Conservation Service Curve Number Method Research Articles

Cost-Benefit Analysis of Minor Irrigation Tank Rehabilitation Using Run-Off and Storage Capacity: A Case Study from Ambuliyar Sub-Basin, Tamil Nadu, India

This research examines the significance of restoring efficient water management systems in India’s semiarid environment, with special emphasis on the role of traditional irrigation structures, such as tanks, in collecting and storing limited water resources. Assessing the benefits of any restoration program, especially when socioeconomic and environmental benefits are involved, is challenging. In the context of tank rehabilitation, a cost-benefit analysis will be conducted regarding economic and ecological returns in the post-desiltation phase. Since the restoration process requires a significant investment, assessing the project’s viability during the planning stage is better. The present study proposes a novel method to indirectly analyse the cost-benefit of the tank restoration process by correlating run-off and storage capacity of tanks before the planning phase. The Ambuliyar sub-basin, which covers an area of 930 square kilometres in Tamil Nadu, India, comprising 181 tanks (water bodies) of varying sizes and shapes, was taken for this study. This study employed the Soil Conservation Service Curve Number (SCS-CN) method, incorporating factors such as soil type, land cover, land use practices, and advanced remote sensing and Geographic Information System (GIS) tools to simulate surface run-off. Run-off volume and tank capacity were compared for all seasons at the micro-watershed level. The results demonstrated that the run-off volume in each micro-watershed significantly exceeded the tank capacity across all seasons. Even during the summer, the run-off volumes in the micro-watershed were considerably higher than the tank capacity. The findings suggest tank restoration can effectively store run-off and significantly fulfil agricultural and other essential needs throughout the year, thereby improving the local rural economy. This study also highlights the need for periodic maintenance and rehabilitation of these tank systems to retain their functionality.

Energy potential assessment and techno–economic analysis of micro hydro–photovoltaic hybrid system in Goda Warke village, Ethiopia

Abstract Rural Ethiopia has significant untapped potential for hydro and solar energy generation systems. However, challenges arise from seasonal variations and unfavourable topographic positions of flowing rivers, hindering the efficient exploitation of these resources. Despite the country’s abundance in hydro and solar energy resources, >75% of the population still lack access to electricity from the national grid. This work deals with energy resource potential assessment and techno–economic analysis of micro hydro–photovoltaic (PV) hybrid systems, considered in the case study of Goda Warke village, located in the Yaya Gulele district. A novel framework is proposed that utilizes the Natural Resource Soil Conservation Service curve number method to assess the energy potential of micro-hydro energy in ungauged basins, specifically at the exit point of the Girar River basin catchment. The average monthly flow rate in the basin is 0.975 m3/s, while the area exhibits a solar radiation potential of 5.39 kWh/m2/day. Energy policy promotes expanding access to modern energy sources and utilization of indigenous energy resources. Simulation results indicate that the hydro/PV/diesel generator (DG)/battery and hydro/PV/battery systems are the most optimal choices based on net present cost, with the inclusion of a DG for economic comparison. Micro-hydro energy covers most of the electric load in the area, achieving a capacity factor of 47.5%. The cost of energy and net present cost were found to be sensitive to variables such as the price of diesel fuel, pipe head loss, and the growth of the village load. The optimized system demonstrated a hydro energy potential of 1405.37 MWh/year and a PV energy output of 274.04 MWh/year, resulting in a levelized cost of energy of 0.0057 and 0.049 $/kWh for the hydro and PV components, respectively.

Integrated Hydrological Modeling for Watershed Analysis, Flood Prediction, and Mitigation Using Meteorological and Morphometric Data, SCS-CN, HEC-HMS/RAS, and QGIS

Flooding is a natural disaster with extensive impacts. Desert regions face altered flooding patterns owing to climate change, water scarcity, regulations, and rising water demands. This study assessed and predicted flash flood hazards by calculating discharge volume, peak flow, flood depth, and velocity using the Hydrologic Engineering Centre-River Analysis System and Hydrologic Modelling System (HEC-HMS and HEC-RAS) software. We employed meteorological and morphological data analyses, incorporating the soil conservation service (SCS) curve number method for precipitation losses and the SCS-Hydrograph for runoff transformation. The model was applied to two drainage basins (An-Nawayah and Al-Rashrash) in southeastern Cairo, Egypt, which recently encountered several destructive floods. The applied model revealed that 25-, 50-, and 100-year storms produced runoff volumes of 2461.8 × 103, 4299.6 × 103, and 5204.5 × 103 m3 for An-Nawayah and 6212 × 103, 8129.4 × 103, and 10,330.6 × 103 m3 for Al-Rashrash, respectively. Flood risk levels, categorised as high (35.6%), extreme (21.9%), and medium (21.12%) were assessed in low- and very-low-hazard areas. The study highlighted that the areas closer to the Nile River mouth faced greater flood impacts from torrential rain. Our findings demonstrate the effectiveness of these methods in assessing and predicting flood risk. As a mitigation measure, this study recommends the construction of five 10 m high dams to create storage lakes. This integrated approach can be applied to flood risk assessment and mitigation in comparable regions.

Using remote sensing technology in estimating flood discharge

Floods are the most natural disasters occurring on earth. Recently, Egypt has been subjected to more frequent floods due to climate change. The main objective of this paper is creating hydrological analysis and estimating water discharge due to a flood hitting a hazardous zone near Safaga city. The research is divided into four main stages; 1) Morphological study, 2) Meteorological study, 3) Losses estimation, and 4) Flood discharge estimation. First, morphological study in which watershed boundaries, main streams and morphological data are delineated using geographic information system (GIS) with the aid of Landsat-8 satellite images and 30-m resolution digital elevation model (DEM). Second, meteorological study in which conventional rainfall frequency analysis is generated to estimate rainfall depth at different return periods using 15-years rainfall historical data from weather stations. Third, losses estimation is determined by using soil conservation service-curve number method (SCS-CN). Fourth, water discharge volume is carried out through hydrological modelling using a hydrologic engineering centre model. The estimated water volume is an appropriate information for decision makers to propose the adequate protection works to mitigate flood impacts.

Identification of potential zones on the estimation of direct runoff and soil erosion for an ungauged watershed based on remote sensing and GIS techniques

An investigation of soil and water resources is essential to determine the future scenario of water management and water resources to attain food and water security. The improper management of watersheds results in a huge amount of sediment loss and surface runoff. Therefore, the present study was carried out to estimate the surface runoff and soil erosion using the Soil Conservation Service Curve Number (SCS-CN) method and RUSLE approach, respectively. These have been estimated using geospatial technologies for the ungauged Mandri river watershed from the Kanker district of Chhattisgarh State in India. The runoff potential zones, which are defined by the area's impermeable surfaces for a given quantity of precipitation were identified based on curve numbers at the sub-watershed levels. The land use data were collected from LISS IV images of 2009. The results showed that the average volume of runoff generated throughout the 16 years (2000-2015) was 14.37 million cubic meters (mM3). While average annual soil loss was found to be 17.23 tons/ha/year. Most of the eroded area was found to be around the major stream in a drainage system of Mandri River and on higher slopes of the terrain in the watershed. This study revealed that surface runoff and soil erosion are primary issues, which adversely affected the soil and water resources in this watershed. Therefore, suitable water harvesting sites and structures can be constructed based on the potential runoff zone and severity of soil erosion to conserve the soil and water in the watershed.

Estimation of Equivalent Rainfall for Ungauged Reservoir Using Satellite-Based High-Resolution Terrain Data

Equivalent rainfall refers to the amount of precipitation required to reach a specific water level from the current water level in a reservoir. It serves as a flood forecasting and warning system that allows for the rapid assessment of the reservoir’s maximum water level at the moment of rainfall forecast. In reservoirs where terrain and survey data can be obtained, deriving equivalent rainfall is not difficult. However, without terrain data, satellite imagery and global topographic data are the only available options. In this study, high-resolution topographic data based on satellites were utilized to estimate the equivalent rainfall in the ungauged reservoir, Hwanggang Dam, located in the upper stream of the Imjin River in North Korea. To calculate the inflow into the reservoir, the Natural Resources Conservation Service-Curve Number method was used to determine the effective rainfall, taking into account the antecedent conditions, as the inflow into the reservoir can be changed for the same amount of rainfall depending on the soil moisture content of the watershed.

Integrating geographic data and the SCS-CN method with LSTM networks for enhanced runoff forecasting in a complex mountain basin

IntroductionIn complex mountain basins, hydrological forecasting poses a formidable challenge due to the intricacies of runoff generation processes and the limitations of available data. This study explores the enhancement of short-term runoff forecasting models through the utilization of long short-term memory (LSTM) networks.MethodsTo achieve this, we employed feature engineering (FE) strategies, focusing on geographic data and the Soil Conservation Service Curve Number (SCS-CN) method. Our investigation was conducted in a 3,390 km2 basin, employing the GSMaP-NRT satellite precipitation product (SPP) to develop forecasting models with lead times of 1, 6, and 11 h. These lead times were selected to address the needs of near-real-time forecasting, flash flood prediction, and basin concentration time assessment, respectively.Results and discussionOur findings demonstrate an improvement in the efficiency of LSTM forecasting models across all lead times, as indicated by Nash-Sutcliffe efficiency values of 0.93 (1 h), 0.77 (6 h), and 0.67 (11 h). Notably, these results are on par with studies relying on ground-based precipitation data. This methodology not only showcases the potential for advanced data-driven runoff models but also underscores the importance of incorporating available geographic information into precipitation-ungauged hydrological systems. The insights derived from this study offer valuable tools for hydrologists and researchers seeking to enhance the accuracy of hydrological forecasting in complex mountain basins.

Exploring the impact of climate change on flood risk at cultural heritage sites using a GIS-based SCS-CN method: A case study of Shanxi province, China

Cultural heritage sites in China are facing an increasing risk of flooding caused in part by global climate change. This paper aims to provide a new method used to predict flood risk of cultural heritage sites while considering the impact of climate change. Using a GIS-based Soil Conservation Service Curve Number (SCS–CN) method, we assessed the risk of flooding at cultural heritage sites in Shanxi Province by the end of 21st century under three different climate change scenarios, namely SSP119, SSP245, and SSP585. The results show that 268 sites are currently at risk from a 100-year storm event. By 2099, about 100 additional cultural heritage sites are projected to be threatened by flooding. The cultural heritage sites protected at the city and county level are generally more vulnerable to climate change. In addition, those along the Fen River in Taiyuan City, the Qin and Dan rivers in Jincheng City, and the upstream region of the Zhuozhang River in Changzhi City also have relatively high flood risks. These findings can provide insights for climate change adaptive action and cultural heritage conversation in Shanxi Province.

Improving Runoff Prediction Accuracy in a Mountainous Watershed Using a Remote Sensing-Based Approach

Due to the limited number and sparse distribution of meteorological and hydrometric stations in most watersheds, the runoff estimation based on these stations may not be accurate. However, the accurate determination of the Antecedent Soil Moisture (ASM) in watersheds can improve the accuracy of runoff forecasting. The objective of this study is to utilize the ASM derived from satellite imagery to enhance the accuracy of runoff estimation in a mountainous watershed. In this study, a range of Remote Sensing (RS) data, including surface biophysical and topographic features, climate data, hydrometric station flow data, and a ground-based measured SM database for the Balikhli-Chay watershed in Iran, were utilized. The Soil Conservation Service Curve Number (SCS-CN) method was employed to estimate runoff. Two approaches were used for estimating the ASM: (1) using the precipitation data recorded in ground stations, and (2) using the SM data obtained from satellite images. The accuracy of runoff estimation was then calculated for these two scenarios and compared. The mean Nash–Sutcliffe statistic was found to be 0.63 in the first scenario and 0.74 in the second scenario. The inclusion of ASM derived from the satellite imagery in the precipitation–runoff model resulted in a 51% increase in the accuracy of runoff estimation compared to using precipitation data recorded in ground stations. These findings have significant implications for improving the accuracy of ASM and runoff modeling in various applications.

Simulation of the impact of land use change on surface run-off in Karst Leang Lonrong Sub-Watershed

Estimation of surface run-off in karst watersheds has not been widely carried out and the estimation method is generally developed for non-karst watersheds. This study aims to analyze the accuracy of estimation of river discharge at the outlet of the Karst Biringere Sub-watershed using the modified Soil Conservation Service Curve Number (SCS-CN) method and analyzed the impact of land use change on river discharge at the outlet of the Karst Biringere Sub-watershed. Modification of the SCS-CN method in estimating direct flow at the outlet of the Beringere Sub-watershed is influenced by the similarity of rainfall and direct flow fluctuation of river discharge. The modified SCS-CN method provides satisfactory direct flow estimation when rainfall with observed direct flow of river discharge forms a linear relationship with a strong correlation. Changes in land use with reduced forest cover into mining areas result in increased run-off and reduced storage, the larger the forest land becomes mining areas, the greater the increase in run-off and reduction in storage. Reclamation of the former mining area to be a forest reduces run-off and increases water storage.

Estimation of Surface-Subsurface Water Balance in Lower Tapi River Basin Using Gridded Data and Station-Based Observed Data

ABSTRACT Water is an essential resource. An understanding of catchment water balance is crucial to ensure water availability in the region. Hydrological models are credible tools for water balance assessment of a region. These models are data intensive. The traditional hydrological modeling approach relies on station-based observed data. The availability of sufficient long-term consistent observed data is often limited. On the other hand, climate reanalysis data for a long timeperiod is available from multiple data sources. This study estimates runoff characteristics for Lower Tapi River Basin in western India, with the help of a Soil Conservation Service Curve Number method. The catchment water balance in terms of runoff, baseflow, and recharge at sub-basin scale is worked out with the help of station-based and climate reanalysis datasets. The model output are calibrated against observed river gauging data. A reasonable fit between model-simulated and observed runoff is obtained in terms of duration and magnitude of runoff peak. Tested model is applied to future climate scenarios. The simulations show an increase in surface runoff, recharge, baseflow and total runoff for future time period. Results reveal that climate changes have significant impact on hydrology of the basin.

A comparison of the SCS-CN-based models for hydrological simulation of the Aghanashini River, Karnataka, India

Abstract This present study investigates different techniques for estimating the surface runoff using the Soil Conservation Service Curve Number (SCS-CN) method for the Aghanashini River in Karnataka, India. The SCS-CN method is a simplified approach for runoff estimation, but it does not take into account the actual moisture content in the soil. Consequently, insignificant moisture level changes could induce significant variations in the runoff. The study analyzes six different models based on the SCS-CN method, including the original SCS-CN model and several variations with added features (SCS-CN with slope correction, SCS-CN with λ-optimization, Mishra and Singh, Michel-Vazken -Perrin (MVP), Activation Soil Moisture Accounting SCS-CN). The accuracy of each model was compared using several goodness-of-fit statistics. Furthermore, based on the flood frequency analysis, three large flood events were reported in 2005, 2013, and 2014. The results showed that the MVP model was the best-performing method in simulating runoff. The outcomes of this study can provide valuable information to the local authorities in making informed decisions about flood forecasting and water conservation.

Determination of nitrogen sources and losses in surface runoff from different lands at a watershed scale.

Nitrogen (N) loss by surface runoff inevitably results in severe N pollution and eutrophication of aquatic ecosystems. In this study, surface runoff from different land uses in the East Tiaoxi River watershed was collected, and the N concentrations, sources and losses were measured using the dual isotope (δ15N-NO3- and δ18O-NO3-), a Bayesian isotopic mixing (SIAR) model and Soil Conservation Service Curve Number (SCS-CN) method. The results showed that the N concentrations in surface runoff from agricultural lands were higher than those from urban areas and forestlands, and nitrate (NO3-), particulate nitrogen (PN) and dissolved organic nitrogen (DON) were the major forms of N in surface runoff in the East Tiaoxi River watershed. The total loss rate of total nitrogen (TN) from surface runoff in the East Tiaoxi River watershed was 5.38kg·ha-1·a-1, with NO3--N (46%) contributing the most to TN loss. The TN, and NO3--N loss rates in surface runoff from tea planting lands (21.08kg·ha-1·a-1, 11.98kg·ha-1·a-1) and croplands (16.93kg·ha-1·a-1, 10.96kg·ha-1·a-1) were high, those from vegetable lands and urban areas were medium, and those from economic and natural forestlands were low in the East Tiaoxi River watershed. The NO3--N contributions of chemical fertiliser (CF), soil N (SN), sewage/manure (SM), and atmospheric deposition (AD) in surface runoff in the East Tiaoxi River watershed were 124.32 × 103, 104.84 × 103, 82.25 × 103 and 58.69 × 103kg·a-1, respectively. The N pollutant losses in surface runoff from agricultural lands (croplands with rice growing, vegetable lands and tea planting lands) were responsible for most of the N pollutants being transported into the East Tiaoxi River systems.

Rain garden design for stormwater management in Chiang Mai, Thailand: A Research-through-Design Study

Conventional stormwater management may cause long term environmental issues. Fortunately, Water Sensitive Urban Design (WSUD) can manage stormwater more sustainably. However, the design examples of WSUD elements, such as rain gardens within the geographical and cultural context of Thailand are lacking. This study investigated the patterns of rain garden design suitable for urban areas in Chiang Mai and developed examples of rain garden design processes and prototypes in an urban context for Chiang Mai. 
 This research used the Research by design Method (RDM), which has great potential in bridging the gap between research and application. The researchers selected the site at the Faculty of Agriculture, Chiang Mai University. They designed 2 schematics of rain gardens with local Lanna plants. Then, they compared stormwater capacity with the existing site via the Natural Resources and Conservation Service (NRCS) Curve Number Method. The design results were evaluated by stakeholders and design experts to bridge the gaps between international standards and local contexts. 
 We found that 1) the west side of the site was most appropriate to develop the pilot project. 2) Both design schematics performed better than the original site. 3) Stakeholders and design experts see the potential of the site, but had concerns regarding its actual performance, maintenance, scale, and safety. This paper offers and provides an example of the rain garden design process which can be used as a baseline for future designs of rain garden and water sensitive urban designs.

Runoff Estimation and Dam Selection Site in the Khur khur Watershed (KHW), Using (SCS-CN) Method and (GIS & RS) Techniques

The Soil Conservation Service Curve Number (SCS-CN) method was applied to calculate the runoff in the Khur khur watershed (KHW) based on (GIS and RS) techniques. The watershed (KHW) is located southeast of the Iraqi Kurdistan region and northeast Iraq in the foothill zone. The total area of (KHW) is (106.84) km2, and in the fifth order, it meets the Sirwan river. The study aim is to speculate annual runoff volume and to select the dam site in order to harvest water from (KHW). The research reached specific basic results; the annual rate of water returns was (14408514.23 m3), and a suitable dam location was proposed that could be exploited from the volume of surface runoff, with a capacity approximately (14 million m3).

Application of Soil Conservation Service Curve Number Method for Runoff Estimation in Sebou Watershed, Morocco

Application of Soil Conservation Service Curve Number Method for Runoff Estimation in Sebou Watershed, Morocco

An improved MUSLE model incorporating the estimated runoff and peak discharge predicted sediment yield at the watershed scale on the Chinese Loess Plateau

An accurate prediction of sediment yield at the watershed scale is critical not only for sustainable watershed management but also for improving knowledge regarding the relationship between sediment yield and its determinant factors, which often rely on the varying model complexity. In this study, a modified sediment yield formula based on the modified universal soil loss equation (MUSLE) model was developed by introducing a channel factor into the original formula. The reliability of the proposed method was tested using data from 1,341 storm events in 38 watersheds and was applied to 256 storm events in five application watersheds using the optimized parameters. Results indicated that the proposed method is very accurate, as demonstrated by the Nash–Sutcliffe efficiency (NSE) values of 88.18 %, 85.72 %, and 85.51 % during calibration, validation, and application, respectively. The performance of the proposed model was superior to that of the original MUSLE model. Subsequently, the proposed method was used to predict sediment yield from the last five typical watersheds. This prediction utilized the parameters derived from the initial 38 watersheds; the peak discharge predicted by the modified Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS); and the runoff estimated by the modified Soil Conservation Service Curve Number (SCS-CN) method. Elevated NSE (61.88–81.42 %) and low root mean square error values (2.35–11.40 t ha−1) were calculated for the five watersheds. From the results, the proposed sediment yield model, combined with the modified SCS-CN method and CREAMS, was found to accurately predict the event-based sediment yield, peak discharge, and runoff in the Loess Plateau region under varying hydrological and geomorphic conditions.

Capacity of River Valleys to Retain Nutrients from Surface Runoff in Urban and Rural Areas (Southern Poland)

Studies on water quality are necessary, as catchments of small watercourses are exposed to anthropogenic influences associated with agricultural activities, settlement, transport and other undertakings, leading to water pollution. There has been insufficient research performed on the valley’s ability to retain nutrients during floods, contributing to water accumulation. The main object of the study was to identify the retention capacity of river valleys under various aspects of human urbanization. To represent soil water retention, the Soil Conservation Service Curve Number (SCS-CN) method was used. Spatiotemporal autoregressive models were exploited to investigate the relationship between pollutants in precipitation and surface water in rivers. In contrast, multivariate analysis was used to identify and reveal patterns of land use for specific chemical compounds in the headwaters. The canonical-correlation analysis (CCA) showed that Mg+2 and Ca+2 cations in rainwater and surface waters play the main roles in the geochemical cycle in urban and rural areas. In the urban catchment area, the strongest relations were found for NO3−, K+ and Na+. The average NO3− concentration in urban headwater was 8.3 mg·dm−3, the highest in the study area. The relationship between NO3− concentration in headwater and rainwater was found for all study catchments using spatial autoregression (SAR). High concentrations of SO42− in surface water have been identified in urban areas. Severe water erosion raises the risk of nutrient leaching in soils prone to surface runoff. As a consequence of low soil permeability and urbanization, retention capacity is significantly reduced in areas with low soil permeability. Land development plans should take spatial retention capacity into consideration. To ensure that large reservoirs can retain water in the face of climate change, riparian buffer zones (protective zones in valleys for small water bodies as well as Nature-based Solution) are important.

An improved method that incorporates the estimated runoff for peak discharge prediction on the Chinese Loess Plateau

An accurate prediction of peak discharge in watersheds is critical not only for water resource management, but also for understanding the complex relationships of hydrological processes. In this study, a modified peak discharge formula based on the Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS) model was developed by introducing rainfall intensity and soil moisture factors. The reliability of the proposed method was tested with data from 1464 storm events in 41 watersheds and was applied to 256 storm events in five remaining typical watersheds using the optimized parameters. The results indicate that the proposed method is highly accurate in terms of model efficiency, as determined by Nash–Sutcliffe efficiencies (NSEs) of 88.60%, 74.04%, and 90.12% during the calibration, validation, and application cases, respectively. Furthermore, it performed better than the original and modified CREAMS methods. Subsequently, using the parameters derived from the initial 41 watersheds and the runoff estimated using the modified Soil Conservation Service curve number (SCS–CN) method, the proposed method was used to predict the peak discharge from the last five typical watersheds. Large NSE (63.88–80.83%) and low root mean square error (RMSE) values (0.31–35.93 m3s-1) were obtained for the five watersheds. Overall, the proposed peak discharge model, combined with the modified SCS-CN method, may accurately predict event-based peak discharge and runoff for general applications under various hydrological and geomorphic conditions in the Loess Plateau region.

Long-Term (1990–2013) Changes and Spatial Variations of Cropland Runoff across China

Quantitative information on regional cropland runoff is important for sustainable agricultural water quantity and quality management. This study combined the Soil Conservation Service Curve Number (SCS-CN) method and geostatistical approaches to quantify long-term (1990–2013) changes and regional spatial variations of cropland runoff in China. Estimated CN values from 17 cropland study sites across China showed reasonable agreement with default values from the National Engineering Handbook (R2 = 0.76, n = 17). Among four commonly used geostatistical interpolation methods, the inverse distance weighting (IDW) method achieved the highest accuracy (R2 = 0.67, n = 209) for prediction of cropland runoff. Using default CN values and the IDW method, estimated national annual cropland runoff volume and runoff depth in 1990–2013 were 253 ± 25 km3 yr−1 and 182 ± 15 mm yr−1, respectively. Estimated cropland runoff depth gradually increased from the drier northwest inland region to the wetter southeast coastal region (range: 2–1375 mm yr−1). Regionally, eastern, central and southern China accounted for 39% of the cultivated area and 53% of the irrigated land area and contributed to 68% of the national cropland runoff volume. In contrast, northwestern, northern, southwestern and northeastern China accounted for 61% of the cultivated area and 47% of the irrigated land area and contributed to 32% of the runoff volume. Rainfall was the main source (72%) of cropland runoff for the entire nation, while irrigation became the main source of cropland runoff in drier regions (northwestern and southwestern China). Over the 24-year study period, estimated cropland runoff depth showed no significant trends, whereas cropland runoff volume and irrigation-contributed percentages decreased by 7% and 35%, respectively, owing to implementation of water-saving irrigation technologies. To reduce excessive runoff and increase water utilization efficiencies, regionally specific water management strategies should be further promoted. As the first long-term national estimate of cropland runoff in China, this study provides a simple framework for estimating regional cropland runoff depth and volume, providing critical information for guiding developments of management practices to mitigate agricultural nonpoint source pollution, soil erosion and water scarcity.