Effects of land-use pattern change on rainfall-runoff and runoff-sediment relations:a case study in Zichang watershed of the Loess Plateau of China

The purpose of this article is to identify the effect of land use pattern on rainfall runoff and runoff sediment relations in Zichang Watershed of the Loess Plateau. From 1986 to 1997, many farmlands changed into grassland or woodland, especially the farmland in steep slope positions or far away from the river. The change of land use pattern altered the rainfall runoff and runoff sediment relationships, and led to higher slope of trend curves(STCs) of annual rainfall runoff mass curve and runoff sediment mass curve in 1990s than that in 1980s. It is implied that more soil and water loss yielded in 1990s. In order to reduce soil loss, more attentions should be paid to land use pattern and some grass or other herbaceous filter strips should be built along rivers.

A Study of Rainfall-Runoff Response in a Catchment Using TOPMODEL

The simplicity of Topography-based hydrological model (TOPMODEL), as a way of reflecting the topographic controls on soil water storage and runoff generation, has become more attractive and more popular for land surface process study since digital elevation models (DEMs) have become widely available. In this paper, the effect of the topography index on soil water storage distribution, which is the key to TOPMODEL, is explained. Then a simple water cycle model for estimating other components of the surface water cycle is developed, which is implemented into the TOPMODEL to integrate the water cycle of the catchment. Using the output of a DEM from 100 m×100 m resolution data and a single flow direction algorithm, the index distribution function is calculated for a catchment (around 2500 km2 )in the upper reaches of the Yangtze River under different channel initiation thresholds. Finally, the daily and monthly rainfall-runoff response from 1960 to 1987 for the catchment is simulated with the TOPMODEL coupled with the simple water cycle model.

Determination of Nutrient Concentrations in Simulated Rainfall-Runoff from Poultry House Dust Deposited Adjacent to Exhaust Fans

Until recently, little attention has been given to the loss of nutrients that may occur in stormwater runoff from poultry houses. Dust emitted from poultry house fans and deposited near the fans has been shown to contain similar amounts of phosphorus (P) and nitrogen (N) as in poultry litter, thus, there is need for information on the potential of runoff to transport deposited dust off-site. The objectives of this study are to quantify P and N in simulated rainfall-runoff from sites immediately adjacent to fans (sidewall and tunnel) from a commercial poultry house in northwest Arkansas. Runoff from fan plots range in total P (TP) and total N (TN) concentration from 1.0 to 26.0 mg·L-1 and from 5.1 to 189 mg·L-1. The concentration of P and N in runoff from plots adjacent to sidewall fans is significantly lower (P < 0.05) during warmer (June to August;1 and 2 mg·L-1 for TP and TN, respectively) than cooler months (November through March;3 and 7 mg·L-1 for TP and TN, respectively). In contrast, TP and TN concentrations of runoff from tunnel fan plots are significantly greater (P < 0.05) during warm (14 and 170 mg·L-1, respectively) than cool months (5 and 60 mg·L-1, respectively). The results of this research indicate that conservation practices are needed around poultry production houses to minimize the potential for runoff of nutrients in emitted dust entering nearby surface waters.

Rainfall-runoff simulation and flood forecasting for Huaihe Basin

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

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

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

The changes in the annual distribution of mountain runoff during the period of 1965-2018 in Hexi Corridor,Northwest China

The annual distribution characteristics of river runoff in arid regions have significant implications for water resource stability and management.Based on the mountain runoff data from 1965 to 2018,this study examines the annual change characteristics of monthly runoff of the Shiyang River Basin,Heihe River Basin,and Shule River Basin in the Hexi Corridor,Northwest China.Many indexes are used and analyzed,including the coefficient of variance,the complete regulation coefficient,the concentration degree and concentration period,the magnitude of change,the skewness coefficient,and the kurtosis coefficient of the annual distribution curves.The results reveal the following:(1)The inhomogeneity of annual runoff distribution in the Taolai River and the rivers to the west of it,except the Shiyou River,show an increasing trend.Conversely,the inhomogeneity of the rivers to the east of the Taolai River generally show a downward trend,but the coefficient of variance value is still very high.(2)In the Shiyang River Basin,the annual distribution of the concentration period is characterized by a relatively discrete pattern.Conversely,the Heihe River Basin exhibits a relatively concentrated pattern,and the distribution pattern of the Shule River Basin is quite different.Notably,all concentration periods in the three basins have shifted backward after the 2000s.(3)The Shiyang River Basin exhibits disordered annual distribution curves of runoff in different years.In contrast,the Heihe River Basin presents a typical‘single-peak’pattern with a prominent right-skewed.The Shule River Basin has regular distribution curves,with a gradually significant‘double-peak’pattern from east to west.Overall,there has been a slight change in runoff in the Shiyang River Basin,while the Heihe River Basin and Shule River Basin have experienced significant increases in runoff.The annual distribution curves of runoff in the Liyuan River and the rivers to the east of it exhibit a gentle peak pattern,and the appearance probability of extreme runoff during the year is low.Conversely,the rivers to the west of the Liyuan River,excluding the Danghe River,display a sharp peak and thick tail pattern,indicating that the appearance probability of extreme runoff during the year is high.These findings have practical implications for the planning and management of water resources in the Hexi Corridor.Moreover,they provide a solid foundation for predicting future changes in regional water resources.

Rainfall-runoff modeling for storm events in a coastal forest catchmen t using neural networks

The process of transformation of rainfall into runoff over a catchment is very complex and highly nonlinear and exhibits both tempor al and spatial variabilities. In this article, a rainfall-runoff model using th e artificial neural networks (ANN) is proposed for simula ting the runoff in storm events. The study uses the data from a coa stal forest catchment located in Seto Inland Sea, Japan. This article studies the accuracy of the short-term rainfall forecast obta ined by ANN time-series analysis techniques and using antecedent rainfa ll depths and stream flow as the input information. The verification results from the proposed model indicate that the approach of ANN rai nfall-runoff model presented in this paper shows a reasonable agreement in rainfall-runoff modeling with high accuracy.

Straw mulching alters the composition and loss of dissolved organic matter in farmland surface runoff by inhibiting the fragmentation of soil small macroaggregates

Straw mulching is a widespread practice for reducing the soil carbon loss caused by erosion.However,the effects of straw mulching on dissolved organic matter(DOM)runoff loss from black soil are not well studied.How straw mulching affects the composition and loss of runoff DOM by changing soil aggregates remains largely unclear.Here,a straw mulching treatment was compared to a no mulching treatment(as a control)on sloping farmland with black soil erosion in Northeast China.We divided the soil into large macroaggregates(>2 mm),small macroaggregates(0.25-2 mm),and microaggregates(<0.25 mm).After five rain events,the effects of straw mulching on the concentration(characterized by dissolved organic carbon(DoC)and composition(analyzed by fluorescence spectroscopy)of runoff and soil aggregate DOM were studied.The results showed that straw mulching reduced the runoff amount by 54.7%.Therefore,although straw mulching increased the average DOc concentration in runoff,it reduced the total runoff DOM loss by 48.3%.The composition of runoff DOM is similar to that of soil,as both contain humic-like acid and protein-like components.With straw mulching treatment,the protein-like components in small macroaggregates accumulated and the protein-like components in runoff declined with rain events.Fluorescence spectroscopy technology may help in understanding the hydrological paths of rain events by capturing the dynamic changes of runoff and soil DOM characteristics.A variation partitioning analysis(VPA)indicated that the DOM concentration and composition of microaggregates explained 68.2%of the change in runoff DOM from no mulching plots,while the change in runoff DOM from straw mulching plots was dominated by small macroaggregates at a rate of 55.1%.Taken together,our results demonstrated that straw mulching reduces the fragmentation of small macroaggregates and the loss of microaggregates,thus effecting DOM compositions in soil and reducing the DOM loss in runoff.These results provide a theoretical basis for reducing carbon loss in sloping farmland.

Assessment of runoff changes in the sub-basin of the upper reaches of the Yangtze River basin, China based on multiple methods

Quantitative assessment of the impact of climate variability and human activities on runoff plays a pivotal role in water resource management and maintaining ecosystem integrity.This study considered six sub-basins in the upper reaches of the Yangtze River basin,China,to reveal the trend of the runoff evolution and clarify the driving factors of the changes during 1956–2020.Linear regression,Mann-Kendall test,and sliding t-test were used to study the trend of the hydrometeorological elements,while cumulative distance level and ordered clustering methods were applied to identify mutation points.The contributions of climate change and human disturbance to runoff changes were quantitatively assessed using three methods,i.e.,the rainfall-runoff relationship method,slope variation method,and variable infiltration capacity(Budyko)hypothesis method.Then,the availability and stability of the three methods were compared.The results showed that the runoff in the upper reaches of the Yangtze River basin exhibited a decreasing trend from 1956 to 2020,with an abrupt change in 1985.For attribution analysis,the runoff series could be divided into two phases,i.e.,1961–1985(baseline period)and 1986–2020(changing period);and it was found that the rainfall-runoff relationship method with precipitation as the representative of climate factors had limited usability compared with the other two methods,while the slope variation and Budyko hypothesis methods had highly consistent results.Different factors showed different effects in the sub-basins of the upper reaches of the Yangtze River basin.Moreover,human disturbance was the main factor that contributed to the runoff changes,accounting for 53.0%–82.0%;and the contribution of climate factors to the runoff change was 17.0%–47.0%,making it the secondary factor,in which precipitation was the most representative climate factor.These results provide insights into how climate and anthropogenic changes synergistically influence the runoff of the upper reaches of the Yangtze River basin.

Responses of runoff to changes in climate and human activities in the Liuhe River Basin, China

Since the 1950s,numerous soil and water conservation measures have been implemented to control severe soil erosion in the Liuhe River Basin(LRB),China.While these measures have protected the upstream soil and water ecological environment,they have led to a sharp reduction in the downstream flow and the deterioration of the river ecological environment.Therefore,it is important to evaluate the impact of soil and water conservation measures on hydrological processes to assess long-term runoff changes.Using the Soil and Water Assessment Tool(SWAT)models and sensitivity analyses based on the Budyko hypothesis,this study quantitatively evaluated the effects of climate change,direct water withdrawal,and soil and water conservation measures on runoff in the LRB during different periods,including different responses to runoff discharge,hydrological regime,and flood processes.The runoff series were divided into a baseline period(1956-1969)and two altered periods,i.e.,period 1(1970-1999)and period 2(2000-2020).Human activities were the main cause of the decrease in runoff during the altered periods,contributing 86.03%(-29.61 mm),while the contribution of climate change was only 13.70%(-4.70 mm).The impact of climate change manifests as a decrease in flood volume caused by a reduction in precipitation during the flood season.Analysis of two flood cases indicated a 66.00%-84.00%reduction in basin runoff capacity due to soil and water conservation measures in the upstream area.Soil and water conservation measures reduced the peak flow and total flood volume in the upstream runoff area by 77.98%and 55.16%,respectively,even with nearly double the precipitation.The runoff coefficient in the reservoir area without soil and water conservation measures was 4.0 times that in the conservation area.These results contribute to the re-evaluation of soil and water conservation hydrological effects and provide important guidance for water resource planning and water conservation policy formulation in the LRB.

Runoff change in the Yellow River Basin of China from 1960 to 2020 and its driving factors

Analysing runoff changes and how these are affected by climate change and human activities is deemed crucial to elucidate the ecological and hydrological response mechanisms of rivers.The Indicators of Hydrologic Alteration and the Range of Variability Approach(IHA-RVA)method,as well as the ecological indicator method,were employed to quantitatively assess the degree of hydrologic change and ecological response processes in the Yellow River Basin from 1960 to 2020.Using Budyko's water heat coupling balance theory,the relative contributions of various driving factors(such as precipitation,potential evapotranspiration,and underlying surface)to runoff changes in the Yellow River Basin were quantitatively evaluated.The results show that the annual average runoff and precipitation in the Yellow River Basin had a downwards trend,whereas the potential evapotranspiration exhibited an upwards trend from 1960 to 2020.In approximately 1985,it was reported that the hydrological regime of the main stream underwent an abrupt change.The degree of hydrological change was observed to gradually increase from upstream to downstream,with a range of 34.00%-54.00%,all of which are moderate changes.However,significant differences have been noted among different ecological indicators,with a fluctuation index of 90.00%at the outlet of downstream hydrological stations,reaching a high level of change.After the mutation,the biodiversity index of flow in the middle and lower reaches of the Yellow River was generally lower than that in the base period.The research results also indicate that the driving factor for runoff changes in the upper reach of the Yellow River Basin is mainly precipitation,with a contribution rate of 39.31%-54.70%.Moreover,the driving factor for runoff changes in the middle and lower reaches is mainly human activities,having a contribution rate of 63.70%-84.37%.These results can serve as a basis to strengthen the protection and restoration efforts in the Yellow River Basin and further promote the rational development and use of water resources in the Yellow River.

Glacier area change and its impact on runoff in the Manas River Basin,Northwest China from 2000 to 2020

Understanding the distribution and dynamics of glaciers is of great significance to the management and allocation of regional water resources and socio-economic development in arid regions of Northwest China.In this study,based on 36 Landsat images,we extracted the glacier boundaries in the Manas River Basin,Northwest China from 2000 to 2020 using eCognition combined with band operation,GIS(geographic information system)spatial overlay techniques,and manual visual interpretation.We further analyzed the distribution and variation characteristics of glacier area,and simulated glacial runoff using a distributed degree-day model to explore the regulation of runoff recharge.The results showed that glacier area in the Manas River Basin as a whole showed a downward trend over the past 21 a,with a decrease of 10.86%and an average change rate of–0.54%/a.With the increase in glacier scale,the number of smaller glaciers decreased exponentially,and the number and area of larger glaciers were relatively stable.Glacier area showed a normal distribution trend of increasing first and then decreasing with elevation.About 97.92%of glaciers were distributed at 3700–4800 m,and 48.11%of glaciers were observed on the northern and northeastern slopes.The retreat rate of glaciers was the fastest(68.82%)at elevations below 3800 m.There was a clear rise in elevation at the end of glaciers.Glaciers at different slope directions showed a rapid melting trend from the western slope to the southern slope then to the northern slope.Glacial runoff in the basin showed a fluctuating upward trend in the past 21 a,with an increase rate of 0.03×10^(8) m^(3)/a.The average annual glacial runoff was 4.80×10^(8) m^(3),of which 33.31%was distributed in the ablation season(June–September).The average annual contribution rate of glacial meltwater to river runoff was 35.40%,and glacial runoff accounted for 45.37%of the total runoff during the ablation season.In addition,precipitation and glacial runoff had complementary regulation patterns for river runoff.The findings can provide a scientific basis for water resource management in the Manas River Basin and other similar arid inland river basins.

Particle Swarm Optimization for Identifying Rainfall-Runoff Relationships

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

Comparative Assessment of Impacts of Future Climate Change on Runoff in Upper Daqinghe Basin,China

Assessing runoff changes is of great importance especially its responses to the projected future climate change on local scale basins because such analyses are generally done on global and regional scales which may lead to generalized conclusions rather than specific ones.Climate change affected the runoff variation in the past in the upper Daqinghe Basin,however,the climate was mainly considered uncertain and still needs further studies,especially its future impacts on runoff for better water resources management and planning.Integrated with a set of climate simulations,a daily conceptual hydrological model(MIKE11-NAM)was applied to assess the impact of climate change on runoff conditions in the Daomaguan,Fuping and Zijingguan basins in the upper Daqinghe Basin.Historical hydrological data(2008–2017)were used to evaluate the applicability of the MIKE11-NAM model.After bias correction,future projected climate change and its impacts on runoff(2025–2054)were analysed and compared to the baseline period(1985–2014)under three shared social economic pathways(SSP1-2.6,SSP2-4.5,and SSP5-8.5)scenarios from Coupled Model Intercomparison Project Phase 6(CMIP6)simulations.The MIKE-11 NAM model was applicable in all three Basins,with both R^(2)and Nash-Sutcliffe Efficiency coefficients greater than 0.6 at daily scale for both calibration(2009–2011)and validation(2012–2017)periods,respectively.Although uncertainties remain,temperature and precipitation are projected to increase compared to the baseline where higher increases in precipitation and temperature are projected to occur under SSP2-4.5 and SSP5-8.5 scenarios,respectively in all the basins.Precipitation changes will range between 12%–19%whereas temperature change will be 2.0℃–2.5℃ under the SSP2-4.5 and SSP5-8.5 scenarios,respectively.In addition,higher warming is projected to occur in colder months than in warmer months.Overall,the runoff of these three basins is projected to respond to projected climate changes differently because runoff is projected to only increase in the Fuping basin under SSP2-4.5 whereas decreases in both Daomaguan and Zijingguan Basins under all scenarios.This study’s findings could be important when setting mitigation strategies for climate change and water resources management.

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

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

Runoff Characteristics of Different Stands in Dongjiang Lake Reservoir Area

Different forest stands in the Dongjiang Lake Reservoir area of Zixing were selected as the research objects to study the characteristics of runoff generation in different forest stands.The results showed that there was no significant difference in annual runoff among M3,M1,and M5,and no significant difference between each forest stand and the control.The order was M3(22.75 mm)>M1(21.77 mm)>M5(20.14 mm).Forest vegetation generates less runoff through vegetation restoration compared to the control,indicating that forest vegetation reconstruction and restoration are beneficial for soil and water conservation.

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

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

Artificial Neural Networks for Event Based Rainfall-Runoff Modeling

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

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

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

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

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