The Natural Resource Conservation Service – Curve Number (NRCS-CN) methodology is a widely used tool for estimating surface runoff, which is of prime importance in hydrological engineering, agricultural planning and management, environmental impact assessment, flood forecasting, and others fields. This article reviews the methodology and associated hydrological models used for runoff estimation along with their advantages and limitations. Furthermore, discussion focuses on the potential applications of Remote Sensing (RS) and Geographical Information System (GIS) techniques for estimating hydrological variables, such as rainfall, soil moisture and CN required for the NRCS-CN methodology, as well as future research and opportunities for improved runoff estimation at the macro scale.

In this study, environmental flows (EFs) are estimated for six watersheds of Damodar River Basin (DRB) using flow duration curve (FDC) derived using two approaches: (a) period of record and (b) stochastic approaches for daily, 7-, 30-, 60-day moving averages, and 7-daily mean annual flows observed at Tenughat dam, Konar dam, Maithon dam, Panchet dam, Damodar bridge, Burnpur during 1981–2010 and at Phusro during 1988–2010. For stochastic FDCs, 7-day FDCs for 10, 20-, 50- and 100-year return periods were derived for extraction of discharge values at every 5% probability of exceedance. FDCs derived using the first approach show high probability of exceedance (5–75%) for the same discharge values. Furthermore, discharge values of 60-day mean are higher than those derived using daily, 7-, and 30-day mean values. The discharge values of 95% probability of exceedance (Q95) derived from 7Q10 (ranges from 2.04 to 5.56 cumec) and 7Q100 (ranges from 3.4 to 31.48 cumec) FDCs using the second approach are found more appropriate as EFs during drought/low flow and normal precipitation years.

In this study, four surface water quality datasets of upper Damodar river basin (DRB) covering three seasons; pre-monsoon, monsoon, post-monsoon and annual, for years 2007–2010 were generated by analyzing 280 grab water samples. Each dataset consist of water quality constituents of 35 monitoring stations and sample of each station was evaluated by 17 critical parameters (total 4760 observations). Furthermore, each dataset was treated using six water quality indices (WQIs): four developed simplified indices (WQI_m, WQI_min, WQI_DO, and WQI_pca) and two existing extended indices (WQI_obj and WQI_sub), to assess spatiotemporal variations and suitability for human use and aquatic life. Results revealed that developed indices show on an average similar spatiotemporal variations as compared to WQI_obj at a lower analytical cost at most of sampling sites comes under good to medium categories of water quality. Geographical information system (GIS) technique was also used for generation of temporal pollution potential maps of DRB. Consequently, this study also presents the necessity and usefulness of developed indices over extended indices especially for the developing countries, because the cost of monitoring and expenses associated with the implementation is less compared to extended methods and generated maps may also facilitate the decision-making processes under various scenarios considering spatial and temporal variability in DRB.