Spatial heterogeneity of a river basin increases the predicting uncertainty of streamflow using hydrological models, and for such river basins calibration and prediction become a challenge. For a large and low flow–producing river basin like the Pennar basin of India, single-site calibration may ignore spatial heterogeneity, which leads to the use of a multiple-site calibration approach. The present study used Soil and Water Assessment Tool (SWAT) model to develop a real-world numerical model for predicting streamflow in a large, low runoff–producing river basin and evaluated the performance of the model under single-site and multiple-site calibration approaches. Under multiple-site approach, the large basin was divided into smaller subbasins, and the calibrated parameters were sequentially applied to the entire basin, and so local conditions were incorporated very effectively into the calibration process. The results demonstrated the superiority of a multiple-site calibration over a single-site calibration approach in predicting streamflow. The overall improvement of model performance in predicting streamflow using multiple-site approach over single-site approach reached as high as 133% during calibration and 140% during validation, as observed at the basin outlet (Chennur station). It was also observed that, within the basin, precipitation contributed only 15.8% to surface runoff, 2.6% to total aquifer recharge, and 69.3% to evapotranspiration. Uncertainty analysis indicated that more than 64% of the observed streamflow was bracketed by a 95% prediction uncertainty (PPU) band under the multiple-site approach. Thus, the multiple-site calibration approach demonstrated its ability to improve model performance by capturing the heterogeneity of a low runoff–producing basin like Pennar.

The hydrologic behaviour of the Brahmani River basin (BRB) (39,633.90 km2), India was assessed for the base period (1970–1999) and future climate scenarios (2050) using the Soil and Water Assessment Tool (SWAT). Monthly streamflow data of 2000–2009 and 2010–2012 was used for calibration and validation, respectively, and performed satisfactorily with Nash-Sutcliffe Efficiency (ENS) of 0.52–0.55. The projected future climatic outcomes of the HadGEM2-ES model indicated that minimum temperature, maximum temperature, and precipitation may increase by 1.11–3.72 °C, 0.27–2.89 °C, and 16–263 mm, respectively, by 2050. The mean annual streamflow over the basin may increase by 20.86, 11.29, 4.45, and 37.94% under representative concentration pathway (RCP) 2.6, 4.5, 6.0, and 8.5, respectively, whereas the sediment yield is likely to increase by 23.34, 10.53, 2.45, and 27.62% under RCP 2.6, 4.5, 6.0, and 8.5, respectively, signifying RCP 8.5 to be the most adverse scenario for the BRB. Moreover, a ten-fold increase in environmental flow (defined as Q90) by the mid-century period is expected under the RCP 8.5 scenario. The vulnerable area assessment revealed that the increase in moderate and high erosion-prone regions will be more prevalent in the mid-century. The methodology developed herein could be successfully implemented for identification and prioritization of critical zones in worldwide river basins.

Despite the growing importance of soil and water conservation and watershed development projects as an approach to rural development and natural resource management, there has been relatively little research on devising site-specific best management practice (BMP) to check the soil erosion losses within permissible limits, especially in hilly regions. For a sustainable watershed management programme and implementation, site specific BMPs assume importance and hold the promise of making conservation planning and watershed management simpler and more effective. The study was attempted to develop a methodology to obtain BMPs, aiming to reduce the erosion losses in erosion risk areas of the northwestern Himalayas by employing Analytic Hierarchy Process (AHP). The AHP technique was employed to prioritise the potential technologies and select the BMP suitable for a particular land area. The prioritization of technologies was performed with four criteria viz. soil erosion resistance, cost, benefit, maintenance and environment friendliness of conservation measures. The soil erosion scenario of the study area located in the northwestern Himalayas was generated with each selected measure in a SWAT model using DEM, land use maps, a soil map and climate data of the study area. Then, the resultant erosion scenario of the conservation measures was compared and used for the AHP analysis. However, other criteria were assessed based on the judgement of a group of experts as well as farmers. In this study, four conservation measures, viz. Bench Terraces (BT), Vegetative Barrier (VB), Contour Farming (CF) and Zero Tillage + Live Mulch (ZL), were considered for BMP selection. Three scenarios, viz. experts’ judgement, farmers’ opinions and combined expert and farmer opinion, were analyzed to uncover the BMP for the different zones. The result revealed that experts and farmers unanimously preferred ZL as a BMP because of its low-cost implementation value and lower maintenance requirement while significantly controlling the erosion level as well as being environment friendly. The BT was the second most preferred technology for the study area. However, BMP was recommended for different zones having high to very severe erosion (soil loss > 10 t/ha/yr). Therefore, ZL was recommended for the areas with low altitude, whereas BT was recommended for the areas having high slopes because of its high capability for erosion control in the high slopping area. The methodology will act as a useful strategy for decision makers to prioritize the technology and recommend the best management for any region after considering suitable criteria. Future work may consider more criteria for inclusion to thus recommend the technology for a region in a more realistic way.