on the ground (Hidayah et al., 2022).As a result, the CN value is classified at the high value.This supports the assertion that F2-Qmi possesses the highest runoff potential across all seasons caused by built up area (Shrestha et. al., 2021).

Annual Potential
The largest runoff volume predominates in the central region of Bantul Regency, characterized by the F2-Qmi, amounting to 120,347,749.8m 3 (Table 5).The distribution of runoff volume is shown in substantial infiltration (Munawir et al., 2019).
The potential for large surface runoff volumes can yield both advantages and disadvantages.
Areas exhibiting significant surface runoff volumes are suitable for sustainable agriculture development (Mohamed et. al., 2020)

Potential in Rainy Season
The

Figure 2
the year 2020.This process is undertaken to acquire accurate daily rainfall data.When the coefficient correlation value (R) approaches 1, the correlation relationship becomes stronger or more accurate(Motovilov et al., 1999).The rainfall data necessary for calculating the potential surface runoff volume is the average rainfall of the region obtained using the Thiessen polygon method with the assistance of image data processing software, specifically GNU Octave-5.2.0.The SCS-CN method fundamentally correlates soil characteristics, vegetation, and land use with the CN, which represents the potential for runoff formation in response to specific rainfall events (Asdak, 2020).The determination of CN involves overlaying land use maps with hydrological soil group (HSG).HSG is based on soil texture, which affects the soil's infiltration capacity.Soil infiltration capacity decreases from class A to D (Wang et al., 2017).The determination of CN for calculation begins with values representing normal AMC based on

Figure
Figure 3b.These classes are determined based on the soil types present within each analytical unit, sourced from the soil data provided by the Regional Development Planning Agency (Bappeda) of Bantul Regency.The soil types identified within Bantul Regency include Udipsamments, Haplustepts, Endiaquepts, Haplustolls, and Haplusterts.These soil types are classified into HSG based on their textural characteristics, which are closely linked to the soil's effective water capacity and its influence on infiltration processes.HSG are categorized into four classes, denoted as A, B, C, and D (McCuen, 1998).Bantul Regency is predominantly characterized by

Figure 6 .
Figure 6.The expansive nature of this landform exerts a significant influence on the accumulation of runoff volume.The B-type exhibits the largest area within this landform, indicating a comparatively greater infiltration capacity than types C and D. However, the predominant land use, primarily comprising settlements and irrigated paddy fields, significantly contributes to the high CN values within this landform.The CN values associated with this land use are notably high, thereby indicating a substantial potential

Figure 6 .
Figure 6.The potetial volume of surface runoff map in 2020 Potential in Dry Season

Figure 7
Figure 7 illustrates the spatial distribution of potential surface runoff volumes in Bantul Regency in the dry season.Areas with substantial potential Figure 8.

Table 2 .
Data acquisition and source

Table 3 .
HSG classification Prabhu, et.al., 2020., 2020The AMC or initial soil moisture state serves as a crucial indicator in surface runoff volume.The determination of CN in the SCS-CN method relies on the cumulative precipitation over the preceding five days, with AMC I https://doi.org/10.20961/ge.v10i2.87132https://jurnal.uns.ac.id/GeoEco/article/view/87132SCS-CNModel for Quantifying Surface … | 256 designated for dry conditions, AMC II for normal conditions, and AMC III for wet conditions (Table4).

Table 4 .
Determination of AMC conditions

Table 6 .
The potential volume of surface runoff in 2020 (dry season) SCS-CN Model for Quantifying Surface … | 266

Table 7 .
The potential volume of surface runoff in 2020 (wet season)