The phenomenon of urbanization has led to an increase in residential land and other economic activities that resulted in the conversion of undeveloped land into developed and settled lands. Thus, it has an impact on limited water absorption, and eventually, a flood occurs when extreme rainfall happens. The Kedurus watershed is a flood-prone area where floods consistently occur with a depth of up to 1 m. However, the Kedurus watershed is an area that has a vital function in the economic development of the city of Surabaya. From the previous research, three instruments were declared effective in reducing flooding. By using the positivistic approach, the purpose of this study is a spatial planning concept for flood reduction in the Kedurus River Basin. The results will be presented as spatial modeling of the flood with the existing conditions resulting in a flood inundation area of 228.88 ha. The stages of the formulation of the spatial planning concept for flood reduction resulted in several proposals, namely, the allocation of green open space for all the land assets of the Surabaya City government and the provision of a maximum requirement of 60% development for space allocation on existing nondeveloped land.
Indonesia, as a country in its development, still faces major problems in the development of its cities. One of the major problems in Indonesian cities is the urbanization in big cities that continues to increase, which leads to an increase in the need for urban space such as housing land . This rapid development can cause the problem of land limitations to increase , and as the population increases, land resources become increasingly important . However, the conversion of land function from undeveloped land to developed land can increase the occurrence of inundation and flooding .
The urbanization phenomenon, where rural areas were converted into urban areas, mostly increased built-up areas, such as housing or various economic activities. Therefore, there were conversions from nonbuilt-up areas such as open spaces to built-up areas. One of the common impacts of these conversions is the decrease in the water catchment capacity. In general, three main concepts can be utilized to reduce the flood risk caused by open space conversion: land use management, building regulations, and improvement of the drainage system.
These problems regarding land use increase the volume of surface runoff, which causes an imbalance in the water system or a change in the hydrological cycle [5,6]. Changes in land use in watersheds (catchment area of river system [DAS]) have a significant effect on floods  and resulted in an increase in water volume of 9.84% and peak discharge of 4.13% in all sub-watersheds [8,9].
The hydrologic approach is a modeling approach that is formulated using statistical, physical, and hydrographic data. The model formulation usually involved incomplete or generalized information about meteorological data, hydrological data, and the catchment area characteristics. Examples of modeling approaches for flood modeling are HEC-RAS, DUFLOW, and LISFLOOD .
The geomorphologic approach is a modeling approach that is formulated based on the geomorphologic analysis toward geologic characteristics and fluvial systems and supported by previous flood events and detailed-level topographic information . This approach stems from the fact that micro-reliefs that exist on flood plains indicate the water-flow pattern. Furthermore, existing land-form configurations and fluvial sediment distributions are results of the same water-flow pattern that may cause floods in the future.
A combination of the hydrologic and geomorphologic approaches, which utilizes past flood events, analysis of monitoring data on meteorological and hydrological factors, and geomorphologic analysis to make a summary of past flood events using the geomorphologic characteristics. Hence, the study area can be grouped into three categories: areas that were previously flooded, areas with the same characteristics but not yet flooded, and areas that are very unlikely to be flooded in the future.
The previous research in Indonesia, especially in Surabaya city, mostly focused on how to increase the drainage capacity, provide water pumps, and maximize the regulatory infrastructures. However, if we consider that conversion from nonbuilt-up to built-up area as the main contributor to the increase in flood hazard, it is necessary to focus on how to manage land use in the study area. This research provides an alternative solution to flood risk management other than increasing the capacity of drainage infrastructures.
The theoretical contribution of this research is to provide a new approach for flood risk management in the form of land use management and building management, as opposed to the most common method in Surabaya city, which is by increasing the drainage capacity. As for the application contribution, this research can serve as one of the references that can be included by the government of Surabaya city when they are formulating solutions for flood hazards.
1.1 Study area
Surabaya is the second-largest city in Indonesia , and a map of potential flood disasters in the RTRW document for Surabaya divided the city into three locations, namely, the East Coast of Surabaya, the North Coast of Surabaya, and the Kedurus Watershed . The flood that occurred in the Kedurus watershed was caused by the overflow of the Kedurus River and changes in land use. Therefore, it is necessary to interfere to reduce the potential flood hazard. The worst floods in the city of Surabaya occurred in the Wiyung area, which was up to 1 m , more than 100 ha was inundated by the Kedurus River flood. The 2018 Surabaya Drainage Management Plan data show that several areas of Wiyung often experience flooding, with a flood duration of 1 h and an average height of 0.5 m.
Floods during the rainy season in the Wiyung area occur due to the impact of land conversion. This is backed up by the fact that the Wiyung area has a trend of changing the use of agricultural land into a settlement based on the RDTRK UP Wiyung data. As for the data on the RTRW of Surabaya for 2014–2034, the Wiyung Development Unit has the main function for settlements, especially the development of medium-density housing and settlements, education, industry, and protection of nature [17,18]. Apart from these reasons, the Kedurus watershed was also chosen due to the uniqueness of the urban flood area. The aim is to increase the regional economic target in the Kedurus watershed while maintaining its ability to anticipate floods.
In terms of Wiyung’s RDTRK strategic plan, there are several development plans that will have an impact on increasing the chance of flood itself. In terms of infrastructure in the Kedurus watershed in UP Wiyung, the existence of the Middle West Ring Road network will increase settlement activities and business activities around it which will reduce the function of water infiltration into the ground. In addition, when viewed from the spatial planning objective of UP Wiyung’s RDTRK, which is investment friendly, it will make it easy for housing developers to establish housing clusters that will reduce the function of water absorption in the Kedurus watershed.
This is supported by the condition of the existing spatial pattern, namely, formal housing in the Kedurus watershed in UP Wiyung. This also applies to the RDTRK UP spatial plan. Wiyung will have a medium-density settlement space allocation plan (R3) around the Kedurus watershed. Due to the potential for flooding in the Kedurus watershed, which has an impact on the disruption of urban activities, it is necessary to take steps to control the flooding in the Kedurus watershed.
In spatial planning, there are various instruments that can be used to control flooding. There are three spatial planning instruments, namely, land use regulation, building regulation, and drainage systems. From previous studies [19,20,21,22], these three instruments were declared effective in reducing flooding. Where related to the study of flood reduction in the Kedurus watershed through land use regulation, it can reduce the flood discharge up to 12.92% of the flood discharge in existing land uses. In addition, the previous study  discussed the related building regulation, specifically setting the basic building coefficient (maximum percentage within a land parcel that can be built [KDB]) and green basic coefficient (minimum percentage of open space within a land parcel [KDH]). The results obtained by adding 10% KDH in residential areas will reduce the flood discharge by 1.4%. Arrangement of the drainage system can be done by providing a drainage network and retention pond. From previous studies [24,25,26], it is found that a good drainage system can reduce floods by 58.79%.
Empirical facts in the field of flood control in Surabaya are still inaccurate considering that, currently, the area in the Kedurus watershed has exceeded 50% of the watershed area and so efforts to add drainage channels and increase river capacity are difficult to carry out . Similar research was conducted  related to reducing floods in the Kedurus watershed by using land use regulation instruments and building codes, which were analyzed by using the soil and water assessment tool model. The results of the research were that all areas of the Kedurus watershed were divided into 27 sub-watersheds that experienced a flood, namely, sub-watershed 1, 2, 3, 5, 6, 8, 12, 13, 15, 22, 24, and 27 with a total overflow volume of 546797.53 m3. The combination of land use regulations and building codes can reduce flood discharge by 47.51% .
Based on the description of the aforementioned problem, the aim of this study is to formulate a spatial planning concept in the form of land use regulation, building codes, and drainage systems for flood reduction in the Kedurus River watershed. The scope of the area in this study is the flood area identified by  in the Kedurus watershed. The research area used is the sub-watershed in the administrative area of Surabaya, and the justification is the availability of data on the surface model digitization, with an accuracy of 0.33 m × 0.33 m. The research area is the Lakarsantri District. The administrative boundaries of the research area are Lakarsantri District to the north, Wiyung District to the east, Karangpilang District to the south, and Menganti District to the west (Figure 1).
This study uses a positivistic research paradigm. This study will identify the hydrological conditions of the Kedurus watershed with numerical data on rainfall, river profiles, topography, area per land use, and building base coefficient. Then, the related spatial plans related to land use arrangements, building codes, and drainage networks will be evaluated. The population of this study was all flooded locations in the spatial model of the rain flood on November 25, 2017. As for the sample, several locations were selected based on spatial random sampling with Arc Map 10.7 software. The number of samples from 47 locations was taken from a combination of inundation survey data for the Surabaya Drainage Management Plan 2018 document and Online News.
The data analysis in this study is divided into three phases, namely, building a spatial model of floods based on the existing hydrological conditions that cause flooding in the Kedurus watershed; evaluating land use arrangements, building rules, and existing drainage systems in order to reduce flooding in the Kedurus watershed; and formulating spatial concepts. Related to land use regulations, this research intended to formulate new building codes and an effective drainage system in reducing flooding in the Kedurus watershed. The tools used for analysis are HEC-RAS (as software for combining flood discharge data and river profiles to create a flood condition map) and Arc GIS 10.5 (as software for spatial data processing).
2.1 Building a spatial flood model based on existing hydrological conditions that cause floods in the Kedurus watershed
This target is divided into several stages in the process of developing a spatial flood model  in the Kedurus watershed, namely:
Identification of the peak discharge (Q p) in the Kedurus watershed. At this stage, it is carried out to determine the maximum load volume of rain that flows into the channel by using the unit synthesis hydrograph calculation to convert the rainfall in the study area to peak discharge. In identifying the peak discharge, it is necessary to determine the value of the flow coefficient (runoff), which is carried out using the Cook flow coefficient method. This is done by inputting a map of the level of soil infiltration capacity, flow density, vegetation cover, and slope  and furthermore by analyzing the frequency of potential extreme rainfall with the formula of the Gumbel distribution method  and converting the daily rainfall into the effective rain per hour using the Ø Index method and the Horton method. Then, the hydrograph of the Snyder synthesis unit is calculated and the superposition hydrograph process is carried out, which produces a superposition hydrograph at the outlet of the Kedurus watershed segment, which is the outlet of all sub-watersheds in the upstream watershed segment. The outlet will be defined as an inlet in hydraulic modeling. This process is carried out in the upstream segment whose outlet is adjacent to the downstream segment inlet, which was affected by the flood, namely, the Kedurus sub-watershed. These discharge data then become the input for hydraulic modeling in the HEC-RAS software. The area of the sub-watershed that was affected by the flooding based on the last flood event in 2017 and which was the delineation of the analysis area in HEC-RAS was 70 km2.
The geometry correction process of Kedurus Main River on Digital Terrain Model Lidar Surabaya is performed. Digital Terrain Model (DTM) data from Lidar Surabaya with a resolution of 0.33 m × 0.33 m are processed into variable topographic conditions as input for hydraulic modeling in the HEC-RAS and also as a watershed characteristic variable in processing discharge data.
A map of the distribution of the Manning roughness coefficient in the Kedurus watershed is created. At this stage, a global reference is used to assess the Manning roughness coefficient in the study area [32,33]: the Manning roughness coefficient is not directly used, but it is combined with the green baseline coefficient.
Spatial modeling of floods in the Kedurus watershed. At this stage, the data obtained from steps 1–3 are used as data input. These data through HEC-GeoRAS will be packaged into a file in RAS format, as input for geometric data in HEC-RAS . The hydraulic analysis was performed using the unsteady flow method. This stage produces a flow profile, which is then converted through the HEC-GeoRAS extension into spatial information in the form of the distribution of the affected location, the extent, and the depth of the flood .
2.2 Evaluating land use regulations, building codes, and existing drainage systems to reduce flooding in the Kedurus watershed
In this section, planning evaluations related to land use arrangements, building codes, and drainage systems are carried out by adjusting the conditions of the plans and referred documents. The planning document referred to for regulating land use is the Detailed Spatial Plan for the Wiyung Development Unit with the data of the Public Housing Service for Settlement Areas and the Surabaya City Spatial Planning Cipta Karya. Meanwhile, the drainage system uses the Surabaya Drainage Management Plant document with the data of the Public Works Office of Bina Marga. This target is divided into several stages:
Identification of the peak discharge due to the implementation of the land use plan and the basic building coefficient plan: This stage is carried out to determine the discharge load, which is caused by the implementation of the land use plan and the planning of the basic building coefficient. First, it is necessary to determine the runoff value due to the application of the land use plan and the basic building coefficient (KDB) plan using the Cook flow coefficient approach, in which the vegetation cover parameters are adjusted to the land use plan and the basic building plan. The reference value of the runoff coefficient for each class of land use plans is derived from ref. . The runoff value of each land use plan classification is then multiplied by the planned basic building coefficient per land use plan block. Furthermore, the conversion of daily rainfall to effective rain per hour is carried out by running off the plan and carrying out the superposition hydrograph process with a runoff plan.
Geometry correction of the main Kedurus River based on the River Cross Section Plan in the Surabaya Drainage Management Plan: At this stage, the River Cross Section Plan for SDMP 2018 will be applied to the Model Lidar Surabaya Digital Terrain data 0.33 m × 0.33 m. The SDMP application in DTM uses the Cross-Section Editor in the HEC-RAS 5.0 Software. The value in the section that will be changed is in accordance with the value in the 2018 SDMP.
Developing a manning roughness coefficient distribution map based on the Land Use Plan and the Basic Building Coefficient Plan: At this stage, the manning roughness coefficient will be created based on the land use plan data and the green baseline coefficient. The value will then be multiplied by the green base’s coefficient because the larger the non-built land, the greater the green base’s coefficient value.
Spatial Modeling of Kedurus Watershed Flood for Evaluation of Land Use Plans, Basic Building Coefficient Plans, and Drainage Channel Plans: At this stage, the HEC-RAS 5.0 software is still using the same as target 1. The difference in settings is only in the value of the hydrograph graph according to the Run-Off Plan, the Terrain model uses the results of the DTM correction with SDMP 2018, and the manning coefficient map uses the land use plan data and the basic building coefficient.
2.3 Formulation of the concept of spatial planning to reduce flooding in the Kedurus watershed
In this section, the conceptual formulation is carried out using sensitivity analysis tools to assess the significance of variable changes in the area of flood inundation. From the sensitivity analysis, it is known that the priority variables are significant in reducing the area of flood inundation. Then, the formulation is carried out in the form of scenarios 1 and 2. Sensitivity analysis has several stages:
Sensitivity 1: Changes in Land Use Variables. Sensitivity testing of land use intensity parameters was carried out by increasing the agricultural area and open area by 15% from current conditions. This is because agriculture and open areas have the least coefficient of runoff and are optimal for absorbing water into the soil
Sensitivity 2: Basic Building Coefficient. Testing of the basic building coefficient parameters is carried out by lowering the KDB for Developed Land by 15% from the current condition. The basic building coefficient is decreased from KDB 50–100%. This is because KDB below 40 is a nonbuilt area with dominance in open areas.
Sensitivity 3: Drainage Channel Capacity. Testing of the drainage channel capacity parameters is carried out by deepening the main Kedurus drainage channel by 15% from its existing depth. The technique used is to change the Lidar Surabaya DTM data from 0.33 × 0.33 m with XS Interpolation with the help of RAS Mapper in HEC-RAS 5. The main Kedurus drainage channel will be divided into 31 cross-sections to identify the depth of the existing channel. Then it will be set by 15% of the existing condition.
Sensitivity 4: Combination of Land Use Intensity, Building Base Coefficient, and Drainage Capacity. In this sensitivity test, a combination of parameters of land use intensity, basic building efficiency, and channel capacity will be carried out. The technique is used to combine data on sensitivity 1, 2, and 3.
After knowing the impact of changing each parameter on reducing the area of flood inundation. Then, it is prioritized based on how sensitive parameter changes are to flood reduction.
The condition of the maximum daily rainfall per year in the study area fluctuated from 1979 to 2020 with a pattern that shows higher rainfall every year, and one of them is caused by global warming. The existing flood conditions in the research area from data records in 2017 caused 251.7 ha of submerged areas with an average height of 18.94 cm and with a duration of 64.55 min. This shows that the submerged area is quite large with different conditions. The condition of the existing land use in the research area was obtained from the Base Map of the RTDRK UP Wiyung of the Surabaya City Settlement, and Human Settlements Area Public Housing Service in 2018 shows that the research area is dominated by residential areas with 46.21%, while the open area is 18.73%. This has an impact on increasing the Runoff coefficient so that the rainwater that overflows the drainage channel will be even greater. The conditions of the existing basic building coefficient (KDB) and green base coefficient (KDH) are 10 and 90. This shows that the condition of development in the Kedurus watershed is still relatively low, and the Kedurus watershed has the potential to withstand a fairly high flood rate. The RDTRK Land Use Plan (Detailed Plan for Spatial Planning) in the Kedurus watershed shows that the dominance of land use plans in the Kedurus watershed is housing, especially with medium and high density covering an area of 696.32 and 655.77 ha. Detailed results for each objective are presented in the following sections.
3.1 Building a spatial flood model based on existing hydrological conditions that cause floods in the Kedurus watershed
In the analysis of target 1, a flood map with five time series is generated: the flood on November 25, 2017, 2-year return period, 5-year return period, 10-year return period, and 20-year return period (Figure 2). The results of the spatial model of the flood are in the form of a.TIF raster file that describes the results of the model that has not been filtered/cut in areas that are waters (rivers and other water areas).
The level of accuracy of the model to the actual flood conditions is measured by the value of root mean square error (RMSE) and (LE90 Linear Error 90%), which have become the standard in the vertical accuracy test of spatial data [34,35,36,37]. The results of the flood model were validated by testing the RMSE flood model on November 25, which had a value of 0.15, which means that on average the model had an error rate in describing the actual flood conditions of 0.046 m. Meanwhile, the calculation of LE09 shows that the value of the model is 0.24, which means that the maximum difference between the flood model and the actual condition of the flood is 0.24 m. From the RMSE value of 0.15 below the value of errors 1 [35,36], the model is declared valid. When compared with a similar study from ref. , which modeled flooding with the same method, the RMSE value was 0.076, and then the flood model in this study is better. Because the LE09 value is less than the value of 1, the model is categorized as quality model 1 . From the spatial flood model, it is known that the flood area covers 8.27% of the research area or an area of 228.88 ha in the most extreme conditions during the 20-year return period and from the worst-case scenario, and the peak discharge reaches 20.90 m3/s, which is assumed to be the maximum load that must be accommodated by the Kedurus watershed.
3.2 Evaluating land use regulations, building codes, and existing drainage systems to reduce flood in the Kedurus watershed
In the analysis of target 2, the Kedurus watershed runoff coefficient is generated based on the land use plan and the basic building coefficient plan. As a result of the implementation of the land use plan and the KDB plan in the Kedurus watershed, the Run-Off value of 0.38 is obtained, meaning that of 100 mm of rain in a day, 38 mm could not be infiltrated into the ground and had to be accommodated in drainage channels. The runoff parameter of the plan increased by 0.2 points from the existing runoff parameter. Thus, RDTRK in the Kedurus watershed does not decrease the Run-Off value and even increases the Run-Off value, which has the potential to increase flooding. The peak discharge in the planned condition also increases compared to the peak discharge in the existing condition.
The results of the spatial flood modeling in the Kedurus watershed using the parameters of the land use plan, KDB plan, and Kedurus Drainage Plan (Figure 2) show that the existing land use plans, KDB plans, and drainage plans that currently exist do not reduce the potential for flooding, and in fact, they tend to increase the potential for flooding, in slightly.
3.3 Formulating the concept of spatial planning to reduce flooding in the Kedurus watershed
The resulting spatial layout concept for flood reduction in the Kedurus watershed is a combination of two scenarios (Table 1). Scenario 1 is a concept consisting of changes in land use variables, basic building coefficients, and channel capacity based on the significant value and the possibility to do so. Scenario 2 is a concept that consists of optimizing all variables and using green infrastructure components to reduce flooding by 100%. With the sensitivity analysis and the concept of reducing inundation area, the application of the spatial planning concept for reducing flooding in the Kedurus watershed still leaves a flood inundation area of 6.26 ha from 80.27 or has decreased by 97.26% from the existing conditions. In addition, the results obtained by changing the basic coefficient of buildings have the greatest impact in reducing the flood inundation area by 42.29%. Then in second place is changing the intensity of land use, which has an impact on reducing the inundation area by 36.77%. Finally, changing the capacity of the drainage channel reduces the inundation area by 16.00%. Combining these three parameters will reduce the inundation area by 69.38%. From the results of the process of formulating the spatial planning concept for flood reduction in the Kedurus watershed, the overall conclusion is presented in Table 1.
|No.||Parameter||Results||Total flood inundation area (ha)|
|Run off||Input rain through channel||Q p 1||Inundation area in ha|
|1. Land use intensity||0.3||43.182||17.4||37.44||91.16||13.96||2.16||144.73|
|Reducing percentage from existing condition||11.55||21.26||79.25||38.19||36.77|
|2. Basic building coefficient||0.28||40.3||16.5||37.88||79.29||12.91||2.01||132.09|
|Reducing percentage from existing condition||10.51||31.52||80.81||42.45||42.29|
|Reducing percentage from existing condition||5.26||21.94||13.23||2.90||16.00|
|4. Land use and basic coefficients of buildings and drainage channels||0.25||35.48||14.43||17.93||40.34||10.81||0.99||70.07|
|Reducing percentage from existing condition||57.64||65.16||83.94||71.57||69.38|
|The concept of reducing flood inundation amount|
|1. Scenario 1||0.28||40.48||16.45||20.13||43.74||15.11||1.29||80.27|
|Reducing percentage from existing condition||52.45||62.22||77.54||63||64.93|
|2. Scenario 2||0.23||33.26||12.65||1.19||2.87||2.2||0||6.26|
|Reducing percentage from existing condition||97.19||97.53||96.73||100||97.26|
1Return period of 20 years.
Bold values are input or output of the model.
The results of the process of formulating the spatial planning concept for flood reduction in the Kedurus watershed (Table 1) were obtained from the planned changes in each parameter. These changes use 15% incremental increase/decrease as follows:
In the parameter of land use intensity, the changes that must be made are increasing the agricultural area and open area by 15% from current conditions.
In the basic building coefficient parameter, the changes that must be made are reducing the KDB of built land by 15% from the current condition.
In the drainage channel capacity parameter, changes that must be made are increasing the capacity of the drainage channel by 15% from the current condition.
In the parameters of land use and the basic coefficient of buildings and drainage channels, the changes that must be made increase the agricultural area and open areas by 15% from current conditions and reduce the KDB of built land by 15% from current conditions and increase the capacity of the drainage channels by 15% of the current state.
In the concept of reducing the area of flood inundation in scenario 1, the changes that must be made are adjusting land use and basic building coefficients as well as channel capacity based on possibilities.
In the concept of reducing the area of flood inundation in scenario 2, the changes that must be made are adding retention ponds.
Overall, the spatial planning concept for reducing flooding in the Kedurus watershed is divided into four variables: land use (Table 2 and Figure 3), basic building coefficient (Table 3 and Figure 4), channel capacity, and use of the retention pond.
|Proposed land use plan||Area (ha)||%|
|Office and business district||24.5||0.7|
|Defense and security||0.0||0.0|
|Agriculture and livestock||302.8||8.9|
|Green open space on city government asset land||71.9||2.1|
|Other public service facilities||0.0||0.0|
|Park and field||257.0||7.6|
|Basic building coefficient recommendations||Total area (ha)||%|
To illustrate that the recommendations for engineering actions on land use variables, basic building coefficients, and channel capacity can be implemented in the field. The implementation level of each recommendation was determined using a series of calculation to determine the suggested value, which are the minimum or maximum values to produce a significant flood reduction. The recommendations for flood reduction in the Kedurus Watershed using those values are as follows:
The land of Surabaya City Government assets is turned into a green open space (green open spaces which are managed by the government [RTH]).
Space allocation for protected area zones follows the spatial plan for the Surabaya City RDTRK spatial plan.
Spatial allocation for cultivation in the sub-zone of settlement, trade, public service, and industry, are allocated on existing non-built land, with maximum 60% percentage of the land, and must have infiltration wells.
Decreasing the basic building coefficient by 5% in various industries, utility installations, government offices, public facilities, defense, and security.
A 10% decrease in the basic building coefficient for trade and services.
Decrease the base building coefficient by 15% for high-density housing, medium-density housing, and high-density housing.
Allocation of the basic building coefficient is a maximum of 60% on the allocation of cultivation that converts the existing undeveloped land.
Increase the capacity of the Kedurus drainage channel by deepening it by 25% from the existing condition to a maximum of 4.3 m or according to the 2018 SDMP.
The construction of two new retention ponds covering an area of 22.98 and 8.53 ha.
Expansion of the existing Kedurus retention pond covering an area of 4.9 and 3.8 ha.
The main result obtained from this research is a spatial modeling of the flood with the existing conditions, resulting in a flood inundation area of 228.88 ha. The model was validated by RMSE with a value of 0.046 and declared excellent. Evaluation of the planned conditions of the 2018 Surabaya City RDTRK and 2018 Surabaya Management Drainage Plan with a model that has been built resulting in a flood area of 226.41 ha. The implementation of RDTRK and SDMP in the City of Surabaya tends not to accommodate the reduction in the area of flood inundation. The stages of the formulation of the spatial planning concept for flood reduction resulted in several proposals, namely, the allocation of green open space for all the land assets of the Surabaya City government and the provision of a maximum requirement of 60% development for space allocation on the existing undeveloped land. In addition, it is proposed to reduce the maximum KDB from 5 to 15% according to land use. It is also proposed to increase the channel capacity by deepening 25% of the existing condition. Then, a flood reduction instrument in the form of a detention pond is involved. The implementation of these recommendations has the potential to reduce the area of flood inundation by 222.62 ha or 97.26%.
This research was funded by Graduate Research Grant, Institut Teknologi Sepuluh Nopember, ref. number 916/PKS/ITS/2020.
Author contributions: Cahyono Susetyo: evaluating land use regulations, building codes, and existing drainage systems to reduce flood in the Kedurus watershed. Lukman Yusuf: building a Spatial Flood Model based on existing hydrological conditions that cause floods in the Kedurus watershed. Rulli Pratiwi S: formulation on the concept of spatial planning to reduce flooding in the Kedurus watershed.
Conflict of interest: Authors state no conflict of interest.
 Machyus M. Evaluasi Strategi Pengembangan Kawasan Perumahan melalui Pendekatan Urban Redevelopment di Kawasan Kemayoran DKI Jakarta. Jakarta, Indonesia: Universitas Diponegoro; 2006.Search in Google Scholar
 Masitoh L, Ma’rif S, Rudiarto I. Pengaruh Keberadaan Perumahan Terhadap Perubahan Harga Lahan Di Kecamatan Ciledug. Semarang, Indonesia: Universitas Diponegoro; 2002.Search in Google Scholar
 Rustiadi E, Saefulhakim S, Panuju DR. Perencanaan Pengembangan Wilayah. Bogor, Indonesia: Crespent Press; 2009.Search in Google Scholar
 Hu S, Fan Y. Assessing the effect of land use change on surface runoff in a rapidly urbanized city: a case study of the central area of Beijing. Land. 2020;9(1):17.10.3390/land9010017Search in Google Scholar
 Wang H, Stephenson SR. Quantifying the relationship between streamflow and climate change in a small basin under future scenarios. Ecol Indic. 2020;113:106251.10.1016/j.ecolind.2020.106251Search in Google Scholar
 Jayadi R. Hidrologi I Pengenalan Hidrologi Teknik Sipil. Yogyakarta, Indonesia: UGM-Press; 2000.Search in Google Scholar
 Aryanto A. Pengaruh Perubahan Penutup Lahan Terhadap Debit Aliran Permukaan di Sub-DAS Keduang Kabupaten Wonogiri. Surakarta, Indonesia: Universitas Sebelas Maret; 2010.Search in Google Scholar
 Yang X, Chen H, Wang Y. Evaluation of the effect of land use/cover change on flood characteristics using an integrated approach coupling land and flood analysis. Hydrol Res. 2016;47(6):1161–71.10.2166/nh.2016.108Search in Google Scholar
 Kingma N. ITC, Enschede. The Netherlands: Flood Hazard Assessment and Zonation; 2002.Search in Google Scholar
 Falter D, Dung N, Vorogushyn S, Schröter K, Hundecha Y, Kreibich H, et al. Continuous, large‐scale simulation model for flood risk assessments: proof‐of‐concept. J Flood Risk Manag. 2016;9(1):3–21.10.1111/jfr3.12105Search in Google Scholar
 David I, Beilicci E, Beilicci R. Basics for hydraulic modelling of flood runoff using advanced hydro informatic tools. Geospatial Research: Concepts, Methodologies, Tools, and Applications. Hershey, Pennsylvania: IGI Global; 2016.10.4018/978-1-4666-9845-1.ch060Search in Google Scholar
 Manfreda S, Nardi F, Samela C, Grimaldi S, Taramasso AC, Roth G, et al. Investigation on the use of geomorphic approaches for the delineation of flood prone areas. J Hydrol. 2014;517:863–76.10.1016/j.jhydrol.2014.06.009Search in Google Scholar
 Purwaningsih S. A combination of green and grey infrastructures approaches in flood reduction: Kedurus Case Study, Indonesia. Paper presented at the International Conference on Disaster Management, Universitas Andalas, Padang, Indonesia; 2018.Search in Google Scholar
 Pamungkas A. Purwitaningsih. Green and grey infrastructures approaches in flood reduction. Int J Disaster Resil Built Environ. 2019;10(5):343–62.10.1108/IJDRBE-03-2019-0010Search in Google Scholar
 Sumiati I. Kajian Strategis Kebijakan Satu Peta (One Map Policy) Bidang Perencanaan Tata Ruang. Paper presented at the Seminar Nasional Administrasi Publik Dinamika Perkembangan Administrasi Publik Di Era Disrupsi dan Tantangan Global; 2019.Search in Google Scholar
 Johnson C, Suri SN, Lipietz B. Words into action guidelines: Implementation guide for land use and urban planning; 2020.Search in Google Scholar
 Purwitaningsih S, Pamungkas A. Analisis Kondisi Hidrologi Daerah Aliran Sungai Kedurus untuk Mengurangi Banjir Menggunakan Model Hidrologi SWAT. J Teknik ITS. 2017;6(2):107–11.10.12962/j23373539.v6i2.24809Search in Google Scholar
 Wizor CH, Wali E. Geo-spatial analysis of urban wetlands loss in Obio/Akpor local government area of rivers state, Nigeria. Asian J Geograph Res. 2020;3(1):35–48.Search in Google Scholar
 Yuliantari E, Dwita HR, Pramono RWD. Pengaruh Kesesuaian Implementasi Ketentuan Intesitas Ruang Pada Peraturan Zonasi Terhadap Suhu Permukaan Di Kota Semarang. Yogyakarta, Indonesia: Universitas Gadjah Mada; 2019.Search in Google Scholar
 Al Amin MB. Analisis Genangan Banjir di Kawasan Sekitar Kolam Retensi dan Rencana Pengendaliannya, Studi Kasus: Kolam Retensi Siti Khadijah Palembang. J Perenc Wil dan Kota. 2016;27(2):69–90.10.5614/jrcp.2016.27.2.1Search in Google Scholar
 Chalid A, Prasetya B. Utilization of a pond in East Jakarta for a sustainable urban drainage system model. Paper presented at the IOP Conference Series: Earth and Environmental Science; 2020.10.1088/1755-1315/437/1/012018Search in Google Scholar
 Kallioras A. Urban flood hazard management-Case study: Shanghai. Delft, The Netherlands: Delft University of Technology; 2020.Search in Google Scholar
 Ghifari RA. Zonasi Ruang Berbasis Pengurangan Risiko Bencana Pada Kawasan Bahaya Bencana Banjir Di DAS Wae Apu, Pulau Buru. (Magister). Yogyakarta, Indonesia: Universtas Gajah Mada; 2018.Search in Google Scholar
 Rahman R. Model Sistem Informasi Geografis untuk estimasi koefisien aliran dan hubungannya dengan tutupan lahan di DAS Riam Kanan Provinsi Kalimantan Selatan. Bumi Lestari J Environ. 2013;13(1):1–8.Search in Google Scholar
 Utomo TC. Kusumawardani. Pemilihan distribusi probabilitas pada analisa hujan dengan metode goodness of fit test. J Teknik Sipil dan Perenc. 2016;18(2):139–48.10.15294/jtsp.v18i2.7480Search in Google Scholar
 Guo H, Han Y, Bai X. Hydrological effects of litter on different forest stands and study about surface roughness coefficient. J Nanjing Forestry Univ. 2010;24(2):179–83.Search in Google Scholar
 USACE. HEC-RAS River Analysis System Hydraulic Reference Manual. Version 5.0. Hydrological Engineering Center Davis: Institute of Water Resources; 2016.Search in Google Scholar
 USACE. HEC-RAS River Analysis System: User’s Manual version 3.0. Hydrologic Engineering Center. USAGE (US Army of Engineers); 2001.Search in Google Scholar
 McCuen RH. Hydrologic analysis and design. Englewood Cliffs, NJ: Prentice-Hall; 1989.Search in Google Scholar
 Willmott CJ, Matsuura K. On the use of dimensioned measures of error to evaluate the performance of spatial interpolators. Int J Geographical Sci. 2006;20(1):89–102.10.1080/13658810500286976Search in Google Scholar
 Sharif AA. Chapter 7 – Numerical modeling and simulation . In: Ahmadian S, editor. Numerical Models for Submerged Breakwaters. Boston: Butterworth-Heinemann; 2016. p. 109–26.10.1016/B978-0-12-802413-3.00007-9Search in Google Scholar
 Badan Informasi Geografis. Peraturan Kepala Badan Informasi Geospasial Nomor 15 Tahun 2015 Tentang Pedoman Teknis Ketelitian Peta Dasar. Bogor; 2014.Search in Google Scholar
© 2022 Cahyono Susetyo et al., published by De Gruyter
This work is licensed under the Creative Commons Attribution 4.0 International License.