Low Flow Months Research Articles

ASSESSMENT OF SEDIMENT REPLENISHMENT VOLUME IN LANGAT RIVER SYSTEM

The river sand mining activity has taken place in a sand-bed river system in Selangor, Malaysia for decades even before the legalisation was initiated in 2008. This study focuses on the determination of optimum sand extraction for low-flow and high-flow seasons. The sand replenishment rate was used as the benchmark in determining the threshold level of the extractable rate in the Langat River, Selangor system. The total sediment load was computed using Yang (1973) equation due to the high percentage of agreement between the predicted sediment load and measured sediment load. Almost 41.6% of the predicted data fall within the allowable discrepancy ratio test between the predicted value and measured value. The comparison of sand replenishment rate in high and low flow seasons proved that the river system has quicker capabilities in sand replenishment rate at the extraction point during the high-flow season compared to the latter by 83%. The quantifiable volume of the extractable sand rate is proposed specifically during low-flow months (May to September) whereby the slower replenishment rate is critical and riskier. The optimal sand mining volume during the low-flow months is calculated by reducing 10% from the total replenishment volume and the recommended optimum extraction load has been delivered by the number of 25 tons lorries for easier observation by the contractor and authority’s body. The monthly optimum extraction in Langat River during low-flow months is calculated at a minimum of 437 trucks to a maximum of 20,114 trucks per month.

Time-varying network-based approach for capturing hydrological extremes under climate change with application on drought

Hydrologic extremes often lead to droughts and floods that adversely affect the socio-economic development. Change in the characteristics and causes of hydrologic extremes due to climate variability and climate change poses a challenge for its reliable prediction. We propose a time-varying approach to capture such temporal changes, often gradual, in hydrologic extremes through temporal networks (a series of network structures). Graphical Modelling (GM) based networks are developed through Bayesian Model Averaging (BMA) to deal with the complexity between the causal variables and extreme events. A demonstration of the proposed time-varying approach is shown for 1-month and 3-month ahead hydrological drought prediction in terms of Standardized Streamflow Anomaly Index (SSAI), at basin scale, that has notably changed in the recent years in terms of its frequency and severity. The frequency and severity of below-normal flow events has increased, particularly during the monsoon season (high flow months). We hypothesize that time-varying cause-effect relationship is important to capture such gradual change in the characteristics of hydrologic extremes. The results indicate that SSAI values for the low flow months are strongly associated with streamflow whereas for the high flow months the dominant predictors are rainfall, precipitable water and relative humidity. Furthermore, the cause-effect relationship between hydroclimatic variables and extreme events needs to be updated every 2 years for high flow and 3 years for low flow months. The proposed model very well captures the above and below-normal flow events and can be used as a remedial measure to handle similar cases through a proper assessment of time-varying cause-effect relationship between hydroclimatic variables and extreme events.

Changes in monthly streamflow in the Hindukush–Karakoram–Himalaya Region of Pakistan using innovative polygon trend analysis

The present study explored the changes in monthly streamflow in the Hindukush–Karakoram–Himalaya (HKH) region within Pakistan using the recently developed trend analysis method known as innovative polygon trend analysis (IPTA). The monthly streamflow data of 34 gauging stations installed in the HKH region was analyzed, and the Pettitt test was applied to check the homogeneity of the time series. The entire study area was divided into 13 sub-basins, and then changes in monthly streamflow of each sub-basin were explored using the IPTA method. The streamflow of high elevated glaciated and snow/ice-covered sub-basins (e.g., Shyok, Astore, and Chitral) have increased in high flow months (June–August), where there is a downward trend for the Hunza sub-basin in these months. In the Gilgit sub-basin, a transition occurred from no trend in May to a decreasing trend from June to August. The upstream gauges of Swat and Kabul sub-basins showed an increasing trend throughout the year, while downstream gauging stations in the same sub-basins exhibited a strong decreasing trend only in high flow months (June–August). The upper reaches of the Indus part in the Upper Indus Basin (UIB) showed increasing trends in high flow months (June–August), however the downstream gauges of UIB showed decreasing trends throughout the year. Overall, only the glaciated and snow/ice-covered sub-basins experienced increasing trends, while most other sub-basins faced decreasing trends in high flow months and increasing trends in low flow months (October–March). The enhancement of the seasonal pattern of streamflow in the upper reaches of UIB is possibly due to the melting of snow and ice that potentially influence floods and hydropower generation. The results of this study can result in a better understanding of the hydrology of the HKH region and support sustainable water management.

Water Temperature and Hydrological Modelling in the Context of Environmental Flows and Future Climate Change: Case Study of the Wilmot River (Canada)

Simulation of surface water flow and temperature under a non-stationary, anthropogenically impacted climate is critical for water resource decision makers, especially in the context of environmental flow determination. Two climate change scenarios were employed to predict streamflow and temperature: RCP 8.5, the most pessimistic with regards to climate change, and RCP 4.5, a more optimistic scenario where greenhouse gas emissions peak in 2040. Two periods, 2018–2050 and 2051–2100, were also evaluated. In Canada, a number of modelling studies have shown that many regions will likely be faced with higher winter flow and lower summer flows. The CEQUEAU hydrological and water temperature model was calibrated and validated for the Wilmot River, Canada, using historic data for flow and temperature. Total annual precipitation in the region was found to remain stable under RCP 4.5 and increase over time under RCP 8.5. Median stream flow was expected to increase over present levels in the low flow months of August and September. However, increased climate variability led to higher numbers of periodic extreme low flow events and little change to the frequency of extreme high flow events. The effective increase in water temperature was four-fold greater in winter with an approximate mean difference of 4 °C, while the change was only 1 °C in summer. Overall implications for native coldwater fishes and water abstraction are not severe, except for the potential for more variability, and hence periodic extreme low flow/high temperature events.

Predicting mean annual and mean monthly streamflow in Colorado ungauged basins

AbstractRiver managers often need estimates of streamflow for ungauged streams. These estimates can be used in water rights acquisitions, in‐stream flow management, habitat assessment, water quality planning, and stream hazard identification. This publication describes new regression models for predicting mean annual and mean monthly streamflow in Colorado. Unlike previous regional regression studies, the new models incorporate snow persistence (SP), the fraction of time a watershed remains snow covered. Models were developed using streamflow data from 131 watersheds with drainage areas <1,500 km2, no transbasin diversions, and <10% urban area. In addition to SP, topographic, climate, geologic, and hydrologic region variables were used in model predictions. All new models had very good performance, with <6% absolute bias and stronger performance compared to current regional regression models in StreamStats. The mean annual model had the strongest performance, with Nash‐Sutcliffe efficiency coefficient (NSE) of 0.93 and <2% absolute bias. Mean monthly models had best performance during snowmelt runoff months (May‐Jul; NSE ≥0.79; absolute % bias ≤ 4) and weaker performance during low flow months (Aug‐Apr; NSE ≥ 0.59; % bias ≤ 5). Tests of the mean annual model using decadal average streamflow from 1910s to 2000s show very good performance (NSE > 0.75), but predictions were biased low by 14–28% in wetter decades. All equations and coefficients needed to run the models are presented in the publication appendix, and the associated data release includes the spatial data and model code, which can be applied using R or within an R‐based Shiny web app.

Hydrologic impacts and trade-offs associated with developing oil palm for bioenergy in Tabasco, Mexico

Study regionOil palm cultivation has rapidly expanded worldwide due to demands for food oils and the potential for liquid fuel production. However, there is a scarcity of research on the hydrologic impacts of oil palm plantations at a watershed scale, especially in Latin America. We focus on a watershed typical of intensive palm oil production in Tabasco, Mexico. Study focusA Soil and Water Assessment Tool model was calibrated to simulate long-term streamflow in the study watershed. The plant growth module was calibrated for leaf area index (LAI) and fruit yield simulations. Oil palm development scenarios were simulated to investigate the impacts of planting density and converted land cover types. New hydrological insights for the regionOil palm evapotranspiration rates were 51 % higher on average than the converted land covers. The higher water use reduced mean annual streamflow by only 9% at the watershed scale, due to high precipitation in the upper watershed. In contrast, a 15 % decline in annual water yield was simulated in the converted areas of the watershed. Corresponding streamflow reductions in low-flow months were on average 34 %. A planting density of 150 palm/ha was the most efficient for water use and fruit production, giving a green water footprint for producing biodiesel of 87 m3/GJ energy, similar to oil palm cultivation elsewhere in the world.

Changes in the vertical distribution of hyporheic and benthic fauna associated with low flow conditions in the headwaters of the Tafna river (northwest Algeria)

This study investigated temporal changes in the vertical distribution of invertebrates during periods of low flows in the Tafna wadi, a semi-arid Mediterranean river characterised by a general decline in average flows. The hyporheos was sampled along a 130-m stretch at depths of 0.3, 0.6 and 1 m in a pool-riffle sequence and a lateral gravel bar. Benthic fauna was collected on each sampling occasion from different locations in the studied sections. Sampling was conducted in two consecutive years (2014 and 2015) at the end of the spring (high waters) and over a 2-month period during the low summer flow. The results indicated that high surface water temperatures may initiate the movement of some taxa into the interstitial habitat, thus supporting the hyporheic refuge hypothesis. In the hyporheic zone, the low oxygen rates recorded deeper in the sediment and in the last low-flow months caused significant declines in taxonomic richness, and lower pH values resulted in a reduction in invertebrate abundances. In the benthic zone, high flow velocities increased richness but decreased invertebrate abundances. A large number of taxa were found in the gravel bar section reflecting the more suitable living conditions in this habitat compared with the river reach (high DO rates).

Temporal Networks‐Based Approach for Nonstationary Hydroclimatic Modeling and its Demonstration With Streamflow Prediction

AbstractLack of stationarity in most of the hydroclimatic variables is no longer a topic of debate rather a reality. It may be hypothesized that alternative methodologies are needed to deal with such nonstationarity and to improve the skill of hydroclimatic modeling/prediction. We propose the concept oftemporal networksin hydroclimatic modeling as a potential solution to this problem. As a typical case, complex association among different hydroclimatic variables and streamflow is considered as an illustrative problem. Evolution of temporal networks over time, obtained through Graphical Modeling (GM), depicts the changes in the model inputs as well as model parameters over time. The proposed concept indicates that the time interval after which the model needs to be updated/recalibrated, referred to as Optimum Recurrence Interval (ORI), is problem specific and is optimized to achieve the best model performance. The proposed concept not only depicts a notable change in the potential predictors for the high and low flow months, but also establishes the different extent of temporal variability for different months, and hence the ORI of model recalibration. As compared to its time‐invariant counterpart, the temporal networks‐based approach shows higher efficacy in capturing the extreme flow events due to its inherent time‐varying characteristics. We recommend the concept of temporal networks to be promising in the context of climate change to capture the time‐varying association. In general, the concept can be applied to other hydroclimatic variables where a time‐varying association is expected due to various reasons including the impacts of climate change.

A preliminary assessment of environmental flow in the three rivers' source region, Qinghai Tibetan Plateau, China and suggestions

The three rivers' source region (TRSR) located in the Qinghai-Tibetan Plateau is an important ecological region of China for its location and high elevation. However, the ecological condition of the region is critical to water conservation and ecological security in China. Therefore, the present study focused on determining the environmental flow requirements (EFRs) of the Lancang (above Xiangda streamflow gauge), Yangtze (Zhimenda), and Yellow (Tangnaihai) Rivers, which will be helpful in the sustainable development of the region. Because of lacking ecological data, we used four hydrological methods (i.e., flow duration curve shifting, Tennant, flow duration curve analysis, and low flow index method) to assess the EFRs for the minimum and optimum eco-environmental conditions of these rivers. Since there was missing data on most gauges and we had streamflow data of only one gauge (Zhimenda) in the Yangtze headwater region, a hydrological model was applied to complete the missing data and simulate the streamflow data for the Tuotuo, DamChu, Chumar, and Tongtian Rivers for the estimation of the EFRs insides the region. The environmental flows of 118 m3/s (76% of mean annual flow, MAF), 312 m3/s (72% of MAF), 484 m3/s (77% of MAF) were determined for the conservation of the optimum riverine ecosystem and 67 m3/s (43% of MAF), 155 m3/s (36% of MAF), and 290 m3/s (47% of MAF) for the minimum eco-environmental conditions for the Lancang, Yangtze, Yellow Rivers, respectively. It was also noticed that low flow months (November to April) required more proportions of mean monthly flow than high flow months (May to October). These preliminary results will be very supportive of the water resources managers and policymakers in the case of any sustainable socio-economic development in the region.

Predicted and Projected Water Resources Changes in the Chari Catchment, the Lake Chad Basin, Africa

AbstractThe water resources of the Chari River basin, contributing more than 90% of the water to one of the largest lakes in Africa, known as Lake Chad, are highly vulnerable to natural and anthropogenic changes. Therefore, the changes in water resources were predicted for the next 20 years (i.e., 2016–35) by using the harmonic regression model (HRM), one of the most sophisticated time series methods, and also projected under representative concentration pathways (RCPs) by using the multimodel approach for the periods 2021–50, 2051–80, and 2081–2100, with respect to the baseline period (1971–2001). The Tropical Rainfall Measuring Mission (TRMM), Climatic Research Unit (CRU), and dynamically downscaled climatic data were used in the analysis of the present study. The results showed that under MME-RCP2.6 (multimodel ensemble of RCMs), low flow (average of low-flow months, December–July), high flow (August–November), and annual flow were projected to decrease in the future. In contrast, under MME-RCP4.5 and MME-RCP8.5, high and annual flows were projected to increase in all three time horizons, while low flow will decrease except in 2021–50 under MME-RCP8.5. In the next two decades, the HRM showed decrease in all type of flows (low, high, and annual), very similar to the results under MME-RCP2.6 for the same period. In contrast, almost all flows are expected to increase under MME-RCP4.5 and MME-RCP8.5 in the next two decades. On the whole, the flows are expected to decrease under the HRM and RCP2.6 but to increase under RCP4.5 and RCP8.5.

Potential of the Molawin creek for micro hydro power generation: An assessment

The hydropower potential of the Molawin creek in Laguna, Philippines was evaluated. The river flows along the Molawin-Dampalit subwatershed and was declared a BioPark to protect and develop the flora and fauna. The abundant BioPark resource could showcase beneficial products and technologies for communities in mountainous areas. The study aims to propose methods to assess hydropower potential that can be applied to rivers and small water resources. Limited studies were done on the watershed. Previous hydropower studies were based on elevation alone. Hydrographic survey and analysis for gauged and ungauged locations were done. The Hydrologic Frequency Analysis (HFA), rational equation and Flow Duration Curve (FDC) were used to analyze the actual and simulated streamflow data.The HFA Log Pearson III distribution best fits both actual and simulated data. The rational equation overestimated the streamflow. The Plant Capacity Factor (PCF) was obtained using the FDC. The FDC generated from actual streamflow was used for turbine ratings because the simulated data gave unrealistic PCF results. It is recommended to have two Kaplan turbines, one operational during low flow months and two on months of high flow. The PCF at turbine rating of 2.3–7.5 kW and 1.9–5.5 kW were 49.9% and 51.8%, respectively.

Quantification of Environmental Flow Requirement of the Khun Dan Prakan Chon Dam Using Hydrological-Hydraulic-Habitat Simulation Methods

With increased water demand, reservoir operation has become more complex with the need to quantify the exact amount of water needed for each demand sector. The environmental flow requirement, also known as instream flow is regarded as the first-prioritized objective of the multipurpose water resources projects in Thailand. The capability of reservoirs in Thailand to allocate water for environmental needs depends on available supply, strategies and operating policy. Therefore, this study aims to assess the environmental flow requirements of Khun Dan PrakanChon Dam using three methods; 1) the hydrological method (Tennant, Tessmann, 7Q10, FDC, and VMF), 2) hydraulic method (R2CROSS and wetted perimeter) and 3) habitat simu-lationmethod, using the PHABSIM model for physical habitat simulation of aquatic organisms in the Nakhon Nayok River. The hydrological approach was performed under the historically-naturalized flow data of the NY.1B station and established hydrologic flow regime during low flow and high flow months. The environmental flow rates obtained from two hydraulic methods were based upon field observations at the NY.1B station significantly. However, the biological conditions and interactions of aquatic organisms in the river were not principally characterized in hydrologic and hydraulic approaches. In addition, the estimated results performed by habitat simulation model gave an additional meaning of ecological flow needs mainly for aquatic habitat conservation in the river. By integrating the conditions of hydrologic and hydraulic flow regimes as well as the habitat conservation objectives, environmental flow rates of 8-10 cm were recommended to determine the downstream release of Khun Dan Prakan Chon Dam; these recommendations were very close to those derived using the Tessmann, 7Q10 and PHABSIM methods-Tennant and flow duration curve methods.

Climate change impacts and greenhouse gas mitigation effects on U.S. hydropower generation

Climate change will have potentially significant effects on hydropower generation due to changes in the magnitude and seasonality of river runoff and increases in reservoir evaporation. These physical impacts will in turn have economic consequences through both producer revenues and consumer expenditures. We analyze the physical and economic effects of changes in hydropower generation for the contiguous U.S. in futures with and without global-scale greenhouse gas (GHG) mitigation, and across patterns from 18 General Circulation Models. Using a monthly water resources systems model of 2119 river basins that routes simulated river runoff through reservoirs, and allocates water to potentially conflicting and climate dependent demands, we provide a first-order estimate of the impacts of various projected emissions outcomes on hydropower generation, and monetize these impacts using outputs from an electric sector planning model for over 500 of the largest U.S. hydropower facilities. We find that, due to generally increasing river runoff under higher emissions scenarios in the Pacific Northwest, climate change tends to increase overall hydropower generation in the contiguous U.S. During low flow months, generation tends to fall with increasing emissions, potentially threatening the estimated low flow, firm energy from hydropower. Although global GHG mitigation slows the growth in hydropower generation, the higher value placed on carbon-free hydropower leads to annual economic benefits ranging from $1.8 billion to $4.3 billion. The present value of these benefits to the U.S. from global greenhouse gas mitigation, discounted at 3%, is $34 to $45 billion over the 2015–2050 period.

Changes in monthly flows in the Yangtze River, China – With special reference to the Three Gorges Dam

Summary Much has been written on the hydrology of the Yangtze River in China, especially since the construction of the Three Gorges Dam. Given the range of views in the literature on the impacts of dams and other natural and anthropogenic activities in the catchment on monthly flows, we here set out to analyse the behavior of monthly flows over the period of record 1955–2014. In the literature, the Three Gorges dam has been singled out for particular comment, mostly adverse. In this paper we analyse trend in temperature, precipitation and discharge of the Yangtze River at the monthly time scale over a period that includes the 11 years since the Three Gorges Dam came into operation. The results show that for the upper basin, there has been a marked increase in discharge in the low flow months of January to March that began abruptly in 2003 and an abrupt decrease in flow in October at the same time. Similar changes are found for discharge from the lower basin but in that case the changes have occurred gradually over the period of record. These changes are the outcome of the operation of hydroelectric and flood control dams that have been built continuously in the lower basin since 1955 while in the upper basin the building of the Three Gorges Dam began a phase of rapid dam building not seen in the lower basin. The decreased flows in the late summer and autumn are not of sufficient magnitude to cause any problems for navigation or water supply. The enhanced flows in the winter low flow period are beneficial in that they reduce the likelihood of salt water intrusions in the estuary adversely affecting the supply of freshwater to Shanghai.

The assessment of water use and reuse through reported data: A US case study

Increasing demands for freshwater make it necessary to find innovative ways to extend the life of our water resources, and to manage them in a sustainable way. Indirect water reuse plays a role in meeting freshwater demands but there is limited documentation of it. There is a need to analyze its current status for water resources planning and conservation, and for understanding how it potentially impacts human health. However, the fact that data are archived in discrete uncoordinated databases by different state and federal entities, limits the capacity to complete holistic analysis of critical resources at large watershed scales. Humans alter the water cycle for food production, manufacturing, energy production, provision of potable water and recreation. Ecosystems services are affected at watershed scales but there are also global scale impacts from greenhouse gas emissions enabled by access to cooling, processing and irrigation water. To better document these issues and to demonstrate the utility of such an analysis, we studied the Wabash River Watershed located in the U.S. Midwest. Data for water extraction, use, discharge, and river flow were collected, curated and reorganized in order to characterize the water use and reuse within the basin. Indirect water reuse was estimated by comparing treated wastewater discharges with stream flows at selected points within the watershed. Results show that during the low flow months of July–October, wastewater discharges into the Wabash River basin contributed 82 to 121% of the stream flow, demonstrating that the level of water use and unplanned reuse is significant. These results suggest that intentional water reuse for consumptive purposes such as landscape or agricultural irrigation could have substantial ecological impacts by diminishing stream flow during vulnerable low flow periods.

Accounting for environmental flow requirements in global water assessments

Abstract. As the water requirement for food production and other human needs grows, quantification of environmental flow requirements (EFRs) is necessary to assess the amount of water needed to sustain freshwater ecosystems. EFRs are the result of the quantification of water necessary to sustain the riverine ecosystem, which is calculated from the mean of an environmental flow (EF) method. In this study, five EF methods for calculating EFRs were compared with 11 case studies of locally assessed EFRs. We used three existing methods (Smakhtin, Tennant, and Tessmann) and two newly developed methods (the variable monthly flow method (VMF) and the Q90_Q50 method). All methods were compared globally and validated at local scales while mimicking the natural flow regime. The VMF and the Tessmann methods use algorithms to classify the flow regime into high, intermediate, and low-flow months and they take into account intra-annual variability by allocating EFRs with a percentage of mean monthly flow (MMF). The Q90_Q50 method allocates annual flow quantiles (Q90 and Q50) depending on the flow season. The results showed that, on average, 37% of annual discharge was required to sustain environmental flow requirement. More water is needed for environmental flows during low-flow periods (46–71% of average low-flows) compared to high-flow periods (17–45% of average high-flows). Environmental flow requirements estimates from the Tennant, Q90_Q50, and Smakhtin methods were higher than the locally calculated EFRs for river systems with relatively stable flows and were lower than the locally calculated EFRs for rivers with variable flows. The VMF and Tessmann methods showed the highest correlation with the locally calculated EFRs (R2=0.91). The main difference between the Tessmann and VMF methods is that the Tessmann method allocates all water to EFRs in low-flow periods while the VMF method allocates 60% of the flow in low-flow periods. Thus, other water sectors such as irrigation can withdraw up to 40% of the flow during the low-flow season and freshwater ecosystems can still be kept in reasonable ecological condition. The global applicability of the five methods was tested using the global vegetation and the Lund-Potsdam-Jena managed land (LPJmL) hydrological model. The calculated global annual EFRs for fair ecological conditions represent between 25 and 46% of mean annual flow (MAF). Variable flow regimes, such as the Nile, have lower EFRs (ranging from 12 to 48% of MAF) than stable tropical regimes such as the Amazon (which has EFRs ranging from 30 to 67% of MAF).

Estimation of watershed hydrologic processes in arid conditions with a modified watershed model

Watershed models play an important role in modern water resource management, increasingly demanding a robust hydrologic data framework to estimate watershed hydrochemical processes. The Generalized Watershed Loading Function (GWLF), a typical watershed model with modest data requirements, has been applied to watershed-scale hydrochemical estimation worldwide. However, while it generally successfully estimates flows in humid regions, the model suffers from a weakness in hydrologic estimation during low-flow periods, which are projected to continue increasing with global climate change in many places. To address this issue, three algorithms describing functional responses of flows to saturated water storage, the segment function approach, linear function approach, and exponential function approach, have been proposed in this paper, integrated with a previous leakage mechanism for unsaturated water storage used in two earlier GWLF versions, and applied to a case study of Shuai Shui River watershed in China. Comparisons of this version, including new algorithms or algorithm linkages, with the earlier GWLF versions, show that all the new algorithms improve model accuracy in low-flow months; the linear function approach linking the leakage process has the best effect. This work refines the framework of GWLF model to address both humid and arid conditions that can be used as alternatives for future applications. These new functional dynamic responses should also have potential application in other similar watershed models.

The role of small scale sand dams in securing water supply under climate change in Ethiopia

Community-based water storage in semi arid areas can help to adapt to climate change and mitigate household water shortages. Since little is known on the downstream effects of local water storage, this study employs a water balance model to perform a catchment scale assessment of upscaling local scale water storage in sand dams. The impacts of increasing water storage is evaluated under current climate conditions and future climate change scenarios. Survey information is used to estimate current and future water demand and assess the benefits derived from current sand dams in the Ethiopian study area. Using an indicator of the environmental flow concept, downstream hydrological impacts are simulated for different scenarios. Storage by 613 dams, supplying water to 555,000 people, has no impact on environmental flow downstream of the sand dams. Storage by 2190 dams leads to a modest increase in the number of months with low flow (4 to 9 %). Projected climate change leads to a larger increase in the number of low flow months of 0 to 29 %. Joint climate change and maximum storage scenarios cause an increase in low flow months from 4 to 50 %. Under the most extreme climate change projection 4.5 % of the wet season discharge is stored in sand dams. Because of the local benefits of improved water supply and the acceptable range of downstream impacts, sand dams appear to be a viable way for supplying drinking water in this catchment as well as in other semi-arid regions with similar conditions.

Community structure of aquatic insects in the Esparza River, Costa Rica

This study focused on the structure of the aquatic insect community in spatial and temporal scales in the Esparza River. The river was sampled for one full year throughout 2007. During the dry season low flow months, five sampling points were selected in two different habitats (currents and pools), with five replicates per sample site. During the wet season with peak rain, only the data in the "current habitat" were sampled at each site. Specimens present in the different substrates were collected and preserved in situ. A nested ANOVA was then applied to the data to determine richness and density as the response variables. The variations in temporal and spatial scales were analyzed using width, depth and discharge of the river, and then analyzed using a nested ANOVA. Only a correlation of 51% similarity in richness was found, while in spatial scale, richness showed significant variation between sampling sites, but not between habitats. However, the temporal scale showed significant differences between habitats. Density showed differences between sites and habitats during the dry season in the spatial scale, while in the temporal scale significant variation was found between sampling sites. Width varied between habitats during the dry season, but not between sampling points. Depth showed differences between sampling sites and season. This work studies the importance of community structure of aquatic insects in rivers, and its relevance for the quality of water in rivers and streams.

Reallocating water from canal irrigation for environmental flows: benefits forgone in the Upper Ganga Basin in India

This paper assesses the potential loss of irrigation benefits in reallocating water from irrigation to meet requirements for environmental flows (e-flows) in the Upper Ganga Basin (UGB) in northern India. The minimum requirement for e-flows in the UGB is 32 billion cubic meters (BCM), or 42 % of the mean annual runoff. The current runoff during the low-flow months falls below the minimum requirement for e-flows by 5.1 BCM. Depending on irrigation efficiency, reallocation of 41–51 % of the water from canal irrigation withdrawals can meet this deficit in minimum e-flows. The marginal productivity of canal irrigation consumptive water use (CWU), estimated from a panel regression with data from 32 districts from 1991 to 2004, assesses the potential loss of benefits in diverting water away from crop production. In the UGB, canal irrigation contributes to only 8 % of the total CWU of 56 BCM, and the marginal productivity of canal irrigation CWU across districts is also very low, with a median of 0.03 USD/m3. Therefore, at present, the loss of benefits is only 1.2–1.6 % of the gross value of crop production. This loss of benefits can be overcome with an increase in irrigation efficiency or marginal productivity.