Monthly Runoffs Research Articles

Improving the precision of monthly runoff prediction using the combined non-stationary methods in an oasis irrigation area

The optimized agricultural water schedule and management, especially in the large irrigation district along the river basins, were closely related to the spatial and temporal runoff variations. However, the impacts of climate change and human activities leads to non-linear and non-stationary monthly runoffs. Under this condition, effectively capturing the variation of the runoff time series and improving the accuracy of the prediction model are of vital importance. However, some existing monthly data-driven prediction studies mainly focus on the model structure and calculation load, ignoring the influence of each frequency component of runoff and the fluctuation of runoff series caused by meteorological factors, which may not effectively capture the potential change process. In this paper, a novel method (CEEMD-MPE-EMD-GRU) for the non-stationary monthly runoff prediction was proposed. It fully took advantages of the complementary ensemble empirical mode decomposition (CEEMD), multi-scale permutation entropy (MPE), empirical mode decomposition (EMD) and gated recurrent unit (GRU). The combined model in general is a data-driven model, and compared with the traditional mechanism model, its most notable advantage is that it successfully overcomes the redundant information of the prediction model. In addition, atmospheric input factor analysis is added on the basis of fully decomposing and identifying non-stationary pseudo-components. The hydrological runoff data (1956–2014) obtained from the Manas River locating at Xinjiang, China were used for prediction. The results indicated that the new CEEMD-MPE-EMD-GRU model reached higher accuracy, as its Nash-Sutcliffe efficiency coefficient (0.960) was significantly larger than those of the GRU model (0.813) and the CEEMD-GRU model (0.889). Meanwhile, the root mean square error and the absolute relative error of the CEEMD-MPE-EMD-GRU model decreased to 0.279 and 0.195, respectively. The new runoff prediction model established in this paper would provide more precise evaluation of the monthly runoff prediction and better guidelines for high-efficiency agricultural water scheduling in the irrigation district.

Projecting Hydrological Responses to Climate Change Using CMIP6 Climate Scenarios for the Upper Huai River Basin, China

The influence of climate change on the regional hydrological cycle has been an international scientific issue that has attracted more attention in recent decades due to its huge effects on drought and flood. It is essential to investigate the change of regional hydrological characteristics in the context of global warming for developing flood mitigation and water utilization strategies in the future. The purpose of this study is to carry out a comprehensive analysis of changes in future runoff and flood for the upper Huai River basin by combining future climate scenarios, hydrological model, and flood frequency analysis. The daily bias correction (DBC) statistical downscaling method is used to downscale the global climate model (GCM) outputs from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and to generate future daily temperature and precipitation series. The Xinanjiang (XAJ) hydrological model is driven to project changes in future seasonal runoff under SSP245 and SSP585 scenarios for two future periods: 2050s (2031–2060) and 2080s (2071–2100) based on model calibration and validation. Finally, the peaks over threshold (POT) method and generalized Pareto (GP) distribution are combined to evaluate the changes of flood frequency for the upper Huai River basin. The results show that 1) GCMs project that there has been an insignificant increasing trend in future precipitation series, while an obvious increasing trend is detected in future temperature series; 2) average monthly runoffs in low-flow season have seen decreasing trends under SSP245 and SSP585 scenarios during the 2050s, while there has been an obvious increasing trend of average monthly runoff in high-flow season during the 2080s; 3) there is a decreasing trend in design floods below the 50-year return period under two future scenarios during the 2050s, while there has been an significant increasing trend in design flood during the 2080s in most cases and the amplitude of increase becomes larger for a larger return period. The study suggests that future flood will probably occur more frequently and an urgent need to develop appropriate adaptation measures to increase social resilience to warming climate over the upper Huai River basin.

Comparison between WEAP and SWAT models in a basin at Oaxaca, Mexico

La cuenca del río Sordo, localizada al oeste de Oaxaca, México, presenta problemas de erosión hídrica y pérdida de biodiversidad. El presente trabajo tiene como objetivo comparar los escurrimientos aforados en la estación Ixtayutla (20021) con valores simulados de los modelos WEAP (Water Evaluation And Planning System) y SWAT (Soil and Water Assessment Tool). Se procuró que WEAP, a través del método de la humedad del suelo, utilizara los mismos datos climáticos, de vegetación y suelos que SWAT; reportados para esta misma cuenca por Sánchez-Galindo et al. (2017). La comparación se basó en la eficiencia estadística de ambos modelos para simular los escurrimientos mensuales y anuales ocurridos durante el periodo 1975-1985. Se calcularon tres índices de eficiencia: el coeficiente de determinación (r2), Nash-Sutcliffe (NSE) y el sesgo porcentual (PBIAS). Con respecto a los escurrimientos mensuales aforados WEAP presentó un NSE = 0.73 (Bueno), un PBIAS = -16.05 (Satisfactorio) y una r2 = 0.84 mientras que SWAT, para ese mismo periodo, mostró un NSE = 0.82 (Muy bueno), un PBIAS = -15.92 (Satisfactorio) y una r2 = 0.85. Para los escurrimientos anuales SWAT y WEAP obtuvieron un NSE de 0.73 y 0.3, un r2 de 0.76 y 0.63 y un PBIAS de -4.65 y -16.23, respectivamente. Los dos modelos resultaron satisfactorios para simular escurrimientos mensuales por lo que la elección de uno u otro modelo dependerá de la problemática de la cuenca, los datos con que se cuente y los objetivos por cumplir.

Uncertainty in simulation of land-use change impacts on catchment runoff with multi-timescales based on the comparison of the HSPF and SWAT models

Hydrological modeling has provided key insights into the mechanisms of land-use change impacts on runoff. However, the uncertainty of this impact is poorly understood. This paper examines the uncertainty originated from hydrological models' parameters and structure in simulating hydrological responses to land use change on daily, monthly and annual time scales. Two hydrological models, SWAT and HSPF, were applied to simulate the runoff response in the Xitiaoxi basin of eastern China. The effects of three land use scenarios (in 1985, 2002 and 2014) were analyzed with respect to the expansion of urban areas and reduction of cropland and forests. The changes in streamflow with multi-timescales between two models were compared at the whole basin and the sub-basin scales. The parameter uncertainty was estimated based on a sequential uncertainty analysis method (SUFI-2). The results indicate that the two models (SWAT and HSPF) could reproduce the observed daily and seasonal flows well, but they cannot accurately reconstruct the extreme flows (such as annual 7-day minimum discharge, R_7dMIN). The effect of parameter uncertainty on streamflow varies over time scales. The simulated annual and monthly runoff change values show large discrepancies but with same trends. The simulated changes for annual maximum discharge (R_1dMAX) and R_7dMIN often show different signs. The average width of the predictive interval in the relative change of different flow characteristics exceeded 100% of the average relative changes for both models. HSPF tends to present larger relative changes for the annual and monthly runoffs compared to SWAT. Moreover, the model choice could affect the direction change in R_1dMAX and R_7dMIN. However, when land use change was significant to a certain degree, both models simulated increased R_1dMAX and decreased R_7dMIN, but with different significance levels. The study suggests that the model structure represents an additional uncertainty, which should be accounted for in the land-use change impact assessment.

Implications of Different DEMs on Watershed Runoffs Estimations

Watershed modelling tools like ArcSWAT, an ArcGIS extension of Soil and Water Assessment tool (SWAT), are useful to watershed managers in many ways. One particular use is analyzing model outputs for decision making related to waterway restoration and mitigation, which is often undertaken to improve water quality in streams. The present study evaluates the use of digital elevation model (DEM) at 10 meter, 30 meter, and 100 meter pixel size on non-point runoff predictions for three sub-watersheds in Raritan River Basin in New Jersey. These three watersheds include: Bound Brook, Lamington River, and Lawrence Brook watersheds. ArcSWAT is utilized to investigate the difference due to DEM variation in predicting monthly estimates of pollutant loads including ammonium (NH4), nitrite (NO2) and sediment transported with water out of a watershed. Using land use/cover, slope and soil data for 2012, monthly pollutant loads are calculated for each sub-basin in the watershed over a 10-year simulation period (2012-2022) in ArcSWAT. Overall statistical and spatial results show that ArcSWAT results are sensitive to changes in DEM pixel size for watershed modeling. The results show that total sum of monthly runoffs including NH4, NO2 and sediment differ among the three different DEMs. Moreover, the spatial pattern of input (in sub-catchments) also changes among the three DEMs for most watersheds. This indicates that watershed managers need to supplement model predictions with field measurements before making substantial investments in stream restoration programs.

Applicability evaluation of the SWIM at river basins of the black soil region in Northeast China: A case study of the upper and middle Wuyuer River basin

In this paper, we selected the middle and upper reaches of the Wuyuer River basin in the black soil region of Northeast China as the study area. We adopted the soil and water integrated model (SWIM) and evaluated the parameter sensitivity using partial correlation coefficient. We calibrated and validated our simulation results based on the daily runoff data from Yi’an hydrological station at the outlet of the river basin and the evaporation data recorded by various weather stations from 1961 to 1997. Following evaluation of the modeling data against the observed data, we present the applicability of SWIM in the river basin of the black soil region, and discuss the resulting errors and their probable causes. Results show that in the periods of calibration and validation, the Nash-Sutcliffe efficiency (NSE) coefficients of the monthly and daily runoffs were not less than 0.71 and 0.55, and the relative errors were less than 6.0%. Compared to daily runoffs, the simulation result of monthly runoffs was better. Additionally, the NSE coefficients of the potential monthly evaporation were not less than 0.81. Together, the results suggest that the calibrated SWIM can be utilized in various simulation analyses of runoffs on a monthly scale in the black soil region of Northeast China. On the contrary, the model had some limitations in simulating runoffs from snowmelt and frozen soil. Meanwhile, the stimulation data deviated from the measured data largely when applied to the years with spring and summer floods. The simulated annual runoffs were considerably higher than the measured data in the years with abrupt increases in annual precipitation. However, the model is capable of reproducing the changes in runoffs during flood seasons. In summary, this model can provide fundamental hydrological information for comprehensive management of the Wuyuer River basin water environment, and its application can be potentially extended to other river basins in the black soil region.

Long Term Evolution Characteristics of Runoffs in the Tideway of the Changjiang River

Abstract. Datong hydrological station is the last control station in the Changjiang River mainstream, and its runoffs have great significance on evolution of the tideway and the estuary of the Changjiang River. Therefore, this paper compiled long term series (1950~2010) of daily water discharges at Datong gauging station, and utilized the statistic methods to analyze the long term evolution characteristics of the Datong runoff. The results show that: (1) Inter-annual variability of runoffs was relatively stable, with average fluctuation range below 104m3/s, which may be caused by the location of the river basin and regulation of many large scale lakes; (2) The monthly runoffs have distinctly seasonal variation characteristics, wherein, the runoffs from June to September occupy 51% within a year, and the other months occupy the residual 49%, moreover, the runoff proportion of flood season within 2003~2010 has a slight decline of 2%, compared with that of 1995~2002.

Evaluation of anomalies in GLDAS-1996 dataset

Global Land Data Assimilation System (GLDAS) data are widely used for land-surface flux simulations. Therefore, the simulation accuracy using GLDAS dataset is largely contingent upon the accuracy of the GLDAS dataset. It is found that GLDAS land-surface model simulated runoff exhibits strong anomalies for 1996. These anomalies are investigated by evaluating four GLDAS meteorological forcing data (precipitation, air temperature, downward shortwave radiation and downward longwave radiation) in six large basins across the world (Danube, Mississippi, Yangtze, Congo, Amazon and Murray-Darling basins). Precipitation data from the Global Precipitation Climatology Centre (GPCC) are also compared with GLDAS forcing precipitation data. Large errors and lack of monthly variability in GLDAS-1996 precipitation data are the main sources for the anomalies in the simulated runoff. The impact of the precipitation data on simulated runoff for 1996 is investigated with the Community Atmosphere Biosphere Land Exchange (CABLE) land-surface model in the Yangtze basin, for which area high-quality local precipitation data are obtained from the China Meteorological Administration (CMA). The CABLE model is driven by GLDAS daily precipitation data and CMA daily precipitation, respectively. The simulated daily and monthly runoffs obtained from CMA data are noticeably better than those obtained from GLDAS data, suggesting that GLDAS-1996 precipitation data are not so reliable for land-surface flux simulations.

Runoff Fractal Dimension of Songhua River Basin in Harbin Station Based on Db4 Wavelet

The wavelet analysis and fractal theory into the analysis of hydrological time series, fluctuations in hydrological runoff sequence given the complexity of the measurement methods--- fractal dimension. The real monthly runoffs of 28 years from Songhua River basin in Harbin station are selected as research target. Wavelet transform combined with spectrum method is used to calculate the fractal dimension of runoff. Moreover, the result demonstrates that the runoff in Songhua River basin has the characteristic of self-similarity, and the complexity of runoff in the Songhua River basin in Harbin station is described quantificationally.

기후변화와 토지피복변화를 고려한 한강 유역의 수자원 영향 평가

최근 기후변화와 이상기후에 대한 관심으로 세계 각국에서는 미래 기후에 대한 보다 정확한 정보를 얻기 위하여 IPCC 권장 시나리오인 SRES (Special Report in Emission Scenario)기반의 GCM(General Circulation Model)과 RCM(Regional Circulation Model)을 이용하고 있으며 특히, 최근에는 고해상도 자료를 생산함으로써 국부지역에 대한 지형학적 특성을 효과적으로 모의할 수 있는 RCM모형을 이용한 연구가 활발히 진행되고 있다. 본 연구에서는 기후변화와 토지이용변화에 따른 미래 한강 유역의 수자원을 평가하기 위하여 다음의 과정을 진행하였다. CA-Markov Chain기법으로부터 토지이용변화를 추정하였으며 기온과 강수자료을 독립변수로 이용한 다중 회귀식으로부터 미래 NDVI를 추정하였다. 또한 기상청에서 제공하는 RegCM3 지역지후모형으로부터 축소기법을 이용하여 추정된 RegCM3 RCM 50 set의 기후변화 시나리오를 SLURP 모형에 입력하여 2001년부터 2090년까지 총 90년에 대한 한강 유역의 미래 유출모의를 실시하였다. 예측된 미래의 유출사상을 기반으로 각 댐별 과거와 미래 유출량을 월별로 비교하고 이들의 유황분석을 실시하였다. 최종 모의 지점으로 선택한 팔당댐에서 월단위 유출 모의 결과 8월 보다는 9월 유출량이 증가하는 결과를 보였고 이는 미래 강우 패턴의 변화에 기인한 것으로 판단되었다. 또한, 기후변화가 물 순환 구조에 미치는 영향을 검토한 결과 한강유역은 물 순환 요소(강수량, 증발량, 증산량, 유출량)의 변화에 의하여 수자원 관리 측면에서 어려움이 가중될 수 있음을 확인하였다. As climate changes and abnormal climates have drawn research interest recently, many countries utilize the GCM, which is based on SRES suggested by IPCC, to obtain more accurate forecast for future climate changes. Especially, many research attempts have been made to simulate localized geographical characteristics by using RCM with the high resolution data globally. To evaluate the impacts of climate and landuse change on water resources in the Han-river basin, we carried out the procedure consisting of the CA-Markov Chain, the Multi-Regression equation using two independent variables of temperature and rainfall, the downscaling technique based on the RegCM3 RCM, and SLURP. From the CA-Markov Chain, the future landuse change is forecasted and the future NDVI is predicted by the Multi-Regression equation. Also, RegCM3 RCM 50 sets were generated by the downscaling technique based on the RegCM3 RCM provided by KMA. With them, 90 year runoff scenarios whose period is from 2001 to 2090 are simulated for the Han-river basin by SLURP. Finally, the 90-year simulated monthly runoffs are compared with the historical monthly runoffs for each dam in the basin. At Paldang dam, the runoffs in September show higher increase than the ones in August which is due to the change of rainfall pattern in future. Additionally, after exploring the impact of the climate change on the structure of water circulation, we find that water management will become more difficult by the changes in the water circulation factors such as precipitation, evaporation, transpiration, and runoff in the Han-river basin.

APPLICABILITY OF ARTIFICIAL NEURAL NETWORK MODEL FOR SIMULATION OF MONTHLY RUNOFF IN COMPARISON WITH SOM OTHER TRADITIONAL MODELS

Artificial Neural Network (ANN) model along with Back Propagation Algorithm (BPA) has been applied in many fields, especially in hydrology and water resources management to simulate or forecast rainfall runoff process, discharge and water level - time series, and other hydrological variables. Several researches have recently been focusing to compare the applicability of ANN model with other theory-driven and data-driven approaches. The comparison of ANN with M5 model trees for rainfall-runoff forecasting, with ARMAX models for deriving flow series, with AR models and regression models for forecasting and estimating daily river flows have been carried out. The better results that were implemented by ANN model have been concluded. So, this research trend is continued for the comparison of ANN model with Tank, Harmonic, Thomas and Fiering models in simulation of the monthly runoffs at Dong Nai river basin, Viet Nam. The results proved ANN being the best choice among these models, if suitable and enough data sources were available.

River Regime Changes in the Upper Part of Khabour Catchment Area in North-Eastern Syria in the Second Half of XXth century – Part II: Mean Monthly Runoff

The paper deals with the changes in river regimes of the Khabour River and its tributaries in the Upper Jazirah region, most important Syrian cotton and wheat production area. The comparison of the mean monthly runoff distrubutions, coefficients of variation and asymmetry, distribution ofmaximums and sesonal distributions in the periods 1961-1981 and 1981-2000 showed significant changes. Beside significant lowering of mean monthly runoffs all year round, there are changes in the natural river regime, primarily in much lesser runoffs during the vegetation period. It is a consequence of an intense growth in agricultural water usage, mainly the use of ground-water, which lead to higher variability of runoffs.

최적선형보정을 이용한 앙상블 유량예측 시스템의 개선

일단위 강우-유출모형인 SSARR모형을 이용하여 한강, 낙동강, 섬진강유역에 월 앙상블 유량예측 시스템을 구축하였다. 우선 SSARR모형의 월 평균 유출량에 대한 모의정확성을 평가한 결과 한강과 낙동강유역에서는 과소추정하는 경향이 뚜렷하였으며, 섬진강유역에서는 모의오차의 분산이 커 정확성 개선이 필요하였다. 최적선형 보정기법을 적용하여 SSARR모형의 모의유량을 보정한 결과, 섬진강을 제외한 한강과 낙동강유역의 검증지점에서는 모의 정확성이 크게 개선되었다. 또한 1998년부터 2003년까지 월 앙상블 유량예측을 실시하여 예측 정확성을 평가하였다. 한강과 낙동강유역에서 최적선형 보정기법을 이용할 경우 앙상블 유량예측 정확성이 크게 개선되었으나, 섬진강유역은 개선효과가 미비하였다. A monthly Ensemble Streamflow Prediction (ESP) system was developed by applying a daily rainfall-runoff model known as the Streamflow Synthesis and Reservoir Regulation (SSARR) model to the Han, Nakdong, and Seomjin River basins in Korea. This study first assesses the accuracy of the averaged monthly runoffs simulated by SSARR for the 3 basins and proposes some improvements. The study found that the SSARR modeling of the Han and Nakdong River basins tended to significantly underestimate the actual runoff levels and the modeling of the Seomjin River basinshowed a large error variance. However, by implementing optimal linear correction (OLC), the accuracy of the SSARR model was considerably improved in predicting averaged monthly runoffs of the Han and Nakdong River basins. This improvement was not seen in the modeling of the Seomjin River basin. In addition, the ESP system was applied to forecast probabilistic runoff forecasts one month in advance for the 3 river basins from 1998 to 2003. Considerably improvement was also achieved with OLC in probabilistic forecasting accuracy for the Han and Nakdong River basins, but not in that of the Seomjin River basin.

Influence of the Amazon River runoff on the tropical atlantic

The Amazon river has the biggest flow in the world, 0.2 Sv (1 Sv = 106 m3/s), and is responsible for a large part of the low Sea Surface Salinity (SSS) in the west tropical Atlantic ocean. Very few Ocean General Circulation Model (OGCM) include runoff which brings a specific contribution to the Ocean physics. Comparison of simulations with constant or monthly runoffs shows that the spread of the Amazon fresh waters offshore of the north Brazilian coast is controlled by the ocean circulation and not by the Amazon flow. Therefore, in the model like in the observations, SSS minimum is observed in summer three months after the Amazon flood. In agreement with observations, a thick (more than 40 m) Barrier Layer (BL) is present every summer north of the Amazon mouth. Because of the strong and shallow salinity gradient associated with the Amazon freshwater, an important part of the solar radiation is trapped in the BL and creates an inversion of the vertical gradient of temperature. However with this forced model, BL does not seem to have a clear impact on SST and so on the air-sea interaction. Freshwater flux is also able to bend the sea surface. The geostrophic part of the North Brazilian Current (NBC) retroflection is then lightly weaker in presence of the Amazon runoff.