Modelling Low Impact Development Potential With Urban Hydrological Response Units

The purpose of this thesis is to develop a methodology for hydrological modelling the performance of Low Impact Development technologies using an Urban Hydrological Response Unit approach. The K-Means Cluster Analysis procedure was carried out to create clusters of lot parcels which represented the Urban Hydrological Response Units. Different sampling methods were used to select lots from each of the clusters to model before and after Low Impact Development implementation. The runoff response (m3) of an approximate final cluster centre was used to calculate the total runoff (m3) of each cluster. After adding the total runoff (m3) for a group of 15 clusters, the benchmark runoff value (m3) from modelling all lots was closely approached with and without Low Impact Development. A random sample of 7 % and 90 % of lots from each cluster for a group of three clusters closely approached the benchmark runoff value (m3) for both no Low Impact Development and Low Impact Development respectively.

Modelling Low Impact Development Potential With Urban Hydrological Response Units

The purpose of this thesis is to develop a methodology for hydrological modelling the performance of Low Impact Development technologies using an Urban Hydrological Response Unit approach. The K-Means Cluster Analysis procedure was carried out to create clusters of lot parcels which represented the Urban Hydrological Response Units. Different sampling methods were used to select lots from each of the clusters to model before and after Low Impact Development implementation. The runoff response (m3) of an approximate final cluster centre was used to calculate the total runoff (m3) of each cluster. After adding the total runoff (m3) for a group of 15 clusters, the benchmark runoff value (m3) from modelling all lots was closely approached with and without Low Impact Development. A random sample of 7 % and 90 % of lots from each cluster for a group of three clusters closely approached the benchmark runoff value (m3) for both no Low Impact Development and Low Impact Development respectively.

Multi-Time Scale Evaluation of Forest Water Conservation Function in the Semiarid Mountains Area

Forest water conservation function is an important part of forest ecosystem services. The discontinuous distribution of forests in semiarid areas brings difficulties to the quantitative evaluation of forest water conservation functions at the basin scale. In this paper, we took the upstream of Xiong’an New Area (Zijingguan—ZJG, Zhongtangmei—ZTM and Fuping—FP basins) as an example and combine the soil and water assessment tool (SWAT) and the water balance method to calculate the amount of forest water conservation (AFWC) at annual, monthly and daily scales from 2007 to 2017, and analyzed the changes of AFWC. The results showed that the hydrological response unit (HRU) generated with the threshold area zero can accurately reflect the forest patch distribution in the three basins. On an annual scale, the annual AFWC were all positive in ZJG and ZTM basins from 2007 to 2017. While, the annual AFWC in the FP basin was negative in 2009, 2013, 2014 and 2017. On a monthly scale, the positive values of AFWC mainly appear from June to September, and the negative values of AFWC mainly appear from December to March. On a daily scale, the AFWC during extreme precipitation was positive, while that was negative during extreme drought. The annual and monthly AFWC in the three basins was positively correlated with the wetness index, and FP basin needs more humid climate conditions than ZJG and ZTM basins to make the forest store water and keep in a stable water storage state. The above results can not only provide important insight into sustainable forest and water resources management in the region, but also serve as reference cases for other regions to carry out relevant research work.

Differential Law and Influencing Factors of Groundwater Depth in the Key Agricultural and Pastoral Zones Driven by the Minimum Hydrological Response Unit

The water cycle in the key agricultural and pastoral zones (KAPZs) is an important factor for maintaining the stability of the ecosystem. Groundwater collection and lateral seepage are indispensable parts of the water cycle, and it is difficult to monitor the groundwater situation in each area. The strength of the alternate circulation of groundwater is directly related to the utilization value and development prospects of groundwater; therefore, creating an effective method for the detection of groundwater burial depth has become an issue of increasing concern. In this paper, we attempt to create a method for the detection of groundwater burial depth that combines cokriging interpolation, spatial autocorrelation, geographically weighted regression, and other methods to construct a quantitative relationship between different land cover types and groundwater depth. By calculating the band index of the land cover type, the groundwater depthinformation of the unknown area can be obtained more accurately. Through collaborative kriging interpolation, normalized difference vegetation index (NDVI), precipitation, and hydrogeological conditions were used as covariates. The groundwater burial depth of Wengniute Banner in 2005, 2009, 2013, and 2017 was the response variable, and the groundwater burial depth in the study area was calculated. The groundwater burial depth data after the cokriging interpolation was used to transform the raster data into vector data in space using the improved hydrological response unit (HRU) model to make it more suitable for the actual groundwater confluence. Subsequently, 551 minimum response units (MHRUs) were obtained by division, and the spatial autocorrelation analysis was performed accordingly. The groundwater burial depth in the study area is spatially distinct from east to west, and the groundwater level shows a trend of being high in the west and low in the east, gradually increasing due to precipitation and rivers. The average change of groundwater depth in the time series is not significant, but it does gradually show a trend of accumulation. According to the aggregation characteristics of spatial autocorrelation analysis, a geographically weighted regression model of groundwater depth and NDVI, normalized difference drought index (NDDI), and net relatedness index (NRI) was established. The NDVI representing the forest land and the Adjusted R2 of the groundwater depth is 0.67. The NRI representing the cultivated land and the Adjusted R2 of the groundwater depth is 0.8675. The NDDI representing the bare land and the Adjusted R2 of the groundwater depth is 0.7875. It shows that the band index representing the ground type has a good fitting effect with the groundwater burial depth.

Long-term Monthly Discharge Prediction for Cimanuk Watershed

Although streamflow data is important for water resource planning, it’s long-term availability for Indonesian rivers is limited. One factor could be identified for example lack of observation. Here, we presented observation-based modeling to predict long-term discharge data for Cimanuk watershed in Indonesia. The watershed is categorized as one of the critical watersheds, meanwhile it supports to more than one million people. A well-known hydrological model called Soil and Water Assessment Tools (SWAT) was used to predict monthly discharge. The model was fed with monthly climate data, topography, land use and soil characteristics. We calibrated the model with the observed data from 1974 to 1994 (20 years). Our results showed that the model was a good performance in estimating monthly discharge as indicated by three statistical metrics used. Based on statistical evaluation, the calibration resulted a low percent bias (3.20%), strong correlation (0.73), and high Kling-Gupta Efficiency (0.78). Further, we did a sensitivity analysis for the model, and we found that hydrological response unit was the most influential parameters for the Cimanuk watershed. A long-term discharge data indicated a monsoonal pattern for this watershed.

The Application of a Modified Version of the SWAT Model at the Daily Temporal Scale and the Hydrological Response unit Spatial Scale: A Case Study Covering an Irrigation District in the Hei River Basin

As a well-built, distributed hydrological model, the Soil and Water Assessment Tool (SWAT) has rarely been evaluated at small spatial and short temporal scales. This study evaluated crop growth (specifically, the leaf area index and shoot dry matter) and daily evapotranspiration at the hydrological response unit (HRU) scale, and SWAT2009 was modified to accurately simulate crop growth processes and major hydrological processes. The parameters of the modified SWAT2009 model were calibrated using data on maize for seed from 5 HRUs and validated using data from 7 HRUs. The results show that daily evapotranspiration, shoot dry matter and leaf area index estimates from the modified SWAT2009 model were satisfactory at the HRU level, and the RMSE values associated with daily evapotranspiration, shoot dry matter, and leaf area index were reduced by 17.0%, 1.6%, and 71.2%, compared with SWAT2009. Thus, the influences of various optimal management practices on the hydrology of agricultural watersheds can be effectively assessed using the modified model.

THE LOCAL PARAMETERS SENSITIVITY OF URBAN HYDROLOGICAL RESPONSE UNIT OF CONCEPTUAL HYDROLOGICAL MODEL METQ

The urbanised areas have a significant impact on hydrological processes of the catchment. The average annual urbanisation temp in EU is 0.6%. The existing version of conceptual hydrological model METQ is developed for natural hydrological response units such as forests, swamps and agricultural land. The growing urbanisation level force to add to the model urban hydrological response unit. This study aims to analyse local parameter sensitivity of urban hydrological response unit of conceptual hydrological model METQ. The local sensitivity was made using Monte-Carlo simulations. To evaluate local sensitivity Nash–Sutcliffe efficiency index (NSE), determination coefficient R2, percent bias (PBIAS), ratios the root mean square error to the standard deviation of measured data (RSR) in addition to the graphical method were used. The results show seven parameters to be calibrated the other 16 parameters have to stay as constant values for urban hydrological response unit.