Time of concentration, Tc, is defined as time elapsed from the beginning of rainfall infiltrated into soil layer until it reaches a constant infiltration rate (fc) which is indicated an equilibrium subsurface flow rate. In hydrological view, time of concentration plays a significant role in elaboration of transformation of rainfall into runoff in a watershed. The aims of this research are to define influence of soil density and soil water content in determining time of concentration using infiltration concept based on water balance theory, and to find out the effect of land slope this time. Watershed laboratory experiment using rainfall simulator was employed to examine time of concentration associated with infiltration process under different slope, soil density and soil water content based on water balance concept. The steady rainfall intensity was simulated using sprinklers which produced 2 dm3∙min–1. Rainfall, runoff and infiltration analysis were carried out at laboratory experiment on soil media with varied of soil density (d) and soil water content (w), where variation of land slopes (s) were designed in three land slopes 2, 3 and 4%. The results show that relationship between soil density and land slope to time of concentra-tion showed a quadratic positive relationship where the higher the soil density address to the longer time of concentration. Moreover, time of concentration had an inverse relationship with soil water content and land slope that means time of con-centration decreased when the soil water content increased.

Drought is known as a normal part of climate and including in a slow-onset natural hazard which may have several im-pacts on hydrology, agriculture, and socioeconomic. Drought monitoring, including its severity, spatial and duration is re-quired and becomes an essential input for establishing drought risk management and mitigation plan. Many drought indices have been introduced and applied in regions with different climate characteristics in the last decades. This paper aims to compare standardized precipitation index (SPI) and rainfall anomaly index (RAI) along with standardized streamflow index (SSI) in Pekalen River Basin, East Java, Indonesia. The statistical association analyses, included the Pearson correlation (r), Kendal tau (τ), and Spearman rho (rs) were performed to examine the degree of consistency between monthly and annual drought index of SPI and RAI. Additionally, the comparative analysis was performed by overlapping both monthly and an-nual drought index from the SPI and RAI with the SSI at hydrological years. The study revealed that the characteristic of the annual drought index between the SPI and RAI exhibits pattern similarity which indicated by the high correlation coeffi-cient between them. Further, the comparative analysis on each hydrological year showed that the SPI and RAI were very well correlated and exhibited a similar pattern with the SSI. Overall, the SPI shows better performance than the RAI for es-timating drought characteristic either monthly or annual basis. Hence, the SPI is considered as a reliable and effective tool for analyzing drought characteristic in the study area.

Infiltration process plays important role in water balance concept particularly in runoff analysis, groundwater re-charged, and water conservation. Hence, increasing knowledge concerning infiltration process becomes essential for water manager to gain an effective solution to water resources problems. This study employed multiple linear regression for esti-mating infiltration rate where the soil properties used as the predictor variable and measured infiltration rate as the response variable. Field measurement was conducted at sixteen points to obtain infiltration rate using double ring infiltrometer and soil properties namely soil porosity, silt, clay, sand content, degree of saturation, and water content. The result showed that measured infiltration rate had an average initial infiltration rate (f0) of 6.92 mm∙min–1 and final infiltration rate (fc) of 1.49 mm∙min–1. Soil porosity and sand content showed a positive correlation with infiltration rate by 0.842, 0.639, respectively, while silt, clay, water content, and degree of saturation exhibited a negative correlation by –0.631, –0.743, –0.66 and –0.49, respectively. Three types of regression equations were established based on type of soil properties used as predictor varia-bles. The model performance analysis was conducted for each equation and the result shows that the equation with five predictor variables fMLR_3 = – 62.014 + 1.142 soil porosity – 0.205 clay, – 0.063 sand – 0.301, silt + 0.07 soil water content with R2 (0.87) and Nash–Sutcliffe (0.998) gave the best result for estimating infiltration rate. The study found that soil po-rosity contributes mostly to the regression equation that indicates great influence in controlling soil infiltration behavior.

Flood inundation processes in urban areas are primarily affected by artificial factors such as drainage facilities, local al-terations of topography and land uses. The objective of this study is to examine the capability of hydrological model SI-MODAS to estimate runoff and investigating the utilization of storage well in controlling runoff in a residential area. The result of the estimated runoff from the hydrological model was compared with the existing capacity of the drainage channel to identify which channel experienced the problem of inundation. The location of inundation was used to determine the location and number of storage well. The results showed that SIMODAS model could be applied in runoff analyses with 8.09% of relative error compared with runoff depth from field measurement. The existing capacity of the channel could not accommodate runoff Q10yr where the inundation discharge was approximately 0.24 m3·s–1 (at outlet point 1) and 0.12 m3·s–1 (at outlet point 2). The inundation problem was overcome by using a combination system between channel normalization (reduce 35% of total inundation discharge) and storage well system (reduce 65% of total inundation discharge). The storage well was designed at 20 locations (at outlet point 1) and 16 locations (at outlet point 2) which each well had a discharge of 0.0058 m3·s–1. The storage well combined with channel normalization could be used as an alternative way to solve inunda-tion problems in a residential area considering the constraint of land space limitation in the urban area.

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 ( I_t,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.