Verification of two hydrological models for real-time flood forecasting in the Hindu Kush Himalaya (HKH) region

Natural Hazards - The Hindu Kush Himalayan region is extremely susceptible to periodic monsoon floods. Early warning systems with the ability to predict floods in advance can benefit tens of...     

Impacts of climate variability on water quality with best management practices in sub‐tropical climate of USA

Efficiency of non‐point source pollution control methods may be altered in future climate. This study investigated climate change impacts on sediment and nutrient transport, and efficiency of best management practices (BMPs), in the Upper Pearl River Watershed (UPRW) in Mississippi. The Soil and Water Assessment Tool was applied to the UPRW using observed flow, sediment and nutrient data. Water quality samples were collected at three US geological survey gauging stations. The model was successfully calibrated and validated for daily time steps (Nash Sutcliffe efficiency and coefficient of determination – R² up to 0.7) using manual and automatic (sequential uncertainty fitting version 2) methods from February 2010 to May 2011. Future weather scenarios were simulated using the LARS‐WG model, a stochastic weather generator, with Community Climate System Model, global climate model, which was developed by the National Center for Atmospheric Research in the USA. On the basis of the Special Report on Emissions Scenarios A1B, A2 and B1 of the Intergovernmental Panel on Climate Change, climate change scenarios were simulated for the mid (2046–2065) and late (2080–2099) century. Effectiveness of four BMPs (Riparian buffer, stream fencing, sub‐surface manure applications and vegetative filter strips) on reducing sediment and nutrient were evaluated in current and future climate conditions. Results show that sediment, nitrogen and phosphorus loadings will be increased up to a maximum of 26.3%, 7.3% and 14.3%, respectively, in future climate conditions. Furthermore, the effectiveness of BMPs on sediment removal will be reduced in future climate conditions, and the efficiency of nitrogen removal will be increased, whereas phosphorus removal efficiency will remain unchanged. Copyright © 2013 John Wiley & Sons, Ltd.     

Comparison of AnnAGNPS and SWAT model simulation results in USDA‐CEAP agricultural watersheds in south‐central Kansas

This study was conducted under the USDA‐Conservation Effects Assessment Project (CEAP) in the Cheney Lake watershed in south‐central Kansas. The Cheney Lake watershed has been identified as ‘impaired waters’ under Section 303(d) of the Federal Clean Water Act for sediments and total phosphorus. The USDA‐CEAP seeks to quantify environmental benefits of conservation programmes on water quality by monitoring and modelling. Two of the most widely used USDA watershed‐scale models are Annualized AGricultural Non‐Point Source (AnnAGNPS) and Soil and Water Assessment Tool (SWAT). The objectives of this study were to compare hydrology, sediment, and total phosphorus simulation results from AnnAGNPS and SWAT in separate calibration and validation watersheds. Models were calibrated in Red Rock Creek watershed and validated in Goose Creek watershed, both sub‐watersheds of the Cheney Lake watershed. Forty‐five months (January 1997 to September 2000) of monthly measured flow and water quality data were used to evaluate the two models. Both models generally provided from fair to very good correlation and model efficiency for simulating surface runoff and sediment yield during calibration and validation (correlation coefficient; R², from 0·50 to 0·89, Nash Sutcliffe efficiency index, E, from 0·47 to 0·73, root mean square error, RMSE, from 0·25 to 0·45 m³ s^?1 for flow, from 158 to 312 Mg for sediment yield). Total phosphorus predictions from calibration and validation of SWAT indicated good correlation and model efficiency (R² from 0·60 to 0·70, E from 0·63 to 0·68) while total phosphorus predictions from validation of AnnAGNPS were from unsatisfactory to very good (R² from 0·60 to 0·77, E from ? 2·38 to 0·32). The root mean square error–observations standard deviation ratio (RSR) was estimated as excellent (from 0·08 to 0·25) for the all model simulated parameters during the calibration and validation study. The percentage bias (PBIAS) of the model simulated parameters varied from unsatisfactory to excellent (from 128 to 3). This study determined SWAT to be the most appropriate model for this watershed based on calibration and validation results. Copyright © 2008 John Wiley & Sons, Ltd.     

Assessing sensitivity of hydrologic responses to climate change from forested watershed in Mississippi

The climatic processes such as changes in precipitation, temperature and atmospheric CO₂ concentration can intensify the effects on water resources. An assessment of the effects of long‐term climate change on water resources is essential to the development of water quality improvement programs. This study was conducted in the Upper Pearl River Watershed (UPRW) in east‐central Mississippi to assess the effects of long‐term potential future climate change on average mean monthly stream flow from the five spatially distributed U. S. Geological Survey (USGS) gage stations in the UPRW using the Soil and Water Assessment Tool. The model was calibrated (January 1981 to December 1994) and validated (January 1995 to September 2008) using monthly measured stream flow data. The calibrated and validated model determined good to very good performance for stream flow prediction (R² and E from 0·60 to 0·86) between measured and predicted stream flow values. The root mean square error values (from 14 to 37 m³ s^?1) were estimated at similar levels of errors during model calibration and validation. The results showed that long‐term (50 years) average monthly stream flow sensitivity due to climate change effects was found the greatest as a result of percentage change in the precipitation followed by carbon dioxide (CO₂) concentration and temperature. The long‐term model simulation scenarios as compared with the base scenario for all five spatially distributed USGS gage stations in the UPRW estimated an average monthly stream flow decrease (from 54 to 67%) and average monthly stream flow increase (from 67 to 79%) depending on the spatial characteristics of the USGS gage stations. Overall, the results indicate that the UPRW hydrology is very sensitive to potential future climate changes and that these changes could stimulate increased streamflow generation from the watershed. Copyright © 2010 John Wiley & Sons, Ltd.     

Karez (qanat) irrigation in the Helmand River Basin,Afghanistan: a vanishing indigenous legacy

A karez is a gently sloping tunnel into a hillside with a series of vertical shafts. At the upstream end, the karez depresses the water table such that groundwater enters the tunnel. Farmers all over Afghanistan have built and managed karezes for centuries using indigenous knowledge. This report focuses on karezes in the Helmand River Basin in southern Afghanistan, and describes the location of karezes in relation to geology, technological and managerial aspects of karez irrigation, and their current status. Karez irrigation has declined in recent decades due to the following: a prolonged reduction in precipitation, increase in number of boreholes that lower the water table below the karez tunnel, breakdown in community-based management, and reduced maintenance. Systematic field measurements are a challenge in the Helmand Basin due to security constraints. The current condition and management of the karezes have been assessed through short field visits and structured focus-group discussions with karez farmers and staff from provincial departments. The surveys indicate that over half of the karezes in the Helmand Basin have gone dry. Furthermore, the flow in karezes that are still operational has also declined significantly. The report demonstrates the value of using data from the US National Centres for Environmental Prediction (NCEP) Reanalysis 1 project, to estimate historic precipitation for various karez zones in this data-poor basin. Strategies for rehabilitating karezes are discussed. Rehabilitation is financially expensive in comparison to drilling new boreholes, but karezes are part of the national heritage of Afghanistan and can facilitate social cohesion.     

Power interplay between actors: using material and ideational resources to shape local adaptation plans of action (LAPAs) in Nepal

Deliberation over how to adapt to short or long-term impacts of climate change takes place in a complex political setting, where actors’ interests and priorities shape the temporal dimension of adaptation plans, policies and actions. As actors interact to pursue their individual or collective interests, these struggles turn into dynamic power interplay. In this article, we aim to show how power interplay shapes local adaptation plans of action (LAPAs) in Nepal to be short-term and reactive. We use an interactional framing approach through interaction analyses and observations to analyse how actors use material and ideational resources to pursue their interests. Material and ideational resources that an actor deploys include political authority, knowledge of adaptation science and national/local policy-making processes, financial resources and strong relations with international non-governmental organizations and donor agencies. We find that facilitators and local politicians have a very prominent role in meetings relating to LAPAs, resulting in short-termism of LAPAs. Findings suggest that there is also a lack of female participation contributing to short-term orientated plans. We conclude that such power interplay analysis can help to investigate how decision making on the temporal aspects of climate adaptation policy takes place at the local level.

Key policy insights

• Short-termism of LAPAs is attributed to the power interplay between actors during the policy design process.

• Improved participation of the most vulnerable, especially women, can lead to the preparation of adaptation plans and strategies focusing on both the short and long-term.

• It is pertinent to consider power interplay in the design and planning of adaptation policy in order to create a level-playing field between actors for inclusive decision-making.

• Analysis of dynamic power interplay can help in investigating climate change adaptation controversies that are marked by uncertainties and ambiguities.

     

Exploring the spatiotemporal variability of the snow water equivalent in a small boreal forest catchment through observation and modelling

In snow-fed catchments, it is crucial to monitor and model the snow water equivalent (SWE), particularly when simulating the melt water runoff. SWE distribution can, however, be highly heterogeneous, particularly in forested environments. Within these locations, scant studies have explored the spatiotemporal variability in SWE in relation with vegetation characteristics, with only few successful attempts. The aim of this paper is to fill this knowledge gap, through a detailed monitoring at nine locations within a 3.49 km² forested catchment in southern Québec, Canada (47°N, 71°W). The catchment receives an annual average of 633 mm of solid precipitation and is predominantly covered with balsam fir stands. Extracted from intensive field campaign and high-resolution LiDAR data, this study explores the effect of fine scale forest features (tree height, tree diameter, canopy density, leaf area index [LAI], tree density and gap fraction) on the spatiotemporal variability in the SWE distribution. A nested stratified random sampling design was adopted to quantify small-scale variability across the catchment and 1810 manual snow samples were collected throughout the consecutive winters of 2016–17 and 2017–18. This study explored the variability of SWE using coefficients of variation (CV) and relating to the LAI. We also present existing spatiotemporal differences in maximum snow depth across different stands and its relationship with average tree diameter. Furthermore, exploiting key vegetation characteristics, this paper explores different approaches to model SWE, such as multiple linear regression, binary regression tree and neural networks (NN). We were unable to establish any relationship between the CV of SWE and the LAI. However, we observed an increase in maximum snow depth with decreasing tree diameter, suggesting an association between these variables. NN modelling (Nash-Sutcliffe efficiency [NSE] = 0.71) revealed that, snow depth, snowpack age and forest characteristics (tree diameter and tree density) are key controlling variables on SWE. Using only variables that are deemed to be more readily available (snow depth, tree height, snowpack age and elevation), NN performance falls by only 7% (NSE = 0.66).     

Relationships Between Water Table and Model Simulated ET

This research was conducted to develop relationships among evapotranspiration (ET), percolation (PERC), groundwater discharge to the stream (GWQ), and water table fluctuations through a modeling approach. The Soil and Water Assessment Tool (SWAT) hydrologic and crop models were applied in the Big Sunflower River watershed (BSRW; 7660 km²) within the Yazoo River Basin of the Lower Mississippi River alluvial plain. Results of this study showed good to very good model performances with the coefficient of determination (R²) and Nash‐Sutcliffe efficiency (NSE) index from 0.4 to 0.9, respectively, during both hydrologic and crop model calibration and validation. An empirical relationship between ET, PERC, GWQ, and water table fluctuations was able to predict 64% of the water table variation of the alluvial plain in this study. Thematic maps were developed to identify areas with overuse of groundwater, which can help watershed managers to develop water resource programs.     

Application of statistical downscaling in GCMs at constructing the map of precipitation in the Mekong River basin

This study used the Statistical Downscaling Model (SDSM) to increase the resolution of the Global Circulation Model (GCM) at forecasting the amount of precipitation in the Mekong River basin. The model was initially calibrated using the reanalysis data by National Centers for Environmental Prediction (NCEP) and the data on observed precipitation. The results of comparison between the SDSM calculations and the observational data were used to generate the distribution of precipitation until 2099 using HadCM3, SRES A2 and B2 scenarios. After total annual precipitation had been downscaled, the percentage change in precipitation was interpolated among the selected stations in order to create precipitation maps. Both A2 and B2 scenario indicate the possibility of remarkable increase in annual precipitation in the Mekong basin, which may amount to 150 and 110%, respectively. The December–January–February precipitation is likely to increase significantly in the most part of the region, and in some areas, almost by three times. On the contrary, the June–July–August precipitation will remarkably decrease in the different parts of the territory under study. As the water resource sector is the backbone of the economics of this region including hydropower and agricultural sector, the changes in the amount of precipitation and its interannual variability can put the usual water business into stress. Thus, proper adaptive measures should be applied both at local and at regional levels for the benefit of all associated countries utilizing the resource of the Mekong River.