|Atie Tri Juniati||Civil Engineering Study Program. Faculty of Engineering. Universitas Pancasila. Jakarta 16411. Indonesia|
|Dwita Sutjiningsih||Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia, Depok 16424, Indonesia|
|Herr Soeryantono||Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia, Depok 16424, Indonesia|
|Eko Kusratmoko||Department of Geography. Faculty of Mathematics & Natural Sciences. Universitas Indonesia, Depok 16424. Indonesiaode, and country|
Water is one of the main resources for sustainable city development. To ensure the availability of adequate water for human use, water resource managers need to estimate the amounts of water that enter, pass through, and leave individual watersheds. This is a challenge, because the relative magnitudes of the transfers of individual components in the hydrologic cycle can vary greatly. This paper analyses water availability estimation using the modified Soil Conservation Service Curve Number (SCS-CN) model. The model provides a hydrologically sound procedure to better represent capture behaviour. The study focuses on upper catchments located in West Java, Indonesia. Water availability estimation from this catchment area is needed to understand changes in river flow, as it constitutes information for the Indonesian Regional Water Utility Company (Perusahaan Daerah Air Minum (PDAM) Tirta Pakuan) in meeting the clean water needs of Bogor city. The existing SCS-CN model determines the Curve Number (CN) variable using Antecedent Moisture Condition (AMC). Daily moisture storage is updated based on varying the curve number and other hydrologic abstractions. A model was used to estimate stream flow components, direct-surface runoff, base flow, and hydrological abstractions. The calibration results indicate good model performance, with R2 and Nash Sutcliffe efficiency values for simulated monthly data of 0.62 and 0.36, respectively. The model was also successfully validated in the upper Cisadane catchment area by the respective R2 and Nash Sutcliffe efficiency values of 0.65 and 0.42. Validation of the model indicates that it reasonably simulates the catchment response and is suitable for use as a tool in estimating water availability. From these estimates, and in accordance with the data used, it can be concluded that the level of water availability can still meet Bogor's water needs from 2004-2009.
Long term hydrologic simulation; SCS-CN model; Upper Cisadane; Water availability; West Java
Rapid urban growth puts pressure on the environment, and is the cause of social change, infrastructure development and pollution problems. Water sources are one of the main needs for sustainable city development. Water managers, particularly in less developed countries, face issues with regard to lack of hydrological data and limitations in terms of resources and equipment to collect such data. In cases where hydrological data is scarce or incomplete, long term hydrologic simulation can help augment what is available. The availability of rainfall data over long periods, for example, can be used to extend a smaller stream flow dataset through long term simulation, which is useful for water resource planning and watershed management. Long-term hydrologic data are specifically required for analyses of water availability; computation of daily, fortnightly and monthly flows for reservoir operation; and drought analyses. (Mishra and Singh 2003).
Long term hydrologic simulation is conducted in various ways. Attempts at cataloguing such models have been previously made: the inventory prepared by the US Bureau of Reclamation in 1991 listed 64 watershed models in four categories; Wurbs (1998) categorized them into seven groups; at least two compilations of related proceedings exist, the first by Burton (1993) and the second by the Subcommittee on Hydrology of the IACWD (1998), which documented models developed by US federal agencies; and finally Singh (1995) discussed 26 models in use around the world. The models vary in their description of the hydrological cycle components, input complexities, number of parameters, time interval and output (Mishra and Singh 2003).
Mishra and Singh 2003 also explain that according to Woodward & Gburek (1992), there are two main factors that hinder adaptation of some of the most successful models in developing countries such as India, Pakistan, Nepal, and other Asian and African countries. The first is that some models may require hydrological information which water managers do not yet have the capacity to gauge, while the second is that some models may contain too many parameters which vary across basins and are difficult to estimate. Model practicality, coupled with limited data availability, further translate into reliability issues in performance.
The SCS-CN model is relatively simple and can perform well with a basic level of hydrological data, explaining its popularity among water managers and practitioners in Indonesia as one of the models of choice for runoff estimation. In 2007, a paper by Geetha et al. (2007) proposed a modification to the established CN model. Tested in four river basins in India located in different climatological settings, the modified CN procedure showed better performance than the standard model. This paper proposes to evaluate the modification to the CN model in an Indonesian climate setting in order to assess the merit of replacing the standard model in future practice.
Numerous studies have emphasized the impacts of climate change, LULC changes and/or population growth on water availability (Kumar et al., 2018; Nikam et al., 2018). Other studies have addressed more specific changes, such as the affect of water resource availability on the growth in house prices (Wu et al., 2018). Moreover, Lakshmi et al. (2018) conducted research on how satellite remote sensing can be used over large areas and long time periods to identify spatial and temporal variations. They also studied how to estimate total water fluctuations using a simple water balance model, and how to compare hydrologic phenomena across hydrologic regions. One common conclusion from all these studies is that the amount of water available is decreasing as a result of both climate change and increasing population.
The development of GIS technology has further increased its popularity in the processing, management, analysis, and presentation of digital data. Current utilization of GIS includes the spatial processing of data for analysis and modelling of water resource systems. The integration of GIS in such modelling for decision-making purposes has been practiced since the beginning of the 21st century, when spatial database and capable GIS software was introduced (Wade et al., 2012; Zerger & Ingle, 2003, cited in Osta & Masoud, 2015b). Several recent studies of water resource management integrating the use of GIS are Behailu et al. (2014), Hanson et al. (2014), Herrera-Pantoja et al. (2015), Mora et al. (2014), Perrin et al. (2012), Post et al. (2012) and Gunawan et al. (2013).
This study aims to conduct a runoff analysis using the SCS-CN method integrated with GIS to estimate water availability. Studies on runoff estimation using such a combined approach have been previously conducted by, for instance, Bank (2010), Mahmoud (2014), Mishra et al. (2012), Osta and Masoud (2015), Singh and Goyal (2017), Uwizeyimana et al. (2019) and Zelelew (2017).
Considering this background, this study therefore intends to estimate water availability using the modified SCS-CN model. This model reasonably simulates catchment response and is applicable to watersheds of a complex nature (Geetha et al. 2007). The study focuses on upper Cisadane catchments located in west Java, Indonesia (Fig. 1). Water availability estimation from this catchment area is needed to understand changes in river flow and as information for PDAM Tirta Pakuan in meeting the clean water needs of Bogor city.
The article is organized as follows. In the first section, the methodology and data will be discussed, explaining which data and methods were used, and how water availability was estimated. The second section discusses the results of the SCS-CN model employed, which determines the Curve Number (CN) variable using Antecedent Moisture Condition (AMC).
Finally, in the third part of the article, the performance of the calibrated and validated model is evaluated using stream flow data, and statistical evaluation is employed as the objective function to assess model performance. Model evaluation was conducted using 1) the correlation coefficient (R2), and 2) Nash–Sutcliffe efficiency (NSE). According to Waseem et al. (2017), NSE and R2 can give better agreement even for very poor models.
This research was funded by Ministry of Research and High Education Grand PDD 2018 with decree number 3/E/KPT/2018 and contract number 2108/LPPM/UP/III/2018. We are grateful to Dr. Ir. Setyo Sarwanto Moersidik, DEA, Eko Kusratmoko DR.rer nat, MS and Dr. Nyoman Suwartha, MT., MAgr., for their support in completing the research gap information.
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