Bendungan direncanakan dibangun untuk dimanfaatkan dalam memenuhi kebutuhan di bidang sumber daya air. Disamping manfaat yang terkandung di dalamnya, akan terdapat bahaya besar bila ada ketidakmampuan struktur bendungan dalam menahan banjir yang masuk ke dalam waduk. Pemilihan metode yang tepat untuk memperkirakan besaran banjir rencana merupakan bagian dari keamanan bendungan. Permasalahan yang terjadi di Indonesia adalah pencatatan data pada pos duga air tidak tersedia. Salah satu metode perhitungan kehilangan air (losses) pada pemodelan banjir adalah NRCS-CN. Kelebihan metode ini dapat digunakan untuk wilayah yang tidak memiliki data hidrograf banjir maupun tinggi muka air waduk, tetapi tersedia data pencatatan hujan. Dalam penentuan nilai CN, Indonesia belum memiliki peta HSG (Hydrologic Soil Group) sehingga perlu dibuat peta tanah seperti HWSD. Penelitian dilakukan dengan penentuan CN menggunakan peta tanah (HWSD), tataguna lahan (BAPPEDA). Kehilangan air dilakukan dengan model HEC-HMS. Penelitian  dilakukan di DAS Brantas Hulu dengan titik outlet Bendungan Sutami. Simulasi dilakukan dengan kalibrasi tinggi muka air. Kelompok HSG yang didapat dari peta HWSD pada DAS Brantas Hulu adalah D (lempung), B (tanah liat berlanau), dan A (pasir bertanah liat). Penentuan HSG dari peta tanah HWSD dengan metode kehilangan air NRCS-CN dan hidrograf satuan NRCS menghasilkan kalibrasi terbaik didapatkan dari RMSE dan beda tinggi pada AMC II dan λ=0,2 untuk bulan Maret 2007 (RMSE=0.55) serta AMC II dan λ=0,05 bulan Desember 2007 (RMSE=0.65).

No abstract

Keterbatasan sebaran dan jumlah pos penakar hujan dapat diatasi pengukuran hujan berbasis satelit. Seiring perkembangan teknologi, pengukuran hujan berbasis satelit, seperti GPM menunjukkan akurasi dan cakupan yang semakin membaik. Tentunya penggunaan hujan satelit ini juga perlu disertai dengan proses validasi berupa koreksi yang semakin mampu meningkatkan performanya. Banyak studi evaluasi dan koreksi data satelit telah dilakukan, hanya ada studi terbatas yang telah dilakukan di Indonesia. Oleh karena itu, studi ini bermaksud untuk mengevaluasi performa data hujan berbasis satelit (GPM IMERG) dan melakukan koreksi dengan metode validasi silang Monte-Carlo di Bandung Raya. Secara spesifik, studi ini menitikberatkan pada perbandingan antara data GPM dan pos hujan melalui analisis statistik untuk hujan bulanan. Hasil menunjukkan bahwa, data GPM mampu mendeteksi pola hujan bulanan dengan baik. Data bulanan tersebut dikelompokkan berdasarkan musimnya dan menghasilkan korelasi hujan musim kering yang lebih baik pada musim basah. Koreksi dengan MCCV dengan simulasi 1.000 kali berdasarkan musim tersebut menunjukkan peningkatan performa rata-rata sebesar 70% untuk bias relatif, dan 30% untuk RMSE, di kawasan Bandung Raya.

Rainfall is a major water resource with a significant role in terms of growth, environment concerns, and sustainability. Several human activities demand adequate water supply for drinking, agriculture, domestic, and commercial consumption. The accuracy of any hydrologic study depends heavily on the availability of good-quality precipitation estimates. Most countries are unable to provide sufficient climatic data, including rainfall and observed discharge statistics. This scarcity is a huge obstacle in conducting thorough hydrologic studies over a certain period. For instance, Indonesia, as an archipelagic country, has long been faced with data availability problems. For this reason, Tropical Rainfall Measuring Mission (TRMM), which was developed by NASA, became an alternative solution to rainfall data limitations. However, to be applied in hydrologic investigations, TRMM data require proper estimation and adjustment. The aim of this study was to evaluate the quality of TRMM rainfall data and its application in determining design flood and water availability. Dividing the data into several groups based on its magnitude and multiplying each unit with a correction coefficient are parts of the modification process. Subsequently, objective functions, including false alarm ratio (FAR), probability of detection (POD), and root mean square error (RMSE) were also applied. Rainfall-runoff modeling and design storm analysis at Delingan dam were used to study the TRMM correction performance. Based on the analysis, corrected TRMM showed considerable findings compared to ground station data.  Model calibration and verification using corrected TRMM data provide satisfactory model parameters compared to ground station derivatives. The results also disclosed a closer fit of the corrected TRMM to catchment response translated from derived rainfall-runoff model parameters to ground station compared to control.  Furthermore, design storm calculated from corrected TRMM reflects an improvement compared to uncorrected TRMM data.

Batam City is the economic center of Riau Province with a predicted population of 1.8 million people in 2025. To support economic development, Batam City needs a reliable supply of raw water. Mukakuning and Duriangkang reservoirs, which are cascade reservoirs, are the largest contributors to raw water supply in Batam City. This study aims to determine the maximum capacity of the two reservoirs to meet current and future raw water demand. Discharge in the watershed is calculated using daily HEC-HMS model calibrated using Duriangkang Reservoir water level data. The storage of Mukakuning and Duriangkang Reservoir are 6.3 and 106.1 million m3 respectively, equivalent to 39% and 77% of the runoff volume of each watershed, classifying the two reservoirs in the multi-year category. Using current operation, the two reservoirs can supply up to 3.24 m3/s at 100% reliability, compared to existing capacity of 3.1 m3/s. The water loss is dominated by evaporation which reaches 32.6 million m3/year while spilled water is only 8.3 million m3/year. At 95% reliability, the reservoirs are almost at maximum capacity and able to supply 4.03 m3/s of raw water with the spilled water is only 0.4 million m3/year. Efforts to increase capacity by increasing normal water levels are not effective and lead to dam overtopping in PMF condition. More effective way to increase water supply can be obtained by changing operating patterns. If the reservoir is in dry condition, determined by predicted SPI, the water supply is limited so that the discharge can be utilized for a longer period.