World Environmental and Water Resources Congress 2019: Watershed Management, Irrigation and Drainage, and Water Resources Planning and Management

The estimation of crop water requirement (CWR) is an important aspect in efficient usage of water, especially in regions where water is scarce. This study estimates the change in agricultural land of major crops in Gujranwala District due to urbanization using remote sensing. The irrigation water demand (IWD) and irrigation cost are computed for the study years of 1992, 1995, 2000, 2008, 2014, and 2016. Wheat and rice are studied as they are the major crops grown in the district. Remote sensing image classification was used to prepare the land use maps and estimate cropping area. Evapotranspiration-based CWR was estimated using ET_o calculator from FAO and crop coefficient (K_c) of each crop. Finally, using the water pricing for the province, change in cost of irrigation due to variation in IWD is computed. The results show that the urban area has doubled from 20 to 40 thousand hectares between 1992 and 2016 with the area sown under wheat and rice decreased by 10% and 19%, respectively. The CWR value for 2016 was 381 and 605 mm/season for wheat and rice, respectively. Between 1992 and 2016, IWD of wheat [measured in million acre-feet/year (MAF)] decreased from 0.83 to 0.70 whereas it reduced from 1.47 to 1.03 MAF for rice. During this period, the total cost of water (in million USD) for wheat varied between 0.65 and 0.33 and for rice varied between 1.69 and 0.84. Use of remotely sensed image displayed the spatiotemporal distribution of urban expansion as well as of wheat and rice within the district. This information can play a key role in tracking the state of agricultural activity and efficient agricultural water distribution.

Freshwater natural wetlands are under threat of environmental degradation due to the anthropogenic and natural activities. In some cases, wetlands are transformed into manmade water reservoirs which have resulted in waterlogged and salinity problems in the nearby areas. Conversion of Chotiari natural wetland into the off canal manmade Chotiari Reservoir is a typical example of unsustainable irrigation project in Pakistan. A study was conducted to quantify the impact of construction of a reservoir on the vegetation and waterlogging in the adjacent areas of the reservoir using remote sensing and geospatial tools. The analysis of satellite imagery of the 5 km buffer around the periphery of the reservoir revealed that before the conversion of the lake into the reservoir about 2594 ha (4.6% of the buffer area) was waterlogged which increased to 6850 ha (12.1%) in the year 2017. The salt-affected area was 4786 ha (8.5%) which increased to 7364 ha (13%) in the year 2017. Thus, about 2578 ha (4.5%) of the fertile agricultural land changed into unproductive salt-affected soil. About 9% of natural vegetation within lake boundaries decreased due to conversion of natural wetland into the reservoir and resulted in degradation of lake and environmental disaster.

Current in-canopy sprinkler packages can allow center pivot irrigation systems to operate more efficiently and uniformly, however, these in-canopy sprinklers hang low in the canopy and have the potential to become entangled in crop biomass and detach from the center pivot. Detached in-canopy sprinklers impact the efficiency and uniformity of an irrigation system resulting in decreased crop yields by disrupting the flow and pressure requirements of the sprinkler package. Therefore, it is crucial that producers detect and replace missing in-canopy sprinklers immediately. A prototype in-canopy sprinkler monitoring system was designed to monitor in-canopy sprinklers on a center pivot irrigation system and to alert the user when and where an in-canopy sprinkler becomes detached from the center pivot span. If a sprinkler is found to be absent, the system alerts the user via a text message that the in-canopy sprinkler is missing and can be found at approximate geographic coordinates. Performance trials revealed the monitoring system to operate efficiently and accurately, however, minor changes need to be employed before large scale implementation.

Quantifying crop water requirement accurately can save two precious interdependent resources: water and energy. The soil moisture data can play an important role to determine the crop water requirements. To that end, understanding the water movements in soil-plant continuum, in other words classifying and quantifying soil moisture data related to water movements is the key to determine the crop water requirements. This study used numerical methods to classify and quantify the soil moisture data collected from an olive orchard located at the California State University Fresno Agricultural Laboratory in terms of infiltration, plant root intake, etc. Results show that the water movement is more evident in the upper portion of the soil column than in the lower portion of the column of 42” depth. Less infiltration is observed in the bottom soil layers as less water is available for infiltration after the applied water consumed by the plant root in the top soil layers. Results also show that the calculated average crop water requirement for summer found in this study is about 12.1 percent less than the crop water requirement based on traditional ET based method.

The Mekong River is the 7^th largest river in Southeast Asia and supports a population of more than 60 million people. The food security of such a large population is dependent on agriculture production. Irrigated wet season rice is the primary crop, which is grown throughout the year in the Mekong Delta region. At present, the major land transformation is observed in the basin in form of conversion of forest and grassland areas to the agricultural land. The increasing intensity of the irrigation in the region is causing high fluctuation in the evapotranspiration estimates. The basin also contains the enormous untapped hydropower potential. The crop water requirement, dominated by the evapotranspiration, is the crucial factor in segregating the available water for the irrigation and hydropower generation purposes. This study focuses on the estimation of the water distribution for different purposes under the influence of the changing irrigated area and intensification of the crop cycles per year. Six different scenarios were analyzed comparing the increased water demand from the irrigation sector using the water evaluation and planning (WEAP) model. The variable infiltration capacity (VIC) model was used for the assessment of the water budget and streamflow for the selected dams in the basin. The effect is dominantly observed in the small storage capacity dams which supply 70% of the total water requirement with the loss of 9% of the energy generation, while large dams were able to withstand the growing needs, delivering 90% of the demand and marginal effect on the energy generation. The increase in the number of crop cycles per year has the dominant effect on the supply and energy generation as compared to the expansion of the irrigated area.

In December 2010, EPA released the TMDL for the Chesapeake Bay. Specifically, the TMDL sets Bay watershed limits of 84.4 million kg/yr of nitrogen, and 5.7 million kg/yr of phosphorus, a 25% reduction in nitrogen and 24% reduction in phosphorus. Agriculture is the largest single source of nitrogen, phosphorus, and sediment loading to the bay. Each state was to reduce nitrogen, phosphorus, and sediment TMDL target reduction loads by 60% by 2017. West Virginia is the only state that has achieved their 2017 target load reductions for nitrogen, phosphorus, and sediment. Maryland, Pennsylvania, Virginia, and New York have not achieved their 2017 nitrogen load reductions for agriculture. Septic tank nitrogen loads have increased in Maryland and Virginia.

The Mekong River is one of the important rivers in Southeast Asia. The river basin management is a subject of debate as its stakeholders have varying priorities such as hydropower, irrigation, water recreation, fisheries, and industrial and municipal water supplies. It is also subjected to natural and anthropogenic-induced changes. In this study, we evaluated the drought conditions using a hydrologic simulation in the Lower Mekong River basin (LMB), and moderate to severe drought frequently occurred last 30 years that led to detrimental economic losses. Based on the results of drought, we will investigate the demand and supply strategies for meeting food security in the LMB. The analysis includes a crop simulation using the AquaCrop, streamflow simulation, and irrigation demand, which determine the resiliency of the system under extreme drought events under climate change and hydrologic responses.

Recent technological advances in information and communication technology (ICT) have opened new opportunities for monitoring and controlling of micro-scale low impact development (LID) practices almost in real-time. In this work, the smart rain barrel (SRB) concept combines LID and ICT in one system allowing new possibilities for the operation and management of small storage volumes used as temporary storage for stormwater control as well as for rainwater harvesting. To support the development of the SRBs, the effectiveness of the SRB concept on household scale is evaluated by using a 1-year rainfall series combined with real weather forecasts for that period. Results show, that stormwater retention is clearly increased by adding weather forecast to control strategies, while the amount of substituted potable water decreases with increasing accumulation time of the weather forecast. However, as the main purpose of rainwater harvesting is the substitution of potable water used for irrigation, the main challenge for small storage volumes used for both rainwater harvesting and stormwater control, is the accurate prediction of the stormwater runoff.

In this paper an attempt has been made to investigate change in crop acreage with soil moisture variations derived from AMSR-E passive microwave data. A set of 38 soil moisture and corresponding crop acreage observations for 6 Indian states viz. Punjab, Rajasthan, Gujarat, Bihar, Haryana, and Western Uttar Pradesh were analysed which indicated that in general crop acreage increases with increase in soil moisture. Results of statistical analysis (R²) between crop acreage and average soil moisture indicate that soil moisture is one of an important factor which governs crop acreage. Results have also been validated using five independent observations and resulted in a RMSE of 10.62. Study indicates the feasibility of use of large area soil moisture information for the assessment of crop acreage.

Modern, flexible irrigation service inherently results in more demanding operating conditions throughout an irrigation district’ s delivery system compared to more rigid rotational delivery schemes. Supervisory control and data acquisition (SCADA) systems are commonly used by irrigation districts to provide some of the enhanced management capabilities required for flexible deliveries. In these cases, robustness and accuracy are important SCADA system characteristics. Achieving robustness and accuracy requires extra attention to detail well beyond specifying good quality hardware. This paper presents specific examples deficiencies commonly identified by the authors in the field that can have real impacts on the robustness and accuracy of SCADA systems. Recommendations for improvement are also presented so that readers might avoid these issues in the future.

The Brazilian interconnected power system consists of a linked network of over 150 medium and large reservoirs, and a large set of small hydropower, thermal, and wind power plants. In Brazil, hydropower has been the predominant source of electrical energy supply, but the system has changed significantly over the last five years. From 2003 to 2012, 91% of the electrical energy was supplied by hydropower plants, while the reservoir system operated with, on average, 68% of active storage. From 2013 to 2017, 74% was supplied by hydropower plants, while the reservoir system operated with, on average, only 39% of active storage. Wind power provided, on average, of less than 1% until 2013, and increased to 8% in the last four years. Energy demand, hydropower production, reservoir storage, wind power generation, and thermal dispatch have shown significant changes within their shared patterns and seasonality. Additionally, a series of recent moderate to severe droughts occurred in Brazil. An important question that needs to be addressed is: Is it reasonable to operate for more than five years with such low levels of reservoir storage? Furthermore, with the added issues of water security and system resilience, what is the effect in terms of productivity reduction in this complex system of reservoirs? In this paper we use the HIDROTERM, a nonlinear programming optimization model previously developed for planning the operation of the Brazilian hydrothermal system, to estimate the hydropower productivity reduction within recent years with low reservoir storage variations.

The metropolitan region of São Paulo (MRSP) has suffered from its worst drought in history, which started in 2013 and is not over yet in 2018. With 21.4 million inhabitants, the region has one of the largest water supply systems in the world, consisting of ten partially interlinked reservoir systems. Cantareira system is the largest, serving about nine million inhabitants. Mitigation measures for the drought included pumping water from the dead storage in the Cantareira system, operational changes, pressure reduction at night, and discounts as water saving incentives. The newly built water transfer system from the Jaguari Reservoir improves the reliability of the Cantareira system, but has significant energy cost and competes with energy production and water supply to downstream cities. The newly built water transfer system from the São Lourenço Reservoir has very high energy cost and competes with energy production in a highly productive cascade of hydropower plants. The primary role of the two newly built water transfer systems is to increase water security. Water savings and expansion of the water system allowed the storage to recover in the main reservoirs and eased the more severe mitigation measures. However, characteristics of the newly built water transfer systems bring new challenges for planning and management of the water supply. This paper discusses using the SISAGUA, a previously developed nonlinear optimization model, to evaluate aspects of cost-effective, reliability, and resilience of the newly expanded water supply system and points out limitations and suggestions to deal with its increased complexity.

Located at the confluence of the Mississippi River with the Gulf of Mexico, and just south of Lake Pontchartrain, New Orleans, is surrounded by water in every direction. Moreover, a substantial portion of the city is situated below sea level, creating a “bowl-shaped” topography that is susceptible to flooding. The city currently provides flood and hurricane protection with levees and floodwalls and employs a series of large pumping stations to remove water from the floodplain as quickly as possible during wet weather events. Building a resilient system that addresses physical vulnerabilities such as climate change, subsidence, and sea level rise, and social vulnerabilities such as poverty and income inequality is a difficult challenge that requires a triple bottom line solution. The Blue and Green Corridors project aims to provide an example of a path to success to communities aspiring to resilient and sustainable living in the face of flood risk and natural disasters.

In this paper, a copula-based method was proposed for stochastic simulation of the daily suspended sediment concentration (SSC). In this method, bivariate copula functions were used to describe the dependence structures of the SSCs between adjacent days. To reduce the difficulties of determining the daily marginal distributions of the SSC, the observed daily SSC data were normalized by using the normal quantile transform method. The proposed method was applied to generate the long-term daily SSC data of the Pingshan Station on the Jinsha River, and was compared with the autoregressive (AR) model. The results show that the proposed method can better preserve the statistical properties of observed daily SSC data with high accuracy. In addition, the skewness and nonlinear correlation of the SSCs simulated by the proposed method were better than the AR model. This study can provide a new tool for stochastic simulation of the long-term daily SSCs.

This paper presents the urban drainage study of two small urban catchments in the city of São Paulo, Brazil. São Paulo is a megacity with more than 11 million inhabitants, with enormous social, technical, economic, and environmental problems. Among them is the flooding of several areas during the rainy season. It can be observed that the dense soil occupation, together with the above mentioned problems, shows how diverse and complex is the urban water issue. It is fundamental in studies like this to assess and analyze the causes of floods. Another key issue is how the impacts of urbanization are related to the various hydrological processes, which are even more sensitive in tropical and subtropical cities. The main question to be discussed is how to use various techniques of sustainable urban drainage in densely occupied areas in a city like São Paulo. The case study presents two catchments, located in the central region of the city, constituted by extremely sensitive areas, occupied for housing, mobility, services, and other city demands. Proposals for flood control intervention are also presented.

Codorus Creek, which runs through the city of York, is the focus of an ongoing beautification initiative which is part of a program to revitalize the downtown corridor. Plans include restoring access to the creek shoreline and enhancing its amenity value by providing a compound cross section with a low flow channel, landscaped overbank areas, and side slopes, and retaining walls supporting linear park features, while maintaining adequate conveyance for design flood events. To support the conceptualization of the project and reconcile partially conflicting uses of the channel for low- and high-frequency flows, H&H calculations must be carried out to determine the appropriate stages and design elevations for each project element based on average daily flows for site amenity features, and annual peak discharges for flood control.

There is always a political debate how environmental regulations inhibit economic progress. However, if we look closely at the situation prior to the enactment of major congressional actions in the early 1970s, one can understand that the pollution and contamination of our environment had reached an epidemic level that propelled the environmental movement of the 1960s. Rachel Carson in her book titled Silent Spring captured the impact of indiscriminate use of pesticides such as DDT. Her book served as a wake-up call for the nation to come together to fight for the protection of our environmental resources before environmental pollution would completely destroy our water we drink and the air we breathe. The author will focus on the environmental movement of the 1960s in the United States that resulted in the passage of a number of important pieces of legislation such as the Clean Water Act and the Safe Drinking Water Act. The author will examine the success of the early planning efforts undertaken under Section 208 of the Clean Water Act in developing wastewater management plans throughout the United States with specific focus on wastewater treatment and disposal activities in Massachusetts. This paper will also examine the deterioration of our water and wastewater infrastructure after the successes of the 1980s, and how a more robust policy and leadership is needed at the national and local level to check this trend. Not only public health is endangered but economic gains could be threatened.

This paper aims to show how the integration between weather radar and rain gages is able to improve the flooding forecast in the megacity of São Paulo. The city of São Paulo is one of the five largest cities in the world. However, this megacity has a chronic flood problem that occurs every year, especially during the summer. Structural measures for flood control are extremely expensive and not possible in short term. In this scenario, non-structural measures such as a flood warning system is an alternative solution. This system aims to provide a real-time forecast of floods that may cause impacts in several areas. The accuracy of flooding forecast in real time is extremely important for a good result. Precipitation is the main forcing in this process and has to be estimated properly. Rain gauge networks can represent rainfall locally but has a bad spatial representativeness. Weather radars provide very high spatial resolution but not so good accuracy for rainfall intensity. The integration of radar estimations with rain gauge network is capable to minimize errors of both. The goal of the present work is to evaluate the performance of a methodology to merge weather radar estimates with rain gauge data and it uses as an input in a distributed hydrologic model. For the integration, it was used São Paulo weather radar a rain gage network. The hydrological simulations were performed with the distributed model SWMM. The studied area was the Mandaqui Basin, in the city of São Paulo.

Increasing flood frequency and intensity is leading to a new emphasis on utilizing nonstructural approaches for flood mitigation and in integrating nonstructural and structural approaches for the same objective. Within a watershed, wetlands, detention ponds, and reservoirs play a vital role in mitigating floods. However, in many cases, the effectiveness of these storage systems appears to be limited because they are often not operated in a coordinated manner besides storage limitations. We claim that improved flood mitigation at the watershed scale could be achieved by using all watershed storage systems in a coordinated manner and in response to forecasted storm events. The aim of this work is to present a software and hardware architecture for the optimal and coordinated operation of an array of storage systems such as reservoirs, detention ponds, and wetlands for mitigating floods. This approach will enable adaptive release of water from wetlands hours or days ahead of rainfall events, thereby maximizing storage capacity and mitigating floods. As part of this framework we have developed a modular hardware/software platform for interfacing automated siphons/gates, water level sensors, and sensor control/communication to enable remote operation of an array of actuated water releasing hardware in wetlands, detention ponds, and reservoirs. The remote operation is performed using 3G/4G cellular connection. The DSS combines modules of hydrological modeling, inundation modeling, robust optimization, and ecological and operational constraints. The remotely-controlled system is a relatively inexpensive method for flood mitigation. A low-cost way to manipulate the storage in wetlands, detention ponds, and other storage systems could open the doors to a new cost-efficient method for flood control and other objectives.

A method employing artificial neural networks (ANNs) coupled with stationary wavelet transforms (SWTs) was used to estimate water temperature profiles in Boulder Basin, Lake Mead, from May 2011 through December 2014. Surface temperature measurements and stepwise predictions with depth were used to estimate water temperatures through the entire water column. Comparing different modeling scenarios revealed that vertical mixing mode within the water column influenced whether high or low frequency SWT components generated the most accurate water temperature estimates. Rapid temporal and spatial variations in certain parts of the water column increased prediction errors. SWT decomposition revealed that numerical errors in estimated water temperature signals tended to accumulate in specific SWT sub-signals. Excluding those sub-signals from the system improved method performance. ANNs using specific decomposed parts of the input temperature data yielded the best performance, resulting in a coefficient of determination, R² > 0.96 and maximum relative error of 0.68%.

Due to increasing population growth, water demands for domestic, agricultural, and industrial sectors are increasing at the expense of maintaining a minimum environmental demand. A driving force for societies to rethink the value of providing water for ecological and social benefits is planning for ecotourism. Ecotourism is important for increasing employment and income. Significant in-stream values may be found in the recreational aspects of water use. As water allocation is mostly done based on economic criteria, reallocation of supply is essential to take advantages of new challenges in value-driven environmental economics. From ecotourism point of view, rivers flowing in a city increase esthetic as well as a pleasant environment which tend to become appealing for local people and play an important role in attracting tourists. Improper water allocation influences socioeconomic aspect so that people are deprived of this income opportunity. Proposing a reallocation scheme by comparing the economic value of providing water for domestic, agricultural, and industrial demands with environmental requirements utilizing GWP (global water partnership) principles is the aim of this study. For this purpose, a procedure which regards coordinated development in water, land, and related sources for maximizing economic and social welfare are specified to reach to a more sustainable environment without eruption in supplying other demands. The case study is Zayandeh-Rud River in Isfahan, Iran. This city with attractive structures, Zayandeh-Rud River, and its bridges is one of the main sources of tourism in Iran. However, Zanyandeh-Rud River drought in recent years has caused a reduction in tourism income and has affected local people’ s morale mainly through the river’ s appearance in the city. The water allocation scenarios are tested in a water balance model. The result shows the significant value of utilizing economic consideration in justifying the value of supplying environmental demand in general and ecotourism in particular.

The floods in the city of São Paulo, Brazil, are an historical trouble as a result of its urbanization process. The city has a total area of 1,521 km², with 68% of urban area, where there are 1,000 km of underground streams, which represent 42% of the streams located in the urban area. Therefore, inundation problems are frequently observed due to runoff. The recurrence of floods makes government actions focused on flood control. The zoning of flood areas, associated to hydrological risk, is a technique to be used in the definition of patterns of land use and occupation, with the objective of minimizing the human and material losses resulting from the floods. This work indicates how the zoning of flooded areas can be articulated with the structural measures of flood control from the concept of the coexistence of the city with the urban waters.

The urban water system (UWS) is a highly energy-consuming sector and its efficiency is important for an integrated planning of smart cities towards decarbonisation and in order to ensure in general its sustainability over time due to the risk of having a lack of such resources because climate change and demographic growth may strongly affect the water availability in future. This study focuses on the strategic planning of the UWS with special reference to water and energy saving and greenhouse gas (GHG) emissions reduction. The methodology proposed allows to identify the more efficient and robust intervention strategies by coupling an optimization algorithm to the metabolic model WaterMet², which evaluate each solution with respect to different sustainability objectives and over multiple climate and socio-economic future scenarios. The optimal intervention strategies are compared to a business as usual strategy (BAU) in order to quantify the benefits of the identified solutions in terms of system performance and trajectories. This methodology is applied to the Italian case study of the city of Bresso (Milan, Italy), in the framework of a collaboration with the urban water utility “CAP Holding”. Results show the effectiveness of the optimal intervention strategies in considerably reducing the total cost and the GHG emissions by consequently increasing the overall efficiency of the UWS.

From 2007 to 2017, the state of California experienced two major droughts that required significant governmental action to decrease urban water demand. The purpose of this study is to isolate and explore the effects of these policy changes on water use during and after these droughts, and to see how these policies interact with hydroclimatic variability. The results of the city level water demand models indicate that implementation of mandatory policies that target water use behaviors effectively reduce water use. The findings suggest that drought-related policies impact per capita urban water use along with temperature, income, unemployment, and water stress. The mathematically significant relationships identified in this study offer a path forward for more complex water demand models to include policy changes as a driver of water use. The policy coding methodology offers a start to the complicated task of categorizing drought policies and identifying what qualities make them effective at reducing urban water use.

Since the 13th Five-Year Plan, rural drinking water security has entered a stage of comprehensive consolidation and upgrading, focusing on poverty relief, focusing on improving the operation mechanism of the project, taking strengthening water quality as the core, and comprehensively improving the level of rural drinking water security. Rural water supply project is an important part of poverty relief. Ensuring the long-term operation of such projects is a major problem in the actual operations, in addition to concerns with the water source, technologies, management, staffing, and knowledge relating to water supply. Many management techniques are particularly ineffective in rural areas. After all, the necessary management model is not extant. National policies are reviewed through in-depth analysis and research on the management of water supply utilities in rural areas. The main project management modes in our country include public ownership company management, stock company management, contract management, institution management, and entrusted management. The various types of management models in China are summarized to develop a sustainable model that can help improve the management system of water supply projects in rural areas.

Discharges of wastewater from industrial sources may contain pollutants that can reduce the quality of receiving surface waters. Such point source discharges are regulated through the Clean Water Act (CWA) National Pollutant Discharge Elimination System (NPDES) Program, which establishes conditions and limits for these discharges. When exceedances of such limits occur, mitigation may be considered through either onsite or offsite projects. However, in the cases of certain pollutants, such as pH, nutrients, temperature, and salinity, non-point source contributions may be much larger than permitted industry contributions. In this situation, concerted watershed-wide mitigation may be pursued through the effort of multiple state and federal government agencies. A prime example is the Colorado River Basin Salinity Control Program, which was enacted in 1974 to reduce total dissolved solids (TDS) inputs to the Colorado River from multiple and diffuse sources. This basin-wide program directs funding and oversees projects determined to be highly effective in reducing surface water salinity. Although industries located within the Colorado River Basin can pursue offsite mitigation for discharges of excess TDS, there is currently no basis for incorporating those offsite mitigation efforts into current government-led salinity reduction projects. However, the effectiveness of individual off-site mitigation projects may be significantly enhanced by utilizing decades of government experience to coordinate mitigation efforts throughout the basin. Therefore, we propose a framework for integrating industry mitigation needs into preexisting basin-wide government mitigation efforts, utilizing the Colorado River Basin as a model, to streamline industry mitigation efforts so that mitigation dollars are used to the maximum benefit of watershed-wide surface water quality.

The quantification of climate variability, especially in terms of rainfall patterns, is of vital concern all around the globe at present. Owing to the significant variation of rainfall distribution in both space and time, its precise estimation is crucial at river basin level. In this study, an autoregressive integrated moving average (ARIMA) model is developed for prediction of monthly rainfall over Betwa River Basin, India. The monthly precipitation data for 1960–2012 were obtained from the India Meteorological Department (IMD) Pune. The monthly average precipitation over the whole basin was estimated using Thiessen polygon method. The precipitation time series from 1960 to 2000 was utilized for training purposes in order to frame the most suitable model, and that of 2001 to 2012 was utilized for testing and validation purposes. The metrics viz., Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used for selecting optimum values of the parameters; and the ARIMA (0, 0, 1) (1, 1, 2)₁₂ was established as the parsimonious model. The Nash-Sutcliffe efficiency (NSE) and the coefficient of determination (R²) were used to evaluate the model efficiency. The model forecasts possessed an excellent match with the observed rainfall data (2001–2012). The outstanding accuracy of the model for predicting monthly rainfall for such a long duration of 23 years justifies its future application over the study region. This study will be helpful in developing a proper management framework for the core of Indian monsoon region.

It is necessary to understand the hydrological processes undergoing at small segments in order to apprehend the complex large river systems and this can be achieved by application of hydrological models. This study aims to check the applicability of soil and water assessment tool (SWAT) model over the Kharun River Basin, Chhattisgarh, India. The limitation of data at proper scales is the major problem that hinders research on this area. The meteorological data were collected from climate forecasting system reanalysis (CFSR) database for 1994–2014. The SWAT simulations generated runoff, which was auto-calibrated with the observed values through SWAT-CUP. Generalized uncertainty likelihood estimation (GLUE) optimization approach was used for sensitivity analysis of various parameters during auto-calibration. The results reveal for a moderate correlation between the observed and modelled values at daily time scale i.e. the Nash-Sutcliffe efficiency and R² values are close to 0.5. This highlights the fact that model application needs to be carried out carefully with processed and reliable data sets. Also, some of the popular models may as well be not suitable for few basins with multiple complexities. The possible reasons for such moderate performance of the model are also discussed. This work will be helpful to the decision makers for better planning and management of the basin.

The following article pertains to use the first observed hourly precipitation records and estimated by satellites, such as: global precipitation measurement—GPM (0.1°×0.1°) and the remotely sensed information using artificial neural networks—PERSIANN (0.04°×0.04°) for the flow simulation. For the modelling process, the GR4H included in airGR package was used, which is a free code developed in R. The calibration processes were carried out considering hydrological temporary simulation frame (1h, 3h, …, 24h; where: h=hour). The study area was the humid Rimac River basin, located 50 km from the city of Lima. This basin was selected because it concentrates the largest meteorological and hydrological hourly information around the country. The obtained results suggest that the maximum efficiency is located in modelling scales from 3 to 9 hours with efficiencies within the range [0.5–0.7] from the Nash coefficient. Moreover, it was determined that the product GPM shows a higher efficiency in the representation of the hourly flood hydrographs in the basin.

A recent study by the U.S. Global Change Research Program shows the projected precipitation will increase, particularly in the winters and springs, in the northern Great Plains. Considering the use of fertilizers along with land use change and urbanization, this increase in rainfall and snowmelt may cause severe erosion of land, accumulation of sediment in lakes and reservoirs, higher concentration of nutrients (nitrate and phosphorous), and disease-causing agents in inland and coastal waters. A study of Lake Ashtabula in North Dakota was carried out to confirm if there is a significant linkage of climate change and different land use with the increasing rate of sediment accumulation and nutrient production. For this purpose, the soil and water assessment tool (SWAT) has been built up, calibrated, and validated for flow, sedimentation, and nutrient loads. The results show even in cold climate region, climate change may affect adversely the accumulation of sediment and nutrients in the lake.

Studying water quality problems in natural aquatic environment with numerical models is a very effective approach. As a result, many numerical models have been developed and applied to simulate water quality constituents in rivers, lakes, and coastal waters. The observed water quality in an aquatic system is a result of many physical, chemical, and bio-chemical processes, parameters of a water quality model associated to these processes need to be calibrated. Phytoplankton is one of the most important components in the water quality simulation. Its growth rate is significantly affected by temperature, sun light, and nutrients; while the death rate is influenced by the temperature. More than ten parameters need to be calibrated for modeling phytoplankton kinetics. In this study, a water quality model CCHE_WQ, developed at the National Center for Computational Hydroscience and Engineering (NCCHE), was applied to simulate the phytoplankton (as chlorophyll a) in Pelahatchie Bay in Mississippi. The parameters such as saturation light intensity, light extinction coefficient, optimal temperature for the growth, half-saturation constants for nutrients, etc. were calibrated and statistical analysis was conducted to evaluate the performance of numerical model by using different parameters.

Environmental flow is necessary to maintain healthy ecosystem and sustainability of aquatic lives as well. In the present study an effort has been made to describe the environmental flow condition of a watershed with the help of standardized precipitation index (SPI), an index often used in drought prediction using precipitation. Among the various drought indices SPI is very popular and widely used for drought monitoring. Since SPI has some advantages over other indices like it requires only easily available precipitation data and it enables drought monitoring at different time scales, viz. monthly, seasonal, annual, etc. On the other hand, Tennant method requires flow data, which is too scarce in ungauged catchments. This study attempts to couple the concepts of Tennant and SPI to predict environmental flow condition using rainfall. Five watersheds of Godavari Basin namely Hivra, Kumhari, Nandgaon, Ramakona, and Satrapur have been taken for the analysis. Rainfall and runoff data for the period of 1990–2000 of these watersheds were used in the analysis. SPI at 9 month time scale for the month of June has been evaluated and the percentage of average annual flow was calculated for the same period for respective watersheds. The percentage of average annual flow is plotted against the corresponding values of SPI and the value of coefficient of determination found to be greater than 0.74 for 3 (out of 5) catchments which suggest a very good fit. For each of the five watersheds the percentage of average annual flow increases with the increase in SPI, exhibiting a remarkable dependence of environmental flow on SPI. This relationship can be used for deriving the EF condition for a watershed/gauging site based on SPI, which can be easily derived from the available rainfall data.

Sulfate (S), nitrate (N), and phosphate (P) are the primary contaminants that contribute to harmful algae blooms (HABs). Combined with warm waters and sunlight, the photosynthetic blue-green algae (Cyanobacteria) can flourish. Previous work has established Lake Erie’ s western basin as a point of origin for HABs due to its relatively shallow waters, which can quickly reach warm temperatures in the summer, and its proximity to the mouth of the 137 mile long Maumee River. The Maumee originates in Ft. Wayne, Indiana, and flows northeast through largely agriculture dominated counties and numerous urban areas until it drains directly into Lake Erie’ s western basin. Along its flow path, the Maumee accumulates large amounts of contaminants from agricultural fertilizers, urban runoff, and bedrock. This research quantifies the contaminants present in the water and sediment of the lower ~60 miles of the Maumee River over the course of six months through monthly water quality monitoring at seven sampling points along the river and subsequent laboratory analysis of the samples. The results from the data collected for nutrients and sulfate in the water correlate with precipitation. Each contaminant (N, P, S) exhibit unique concentration patterns over time; each respond differently to precipitation events, which provide some insight about their sources. The results of this study have shown relationships between many of the measured parameters such as the correlations between dissolved oxygen (DO), organic matter (OM) in the sediments, pH, and phosphate concentration in the water. The data have shown that as OM increases, DO and pH decrease due to OM decomposition which releases CO₂. With regard to phosphate, it is more soluble in lower pH waters. Considering that phosphate is one of the fundamental nutrients that fuel HAB development, this is an important relationship. It puts in evidence for the internal sources of phosphate as the minerals stored in the sediments. The input of contaminants into the western basin is not the only factor to consider with regard to HABs. Wind, water temperature, and currents combined with contaminant concentrations determine the presence and severity of HABs in Lake Erie.

While high-resolution models have the potential of advancing the frontier of forecasting in the geosciences, their initialization through data assimilation is computationally challenging because of the huge number of interactions between state variables. This article introduces a method to reduce the dimensionality of state vectors to improve existing assimilation algorithms. The method couples model elements that behave similarly using optimized $k$-means clustering with the goal of making covariance matrices more manageable, and of allowing for smaller errors when dependencies are ignored for efficiency reasons. An experiment using a highly-distributed hydrologic model showed that an intermediate level of compression, with optimized clustering parameters, improved the probabilistic performance of streamflow forecasts. While higher levels of compression could be achieved more efficiently and lower levels offer more realistic representations, an intermediate level yielded the best balance between the degree of cell coupling and the preservation of the spatial heterogeneity of the watershed.

Rainfall-runoff simulation is an essential step in analyzing the impacts of extreme flood events. This can aid in water resource management and planning. In areas that are prone to floods, it becomes necessary to perform an extensive hydrological study. Cache River watershed is one of the flood prone watersheds in Illinois, mainly due to the confluence of two large rivers Mississippi and Ohio, in southern Illinois. This study utilizes hydrological modeling system (HEC-HMS) for simulation of Cache River watershed to analyze the response of rainfall and runoff. Rainfall-runoff modelling helps in estimating peak flows which is very essential to strategize water resources management. This model also incorporates ArcGIS extension HEC-GEOHMS, which performs geospatial analysis and generates the hydrologic modeling inputs for the HEC-HMS model. SCS unit hydrograph method was used for runoff estimation depending on the available parameters to be estimated. Daily precipitation data, elevation data, percentage of impervious, and curve number, which takes into account the land use and soil characteristics of the watershed was used as model inputs for the HEC-HMS model. The model was then calibrated by taking a set of storm events occurring in the catchment from 2010 to 2015. Another set of storm events was used for validation of the model. The model performance was evaluated by using various statistical indices. The model, thus developed, can be used to manage different flood evens and adopt effective decision and warning systems.

In 1997, the EPA created the Mississippi River/Gulf of Mexico Watershed Nutrient Task Force which is commonly known as the hypoxia task force (HTF) to address the growing dead zone problem in the Gulf of Mexico caused by nitrogen and phosphorus. The HTF developed an Action Plan in 2001 to address the issue but little progress was made on the problem, so they developed another one in 2008. The 2008 plan as a first step called for all states in the Mississippi/Atchafalaya River Basin to complete and implement comprehensive nutrient reduction strategies for all watersheds with significant contributions of nutrients to the surface waters in the Basin. All states have developed nutrient reduction strategy plans and have started implementing them. A research study in 2011 which used models to examine phosphorus loading from all 1,768 counties in the Mississippi River Basin found there was little relationship between livestock manure and water quality and, in crop production areas found farmers removed more phosphorus in harvested crops than what they applied in fertilizer, suggesting that overzealous fertilizer use is not the issue. Soil erosion and tile drainage are among the major contributors of phosphorus to the Mississippi and Gulf of Mexico each year. Sewage treatment plants in Chicago and other major metropolitan areas “showed up as hot spots”, because most municipalities don’ t remove phosphorus. Starting in the 1990s there has been a major research effort to evaluate crop production practices and water quality relationships and best management practices to reduce phosphorus loading. Some of the major findings are summarized and discussed in the paper.

The Gumbel and Weibull distributions are closely related probability models with many hydrological and environmental applications. Quite often, when trying to select between one of these distributions and a competing model to fit a data set, the commonly used goodness of fit tests lead to the rejection of neither of the competing models, but the user still needs an objective means of selecting between them. We compare three discrimination methods between the Gumbel/Weibull model and alternative models with the same number of unknown parameters. We base the comparison on the methods’ discrimination power and discrimination bias. One method is the classical ratio of maximized likelihood (RML) procedure. When the competing models have the same number of unknown parameters, RML is equivalent to using the Akaike information criterion (AIC) or the Bayesian information criterion (BIC). Another method is TN.SW, which employs a transformation of the sample to normality, followed by an application of the Shapiro-Wilk (SW) statistic for testing normality. A third method, TN.PPCC, uses the same idea as TN.SW but is based on the probability plot correlation coefficient (PPCC) statistic. We conclude that TN.SW has advantages that merit further follow-up in future research. We illustrate our obtained results in an application involving frequency analysis of low river flows.

An important problem in hydrology is the frequency modeling of extreme events such as floods or heavy rainfall. The Gumbel model is a probability distribution often used to describe the behavior of such events. This distribution is a special case of the generalized extreme values model (GEV). A key goal in fitting frequency distributions to data is to allow the estimation of distribution quantiles, often used as “design events”. The maximum likelihood (ML) method is recommended for fitting the Gumbel model to data. One way of measuring the statistical error involved in estimating design events is to calculate confidence intervals for quantiles ($CIQs$). Hydrologists have traditionally used large-sample theory to construct such $CIQs$, but we show that this leads to inaccurate results for quantiles in the right tail of a Gumbel model, when the sample size is not sufficiently large. We therefore propose an improvement to the classically obtained $CIQs$ by applying a Box-Cox (BC) power transformation to the quantiles. The conventional and proposed approaches are then compared through Monte Carlo simulation. Practical recommendations are put forward and demonstrated in a hydrological application.

Constructed wetlands can intercept and treat agricultural runoff to reduce nutrient transport to larger water bodies. Effective design and monitoring of these systems requires information on runoff retention patterns during and after storm events. An upland rainfall-runoff model and wetland water budget model were developed to determine hydraulic retention for two storm water constructed wetlands receiving runoff from agricultural fields with tile outlet terraced systems. Model results showed a consistent difference in retention time between the two wetlands during the 2015 growing season, which corresponded to similar differences in the wetland’ s effectiveness at nutrient removal. The most significant variable in determining retention time was the amount of antecedent moisture, which affected input runoff flows. Month by month assessment of water retention showed much greater rates of water exchange in May–June compared to July–November in both wetlands. These results will help to improve estimation of nutrient removal in these systems.

In order to mitigate the negative impacts of urbanization and land development on hydrologic variables, green infrastructure (GI) techniques are designed as controlling measures. However, one of the challenges in designing such measures is finding the appropriate types among a variety of candidate GIs, as well as optimum sizes and configuration of selected ones for a given catchment. Running a GI optimization model can find optimum types and configuration of appropriate GIs. Such analysis is critical in order to improve the sustainability and minimize the associated costs of a project. However, due to the substantial computational resources required for such cumbersome optimization analyses, usually a simplified version of the employed GI performance model is used, or even single storm events are considered, rather than a long term analysis. To introduce a more comprehensive GI optimization approach that is able to employ GI performance models without simplification, a systematic multi-objective optimization framework was linked to a high throughput computation (HTC) framework, called HTCondor. NSGA-II was set as the optimization tool, and it optimized candidate GIs in terms of life cycle cost (LCC) and annual runoff volume (ARV).

The uncertainties in the hydrology allied with the climate and land change have been a research topic of recent scientific and engineering communities. Texas Trinity River Basin (TRB) of an area about 46,620 square kilometres comprises the river system with maximum water storage as compared to the other river systems of Texas. TRB also includes hydraulic structures such as locks and dams, water control structures, and reservoirs while the watershed recently faced a flood. The current study will simulate the discharge in the Trinity River utilizing the soil and watershed assessment tool (SWAT) based on the basin characteristics like elevation, type of soil, land use, and hydrological variables like temperature and precipitation. SWAT is an arc geographic information system-based, semi-distributive physical model. The model was developed utilizing the basin properties like soil type, digital elevation model, land use, along with the meteorological inputs like precipitation, temperature, relative humidity, wind speed, and solar radiation adopted from climate forecast system reanalysis within TRB. The sensitivity and calibration of the model parameters were estimated using the sequential uncertainty fitting algorithm in SWAT calibration and uncertainty procedures—a powerful calibrating tool for SWAT models. The model was calibrated based on the observed streamflow from 1990 to 2009, and the model was validated with the observed streamflow of 2010 and 2013. Statistical evaluation indices and graphical presentation were used to analyze the robustness of the simulated results.