Runoff estimation is a key component in various hydrological considerations. Estimation of storm runoff is especially important for the effective design of hydraulic and road structures, for the flood flow management, as well as for the analysis of land use changes, i.e. urbanization or low impact development of urban areas. The curve number (CN) method, developed by Soil Conservation Service (SCS) of the U.S. Department of Agriculture for predicting the flood runoff depth from ungauged catchments, has been in continuous use for ca. 60 years. This method has not been extensively tested in Poland, especially in small urban catchments, because of lack of data. In this study, 39 rainfall-runoff events, collected during four years (2009–2012) in a small (A=28.7 km²), urban catchment of Służew Creek in southwest part of Warsaw were used, with the aim of determining the CNs and to check its applicability to ungauged urban areas. The parameters CN, estimated empirically, vary from 65.1 to 95.0, decreasing with rainfall size and, when sorted rainfall and runoff separately, reaching the value from 67 to 74 for large rainfall events.

The Curve Number method is one of the most commonly applied methods to describe the relationship between the direct runoff and storm rainfall depth. Due to its popularity and simplicity, it has been studied extensively. Less attention has been given to the dimensionless initial abstraction ratio, which is crucial for an accurate direct runoff estimation with the Curve Number. This ratio is most often assumed to be equal to 0.20, which was originally proposed by the method’s developers. In this work, storm events recorded in the years 2009–2017 in two small Polish catchments of different land use types (urban and agroforested) were analyzed for variability in the initial abstraction ratio across events, seasons, and land use type. Our results showed that: (i) estimated initial abstraction ratios varied between storm events and seasons, and were most often lower than the original value of 0.20; (ii) for large events, the initial abstraction ratio in the catchment approaches a constant value after the rainfall depth exceeds a certain threshold value. Thus, when using the Soil Conservation Service-Curve Number (SCS-CN) method, the initial abstraction ratio should be locally verified, and the conditions for the application of the suggested value of 0.20 should be established.

The aims of this study are: i) to better understand the coupled interactions between land use changes, climate change and the aquatic ecosystem in a small agricultural catchment (<100 km²) with a long observation history (1963–2018) and a known land use history, and ii) to test available approaches to separate land use and climate change impacts on water resources in such a small catchment. The pre- and post-change periods have been separated based on change points and the known land use history. Next, conceptual and analytical approaches were applied to quantify and to distinguish between the impacts of climate and land use changes on annual runoff for these two periods. Over the observation period, both land use changes (increase in forest areas) as well as climate change (a temperature rise and a decrease in annual precipitation) occurred. These changes contributed to a decrease in the average annual runoff by 51.9 mm (49% of the long-term average) during the observation period. The quantified contributions of climate and land use changes to the decrease in the mean annual runoff amount to between 60% and 80% and between 40% and 20%, respectively. (i) The results obtained from different methods were consistent - a change in runoff was primarily caused by shifts in climatic variables. (ii) However, the quantified contributions varied depending on the method applied and the form of the Budyko curve. (iii) Thus, special care should be taken in relation to the selection of the Budyko curve for quantifying these changes. (iv) Knowledge of the water deficit sources can result in better planning of water resources management in such small catchments.

The paper presents an application of signal processing and computational intelligence methods to detect presence of the wood boring insects larvae in the wooden constructions (such as the furniture of buildings). Such insects are one of the main sources of the degradation in such objects, therefore they should be detected as quickly as possible, before inflicting serious damage. The presented work involved the acoustic monitoring for detecting the presence of the larvae inside pieces of wood. An accelerometer was used to record the sound, further analyzed by a computer algorithm extracting features important for artificial-intelligence (AI) based classification employed to detect the old house borer’s (Hylotrupes bajulus L.) activity. The presented task is difficult, as the sounds made by the larvae are of relatively low amplitude and the background noise caused by people, electrical appliances or other sources may significantly degrade the accuracy of detection. The classification of sounds is needed to separate sources of noise which deteriorate the proper larva detection and should be suppressed if possible. The employed classification was based on features defined in the time domain followed by the support vector machine used as the binary classifier. The results allowed us to assess the effectiveness of the old house borer’s detection by the acoustic analysis enhanced with the AI algorithm.

Detention ponds constructed in urban areas should perform two major functions: reduce flood flows and improve quality of runoff by trapping sediments and related pollutants. Providing tools for an efficient and low data–demanding assessment of pond performance can greatly support sediment management at the small catchment scale. This paper adopts the approach of a continuously stirred tank reactor (CSTR) to model the sediment concentration in the stormwater outflow from a small detention pond located in an urbanized catchment. The model is developed and tested using data sets of seven rainfall–runoff–suspended sediment events. Good agreement between observed and estimated outflow from the pond is achieved for both hydrographs and sediment graphs in calibration and validation. Thus results indicate that the present model due to its low data demand can predict sediment graphs at the outlet from such low-volume reservoirs.

Climate-induced changes in small watersheds are still not well researched because long-term datasets are usually missing for these watersheds. Such studies can, however, improve our understanding of the watershed response to climatic changes at such a small scale being transparent. In this study, we investigate trends in temperature, precipitation and river-flow characteristics in a small watershed, typical for Central Poland, with 53 years of observations (1963–2015) using the Mann-Kendall test. Particularly, we examine whether any trends in hydro-meteorological variables can be identified, and if any associated changes in water resources in this region can already be observed. We found that this short period already allows for detecting some changes in hydro-meteorological variables. These changes could be characterized by a significant increase in the mean annual air temperature on a daily basis, and a significant decrease in the mean annual discharge on a daily basis and in the minimum annual discharge on a daily basis. Yet, no significant trend could be detected for the total annual precipitation, the maximum summer rainfall, and the maximum annual discharge on a daily basis. These findings indicate that water resources are decreasing in this region, which affects natural habitats, agriculture and local communities.