MIKE SHE Model Research Articles

Changes of blue and green water in arid inland dissipation area based on coupled surface water and groundwater model

Study regionThe Mainstream in the Tarim River Basin, Southern Xinjiang, China Study focusClimate change and human activities have significantly altered the water cycle, and water security evaluation and management are urgent. In arid and semi-arid areas, the assessment of blue and green water is particularly important. In this study, the MIKE SHE model is used to simulate the spatial and temporal changes of blue and green water resources in the mainstream of the Tarim River Basin (TRB) from 1990 to 2050 under land use and climate change conditions. The scarcity and vulnerability of blue-green water are introduced to evaluate the water security of the basin. The impacts of different land uses on blue-green water resources were also calculated according to the model zoning. New hydrological insights for the regionThe results indicate that from 1990 to 2050, blue water resources show a spatial pattern of gradual decrease from upstream to downstream. Compared to blue water, green water is dispersed more evenly over space. Future climatic scenarios will impact water security, as will changes in blue and green water security in terms of time and space. By comparing the influence of ecological water transport on the change of blue and green water before and after 2000, it was found that environmental water transport plays a certain role in improving the blue water scarcity in downstream of the TRB. The study is significant in maintaining regional water security and ecosystem stability.

Modeling streamflow responses to land use and land cover change using MIKE SHE model in the upper Omo Gibe catchment of Ethiopia

AbstractThe land use and land cover (LULC) changes in the upper Gibe catchment were studied intricately using the MIKE SHE model and analyzed through statistical tests. The Mann–Kendall test was used to identify potential trends, while the Pettit test was used to detect abrupt changes in rainfall, temperature, and streamflow. A set of three maps of LULC change (1990, 2003, and 2018) was developed to observe how they affect the hydrological pattern of the catchment. Statistical analyses were conducted at mean annual time scales to establish relationships among the anomalies. It has been noted that certain temperature gauges showed statistically significant increases in temperature. Change points in the 1980s and 1990s were identified during the study period. The annual streamflow trends displayed an increasing trend that was not that significant. LULC changes contributed to increased surface runoff, attributed to agricultural, settlement, and water body expansion, as well as reductions in bare land, forest, shrubland, and grassland. The MIKE SHE model performed well during both the calibration and validation periods on the monthly time scale. The alterations in LULC had a noticeable impact on stream flows during both wet and dry seasons, resulting in increased mean monthly stream flows during the wet season and decreased flows during the dry season. The MIKE SHE study and related statistical analysis is quite a different method to perceive the results.

EXPERIMENTAL RELATIONSHIP BETWEEN LAND USE/LAND COVER AND UNDERGROUND FLOW IN AL BA COMMUNE IN THE CENTRAL REGION OF VIETNAM

Rapid urbanization and intensive agricultural practices in Vietnam's Central Highlands have substantially transformed land use/land cover (LULC) patterns, with implications for groundwater resources necessitating measurement. The objective of this investigation is to examine the links between multi-temporal variations in LULC and changes in underground water flow in Al Ba Commune, Gia Lai Province. Supervised object-based classification of Landsat and Sentinel imagery from the past 25 years has produced consistent LULC maps as inputs for the model. Geospatial data of LULC, meteorological data, and in-situ data of groundwater flow (Q) were used to calibrate and validate the integrated hydrological MIKE SHE model and simulate past Q conditions for correlation analysis. With these data on LULC and groundwater flow, this study investigates the relationship between LULC changes and Q using Multivariate Linear Regression (MLR) and Ridge Regression models. The MLR model showed high R² (0.91) but positive impacts of all LULC classes on Q, contrary to expectations. Further analysis with Variance Inflation Factor (VIF) revealed multicollinearity among LULC variables, which was addressed using Ridge Regression with a bias factor to correct for this issue. The revised model demonstrated that non-vegetative covers negatively affect Q while vegetative covers have a positive impact. These results highlight the complex dynamics of LULC changes on groundwater resources, which can be detected by statistical approaches. The results of study could be important for sustainable land management.

MIKE 모델을 이용한 미계측 소유역의 강우유출 및 침수분석

Recently, due to the impact of climate change, many regions have experienced an increase in both the frequency and intensity of heavy rainfall events compared to the past. These heavy rainfall events increase the likelihood of flooding in downstream basins. To prevent flooding, it is necessary to calculate the appropriate design flood volume. When estimating the design flood volume, it is necessary to calculate the runoff in consideration of spatial distribution in ungauged basin. In this study, the runoff of the ungauged basin was calculated using the MIKE SHE model, and the flooding impact of the downstream area was analyzed using the MIKE 21 Flow Model. The study confirmed the runoff, downstream travel time, and flooding occurrence times based on rainfall events in the ungauged basin. It has been confirmed that when estimating the design flood volume, consideration must be given to intense rainfall occurring in a short period. This study can be utilized as one of the methods for calculating design flood volume and can be deemed to establish a disaster management system.

Assessing the Impacts of Future Climate and Land-Use Changes on Streamflow under Multiple Scenarios: A Case Study of the Upper Reaches of the Tarim River in Northwest China

Climate change and land use/cover change (LUCC) are two major factors that alter hydrological processes. The upper reaches of the Tarim River, situated in the northwest region of China, experience a dry and less rainy climate and are significantly influenced by human activities. This study comprehensively assessed the impacts of individual and combined climate changes and LUCCs on streamflow. Three general circulation models (GCMs) were utilized to predict future climate changes under three shared socioeconomic pathways (SSP119, SSP245, and SSP585). Cellular Automata–Markov (CA–Markov) was employed to predict future LUCC under three scenarios (i.e., ecological protection, historical trend, and farmland development). Streamflow for the period 2021–2050 was simulated using the calibrated MIKE SHE model with multiple scenarios. The results showed that from 2021 to 2050, increments in both average annual precipitation and average annual temperature under the three SSPs were predicted to lead to an increased streamflow. In comparison to the conditions observed in 2000, under three LUCC scenarios for 2030, the grassland area decreased by 1.04% to 1.21%, while the farmland area increased by 1.97% to 2.26%, resulting in reduced streamflow. The related changes analysis indicated that the variation in streamflow during winter is most significant, followed by spring. The study predicted that climate change would increase streamflow, while LUCC would decrease it. Due to the greater impact of LUCC, considering the combined effect of both factors, runoff would decrease. The contribution analysis indicated that climate change contributed between −7.16% and −18.66%, while LUCC contributed between 107.16% and 118.66%.

Spatial and temporal variability of saturated areas during rainfall-runoff events

Abstract Spatially distributed hydrological model Mike SHE was used as a diagnostic tool to provide information on possible overland flow source areas in the mountain catchment of Jalovecký Creek (area 22.2 km2, elevation range 820–2178 m a.s.l.) during different rainfall-runoff events. Selected events represented a sequence of several smaller, consecutive events, a flash flood event and two large events caused by frontal precipitation. Simulation of hourly runoff was better for runoff events caused by heavy rainfalls of longer duration than for the flash flood or consecutive smaller runoff events. Higher soil moisture was simulated near the streamflow network and larger possibly saturated areas were located mainly in the upper parts of mountain valleys. The most pronounced increase in the areal extent of possibly saturated areas (from 6.5% to 68.6% of the catchment area) was simulated for the event with high peak discharge divided by a short rainfall interruption. Rainfall depth exceeding 100 mm caused a large increase in the potentially saturated areas that covered subsequently half of the catchment area or more. A maximum integral connectivity scale representing the average distance over which individual pixels were connected varied for the selected events between 45 and 6327 m.

Advancing integrated river basin management and flood forecasting in the Cagne catchment: a combined approach using deterministic distributed models

Abstract To achieve an integrated river basin management for the Cagne catchment (France) and better predict floods, various modelling tools are integrated within a unified framework, forming a decision support system (DSS). In the paper, an integrated modeling approach employing deterministic distributed hydrological (MIKE SHE), hydraulic (MIKE 21 FM), and hydrogeological (FEFLOW) models is presented. The hydrological model was validated with recorded data and following a sensitivity analysis for optimizing grid resolution with 20 m. The hydraulic model based on MIKE 21 FM utilizes the results generated by the MIKE SHE model as boundary conditions, producing inundation maps for both normal and extreme periods. The hydrogeological model addresses the various complex relationships taking place within the catchment and was validated with piezometer data. The integration of these three models into a DSS provides a valuable tool for decision-makers to manage the Cagne catchment and the water-related issues more effectively during various hydrological situations. This comprehensive modelling framework underscores the importance of interdisciplinary approaches for addressing complex hydrological processes and contributes to improved flood management strategies in the catchment.

Mikecalsetup: an open-source python tool for automatically creating calibration setups of MIKE SHE models in PEST or OSTRICH

mikecalsetup: an open-source python tool for automatically creating calibration setups of MIKE SHE models in PEST or OSTRICH

Research on green water components and potential evaluation framework based on MIKE SHE model – A case study in the Loess Plateau of China

Exponentially increasing water demand and increasingly uncertain hydrological conditions due to climate change (CC) and land use/cover change (LUCC) undoubtedly pose significant challenges to the sustainability of water systems in arid and semi-arid regions worldwide, and even more so in the rain-fed agricultural area of the Loess Plateau (LP) in China, where green water supports all ecological landscapes and most agriculture. Therefore, an accurate assessment of green water resources is crucial for regional development. This paper constructed a comprehensive framework for assessing green water resources based on the MIKE SHE model, defined a new concept of green water components (GWCs) that can be extracted based on existing studies, proposes the potential of green water (GWP), and present a research methodology. To validate this research framework, we applied it to a typical basin in the LP gully area of the Nanxiaohegou (NXHG) basin. The model was calibrated using runoff data from basin outlet stations to extract four GWCs: high-efficiency green water (GWH), low-efficiency green water (GWL), unused green water (GWU), ineffective green water (GWI). We then assessed the GWP of the basin and analyzed its trends, consistency, and dependence on changing environments. The assessment framework is simple and easy to use, providing valuable information for regional revegetation and basin water management, and is highly recommended for replication in other regions.

Regulation of Flood Dynamics by a Check Dam System in a Typical Ecological Construction Watershed on the Loess Plateau, China

The check dam is the most important engineering measure in place for controlling water and preventing soil loss in the gully on the Loess Plateau. This study assesses Jiuyuangou, a typical governance watershed of the Loess Plateau, and studies the influence that the check dam system has on the dynamics of sub-storm floods over different return periods by coupling the one-dimensional hydrodynamic MIKE 11 model with the distributed hydrological MIKE SHE model. This research demonstrates the following: The check dam system significantly reduces a flood’s peak flow and total volume in the basin and also increases the flood duration. The former effects are greater than the latter effect. The flood peak’s rate of reduction, the flood volume’s rate of reduction and the flood duration’s rate of increase all increase linearly as the number of check dams increase. Of all dam systems, the check dam has the best linear response to a flood peak’s rate of reduction. The check dam system reduces the flow rate of flood runoff in the basin. After the dam is built, the average flow rate in the basin decreases by 54%. The runoff velocity of the flood is reduced by different degrees over different return periods and the average peak value decreases compared with a scenario lacking any kind of dam. The check dams have a greater impact on the runoff velocity over a shorter return period, with the velocity being 58.56% slower. Finally, the check dam system significantly reduces the intensity of erosion in the middle and lower reaches of the watershed, and it changes the distribution of the intensity compared to the original channel runoff. These findings are expected to provide a scientific basis for guiding the construction and high-quality development of check dams on the Loess Plateau. In addition, check dam construction in basins can trap water, sediment and nutrients, and it can also contribute to ecosystem diversity and maintaining ecosystem imbalances around the world.

Integrated modelling approach for flood forecasting in small Mediterranean catchment – Application to the Cagne Catchment, France

The French Mediterranean region is vulnerable to flooding caused by extreme rainstorm events. To better predict floods and anticipate consequences, the technical managing services operating on the field need to analyze the hydrological situation, receive accurate forecasts and issue alerts to the exposed population. Within this context, the various needed modelling tools are integrated within a common framework of a Decision Support System (DSS). This approach has been developed and implemented in the Cagne catchment located in the French Riviera. The Cagne catchment covers 96 km2 area and it is densely urbanized with high risks of inundation in the downstream area. The hydrological model MIKE SHE covers 96 km2 with a 20 m resolution. The river network is represented in a 1D MIKE 11 model by 18 branches and 1899 cross sections. The downstream area is covered with a high-resolution hydraulic model built with MIKE 21 FM. The model receives inputs from the hydrological model and can produce detailed inundation maps and forecasts. A major rainfall event observed from October to December 2020 is currently used as validation situation and the built modelling system has demonstrated its efficiency to reproduce the observed processes and to deliver the forecasts on due time.

Climate change as an environmental threat on the central plains of the Carpathian basin based on regional water balances

Climate change is an essential environmental challenge nowadays. Its effects are already being felt in multiple ways. In the future, we will also have to adapt to its effects because of our farming and our daily lives. In our research, we assessed the climate sensitivity of the lowland areas of Hungary through the changes in landscapes and the changes in groundwater resources that have the greatest impact on agriculture, using data from more than half of a century. We have quantified that at the mid-territory level (5-10 thousand km2) the groundwater resources show up to 3-5 km3/year changes in both positive and negative directions due to climatic effects. This significantly exceeds the anthropogenic water uses (the total water use of Hungary is about 5 km3 per year), so the effect of climate is the determining factor in the changes of regional water resources. Future changes in water circulation were modelled using the MIKE-SHE model in two micro-regions in Hungary. We have found that already at the level of the small catchments presented in our study, the water shortage increases by hundreds of millions of m3 per year due to the expected increase in temperature (mainly due to the increase in evapotranspiration), which cannot be compensated by current water supply solutions. Model simulations have confirmed previous results showing that groundwater movements play a very important role even in lowland landscapes. Based on our research, we would like to draw the attention of decision-makers and agricultural experts to the fact that current methods (irrigation, regional water transfers) are not sufficient for successful adaptation to climate change. So, it is not the limited precipitation but the inappropriate agricultural practices that cause a real threat in a changing climate. Based on our research, we have made a proposal for the adaptation of agriculture to climate change.

Sensitivity Analysis for Effect of Changes in Input Data on Hydrological Parameters and Water Balance Components in the Catchment Area of Hungarian Lowland

Abstract Extreme weather and climate changes are emerging more frequently in Central Europe, Hungary, and in the near future the increase in prolonged droughts, high-intensity precipitation events and the temporal variations of precipitation are expected, which may increase the magnitude of local water damages (OVF, 2016). As a result of climate change, these extreme weather events will be more frequent, however it is difficult to predict them, as until now insufficient amount of observations are available on smaller watercourses and on refined territorial water balances. For the future assessment of the environmental and economic impacts of climate change, it is essential to explore the integrated relationship of evapotranspiration, runoff, infiltration, surface and subsurface waters, and other hydrological processes, which can fundamentally describe regionally the water management conditions. In this research, an earlier study (DHI Hungary 2019) on the catchment area of the main canal of the Dong-ér Brook is pursued to continue the development of the MIKE SHE model in a more complex manner. Within the frame of the present study, the relationship between the individual hydrological parameters, the water balance components and extreme precipitation events (drought, heavy rainfall events) for the entire drainage basin have been examined, besides, the expected effects of the predicted temperature rise on the water balance is evaluated. Using data from 2018 as reference, the sensitivity of the changes in daily precipitation and daily mean temperature has been assessed to estimate the effects of the future climate change on hydrological parameters and water balance components.

Characterizing distributed hydrological model residual errors using a probabilistic long short-term memory network

Errors in hydrological simulations have impacted their applications in flood prediction and water resources management. Properly characterizing the properties of errors such as heteroscedasticity and autocorrelation can provide improved hydrological predictions. Here, we present a probabilistic Long Short-Term Memory (LSTM) network for modeling hydrological residual errors. Three steps are undertaken to characterize uncertainty using the LSTM: (i) the network is trained with gradient optimization to obtain optimal predictions; (ii) the distribution of the errors for optimal predictions are estimated using a Bayesian Markov chain Monte Carlo (MCMC) algorithm; (iii) probabilistic predictions are made using the inferred error distribution and optimal predictions. We examine the model in the source of Yellow River, China over the period 1992–2015. A distributed hydrological model MIKE SHE is applied to simulate streamflows in the catchment. As benchmarks, we compare the results with a Bayesian linear regression model and a traditional probabilistic residual error model. Results show the probabilistic LSTM network reduces the heteroscedasticity and removes almost all autocorrelations in residual errors. Besides, compared with the other two methods, the proposed method produces more than 50% narrower uncertainty intervals with the best probability coverage. Our results highlight the potential ability of a deep learning approach integrated with a hydrological model to better characterize predictive uncertainty in hydrologic modeling.

Hydrological simulation of the Jialing River Basin using the MIKE SHE model in changing climate

Abstract Climate change and human activities have an important impact on the changing environment, leading to significant changes in the basin water cycle process. The Jialing River Basin, the largest tributary of the upper Yangtze River, is selected as the study area. Three different rainfall datasets, the China Meteorological Assimilation Driving (CMAD) dataset, the Tropical Rainfall Measuring Mission data, and gauged observation data, were used as inputs for the MIKE System Hydrological European (MIKE SHE) model. By comparing the simulation results driven by various meteorological data, the applicability of the MIKE SHE model at four stations is evaluated, and the sensitivity and uncertainty of model parameters are analyzed. Meanwhile, the impact of large hydropower stations on the runoff of the Jialing River Basin is assessed, and the influence of human activities on the runoff change is determined. The future climate change of the watershed was analyzed by using the typical representative concentration pathway (RCP) 4.5 and RCP8.5 climate scenarios. Based on the MIKE SHE model, the runoff of the Jialing River Basin in the future climate scenario is predicted, and the corresponding response of the Jialing River Basin is analyzed quantitatively. The results show that the CMAD data-driven model has better Nash–Sutcliffe efficiency and correlation coefficient for each period. By analyzing the influence of the hydropower station on the runoff process at the outlet of the basin, it is found that the hydropower station has a certain regulating effect on the runoff process at the outlet of the basin. In addition, the RCP4.5 scenario is more consistent with the future scenario, indicating that the Jialing River Basin will become colder and drier.

A review of the current state of process-based and data-driven modelling: guidelines for Lake Erie managers and watershed modellers

Elevated phosphorus (P) loading from the watersheds draining into Lake Erie, particularly from agricultural (53%) and urban (43%) sources, is identified as one of the main drivers of the severe eutrophication. In this study, we present a comprehensive evaluation of 11 process-based models to characterize the water cycle as well as nutrient fate and transport within a watershed context, and to find a robust and replicable way to optimize the modelling strategy for the Lake Erie watershed. Our primary objective is to review the conceptual/technical strengths and weaknesses of the individual models for reproducing surface runoff, groundwater, sediment transport, nutrient cycling, and channel routing, and to collectively guide the management of the Lake Erie Basin. Our analysis suggested that the available models either opted for simpler approximations of the multifaceted, nonlinear dynamics of nutrient fate and transport, and instead placed more emphasis on the advanced representation of the water cycle or, introduced a greater degree of biogeochemical complexity but simplified their strategies to recreate the roles of critical hydrological processes. Notwithstanding its overparameterization problem, the MIKE SHE model provides the most comprehensive 3D representation of the interplay between surface and subsurface hydrological processes with a fully dynamic description, whereby we can recreate the solute transport that infiltrates from the surface to the unsaturated soil layer and subsequently percolates into the saturated layer. Likewise, the physically based submodels designed to represent the sediment detachment and erosion/removal processes (DWSM, HBV-INCA, HSPF, HYPE, and MIKE SHE), offer a distinct alternative to USLE-type empirical strategies. The ability to explicitly simulate the daily plant growth (SWAT and APEX) coupled with a dynamic representation of soil P processes can be critical when evaluating the long-term watershed responses to various agricultural management strategies. Drawing parallels with the (sub)surface and sediment erosion processes, a more complicated physically based approach, e.g., the dynamic wave model provided by MIKE SHE (coupled with MIKE URBAN or MIKE HYDRO) and SWMM may be more appropriate for realistically simulating the pressurized flow and backwater effects of water routing in both open channels and closed pipes. While our propositions seem to favor the consideration of complex models that may lack the commensurate knowledge to properly characterize the underlying processes, we contend this issue can be counterbalanced by the joint consideration of simpler empirical models under an ensemble framework, which can both constrain the plausible values of individual processes and validate macroscale patterns. Finally, our study discusses critical facets of the watershed modelling work in Lake Erie, such as the role of legacy P, the challenges in reproducing spring-freshet or event-flow conditions, and the dynamic characterization of water/nutrient cycles under the nonstationarity of a changing climate.

Runoff responses to climate change in China's Buyuan River Basin

AbstractClimate change has affected the dynamics of the water cycle and its consequent effects on water resources in many regions. The Buyuan River, the largest tributary of the Upper Mekong River, is one of the regions with the strongest climate change in the Mekong River Basin, and its cross‐border impact on water resources has received increasing attention. However, few studies have focused on the runoff responses to future climate change in the Buyuan River Basin (BRB). In this study, the MIKE SHE model was applied to estimate the runoff of the BRB, based on climate‐change scenarios from the Beijing Climate Center Climate System Model (BCC‐CSM1‐1) under two Representative Concentration Pathways (RCPs). The simulations predicted a slight decrease in the mean annual runoff of the BRB under the RCP4.5 and RCP8.5 scenarios (2020–2049) compared with the reference period (1959–2012), with an increase in the magnitude of inter‐annual variation, leading to increased deficit and surplus during dry and wet years. The simulations predicted the earlier maximum monthly runoff and a more evenly distributed annual distribution of the runoff under RCP4.5 and RCP8.5 scenarios as compared to the reference period. The arrival of the flood season in the BRB was advanced by a month under future climate‐change scenarios. The results showed that the average annual runoff of the BRB does not change significantly under future climate‐change scenarios. However, there are obvious changes in the inter‐annual and intra‐annual distribution of the runoff.

Impact of sedimentation by check dam on the hydrodynamics in the channel on the Loess Plateau of China

The sedimentation by check dam in the channel affects hydrological process. In this study, the effects of the sedimentation on the dynamic process of runoff and erosion power were investigated by dynamic coupling models (MIKE SHE model and MIKE 11 model). The study area was located in Wangmaogou watershed in the Loess Plateau of China. Four scenarios including no check dam and check dam with siltation depths of 0, 4 and 8 m were designed to study the reduction effectiveness of check dam on the hydrodynamic processes. The research showed that the silt dam not only reduced the total volume flow rate of floods but also increased the flood duration and delayed the occurrence of flood peaks. The siltation depths of the dam influenced the flow velocity and runoff shear stress. With deposition, the channel was longer in 8 m siltation compared with 0 and 4 m siltation. The shear force and unit runoff power were remarkably reduced in the scenario of 8 m siltation, followed by 4 m, and lastly by 0 m. The dam system can still vastly reduce the flow velocity along the channel in the full state and decrease the maximum flow velocity along the channel by more than 50%. The decrease in flow velocity was the main reason for the decrease in the sediment-carrying capacity of the runoff, which directly reduced the runoff erosion intensity. This study provides the scientific basis for understanding the regulation of check dam and sedimentation on hydrological process.

Flood Simulation Analysis of the Biliu River Basin Based on the MIKE Model

The Biliu River is the largest river in Dalian. The occurrence of floods and droughts in this basin has extremely important impacts on local industry, agriculture, and urban development. For a long time, the annual distribution of precipitation in the Biliu River Basin is extremely uneven, the river runoff varies greatly from year to year and season to year, floods and droughts occur frequently, and serious soil erosion results in fragile ecological environment and severe shortage of water resources. In this paper, the spatial and temporal changes of rainfall and runoff in the Biliu River Basin are studied through the coupling of the MIKE 11 model and the MIKE SHE model. The hydrological changes in the Biliu River Basin are simulated. The coupled model is verified by monthly runoff data from 1996 to 2015, and the simulation values are found to be true. The values match well. Based on the cyclical pattern of precipitation and runoff in the Biliu River Basin, the rainfall and runoff data in the Biliu River Basin from 2016 to 2030 are derived. The MIKE SHE/MIKE 11 coupling model is used to predict the Biliu River from 2016 to 2030. The results show that flood disasters are expected to occur in August 2020, July 2025, and July 2030, which can provide a basis for hydrological management in the Biliu River Basin.

Impact of land use/land cover change on stream flow in the Shaya catchment of Ethiopia using the MIKE SHE model

The impact of land use/land cover (LULC) change on the stream flow of the Shaya catchment was assessed by employing the MIKE SHE hydrological model. The digital elevation model, soil, LULC, climate, and stream flow data were used as model inputs. The LULC was analyzed from different years of satellite imageries using ERDAS IMAGINE software package and its accuracy was verified following the standard procedures. Trend and shift detection analysis were also conducted to study the effect of rainfall on stream flow using the Mann–Kendall (MK) and Pettit tests, respectively. The result showed that there is a significant expansion of settlement and agricultural area, while there was a decrease of bare land, forest, and bush land in the catchment. In contrary, rangeland was increased from the year 1987 to 2000 and then decreased from 2000 to 2015. The performance of the MIKE SHE hydrological model was very good both during model calibration and validation periods. It has been observed that rainfall did not show any significant trends and shifts, but the stream flow was increased significantly in the two decades. In this study, the effects of LULC change on the stream flow in the study area have been distinguished: the mean monthly stream flow was increased during the wet season, while it was decreased during the dry season. Therefore, we recommend concerned bodies to monitor and take appropriate control of the LULC changes, especially settlement and deforestation, before it makes acute problems of the hydrologic imbalance in the catchment.