Donny Harisuseno

This research aims to develop Horton infiltration for tropical peatland using an injection-well approach that relates soil moisture to the infiltration rate. The research was conducted in the peatland of Palangka Raya City – Sebangau District, Indonesia. Soil sampling was carried out to determine the depth of shallow peatland (50–100 cm) and medium peatland (100–200 cm) using an auger and ring samples. The methodology consisted of investigating a simple laboratory-scale injection-simulator model covering dimension, depth, number, and flow velocity, and then developing a Horton infiltration model for tropical peatland using an injection-well approach that relates soil moisture to the infiltration rate. The results show that the modified Horton infiltration analysis, with the addition of moisture in the simple injection-simulator tool, produces a very strong relationship between discharge and modified Horton infiltration, a very strong relationship between discharge and groundwater level, and a very strong relationship between modified Horton infiltration and groundwater level in medium-depth peatland deeper than one metre (>1 m). The modified Horton infiltration development model for tropical peatland is better than the original Horton infiltration model because peatland is porous and infiltration increases with increasing water volume and soil moisture. In addition, the injection well increases the infiltration-capacity system, whereas the original Horton model analyses only natural infiltration.

This study evaluates the performance of Global Precipitation Measurement (GPM) satellite-based rainfall data in comparison to Automatic Rainfall Recorder (ARR) data in forming rainfall distribution patterns and assessing its impact on flood discharge simulation using the HEC-HMS model. Statistical validation was conducted using the Pearson Correlation Coefficient, the ratio of standard deviation of observations to RMSE (RSR), Percent Bias (PBIAS), and Mean Absolute Percentage Error (MAPE). The results show that GPM has a strong correlation with ARR (r = 0.875) and a low RSR value (RSR= 0.256), yet it exhibits a notable negative bias (PBIAS = –24.41%), indicating an underestimation of rainfall values. In contrast, simulations using ARR rainfall patterns produce peak discharges that closely match actual discharge records at the Jatigede Dam outlet, with an average deviation of less than 3% and a MAPE of 1.17%, categorized as very good. The GPM simulation produces peak discharges 13–16% higher than actual observations, with a MAPE of 14.53%, which still falls into the good category. These results suggest that while ARR provides higher accuracy, GPM remains a viable alternative source, especially in data-scarce areas, provided that appropriate calibration methods such as bias correction are applied. This study supports future research in satellite data calibration using machine learning and multivariate statistical approaches.

The drainage system in Malang City currently relies on the Sengkaling Kiri irrigation network to discharge urban drainage water. However, the existing channel capacity is insufficient to accommodate the increasing water flow during rainfall events due to channel narrowing and sedimentation. This limitation has resulted in frequent waterlogging and localized flooding, particularly around Jl. Soekarno Hatta, Jl. Ahmad Yani, and Jl. Lt. Gen. Sutoyo. This research aims to evaluate the performance of the current drainage system, identify the primary causes of flooding, and propose effective solutions to reduce inundation in these critical areas. The study employs a descriptive and analytical approach, combining field surveys, hydrological data collection, and hydraulic modeling to assess the channel’s capacity and identify critical points of overflow. The findings reveal that the current Sengkaling Kiri irrigation network has experienced significant sedimentation and reduced cross-sectional area, leading to a capacity deficit during peak discharge events. Proposed solutions include channel widening, sediment removal, and the construction of alternative drainage routes, such as diverting part of the flow directly from the Sengkaling Kiri network to the nearest Sungai Brantas. These interventions are expected to significantly reduce waterlogging and improve flood management in the affected areas. The implications of this study highlight the importance of regular maintenance, capacity upgrades, and the integration of urban drainage systems with natural waterways to ensure long-term flood resilience in rapidly developing urban areas.

Bencana kekeringan menjadi perhatian bagi Badan Penanggulangan Bencana Daerah (BPBD) Kabupaten Bangkalan beberapa tahun terakhir. Studi ini bertujuan untuk menganalisis indeks kekeringan dan mengembangkan peta spasial kekeringan di Kabupaten Bangkalan khususnya di DAS Blega. Penelitian ini menggunakan konsep kekeringan meteorologis untuk menganalisa karakteristik kekeringan di lokasi penelitian. Data yang digunakan adalah data curah hujan bulanan, data curah hujan satelit, dan peta DAS Blega. Indeks kekeringan dianalisis menggunakan metode Standardised Precipitation Index (SPI). Peta spasial kekeringan diperoleh menggunakan metode Inverse Distance Weight (IDW) pada aplikasi ArcGIS 10.8. Hasil studi menunjukkan intensitas kekeringan terparah terjadi selama tujuh bulan (bulan Mei hingga November). Pola hubungan antara indeks kekeringan bulanan dengan tingkat kekeringan rentang 1992 - 2021 menunjukkan tingkat kekeringan "Amat Sangat Kering" terjadi secara berkala setiap empat tahun. Hasil perbandingan antara kejadian tahun kering dari hasil analisis metode SPI dan kejadian tahun EL Nino yang dikeluarkan BMKG menunjukkan terdapat kesesuaian antara kejadian tahun kering yang terjadi. Analisis kesesuaian menunjukkan persentase sebesar 75,97%, menunjukkan adanya kesamaan yang relatif baik antara kejadian kekeringan historis di daerah penelitian dengan kekeringan yang berasal dari metode SPI. Hasil studi memverifikasi bahwa metode SPI layak digunakan untuk menggambarkan karakteristik kekeringan di lokasi studi.

The overflow of the Sadar River often causes flooding, which is detrimental to the community. Effective measures to address the flood problem require a good quality and quantity of rainfall data. This study aims to develop an isohyetal map of design rainfall for various return periods using the interpolation linear method. The design rainfall is computed using frequency analysis of Log Normal, Gumbel, and Log Person III distributions with return periods of 2, 5, 10, 25, 50, and 100 years. The isohyet map was produced using the Inverse Distance Weight (IDW) and spline interpolation methods. The map results are then evaluated against the design rainfall values obtained from the frequency analysis using the NSE and RSR parameters. The IDW and spline interpolation maps show an excellent level of fit. Furthermore, the isohyet map was compared with the design rainfall map issued by the Ministry of Public Works and Public Housing, which shows a level of fit of 49.693% for the IDW method and 33.194% for the spline method. The results confirmed that the IDW method is the most accurate to estimate isohyet map of design rainfall in the study area.

Purpose: This research intends to compare two numerical method models, which are Runge-Kutta and by using HYDRUS software.   Theoretical reference: One of the consequences of human population that grows rapidly is the increase of human activity, along with the increase of pollutant that flows into water bodies. Water pollution is a significant environmental issue that threatens the health of ecosystems and human populations worldwide.   Method: To determine a set of parameters of the mechanism in a constructed wetland, a numerical model may be of aid to acquire parameters which represent the mechanism of pollutant removal in it.   Result and Conclusion: This study yields different efficiency of pollutant removal when simulated with HYDRUS and with Runge-Kutta. The differences in the effectivity results in HYDRUS and Runge-Kutta might be caused by the detail of simulated mechanism, where HYDRUS considers the mechanism happened in soil column, while Runge-Kutta only focuses on the water column.   Implication of research: In order to observe the effectivity of a constructed wetland, a numerical model may be used. The parameters needed to represent the environment and properties of both the plants and soil can be obtained by building a demonstration plot.   Originality/ value: to compare two numerical method models, which are Runge-Kutta and by using HYDRUS software.

Rainfall is one of the main components of the hydrologic cycle; thus, the availability of accurate rainfall data is fundamental for designing and operating water resources systems and infrastructure. This study aims to develop an empirical model of rainfall intensity ( It,p) as a function of its probability ( p) and duration ( t). In 1999–2020, data on the hourly duration of rainfall were collected from automatic rainfall recorder (ARR) gauges. The empirical model has been developed using a statistical approach based on duration ( t) and probability ( p), and subsequently they have been validated with those obtained from ARR data. The resulting model demonstrates good performance compared with other empirical formulas (Sherman and Ishiguro) as indicated by the percent bias ( PBIAS) values (2.35–3.17), ratio of the RMSE (root mean square error) between simulated and observed values to the standard deviation of the observations ( RSR, 0.028–0.031), Nash–Sutcliffe efficiency ( NSE, 0.905–0.996), and index of agreement (d, 0.96–0.98) which classified in the rating of “very good” in model performance. The reliability of the estimated intensity based on the empirical model shows a tendency to decrease as duration ( t) increases, and a good accuracy mainly for the rainfall intensity for shorter periods (1-, 2-, and 3-hours), whereas low accuracy for long rainfall periods. The study found that the empirical model exhibits a reliable estimate for rainfall intensity with small recurrence intervals ( Tr) 2-, 5-, 10-, and a 20-year interval and for a shorter duration ( t). Validation results confirm that the rainfall intensity model shows good performance; thus, it could be used as a reliable instrument to estimate rainfall intensity in the study area.

Land-use changes that occur in the Lesti watershed will indirectly affect the infiltration rate. Reduced land cover vegetation and the existence of soil processing processes such as compaction will change the characteristics of the infiltration rate. This study aims to determine the effect of soil physical properties on the infiltration rate using multiple linear regression models. This study was conducted on agricultural land in the Lesti watershed. At each point infiltration data was collected using a Double Ring Infiltrometer and soil samples were taken. From the results of correlation and determination analysis, it was found that the variables ln sand, ln clay, and ln water content have good correlation and determination coefficient values. After that, several multiple linear regression models were made. From the results of the analysis, the regression model using the variables was ln clay and ln moisture contentable to fulfill the classical assumption test and hypothesis testing with the strength of the ln clay and ln water content variables together being able to explain the initial infiltration rate ln variable of 88.4%. The results of the model validation test, it shows that the regression modeling value is close to the measurement results in the field.  Perubahan tata guna lahan yang terjadi pada DAS Lesti secara tidak langsung akan mempengaruhi laju infiltrasi. Berkurangnya vegetasi penutup lahan dan adanya proses pengolahan tanah seperti pemadatan akan mengubah karakteristik laju infiltrasi pada suatu lahan. Studi ini ditujukan untuk mengetahui pengaruh sifat fisik tanah terhadap laju infiltrasi dengan menggunakan model regresi linear berganda. Kajian ini dilakukan pada lahan pertanian yang berada di DAS Lesti. Pada setiap titik dilakukan pengambilan data infiltrasi menggunakan alat Double Ring Infiltrometer dan pengambilan sampel tanah. Dari hasil analisis korelasi dan determinasi didapatkan bahwa variabel ln sand, ln clay dan ln kadar air memiliki nilai koefisien korelasi dan determinasi yang baik. Setelah itu kemudian dilakukan pembuatan beberapa model regresi linear berganda. Dari hasil analisis tersebut, model regresi yang menggunakan variabel ln clay dan ln kadar air mampu memenuhi uji asumsi klasik dan uji hipotesis dengan kekuatan variabel ln clay dan ln kadar air secara bersama-sama mampu menjelaskan variabel ln laju infiltrasi awal sebesar 88,4%. Dari hasil uji validasi model menunjukkan bahwa nilai pemodelan regresi mendekati dengan hasil pengukuran di lapangan.

The Lesti watershed area has land use problems that cause changes in infiltration in various land uses. This change can cause new problems. In this case, research is carried out on each land use including vegetation land, agricultural land, residential land and open land using a Double Ring Infilrometer with each point being measured twice. The results of the infiltration rate measurement show that residential land has a very fast infiltration rate, while open land has a slow infiltration rate. The models used in the infiltration analysis are the Horton Model and the Kostiakov Model. After analyzing using this model, the highest infiltration rate was found in the Horton model of 10.954 mm/minute on residential land and the lowest infiltration rate of 0.518 mm/minute on open land, while the Kostiakov model obtained the highest infiltration rate of 9.767 mm/minute on land. settlements and the lowest infiltration rate is 0.563 mm/minute on open land. Based on the results of the validation test using the relative error test, correlation and determination, RMSE, MAE, NSE, the result of the selected model is the Horton Model. Wilayah DAS lesti memiliki permasalahan tata guna lahan yang menyebakan terjadinya perubahan infiltrasi pada berbagai tata guna lahan. Dengan adanya perubahan tersebut maka dapat menyebabkan permasalahan baru. Dalam hal ini maka dilakukan penelitian pada setiap tata guna lahan meliputi lahan vegetasi, lahan pertanian, lahan pemukiman dan lahan terbuka dengan menggunakan alat Double Ring Infilrometer dengan masing-masing titik dilakukan dua kali pengukuran. Hasil pengukuran laju infiltrasi menunjukkan bahwa lahan pemukiman memiliki laju infiltrasi sangat cepat, sedangkan lahan terbuka memiliki laju infiltrasi lambat. Model yang digunakan dalam analisa infiltrasi yaitu Model Horton dan Model Kostiakov. Setelah dilakukan analisis menggunakan model tersebut didapatkan hasil laju infiltrasi tertinggi pada Model Horton sebesar 10,954 mm/menit pada lahan pemukiman dan laju infiltrasi terendah sebesar 0,518 mm/menit pada lahan terbuka, sedangkan pada Model Kostiakov didapatkan laju infiltrasi tertinggi sebesar 9,767 mm/menit pada lahan pemukiman dan laju infiltrasi terendah sebesar 0,563 mm/menit pada lahan terbuka. Berdasarkan hasil uji validasi menggunakan uji kesalahan relatif, korelasi dan determinasi, RMSE, MAE,NSE didapatkan hasil model terpilih yaitu Model Horton.

Rainfall intensity known as an essential variable in rainfall-runoff transformation. Flood events occurred in 2017 at Brawijaya University campus caused by high intensity and landuse change in campus's internal and external environment. The study aims to examine performance of several empirical formulas in estimating rainfall intensity, investigating characteristic of each empirical formula’s contant due to varying return period (Tr), and determining appropriate Intensity Duration Frequency (IDF) curve. The formula of Sherman, Talbot, and Ishiguro was employed to obtain empirical intensity, while intensity on varying return period was calculated using Log Pearson Type III. The proposed rainfall intensity formula was selected through comparison between empirical intensity with those from observation according to criteria of relative error (KR), Nash Sutcliffe Efficiency (NSE), and Peak Weight Root Mean Square Error (PWRMSE). The Sherman formula showed best performance in estimating rainfall intensity as indicated by low value of KR and PWRMSE, followed by NSE close to one. The constant of empirical formula “a” was directly proportional with increasing of Tr; conversely, constant “b” and “n” were inverse with Tr. The validation result of Sherman formula demonstrated that the formula showed good reliability, thus recommended to estimate intensity and IDF curve in the study area.