Rainfall-Runoff Modeling and Hydrological Responses to the Projected Climate Change for Upper Baro Basin, Ethiopia

This paper presents the results of Rainfall-Runoff modeling and simulation of hydrological responses under changing climate using HEC-HMS model. The basin spatial data was processed by HEC-GeoHMS and imported to HEC-HMS. The calibration and validation of the HEC-HMS model was done using the observed hydrometeorological data (1989-2018) and HEC-GeoHMS output data. The goodness-of-fit of the model was measured using three performance indices: Nash and Sutcliffe coefficient (NSE) = 0.8, Coefficient of Determination (R2) = 0.8, and Percent Difference (D) = 0.03, with values showing very good performance of the model. Finally, the optimized HEC-HMS model has been applied to simulate the hydrological responses of Upper Baro Basin to the projected climate change for mid-term (2040s) and long-term (2090s) A1B emission scenarios. The simulation results have shown a mean annual percent decrease of 3.6 and an increase of 8.1 for Baro River flow in the 2040s and 2090s scenarios, respectively, compared to the baseline period (2000s). A pronounced flow variation is rather observed on a seasonal basis, reaching a reduction of 50% in spring and an increase of 50% in autumn for both mid-term and long-term scenarios with respect to the base period. Generally, the rainfall-runoff model is developed to solve, in a complementary way, the two main problems in water resources management: the lack of gauged sites and future hydrological response to climate change data of the basin and the region in general. The study results imply that seasonal and time variation in the hydrologic cycle would most likely cause hydrologic extremes. And hence, the developed model and output data are of paramount importance for adaptive strategies and sustainable water resources development in the basin.

Hydrological daily rainfall-runoff simulation with BTOPMC model and comparison with Xin'anjiang model

A grid-based distributed hydrological model, the Block-wise use of TOPMODEL （BTOPMC）, which was developed from the original TOPMODEL, was used for hydrological daily rainfall-runoff simulation. In the BTOPMC model, the runoff is explicitly calculated on a cell-by-cell basis, and the Muskingum-Cunge flow concentration method is used. In order to test the model＇s applicability, the BTOPMC model and the Xin＇anjiang model were applied to the simulation of a humid watershed and a semi-humid to semi-arid watershed in China. The model parameters were optimized with the Shuffle Complex Evolution （SCE-UA） method. Results show that both models can effectively simulate the daily hydrograph in humid watersheds, but that the BTOPMC model performs poorly in semi-humid to semi-arid watersheds. The excess-infiltration mechanism should be incorporated into the BTOPMC model to broaden the model＇s applicability.

Rainfall-runoff simulation and flood forecasting for Huaihe Basin

The main purpose of this study was to forecast the inflow to Hongze Lake using the Xin＇anjiang rainfall-runoff model. The upper area of Hongze Lake in the Huaihe Basin was divided into 23 sub-basins, including the surface of Hongze Lake. The influence of reservoirs and gates on flood forecasting was considered in a practical and simple way. With a one-day time step, the linear and non-linear Muskingum method was used for channel flood routing, and the least-square regression model was used for real-time correction in flood forecasting. Representative historical data were collected for the model calibration. The hydrological model parameters for each sub-basin were calibrated individually, so the parameters of the Xin＇anjiang model were different for different sub-basins. This flood forecasting system was used in the real-time simulation of the large flood in 2005 and the results are satisfactory when compared with measured data from the flood.

Particle Swarm Optimization for Identifying Rainfall-Runoff Relationships

Rainfall-runoff processes can be considered a single input-output system where the observed rainfall and runoff are inputs and outputs, respectively. Conventional models of these processes cannot simultaneously identify unknown structures of the system and estimate unknown parameters. This study applied a combinational optimization and Particle Swarm Optimization (PSO) for simultaneous identification of system structure and parameters of the rainfall-runoff relationship. Subsystems in proposed model are modeled using combinations of classic models. Classic models are used to transform the system structure identification problem into a combinational optimization and can be selected from those typically used in the hydrological field. A PSO is then applied to select the optimized subsystem model with the best data fit. The parameters are estimated simultaneously. The proposed model is tested in a case study of daily rainfall-runoff for the upstream Kee-Lung River. Comparison of the proposed method with simple linear model (SLM) shows that, in both calibration and validation, the PSO simulates the time of peak arrival more accurately compared to the SLM. Analytical results also confirm that the PSO accurately identifies the system structure and parameters of the rainfall-runoff relationship, which are a useful reference for water resource planning and application.

The hydrothermal changes of permafrost active layer and their impact on summer rainfall-runoff processes in an alpine meadow watershed,northwest China

The freezing-thawing variation of permafrost active layer increases the complexity of rainfall-runoff processes in alpine river basins,Northwest China.And alpine meadow is the prominent ecosystem in these basins.This study selected a small alpine meadow watershed in the upper reaches of the Shule River Basin,China.We investigated alpine rainfall-runoff processes,as well as impacts of summer thaw depth of active layer,soil temperature and moisture variation on streamflow based on in-situ observations from July 2015 to December 2020.Some hydrologic parameters or indices were calculated using statistical methods,and impacts of permafrost change on river runoff were assessed using the variable infiltration capacity model(VIC).In the alpine meadow,surface soil(0–10 cm depth)of the active layer starts to freeze in mid-October each year,and begins to thaw in early April.Also,the deeper soil(70–80 cm depth)of the active layer starts to freeze in late October,and begins to thaw in late June.Moisture content in shallow soils fluctuates regularly,whereas deeper soils are more stable,and their response to rainstorms is negligible.During active layer thawing,the moisture content increases with soil depth.In the alpine meadow,vertical infiltration only occurred in soils up to 40 cm deep,and lateral flow occurred in0–20 and 60–80 cm deep soils at current rainfall intensity.Summer runoff ratios were 0.06–0.31,and runoff floods show lags of 9.5–23.0 h following the rainfall event in the study area.The freeze–thaw process also significantly impacts runoff regression coefficients,which were 0.0088–0.0654 per hour.Recession coefficient decrease negatively correlates with active layer thawing depth in summer and autumn.Alpine river basin permafrost can effectively increase peak discharge and reduce low flow.These findings are highly significant for rainfall–runoff conversion research in alpine areas of inland rivers.

Artificial Neural Networks for Event Based Rainfall-Runoff Modeling

The Artificial Neural Network (ANN) approach has been successfully used in many hydrological studies especially the rainfall-runoff modeling using continuous data. The present study examines its applicability to model the event-based rainfall-runoff process. A case study has been done for Ajay river basin to develop event-based rainfall-runoff model for the basin to simulate the hourly runoff at Sarath gauging site. The results demonstrate that ANN models are able to provide a good representation of an event-based rainfall-runoff process. The two important parameters, when predicting a flood hydrograph, are the magnitude of the peak discharge and the time to peak discharge. The developed ANN models have been able to predict this information with great accuracy. This shows that ANNs can be very efficient in modeling an event-based rainfall-runoff process for determining the peak discharge and time to the peak discharge very accurately. This is important in water resources design and management applications, where peak discharge and time to peak discharge are important input

Evaluating the Performance of HEC-HMS and SWAT Hydrological Models in Simulating the Rainfall-Runoff Process for Data Scarce Region of Ethiopian Rift Valley Lake Basin

A number of physically-based and distributed watershed models have been developed to model the hydrology of the watershed. For a specific watershed, selecting the most suitable hydrological model is necessary to obtain good simulated results. In this study, two hydrologic models, Soil and Water Assessment Tool (SWAT) and Hydrological Engineering Centre-The Hydrologic Modeling System (HEC-HMS), were applied to predict streamflow in Katar River basin, Ethiopia. The performances of these two models were compared in order to select the right model for the study basin. Both models were calibrated and validated with stream flow data of 11 years (1990-2000) and 7 years (2001-2007) respectively. Nash-Sutcliffe Error (NSE) and Coefficient of Determination (R2) were used to evaluate efficiency of the models. The results of calibration and validation indicated that, for river basin Katar, both models could simulate fairly well the streamflow. SWAT gave the model performance with the R2 > 0.78 and NSE > 0.67;and the HEC-HMS model provided the model performance with the R2 > 0.87 and NSE > 0.73. Hence, the simulated streamflow given by the HEC-HMS model is more satisfactory than that provided by the SWAT model.

Using SWAT Model and Field Data to Determine Potential of NASA-POWER Data for Modelling Rainfall-Runoff in Incalaue River Basin

Incalaue is a tributary of Lugenda River in NSR (Niassa Special Reserve) in North-Eastern Mozambique. NSR is a data-poor remote area and there is a need for rainfall-runoff data to inform decisions on water resources management, and scientific methods are needed for this wide expanse of land. This study assessed the potential of a combination of NASA-POWER (National Aeronautics and Space Administration and Prediction of Worldwide Energy Resources) remotely sensed rainfall data and FAO (Food and Agriculture Organization of the United Nations) soil and land use/cover data for modelling rainfall-runoff in Incalaue river basin. DEM (Digital Elevation Model) of 1:250,000 scale and a grid resolution of 30 m × 30 m downloaded from USGS (the United States Geological Survey) website;clipped river basin FAO digital soil and land use/cover maps;and field-collected data were used. SWAT (Soil and Water Assessment Tool) model was used to assess rainfall -runoff data generated using the NASA-POWER dataset and gauged rainfall and river flow data collected during fieldwork. FAO soil and land use/cover datasets which are globally available and widely used in the region were used for comparison with soil data collected during fieldwork. Field collected data showed that soil in the area is predominantly sandy loam and only sand content and bulk density were uniformly distributed across the soil samples. SWAT model showed a good rainfall-runoff relationship using NASA-POWER data for the area (R2 = 0.7749) for the studied period (2019-2021). There was an equally strong rainfall-runoff relationship for gauged data (R2 = 0.8131). There were uniform trends for the rainfall, temperature, and relative humidity in NASA-POWER meteorological data. Timing of peaks and lows in rainfall and river flow observed in the field and modelled were confirmed by residents as the trend in the area. This approach was used because there was no historical rainfall and river flow data since the river basin is ungauged for hydrologic data. The study showed that NASA-POWER data has the potential for use for modelling the rainfall-runoff in the basin. The difference in rainfall-runoff relationship with field-collected data could be because of landscape characteristics or topsoil layer not catered for in the FAO soil data.

Assessment of soil erosion in the Irga watershed on the eastern edge of the Chota Nagpur Plateau,India

Human activities to improve the quality of life have accelerated the natural rate of soil erosion.In turn,these natural disasters have taken a great impact on humans.Human activities,particularly the conversion of vegetated land into agricultural land and built-up area,stand out as primary contributors to soil erosion.The present study investigated the risk of soil erosion in the Irga watershed located on the eastern fringe of the Chota Nagpur Plateau in Jharkhand,India,which is dominated by sandy loam and sandy clay loam soil with low soil organic carbon(SOC)content.The study used the Revised Universal Soil Loss Equation(RUSLE)and Geographical Information System(GIS)technique to determine the rate of soil erosion.The five parameters(rainfall-runoff erosivity(R)factor,soil erodibility(K)factor,slope length and steepness(LS)factor,cover-management(C)factor,and support practice(P)factor)of the RUSLE were applied to present a more accurate distribution characteristic of soil erosion in the Irga watershed.The result shows that the R factor is positively correlated with rainfall and follows the same distribution pattern as the rainfall.The K factor values in the northern part of the study area are relatively low,while they are relatively high in the southern part.The mean value of the LS factor is 2.74,which is low due to the flat terrain of the Irga watershed.There is a negative linear correlation between Normalized Difference Vegetation Index(NDVI)and the C factor,and the high values of the C factor are observed in places with low NDVI.The mean value of the P factor is 0.210,with a range from 0.000 to 1.000.After calculating all parameters,we obtained the average soil erosion rate of 1.43 t/(hm^(2)•a),with the highest rate reaching as high as 32.71 t/(hm^(2)•a).Therefore,the study area faces a low risk of soil erosion.However,preventative measures are essential to avoid future damage to productive and constructive activities caused by soil erosion.This study also identifies the spatial distribution of soil erosion rate,which will help policy-makers to implement targeted soil erosion control measures.

Indoor imitation experimental study on driving factors of rainfall-runoff process

The driving actions of rainfall-runoff process can be attributed to two aspects. The first is the influence of precipitation process, and the second is that of the ground pad. The re- search results of 179 indoor experiments conducted to imitate rainfall-runoff process indicate that both precipitation duration and intensity play important roles in affecting confluence lag time, which is obviously inconsistent with the traditional hypotheses. The nonlinear relationship is of great significance to the confluence curve especially when the precipitation duration is less than the total confluence time or the precipitation intensity is small. Therefore it can be concluded that the unit hydrograph (UH) can be applied to rainfall-runoff process imitation in the humid areas in the south China region. However, the UH application should be strictly modified in accordance with precipitation conditions in the arid and semiarid region of north China where the precipitation duration is short and the intensity is unstable. It will be hard to get ideal imitation results if the UH is applied blindly without considering specific conditions in the north China region. This also explains the unsatisfactory imitation results caused by using various hydrological models in the north China region. When the precipitation duration is short, and the watershed has not reached total watershed concentration, the characteristics of confluence change greatly, which reflects the actual situation in the north China region. Therefore necessary nonlinear corrections should be made when UH is applied. If the duration is longer than the total confluence time and the balance between pondage and discharge is stricken, the imitation research results will be applicable to both rainfall-runoff relation with longer duration in the south China region and the basic theoreti- cal research on runoff generation and concentration. On conditions of adequate rainfall, peak discharge is in linear relationship with intensity, but has nothing to do with the ground pad. There is a negative linear relationship between intensity and time to peak . The amount of pondage capacity in a catchment is in linear relationship with intensity and peak discharge, with obvious influence by the ground pad status and interception, and it has nothing to do with the position of interceptions.

Integrated rainfall-runoff process with shallow water model by mass varied smoothed particle hydrodynamics:Infiltration effect implementation

Rainfall-runoff modeling is essential for addressing a wide range of issues in urban drainage system design and operation in both scientific research and engineering practice.Recently,it has become increasingly attractive to use the smoothed particle hydrodynamics(SPH)method to model rainfall-runoff because of its inherent features such as mesh-free and automatic adaptiveness for wet-dry interfaces.However,one of its inadequacies is the lack of an infiltration effect within rainfall-runoff modeling.Hence,we propose a new methodology that innovatively integrates the infiltration effect into the shallow water equation(SWE)system with the SPH method(SPH-SWE)to represent a more complete rainfall-runoff process.In the proposed method,the mass-varied SPH-SWE(MVSPH-SWE)method is enhanced by integrating the infiltration model.A naked area treatment(NAT)method is subsequently proposed to improve the modeling efficiency and accuracy.The obtained numerical results are validated using experimental data from the literature.The results demonstrate that the proposed method is accurate and reliable.The achievements and findings of this study are expected to improve and extend the use of existing hydrological process models.

Comparison of the performance of a hydrologic model and a deep learning technique for rainfall-runoff analysis

Rainfall-runoff analysis is the most important and basic analysis in water resources management and planning.Conventional rainfall-runoff analysis methods generally have used hydrologic models.Rainfall-runoff analysis should consider complex interactions in the water cycle process,including precipitation and evapotranspiration.In this study,rainfall-runoff analysis was performed using a deep learning technique that can capture the relationship between a hydrological model used in the existing methodology and the data itself.The study was conducted in the Yeongsan River basin,which forms a large-scale agricultural area even after industrialization,as the study area.As the hydrology model,SWAT(Soil and Water Assessment Tool)was used,and for the deep learning method,a Long Short-Term Memory(LSTM)network was used among RNNs(Recurrent Neural Networks)mainly used in time series analysis.As a result of the analysis,the correlation coefficient and NSE(Nash-Sutcliffe Efficiency),which are performance indicators of the hydrological model,showed higher performance in the LSTM network.In general,the LSTM network performs better with a longer calibration period.In other words,it is worth considering that a data-based model such as an LSTM network will be more useful than a hydrological model that requires a variety of topographical and meteorological data in a watershed with sufficient historical hydrological data.

The effects of rainfall regimes and rainfall characteristics on peak discharge in a small debris flow-prone catchment

Peak discharge plays an important role in triggering channelized debris flows.The rainfall regimes and rainfall characteristics have been demonstrated to have important influences on peak discharge.In order to explore the relationship between rainfall regimes and peak discharge,a measuring system was placed at the outlet of a small,debris flow-prone catchment.The facility consisted of an approximately rectangular stilling basin,ending with a sharp-crested weir.Six runoff events were recorded which provided a unique opportunity for characterizing the hydrological response of the debris flow-prone catchment.Then,a rainfall–runoff model was tested against the flow discharge measurements to have a deep understanding of hydrological response.Based on the calibrated rainfall-runoff model,twelve different artificially set rainfall patterns were regarded as the input parameters to investigate the effect of rainfall regimes on peak discharge.The results show that the rainfall patterns have a significant effect on peak discharge.The rainfall regimes which have higher peak rainfall intensity and peak rainfall point occur at the later part of rainfall process are easy to generate larger peak discharge in the condition of the same cumulative rainfall and duration.Then,in order to explore the relationship between rainfall characteristics and peak discharge under different cumulative precipitation and different duration,167 measured rainfall events were also collected.On the basis of rainfall depth,rainfall duration,and maximum hourly intensity,all the rainfall events were classified into four categories by using K-mean clustering.Rainfall regime 1 was composed of rainfall events with a moderate mean P(precipitation),a moderate D(duration),and a moderate I60(maximum hourly intensity).Rainfall regime 2 was the group of rainfall events with a high mean P,long D.Rainfall regime 3,however,had a low P and a long D.The characteristic of Rainfall regime 4 was high I60 and short duration with large P.The results show that the rainfall regime 2 and 4 are easier to generate peak discharge as the rainfall intensity plays an important role in generating peak discharge.The results in this study have implications for improving peak discharge prediction accuracy in debris flow gully.

Sediment transport following water transfer from Yangtze River to Taihu Basin

To meet the increasing ：need of fresh water and to improve the water quality of Taihu Lake, water transfer from the Yangtze River was initiated in 2002. This study was performed to investigate the sediment distribution along the river course following water transfer. A rainfall-runoff model was first built to calculate the runoff of the Taihu Basin in 2003. Then, the flow patterns of river networks were simulated using a one-dimensional river network hydrodynamic model. Based on the boundary conditions of the flow in tributaries of the Wangyu River and the water level in Taihu Lake, a one-dimensional hydrodynamic and sediment transport numerical model of the Wangyu River was built to analyze the influences of the inflow rate of the water transfer and the suspended sediment concentration （SSC） of inflow on the sediment transport. The results show that the water transfer inflow rate and SSC of inflow have significant effects on the sediment distribution. The higher the inflow rate or SSC of inflow is, the higher the SSC value is at certain cross-sections along the ：river course of water transfer. Higher inflow rate and SSC of inflow contribute to higher sediment deposition per kilometer and sediment thickness. It is also concluded that a sharp decrease of the inflow velocity at the entrance of the Wangyu River on the river course of water transfer induces intense sedimentation at the cross-section near the Changshu hydro-junction. With an increasing distance from the Changshu hydro-junction, the sediment deposition and sedimentation thickness decrease gradually along the river course.

GIS-Based Spatial Mapping of Flash Flood Hazard in Makkah City, Saudi Arabia

Flash floods occur periodically in Makkah city, Saudi Arabia, due to several factors including its rugged to-pography and geological structures. Hence, precise assessment of floods becomes a more vital demand in development planning. A GIS-based methodology has been developed for quantifying and spatially mapping the flood characteristics. The core of this new approach is integrating several topographic, metrological, geological, and land use datasets in a GIS environment that utilizes the Curve Number (CN) method of flood modelling for ungauged arid catchments. Additionally, the computations of flood quantities, such as depth and volume of runoff, are performed in the attribute tables of GIS layers, in order to assemble all results in the same environment. The accomplished results show that the runoff depth in Makkah, using a 50-years re-turn period, range from 128.1 mm to 193.9 mm while the peak discharge vary from 1063 m3/s to 4489 m3/s. The total flood volume is expected to reach 172.97 million m3 over Makkah metropolitan area. The advan-tages of the developed methodology include precision, cost-effective, digital outputs, and its ability to be re-run in other conditions.

Improvement of LCM model and determination of model parameters at watershed scale for flood events in Hongde Basin of China

Considering the fact that the original two-parameter LCM model can only be used to investigate rainfall losses during the runoff period because the initial abstraction is not included, the LCM model was redefined as a three-parameter model, including the initial abstraction coefficient l, the initial abstraction Ia, and the rainfall loss coefficient R. The improved LCM model is superior to the original two-parameter model, which only includes r and R, where r is the initial rainfall loss index and can be calculated with l using the Soil Conservation Service curve number （SCS-CN） method, with r = 1/（1 ＋ λ）. The trial method was used to determine the parameter values of the improved LCM model at the watershed scale for 15 flood events in the Hongde Basin in China. The results show that larger r values are associated with smaller R values, and the parameter R ranges widely from 0.5 to 2.0. In order to improve the practicability of the LCM model, r = 0.833 with λ = 0.2 is reasonable for simplifying calculation. When the LCM model is applied to arid and semi-arid regions, rainfall without yielding runoff should be deducted from the total rainfall for more accurate estimation of rainfall-runoff.

Effects of urban grass coverage on rainfall-induced runoff in Xi'an loess region in China

In this study, laboratory rainfall simulation experiments were conducted to investigate the regulatory effects of grass coverage on rainfallrunoff processes. A total of 80 grass blocks planted with well-grown manilagrass, together with their root systems, were sampled from an eastern suburban area of Xi'an City in the northwest arid area of China and sent to a laboratory for rainfall simulation experiments. The runoff and infiltration processes of a slope with different grass coverage ratios and vegetation patterns were analyzed. The results show that the runoff coefficient decreases with the increase of the grass coverage ratio, and the influence of grass coverage on the reduction of runoff shows a high degree of spatial variation. At a constant grass coverage ratio, as the area of grass coverage moves downward, the runoff coefficient, total runoff,and flood peak discharge gradually decrease, and the flood peak occurs later. With the increase of the grass coverage ratio, the flood peak discharge gradually decreases, and the flood peak occurs later as well. In conclusion, a high grass coverage ratio with the area of grass coverage located at the lower part of the slope will lead to satisfactory regulatory effects on rainfall-induced runoff.

Monthly and seasonal streamflow forecasting of large dryland catchments in Brazil

Streamflow forecasting in drylands is challenging.Data are scarce,catchments are highly humanmodified and streamflow exhibits strong nonlinear responses to rainfall.The goal of this study was to evaluate the monthly and seasonal streamflow forecasting in two large catchments in the Jaguaribe River Basin in the Brazilian semi-arid area.We adopted four different lead times:one month ahead for monthly scale and two,three and four months ahead for seasonal scale.The gaps of the historic streamflow series were filled up by using rainfall-runoff modelling.Then,time series model techniques were applied,i.e.,the locally constant,the locally averaged,the k-nearest-neighbours algorithm(k-NN)and the autoregressive(AR)model.The criterion of reliability of the validation results is that the forecast is more skillful than streamflow climatology.Our approach outperformed the streamflow climatology for all monthly streamflows.On average,the former was 25%better than the latter.The seasonal streamflow forecasting(SSF)was also reliable(on average,20%better than the climatology),failing slightly only for the high flow season of one catchment(6%worse than the climatology).Considering an uncertainty envelope(probabilistic forecasting),which was considerably narrower than the data standard deviation,the streamflow forecasting performance increased by about 50%at both scales.The forecast errors were mainly driven by the streamflow intra-seasonality at monthly scale,while they were by the forecast lead time at seasonal scale.The best-fit and worst-fit time series model were the k-NN approach and the AR model,respectively.The rainfall-runoff modelling outputs played an important role in improving streamflow forecasting for one streamgauge that showed 35%of data gaps.The developed data-driven approach is mathematical and computationally very simple,demands few resources to accomplish its operational implementation and is applicable to other dryland watersheds.Our findings may be part of drought forecasting systems and potentially help allocating water months in advance.Moreover,the developed strategy can serve as a baseline for more complex streamflow forecast systems.

Hydrological modelling in the anthroposphere: predicting local runoff in a heavily modified high-alpine catchment

Hydrological models within inflow forecasting systems for high-alpine hydropower reservoirs can provide valuable information as part of a decision support system for the improvement of hydropower production or flood retention. The information, especially concerning runoff, is however rarely available for the calibration of the hydrological models used. Therefore, a method is presented to derive local runoff from secondary information for the calibration of the model parameters of the rainfallrunoff model COSERO. Changes in water levels in reservoirs, reservoir outflows, discharge measurements at water intakes and in transport lines are thereby used to derive the local, "natural" flow for a given sub-catchment. The proposed method is applied within a research study for the ?BB Infrastructure Railsystem division in the Stubache catchment in the central Austrian Alps. Here, the ?BB operates the hydropower scheme "Kraftwerksgruppe Stubachtal", which consists of 7 reservoirs and 4 hydropower stations. The hydrological model has been set up considering this human influences and the high natural heterogeneity in topography and land cover, including glaciers. Overall, the hydrological model performs mostly well for the catchment with highest NSE values of 0.78 for the calibration and0.79 for the validation period, also considering the use of homogeneous parameter fields and the uncertainty of the derived local discharge values. The derived runoff data proved to be useful information for the model calibration. Further analysis, examining the water balance and its components as well as snow cover, showed satisfactory simulation results. In conclusion, a unique runoff dataset for a small scale high-alpine catchment has been created to establish a hydrological flow prediction model which in a further step can be used for improved and sustainable hydropower management.

Rainfall and Runoff Observations in the Subtropical Forest of Okinawa Island, Japan

We set up two experimental catchments to provide an improved understanding of hydrological processes in a subtropical forested area in the northern part of Okinawa Island, Japan. We calculated runoff using water level data (recorded by a pressure-type water level gauge installed in a box culvert) and a discharge rating curve (derived from in situ observations). Water balance calculations for 2010 showed that the rainfall, runoff and evapotranspiration losses (= rainfall – runoff) were 3403.6 mm, 2285.7 mm and 1117.4 mm, respectively. This result was in agreement with previous results from other forested experimental catchments in this region. Direct runoff, as a proportion of event total rainfall, can be expressed by the empirical equation (Qdirect = 0.0048, Pevent 1.7971, R2 = 0.9599). When Pevent was 100 mm or less, the ratios of Qdirect to Pevent were less than 15% in general. When Pevent exceeded 100 mm, the ratios were 20% - 30%.