A new lumped conceptual model based on the Soil Conservation Service Curve Number (SCS-CN) concept has been proposed in this paper for long-term hydrologic simulation and it has been tested using the data of five catchments from different climatic and geographic settings of India. When compared with the Mishra et al. (2005) model based on variable source area (VSA) concept, the proposed model performed better in all applications. Both the models however exhibited a better match between the simulated and observed runoff in high runoff producing watersheds than did in low runoff producing catchments. Using the results of the proposed model, dominant/dormant processes involved in watershed's runoff generating mechanism have also been identified. The presented model is found useful in the continuous simulation of rainfall-runoff process in watersheds.Keywords hydrological forecasting . long-term hydrologic simulation . saturation excess overland flow . streamflow . rainfall-runoff . variable source area . curve number . antecedent moisture Nomenclature P total rainfall I a initial abstraction P e effective rainfall F t infiltration at any time 't' in SCS-CN-based model Water Resour Manage (2008) 22:165-190 RO t rainfall excess (surface runoff) at any time 't' for 5-days from beginning of storm DR t subsoil drainage at any time 't' PR t percolation at any time 't' DSP t deep seepage at any time 't' in SCS-CN-based model DPR t deep percolation at any time 't' SRO t surface runoff at any time 't', if t>5-days THR t throughflow at any time 't' in SCS-CN-based model BF t base flow at any time 't' in SCS-CN-based model TRO t total runoff at any time 't' in SCS-CN-based model EVP t potential evaporation at any time 't' EV t evaporation at any time 't' TR t transpiration at any time 't' ET t actual evapotranspiration at any time 't' in SCS-CN-based model SMS soil moisture store GWS ground water store SCS-CN Soil Conservation Service-Curve Number
Over the past decade, water-centric research has increasingly taken into consideration the interactions between the water cycle and the social, economic, and biogeophysical processes that drive watershed dynamics. In parallel, water management has made great strides in data sharing and collaborative modeling that support decision making through integrated planning and stakeholder involvement. Both research and management communities require data and simulation models that cover large spatial scales and workflows that enable investigations and decision making in real time with participation of multiple watershed actors. To efficiently accomplish their goals, these two communities are tapping into the capabilities of advanced cyberinfrastructure (CI) platforms that facilitate an understanding of watershed processes, knowledge management, visualization, interaction, and collaboration in multiple watershed science and engineering disciplines. This paper illustrates an implementation of an end-to-end CI system for understanding of the ecological threats, shifts in soil conservation practices, and public perception of environmental health with preservation of the economic benefits of agricultural production at the watershed scale. The systems were implemented in a 270 km 2 Clear Creek catchment in eastern Iowa.
Groundwater salinity, caused by over-extraction and aggravated by climate change, negatively affects crop productivity and threatens global food security. Poor farmers are vulnerable due to low adaptive capacity. A better understanding of their perceptions and adaptation is important to inform policies for successful adaptation. This paper represents an important study by exploring the same in Mewat, a salinity-affected socioeconomically backward district of northern India. The study uses a mixed-method approach with both secondary data and a primary survey of 250 farmers. A large number of farmers perceived negative impacts on water, crop, income, and assets; and adapt in various ways like water management, crop, and land management, livelihood diversification, and shift towards surface water irrigation. Perceived impacts differed between richer and poorer farmers, whereas adaptation measures varied across the educational, social, and economic backgrounds of farmers. Lack of awareness, education, skill development, and livelihood-opportunities are found to be hindrances, whereas institutional and infrastructural support as facilitators of adaptation. Comparing the findings with global experiences we argued that developed countries intervene more in the policy level and infrastructure, whereas in developing countries, adaptation strategies are local, context-specific, and low-cost. The insights from our study will be useful for intervention in Mewat and similar areas across the developing world. We further argue that farmers take adaptation decisions based on perceived impacts and cost-benefit analysis. Therefore, future research work on quantifying the negative impacts and cost-benefit analysis of various adaptation measures will be useful to ensure successful adaptation in the region and beyond.
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