Irrigation Water Allocation Using an Inexact Two‐Stage Quadratic Programming with Fuzzy Input under Climate Change

Agricultural irrigation accounts for nearly 70% of the total water use around the world. Uncertainties and climate change together exacerbate the complexity of optimal allocation of water resources for irrigation. An interval‐fuzzy two‐stage stochastic quadratic programming model is developed for determining the plans for water allocation for irrigation with maximum benefits. The model is shown to be applicable when inputs are expressed as discrete, fuzzy or random. In order to reflect the effect of marginal utility on benefit and cost, the model can also deal with nonlinearities in the objective function. Results from applying the model to a case study in the middle reaches of the Heihe River basin, China, show schemes for water allocation for irrigation of different crops in every month of the crop growth period under various flow levels are effective for achieving high economic benefits. Different climate change scenarios are used to analyze the impact of changing water requirement and water availability on irrigation water allocation. The proposed model can aid the decision maker in formulating desired irrigation water management policies in the wake of uncertainties and changing environment.     

Water Management Decision Making in the Face of Multiple Forms of Uncertainty and Risk

In the Wasatch Range Metropolitan Area of Northern Utah, water management decision makers confront multiple forms of uncertainty and risk. Adapting to these uncertainties and risks is critical for maintaining the long‐term sustainability of the region's water supply. This study draws on interview data to assess the major challenges climatic and social changes pose to Utah's water future, as well as potential solutions. The study identifies the water management adaptation decision‐making space shaped by the interacting institutional, social, economic, political, and biophysical processes that enable and constrain sustainable water management. The study finds water managers and other water actors see challenges related to reallocating water, including equitable water transfers and stakeholder cooperation, addressing population growth, and locating additional water supplies, as more problematic than the challenges posed by climate change. Furthermore, there is significant disagreement between water actors over how to best adapt to both climatic and social changes. This study concludes with a discussion of the path dependencies that present challenges to adaptive water management decision making, as well as opportunities for the pursuit of a new water management paradigm based on soft‐path solutions. Such knowledge is useful for understanding the institutional and social adaptations needed for water management to successfully address future uncertainties and risks.     

Sensitivity and Uncertainty of Ground‐Water Discharge Estimates for Semiarid Shrublands1

Abstract: We proposed a step‐by‐step approach to quantify the sensitivity of ground‐water discharge by evapotranspiration (ET) to three categories of independent input variables. To illustrate the approach, we adopt a basic ground‐water discharge estimation model, in which the volume of ground water lost to ET was computed as the product of the ground‐water discharge rate and the associated area. The ground‐water discharge rate was assumed to equal the ET rate minus local precipitation. The objective of this study is to outline a step‐by‐step procedure to quantify the contributions from individual independent variable uncertainties to the uncertainty of total ground‐water discharge estimates; the independent variables include ET rates of individual ET units, areas associated with the ET units, and precipitation in each subbasin. The specific goal is to guide future characterization efforts by better targeting data collection for those variables most responsible for uncertainty in ground‐water discharge estimates. The influential independent variables to be included in the sensitivity analysis are first selected based on the physical characteristics and model structure. Both regression coefficients and standardized regression coefficients for the selected independent variables are calculated using the results from sampling‐based Monte Carlo simulations. Results illustrate that, while as many as 630 independent variables potentially contribute to the calculation of the total annual ground‐water discharge for the case study area, a selection of seven independent variables could be used to develop an accurate regression model, accounting for more than 96% of the total variance in ground‐water discharge. Results indicate that the variability of ET rate for moderately dense desert shrubland contributes to about 75% of the variance in the total ground‐water discharge estimates. These results point to a need to better quantify ET rates for moderately dense shrubland to reduce overall uncertainty in estimates of ground‐water discharge. While the approach proposed here uses a basic ground‐water discharge model taken from an earlier study, the procedure of quantifying uncertainty and sensitivity can be generalized to handle other types of environmental models involving large numbers of independent variables.     

Modeling Postfire Response and Recovery using the Hydrologic Engineering Center Hydrologic Modeling System (HEC‐HMS)1

Abstract: This paper investigates application of the Army Corps of Engineers’ Hydrologic Engineering Center Hydrologic Modeling System (HEC‐HMS) to a burned watershed in San Bernardino County, California. We evaluate the HEC‐HMS’ ability to simulate discharge in prefire and postfire conditions in a semi arid watershed and the necessary parameterizations for modeling hydrologic response during the immediate, and subsequent recovery, period after a wildfire. The model is applied to City Creek watershed, which was 90% burned during the Old Fire of October 2003. An optimal spatial resolution for the HEC‐HMS model was chosen based on an initial sensitivity analysis of subbasin configurations and related model performance. Five prefire storms were calibrated for the selected model resolution, defining a set of parameters that reasonably simulate prefire conditions. Six postfire storms, two from each of the following rainy (winter) seasons were then selected to simulate postfire response and evaluate relative changes in parameter values and model behavior. There were clear trends in the postfire parameters [initial abstractions (I_a), curve number (CN), and lag time] that reveal significant (and expected) changes in watershed behavior. CN returns to prefire (baseline) values by the end of Year 2, while I_a approaches baseline by the end of the third rainy season. However, lag time remains significantly lower than prefire values throughout the three‐year study period. Our results indicate that recovery of soil conditions and related runoff response is not entirely evidenced by the end of the study period (three rainy seasons postfire). Understanding the evolution of the land surface and related hydrologic properties during the highly dynamic postfire period, and accounting for these changes in model parameterizations, will allow for more accurate and reliable discharge simulations in both the immediate, and subsequent, rainy seasons following fire.     

Field Evaluation of DRAINMOD 5.1 Under a Cold Climate: Simulation of Daily Midspan Water Table Depths and Drain Outflows1

Abstract: The hydrologic performance of DRAINMOD 5.1 was assessed for the southern Quebec region considering freezing/thawing conditions. A tile drained agricultural field in the Pike River watershed was instrumented to measure tile drainage volumes. The model was calibrated using water table depth and subsurface flow data over a two‐year period, while another two‐year dataset served to validate the model. DRAINMOD 5.1 accurately simulated the timing and magnitude of subsurface drainage events. The model also simulated the pattern of water table fluctuations with a good degree of accuracy. The R² between the observed and simulated daily WTD for calibration was >0.78, and that for validation was 0.93. The corresponding coefficients of efficiency (E) were >0.74 and 0.31. The R² and E values for calibration/validation of subsurface flow were 0.73/0.48 and 0.72/0.40, respectively. DRAINMOD simulated monthly subsurface flow quite accurately (E > 0.82 and R² > 0.84). The model precisely simulated daily/monthly drain flow over the entire year, including the winter months. Thus DRAINMOD 5.1 performed well in simulating the hydrology of a cold region.     

Conversion of a Missouri River Dam and Reservoir to a Sustainable System: Sediment Management1

Abstract: A present and future challenge for water resources engineers is to extend the useful life of our dams and reservoirs. Ongoing reservoir sedimentation in impoundments must be addressed; sedimentation in many reservoirs already limits project benefits and effective project life. Sustainability requires that incoming sediment be moved downstream past the impounding dam. We use Lewis and Clark Lake, the most downstream of the six Missouri River main stem reservoirs, to demonstrate how a reservoir in advanced stages of its project life could be converted to a sustainable system with local benefits exceeding costs by a factor of 1.5. Full consideration of benefits would further enhance project justification. The proposed strategy involves four phases that will take about 50 years to complete. Cost estimates for this potential project range from the quantitative to the plausible, but it is clear that the results justify a full engineering, environmental, and economic study of this model project. If implemented, the project will create scientific knowledge and develop technologies useful for achieving sustainability at many other reservoirs in the Mississippi River basin and beyond.     

Seasonal temperatures have more influence than nitrogen fertilizer rates on cucumber yield and nitrogen uptake in a double cropping system

Two-year greenhouse cucumber experiments were conducted to investigate seasonal effects on fruit yield, dry matter allocation, and N uptake in a double-cropping system with different fertilizer management. Seasonal effects were much greater than fertilizer effects, and winter-spring (WS) cucumber attained higher fruit yields and N uptake than autumn-winter (AW) cucumber due to lower cumulative air temperatures during fruit maturation in the AW season. Fertilizer N application and apparent N loss under recommended N management (Nmr) decreased by 40-78% and 33-48% without yield loss compared to conventional N management (Nmt) over four growing seasons. However, there were no seasonal differences in N recommendations, taking into consideration seasonal differences in crop N demand, critical nutrient supply in the root zone and N mineralization rate.     

碳氮磷比失调对污水生物脱氮除磷的影响

我国南方城市污水普遍存在低碳相对高氮磷特征,本文介绍了同时生物脱氮除磷的机理、对碳源的需求与竞争,以及一些针对此类污水生物脱氮除磷的改进工艺及其在实际运用中的效果,并对此类污水的处理方向进行了展望。     

富氧空位/梯次结构CeO2的制备及光催化CO2还原

采用Ce-BTC(均苯三甲酸)为模板,通过尿素溶液浸渍合成了具有富氧空位/梯次结构的CeO₂催化剂,并用X射线衍射(XRD)、扫描电子显微镜(SEM)、透射电子显微镜(TEM)、拉曼光谱(Raman)和紫外可见漫反射(DRS)等手段对其进行了表征.结果表明,与金属有机框架(MOFs)浸渍尿素高温煅烧可以获得金属氧化物/g-C₃N₄复合材料不同,Ce-BTC/尿素体系煅烧后产品中未检测到g-C₃N₄,这可能与CeO₂的存在抑制了尿素分解产物的热缩聚过程,影响了g-C₃N₄的生成有关,但尿素的引入改变了Ce-BTC煅烧产物CeO₂的氧空位浓度,且获得梯次结构.将具有富氧空位/梯次结构的CeO₂-5用于光催化CO₂还原,催化结果表明:反应4h的CO产率可达2.06μmol/g,CH₄产率可达1.42μmol/g,性能是Ce-BTC未...