Discharge Stations Research Articles

Hydrologic Characteristics of Streamflow in the Southeast Atlantic and Gulf Coast Hydrologic Region during 1939–2016 and Conceptual Map of Potential Impacts

Streamflow is one the most important variables controlling and maintaining aquatic ecosystem integrity, diversity, and sustainability. This study identified and quantified changes in 34 hydrologic characteristics and parameters at 30 long term (1939–2016) discharge stations in the Southeast Atlantic and Gulf Coast Hydrologic Region (Region 3) using Indicators of Hydrologic Alteration (IHA) variables. The southeastern United States (SEUS) is a biodiversity hotspot, and the region has experienced a number of rapid land use/land cover changes with multiple primary drivers. Studies in the SEUS have been mostly localized on specific rivers, reservoir catchments and/or species, but the overall region has not been assessed for the long-term period of 1939–2016 for multiple hydrologic characteristic parameters. The objectives of the study were to provide an overview of multiple river basins and 31 hydrologic characteristic parameters of streamflow in Region 3 for a longer period and to develop a conceptual map of impacts of selected stressors and changes in hydrology and climate in the SEUS. A seven step procedure was used to accomplish these objectively: Step 1: Download data from the 30 USGS gauging stations. Steps 2 and 3: Select and analyze the 31 IHA parameters using boxplots, scatter plots, and PDFs. Steps 4 and 5: Synthesize the drivers of changes and alterations and the various change points in streamflow in the literature. Step 6: Synthesize the climate of the SEUS in terms of temperature and precipitation changes. Step 7: Develop a conceptual map of impacts of selected stressors on hydrology using Driver–Pressure–State-Impact–Response (DPSIR) framework and IHA parameters. The 31 IHA parameters were analyzed. The meta-analysis of literature in the SEUS revealed the precipitation changes observed ranged from −30% to +35% and temperature changes from −2 °C to 6 °C by 2099. The fiftieth percentile of the Global Climate Models (GCM) predict no precipitation change and an increase in the temperature of 2.5 °C in the region by 2099. Among the GCMs, the 5th and 95th percentile of precipitation changes range between −40% and 110% and temperature changes between −2 °C and 6 °C by 2099. Meta-analysis of land use/land cover show the region has experienced changes. A number of rapid land use/land cover changes in 1957, 1970, and 1998 are some of the change points documented in the literature for precipitation and streamflow in the region. A conceptual map was developed to represent the impacts of selected drivers and the changes in hydrology and climate in the study region for three land use/land cover categories in three different periods.

Effects of thermal discharge from Neka power plant (southern Caspian Sea) on macrobenthic diversity and abundance

Effects of thermal discharge from Neka power plant on macrobenthic diversity and abundance was studied in the southern coast of the Caspian Sea. Samples were collected with Van Veen grab of 0.0250 m2 surface area from 7 stations in winter and summer. A total of 42 species were identified that belonged to 22 genera, 18 families, 13 orders, six classes and three phyla. Bivalve with a total abundance of 90% in winter and 86% in summer constituted the most abundant group throughout samplings, the highest abundance of which belonged to the family Cardiidae. Gastropods followed bivalve in total abundance (8%) in summer and polychaetes (7%) in winter. Statistical analysis indicated significantly higher macrobenthos density at the thermal discharge stations that also took separate positions in the cluster analysis. Temperature was an important factor on the amount of organic matter. Chlorophyll and phaeopigment at the thermal discharge stations were lower than the other stations because of the increased turbulence. The CCA test indicated that temperature was the most influential among all the studied physicochemical factors. The Spearman rank correlation coefficient also showed that the majority of macrobenthic groups had a positive correlation with the organic matter (r = 0.34, p < 0.05). Macrobenthic species were grouped according to their commonalities relative to these three classes using a Bray-Curtis similarity index and similarity profile (SIMPROF) permutation tests analysis (PRIMER 6). Based on the SIMPER analysis, the cockle Hypanis minima and the polychaete Hypaniola kowalewskii with high abundances played the most important role in making differences among the stations, but won’t be taken as the “thermal indicating species”. The PERMANOVA test showed that the combination of season and stations had a significant effect. The density of macrobenthos was higher in the thermal discharge stations, but diversity in these stations reduced in comparison with the other stations.

Penerapan model kendali mutu data hidrologi dalam rangka peningkatan kualitas data

Planning and management of water resources are dependent on the quality of hydrological data. Hydrological data plays an important role in hydrological analysis. The availability of good and qualified hydrological data is one of the determinants of the results of hydrological analysis. However, the facts indicate that many of the available data do not fit their ideal state. To solve this problem, a hydrological data quality control model should be established in order to improve the quality of national hydrological data. The scope includes quality control of rainfall and discharge data. Analysis of the quality control of rainfall data was conducted on 58 rainfall stations spread on the island of Java. The analysis shows that 41 stations are good categorized, 14 stations are in moderate category and 3 stations are badly categorized. Based on these results, a light improvement scenario was performed, good category Station increased to 46 stations, moderate category decreased to 11 stations and bad category reduced to 1 Stations. Quality control of discharge data analysis was conducted on 14 discharge stations spread on Java Island. Analyzes were performed for QC1, QC2 and QC3 then got final QC value. The results on the final QC show no stations for good category, 2 stations for moderate categories and 12 stations for bad category. Based on the results of the analysis, a light improvement scenario was performed with the result of bad category increased to good category 5 stations, bad category increased to moderate 7 stations, and moderate category 1 stations.

Quantifying human impacts on hydrological drought using a combined modelling approach in a tropical river basin in central Vietnam

Abstract. Hydrological droughts are one of the most damaging disasters in terms of economic loss in central Vietnam and other regions of South-east Asia, severely affecting agricultural production and drinking water supply. Their increasing frequency and severity can be attributed to extended dry spells and increasing water abstractions for e.g. irrigation and hydropower development to meet the demand of dynamic socioeconomic development. Based on hydro-climatic data for the period from 1980 to 2013 and reservoir operation data, the impacts of recent hydropower development and other alterations of the hydrological network on downstream streamflow and drought risk were assessed for a mesoscale basin of steep topography in central Vietnam, the Vu Gia Thu Bon (VGTB) River basin. The Just Another Modelling System (JAMS)/J2000 was calibrated for the VGTB River basin to simulate reservoir inflow and the naturalized discharge time series for the downstream gauging stations. The HEC-ResSim reservoir operation model simulated reservoir outflow from eight major hydropower stations as well as the reconstructed streamflow for the main river branches Vu Gia and Thu Bon. Drought duration, severity, and frequency were analysed for different timescales for the naturalized and reconstructed streamflow by applying the daily varying threshold method. Efficiency statistics for both models show good results. A strong impact of reservoir operation on downstream discharge at the daily, monthly, seasonal, and annual scales was detected for four discharge stations relevant for downstream water allocation. We found a stronger hydrological drought risk for the Vu Gia river supplying water to the city of Da Nang and large irrigation systems especially in the dry season. We conclude that the calibrated model set-up provides a valuable tool to quantify the different origins of drought to support cross-sectorial water management and planning in a suitable way to be transferred to similar river basins.

Peak Discharge and Hydrograph Assessments Induced by Heavy Rainfall Events Using Tank Model

Tank Model is a kind of simulation of rainfall movement in soil horizon. With the runoff and piping rate, the peak discharge could be effectively calculated. Having 17 rain gauge stations in 13 debris flow events during 1996-2010 as the studied cases, the peak discharge at 12 control points along Chenyulan River is simulated. Furthermore, the data in Neimaopu discharge station is established parameters of Tank Model to estimate the peak discharge in Shenmu Village. By comparing with the parameters of Shueili Station and Japanese Granite, the mean error of the parameter in this study is 51.0%, which is better than those of Japanese Granite 189% and Shueili discharge stations 251%. The parameter in this study appears the highest in allowance analysis, showing that it is more suitable for simulating the peak discharge than the other two. In spite that the percentage of the three parameters is still low, Shenmu Village could be ignored as it locates in the sub-basin of Chenyulan River with few factors. The parameters of Tank Model are applied to transform average rainfall into hydrograph so as to solve the problem of no discharge records when analysing the areas with various debris flow simulation programs.

Spatial pattern evaluation of a calibrated national hydrological model – a remote-sensing-based diagnostic approach

Abstract. Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land–atmosphere interface, obtained from two different approaches at the national scale of Denmark. The first approach is based on a national water resources model (DK-model), using the MIKE-SHE model code, and the second approach utilizes a two-source energy balance model (TSEB) driven mainly by satellite remote sensing data. Ideally, the hydrological model simulation and remote-sensing-based approach should present similar spatial patterns and driving mechanisms of ET. However, the spatial comparison showed that the differences are significant and indicate insufficient spatial pattern performance of the hydrological model.The differences in spatial patterns can partly be explained by the fact that the hydrological model is configured to run in six domains that are calibrated independently from each other, as it is often the case for large-scale multi-basin calibrations. Furthermore, the model incorporates predefined temporal dynamics of leaf area index (LAI), root depth (RD) and crop coefficient (Kc) for each land cover type. This zonal approach of model parameterization ignores the spatiotemporal complexity of the natural system. To overcome this limitation, this study features a modified version of the DK-model in which LAI, RD and Kc are empirically derived using remote sensing data and detailed soil property maps in order to generate a higher degree of spatiotemporal variability and spatial consistency between the six domains. The effects of these changes are analyzed by using empirical orthogonal function (EOF) analysis to evaluate spatial patterns. The EOF analysis shows that including remote-sensing-derived LAI, RD and Kc in the distributed hydrological model adds spatial features found in the spatial pattern of remote-sensing-based ET.

Estimation of flow regime for a spatially varied Himalayan watershed using improved multi-site calibration of the Soil and Water Assessment Tool (SWAT) model

Due to the influential role in global climate, the hydrologic modeling of the watersheds in Himalayan mountain range is critically important for the socioeconomy and livelihood of surrounding regions. As these watersheds usually have snow-driven hydrology and abrupt changes in orography, the challenges in hydrologic model are acknowledged in scientific community. In this study, we addressed this challenge by implementing an improved multivariable and multi-site approach to calibration and validation of the Soil Water Assessment Tool (SWAT) model for determining its ability to mimic flow regime of the watershed. In the improved multi-site approach, the model was successfully calibrated using 1980–1985 streamflow data and validated using 1990–1995 data for the daily time steps. Combination of different performance metrics indicates that the improved method increased the efficiency of daily prediction of Karnali River discharge. We utilized 30 years of streamflow data from four discharge stations to explore the changes in flow pattern at the decadal scales. Groundwater flow decreased in monsoon season compared to other season where the changes in flow regimes were insignificant within the decadal scale. The proposed calibration method can be used to any other large mountainous watershed to improve the estimation of the hydrologic processes.

Influence of Bizerte city wastewater treatment plant (WWTP) on abundance and antibioresistance of culturable heterotrophic and fecal indicator bacteria of Bizerte Lagoon (Tunisia)

The waste water treatment plant (WWTP) of the city of Bizerte concentrates different types of chemical and biological pollutants in the Bizerte lagoon (Tunisia). Considering four upstream and downstream WWTP discharge stations, seventy nine, culturable bacterial strains were isolated and identified from water and sediment as fecal coliforms, fecal streptococci, pathogenic staphylococci and non-enterobacteriacea. Fecal coliforms were most abundant (2.5 105 bacteria/mg) in sediment of WWTP discharge. Leuconostoc spp (23.1%) and Chryseomonasluteola (23.1%) were the most prevalent culturable fecal indicator bacteria (FIB) isolated at the upstream discharge stations. However, Staphylococcus xylosus (13.9%) was the most prevalent culturable FIB isolated at the WWTP discharge stations. Moreover, high antibioticresistance phenotypes were present in all sampling stations, but especially in WWTP discharge station in both water and sediment. Resistance levels in water and sediment, respectively were amoxicillin (58.8%; 34.8%), penicillin (50%; 31.6%), oxacillin (60%; 33.3%), cefotaxim (55.2%; 39.1%), ceftazidim (66.7%; 50%), gentamycin (42.9%; 38.9%), tobramycin (50%; 25%), vancomycin (33.3; 71.4%), amikacin (66.7%; 0%) and ciprofloxacin (100%; 100%). Interestingly, ß-lactam antibiotic resistant FIB were mostly isolated from water as well as from sediments of upstream and WWTP discharge station. Canonical correspondence analysis CCA correlating antibiotic resistance profile with the abiotic data showed that, in water column, culturable bacterial strains isolated in upstream WWTP discharge stations were interestingly correlated with the resistance to amikacin, oxacillin, cefotaxim, ciprofloxacin and gentamycin, however, in sediment, they were correlated with the resistance to amoxicillin, oxacillin, céfotaxim and vancomycin. Serious ß-lactams and aminoglycosides acquired resistance appeared mainly in fecal streptococci and pathogen staphylococci groups.

Annual cycle of temperature and snowmelt runoff in Satluj River Basin using in situ data

Abstract Melting of snow and ice contributes a large amount of water to the streamflow in the Satluj River. During the winter season, there is low base flow in the river as compared to spring and summer. Temperature is one of the key factors which directly impacts snow and ice melting throughout the year. A substantial amount of snowmelt only occurs when all the snow in a pack reaches isothermal condition. It is therefore very important to know the duration of impact of temperature on snowmelt runoff. Since the Himalayas have very few stations observing hydrological as well as meteorological conditions, it is difficult to validate the snowmelt models and examine changes in small-scale features in river basins of the region. The present study examines the annual cycle and interannual variability of runoff in the Satluj Basin in the western Himalayas and documents the impact of temperature on snowmelt runoff of Satluj River using daily in situ data for the period 1982–2005. A multivariate regression model using precipitation and surface temperature has been developed to predict the discharge of Satluj River at a daily scale. It is seen that after every warm phase and cold phase of temperature, the impact persists for around one month and affects the snowmelt runoff during January, February and March at lower- and higher-elevation stations such as Bhakra and Kasol, respectively. The effect of a large fall and rise in temperature is noticed on snowmelt runoff measured at all the discharge stations, while a small temperature change does not affect the observed discharge at all the stations. The remote sensing and reanalysis data are consistent with in situ data in the basin, and there is no major change in peak month of discharge or the amplitude during two different periods at Rampur gauge station.

Optimization of hydrometric monitoring network in urban drainage systems using information theory.

Regular and continuous monitoring of urban runoff in both quality and quantity aspects is of great importance for controlling and managing surface runoff. Due to the considerable costs of establishing new gauges, optimization of the monitoring network is essential. This research proposes an approach for site selection of new discharge stations in urban areas, based on entropy theory in conjunction with multi-objective optimization tools and numerical models. The modeling framework provides an optimal trade-off between the maximum possible information content and the minimum shared information among stations. This approach was applied to the main surface-water collection system in Tehran to determine new optimal monitoring points under the cost considerations. Experimental results on this drainage network show that the obtained cost-effective designs noticeably outperform the consulting engineers' proposal in terms of both information contents and shared information. The research also determined the highly frequent sites at the Pareto front which might be important for decision makers to give a priority for gauge installation on those locations of the network.

Choice of rainfall inputs for event-based rainfall-runoff modeling in a catchment with multiple rainfall stations using data-driven techniques

Input selection for data-driven rainfall-runoff models is an important task as these models find the relationship between rainfall and runoff by direct mapping of inputs to output. In this study, two different input selection methods were used: cross-correlation analysis (CCA), and a combination of mutual information and cross-correlation analyses (MICCA). Selected inputs were used to develop adaptive network-based fuzzy inference system (ANFIS) in Sungai Kayu Ara basin, Selangor, Malaysia. The study catchment has 10 rainfall stations and one discharge station located at the outlet of the catchment. A total of 24 rainfall-runoff events (10-min interval) from 1996 to 2004 were selected from which 18 events were used for training and the remaining 6 were reserved for validating (testing) the models. The results of ANFIS models then were compared against the ones obtained by conceptual model HEC-HMS. The CCA and MICCA methods selected the rainfall inputs only from 2 (stations 1 and 5) and 3 (stations 1, 3, and 5) rainfall stations, respectively. ANFIS model developed based on MICCA inputs (ANFIS-MICCA) performed slightly better than the one developed based on CCA inputs (ANFIS-CCA). ANFIS-CCA and ANFIS-MICCA were able to perform comparably to HEC-HMS model where rainfall data of all 10 stations had been used; however, in peak estimation, ANFIS-MICCA was the best model. The sensitivity analysis on HEC-HMS was conducted by recalibrating the model by using the same selected rainfall stations for ANFIS. It was concluded that HEC-HMS model performance deteriorates if the number of rainfall stations reduces. In general, ANFIS was found to be a reliable alternative for HEC-HMS in cases whereby not all rainfall stations are functioning. This study showed that the selected stations have received the highest total rain and rainfall intensity (stations 3 and 5). Moreover, the contributing rainfall stations selected by CCA and MICCA were found to be located near the outlet of contributing sub-catchments. This provides valuable information towards identifying the more contributing sub-catchments in catchments such as Sungai Kayu Ara where no flow measurement is available for sub-catchments.

Spatiotemporal processes that contribute to hydrologic exchange between hillslopes, valley bottoms, and streams

AbstractQuantifying how watershed structure influences the exchanges of water among component parts of a watershed, particularly the connection between uplands, valley bottoms, and in‐stream hydrologic exchange, remains a challenge. However, this understanding is critical for ascertaining the source areas and temporal contributions of water and associated biogeochemical constituents in streams. We used dilution gauging, mass recovery, and recording discharge stations to characterize streamflow dynamics across 52 reaches, from peak snowmelt to base flow, in the Tenderfoot Creek Experimental forest, Montana, USA. We found that watershed‐contributing area was only a significant predictor of net changes in streamflow at high moisture states and larger spatial scales. However, at the scale of individual stream reaches, the lateral contributing area in conjunction with underlying lithology and vegetation densities were significant predictors of gross hydrologic gains to the stream. Reach lateral contributing areas underlain by more permeable sandstone yielded less water across flow states relative to those with granite gneiss. Additionally, increases in the frequency of steps across each stream reach contributed to greater hydrologic gross losses. Together, gross gains and losses of water along individual reaches resulted in net changes of discharge that cumulatively scale to the observed outlet discharge dynamics. Our results provide a framework for understanding how hillslope topography, geology, vegetation, and valley bottom structure contribute to the exchange of water and cumulative increases of stream flow across watersheds of increasing size.

A regional parameter estimation scheme for a pan-European multi-basin model

Abstract Study region Europe. Study focus A semi-distributed continuous hydrological model, HYPE, was applied to model daily stream flows in more than 35,000 subcatchments across Europe. A stepwise regionalization approach was implemented to estimate different groups of model parameters. HRU based parameters were estimated first for each soil and landuse class, respectively. Lake and reservoir parameters were estimated separately. Catchments were grouped based on similarity of their characteristics and model parameters defined at a catchment scale were then regionalized for each group as functions of the catchment characteristics by simultaneously calibrating the model for a number of catchments to concurrently optimize the overall model performance and the functional relationships between the parameters and the catchment characteristics. Calibration was performed at 115 discharge stations and the approach was validated at 538 independent stations. New hydrological insights for the region Parameters could be linked to catchment descriptors with good transferability, with median NSE of 0.54 and 0.53, and median volume error of ⿿1.6% and 1.3% in the calibration and validation stations, respectively. Although regionalizing parameters for different groups of catchments separately yielded a better performance in some groups, the overall gain in performance against regionalization using a single set of regional relationships across the entire domain was marginal. The benefits of separate regionalization were substantial in catchments with considerable proportion of agricultural landuse and higher mean annual temperature.

Attribution of high resolution streamflow trends in Western Austria – an approach based on climate and discharge station data

Abstract. The results of streamflow trend studies are often characterized by mostly insignificant trends and inexplicable spatial patterns. In our study region, Western Austria, this applies especially for trends of annually averaged runoff. However, analysing the altitudinal aspect, we found that there is a trend gradient from higher-altitude to lower-altitude stations, i.e. a pattern of mostly positive annual trends at higher stations and negative ones at lower stations. At mid-altitudes, the trends are mostly insignificant. Here we hypothesize that the streamflow trends are caused by the following two main processes: on the one hand, melting glaciers produce excess runoff at higher-altitude watersheds. On the other hand, rising temperatures potentially alter hydrological conditions in terms of less snowfall, higher infiltration, enhanced evapotranspiration, etc., which in turn results in decreasing streamflow trends at lower-altitude watersheds. However, these patterns are masked at mid-altitudes because the resulting positive and negative trends balance each other. To support these hypotheses, we attempted to attribute the detected trends to specific causes. For this purpose, we analysed trends of filtered daily streamflow data, as the causes for these changes might be restricted to a smaller temporal scale than the annual one. This allowed for the explicit determination of the exact days of year (DOYs) when certain streamflow trends emerge, which were then linked with the corresponding DOYs of the trends and characteristic dates of other observed variables, e.g. the average DOY when temperature crosses the freezing point in spring. Based on these analyses, an empirical statistical model was derived that was able to simulate daily streamflow trends sufficiently well. Analyses of subdaily streamflow changes provided additional insights. Finally, the present study supports many modelling approaches in the literature which found out that the main drivers of alpine streamflow changes are increased glacial melt, earlier snowmelt and lower snow accumulation in wintertime.

Hydrologic data as a human right? Equitable access to information as a resource for disaster risk reduction in transboundary river basins

Principles of equitable and reasonable use underpin international water agreements. Despite the potential for hydrologic information to enhance resilience to extreme events, comparable application of just principles to the distribution of hydrometeorological data is poorly established. Within the Ganges–Brahmaputra–Meghna (GBM) river basin, we find that water allocation agreements are codified into treaties or Memorandums of Understanding (MoUs). Analogous decisions regarding hydrometeorological data sharing are often internalized at the level of river basin organizations and are not upheld as MoUs. This institutional structure provides extremely limited data to the most downstream nation of Bangladesh. Available precipitation and discharge stations are well below the minimum densities recommended by the World Meteorological Organization. Forecasters in Bangladesh therefore contend with vast areas of geopolitically ungauged catchment, precluding the application of basin-wide modelling approaches driven by observed data. Thus, capacity for increasing resilience to extreme events within Bangladesh is obstructed, demonstrating the potential for perceived injustice related to distribution of hydrometeorological data. Consensus that water is a human right warrants the application of equity to water allocation. But is security from water-related disasters also a human right? As hydrometeorological data can be a powerful resource with potential to profoundly affect lives and livelihoods, enhanced awareness of justice related to data sharing is needed.

Effects of El-Niño and La-Niña Sea Surface Temperature Anomalies on Annual Precipitations and Streamflow Discharges in Southeastern United States

Clark II, C.; Nnaji, G.A., and Huang, W., 2014. Effects of El-Nino and La-Nina sea surface temperature anomalies on annual precipitations and streamflow discharges in southeastern United States.Statistical analysis shows that El Niño and La Niña are partially responsible for the amounts of annual precipitation and annual streamflow discharges in Gulf Atlantic hydrologic unit of Southeast United States. The study is based on 61-year records of precipitation and streamflow discharge stations spread across the region. The cross-correlation coefficients for both the sea surface temperature (SST) anomalies and precipitation, and SST anomalies and streamflow were calculated after the data series were prewhitened by an Autoregressive Integrated Moving Average (ARIMA) model (2,0,3). The cross-correlations between SST anomalies and both precipitations and streamflow discharges were positively significant. Using statistical relationship established relating SST anomalies with precipitation and streamflow in the area; comparison analyses of observed and filtered data series are performed at locations where there is significant influence of El Niño – Southern Oscillation (ENSO) on precipitations and streamflow discharges in the region. The degree of influence ENSO has on each hydrologic series hence can be predicted for different water sheds in the area. This can be of immense help for water management strategy and planning in the region.

English

This study describes hydrological fluctuations of Lake Abaya-Chamo via direct local measurements in relation to time-integrated climate anomalies. Reconstruction of an index involved compositing lake level and flow discharge station records in the period 1983-2009. Satellite and model interpolated rainfall, latent heat flux and run-off anomalies follow the hydrological records when summed over and lagged by one year. Correlation of ECMWF climate fields reveals that east Pacific and subtropical Atlantic surface temperature are influential on continuous flow discharge, while the Indian Ocean dipole has influence in September to November season. A predictive algorithm accounts for 44% of inter-annual fluctuations in the period 1983-2009. Rapid increases in lake level coincide with maturing El Ni&ntilde;o and Indian Ocean dipole, bringing floods for example in October 1997. Early season dry spells prevail when the equatorial trough remains over Tanzania, and dry northerly winds accelerate evaporation such as in March 2000. &nbsp; Key words: Ethiopia rift lakes, hydrological fluctuations.

Regional water balance modelling using flow-duration curves with observational uncertainties

Abstract. Robust and reliable water-resource mapping in ungauged basins requires estimation of the uncertainties in the hydrologic model, the regionalisation method, and the observational data. In this study we investigated the use of regionalised flow-duration curves (FDCs) for constraining model predictive uncertainty, while accounting for all these uncertainty sources. A water balance model was applied to 36 basins in Central America using regionally and globally available precipitation, climate and discharge data that were screened for inconsistencies. A rating-curve analysis for 35 Honduran discharge stations was used to estimate discharge uncertainty for the region, and the consistency of the model forcing and evaluation data was analysed using two different screening methods. FDCs with uncertainty bounds were calculated for each basin, accounting for both discharge uncertainty and, in many cases, uncertainty stemming from the use of short time series, potentially not representative for the modelling period. These uncertain FDCs were then used to regionalise a FDC for each basin, treating it as ungauged in a cross-evaluation, and this regionalised FDC was used to constrain the uncertainty in the model predictions for the basin. There was a clear relationship between the performance of the local model calibration and the degree of data set consistency – with many basins with inconsistent data lacking behavioural simulations (i.e. simulations within predefined limits around the observed FDC) and the basins with the highest data set consistency also having the highest simulation reliability. For the basins where the regionalisation of the FDCs worked best, the uncertainty bounds for the regionalised simulations were only slightly wider than those for a local model calibration. The predicted uncertainty was greater for basins where the result of the FDC regionalisation was more uncertain, but the regionalised simulations still had a high reliability compared to the locally calibrated simulations and often encompassed them. The regionalised FDCs were found to be useful on their own as a basic signature constraint; however, additional regionalised signatures could further constrain the uncertainty in the predictions and may increase the robustness to severe data inconsistencies, which are difficult to detect for ungauged basins.

Application of swat model in assesment water resources of upper stream of Thi Nai lagoon serving sustainable develoment of Binh Dinh province

Water resources from Kôn and Hà Thanh river basin, upstream areas of Thi Nai lagoon plays a very essential role on hydrological in economic – social development of Binh Dinh province. Assessment of potential water resources in the region can be servered for water resources planning toward sustainable development. In this paper, the SWAT model was applied in this study to evaluate river flow in the rivers. The simulation data were used with with the length of meteorological input data up to 36 years. The parameters of model were calibrated by SWAT-CUP with Sufi-2 algorithm (Semi Automated Sequential Uncertainty Fitting) using data of Binh Tuong discharge station(1980-1995), that also used to analyze parameter sensitivity. The coefficient of determination (R2), NSE values and PBIAS index for the daily runoff were obtained as 0,54; 0,51 and 15,01 % .The average input flow to Thi Nai lagoon were 105,16 m3/s (from Kon river) and 19,77 m3/s (from Ha Thanh river). The results of this study can be used for others research such as water balance calculation in the river basin or it can be used as inputs of water quality and sediment transport model in Thi Nai lagoon.

ENSO impact on hydrology in Peru

Abstract. The El Niño and La Niña impacts on the hydrology of Peru were assessed based on discharge data (1968–2006) of 20 river catchments distributed over three drainage regions in Peru: 14 in the Pacific Coast (PC), 3 in the Lake Titicaca (TL) region, and 3 in the Amazonas (AM). To classify the El Niño and La Niña events, we used the Southern Oscillation Index (SOI) based on hydrological years (September to August). Using the SOI values, the events were re-classified as strong El Niño (SEN), moderate El Niño (MEN), normal years (N), moderate La Niña (MLN) and strong La Niña (SLN). On average during the SEN years, sharp increases occurred in the discharges in the north central area of the PC and decreases in the remaining discharge stations that were analyzed, while in the years of MEN events, these changes show different responses than those of the SEN. During the years classified as La Niña, positive changes are mostly observed in the majority of the stations in the rivers located in the center of Peru's Pacific Coast. Another important result of this work is that the Ilave River (south of the Titicaca watershed) shows higher positive (negative) impacts during La Niña (El Niño) years, a fact that is not clearly seen in the rivers of the northern part of the Titicaca watershed (Ramis and Huancane rivers).