Discharge Values Research Articles

Evaluation of demographic/clinical features and hemorrhagic complications in patients with ischemic stroke who underwent reperfusion therapy.

The relationship between demographic/clinical characteristics, clinical outcomes and the development of hemorrhagic complications in patients with ischemic stroke who underwent reperfusion therapy has not been studied sufficiently. We have aimed to compare genders and age groups in terms of clinical features and outcome; and types of reperfusion treatments and clinical features regarding the development of hemorrhagic complications in patients with ischemic stroke who underwent recombinant tissue plasminogen activator (rtPA) and/or thrombectomy. Patients with acute ischemic stroke undergoing rtPA and/or thrombectomy were divided into six age groups. Parameters including hemorrhagic complications, anticoagulant and antiaggregant use, hyperlipidemia, smoking status, biochemical parameters, and comorbidities were documented. National Institutes of Health Stroke Scale (NIHSS) scores, modified Rankin Score (mRS) and Glasgow Coma Scale scores were recorded. Etiological classification of stroke was done. These parameters were compared in terms of age groups, genders, and hemorrhagic complications. Significant differences were found between age groups concerning hypertension, coronary artery disease, smoking status, and antiaggregant use. Rate of hemorrhagic complications in rtPA group was significantly lower when compared with other treatment groups. Hemorrhagic complications developed mostly in the rtPA+thrombectomy group. Among the patients who developed hemorrhagic complications, NIHSS scores on admission were found to be significantly lower in men than women. Admission, discharge, and 3rd month mRS values in men were significantly lower than those of women. Knowing demographic and clinical features of patients that may have an impact on the clinical course of ischemic stroke managed with reperfusion therapy will be useful in predicting the hemorrhagic complications and clinical outcomes.

Prediction of Peak Discharge Using the SCS Curve Number Method in the Manikin Watershed

Surface runoff is a crucial hydrological variable in the analysis of water infrastructure planning. A reliable method for predicting surface runoff resulting from rainfall in an ungauged watershed is the SCS CN method. This research aims to represent the effectiveness of the Curve Number (CN) method in calculating peak discharge in the Manikin Watershed. The data used for this analysis includes rainfall data from three rain stations, each with a 25-year dataset, water level data of 11 years, digital elevation model (DEM) data, land use maps, and hydrogeological maps. The SCS curve number method is the most commonly used method for the estimation of peak discharge in a watershed. The calculated flood discharge values for the Manikin River Basin, with return periods of 5, 10, 20, 25, 50, 100, 500, and 1000 years, are as follows: 60.32 m3/s, 84.74 m3/s, 111.98 m3/s, 121.41 m3/s, 153.25 m3/s, 188.79 m3/s, 287.24 m3/s, and 337.30 m3/s, respectively. The reliability testing of the method in the Manikin Watershed was determined by a Nash–Sutcliffe efficiencies (NSE) value of 0.93 and root mean square error (RMSE) value of 19.70. As a result, the Curve Number Method proves to be highly reliable in representing the peak discharge in the Manikin Watershed.

Evaluation of Hydraulic Structures for Agricultural Discharge Optimization

The objective of the research was to evaluate the hydraulic structures on the Al-Gharraf River in southern Iraq and their ability to achieve the required discharge for agricultural areas that depend on them. Al-Gharraf head regulator discharges unstable volumes of water, ranging from 280 m3/s in winter to 100 m3/s in summer. The research aimed to determine whether the operational discharges are achievable for the offtakes branching from the Al-Gharraf River when the river's discharge ranges from 60% to 100% of the operational discharge. The researchers utilized a simulation of the irrigation channel (SIC) model to simulate river flow. The researchers used hydraulic indicators such as Delivery Performance Ratio (DPR), Discharge Deviation (∆Q), and Sensitivity (S) to evaluate the work of the hydraulic structures (regulators), determine the more and less efficient regulators in delivering water to the offtakes, and determine the reasons for inefficiency. Depending on the discharge values for each offtake from simulation results by SIC and calculating the hydraulic indicators, it is observed that some offtakes exceed their operational discharges, such as Al-Zydia and Al-Sabila. Also, some offtakes do not receive their operational discharge (Al-Dawaiya, Shatt Al-Shatra, and Al-Basra) projects, which failed to reach even 10% of their operational discharges. The researchers suggest redesigning some offtakes and ensuring reasonable control of gate openings for other offtakes to make the water distribution proportional. Doi: 10.28991/CEJ-2024-010-05-010 Full Text: PDF

Spatial Sensitivity of River Flooding to Changes in Climate and Land Cover Through Explainable AI

AbstractExplaining the spatially variable impacts of flood‐generating mechanisms is a longstanding challenge in hydrology, with increasing and decreasing temporal flood trends often found in close regional proximity. Here, we develop a machine learning‐informed approach to unravel the drivers of seasonal flood magnitude and explain the spatial variability of their effects in a temperate climate. We employ 11 observed meteorological and land cover (LC) time series variables alongside 8 static catchment attributes to model flood magnitude in 1,268 catchments across Great Britain over four decades. We then perform a sensitivity analysis to assess how a 10% increase in precipitation, a 1°C rise in air temperature, or a 10 percentage point increase in urban or forest LC may affect flood magnitude in catchments with varying characteristics. Our simulations show that increasing precipitation and urbanization both tend to amplify flood magnitude significantly more in catchments with high baseflow contribution and low runoff ratio, which tend to have lower values of specific discharge on average. In contrast, rising air temperature (in the absence of changing precipitation) decreases flood magnitudes, with the largest effects in dry catchments with low baseflow index. Afforestation also tends to decrease floods more in catchments with low groundwater contribution, and in dry catchments in the summer. Our approach may be used to further disentangle the joint effects of multiple flood drivers in individual catchments.

Evaluation of contrast induced nephropathy related risk factors and long-term results.

We aimed to evaluate the frequency of contrast induced nephropathy (CIN), its relationship with accepted risk factors and long-term renal outcomes in patients who underwent coronary angiography (CAG). All patients who underwent CAG between April 2020 and April 2021 were retrospectively evaluated. CIN was defined as characteristic increase in serum creatinine after CAG. CIN developed in 50 (5.4%) of 934 patients. The CIN rate was found to be statistically significantly higher in patients with diabetes, hypertension, heart failure and those using diuretics. Pre-procedural hemoglobin, albumin and GFR were found to be independent risk factors for CIN. After discharge, the urea and creatinine values of the patients who developed CIN were significantly higher than those who did not. We concluded that in order to reduce the development of CIN, hemoglobin and albumin levels should be evaluated with renal functions before the procedure and they should be kept within normal limits.

Uncertainty Estimation in the Modeling of a Flood Wave Caused by a Dam Failure in a Hydropower System with Pumped Hydro Energy Storage

Future global sustainability depends heavily on the development of renewable energy. The object of this study is a system of two plants (Kaunas hydropower plant (HP) and Kruonis pumped-storage hydropower plant) and upper and lower reservoirs. A possible dam failure accident in such an important system can endanger the population of Kaunas City. The methodology for estimating dam-failure-induced flood wave uncertainty included scenarios of the upper reservoir embankment failure hydrographs, modeling flood wave spreading (MIKE 21 hydrodynamic model), and estimating wave heights. The GRS methodology was selected to assess the uncertainty of flood wave modeling results and the sensitivity of hydrodynamic model parameters. The findings revealed that the discharge values of the Nemunas inflow and outflow through the HP outlets are the most important parameters determining the greatest height of the flood wave. Therefore, by correctly managing the amount of water in the upper reservoir, it would be possible to prevent the lower reservoir dam from breaking.

An Investigation of Contaminant Transport and Retention from Storage Zone in Meandering Channels

Contaminant trapping by recirculation zones occurring at the apex of natural meandering channels induces a long tail in the contaminant cloud, thereby complicating the prediction of mixing behaviors. Thus, the understanding of the interaction between solute trapping and recirculating flow is important for responding to and mitigating water pollution accidents. In this research, the EFDC model was employed to reproduce three-dimensional flow structures of recirculating flow at the channel apex and investigate the influence on contaminant mixing. To investigate the contaminant transport characteristics from the storage zone in meandering channels, simulations were conducted using various discharge values to assess the impact of storage zone development on the concentration–time curves. The analysis of the relationship between the storage zone size and mixing behaviors indicates that an increase in discharge could result in a shorter tail and larger longitudinal dispersion even with the larger storage zone size. On the other hand, the enlarged recirculation zone size contributes to reducing transverse dispersion, evidenced by flatter dosage curves under lower flow rate conditions. These findings suggest that the increase in longitudinal dispersion with a larger flow rate is primarily caused by the reduction in transverse dispersion resulting from the formation of the recirculation zone.

Improved general unit hydrograph model for dam-break flood hydrograph

Dam breaks pose significant risks, necessitating simple and effective predictive models for disaster management. This study aims to enhance the understanding of dam-break flood hydrographs, an aspect less emphasized in traditional research focusing mainly on peak discharge and flow depth values. Employing a series of experiments, an improved general unit hydrograph model was used to analyze both discharge and flow depth hydrographs. This model is then critically compared with the standard gamma and log-normal asymmetric distribution models. The results reveal that the improved unit hydrograph model significantly outperforms these traditional models, particularly in predicting the rising stage of discharge hydrographs, evidenced by a 65 % reduction in root mean square error. Comparison of this model with real dam failures in natural river valleys shows its potential to be applied to changes in river slope and different dam-break rates. These advancements present a more precise methodology for predicting dam-break flood hydrographs, offering benefits for disaster management strategies.

On time-horizons based post-processing of flow forecasts

Post-processing raw stream flow forecasts are generally understood as estimating the univariate predictive density of stage or discharge values at selected future time steps, which is conditional on a single or multiple streamflow forecasts and observations up to the forecast start time to. The predictive density indicates to a forecaster in the most comprehensive way which flood level is likely to be expected. To this end, a variety of post-processing methods were proposed, which have respective strengths and weaknesses. These methods focus near-exclusively on the probabilistic forecast of the predictand at a single set future time ti, without addressing the predictive capability over the sequence of temporal sub-horizons (to, t1] ⊂ (to, t2] ⊂ … ⊂ (to, tk] nested into the overall forecast horizon. Here, we demonstrate the advantages of time-horizon dependent processing of streamflow forecasts, which evaluates the evolution of the predictive density over the sub-horizons by considering the temporal correlation among forecast ensemble members in addition to their cross-correlation with observations. The resulting probabilistic forecast consists of a multivariate distribution of stages and/or discharges at lagged forecasting times. These multivariate predictive distributions have the advantage of providing the likelihood of exceeding a critical threshold during the forecasting horizon while simultaneously offering valuable insights into the expected time of such exceedance. This approach supports not only decisions on issuing timely flood warnings but also the planing and roll-out of mitigating actions.

Climate variability and river flow changes in Wundanyi sub-catchment of Taita hills, Kenya

<p>Wundanyi sub-catchment of Taita hills is experiencing a high rate of deforestation due to the conversion of all its original forestland to agriculture and settlement during the last century. The landscape dynamics coupled with rainfall fluctuations in these critical ecosystems may significantly affect water resource distribution and food security in Taita Taveta County and its environs. This study aimed to establish the trends of selected hydroclimatic variables in Wundanyi sub-catchment from 1970 to 2030 and their specific and combined effects on surface runoff and streamflow in the same period. The analysis was based on statistical trend analysis and dynamic landscape modelling using both historical and primary hydroclimatic data from Wundanyi and Voi weather stations. Results show highly variable mean seasonal and annual values of temperature, rainfall, runoff and discharge in both Wundanyi and Voi weather stations. Increasing mean temperatures and rainfall were observed during the long dry season (JJAS), while decreasing seasonal discharges were observed during both the JJAS dry season and the OND short rainy season. These anomalies were pronounced in 1980–1981, 1986–1987 and 1992–1993, probably due to both global and local environmental changes affecting Taita Hills in general and Wundanyi sub-catchment in particular. The predicted effects of rainfall fluctuation were supported by declining surface runoff of 1.3% during JJAS, and an increase of 0.8% during the OND, with similar effects on river discharges. The combined effects of climate variability and Land use and cover changes (LUCC) on surface runoff were estimated to an increase of 200 mm during JJAS and 370 mm during OND, and while river discharges increased by 2.37 m<sup>3</sup>/s and 1.93 m<sup>3</sup>/s during JJAS and OND, respectively. Consequently, natural forest covers have significant control effects on surface runoff and can boost river discharges amid diverse agricultural cropping practices. Hence, crop diversification, agroforestry, and soil and water conservation structures are recommended to maintain effective control of LUCC on hydrological processes going on in Wundanyi sub-catchment.</p>

STRATEGI MITIGASI BANJIR BERDASARKAN KAPASITAS SALURAN DRAINASE DI KELURAHAN JAGALAN

<p><em>Flood mitigation is an important step in maintaining the sustainability and safety of urban environments. One key factor that affects the capacity of drainage channels is the flow rate of water through the channels. Therefore, this research aims to assess flood mitigation strategies based on the flow rate in drainage channels using the HSS SCS method. The study was conducted in Jagalan Sub-District, which frequently experiences flooding due to inadequate drainage channel capacity. The HSS SCS method was used to estimate the maximum flow rate that can be accommodated by the drainage channels. Hydrological and topographic data of the study area were collected and analyzed to identify relevant hydrological characteristics and physical parameters.</em></p><p><em>The analysis results showed the planned flood discharge values in Jagalan Sub-District through the Kali Boro Watershed, which were 3.1154 mm3/dt for a 2-year return period, 3.8297 mm3/dt for a 5-year return period, 4.3025 mm3/dt for a 10-year return period, and 4.7501 mm3/dt for a 20-year return period. The existing discharge values were 14.5243 mm3/dt for Surya Road, 19.1823 mm3/dt for Rejosari Road, 8.7376 mm3/dt for Kali Kepunton Road, 66.0338 mm3/dt for Kali Simpang Road, 21.7882 mm3/dt for Bororejo Road, and 42.2077 mm3/dt for Ir. Juanda Road. From these values, it can be concluded that the drainage channels in Jagalan Sub-District have sufficient capacity to accommodate the maximum flow rate during high-intensity rainfall. </em></p>

Rainfall–runoff modeling using an Adaptive Neuro-Fuzzy Inference System considering soil moisture for the Damanganga basin

ABSTRACT Rainfall is the major component of the hydrologic cycle and it is the primary source of runoff. The main purpose of this study was to estimate daily discharge by employing an Adaptive Neuro-Fuzzy Inference System (ANFIS) model using rainfall and soil moisture data at three different depths (5 cm, 100 cm and bedrock) for the Damanganga basin. The length of the data for the study period 1983–2022 is 39 years. The model employed nine membership functions for each variable of soil moisture, rainfall, discharge and 30 rules were optimized. The results were compared considering a range of model performance indicators as correlation coefficient (R2) and Nash–Sutcliffe efficiency (NSE) coefficient. The model application results shows that soil moisture at bedrock gives more precise value of daily discharge with (R2) and NSE value as 0.9936 and 0.9981, respectively, as compared to the soil moisture at depths of 5 and 100 cm. The better results obtained for the measurement of soil moisture in the deeper soil layer are consistent with the hydrological behavior anticipated for the analyzed catchment, where the root-zone soil layer is the driver of the runoff response rather than the surface observations. This study can be helpful to hydrologists in selecting appropriate rainfall–runoff models.

Flood Mapping Potential Areas Using HEC-RAS Software (Case Study: Kota Lama of Semarang)

Semarang has experienced floods every year, with a peak in the rainy season. At the end of 2022, there was heavy rain which caused the East Flood Canal River to overflow. As a result, the floods inundated several areas in Semarang City, including Kota Lama of Semarang. This study aims to determine the value of the designed discharge, the area of the flood inundation that occurred and the flood inundation map for return periods of 2, 5, 10, 25, 50 and 100 years. The methodology of this research consist of hydrological analysis, hydrological modelling with HEC-HMS and hydraulics modelling with HEC-RAS and integration with ArcGIS. In this study, it was found that for a return period of 2 years the planned flood discharge value was 153.7 m3/second with an inundation area of 406 Ha and a flood height of 17 cm to 68 cm, up to a return period of 100 years with a planned flood discharge value of 455.7 m3/second with an inundation area of 796 Ha and a flood height of 83 cm to 180 cm.

Water hammer mitigation by internal rubber hose

The aim of this research was to experimentally analyse the possibility of using a rubber hose placed inside a pipeline to mitigate the water hammer phenomenon. The experiments were conducted using a steel pipeline with an inner diameter of 53 mm and an EPDM rubber hose with a diameter of 6 mm. Hydraulic transients were induced by a rapid closure of the valve located at the downstream end of the pipeline system. In order to analyse the influence of steady-state flow conditions on the maximum pressure increase, measurements were carried out for different values of initial pressure and discharge. The experimental results indicate that placing a rubber hose inside a pipeline can substantially attenuate valve-induced pressure oscillations. It was observed that the initial pressure has a significant influence on the capacity of the rubber hose to dampen the water hammer phenomenon. Comparative numerical calculations were performed using the Brunone–Vitkovský instant acceleration-based model of unsteady friction. It was demonstrated that this approach does not allow satisfactory reproduction of the observed pressure oscillations due to the viscoelastic properties of the EPDM hose used in the tests.

Unveiling Torrential Flood Dynamics: A Comprehensive Study of Spatio-Temporal Patterns in the Šumadija Region, Serbia

This paper presents a comprehensive analysis of flood frequency and a spatio-temporal characterization of historical torrential floods in the Šumadija region using water discharge datasets and documented events. A chronology of 344 recorded torrential flood events, spanning from 1929 to 2020, illustrates the region’s vulnerability, with a death toll exceeding 43. The study defines the intra-annual primary and secondary peaks of torrential flood occurrences and explains their spatial distribution. Furthermore, the identification of suitable probability distribution functions underscores the necessity of tailored approaches for effective flood risk management in this diverse geographical environment. The study employed Flood Frequency Analysis (FFA) and goodness-of-fit tests, including the Kolmogorov–Smirnov (K-S) and Cramér–von Mises (CvM) tests, to assess the frequency and magnitude of flood events and evaluate diverse distribution functions. The main results include the identification of suitable probability distribution functions for each river within the region, emphasizing the need for tailored approaches in flood risk management. Additionally, discharge values for various return periods offer crucial insights for informed decision-making in flood risk management and infrastructure planning.

A hybrid self-adaptive DWT-WaveNet-LSTM deep learning architecture for karst spring forecasting

Karst spring discharge plays a vital role in understanding karst systems and managing karst groundwater resources. Due to its inherent heterogeneity and complexity, hydrological factors in the karst system often exhibit highly nonlinear and nonstationary characteristics. To overcome this challenge, a novel self-adaptive deep learning architecture is proposed to forecast daily karst spring runoff with precipitation in this study. The newly proposed model effectively integrates discrete wavelet transform (DWT), WaveNet, and long short-term memory (LSTM), enhanced by the attention mechanism and residual connections to learn underlying patterns, mitigate the overfitting risk, focus on the most relevant time steps, and improve the prediction accuracy. The framework is structured into two parts: one part is dedicated to predicting the karst spring discharge, whereas another part primarily predicts the residuals arising from the main predictions. By intergrading the two-part approach, the innovative model can adaptively correct the systematic errors and refine its understanding of some aspects that it might initially struggle with. The newly proposed model and three existing deep learning models including LSTM, GRU and simple RNN models are applied to predict karst spring discharge at Barton Springs, Texas, USA. The results imply that the newly developed DWT-WaveNet-LSTM model can leverage the advantages of various models, adapt to various aspects of the hydrometeorological data, and better capture intrinsic patterns from nonlinear and nonstationary input features. It outperforms other models at all time steps, evidenced by lower RMSE and higher NSE values. The residual analysis is conducted by comparing the predicted and observed spring discharge values. The self-adaptive DWT-WaveNet-LSTM model exhibits residuals that are closely centered around zero with a symmetrical, bell-shaped distribution, indicating superior performance and robust predictions in the karst system due to its effective capture of complex and nonlinear patterns.

Geneticizing input selection based advanced neural network model for sediment prediction in different climate zone

The study focuses on developing an accurate prediction model for suspended sediment load (SSL) based on antecedent SSL and water discharge values. Two Artificial Intelligence (AI) models, Hybrid and Parallel, were employed to test on the Kelantan and Mississippi Rivers in different climate zones and river sizes. The parallel model showed better performance than the hybrid in most cases, with the best results based on Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) (432.06 and 782.15 respectively) for Kelantan and (31672.25 and 62356.60 respectively) for Mississippi. The multifunctional GA neural-network model results have proven its ability to predict SSL in tropical and semi-arid zones. In the Kelantan River, the 8-input combination set was the best prediction model, showing an improvement of more than 38% compared to traditional models. The proposed method has proven to be more accurate than traditional models, ensuring better water resource planning, agricultural management and reservoir operation.

Analisis variasi pipa penstock terhadap kecepatan inlet turbin pada PLTMH Boonpring menggunakan CFD

The development of renewable energy is a necessity in order to reduce the consumption of fossil energy. One of the alternative technologies to obtain sustainable energy resources is to use a Micro Hydro Power Plant (PLTMH). In order to obtain high-efficiency power, it is necessary to analyze the maximum head and discharge values. In this study, an analysis of variations in the design of the penstock pipe from the forebay was carried out to obtain the highest velocity value for rotating the water turbine. The method used in this research is a simulation using ANSYS Fluent software. Based on the results obtained, the highest velocity values were obtained for penstock numbers 2 and 4. Pipe elevation causes the flow velocity to increase smoothly. The branching at the inlet does not affect the velocity value but increases the possibility of a vortex which is detrimental to the flow leading to the turbine.

Evolution of the Pingluo Section of the Upper Yellow River over the Past 50 Years: Responses to Environmental Change and Human Activity

The instability of the river channels has increased in response to the combined effects of global warming and human activity. This instability threatens the lives and property of people who live along river courses. This study takes the Pingluo section of the upper Yellow River, which is ~28 km long and ~400 m wide, as its research focus. We studied 11 periods of Landsat remote sensing images from 1973 to 2023 and analyzed the evolutionary characteristics of the Pingluo section over the past 50 years. The channel morphology indices included the channel braiding index (BIT), the bar braiding index (BIB), the average area of the bar (Ab), and the width of the wet channel area (BW). The results showed that there was an overall shrinking trend in this section of the Yellow River; more particularly, fluctuations in indicators such as the river width and the braiding index highlighted an increasing–decreasing–increasing pattern of change. During the 1973–1986 period, the river showed a widening trend, with narrow anabranches cutting through the floodplain and both the river width and the braiding index increasing dramatically over a short period. Over the 1986–2018 period, the area of the wet channel continued to shrink to its lowest level for the past 50 years, the river’s branches were diverted and abandoned, and the channel tended to straighten out. Between 2018 and 2023, the river showed a slightly expanding trend. The evolution of the river channel appears to be related to regional human activity and climate change. For example, after the joint filling of the Longyangxia and Liujiaxia reservoirs in the upper reaches of the Pingluo section of the Yellow River in 1986, runoff and sediment load along this section decreased, flood events became less frequent, and the channel tended to contract. In addition, the increase in extreme precipitation events over the last five years has led to an increase in the magnitude and frequency of peak discharge values in the region, which is the main reason for the increase in the river braiding index and area.

Validation of a new global irrigation scheme in the land surface model ORCHIDEE v2.2

Abstract. Irrigation activities are important for sustaining food production and account for 70 % of total global water withdrawals. In addition, due to increased evapotranspiration (ET) and changes in the leaf area index (LAI), these activities have an impact on hydrology and climate. In this paper, we present a new irrigation scheme within the land surface model ORCHIDEE (ORganising Carbon and Hydrology in Dynamic EcosystEms)). It restrains actual irrigation according to available freshwater by including a simple environmental limit and using allocation rules that depend on local infrastructure. We perform a simple sensitivity analysis and parameter tuning to set the parameter values and match the observed irrigation amounts against reported values, assuming uniform parameter values over land. Our scheme matches irrigation withdrawals amounts at global scale, but we identify some areas in India, China, and the USA (some of the most intensively irrigated regions worldwide), where irrigation is underestimated. In all irrigated areas, the scheme reduces the negative bias of ET. It also exacerbates the positive bias of the leaf area index (LAI), except for the very intensively irrigated areas, where irrigation reduces a negative LAI bias. The increase in the ET decreases river discharge values, in some cases significantly, although this does not necessarily lead to a better representation of discharge dynamics. Irrigation, however, does not have a large impact on the simulated total water storage anomalies (TWSAs) and its trends. This may be partly explained by the absence of nonrenewable groundwater use, and its inclusion could increase irrigation estimates in arid and semiarid regions by increasing the supply. Correlation of irrigation biases with landscape descriptors suggests that the inclusion of irrigated rice and dam management could improve the irrigation estimates as well. Regardless of this complexity, our results show that the new irrigation scheme helps simulate acceptable land surface conditions and fluxes in irrigated areas, which is important to explore the joint evolution of climate, water resources, and irrigation activities.